CADRA Project - Program Evaluation Final Report 2015

Running Head: PROGRAM EVALUATION OF CADRA PROJECT 1

A Program Evaluation of the Community Advanced Data and Research Analysis Project at the

UNLV School of Environmental and Public Affairs

By

Michael Bernardo, Brandie Green, Amber Konold, and Kathryn Weavil

PUA 729

Submitted to the School of Environmental and Public Affairs

University of Nevada Las Vegas

In Partial Fulfillment for the Requirements for the Degree of Master of Public Administration

Faculty Approval:

_______________________________ Jaewon Lim, Ph.D.

Assistant Professor, School of Environmental and Public Affairs

_______________________________ Christopher Stream, Ph.D.

Director, School of Environmental and Public Affairs

PROGRAM EVALUATION OF CADRA PROJECT 2

Table of Contents

Executive Summary ........................................................................................................................ 3

Introduction ..................................................................................................................................... 4

Literature Review............................................................................................................................ 5

Purpose .......................................................................................................................................... 16

Methods......................................................................................................................................... 17

Evaluation Methodology ............................................................................................................... 18

Programs Studied .......................................................................................................................... 20

Recommendations ......................................................................................................................... 65

Conclusion .................................................................................................................................... 69

References ..................................................................................................................................... 72

Appendix A – Quantitative Survey Information ........................................................................... 73

Appendix B – Qualitative Interview Matrix ................................................................................197


Executive Summary

The Community Advanced Data and Research Analysis Project (CADRA) is project that

houses an interdisciplinary research team located at the University of Nevada, Las Vegas. The

vision of CADRA, as defined by its stakeholders, is to create positive community outcomes by

encouraging and engaging nonprofit organizations, as well as student and professional

researchers, to develop and evolve their data management practices. CADRA offers three

program options including Nonprofit Audits, Program Development and Grant Writing, and

Community Data Mining. The purpose of this program evaluation will be to evaluate the

Community Advanced Data and Research Analysis (CADRA) Project, with a specific

assessment of their access and obtainability to data in the Las Vegas community.

A convergent parallel mixed methods design was used, where qualitative and quantitative

data were collected concurrently, analyzed separately, and then merged. The quantitative data

was used to assess whether nonprofits, higher education institution faculty, or public sector

employees had ease and access in obtaining data. A survey was administered to any nonprofit

organization, higher-education faculty member, and public sector employee, from which the data

was collected. The qualitative semi-structured interviews were simultaneously conducted in

order to create a benchmark analysis of existing community data centers, in an effort to explore

existing program methodology and best practices.

The program evaluation yielded various significant findings that may help CADRA

improve its process and efficiency. Results of both the survey and benchmark analysis indicated

that the three primary focuses of CADRA should be on: social networking amongst the primary

stakeholder groups, implementation as the local data clearinghouse for Nevada, as well as,

establishment of a long-term funding resource. It is our hope that CADRA members take this

PROGRAM EVALUATION OF CADRA PROJECT 4 alpha analysis and use it to better shape this program throughout its maturation to fit the needs of

its users. We strongly recommend a beta analysis is conducted as well in the future, to better

address the evolving needs of this program.

Introduction

The Community Advanced Data and Research Analysis Project, or CADRA, is a newly

implemented program designed to oversee the development of the Clark County Data Hub, as

well as expand the existing MyResearcher data sets created by Applied Analysis. Currently the

lab is located in the School of Environmental and Public Affairs facility on the UNLV campus

and its maturation will be overseen by volunteer members of the CADRA team, who are also

partnering with the Nonprofit, Community, and Leadership Initiative (NCLI). The researchers

are tasked with completing a Community Needs Assessment for the United Way of Southern

Nevada (UWSN) every two years, as well as to collect data for Applied Analysis to incorporate

in their MyResearcher database. The program will also create grant-writing initiatives and

workshops for nonprofit organizations in the area, with the hopes of improving their ability to

secure funding. That, along with a focus on data management, is intended to optimize positive

outcomes for the community.

With the growing emphasis on data collection, the vision of CADRA is to create a nexus

of information that connects, faculty and student researchers, with community partners as well as

non-profit organizations to create positive outcomes for the Las Vegas community. However,

due to the program’s infancy, and ever evolving structural design, a community needs

assessment to gage awareness and expectations was vital to the success of this project. The aim

of this paper is to provide an overview of the growing data centric nature of community

PROGRAM EVALUATION OF CADRA PROJECT 5 nonprofit organizations, and demonstrate, through tangible data collection and interpretation,

whether or a not the need for CADRA and its services is perceived or actual.

Literature Review

Introduction In order to gain a better understanding of the role data plays in nonprofit organizations,

faculty research and the community, a review of all current literature was necessary. The

following literature review provides an overview of relevant academic publications that, in part,

addresses the program evaluation and data collection and utilization relationship.

Summary

In Using Social Network Analysis to Enhance Nonprofit Organizational Research

Capacity: A Case Study, by Johnson, Jennifer A., Julie A. Honnold, and F. Paul Stevens, the

authors speaks on the potential benefits of collaboration between a nonprofit agency and its

immediate neighbor organizations. A local funding agency in Virginia commissioned a study to

look at the ways in which social network analysis (SNA) can enhance the data resources

available to nonprofits for funding and grant requests. SNA is a visually descriptive

methodology used in social science that maps and measures connectivity. The centralized data is

then used as a metric. The article presents a case study of a network of 52 nonprofit

organizations to illustrate the how the social network analysis works and whether or not it is a

viable option for organizations to utilize. The ultimate goal is to produce tangible data collection

to increase the strength and merit of grant requests that are growing more specific with their

application criteria, and often times rely heavily on data outputs.

The research objectives for this study were “to explore the viability of SNA in terms of

research questions specific to nonprofit organizations and to conduct a pretest of a networking

PROGRAM EVALUATION OF CADRA PROJECT 6 initiative just launched by the funding agency intended to facilitate inter-organizational

connections among local nonprofits in a specified geographical region.” (Johnson et. al, 494).

Ultimately, the article concludes that, “Participation in networks enhances an NPO’s

innovation in services and acquisition of can improve organizational performance (Galaskiewicz

et al., 2006), can sustain and strength collaborative relationships (Guo & Acar, 2005), and

increases the organization’s chances of survival (Hager et al., 2004),” (Johnson et. al, 509). In

other words, there is increased access to funding and increased productivity and outputs when

organizations and nonprofits collaborate and share information.

An article which addresses that question of whether or not nonprofit organizations have a

need for better data management practices and if they are successfully utilizing current research

and incorporating findings is The Research Practices and Needs of Non-Profit Organizations in

an Urban Center by Randy Stoker. This study included 80 nonprofit organizations in Toledo,

Ohio each of whom completed a survey focused on their data needs and practices, (Stoeker,

101). The following table taken from the paper, illustrates the level of analysis at which the non-

profit organizations collect data.

The survey found that nonprofits collect data on a wide variety of topics, but do not use much of

PROGRAM EVALUATION OF CADRA PROJECT 7 the data that they collect, and do not collect useful data for other groups, particularly

neighborhood organizations. The contention is that without being efficient in not only the

collection, but the utilization of data, small to medium sized nonprofit organizations fall prey to

larger groups who can impose performance standards or measures.

Two central questions of the study were: How much research capacity do nonprofit

organizations have? How much do they need? One key finding of this study showed that

“Toledo nonprofits have piles and piles of data. Seventy-one of the 80 organizations store data

more than three years. On average, 61% of the data is saved in paper files, likely creating both

space and data recovery issues for many nonprofits,” (Stoeker, 104). The following table

illustrates the categories on which non-profit organizations collect and report data.

The article suggests four potential areas of improvement, which are, providing better

research methods training for nonprofit staff and volunteers, educating funders on the importance

PROGRAM EVALUATION OF CADRA PROJECT 8 of supporting nonprofit research and data management capacity, providing better stock databases

for nonprofits to easily use, and engaging higher education students and faculty in nonprofit

research data collection and management, (Stoeker, 113).

Community-Based Program Research: Context, Program Readiness, and Evaluation

Usefulness, by Jay A. Mancini, Lydia I. Marek, Richard A. W. Byrne, Angela J. Huebner, deals

with the relationship between individuals who manage and oversee operations of nonprofit

organizations with program evaluators. The overarching theme is if you improve the

evaluator/organization partnership and make it more harmonious, the overall outcome of the

organization improves. This can be done through a series of quality control questions that both

parties can utilize to make sure that the communication is clear and that the projected outcomes

remain the same. One aspect of this paper is identifying whether or not a program is “ready” for

evaluation. There are three key questions that are posed, what are the contextual influences on

program development and evaluation research efforts? Is the program ready for evaluation? And

does the evaluation research “work” for the program?” (Mancini et. al, 11).

The article further outlines detailed questions for each subsection that should be asked

about and discussed throughout the evaluation journey, (Mancini et. al, 12). Including, is what

we know about the community informed by data collected by some agency or organization, or is

it based on anecdotes? How do we describe the community? Who are the programs serving? And

Over the past several years how has this community changed, if at all? Over the next several

years are particular changes expected? The article then poses the final questions that should be

asked by evaluators which are; Is the program fully active and, if so, for how long? Are desired

program results specific and clear enough so that they can be assessed? Are program activities

consistent with the program purpose and its desired results? What is the program intervention?

PROGRAM EVALUATION OF CADRA PROJECT 9 Which dimensions of what occurs in the program are related to particular changes that are

anticipated? Is the understanding of the intervention clear and does it seem that results from the

intervention can be observed? And can the program be evaluated and its merit supported or not

supported?

The main focus of Challenging Institutional Barriers to Community-Based Research, by

Randy Stoeker, is recognizing and developing methods to break through various barriers of

community-based research. Specifically, the article targets a case involving community/campus

collaboration and utilizing students as primary researchers. The final conclusion of the research

is, “The main way to equalize partnership power between higher education institutions and

communities is to equalize the information power of the two. That does not mean that power is

not fundamentally material, rooted in resource inequalities. But the primary form of campus–

community partnerships revolves around information processes, and provides the first open door

to equality and justice.” (Stoeker, 54). In other words, there has to be a positive flow of

information for collaboration success. The following chart illustrates the power flow and

organization of community/college partnerships with their defined roles.


Assessing the Effectiveness of Capacity-Building Initiatives: Seven Issues for the Field by

Kennard T. Wing, outlines two of the most recent trends in philanthropy and nonprofit

organizations which include an increased emphasis on “measurable outcomes and greater

investment in capacity building or organizational effectiveness,” (Stoeker, 154). This leads the

authors to try and figure out how exactly can you measure capacity building? The answer lies in

seven questions that must be addressed upon assessment for the future of measuring

organizational capacity building. These seven questions according to the article are, How can an

abstract concept be concretely measured? The author suggests with properly and specifically

defined terms and matrices. How can we measure performance improvement when we cannot

measure performance? The article advises to measure a particular outcome and whether it is

improving or declining across the organization. Against whose goals should be measure

improvement? Stoeker suggests the goals which the participants set for themselves because

realistically they are much more likely to follow through on them. What can be done about

unrealistic timetables for both capacity building and its relationships to program evaluators?

Stoeker states that the organization must have realistic expectations for the long run in order to

not compromise the integrity of the institution. Short-term goals must not be met at the

expensive of long-term gain. How can we document how soft people relate to hard systems?

Stoeker claims “It is better to do a poor job evaluating a good intervention than a great job

evaluating a pathetic one,” (Stoeker, 155). Should be measure participants’ behavior change or

clients’ internal learning? Stoeker suggest that “The evaluator seeks measurable external

changes. The consultant, on the other hand, particularly when working with senior executives,

often tends to focus on the clients’ internal learning. The consultant believes that, unless the

client internalizes the learning, any external change will be temporary and, in the case of

PROGRAM EVALUATION OF CADRA PROJECT 11 behavior, possibly phony. Thus, external change without an “Aha!” is empty. The evaluator

believes that insight alone has no cash value: Actions speak louder than words,” (Stoeker, 156).

In other words, change is difficult and if the participants don’t internalize the changes and make

them into habits, all previous instruction will be wasted as behavioral patterns will resort back to

the status quo. And finally, How can researchers design a study when consultants keep

changing what they are working on? The article states that, “Foundation and nonprofit

executives need to be aware that there are real limits to evaluation. It would be foolish to limit

interventions to what can be effectively evaluated. Instead, we have to keep those limitations in

mind when Capacity-Building Initiatives using evaluation results concerning a capacity-building

intervention that is operating, in part, beyond those limits,” (Stoeker, 157).

In Nonprofits, Funders, and Evaluation Accountability in Action by Joanne G. Carmen,

the article addresses what grant funders are seeking when they ask for performance and

evaluation data, and whether or not those nonprofit organizations are able to comply with that

request. The article ran tests on a series of six hypotheses and found that contrary to popular

opinion, there is a widespread move towards evaluation and performance measurement data only

in organizations that claim Federal or United Way funding, (Carmen, 3). They did this by

surveying nonprofit organizations including one on one interview with 31 employees and 10

funding sources in New York State. Those seeking grants at the state and local level were not, in

general, required to submit outcome data. The following six hypotheses that were tested were as

follows, (Carmen, 3):

Hypothesis 1: Nonprofits that receive a higher percentage of funding from federal government

sources are more likely to comply with external monitoring requirements.


Hypothesis 2: Nonprofits that receive a higher percentage of funding from state and local

government sources are more likely to comply with external monitoring requirements.

Hypothesis 3: Nonprofits that receive a higher percentage of funding from the United Way are

more likely to engage in descriptive reporting activities.

Hypothesis 4: Nonprofits that receive a higher percentage of funding from foundations are more

likely to engage in descriptive reporting activities.

Hypothesis 5: Nonprofits that receive a higher percentage of funding from the United Way are

more likely to engage in evaluation and performance measurement activities.

Hypothesis 6: Nonprofits that receive a higher percentage of funding from the federal

government are more likely to engage in evaluation and performance measurement activities.

The results of the testing showed that for Federal Funding, “The regression models

indicated that federal funding was a significant predictor for the extent to which nonprofit

organizations comply with external monitoring requirements (β=.370) and conducting evaluation

and performance measurement (β=.219). These findings were consistent with the hypotheses

(Hypotheses 1 and 6). For state and local funding, “The regression models indicated that state

and local government funding was a significant predictor of external monitoring (β=. 281) as

expected (Hypothesis 2),” (Carmen, 8).

Financing and Evaluating Nonprofits: Mapping the Knowledge Base of Nonprofit

Management in the Human Services by Sara L. Schwartz and Michael J. Austin, focuses on the

knowledge base that nonprofit organizations rely on in terms of their ability to map their

financial base. Because of varied political and economic climates, these organization have had

to diversify funding sources and also provide detailed accounts of budgeting due to increased

emphasis on accountability. This paper is inherently a literature review in it of itself that

PROGRAM EVALUATION OF CADRA PROJECT 13 browses all of the current literature where five apparent themes were discovered. The different

types of “themes” that the researchers isolated were, Financing and Evaluating Nonprofits,

which includes articles “considering the financial management of nonprofits, sources of revenue,

social enterprise, accountability requirements, program evaluation, and management information

systems,” (Schwartz et. al, 6). Leading and Managing Nonprofits includes articles addressing

“nonprofit history, organizational theory, leadership, management, nonprofit governance,

communications and marketing, and managing external relations that include inter-organizational

relationships as well as relations with external environments such as the law, public policy,

professional associations, and the community at large,” (Schwartz et. al, 7). Managing Human

Resources which include a employee’s happiness, education and trading programs, employee

management, volunteer efforts and promoting diversity, (Schwartz et. al, 7). Managing Different

Types of Nonprofits to which articles that research and classify nonprofit organization are

included, as well as articles that explore “domestic nonprofit service sectors, membership

associations, community development nonprofits and citizen political nonprofits,” (Schwartz et.

al, 7). And the final theme, Managing NGOs Worldwide, whose papers includes topics such as

the management of non-governmental organizations internationally, the management of human

resources as well as different types of non-governmental organizations, (Schwartz et. al, 7).


Because United Way’s approach to program outcome measurement is one of the most

widely used systems throughout the nonprofit sector, Measuring Outcomes of United Way–

Funded Programs: Expectations and Reality by Michael Hendricks, Margaret C. Plantz,

Kathleen J. Pritchard, wanted to examine whether or not the expectations of its effectiveness

measure up to the reality. Some of the distinguishing characteristics of the United Way approach

include, a focus on outcomes, a quantitative measure of outcomes. Consistent, systematic

measurement. The main objective being program improvement, working from logical model.

Also United Way’s approach includes programs that are required to identify their own outcomes,

a long time horizon for implementation, and analysis done by in in house staff. The following

table illustrates the base information for those organizations utilizing the United Way approach,

as well as the Bivariate Correlation to funding.


There was a wide array of experiences with United Way, including both negative and

positive. The article secedes there are certain factors that are out of the organizations control,

which can have an impact on the success of the United Way’s methodology. This includes the

commitment of agency leadership and the inherent difficulty of the measured outcomes,

(Hendricks et. al, 27).

These articles demonstration a trend towards the centralization and utilization of data and

the effect that has on an organization’s ability to apply for and be awarded federal funding.

There is a real correlation between how efficient an organization is with managing its data and

the ability of that nonprofit to receive funding as well as deliver on expected outcomes,

(Hendricks et. al, 35).

Findings Overall, the studies whose findings were particularly relevant to the program evaluation

of CADRA were Assessing the Effectiveness of Capacity-Building Initiatives: Seven Issues for

PROGRAM EVALUATION OF CADRA PROJECT 16 the Field by Kennard T. Wing, and Nonprofits, Funders, and Evaluation Accountability in Action

by Joanne G. Carmen. The first article deals specifically with the current demand for data

inclusion in grant funding requirements, and outlines seven questions that act as guidelines for

organizations to handle capacity building and data management. The second article shows an

actual statistical correlation with expected data outcomes and federal or state funding. In both of

these cases, the evidence is clear that understanding and growing data management and

collection is a vital component of expanding organizations, demonstrating a real need for

projects such as CADRA.

Purpose

Statement of Problem

In light of the research reviewed on community based research centers, institutional

barriers to community research, and the research practices of nonprofit organizations, there is no

current research conducted to evaluate the need for a community driven data center in the Las

Vegas community.

The purpose of this program evaluation will be to evaluate the Community Advanced

Data and Research Analysis (CADRA) Project, with a specific assessment of their access and

obtainability to data in the Las Vegas community.

A convergent parallel mixed methods design was used, and is a type of design in which

qualitative and quantitative data were collected concurrently, analyzed separately, and then

merged. In this study, quantitative data was used to assess whether nonprofits, higher education

institution faculty, or public sector employees had ease and access in obtaining data.

Furthermore, did they perceive a need for assistance in analysis and do they desire to contribute

to further community collaboration. The quantitative data was collected via written survey

PROGRAM EVALUATION OF CADRA PROJECT 17 questionnaires from any nonprofit organization, any higher-education faculty member, and any

public sector employee. The qualitative semi-structured interviews were simultaneously

conducted by performing a benchmark analysis of existing community data centers in an effort to

explore existing program methodology and best practices.

The reason for collecting both quantitative and qualitative data is to achieve triangulation

and a greater data context. As Creswell and Clark (2011) state, triangulation refers to a

traditional view where quantitative and qualitative research is combined, in order to be mutually

corroborated for a greater validity (p. 62). By collecting quantitative data that evaluates

constituents’ perceptions of access and obtainability, and subsequently collecting qualitative data

that provides input regarding feasibility, research can more effectively add context to the data

when interpreted concurrently.

Research Questions

1. Does CADRA provide increased access and attainability to data driven decision-making

within the Las Vegas community?

2. Does the increased access appropriately target the three stakeholder groups?

Methods

Participants

Participants for the quantitative portion of the program evaluation were selected

randomly with no limitation to survey response. Three target population groups were identified

upon the foundation of the CADRA evaluation project, and were as follows: higher education

graduate students and faculty, nonprofit organizations, and public sector employees.

A standardized email was sent to all of the various participant groups via methods as

outlined below detailing the survey information and soliciting their participation. To be

PROGRAM EVALUATION OF CADRA PROJECT 18 considered for inclusion into the study, participants were to have been in one of the above target

population groups. There were no exclusion factors for this survey research.

The benchmark analysis had seven pre-determined community data collection programs

identified that were similar in scope to CADRA. The programs were selected in an effort to

compile a comprehensive analysis of best practices and current trends. The Alpha Group, with

help from Capstone Director Dr. Jaewon Lim, identified the following well-established data labs

in which to contact:

1. University of Washington DataLab,

2. UC Berkeley D-Lab,

3. Princeton University Data & Statistical Services (DSS) Lab,

4. University of Tennessee Census State Data Center,

5. Ball State University CBER Data Center,

6. Penn State Social Capital Index,

7. Minnesota Population Center

Evaluation Methodology

In order to identify the need for a centralized data repository to determine if CADRA will

be able to provide increased access and attainability to data driven decision making within the

Las Vegas community, a mixed methods research approach was used. The evaluation team

chose to conduct a (qualitative) benchmark study to identify data collection programs similar in

scope to CADRA with the desire to identify best practices and make recommendations for

CADRA’s future direction. The team also elected to create and distribute a (quantitative) survey

in order to identify particular data needs among the study’s three target populations (institutions

of higher learning, nonprofit organizations, and public agencies).

PROGRAM EVALUATION OF CADRA PROJECT 19 Benchmark Analysis (Qualitative)

The purpose of the benchmark analysis was to query well-known and established

programs via qualitative interviews to see which methods and best practices they employ which

may help CADRA become even more successful through implementation.

An effort began in April of 2015 to reach out and establish an internal point of contact

with each data lab to help facilitate an interview with the program director. This effort began by

reaching out to each program’s generic mailbox on two separate occasions; only 3 of the 7

(42.8%), were responsive. These three labs include Princeton University Data & Statistical

Services (DSS) Lab, the University of Tennessee Census State Data Center, and the University

of Washington DataLab. The Alpha Group was able to go on and interview each of these labs,

with the exception of the University of Washington DataLab which was initially responsive and

then removed from the list after subsequent attempts to coordinate an interview were ignored. An

example of the email dialogue can be found in Appendix X – Benchmark Information.

In an attempt to prompt a response from the four (4) unresponsive data labs, their

websites were reviewed, and the introduction email was written to the program director with the

Data Lab in the CC field. This approach was greeted with a response from the UC Berkeley D-

Lab and the University of Minnesota Population Center (MPC), which each later set aside the

time for an interview.

Despite numerous attempts to contact both Ball State University’s CBER Data Center

and Penn State’s Social Capital Index, the programs were unresponsive and therefore removed

from the list.

The figure below depicts the program, contact, if they were responsive/unresponsive, and

if the Alpha Group was able to interview them to be part of this benchmark study.


In total, four (4) data labs chose to participate in this study and were interviewed. The

Alpha Group extends our sincerest Thanks to Dr. Jon Stiles, Dr. Catherine Fitch, Ms. Melissa

Stefanini, and Mr. Bobray Bordelon for taking the time to help make this study possible.

The following sections will provide additional information into the programs chosen for

insertion into this study, descriptive analysis of the questions asked including commonalities,

disparities, and findings, and recommendations and lessons learned. This information may be

helpful to future program evaluators as CADRA evolves from its infancy to an established

program.

Programs Studied

The aforementioned data labs were all selected for their relevancy to CADRA’s mission,

as well as their prestige within the research community. In addition to the qualitative interviews,

Alpha Group reviewed each lab’s website for relevant information to include in this baseline

study to make it as complete as possible. The following is a summary of the data collected:

The University of Washington (UW) DataLab

According to their website, the University of Washington’s DataLab is a:


“…nexus for research on Data Science and Analytics at the UW iSchool.

We study large-scale, heterogeneous human data in an effort to

understand why individuals, consumers, and societies behave the way

they do. Our goal is to use data for the social good, in an ethical manner

that can inform policy and impact lives for the better. As the focal point

for industry partnerships related to “big data” and business analytics,

the DataLab also provides infrastructure and support for student training

and engagement in projects that involve the analysis of large datasets.”1

This program was thought to very closely coincide with CADRA’s goal of providing

descriptive analysis and trends of socioeconomic data to the community to enhance data literacy.

Unfortunately, the UW DataLab was not available for an interview, however, in review of their

website, the UW DataLab is a multi-disciplinary team with a common purpose; data science for

social good. Their research uses “Big Data” to better understand the behavior of individuals and

society. Some core areas in which the UW DataLab is currently focused includes: societal and

economic problems in developing countries, crisis informatics, and economic and social

processes that drive scholarly communication. In societal and economic problems in developing

countries, UW students have the opportunity to spend time in the field to better understand the

cultures that supply the data in which they are studying. For crisis informatics, UW DataLab is

analyzing how information spreads over social media during disasters, including what indicators

people pay attention to, and the credibility of the information available to develop better disaster

response mechanisms. The DataLab is also trying to address the thousands of scholarly

1UW Information School, Retrieved July 31, 2015, from https://datalab.ischool.uw.edu/about

PROGRAM EVALUATION OF CADRA PROJECT 22 publications being created every day and the major modern challenge of information overload.

The academically diverse students play an essential role in research from planning through

publication, while the faculty members share their research and work with collaborators at other

Universities, Companies, and Governments all over the world.

The University of California (UC) Berkeley D-Lab

According to their website, the UC Berkeley D-lab:

“…helps Berkeley faculty, staff, and graduate students move forward

with world-class research in data intensive social science. We think of

data as an expansive category, one that is constantly changing as the

research frontier moves. We offer a venue for methodological exchange

from all corners of campus and across its bounds.

D-Lab provides cross-disciplinary resources for in-depth consulting and

advising, access to staff support, and training and provisioning for

software and other infrastructure needs. Networking with other Berkeley

centers and facilities and with our departments and schools, we offer our

services to researchers across the disciplines and underwrite the breadth

of excellence of Berkeley’s graduate programs and faculty research. D-

Lab builds networks through which Berkeley researchers can connect

with users of social science data in the off-campus world.”2

2University of California D-Lab, Retrieved July 31, 2015, from http://dlab.berkeley.edu/about-d-lab


The program at UC Berkeley provides services, support, and a location for research

design and experimentation in social science data. UC Berkeley’s D-Lab was not available for

interview, but upon detailed review of their website, Alpha Group was able to find relevant

information for inclusion to this study. D-Lab targets its services at UC Berkeley social science

researchers, which consist of, graduate students, staff, and faculty, and their online resources are

available to the public. Initial funding investments in D-Lab came from the Vice Chancellor for

Research, the Provost, the Dean of Social Science and the Deans of social science faculties

across Berkeley. D-Lab reports to the Vice Chancellor for Research and is overseen by a

governing board. There are several workshops available for graduate students who need data for

the writing of their thesis or dissertation, and D-Lab can provide consulting services for the

writing of grant-funded research on a paid or recharge basis.

Princeton University Data & Statistical Services (DSS) Lab

Princeton University’s DSS Lab has been around for over 50 years and is housed within

the Firestone Library. DSS provides statistical and software assistance in quantitative analysis of

electronic data as part of independent research projects, such as junior papers, senior theses, term

papers, dissertations, and scholarly articles. The lab is available to all currently enrolled or

employed members of Princeton University and focuses on social science data, statistics,

science, and humanities. Since the lab is housed in the library, there is support for researchers

with locating appropriate data, preparing restricted data plans, determining methodologies, and

getting ready to use statistical packages. DSS has informal partnerships with GIS (another part of

the library system), Library's Systems Department (they manage and maintain the many servers),

Office of Population Research Data Archive (largely informational in terms of acquisitions), and

the Center for Health & Well Being Data Archive (non-restricted data). The program is funded

PROGRAM EVALUATION OF CADRA PROJECT 24 by a regular line in the library budget (staff, software, collections, etc…). The lab does not assist

with grant writing, and because Princeton is a private university, its resources are restricted to its

own researchers, therefore no work is done to support the nonprofit community. DSS is staffed

by three full-time librarians; two full-time statistical consultants; 1/2 FTE support staff member;

and 40 hours of Graduate Assistant support per week. The lab does not normally advertise or

market as they are very heavily used and part of numerous classes, so campus awareness is high.

University of Tennessee Census State Data Center

According to their website, the University of Tennessee Census State Data Center (SDC)

is a:

“…State/Census Bureau cooperative program with a mission of

providing efficient access to US Census data and products, providing

training and technical assistance to data users, and providing feedback

to the Census Bureau on data usability, as well as state and local

government data needs and operational issues. The State Data Center

disseminates Census and other data to the public through a network of

over 1,800 state and local agencies, libraries, universities, chambers of

commerce, and others. The State Data Centers are the official source of

demographic, economic, and social statistics, and redistricting data

produced by the Census Bureau.”3

The SDC program started in 1978 and the Center for Business and Economic Research

(CBER) at UT, Knoxville, has been the lead agency since 1980. Ms. Melissa Stefanini described

3University of Tennessee Census State Data Center, Retrieved July 31, 2015, from http://tndata.utk.edu/

PROGRAM EVALUATION OF CADRA PROJECT 25 their main audience as data users of all kinds. The services provided are to the Census, to

affiliates, and to data users across the state. The SDC provides:

• Technical assistance on Census data analysis and mapping,

• Efficient access to Census Bureau data and data products, including timely data

summaries, research, and statistical reports,

• User-training workshops and conferences on all aspects of demographic data to a

broad range of users,

• A State Data Center website (http://tndata.utk.edu),

• An E-newsletter

• Service as the primary contact for data users who require demographic or economic

data for Tennessee, its counties, cities, tracts, blocks and zip code areas.

• Service as the official Federal-State Population Estimates Cooperative representative

to the Census Bureau’s Population Estimates Division to include data gathering,

estimates review and dissemination.

The SDC is a partnership between the state of Tennessee (TN) and the US Census

Bureau. It is funded through the TN Department of Finance & Administration. Methods of

raising awareness include annual data users’ conference as well as other workshops across the

state to help get data users be more efficient and more aware of what the Census is working on

and what data is available. They are currently in a large social media push and have a Twitter,

Facebook, and LinkedIn account, SDC website, E-newsletter, and large distribution lists for

email blasts. They also utilize press releases when something exciting is released by the Census

with a description of why it is important and what happened in the state.

PROGRAM EVALUATION OF CADRA PROJECT 26 Ball State University Center for Business and Economic (CBER) Data Center

Ball State University’s CBER Data Center was unresponsive, however, according to their

website, the CBER Data Center’s mission is to: “…offer simple, visual, easily accessible

economic web tools for economic developers, community leaders, grant writers, policymakers,

and the general public.”4

The CBER Data Center conducts relevant and timely public policy research on a wide

range of economic issues affecting the state and nation. It is an economic policy and forecasting

research center which covers topics including public finance, regional economics,

manufacturing, transportation, and energy sector studies.

Penn State Social Capital Index

The Penn State Social Capital Index, also known as the Northeast Regional Center for

Rural Development (NERCRD), was also unresponsive. Their website however had a plethora of

data on the Center’s mission, vision, organization, goals, and strategies, which the team felt was

sufficient for inclusion into this study. According to their website, the NERCRD is:

“…dedicated to providing research-based information that helps create

regional prosperity through entrepreneurial and cluster-based

innovation, while assuring balanced uses of natural resources in livable

communities in the northeastern United States.”5

The Northeast Center is one of four Regional Rural Development Centers established in

the early 1970s at Cornell University, and later moved to Penn State in 1985. Although

NERCRD’s mission focuses on enhancing the capacity of Land Grant Universities to foster 4Ball State University Center for Business and Economic Data Center, Retrieved July 31, 2015, from http://cms.bsu.edu/academics/centersandinstitutes/bbr/datacenter 5 Penn State College of Agricultural Sciences, Retrieved July 31, 2015, from http://aese.psu.edu/nercrd/about

PROGRAM EVALUATION OF CADRA PROJECT 27 regional prosperity and rural development, and is dissimilar to CADRA’s, it was chosen because

of its success and prestige in the data community. The Center’s belief is that small towns and

rural places are becoming increasingly more complex and multi-dimensional in the context of

today’s global society. NERCRD’s major core funding comes from the National Institute of

Food and Agriculture (NIFA) and the region's land-grant universities. Additionally, other federal

and state agencies, private foundations, and public interests contribute funding in support of

various special programs on case-by-case basis. NERCRD is governed by a Board of Directors

and a Regional Technical Advisory Committee which have set several goals for the program:

• Goal 1: Improving Economic Competitiveness, Diversity and Adaptability of Small

and/or Rural Communities

• Goal 2: Facilitating Development of Policies that Enhance the Well-being of Rural

People and Small Towns

• Goal 3: Increasing Community Capacity to Deal with Change

• Goal 4: Increasing Social viability through Enhancing the Self-reliance of Families

and Communities

• Goal 5: Linking Natural Resource Industries, Including Agriculture, with Community

and Environmental Resources

The Center raises awareness through: assistance of Northeast states in responding to

development needs; workshop facilitation and conference participation on current rural

developmental issues, grant support activities, network coordination among rural development

partners, and production and distribution of research and educational materials through

newsletters, annual reports, its web page, and other publications. Its staff consists of a program

director, four administrative staffers, two postdoctoral scholars, and five graduate assistants.

PROGRAM EVALUATION OF CADRA PROJECT 28 Minnesota Population Center (MPC)

The Minnesota Population Center (MPC) was established in March 2000 by founding

collaborators from four colleges. The MPC focuses on Social Sciences and Health Data with an

internal audience of the University community (i.e. students and faculty) in mind. Infrastructure

projects are federally funded and have an advisory board, with additional University funding

available from the Office of the VP for Research for University funded staff. The major external

stakeholder for the MPC is the US Census Bureau's National Statistical Office. The MPC

provides support to through seven shared cores and all MPC members are eligible to use the

services of these cores. Cores also offer fee-based services for non-members. According to the

MPC website, each core’s function is as follows:

“The Administrative Core maximizes the productivity of MPC

researchers by reducing administrative burdens and handling day-to-day

operations of the Center.

The Information Technology Core maintains computing hardware and

software for data analysis and provides software development services

for data creation, management and dissemination.

The Data Access Core manages and disseminates our own data

collections and provides MPC researchers with access to demographic

data from other centers and archives.

The Data Services Core provides data processing, coding, and cleaning

services for MPC-based research projects, and provides a variety of

demographic data services to external clients worldwide.


The Spatial Analysis Core provides research support for spatial data

creation and analysis for MPC-based research projects and provides GIS

training for MPC members.

The Dissemination and Outreach Core provides user support for MPC-

produced data products, maximizing the accessibility of MPC data not

only for academic researchers but also for students, policy makers,

journalists and the general public.

The Data Integration Core specializes in harmonization processes and

metadata creation, so that variables from multiple datasets may be

readily subject to comparisons across time and space.”6

The Center is staffed by six full-time University funded employees, and numerous

research staff working on infrastructure awards and funded by grants. At the time of the

interview with Dr. Fitch, there were 168 total research staffers in the MPC of which 75 are non-

students (i.e. research staff, software developers, etc...). To raise awareness, Academic

researchers exhibit at special events for professional societies, they sponsor University hosted

publicized events and data workshops, and most importantly, scholarly articles get cited using

MPC data. The MPC offers program development grant writing support for affiliated research,

and assisted with the writing of nearly 30 grants in 2014. At this time however, they do not

currently work with the local nonprofit community.

6University of Minnesota, Retrieved July 31, 2015, from https://www.pop.umn.edu/about

PROGRAM EVALUATION OF CADRA PROJECT 30 Survey (Quantitative)

The evaluation team created an online survey using Qualtrics software. Survey content

and structure was developed by Alpha Group in conjunction with input from CADRA program

staff members. The information provided by the CADRA program helped Alpha Group develop

the survey questions which were then submitted to CADRA, specifically John Wagner and Lola

Brooks, for approval. Alpha Group received suggested changes to the survey questions and

formatting, and the survey was edited accordingly. Upon completion of all components of the

survey, it was distributed to the three target populations and the survey collection period began.

A link to the survey was disseminated to UNLV research faculty, nonprofit community

agencies identified by UNLV’s Nonprofit, Community, and Leadership Initiative (NCLI), and

government agencies via email. Group members also created an introductory letter briefly

describing the scope of the CADRA program along with survey instructions to explain the

purpose of the survey and the need for respondents. The evaluation group collected survey

responses from June 22, 2015 through July 22, 2015. Alpha Group received 232 total survey

responses during the collection period.

The survey consisted of 27 questions, 22 core questions and 5 demographic questions.

The survey questions were designed to identify to which of the three target groups the responded

belonged, specific needs reported regarding data collection and analysis, satisfaction with

existing data collection and research tools, frequency of grant writing and desire for services

offered through the CADRA program.

Demographic questions collected information on the respondents’ age, race, sex, level of

education, and employment status. The respondents’ answer regarding which type of agency

they worked for determined the following sequence of questions with which they would be

PROGRAM EVALUATION OF CADRA PROJECT 31 presented. For example, if a respondent reported being employed by a nonprofit institution, they

would see a subgroup of questions geared specifically toward the data collection and analysis

needs of nonprofit agencies.

The survey was promoted through an email announcement containing an electronic link

to the survey along with instructions regarding the time commitment required, the purpose of the

survey, and all potential respondents were provided with a contact from the evaluation team

during the survey period. The contact (Amber Konold) received several emails containing

feedback from respondents, most noting that the survey did not provide a comprehensive list of

terminal degrees which made choosing a level of education difficult for respondents.

Survey responses were collected through Qualtrics, which resulted in viable data for

analysis. The total number of respondents was 232, subgroup totals were: 153 (66%) from

higher education institutions, 44 (19%) from nonprofit organizations other than higher education

institutions, 23 (10%) from government agencies, 10 (4%) employed in the private sector, 1 (0%)

retired, and 1 (0%) reported “other please specify” and noted that they were employed by the

school district.

Findings

Qualitative Findings

For this study Alpha Group developed eleven (11) questions to ask during the qualitative

interviews that would provide the most benefit in the evaluation of CADRA. Some of these

questions such as Question #6 – Do you work with the nonprofit community? Proved to result in

a common theme among the four programs interviewed; No, they do not. Below are each of the

questions asked with a narrative:

1. How long has the program been in operation?


Each of the programs is at least 15 years old with these exception of the UC Berkeley D-

Lab which opened its doors in 2013. This was expected as the team chose these programs

for being well established and prestigious. That doesn’t happen overnight as it takes time

to establish a reputation of data integrity and is usually a result of years of data being

cited. Princeton’s DSS Lab was the oldest at over 50 years old.

2. What is your focus area? Who is your main audience?

Each of the programs had different foci and although some may cross paths, there didn’t

seem to be much, if any, duplication of effort. UC Berkeley’s D-lab focuses on training,

consulting, community building, computing infrastructure, and data. It also transmits this

information to the Census Bureau. Princeton is internally focused on social science data

and statistics. The University of Tennessee’s State Data Center is focused on census data

and its reporting. Penn State’s NERCRD is focused on rural development and educating

individuals in rural areas to create a shared vision for future sustainable communities; and

the Minnesota Population Center is focused on social sciences, health, and data. As with

UC Berkeley and the University of Tennessee, the MPC is also partnered with the Census

Bureau.

3. Who are your internal and external stakeholders?

Most of the programs had a common answer and identified internal stakeholders as

research faculty, students, and staff. The external stakeholders vary greatly based upon

grant-funded research, and the current external stakeholders during the time of the

interviews may not be the same stakeholders years down the road. As mentioned above,

three of the programs cited the US Census Bureau.

PROGRAM EVALUATION OF CADRA PROJECT 33 4. How is the program funded?

The funding structure of each lab is in some way supplemented by long-term guaranteed

funding such as by the University they belong to, or as a result of a strategic partnership

with the federal government. The UC Berkeley D-Lab receives support from the Deans of

the professional schools and academic departments. Princeton’s DSS Lab is part of the

regular library operations budget. The University of Tennessee is funded by the TN

Department of Finance & Administration. Penn State’s NERCRD’s major core funding

comes from the National Institute of Food and Agriculture (NIFA) and the region's land-

grant universities; and MPC’s projects are mostly funded by federal grants, however,

some University of Minnesota funding comes from the Office of the Vice President for

Research.

5. Do you provide assistance in the writing of grants?

This question received a mixed response. UC Berkeley’s D-Lab provides training and

workshops on the writing of grants towards specific funding sources such as the National

Institutes of Health (NIH) and the National Science Foundation (NSF), however, they do

not actually write or apply for the grants. Princeton and the University of Tennessee do

not offer any assistance in grant writing. Penn State’s NERCRD advertises that it does,

however, they were unavailable for interview for further information as to how many per

year, and if that is a core mission area. The MPC is heavily involved with the assistance

of writing program development grants for affiliated research and claimed to have written

over thirty (30) in 2014, however, they could not answer as to how many were actually

funded to quantify a success percentage.

PROGRAM EVALUATION OF CADRA PROJECT 34 6. Do you work with the nonprofit community?

Not one of the Data Labs claimed to have worked with the nonprofit community during

the interviews, nor is it advertised as a core business process on any of their websites.

7. What is your program structure? How many staffers? Are they Salaried? Volunteers?

Graduate Assistants?

Each Data Lab varies in its size, with the smallest being Princeton’s DSS Lab with three

full time librarians, two full time statistical consultants, 1/2 full time support staff

member, and a cumulative 40 hours of work put in by graduate assistants each week. The

MPC has the largest structure with 168 research staff currently employed by grants, and

6-7 full time university funded employees. Taken from their website, Penn State’s

NERCRD’s staff consists of one program director, four administrative staffers, two

postdoctoral scholars, and five graduate assistants. The UC Berkeley D-Lab’s staff

consists of a faculty director (part-time), executive director (full-time), academic

coordinator (part-time), data archivist (part-time), IT specialist (full-time), and applied

software/tool developers (2 x part-time). They also employ graduate student and staff as

consultants (approximately 15-20 per semester, 3-5 hours/week), workshop presenters

(15-20 per semester), and GSR operational staff (usually 5-7 half-time). All are paid.

8. What methods are used to raise awareness of your program?

Since the major internal audience of many of these labs are the students, faculty, and

staff, the University is commonly used for communication and raising awareness such as

via email blasts, newsletters, and bulletins. Several labs said to have held workshops and

consultations for the students and faculty to become more literate with their programs.

There was also a common trend of updating their website and social media sites to try


and reach the next generation of researchers, and participation in professional

conferences.

9. How would you assess the data literacy in your community?

The response to data literacy varied depending on the university and the focus of the

program. Some interpreted the community as the University and students, others

interpreted it as the surrounding geographic area. In a future study, I would refine this

question to be less ambiguous. There wasn’t a right or wrong answer, however, the

response is going to be subjective based upon the opinions of the individuals interviewed.

10. What advice or lessons learned would you give to a University beginning implementation of

a Community Assessment and Data Analysis lab?

Discussed in the Lessons Learned section below.

11. How do you measure data needs and type of data needed?

The data labs interviewed detailed several methods to measure the data types and needs.

In some cases it could be as easy as seeing what grants were received and querying the

professional research staff, while others log requests for data that come in through their

systems. The students and faculty can be worked with directly as subject matter experts

of specific fields to learn what is out there, what is popular, and what is possible.

Quantitative Findings

The following section includes graphs and visual representations from the quantitative

data derived from the survey results from the three main target groups beginning with the

demographic questions for each group, followed by results from the core questions for each.

PROGRAM EVALUATION OF CADRA PROJECT 36 Demographics

1. Higher Education Institution

Gender Answered: 153 Skipped: 0

The majority of survey respondents from higher education institutions were male

(50.33%, 77), with 74 females (48.37%) responding to the survey and two individuals (1.31%)

who preferred not to answer.


What is your age? Answered: 153 Skipped: 0

The majority of respondents from higher education institutions (27.63%, 42) indicated

that they were between 40-49 years of age. The second largest percentage of respondents

(23.68%, 36) reported age between 50-59 years. The smallest recorded age group was 21-29

years (3.29%), and there were no respondents under 20 years of age.

What is the highest level of education you have completed?

Answered: 152 Skipped: 1

PROGRAM EVALUATION OF CADRA PROJECT 38 The majority of respondents (82.89%, 126) indicated they had completed a doctoral degree,

while the remaining 17.11%, (26 respondents), indicated that they had completed an

undergraduate degree or higher.

What is your race? Answered: 153 Skipped: 0

The majority of respondents (83.55%, 127) indicated that they identified as White (non-

Hispanic), respondents who identified as Asian made up the second largest group (6.58%, 10).

Those who responded “other race (please specify)” provided the following specifications:

• West Indian-Jamaican • Mixed • American Indian • Adopted with Native American mother, also adopted.


2. Nonprofit Organizations


The majority of survey respondents from nonprofit organizations were female (72.09%),

with 31 females responding to the survey and 12 males responding to the survey.

What is your age?


The majority of respondents from nonprofit organizations were split down the middle

between ages 40-49 (29.55%, 13) and ages 50-59 (29.55%, 13). The second largest percentage

PROGRAM EVALUATION OF CADRA PROJECT 40 of respondents (15.91%, 7) indicated that they were over 60 years of age. The smallest recorded

age group was 21-29 years (11.36%, 5), and there were no respondents under 20 years of age.



The majority of respondents (45.45%, 20) indicated they had completed a master’s

degree, while the second largest group (27.27%, 12) reported having a bachelor’s degree. In

total, 97.73% indicated having attended college, with the remaining 2.27%, (1), indicating that

they were high school graduates with no college.



The majority of respondents (81.82%, 36) indicated that they identified as White (non-

Hispanic), respondents who identified as Hispanic or Latino made up the second largest group

(11.36%, 5). The third largest group was split down the middle with respondents identifying as

Black or African American (4.55%, 2) and Asian (4.55%, 2). The respondent who indicated

“other race (please specify)” provided the following specification: White/Native American.

3. Public Sector Employees

While the total number of respondents from this subgroup is not large enough from which

to draw any definitive conclusions, Alpha Group thought it would be of interest to the CADRA

Program to include the resulting information from the public sector response to the survey

questions.


The majority of survey respondents from the public sector were female (73.91%), with 17

females responding to the survey and 6 males responding to the survey.


What is your age? Answered: 23 Skipped: 0

The majority of respondents from the public sector were split down the middle between

ages 30-39 (39.19%, 9) and ages 40-49 (39.15%, 9). The second largest percentage of

respondents (13.04%, 3) indicated that they were over 60 years of age. The smallest recorded

age group was 50-59 years (8.70%, 2), and there were no respondents 29 years of age or

younger.



PROGRAM EVALUATION OF CADRA PROJECT 43 Overall, 14 respondents (60.87%) indicated they had completed a master’s degree, while 5

respondents (21.74%) reported having a bachelor’s degree. In total, all 23 respondents (100%)

indicated having attained some level of college degree.


Overall, the majority of respondents (60.87%, 14) indicated that they identified as White

(non-Hispanic), respondents who identified as Hispanic or Latino made up the second largest

group (17.39%, 4). The third largest group was split down the middle with respondents

identifying as Asian (8.70%, 2) and with respondents who would prefer not to answer (8.70%,

2). One respondent (4.35%) indicated that they identified as Black or African-American.

PROGRAM EVALUATION OF CADRA PROJECT 44 Core Questions

1. Higher Education Institutions

Do you or your organization collect community data?


The majority of respondents (51.68%, 77) indicated that they or their organization does

collect data, while 48.32%, 72 respondents replied no to the question. When asked what type of

data they collected, an open ended comment section revealed the following responses:

• Economic performance data for state and local regions • Public health-related data • Socioeconomic data • Survey data • Demographic data • K-12 education data (spending, demographics, student performance, etc.) • Program evaluation data and assessment standards • Census data and historical records

When asked what the collected data is utilized for, in an open-ended comment section we

received the following responses:

• Unspecified research • Program development, intervention • Program evaluation • Performance improvement • Journal and report writing


• testing hypotheses, building models and validating theories (if not capable of falsifying yet)

• Don’t know Does your organization share data

with the broader community? Answered: 58 Skipped: 95

When asked if the collected data is shared with the community, the majority of

respondents (58.62%, 34) relied that yes, data is shared. 25.86% of respondents, (15), said no,

they do not share data with the community, and 15.52% of respondents, (9), were unsure.

Do you or your organization analyze data

using statistical tools? Answered: 57 Skipped: 96


In regard to whether respondents or their organizations use statistical tools to analyze

data, the vast majority of responses (75.44%, 43) indicated that they do use statistical tools,

whereas the remaining 24.56% was split down the middle with respondents claiming that either

they do not use statistical tools (12.28%, 7), or they are unsure (12.28%, 7).

Are there any gaps or deficiencies in your data collection and/or analysis methods that you would like to see improved upon?


When asked if they have any deficiencies in their data collection and/or analysis methods

that they would like to see improved upon, the majority (60.38%, 32) said yes, while 39.62%,

(21), responded that they were happy with their data collection and/or analysis methods.

Respondents who indicated yes offered the following explanations:

• Need to have data warehouse for local regions

• Sometimes school district will not share data

• Data collection lacks comprehensive detail

• Need for analytical tools and expert support (especially for statistics)

• We have no plan for who is collecting data for which purpose and how to apply metadata to it to make it discoverable.


Collection/analysis seems random

• We need to learn how to do principle component analysis

• High quality data is sometimes difficult to collect

• We are beginning to explore systems mapping and are looking for tools to help with that

• We could use training on analysis, planning phase of assessment

Does your organization currently collaborate for community data collection and

analysis with other nonprofit or community organizations? Answered: 53 Skipped: 100

The majority (51.85%, 28) of respondents from higher education institutions indicated

that they do collaborate with other nonprofit or community organizations for data collection.

While 33.33%, (18), indicated that they do not collaborate, 14.81%, (8), indicated that they do

not currently collaborate but are interested in future collaboration.


Satisfaction with Data Collection Answered: 115 Skipped: 38

While most of the respondents from higher education institutions (67.24%, 58) reported

that they strongly agree that data collection is important to their organization, only 8.77%, (5),

said that they strongly agree that they are satisfied with their organization’s data practices.

Most of the responses (43.86%, 25) indicate that respondents report that they only agree that

they are satisfied with their organization’s data practices.

Would you or your organization be interested in outside assistance with data collection and analysis?



Though responses were closely split, the majority of respondents (52.94%, 63) indicated

that they would be interested in outside assistance with data collection and analysis whereas

47.06%, or 56, of respondents indicated that they would not be interested in assistance.

Would you or your organization benefit from a center that provides a single repository for data across several focus areas within the community?


Most respondents from higher education institutions (66.67%, 80) agree that their

organization would benefit from a single repository for community data.

Would you or your organization be willing to contribute a small amount of funds to create and maintain a central data repository?



It is interesting to note that although 66.67%, (80), of respondents indicated their

organizations would benefit from a single community data repository, only 3.33%, or 4

respondents reported that they would be willing to pay a small amount of funding for the creation

and maintenance per the graph below.

Are you or your organization familiar with the data collection and analysis services offered by the Community Advanced Data & Research Analysis (CADRA) Lab of UNLV?


Though previously 66.67%, (80), of respondents claimed their organizations would

benefit from a single repository for community data, only 14.05%, (17), of responses from higher

education institutions indicate that they are familiar with the services offered by the CADRA Lab

of UNLV.


2. Nonprofit Organizations



The majority of respondents (69.05%, 29) indicated that they or their organization does

collect data, while 30.95%, (13), responded no to the question. When asked what type of data

they collected, an open ended comment section revealed the following responses:

• Socioeconomic data • Student specific data • Heath & Education data • Program satisfaction • Regional demographic information • Program usage data • Quantitative data



• Recruitment • Program impact analysis • Program planning & improvement • Grant writing and reporting • Grant applications • Benchmarking • Program evaluation • Fundraising


• Strategic Planning • Analysis of community impact

Does your organization share data



respondents from nonprofit organizations (64.00%, 16) relied that yes, data is shared. 28.00%,

(7), of respondents said no, they do not share data with the community, and 8%, (2), of

respondents were unsure.

Do you or your organization analyze data using statistical tools?





whereas the remaining respondents are split, reporting that 28%, (7) respondents, do not use

statistical tools and 28%, (7) respondents, are unsure.




that they would like to see improved upon, the majority (79.17%, 19) said yes, while 20.83%,

(5), responded that they were happy with their data collection and/or analysis methods.

Respondents who indicated yes offered the following explanations: • Data hygiene & communication between multiple databases

• Need better data collection tools

• The use of statistical tools for measuring outcomes

• Data is not always up-to-date

• Lack of training – we are not using our data or data systems to the fullest

• Up-to-date comparative demographic information would be valuable as would survey support

• Capability to query blind data for meaningful statistics


Does your organization currently collaborate for community data collection and analysis

with other nonprofit or community organizations? Answered: 25 Skipped: 19

The majority (44.00%, 11) of respondents from nonprofit organizations indicated that

they do collaborate with other nonprofit or community organizations for data collection. While

32.00%, 8 respondents indicated that they do not collaborate, 24.00% (6 respondents), indicated

that they do not currently collaborate but are interested in future collaboration.



While most of the respondents from nonprofit organizations (76.00%, 19) reported that

they strongly agree that data collection is important to their organization, only 4%, (1

respondent), said that they strongly agree that they are satisfied with their organization’s data

practices. Most of the responses (40.00%, 10) indicate that respondents report that they only

agree that they are satisfied with their organization’s data practices.

Would you or your organization be interested in outside assistance with data

collection and analysis? Answered: 38 Skipped: 6

The majority of respondents (71.05%, 27) indicated that they would be interested in

outside assistance with data collection and analysis whereas 28.95% or 11 respondents indicated

that they would not be interested in assistance.




Most respondents from nonprofit organizations (86.49%, 32) agree that their organization

would benefit from a single repository for community data. Only 13.51%, or 5, respondents

indicated that they would not benefit from a repository.



PROGRAM EVALUATION OF CADRA PROJECT 57 It is interesting to note that although 86.49% of respondents previously indicated their

organizations would benefit from a single community data repository, only 10.53%, (4), reported

that they would be willing to pay a small amount of funding for the creation and maintenance per

the graph below. The majority of respondents (65.79%, 25) indicated that they were unsure if

they or their organizations would be willing to pay a small amount to create and maintain a

repository.

Are you or your organization familiar with the data collection and analysis services offered by the Community Advanced Data & Research Analysis (CADRA) Lab of UNLV?


Though previously 86.49% of respondents claimed their organizations would benefit

from a single repository for community data, only 18.42%, or 7 responses from nonprofit

organizations indicate that they are familiar with the services offered by the CADRA Lab of

UNLV.


3. Public Sector Employees



Overall the majority of respondents (78.26%, 18) indicated that they or their organization

does collect data, while 5 respondents (21.74%) reported no to the question. When asked what

type of data they collected, an open ended comment section revealed the following responses:

• Socioeconomic data • Education-specific data • Heath & Injury data • Qualitative and Quantitative level data • Community demographic data • Student achievement data • Statistical data • Consumer demographics • Demographic data (all types)



• To inform policy development • For budgeting, expenses, resource allocation • To develop and evaluate programs • To identify needs of students/families attending CCSD at-risk schools • Grant applications


• To determine fair allocation of resources • Statewide case management system • Track program participants • To develop funding formula for family resource centers • Strategic decision making

Does your organization share data



respondents from the public sector (81.25%, 13) relied that yes, data is shared. Two respondents

(12.50%) said no, they do not share data with the community, and one respondent (6.25%) were

unsure.

Do you or your organization analyze data using statistical tools?





whereas 3 respondents (20.00%) do not use statistical tools and 1 respondent (6.67%) was

unsure.




that they would like to see improved upon, the majority of respondents (84.62%, 11) said yes,

while 3 (15.38%) responded that they were happy with their data collection and/or analysis

methods.

Respondents who indicated yes offered the following explanations: • More collection/analysis on the value of services offered

• Need more complete data

• Need data sharing agreements

• Usually data is out-of-date

• Need to collect cleaner data, improve data governance of collected data

• Improve storage of data through data warehousing

• Need increased access to outside data


Does your organization currently collaborate for community data collection and

analysis with other nonprofit or community organizations? Answered: 16 Skipped: 7

The majority (75.00%, 12) of respondents from the public sector indicated that they do

collaborate with other nonprofit or community organizations for data collection. The remainder

of respondents were divided with 2 (12.50%) indicating that they do not collaborate, and 2

(12.50%) indicating that they do not currently collaborate but are interested in future

collaboration.



While most of the respondents from the public sector (62.50%, 16) reported that they

strongly agree that data collection is important to their organization, only 1 respondent (6.25%)

said that they strongly agree that they are satisfied with their organization’s data practices.

Most of the responses (50.00%, 8) indicate that respondents report that they only agree that they

are satisfied with their organization’s data practices.

Would you or your organization be interested in outside assistance with data collection and analysis?


The majority of respondents (70.00%, 14) indicated that they would be interested in

outside assistance with data collection and analysis whereas 6 respondents (30.00%) indicated

that they would not be interested in assistance.




Most respondents from the public sector (90.00%, 18) agree that their organization would

benefit from a single repository for community data. Only 2 respondents (10.00%) indicated that

they would not benefit from a repository.



It is interesting to note that although 90.00% of respondents indicated their organizations

would benefit from a single community data repository, only 1 respondent (5.00%) reported that

they would be willing to pay a small amount of funding for the creation and maintenance per the

graph below. The majority of respondents (70.00%, 14) indicated that they were unsure if they

or their organizations would be willing to pay a small amount to create and maintain a

repository.

PROGRAM EVALUATION OF CADRA PROJECT 64 Are you or your organization familiar with the data collection and analysis services offered

by the Community Advanced Data & Research Analysis (CADRA) Lab of UNLV? Answered: 19 Skipped: 4

Though previously 90.00% of respondents claimed their organizations would benefit

from a single repository for community data, only 2 responses from the public sector (10.53%)

indicate that they are familiar with the services offered by the CADRA Lab of UNLV.

Limitations

As with any type of survey research, there are limitations to be identified. First and

foremost, the collected data is based on self-reports, of which the accuracy and completeness

cannot be verified. Secondly, the data only represents a limited population of higher education

professionals, non-profit experts, and public sector employees.

In addition, it should be noted that there was an extremely small sample size for the

public sector employee population subgroup from which inferences cannot be reliably drawn.

Alpha Group felt it necessary to report the findings for this subgroup, however, in order to

provide as much data as possible from which the CADRA Project team can make inferences and

decisions based on projected data trends. Further limitations include the CADRA Project’s

unique scope of work. While the qualitative benchmark study provided much informative data,

PROGRAM EVALUATION OF CADRA PROJECT 65 it is worth noting that the CADRA Project’s scope and direction is different in various ways from

each of the benchmark programs studied. It will therefore fall under the CADRA Project team’s

discretion as to what input feedback from the benchmark programs are put into action throughout

the lifespan of the CADRA Project.

Recommendations

The systematic program evaluation yielded several significant findings that may help

CADRA improve its process and efficiency. Results of both the survey and benchmark analysis

indicated that the three primary focuses of CADRA should be on: social networking amongst the

primary stakeholder groups, implementation as the local data clearinghouse for Nevada, as well

as, establishment of a long-term funding resource. The following recommendations will be

provided in a timeline of three different groupings offered in short-range (1-3 years), medium-

range (3-5 years), and long-range (greater than 5 years) recommendations. This is done in an

effort to provide the most depth and breath to our advices.

Short-Range Recommendations

As results from both the survey data and benchmark analysis directly indicate,

collaboration will be the most significant thing that CADRA could do in the coming one to two

years. Predictably, the qualitative survey results for higher education institutions indicated that

over half of the respondents were either currently collaborating or were interested in

collaborating for greater community data collection and analysis. These results should

undoubtedly guide the CADRA Project into building partnerships within the different UNLV

Schools and Departments where CADRA could eventually become the central hub within UNLV

for researchers to monitor their necessary socioeconomic data. This is an imperative action, as

PROGRAM EVALUATION OF CADRA PROJECT 66 one of the program options and benefits first identified by the CADRA Project team is

community data mining.

Initially, the CADRA Project should focus their efforts on relationship building and

advocating for faculty research support by demonstrating the advantages and potential for

monitoring community data levels. This is especially beneficial as UNLV seeks to achieve Tier 1

research status. The CADRA Project should focus on the student and faculty researchers at

UNLV and use their tangible products as an advertisement that will ultimately raise awareness of

CADRA and can later market to the nonprofit community. Furthermore, through increased

scholarly published articles and citations, CADRA’s reputation will grow thereby increasing its

overall awareness.

To support this, Dr. Jon Stile of the UC Berkeley D-Lab offered the following

recommendation during his qualitative interview:

“Build partnerships with faculty and listen to their needs. Rely on graduate students

heavily – they are more in tune with needs and frustrations, they are eager to help other

graduate students, they bring lots of energy, and they have networks you can use for

offering and building services around. Don’t reinvent wheels – collaborate with campus

partners. Build in feedback and evaluation mechanisms while building your program.

Create buzz, but try not to over-promise. Accept failures, learn, cut your losses and move

on.” (Qualitative Interview, July 09, 2015)

As a second recommendation, the CADRA Project should focus on fostering a place

where nonprofit organizations, public sector departments, and higher education researchers can

network for the greater good of data obtainability. As the qualitative survey results indicated,

there is both a need and desire in the Las Vegas community amongst all three of the targeted

PROGRAM EVALUATION OF CADRA PROJECT 67 survey groups for an increased collaboration for community data collection, while all of the

groups similarly noted that they had gaps or deficiencies in their data collection or analysis

methods. Ultimately, the CADRA Project has the ability to be a nexus point where professionals

of various levels seeking various objectives can come together for the greater good of research,

data accessibility, and data analysis. Moreover, a particularly useful benefit of the CADRA

Project lab that must be advocated for will be program development and grant writing benefits,

an articulated community need.

Although marketable to the nonprofit organizations and community stakeholder groups, it

is imperative that the CADRA Project connects with faculty to communicate their ability to

develop programs that have real world employability and applicability for UNLV students. The

CADRA Project should consider hosting data workshops for the various colleges and

departments throughout the University to inquire about their support for the lab with the funding

of graduate assistants. Furthermore, it may provide faculty with potential practicum concepts for

upcoming advanced studies graduate students.

To support this, Mr. Bobray Bordelon from Princeton offered the following

recommendation during his qualitative interview:

“Focus on your actual university not the trends out there. Don't jump on

bandwagons without seeing what is really needed. Have subject experts that understand

the actual fields they represent (economics, politics, sociology, etc.). Don't expect one

person to know all data content and multiple statistical packages. Take advantage of

graduate students’ knowledge. Attend the biennial summer workshop at ICPSR on

managing a social science data service.” (Qualitative Interview, June 17, 2015)

PROGRAM EVALUATION OF CADRA PROJECT 68 Medium-Range Recommendations

It is highly recommended that this program evaluation be reviewed and recompleted in

three to five years in an effort to try and incorporate the initial baseline data that will be gathered

in the coming years. By using this initial evaluation as a baseline, a subsequent “Beta Group”,

could further refine this study to focus on specific topic areas that the CADRA Project team

could improve upon once they are more established.

Additionally, it is recommended that in three to five years, as CADRA grows and its

mission develops, so should the organizational chain of command. It is imperative that within

any organization, a good leadership be established and clearly articulated to the communities for

which it serves. In this case, CADRA’s service opportunities are considerable and vast, and

therefore must ensure that they appropriately account for all of the stakeholders for which they

assist.

Long-Range Recommendations

First and foremost, a permanent funding source must be secured for the CADRA Project

lab. This is an essential component to any long-term, successful organization and will ensure that

CADRA is able to provide its marketed resources. It was consistently seen throughout the

quantitative results by the various nonprofit organizations and higher-education professionals

that there was a disinterest in contributing self-funding to support or maintain a central data

repository. Therefore, until the CADRA Project can establish its legacy, a more stable funding

source must be obtained. In addition, it was constantly noted in the qualitative findings that

programs were on a strict full-cost recovery basis while receiving aid from their University, or

the programs had an established funding agreement with the federal government. This allowed

these established national programs to support a minimum amount of staff annually to ensure

PROGRAM EVALUATION OF CADRA PROJECT 69 continuity of operations, and established goals. Therefore, securing a guaranteed funding source

will ultimately allow the CADRA Project to ensure that the program staff is available to provide

the promoted services and necessary training to the various students, faculty and outside

organizations.

And finally to support this, Dr. Catherine Fitch of the Minnesota Population Center

offered the following recommendation during her qualitative interview:

“Pay attention to mission. Pay what is necessary for quality employees. Trickle-

up good ideas. Take energy and successes and build off of them” (Qualitative Interview,

June 30, 2015).

Conclusion

This program evaluation has attempted to gain an initial understanding of the data

research collection and analysis practices of the Las Vegas community, while assessing the

current needs of local nonprofit organizations, higher education institution faculty, and public

sector employees. The evaluation team has found that although nonprofit organizations, higher

education faculty, and public sector employees collect voluminous amounts of data on a wide

variety of topics, survey results from these groups indicate a definite need for assistance in data

collection, as well as support in advanced data analysis.

Furthermore, it was evident from the survey results that nonprofit organizations have a

difficult time identifying their own data collection and research needs. Even more apparent from

the survey data was the desire from all responder groups to collaborate within the community for

research data management. Removing barriers to data collection will further assist nonprofit

organizations by increasing their efficiency in data management, thereby, augmenting their grant

applications, evaluation practices, and program planning.


After a careful and systemic initial program evaluation by the Alpha Group, it was

suggested that the CADRA Project introduce several key recommendations in the coming years

that will effectively ensure the program’s long-term success and mission achievement. It was

suggested there be a focus on increased community collaboration and engagement with higher

education faculty and students in research data collection and management, particularly by

utilizing the CADRA Project lab as a nexus for UNLV researchers, nonprofit organizations, and

public sector employees. There is a clear indication that the nonprofit sector specifically has a

need of data analysis resources that higher education institutions can ultimately provide. The

focus should be on building partnerships in the form of service learning where the movement can

truly begin at the forefront of community based research and data analysis. Moreover, a follow-

up evaluation should be completed in three to five years in order to re-evaluate progress and

effectively benchmark out future goals. Finally, the CADRA Project lab should begin to secure a

long-term funding source. As the CADRA Project lab begins to produce sound results in terms of

data collection and management assistance to the community, there will only be enough

volunteers to go around and the lab will require additional revenue to remain adequately staffed.

Although graduate assistants and student researchers will prove to be a valuable asset, the

CADRA Project’s lack of steady financial resources may be an indicator of long-term weakness.

Therefore, a permanent plan of action should be established and should highlight the depth-and

breadth of the services provided by the lab.

Notably, this program evaluation sought to focus on the initial assessment of the CADRA

Project’s start-up, by asking whether CADRA is capable of providing increased access and

obtainability to data within the Las Vegas community. Furthermore, we systematically evaluated

whether they appropriately target the access to the three stakeholder groups, and can definitively

PROGRAM EVALUATION OF CADRA PROJECT 71 report that the CADRA Project appropriately targets all three-stakeholder groups and is capable

of providing the necessary access and obtainability to community data within the Las Vegas

area. We found that all stakeholder groups have challenges in collecting, managing and

analyzing research data, and conceivably require training in advanced research and capacity

building, a need that can be fulfilled by CADRA Project. As Tim Berners-Lee, creator of the

World Wide Consortium and Open Data Institute once said, “Data is a precious thing and will

last longer than the systems themselves” (Tim Berners-Lee, n.d.).

Acknowledgements

Alpha Group would like to sincerely acknowledge and thank everyone at the CADRA

Project who has been involved with this evaluation over the course of the last several months.

Special thanks to John Wagner and Lola Brooks for providing information on the history and

background of the CADRA Project as well as for guidance throughout the data collection

process. We appreciate the input and feedback you have provided throughout this evaluation

process.


References

Carman, J. G. "Nonprofits, Funders, and Evaluation: Accountability in Action." The American

Review of Public Administration: 374-90.

Creswell, J.W., & Plano Clark, V. L. (2011). Designing and conducting mixed methods research

(2nd ed.). Thousand Oaks, CA: Sage Publications.

Hendricks, M., Plantz, M.C., & Pritchard, K.J. "Measuring Outcomes Of United Way-funded

Programs: Expectations And Reality." New Directions for Evaluation: 13-35.

Johnson, J. A., Honnold J.A., and Stevens, P.F., "Using Social Network Analysis to Enhance

Nonprofit Organizational Research Capacity: A Case Study." Journal of Community

Practice 18 (2010): 493-512.

Mancini, J. A., Marek, L.I., Byrne, R. A. W., & Huebner, A.J., "Community-Based Program

Research." Journal of Community Practice (2004): 7-21.

Schwartz, S. L., and Austin, M.J., "Financing and Evaluating Nonprofits: Mapping the

Knowledge Base of Nonprofit Management in the Human Services." Mack Center on

Non-Profit Management, in the Human Services.

Stoecker, R. "Challenging Institutional Barriers To Community-based Research." Action

Research: 49-67.

Stoeker, R. "The Research Practices and Needs of Non-Profit Organizations in an Urban Center."

Journal of Sociology & Social Welfare XXXIV.4 (2007): 97-119.

Tim Berners-Lee. (n.d.). BrainyQuote.com. Retrieved August 11, 2015, from BrainyQuote.com

Web site: http://www.brainyquote.com/quotes/quotes/t/timberners373116.htm

Wing, K.T., "Assessing the Effectiveness of Capacity-Building Initiatives: Seven Issues for the

Field." Nonprofit and Voluntary Sector Quarterly (2004):


Appendix A – Quantitative Survey Information

Community Data Needs Survey

Q1 You are being asked to participate in a survey that was designed for a student project on

advanced program evaluation. The following 5-minute survey examines the socioeconomic data

needs in Southern Nevada. Your responses to this survey are both completely voluntary and

anonymous. If you have any questions, please email them to [email protected] or Dr.

Jaewon Lim at [email protected].

Q2 What is your gender?

Male (1)

Female (2)

Other (please specify): (3) ____________________

I prefer not to answer (4)

Q3 Which category below includes your age?

Younger than 20 years (1)

21-29 (2)

30-39 (3)

40-49 (4)

50-59 (5)

60 or older (6)

Q4 What is your race?

White (Non-Hispanic) (1)

Black or African-American (2)

Asian (3)

Native Hawaiian or Pacific Islander (4)

Hispanic or Latino (5)

Other race (please specify): (7) ____________________

I prefer not to answer (8)

Q7 Which of the following categories describes the level of education you have attained?

Less than high school (1)

High school graduate (2)

Some college but no degree (3)

Associates degree (4)

Bachelors degree (5)

Masters degree (6)

Doctoral degree (7)

Q5 Which of the following categories best describes your current status?

Employed by government (1)

Employed by private sector (5)

Employed by university or higher education institution (6)

Employed by non-profit organization (other than university or higher education institution) (7)

Currently unemployed (8)

Retired (9)

Graduate Student (10)


Q18 Does your organization have current 501(c)(3) status?

Yes (1)

No (2)

Q11 Roughly how many full-time employees work for your organization?

1-10 (1)

11-50 (2)

51-200 (3)

201-500 (4)

500+ (5)

Q17 How much money, in U.S. dollars, does your organization raise annually?

Q8 Do you or your organization collect community data?

Yes (1)

No (2)

If No Is Selected, Then Skip To End of Block

Q19 Please identify what type of data is collected:

Q20 What do you or your organization use collected data for?

Q21 Does your organization share data with the broader community?

Yes (1)

No (2)

Unsure (3)

Q22 Do you or your organization analyze data using statistical tools?

Yes (1)

No (2)

Unsure (3)

Q23 Does your organization utilize data to improve programming?

Yes (1)

No (2)

Unsure (3)

Q29 Are there any gaps or deficiencies in your data collection and/or analysis methods that you

would like to see improved upon?

Yes (explain): (1) ____________________

No (2)

Q16 Does your organization currently collaborate for community data collection and analysis

with other non-profit or community organizations?

Yes (1)

No (2)

Not currently, but interested in collaboration (3)

Q27 Please tell us how much you agree with the following statements.

Strongly Disagree (1)

Disagree (2) Neutral (3) Agree (4) Strongly Agree (5)

Data collection is important to

my organization.

(1)

I am satisfied with my

organization's data

practices. (2)

Q12 Have you or your organization ever applied for an external grant?

Yes (1)

No (2)

If No Is Selected, Then Skip To End of Block

Q14 How many grants have you or your organization written in the last two years?

0 (1)

1-2 (2)

3-5 (3)

5-10 (4)

10+ (5)

Q15 How many grants have you or your organization had awarded in the last two years?

0 (1)

1-2 (2)

3-5 (3)

5-10 (4)

10+ (5)

Q13 What resources do you use for your grant writing?

We have dedicated employee(s) (1)

We have employee(s) with collateral duties (2)

We hire a third party (3)


Q25 If you or your organization use data to conduct research, which data collection methods are

used?

Official Documents (1)

Observations (2)

Surveys (3)

Experimental (4)

Multi-methods Approach (5)


I/We do not use data to conduct research (7)

If I/We do not use data to con... Is Selected, Then Skip To End of Block

Q26 On what topics do you or your program (or department) collect data for research?

Q9 Would you or your organization be interested in outside assistance with data collection and

analysis?

Yes (1)

No (2)

Q30 Would you or your organization benefit from a center that provides a single repository for

data across several focus areas within the community?

Yes (1)

No (2)

Q32 Would you or your organization be willing to contribute a small amount of funds to create

and maintain a central data repository?

Yes (1)

No (2)

Unsure (3)

Q10 Are you or your organization familiar with the data collection and analysis services offered

by the Community Advanced Data & Research Analysis (CADRA) Lab of UNLV?

Yes (1)

No (2)

1. What is your gender?

Results with no FiltersLast Modified: 08/10/2015

1 Male 97 42%

2 Female 132 57%

3 Other (please specify): 0 0%

4 I prefer not to answer 2 1%

Total 231

Min Value 1

Max Value 4

Mean 1.60

Variance 0.29

Standard Deviation 0.54

Total Responses 231

# Answer Bar Response %

Other (please specify):

Statistic Value

2. Which category below includes your age?

1 Younger than 20 years 0 0%

2 21-29 10 4%

3 30-39 54 23%

4 40-49 68 29%

5 50-59 53 23%

6 60 or older 46 20%

Total 231

Min Value 2

Max Value 6

Mean 4.31

Variance 1.34


Total Responses 231


Statistic Value

3. What is your race?

1 White (Non-Hispanic) 184 80%

2 Black or African-American 9 4%

3 Asian 14 6%

4 Native Hawaiian or Pacific Islander 1 0%

5 Hispanic or Latino 16 7%

7 Other race (please specify): 5 2%


West Indian-Jamaican

mixed

American Indian

White/Native American

adopted, native american mother, also adopted

Min Value 1

Max Value 8

Total Responses 231


Other race (please specify):

Statistic Value

4. Which of the following categories describes the level of education you haveattained?

1 Less than high school 0 0%

2 High school graduate 1 0%

3 Some college but no degree 9 4%

4 Associates degree 5 2%

5 Bachelors degree 26 11%

6 Masters degree 59 26%

7 Doctoral degree 131 57%

Total 231

Min Value 2

Max Value 7

Mean 6.28

Variance 1.11


Total Responses 231


Statistic Value

5. Which of the following categories best describes your current status?

1 Employed by government 23 10%


5 Employed by private sector 10 4%

6 Employed by university or higher education institution 153 66%

7 Employed by non-profit organization (other than university or higher education institution) 44 19%

8 Currently unemployed 2 1%

9 Retired 1 0%

10 Graduate Student 0 0%

Employed by school district

Min Value 1

Max Value 9

Total Responses 232



Statistic Value

6. Does your organization have current 501(c)(3) status?

1 Yes 42 98%

2 No 1 2%

Total 43

Min Value 1

Max Value 2

Mean 1.02

Variance 0.02


Total Responses 43


Statistic Value

7. Roughly how many full-time employees work for your organization?

1 1-10 13 30%

2 11-50 12 28%

3 51-200 10 23%

4 201-500 5 12%

5 500+ 3 7%

Total 43

Min Value 1

Max Value 5

Mean 2.37

Variance 1.52


Total Responses 43


Statistic Value

8. How much money, in U.S. dollars, does your organization raise annually?

I don't know

100,000 plus

$1,600,000

0

6,000,000

9 million

1,400,000

$1,000,00-2,000,000

2,475,000

$200000

$500,000

150,000

250000

7,000,000

$1.5 million

1,000,000

$1.2 million

11 million+

800000

13,500,000

$2,000,000

Not sure

$200,000 plus

1,000,000

$12,000,000

$85,000

$28M

$12,000,000

1.3

1,000,000

$3,000,000

1- 1.3 million

Unknown

$2 million

1,500,000

$450,000

$10,000,000

1,3000,000

$30M

Total Responses 39

Text Response

Statistic Value

9. Do you or your organization collect community data?

1 Yes 130 58%

2 No 96 42%

Total 226

Min Value 1

Max Value 2

Mean 1.42

Variance 0.25


Total Responses 226


Statistic Value

10. Please identify what type of data is collected:

Conference evaluations primarily

economic performance data for state and local regions

school student data

primary data on individuals and families and organizations

Personal and health

Don't know exactly

Age/ ticket purchase/ interests

don't know

experimental, observational, economic indices etc.

We are the Libraries - so we collect data from all kinds of organizations -- NGO, governmental, commercial, our center for gaming research collects data related to gamingindustry

I have no idea. i do not personally collect data about my community, nor is my research about my community, but i assume my university does. However, I have no involvementwith this data.

It would have been helpful if you defined "community data". - we collect data on natural background radiation levels

water quality, air quality, student feedback

Social, professional

assessment evaluations

Assessment scores

educational data from classrooms, school administration, families and educational software

Job placement rates of graduates

K-12 education data (spending, demographics, student performance, etc)

historical records documenting the community

Economic data

Census data, public health data

Social economic status of community

psychological research data - surveys, attitudes, ability measures

Statistics regarding reference questions, as well as circulation data.

CCSD student achievement and language proficiency data.

health data, public health data, demographic data,

dietary and physical activity level data, physological profile data, geographic information system (GIS) data, and others

quantitative and qualitative data

vulnerable segments of society that have had violent interactions, just starting this with data from records housed in several repositories in S. Nevada

Weather and census

Individual- and dyadic-level data primarily. Individuals' behaviors in relationships, people's knowledge of personal, social, and health, and it's effects on their communicationand relationships.

Probably all kinds since my employer is a university, but I don't specifically know.

Health data, BRFS, Hospital inpatient and outpatient visits in Nevada

information related to infrastructure

qualitative level (case reviews, user experiences/perceptions) and quantitative, counts of system/ resource use, youth provided services, demographics, duration of servicedelivery etc.

Health and Injury data

health

mental health symptoms and satisfactions ratings

survey data

The focus of our data collection is education-centric

demographics of all types

Student data (Average Daily Attendance, GPA, Required Parent Conferences, In School Suspensions, Out of School Suspensions)

health and education

program satisfaction, frequency of family reading time

I don't collect this type of information and I'm not sure what type of data is collected but I work at UNLV so I answered yes to the previous question because I am sure peoplehere collect this type of data.

Statistics

demographic information, attitudes of community members

Demographics of zip codes and counties

Text Response

Ticket holder information, Ed Outreach demographic information

impact at schools

Mainly consumer demographics (gender, age, ethnicity, poverty status, etc) and service units

Information on program participants such as age, education level attained, ethnicity, etc.

referring agency, client's name, age, zip code, marital status, ethnicity, language spoken, infant's gender, DOB, weight, items needed

Ethnicity, Race, poberty level, encounters, type of insurance, per diagnosis e.g. diabetes, prostate cancer, HTN, among others

demographic, grant and program goals, trends, etc

Informaiton on families and children

Demographics primary but also frequency of services, distance, benefits assessment

Chronically homeless individuals/familes, thosed housed and in services, case management services, individual individuals/families that recieve general assistance

Demographics

user demographics, scholastic improvement, post training employment, web traffic, materials loaned

healthcare data

Community data, various populations, various demographics

Demographics

Program Usage by individuals; number of people trained and reached through outreach, demographics including sexual orientation and gender identity

Student homeless population

Statistics

Health and behavior assessments

Population in zip codes, % of people in those zip codes who live below poverty level, number of childre (birth - 18 y.o.) who live in the zip codes.

Student achievement data

Demographics, employment, barriers to employment, training

Fiancial comparisons

Customer data from local casinos and hospitality establishments

educational needs, social needs

Job Seeker Data, Job Placement and Training Data

demographic

Diversity

data on undergraduate research

Both quantitative and qualitative data

data on clients served, community service needs,

I work for a univeristy so this question is not written well as I don't know all of the data that is collected by the entire org. For my program, I collect BMI, Body fat, substance abusehistory, body image, eating disorders, and other similar data.

Demograhics, eligibility determination and service provision

Quantitative

Data from fieldwork about populations that I write about.

Demographics

protected health information. treatment outcomes. mental health assessment data

HMIS

diseases of our patients

Demographics, clients served, most requested services, functioning improvement

both quant and qual data is collected from justice institutions (locally, nationally), individuals (national surveys, local surveys), community members (key players/stakeholders),and local non profits.

clinic outcome data

Demographic data, socio-economic information, wealth/net worth information

Nonprofit program outcome data

Demographics, educational readiness, educational preferences

Resident needs assessments; community demographics;

Total Responses 95

Statistic Value

11. What do you or your organization use collected data for?

Strategic planning

For research in economic development, demographic and labor market analysis

Research by faculty

We use the data to write peer-review journal articles, issue briefs, reports to funders, and as information for tv and radio interviews.

Providing patient care

i don't collect data but others at the university collect data.

Season selection

don't know

testing hypotheses, building models and validating theories (if not capable of falsifying yet)

making available to users

See above.

research

Analysis of data, report and journal article writing

Research

assessment

Monitor development and progress

educational research

To determine the best way to help graduates obtain jobs

research

to support research and education

Analysis

Public health research and practice

For recruitment

metrics

psychological research

Internal uses (resource allocation, etc.)

Program evaluation and research

To analyze the health of a population (local - Clark County, state, national and international)

Data is used to increase improve measurement methodology, evalution intervention outcomes and public policy, and greater understanding of associations between humanbehavior, personal charateristics, environment and health outcomes.

program evaluation

research

Used for local research project re: homeless population

Basic and applied research

Education and academic research.

Research

sustainable community planning and design

to inform policy development, practice change, budgeting and expenses, resource allocation and system performance.

To Develope, Initiate and evaluate programs

research and student projects

to monitor treatment outcomes and satisfaction of client-therapist relationships

peer reviewed research, policy reports

Identify needs of students/famlies attending CCSD at-risk schools

to help the City run more efficiently, targeting who should be targeted so that resources are allocated fairly

Analyzing the impact of our services on the population served, demonstrating the impact of our program to funders and external stakeholders.

response to donors on effectiveness of money given to agencies.

reassessment of programs, grant applications, board knowledge

See above comment.

Quality improvement

research on attitudes regarding a number of issues, including sense of community and belonging, sexuality issues

We use the data to compare our program/work with other programs similar to ours and youth not in any programs

Better planning and targeting of marketing efforts, better programs to at-risk populations

Text Response

for grants

Statewide case management system

To track participants in programs and to determine who we should be providing outreach and education/marketing to.

creation of plans and laws

to track need by zip code, numberr of agency referrals, how many babies are served

To report to the government, to identify areas of need and create new programs, to apply for new grants.

Reporting purposes, speaking events, grants, program enhancement, etc.

Grant reports and annual marketing materials

Grant program tracking, short term impacts, policy development and evaluation, awareness raising, collaboration between entities in the network, driver of strategic planning forlong term operations, and forecasting trends

Grants applications, renewals, county management and elected officials

Reports and grants

donor accountability reports, ROI analysis, program evaluation, needs assessments

Identifying trends in healthcare utilization, quality measures, spending

community and council reporting, State/County/Federal grants, programmatic assessments and measurable outcomes.

Grant Applications, Strategic Planning, Donor Solicitation Materials

Benchmarking, to know level of community impact

Need assessment

To better serve the community

Demonstrate evidence-based practice; reporting; publications

Funding formula for Family Resource Centers

We use data for improvement of instructional practices and strategic decision making

To analyze and evaluate Title I WIA performance - employment and training services

See how well we are doing compared to our peers.

Journal articles

Develop programs, interventions

Assist people find jobs who have disabilities and other challenges to employment

audience and donor analysis

To identify needs for better and more encompassing programs

developing undergraduate research program

Primarily research and for some evaluation and performance improvement

To improve agency and community service systems

needs assessments, write journal articles

Analysis, monitoring and compliance

Performance management and program improvement

To write books and articles.

Planning

research, treatment planning, evaluation

grant reporting

Electronic Medical Records

Evaluating needs in the community, gaps of services, tailor services to population served, grant opportunities

research, publication, presentations at the local and national level.

improve quality of services, demonstrate value of organization

Fundraising and marketing initiatives.

Program reporting; reporting to funders

Financial Aid, Grants, State.Regents Reporting, Academic Scheduling, Registration.

Prioritizing new park development; programming choices; capital infrastructure determination etc.

Total Responses 97

Statistic Value

12. Does your organization share data with the broader community?

1 Yes 65 63%

2 No 25 24%

3 Unsure 13 13%

Total 103

Min Value 1

Max Value 3

Mean 1.50

Variance 0.51


Total Responses 103


Statistic Value

13. Do you or your organization analyze data using statistical tools?

1 Yes 69 68%

2 No 17 17%

3 Unsure 15 15%

Total 101

Min Value 1

Max Value 3

Mean 1.47

Variance 0.55


Total Responses 101


Statistic Value

14. Does your organization utilize data to improve programming?

1 Yes 74 72%

2 No 8 8%

3 Unsure 21 20%

Total 103

Min Value 1

Max Value 3

Mean 1.49

Variance 0.66


Total Responses 103


Statistic Value

15. Are there any gaps or deficiencies in your data collection and/or analysismethods that you would like to see improved upon?

1 Yes (explain): 63 67%

2 No 31 33%

Total 94

Social science librarians to curate data

Need to have data warehouse for local regions

sometimes school district will not share

More comprehensive detail

analytical tools and supports from experts (statistics)

we have no campus plan for who is collecting what data for which purpose and how to apply metadata to it to make it discoverable --

not applicable

we need to learn how to do principle component analysis

it seems random

high quality data about students, at the student level, is difficult to get (validity, missingness)

The data are publicly available but need to be integrated into an easily usable, single database

small sample size, linking individual data to census data

Use of statistical programs and tools would help analyze the data we collect and give it more impact on our policies and practices.

Greater capacity to collect supplemental data from students.

Greater sharing of data between the different health departments in the state

the word "improve programming" is unclear. It assumes a program is already in place and the data is for improvement. Initially I though you were asking about establishing acomputer program. Some of the data I collect is directly related to evaluation of an exiting intervention while other data is exploring the need, evaluating hindrances andenhancers for a successful interventions, and measuring program outcomes.

We are beginning to explore systems mapping and are looking for tools to help with that

Training on analysis, planning phase of assessment needs help as well

At the unit/department level, more information about our students would be helpful (e.g., numbers, progression, when they register, etc.). For academic research, having datafrom non-college student population would be very valuable.

Hospital emergency room wait times

there needs to be a broader base of independent and high quality research related to physical and social measures of resilience

Many

I do not have any project that collecting the community data so I don't have these information. There are some faculties in my school that do but I do not know what they aredoing.

better facilitation of research by university of IRB

response rates

The number of respondents could be increased

I would like the data we gather from partner school districts to integrate better into our internal data system.

we are not using our data or data systems to the fullest; lack of training

cost to have verified by 3rd party limited to every 3 - 5 years, only part of puzzle so hard to weed out true impact of programs

The survey research center we have used in the past was not as efficient as we would have liked.

Not all people are documented and people move a lot. Not always up to date.

Up to date comparative demographic information would be valuable as well as survey support


Yes (explain):

working with school district is a challenge - they make it difficult to collect data

More collection/analysis on the value of services offered

Some is voluntary and if it were required we would have more complete data.

The use of Statistical Tools for Measuring Outcomes

more input/participation

tracking inventory

capability to query blind data for meaning statistics

Our own internal ability to produce quality, constumizable GIS maps

Data sharing agreements

How we capture information using our current databases and registration forms/ templates

Sharpen our data collection practices

Need better data collection tools, methods to analyze data, ways to store data to easily report out information. Currently, we primarily use Excel aside from a few otherdatabases related to fundraising and volunteerism.

Which data was available thru the CCSD

Don't know enough about it

Greater community collaboration efforts

current information. Usually the data is several years old.

We are working to collect cleaner data, improve data governance of collected data, improve storage of this data through the use of data warehousing, and improve access todata analysis tools throughout the organization

Access to outside data such as UI wages

more detail and long term analysis

We need to do a better job collecting performance data on our students.

We could provide additional data about community needs through better (more timely and consistent) analysis.

Zip code & county level data

Ability to share by interfacing with other systems

data storage is always a problem

collecting data on participants that utilize multiple services within the organization

The ability to pull more detailed and specific reports by age disease race gender

mixed methods, qualitative methods, and higher statistical analysis training

Data hygiene and communication between multiple databases.

Min Value 1

Max Value 2

Mean 1.33

Variance 0.22


Total Responses 94

Statistic Value

16. Does your organization currently collaborate for community data collectionand analysis with other non-profit or community organizations?

1 Yes 52 53%

2 No 31 31%

3 Not currently, but interested in collaboration 16 16%

Total 99

Min Value 1

Max Value 3

Mean 1.64

Variance 0.56


Total Responses 99


Statistic Value

17. Please tell us how much you agree with the following statements.

1 Data collection is important to my organization. 3 0 9 21 70 103 4.50

2 I am satisfied with my organization's data practices. 5 18 31 40 8 102 3.27

Min Value 1 1

Max Value 5 5

Mean 4.50 3.27

Variance 0.78 1.01

Standard Deviation 0.88 1.01

Total Responses 103 102

# Question Strongly Disagree Disagree Neutral Agree Strongly Agree Total Responses Mean

Statistic Data collection is important to my organization. I am satisfied with my organization's data practices.

18. Have you or your organization ever applied for an external grant?

1 Yes 171 86%

2 No 27 14%

Total 198

Min Value 1

Max Value 2

Mean 1.14

Variance 0.12


Total Responses 198


Statistic Value

19. How many grants have you or your organization written in the last twoyears?

1 0 12 7%

2 1-2 43 26%

3 3-5 34 20%

4 5-10 25 15%

5 10+ 52 31%

Total 166

Min Value 1

Max Value 5

Mean 3.37

Variance 1.82


Total Responses 166


Statistic Value

20. How many grants have you or your organization had awarded in the last twoyears?

1 0 29 18%

2 1-2 54 33%

3 3-5 32 19%

4 5-10 15 9%

5 10+ 35 21%

Total 165

Min Value 1

Max Value 5

Mean 2.84

Variance 1.95


Total Responses 165


Statistic Value

21. What resources do you use for your grant writing?

1 We have dedicated employee(s) 50 31%

2 We have employee(s) with collateral duties 49 31%

3 We hire a third party 8 5%


Total 159

there is OSR, but nothing specific to our department

I do it all.

Self

Self

I write them myself, or as a Co-PI with another faculty member

All of the above.

Don't know

I write the major grants that support my lab. My students and post-docs write for fellowships or other small grants.

we each write them ourselves

Self

ourselves, though we have support from office of sponsor program for the formatting etc.

no help

Self

existing staff

individuals write their own grants

myself

I write the grants myself, in partnership with either community partners or other UNLV faculty

I did it myself

I've only applied for one particular grant which has a fairly simple process. No resources have been needed.

We use our own resources and personnel.

not sure

my own data based on my work

Ourselves

indidual employees for their own area of expertise

sponsored programs

myself

myself

I write the grants

we do it

I wrote them myself

Faculty write grant applications themselved

Do it myself.

We write the grants ourselves



All of the above

Individuals apply for grants and write those

research support staff

I write them myself. The only needed resources are preliminary results from my laboratory, and references from journals obtained through the library.

some employees and some colleagues outside of unlv

Sometimes we use a third party

Mgmt staff assists grant team

Workshops

volunteers/board members

My colleagues and I write our proposals

Professors write their own grant applications

graduate research assistant

All of the above

Third party and collateral employees

I do it

i write my grants

I write the grants

Me

Min Value 1

Max Value 4

Mean 2.39

Variance 1.53


Total Responses 159

Statistic Value

22. If you or your organization use data to conduct research, which datacollection methods are used?

1 Official Documents 71 37%

2 Observations 74 39%

3 Surveys 96 50%

4 Experimental 61 32%

5 Multi-methods Approach 81 42%


7 I/We do not use data to conduct research 33 17%

read legal decisions

i cannot answer this question.

NASA multispectral imagry

Hand collection of publicly available data.

Secondary data and administrative data gathered primarily by governmental organizations

administrative data

focus groups

Instruction assessment/assignment samples

All of the above

ethnography

open houses

third party

online tests, 3rd party evaluation

ethnographic interviews

Unknown

video data

search engines

Min Value 1

Max Value 7

Total Responses 191



Statistic Value

23. On what topics do you or your program (or department) collect data forresearch?

Academic papers only

psychopathy, depression, personality, emotion

sexuality, parenting, fertility

Conferences

economic development, demographic analysis

Mental health

Educational

Topics related to Teaching and Learning

mental health, behavioral health, integrated health care, caregiving,

None

Biological and evolutionary research

Infrastructure health, environmental conditions, water quality, weather, seismic activity, and many others

Health disparities

Not sure

developmental genetics in model organisms

Various medical conditions

Theater

everything, that's why we are called a UNVERSity

human movement

Bioinformatics

social phenomena

dispute resolution, psychology

education, market data on prices, demand and others. cost data

Pain and spinal manipulation

we collect data for our own faculty research -- and we collect data for UNLV faculty and the community to use for their own research...... all kinds of topics - our research ismostly in gaming -- student learning -- library use and impact ..

I collect data on my field (medieval history). my university collects data on many diverse topics.

geology, physics

air quality, water quality, student feedback

Linguistic needs

none that i know of

Auditor and client communication, Auditor judgment and decision making

motivation, cognition, metacognition, and student demographics as they influence learning outcomes

K-12 Education, government funding of public services (e.g. Criminal justice, juvenile services, social services)

health care

student use of technology

Firm-Level and Intra-Firm Level Data; business formation, performance, social dynamics, behaviors, goal development, strategy, etc.

Economic research

student progress

Health

Arts

medical and dental treatment

Microviology

decision making, memory, perception, attitudes/opinions, prior experiences

Varies

K-12 literacy and English language proficiency

health, public health, health disparities

The majority of data is related to research methodology, epidemiology, physiology, public policy, and intervention outcomes.

engineering

Almost all our projects depend on some type of data creation or colletion and analysis.

Biochemistry

Text Response

responsible environmental behavior, public understanding of science

interpersonal violence, repeated violent interactions, health consequences of nonlethal violence

radiochemistry, environmental chemistry, geochemistry

Satisfaction, useability research, impact of service

Economic development, entrepreneurship, social enterprise

Communication behaviors, health, relationships,

human cognitive processes

related to project management and performance

Special education, teacher preparation, autism, counselor education, teaching english language learners, early childhood education

Information literacy instruction; library material, facility, and service use; S. NV community history; gaming

Health care access and quality; public health, community health

Topics related to dentistry

issues related to sustainability, urban design and planning

safety of children

substance abuse and domestic violence

Not research oriented

Improving relational capacity to reduce teen pregnancy.

Legal and social

materials chemistry

psychotherapy treatment outcomes

Health, Economic Stability, Education, Community Engagement

quality of life, crime, community policing, sustainability, sexual commerce, aging and health

social issues

Academic and non-academic needs of CCSD students

Cultural programs

the effects of epistemological beliefs on learning and cognition

geology, earthquakes

health status, health behaviors, risk factors, characteristics of investigators pursuing health research

I am currently researching faculty governance at universities throughout the world

Emergency response times

a wide variety of questions regarding social issues such as sexuality, sexual commerce, sex trafficking, attitudes to community, aging, safety, policing, culture, economics & jobs

Education, wage, job market, immigration

Age, gender, ethnicity, geography, ticket purchasing input, program attendance input, marketing, education

impact school gardens on STEM, health and community engagement at schools

Income, housing, employment, education, health

Pariticipation in Higher Education Savings Accounts

various

K-12 Education

animal ownership and advocacy

diabetis, COPD

Headcount of persons who utilize our programs and services

Pediatric cancer

Food insecurity, poverty, distance and service access

educational effectiveness, post training employment, event atrtendance, media utilization

Student progression, graduate programming

I collect data on youth, Child Care Subsidy, CACFP, SFSP, populations served, etc.

Children stats Annie Casey, NV State, County, City sites, COC's, hospitals, police, anywhere relevant to topic need

Homelessness

I do not collect data for research.

journalism and media studies

This table has more than 100 rows. Click here to view all responses

Total Responses 131

Statistic Value

https://unlv.co1.qualtrics.com/WRQualtricsServer/Export.php?Type=CSVTextResponses&Questions%5B0%5D=QID34&ServerID=&SurveyID=SV_0ClnIo4pfWZ8A97&ResponseSetID=RS_0cArKQ2xeRljcoZ&SubgroupID=&StartDate=&EndDate=&QToken=HWimehgEuFxx65oXgh7F8g==

24. Would you or your organization be interested in outside assistance withdata collection and analysis?

1 Yes 105 57%

2 No 78 43%

Total 183

Min Value 1

Max Value 2

Mean 1.43

Variance 0.25


Total Responses 183


Statistic Value

25. Would you or your organization benefit from a center that provides a singlerepository for data across several focus areas within the community?

1 Yes 134 73%

2 No 50 27%

Total 184

Min Value 1

Max Value 2

Mean 1.27

Variance 0.20


Total Responses 184


Statistic Value

26. Would you or your organization be willing to contribute a small amount offunds to create and maintain a central data repository?

1 Yes 9 5%

2 No 57 31%

3 Unsure 119 64%

Total 185

Min Value 1

Max Value 3

Mean 2.59

Variance 0.34


Total Responses 185


Statistic Value

27. Are you or your organization familiar with the data collection and analysisservices offered by the Community Advanced Data & Research Analysis (CADRA)Lab of UNLV?

1 Yes 28 15%

2 No 157 85%

Total 185

Min Value 1

Max Value 2

Mean 1.85

Variance 0.13


Total Responses 185


Statistic Value


HEI DemographicsLast Modified: 08/10/2015Filter By: Report Subgroup

1 Male 77 50%

2 Female 74 48%



Total 153

Min Value 1

Max Value 4

Mean 1.52

Variance 0.33


Total Responses 153



Statistic Value



2 21-29 5 3%

3 30-39 36 24%

4 40-49 42 28%

5 50-59 36 24%

6 60 or older 33 22%

Total 152

Min Value 2

Max Value 6

Mean 4.37

Variance 1.35


Total Responses 152


Statistic Value




3 Asian 10 7%





West Indian-Jamaican

mixed

American Indian

adopted, native american mother, also adopted

Min Value 1

Max Value 8

Total Responses 152



Statistic Value









Total 152

Min Value 5

Max Value 7

Mean 6.82

Variance 0.18


Total Responses 152


Statistic Value








9 Retired 0 0%


Min Value 6

Max Value 7

Total Responses 153



Statistic Value


1 Yes 2 100%

2 No 0 0%

Total 2

Min Value 1

Max Value 1

Mean 1.00

Variance 0.00


Total Responses 2


Statistic Value


1 1-10 0 0%

2 11-50 0 0%

3 51-200 1 50%

4 201-500 1 50%

5 500+ 0 0%

Total 2

Min Value 3

Max Value 4

Mean 3.50

Variance 0.50


Total Responses 2


Statistic Value


I don't know

Total Responses 1

Text Response

Statistic Value


1 Yes 77 52%

2 No 72 48%

Total 149

Min Value 1

Max Value 2

Mean 1.48

Variance 0.25


Total Responses 149


Statistic Value


Conference evaluations primarily

economic performance data for state and local regions

school student data

primary data on individuals and families and organizations

Personal and health

Don't know exactly

Age/ ticket purchase/ interests

don't know

experimental, observational, economic indices etc.

We are the Libraries - so we collect data from all kinds of organizations -- NGO, governmental, commercial, our center for gaming research collects data related to gamingindustry

I have no idea. i do not personally collect data about my community, nor is my research about my community, but i assume my university does. However, I have no involvementwith this data.

It would have been helpful if you defined "community data". - we collect data on natural background radiation levels

water quality, air quality, student feedback

Social, professional

assessment evaluations

Assessment scores

educational data from classrooms, school administration, families and educational software

Job placement rates of graduates

K-12 education data (spending, demographics, student performance, etc)

historical records documenting the community

Economic data

Census data, public health data

psychological research data - surveys, attitudes, ability measures

Statistics regarding reference questions, as well as circulation data.

CCSD student achievement and language proficiency data.

health data, public health data, demographic data,

dietary and physical activity level data, physological profile data, geographic information system (GIS) data, and others

quantitative and qualitative data

vulnerable segments of society that have had violent interactions, just starting this with data from records housed in several repositories in S. Nevada

Weather and census

Individual- and dyadic-level data primarily. Individuals' behaviors in relationships, people's knowledge of personal, social, and health, and it's effects on their communicationand relationships.

Probably all kinds since my employer is a university, but I don't specifically know.

Health data, BRFS, Hospital inpatient and outpatient visits in Nevada

information related to infrastructure

health

mental health symptoms and satisfactions ratings

survey data

I don't collect this type of information and I'm not sure what type of data is collected but I work at UNLV so I answered yes to the previous question because I am sure peoplehere collect this type of data.

demographic information, attitudes of community members

Health and behavior assessments

Customer data from local casinos and hospitality establishments

educational needs, social needs

Diversity

data on undergraduate research

Both quantitative and qualitative data

I work for a univeristy so this question is not written well as I don't know all of the data that is collected by the entire org. For my program, I collect BMI, Body fat, substance abusehistory, body image, eating disorders, and other similar data.

Data from fieldwork about populations that I write about.

Demographics

protected health information. treatment outcomes. mental health assessment data

Text Response

both quant and qual data is collected from justice institutions (locally, nationally), individuals (national surveys, local surveys), community members (key players/stakeholders),and local non profits.

clinic outcome data

Demographics, educational readiness, educational preferences

Total Responses 52

Statistic Value


Strategic planning

For research in economic development, demographic and labor market analysis

Research by faculty

We use the data to write peer-review journal articles, issue briefs, reports to funders, and as information for tv and radio interviews.

Providing patient care

i don't collect data but others at the university collect data.

Season selection

don't know

testing hypotheses, building models and validating theories (if not capable of falsifying yet)

making available to users

See above.

research

Analysis of data, report and journal article writing

Research

assessment

Monitor development and progress

educational research

To determine the best way to help graduates obtain jobs

research

to support research and education

Analysis

Public health research and practice

metrics

psychological research

Internal uses (resource allocation, etc.)

Program evaluation and research

To analyze the health of a population (local - Clark County, state, national and international)

Data is used to increase improve measurement methodology, evalution intervention outcomes and public policy, and greater understanding of associations between humanbehavior, personal charateristics, environment and health outcomes.

program evaluation

research

Used for local research project re: homeless population

Basic and applied research

Education and academic research.

Research

sustainable community planning and design

research and student projects

to monitor treatment outcomes and satisfaction of client-therapist relationships

peer reviewed research, policy reports

See above comment.

research on attitudes regarding a number of issues, including sense of community and belonging, sexuality issues

Demonstrate evidence-based practice; reporting; publications

Journal articles

Develop programs, interventions

To identify needs for better and more encompassing programs

developing undergraduate research program

Primarily research and for some evaluation and performance improvement

needs assessments, write journal articles

To write books and articles.

Planning

research, treatment planning, evaluation

research, publication, presentations at the local and national level.

Text Response

improve quality of services, demonstrate value of organization

Financial Aid, Grants, State.Regents Reporting, Academic Scheduling, Registration.

Total Responses 53

Statistic Value


3 Unsure 9 16%

2 No 15 26%

1 Yes 34 59%

Total 58

Min Value 1

Max Value 3

Mean 1.57

Variance 0.57


Total Responses 58


Statistic Value


1 Yes 43 75%

2 No 7 12%

3 Unsure 7 12%

Total 57

Min Value 1

Max Value 3

Mean 1.37

Variance 0.49


Total Responses 57


Statistic Value


1 Yes 34 59%

2 No 4 7%

3 Unsure 20 34%

Total 58

Min Value 1

Max Value 3

Mean 1.76

Variance 0.89


Total Responses 58


Statistic Value



2 No 21 40%

Total 53

Social science librarians to curate data

Need to have data warehouse for local regions

sometimes school district will not share

More comprehensive detail

analytical tools and supports from experts (statistics)

we have no campus plan for who is collecting what data for which purpose and how to apply metadata to it to make it discoverable --

not applicable

we need to learn how to do principle component analysis

it seems random

high quality data about students, at the student level, is difficult to get (validity, missingness)

The data are publicly available but need to be integrated into an easily usable, single database

small sample size, linking individual data to census data

Use of statistical programs and tools would help analyze the data we collect and give it more impact on our policies and practices.

Greater capacity to collect supplemental data from students.

Greater sharing of data between the different health departments in the state

the word "improve programming" is unclear. It assumes a program is already in place and the data is for improvement. Initially I though you were asking about establishing acomputer program. Some of the data I collect is directly related to evaluation of an exiting intervention while other data is exploring the need, evaluating hindrances andenhancers for a successful interventions, and measuring program outcomes.

We are beginning to explore systems mapping and are looking for tools to help with that

Training on analysis, planning phase of assessment needs help as well

At the unit/department level, more information about our students would be helpful (e.g., numbers, progression, when they register, etc.). For academic research, having datafrom non-college student population would be very valuable.

Hospital emergency room wait times

there needs to be a broader base of independent and high quality research related to physical and social measures of resilience

I do not have any project that collecting the community data so I don't have these information. There are some faculties in my school that do but I do not know what they aredoing.

better facilitation of research by university of IRB

response rates

The survey research center we have used in the past was not as efficient as we would have liked.

Greater community collaboration efforts

We need to do a better job collecting performance data on our students.

Zip code & county level data

data storage is always a problem

mixed methods, qualitative methods, and higher statistical analysis training

Min Value 1


Yes (explain):

Statistic Value

Max Value 2

Mean 1.40

Variance 0.24


Total Responses 53


1 Yes 28 52%

2 No 18 33%


Total 54

Min Value 1

Max Value 3

Mean 1.63

Variance 0.54


Total Responses 54


Statistic Value


1 Yes 112 87%

2 No 17 13%

Total 129

Min Value 1

Max Value 2

Mean 1.13

Variance 0.12


Total Responses 129


Statistic Value


1 Data collection is important to my organization. 3.45% 0.00% 13.79% 15.52% 67.24% 58 4.43

2 I am satisfied with my organization's data practices. 5.26% 10.53% 31.58% 43.86% 8.77% 57 3.40

Min Value 1 1

Max Value 5 5

Mean 4.43 3.40

Variance 0.95 0.96






1 0 12 11%

2 1-2 38 35%

3 3-5 23 21%

4 5-10 12 11%

5 10+ 23 21%

Total 108

Min Value 1

Max Value 5

Mean 2.96

Variance 1.77


Total Responses 108


Statistic Value


1 0 27 25%

2 1-2 44 41%

3 3-5 20 19%

4 5-10 2 2%

5 10+ 15 14%

Total 108

Min Value 1

Max Value 5

Mean 2.39

Variance 1.62


Total Responses 108


Statistic Value






Total 101

there is OSR, but nothing specific to our department

I do it all.

Self

Self

I write them myself, or as a Co-PI with another faculty member

All of the above.

Don't know

I write the major grants that support my lab. My students and post-docs write for fellowships or other small grants.

we each write them ourselves

Self

ourselves, though we have support from office of sponsor program for the formatting etc.

no help

Self

existing staff

individuals write their own grants

myself

I write the grants myself, in partnership with either community partners or other UNLV faculty

I did it myself

I've only applied for one particular grant which has a fairly simple process. No resources have been needed.

We use our own resources and personnel.

not sure

my own data based on my work

Ourselves

sponsored programs

myself

myself

I write the grants

we do it

I wrote them myself

Faculty write grant applications themselved

Do it myself.

We write the grants ourselves

All of the above



Individuals apply for grants and write those

research support staff

I write them myself. The only needed resources are preliminary results from my laboratory, and references from journals obtained through the library.

some employees and some colleagues outside of unlv

Workshops

My colleagues and I write our proposals

Professors write their own grant applications

graduate research assistant

All of the above

I do it

i write my grants

I write the grants

Me

Min Value 1

Max Value 4

Mean 2.68

Variance 1.68


Total Responses 101

Statistic Value




3 Surveys 68 55%





read legal decisions

i cannot answer this question.

NASA multispectral imagry

Hand collection of publicly available data.

Secondary data and administrative data gathered primarily by governmental organizations

administrative data

focus groups

Instruction assessment/assignment samples

All of the above

ethnography

ethnographic interviews

video data

Min Value 1

Max Value 7

Total Responses 124



Statistic Value


Academic papers only

psychopathy, depression, personality, emotion

sexuality, parenting, fertility

Conferences

economic development, demographic analysis

Mental health

Educational

Topics related to Teaching and Learning

mental health, behavioral health, integrated health care, caregiving,

None

Infrastructure health, environmental conditions, water quality, weather, seismic activity, and many others

Health disparities

Not sure

developmental genetics in model organisms

Various medical conditions

Theater

everything, that's why we are called a UNVERSity

human movement

Bioinformatics

social phenomena

dispute resolution, psychology

education, market data on prices, demand and others. cost data

Pain and spinal manipulation

we collect data for our own faculty research -- and we collect data for UNLV faculty and the community to use for their own research...... all kinds of topics - our research ismostly in gaming -- student learning -- library use and impact ..

I collect data on my field (medieval history). my university collects data on many diverse topics.

geology, physics

air quality, water quality, student feedback

Linguistic needs

none that i know of

Auditor and client communication, Auditor judgment and decision making

motivation, cognition, metacognition, and student demographics as they influence learning outcomes

K-12 Education, government funding of public services (e.g. Criminal justice, juvenile services, social services)

health care

student use of technology

Firm-Level and Intra-Firm Level Data; business formation, performance, social dynamics, behaviors, goal development, strategy, etc.

Economic research

student progress

Health

medical and dental treatment

Microviology

decision making, memory, perception, attitudes/opinions, prior experiences

Varies

K-12 literacy and English language proficiency

health, public health, health disparities

The majority of data is related to research methodology, epidemiology, physiology, public policy, and intervention outcomes.

engineering

Almost all our projects depend on some type of data creation or colletion and analysis.

Biochemistry

responsible environmental behavior, public understanding of science

interpersonal violence, repeated violent interactions, health consequences of nonlethal violence

Text Response

radiochemistry, environmental chemistry, geochemistry

Satisfaction, useability research, impact of service

Economic development, entrepreneurship, social enterprise

Communication behaviors, health, relationships,

human cognitive processes

related to project management and performance

Special education, teacher preparation, autism, counselor education, teaching english language learners, early childhood education

Information literacy instruction; library material, facility, and service use; S. NV community history; gaming

Health care access and quality; public health, community health

Topics related to dentistry

issues related to sustainability, urban design and planning

Legal and social

materials chemistry

psychotherapy treatment outcomes

quality of life, crime, community policing, sustainability, sexual commerce, aging and health

social issues

the effects of epistemological beliefs on learning and cognition

geology, earthquakes

health status, health behaviors, risk factors, characteristics of investigators pursuing health research

I am currently researching faculty governance at universities throughout the world

a wide variety of questions regarding social issues such as sexuality, sexual commerce, sex trafficking, attitudes to community, aging, safety, policing, culture, economics & jobs

Student progression, graduate programming

I do not collect data for research.

journalism and media studies

Health; childhood obesity; substance abuse; rural health; nutrition; physical activity

customer behavior

education, special education, early childhood education, English Language Learners, Mental Health, Addictions

science education

Psychology-related areas

undergraduate research

mainly nonprofit and government organizations and student performance data

too many to list for department; nutrition, substance abuse, physical activity, body image, eating pathology for my program

Topics in cultural anthropology.

mental health

Thinking and attitude patterns of K-16 students and UNLV professors.

crime, policing, violence, perceptions of the three, justice system responses to the three, reentry, etc.

my area of research is second language acquisition

Gaming, impact of gaming, hospitality related issues

movement

Sports Related Injuries

Education

Appointment

Rely on institutional research.

neuropsychology, mental illness, substance abuse

Total Responses 94

Statistic Value


1 Yes 63 53%

2 No 56 47%

Total 119

Min Value 1

Max Value 2

Mean 1.47

Variance 0.25


Total Responses 119


Statistic Value


1 Yes 80 67%

2 No 40 33%

Total 120

Min Value 1

Max Value 2

Mean 1.33

Variance 0.22


Total Responses 120


Statistic Value


1 Yes 4 3%

2 No 41 34%

3 Unsure 75 63%

Total 120

Min Value 1

Max Value 3

Mean 2.59

Variance 0.31


Total Responses 120


Statistic Value


1 Yes 17 14%

2 No 104 86%

Total 121

Min Value 1

Max Value 2

Mean 1.86

Variance 0.12


Total Responses 121


Statistic Value


NPO DemographicsLast Modified: 08/10/2015Filter By: Report Subgroup

1 Male 12 28%

2 Female 31 72%



Total 43

Min Value 1

Max Value 2

Mean 1.72

Variance 0.21


Total Responses 43



Statistic Value



2 21-29 5 11%

3 30-39 6 14%

4 40-49 13 30%

5 50-59 13 30%

6 60 or older 7 16%

Total 44

Min Value 2

Max Value 6

Mean 4.25

Variance 1.49


Total Responses 44


Statistic Value




3 Asian 2 5%





White/Native American

Min Value 1

Max Value 7

Total Responses 44



Statistic Value









Total 44

Min Value 2

Max Value 7

Mean 5.11

Variance 1.54


Total Responses 44


Statistic Value








9 Retired 0 0%


Min Value 6

Max Value 7

Total Responses 44



Statistic Value


1 Yes 42 98%

2 No 1 2%

Total 43

Min Value 1

Max Value 2

Mean 1.02

Variance 0.02


Total Responses 43


Statistic Value


1 1-10 13 30%

2 11-50 12 28%

3 51-200 10 23%

4 201-500 5 12%

5 500+ 3 7%

Total 43

Min Value 1

Max Value 5

Mean 2.37

Variance 1.52


Total Responses 43


Statistic Value


I don't know

100,000 plus

$1,600,000

0

6,000,000

9 million

1,400,000

$1,000,00-2,000,000

2,475,000

$200000

$500,000

150,000

250000

7,000,000

$1.5 million

1,000,000

$1.2 million

11 million+

800000

13,500,000

$2,000,000

Not sure

$200,000 plus

1,000,000

$12,000,000

$85,000

$28M

$12,000,000

1.3

1,000,000

$3,000,000

1- 1.3 million

Unknown

$2 million

1,500,000

$450,000

$10,000,000

1,3000,000

$30M

Total Responses 39

Text Response

Statistic Value


1 Yes 29 69%

2 No 13 31%

Total 42

Min Value 1

Max Value 2

Mean 1.31

Variance 0.22


Total Responses 42


Statistic Value


Social economic status of community

Student data (Average Daily Attendance, GPA, Required Parent Conferences, In School Suspensions, Out of School Suspensions)

health and education

program satisfaction, frequency of family reading time

Demographics of zip codes and counties

Ticket holder information, Ed Outreach demographic information

impact at schools

referring agency, client's name, age, zip code, marital status, ethnicity, language spoken, infant's gender, DOB, weight, items needed

demographic, grant and program goals, trends, etc

Informaiton on families and children

Demographics primary but also frequency of services, distance, benefits assessment

Demographics

user demographics, scholastic improvement, post training employment, web traffic, materials loaned

Demographics

Program Usage by individuals; number of people trained and reached through outreach, demographics including sexual orientation and gender identity

Student homeless population

Job Seeker Data, Job Placement and Training Data

demographic

data on clients served, community service needs,

Quantitative

HMIS

diseases of our patients

Demographics, clients served, most requested services, functioning improvement

Demographic data, socio-economic information, wealth/net worth information

Total Responses 24

Text Response

Statistic Value


For recruitment

Analyzing the impact of our services on the population served, demonstrating the impact of our program to funders and external stakeholders.

response to donors on effectiveness of money given to agencies.

reassessment of programs, grant applications, board knowledge

We use the data to compare our program/work with other programs similar to ours and youth not in any programs

Better planning and targeting of marketing efforts, better programs to at-risk populations

for grants

to track need by zip code, numberr of agency referrals, how many babies are served

Reporting purposes, speaking events, grants, program enhancement, etc.

Grant reports and annual marketing materials

Grant program tracking, short term impacts, policy development and evaluation, awareness raising, collaboration between entities in the network, driver of strategic planning forlong term operations, and forecasting trends

Reports and grants

donor accountability reports, ROI analysis, program evaluation, needs assessments

Grant Applications, Strategic Planning, Donor Solicitation Materials

Benchmarking, to know level of community impact

Need assessment

Assist people find jobs who have disabilities and other challenges to employment

audience and donor analysis

To improve agency and community service systems

Performance management and program improvement

grant reporting

Electronic Medical Records

Evaluating needs in the community, gaps of services, tailor services to population served, grant opportunities

Fundraising and marketing initiatives.

Total Responses 24

Text Response

Statistic Value


1 Yes 16 64%

2 No 7 28%

3 Unsure 2 8%

Total 25

Min Value 1

Max Value 3

Mean 1.44

Variance 0.42


Total Responses 25


Statistic Value


1 Yes 11 44%

2 No 7 28%

3 Unsure 7 28%

Total 25

Min Value 1

Max Value 3

Mean 1.84

Variance 0.72


Total Responses 25


Statistic Value


1 Yes 22 88%

2 No 2 8%

3 Unsure 1 4%

Total 25

Min Value 1

Max Value 3

Mean 1.16

Variance 0.22


Total Responses 25


Statistic Value



2 No 5 21%

Total 24

I would like the data we gather from partner school districts to integrate better into our internal data system.

we are not using our data or data systems to the fullest; lack of training

cost to have verified by 3rd party limited to every 3 - 5 years, only part of puzzle so hard to weed out true impact of programs

Not all people are documented and people move a lot. Not always up to date.

Up to date comparative demographic information would be valuable as well as survey support

working with school district is a challenge - they make it difficult to collect data

The use of Statistical Tools for Measuring Outcomes

tracking inventory

capability to query blind data for meaning statistics

Our own internal ability to produce quality, constumizable GIS maps

Sharpen our data collection practices

Need better data collection tools, methods to analyze data, ways to store data to easily report out information. Currently, we primarily use Excel aside from a few otherdatabases related to fundraising and volunteerism.

Which data was available thru the CCSD

more detail and long term analysis

We could provide additional data about community needs through better (more timely and consistent) analysis.

Ability to share by interfacing with other systems

collecting data on participants that utilize multiple services within the organization

The ability to pull more detailed and specific reports by age disease race gender

Data hygiene and communication between multiple databases.

Min Value 1

Max Value 2

Mean 1.21

Variance 0.17


Total Responses 24


Yes (explain):

Statistic Value


1 Yes 11 44%

2 No 8 32%


Total 25

Min Value 1

Max Value 3

Mean 1.80

Variance 0.67


Total Responses 25


Statistic Value




Min Value 3 1

Max Value 5 5

Mean 4.72 3.00

Variance 0.29 1.25






1 Yes 38 97%

2 No 1 3%

Total 39

Min Value 1

Max Value 2

Mean 1.03

Variance 0.03


Total Responses 39


Statistic Value


1 0 0 0%

2 1-2 0 0%

3 3-5 6 16%

4 5-10 9 24%

5 10+ 23 61%

Total 38

Min Value 3

Max Value 5

Mean 4.45

Variance 0.58


Total Responses 38


Statistic Value


1 0 0 0%

2 1-2 4 11%

3 3-5 8 22%

4 5-10 10 27%

5 10+ 15 41%

Total 37

Min Value 2

Max Value 5

Mean 3.97

Variance 1.08


Total Responses 37


Statistic Value






Total 38

indidual employees for their own area of expertise

Mgmt staff assists grant team

volunteers/board members

Min Value 1

Max Value 4

Mean 1.79

Variance 0.87


Total Responses 38



Statistic Value




3 Surveys 14 37%

4 Experimental 2 5%




third party

online tests, 3rd party evaluation

Unknown

Min Value 1

Max Value 7

Total Responses 38



Statistic Value


Arts

Improving relational capacity to reduce teen pregnancy.

Health, Economic Stability, Education, Community Engagement

Education, wage, job market, immigration

Age, gender, ethnicity, geography, ticket purchasing input, program attendance input, marketing, education

impact school gardens on STEM, health and community engagement at schools

Income, housing, employment, education, health

K-12 Education

animal ownership and advocacy

Headcount of persons who utilize our programs and services

Pediatric cancer

Food insecurity, poverty, distance and service access

educational effectiveness, post training employment, event atrtendance, media utilization

Children stats Annie Casey, NV State, County, City sites, COC's, hospitals, police, anywhere relevant to topic need

Homelessness

Television audiences, community needs, educational needs

Employment Statistics, Job Assistance programs, Veteran population demographics, Job Availability,

numerous

nutrition, employment, homelessness, seniors, health

Unknown

healthcare

marketing trends, purchasing/fundraising trends and demographics

Total Responses 22

Text Response

Statistic Value


1 Yes 27 71%

2 No 11 29%

Total 38

Min Value 1

Max Value 2

Mean 1.29

Variance 0.21


Total Responses 38


Statistic Value


1 Yes 32 86%

2 No 5 14%

Total 37

Min Value 1

Max Value 2

Mean 1.14

Variance 0.12


Total Responses 37


Statistic Value


1 Yes 4 11%

2 No 9 24%

3 Unsure 25 66%

Total 38

Min Value 1

Max Value 3

Mean 2.55

Variance 0.47


Total Responses 38


Statistic Value


1 Yes 7 18%

2 No 31 82%

Total 38

Min Value 1

Max Value 2

Mean 1.82

Variance 0.15


Total Responses 38


Statistic Value


Public Sector DemographicsLast Modified: 08/10/2015Filter By: Report Subgroup

1 Male 6 26%

2 Female 17 74%



Total 23

Min Value 1

Max Value 2

Mean 1.74

Variance 0.20


Total Responses 23



Statistic Value



2 21-29 0 0%

3 30-39 9 39%

4 40-49 9 39%

5 50-59 2 9%

6 60 or older 3 13%

Total 23

Min Value 3

Max Value 6

Mean 3.96

Variance 1.04


Total Responses 23


Statistic Value




3 Asian 2 9%





Min Value 1

Max Value 8

Total Responses 23



Statistic Value









Total 23

Min Value 4

Max Value 7

Mean 5.70

Variance 0.58


Total Responses 23


Statistic Value








9 Retired 0 0%


Min Value 1

Max Value 1

Total Responses 23



Statistic Value


1 Yes 0 0%

2 No 0 0%

Total 0

Min Value -

Max Value -

Mean 0.00

Variance 0.00


Total Responses 0


Statistic Value


1 1-10 0 0%

2 11-50 0 0%

3 51-200 0 0%

4 201-500 0 0%

5 500+ 0 0%

Total 0

Min Value -

Max Value -

Mean 0.00

Variance 0.00


Total Responses 0


Statistic Value


Total Responses 0

Text Response

Statistic Value


1 Yes 18 78%

2 No 5 22%

Total 23

Min Value 1

Max Value 2

Mean 1.22

Variance 0.18


Total Responses 23


Statistic Value


qualitative level (case reviews, user experiences/perceptions) and quantitative, counts of system/ resource use, youth provided services, demographics, duration of servicedelivery etc.

Health and Injury data

The focus of our data collection is education-centric

demographics of all types

Mainly consumer demographics (gender, age, ethnicity, poverty status, etc) and service units

Information on program participants such as age, education level attained, ethnicity, etc.

Ethnicity, Race, poberty level, encounters, type of insurance, per diagnosis e.g. diabetes, prostate cancer, HTN, among others

Chronically homeless individuals/familes, thosed housed and in services, case management services, individual individuals/families that recieve general assistance

Community data, various populations, various demographics

Statistics

Population in zip codes, % of people in those zip codes who live below poverty level, number of childre (birth - 18 y.o.) who live in the zip codes.

Student achievement data

Demographics, employment, barriers to employment, training

Demograhics, eligibility determination and service provision

Resident needs assessments; community demographics;

Total Responses 15

Text Response

Statistic Value


to inform policy development, practice change, budgeting and expenses, resource allocation and system performance.

To Develope, Initiate and evaluate programs

Identify needs of students/famlies attending CCSD at-risk schools

to help the City run more efficiently, targeting who should be targeted so that resources are allocated fairly

Statewide case management system

To track participants in programs and to determine who we should be providing outreach and education/marketing to.

creation of plans and laws

To report to the government, to identify areas of need and create new programs, to apply for new grants.

Grants applications, renewals, county management and elected officials

community and council reporting, State/County/Federal grants, programmatic assessments and measurable outcomes.

To better serve the community

Funding formula for Family Resource Centers

We use data for improvement of instructional practices and strategic decision making

To analyze and evaluate Title I WIA performance - employment and training services

Analysis, monitoring and compliance

Prioritizing new park development; programming choices; capital infrastructure determination etc.

Total Responses 16

Text Response

Statistic Value


1 Yes 13 81%

2 No 2 13%

3 Unsure 1 6%

Total 16

Min Value 1

Max Value 3

Mean 1.25

Variance 0.33


Total Responses 16


Statistic Value


1 Yes 11 73%

2 No 3 20%

3 Unsure 1 7%

Total 15

Min Value 1

Max Value 3

Mean 1.33

Variance 0.38


Total Responses 15


Statistic Value


1 Yes 15 94%

2 No 1 6%

3 Unsure 0 0%

Total 16

Min Value 1

Max Value 2

Mean 1.06

Variance 0.06


Total Responses 16


Statistic Value



2 No 2 15%

Total 13

Many

The number of respondents could be increased

More collection/analysis on the value of services offered

Some is voluntary and if it were required we would have more complete data.

more input/participation

Data sharing agreements

How we capture information using our current databases and registration forms/ templates

Don't know enough about it

current information. Usually the data is several years old.

We are working to collect cleaner data, improve data governance of collected data, improve storage of this data through the use of data warehousing, and improve access todata analysis tools throughout the organization

Access to outside data such as UI wages

Min Value 1

Max Value 2

Mean 1.15

Variance 0.14


Total Responses 13


Yes (explain):

Statistic Value


1 Yes 12 75%

2 No 2 13%


Total 16

Min Value 1

Max Value 3

Mean 1.38

Variance 0.52


Total Responses 16


Statistic Value




Min Value 1 2

Max Value 5 5

Mean 4.44 3.06

Variance 1.06 0.73






1 Yes 17 81%

2 No 4 19%

Total 21

Min Value 1

Max Value 2

Mean 1.19

Variance 0.16


Total Responses 21


Statistic Value


1 0 0 0%

2 1-2 4 25%

3 3-5 6 38%

4 5-10 3 19%

5 10+ 3 19%

Total 16

Min Value 2

Max Value 5

Mean 3.31

Variance 1.16


Total Responses 16


Statistic Value


1 0 2 13%

2 1-2 5 31%

3 3-5 4 25%

4 5-10 2 13%

5 10+ 3 19%

Total 16

Min Value 1

Max Value 5

Mean 2.94

Variance 1.80


Total Responses 16


Statistic Value






Total 16

Sometimes we use a third party

Third party and collateral employees

Min Value 1

Max Value 4

Mean 2.25

Variance 0.87


Total Responses 16



Statistic Value




3 Surveys 12 60%





open houses

Min Value 1

Max Value 7

Total Responses 20



Statistic Value


Biological and evolutionary research

safety of children

Not research oriented

Academic and non-academic needs of CCSD students

Cultural programs

Pariticipation in Higher Education Savings Accounts

various

diabetis, COPD

I collect data on youth, Child Care Subsidy, CACFP, SFSP, populations served, etc.

citizen satisfaction

program satisfaction, training objectives

Total Responses 11

Text Response

Statistic Value


1 Yes 14 70%

2 No 6 30%

Total 20

Min Value 1

Max Value 2

Mean 1.30

Variance 0.22


Total Responses 20


Statistic Value


1 Yes 18 90%

2 No 2 10%

Total 20

Min Value 1

Max Value 2

Mean 1.10

Variance 0.09


Total Responses 20


Statistic Value


1 Yes 1 5%

2 No 5 25%

3 Unsure 14 70%

Total 20

Min Value 1

Max Value 3

Mean 2.65

Variance 0.34


Total Responses 20


Statistic Value


1 Yes 2 11%

2 No 17 89%

Total 19

Min Value 1

Max Value 2

Mean 1.89

Variance 0.10


Total Responses 19


Statistic Value


Appendix B – Qualitative Interview Matrix

QuestionsCommunity Advanced Data &

Research Analysis Project, UNLVUniversity of Washington DataLab UC Berkeley D‐Lab Princeton University Data & Statistical Services (DSS) Lab University of Tennessee Census State Data Center

Ball State University CBER Data Center

Penn State Social Capital Index Minnesota Population Center

1) How long has the program been in operation?

Since April 2015

The D‐Lab opened its doors in April 2013. Prior to opening its doors, there was a fairly lengthy (multi‐year) design process, and the D‐Lab folded in some existing programs that provided and supported data access and research.

50 YearsThe State Data Center program started in 1978 (see above) and the Center for Business and Economic Research (CBER) at UT, Knoxville, has been the lead agency since 1980.

Established in the early 1970s in response to a research initiative by the Cooperative State Research Service‐‐USDA (Title V of the Rural Development Act of 1972 added extension activities to the Centers' function.) The Northeast Center was moved from Cornell to Penn State in 1985.

The Minnesota Population Center (MPC) was established in March 2000 by founding collaborators from four colleges: John Adams (Geography); Dennis Ahlburg (Industrial Relations Center); Lynn Blewett (Health Services Research); Deborah Levison (Public Affairs); and Steven Ruggles (History). IPUMS began in 1993. The MPC is an interdisciplinary center hosting new projects and new ideas for individuals who share interest in population funding.

2) What is your focus area? What type of services are available? Who is your main audience?

Grant Writing, Non‐profit Audits, Data Mining

We have foci in training (methods, tools, data, campus resources), consulting (research questions), community‐building (working groups, cross‐unit development meetings), computing infrastructure (local, standard images, cloud), and data (public use, restricted use). We support graduate students (primary audience), faculty, staff, and researchers at centers.

Social science data and statistics though we assist researchers in the sciences and humanities also. Assist researchers with locating appropriate data, preparing restricted data plans, understanding methodology, assist with getting ready for statistical packages, assist with the various statistical packages (Stata, R, SPSS, SAS, Matlab), assist with determining proper statistical methods to use

Our main audience are the data users (of all kinds). The services we provide are to the Census, to our affiliates, and to data users across the state. We provide:•technical assistance on Census data analysis and mapping, •efficient access to Census Bureau data and data products, including timely data summaries, research, and statistical reports, •user‐training workshops and conferences on all aspects of demographic data to a broad range of users, •a State Data Center website (http://tndata.utk.edu), •an E‐newsletter•service as the primary contact for data users who require demographic or economic data for Tennessee, its counties, cities, tracts, blocks and zip code areas. •serves as the official Federal‐State Population Estimates Cooperative representative to the Census Bureau’s Population Estimates Division to include data gathering, estimates review and dissemination.

The Northeast Regional Center for Rural Development believes that small towns and rural places are the basic building blocks of rural society, and, in the context of a global society, they are becoming increasingly complex and multi‐dimensional, resulting in an ever increasing number of public issues needing resolution. The Center recognizes that individuals, the foundation of these rural communities, are capable of growth, development and change, and that rural society can be enhanced by increasing the individual, organizational, and problem‐solving knowledge and skills of its residents. Finally, the Northeast Center believes that creating a shared vision for the future of sustainable communities requires democratic participation.

Focus on Social Sciences & Health and Data

Audience is the University Community ‐ Students, Faculty

3) Who are your internal and external stakeholders? Do you have any strategic partnerships? If so, with who? Public or Private?

Internal ‐ Faculty Researchers, Graduate Students

External ‐ Applied Analysis

Internal (campus) stakeholders include the professional schools, Letters & Sciences, campus IT, and the Library. External stakeholders/partners are limited at this time, but include the Census Bureau.

We are a private university. Resources restricted to our own researchers. Informal partnerships with GIS (another part of the library system), Library's Systems Department (they manage and maintain the many servers), Office of Population Research Data Archive (largely informational in terms of acquisitions), and the Center for Health & Well Being Data Archive (we are in the process of taking over all their nonrestricted data)

The TN SDC is a partnership between the State of Tennessee and the US Census Bureau.

The Northeast Center is administered by a joint agreement between USDA and the site institution operating for the Extension Service and the Experiment Station in the region. Major core funding comes from the National Institute of Food and Agriculture (NIFA) ‐ and the region's land‐grant universities. Increasingly, other federal and state agencies, private foundations, and public interests contribute funding in support of special programs

Internal stakeholders include Faculty, Students, and Staff.

External stakeholders inlude US Census Bureau's National Statistical Office

4) How is the program funded? Can you describe your early funding structure?

By writing itself into grants

Initial funding came from four sources: private gifts (used primarily for space renovation), central campus startup funds (3 years), L&S funding (ongoing), and voluntary annual common good support from deans of the professional schools and academic departments.

A regular line in the library budget (staff, software, collections, etc.) Was part of the former Computing Center (now OIT) until 1995 when it moved into the Library.

We are funded through the TN Department of Finance & Administration.

Major core funding comes from the Cooperative State Research, Education, and Extension Service and the region's land‐grant universities. Increasingly, other federal and state agencies, private foundations, and public interests contribute funding in support of special programs.

Infrastructure Projects are federally funded and have an advisory board. Some University funding comes from the Office of the VP for Research.

5) Do you provide assistance in the writing of grants? If so, about how many per year?

Yes, N/AWe provide training and workshops in grant writing directed toward specific funders (e.g. NIH, NSF).

No No YesProgram development grants support for affiliated research. Nearly 30 grants written in 2014.

6) Do you work with the non‐profit community? If so, do you assist them with writing grants?

Yes, Anticipated yes No No No No No

7) What is your program structure? How many staffers? Are they Salaried? Volunteers? Graduate Assistants?

Several Faculty at UNLV, Part time employee of local NPO, Graduate Assistants

Staff include a faculty director (part‐time), executive director (full‐time), academic coordinator (part‐time), data archivist (part‐time), IT specialist (full‐time), and applied software/tool developers (2 x part‐time). We also employ graduate student and staff as consultants (approximately 15‐20 per semester, 3‐5 hours/week), workshop presenters (15‐20 per semester), and GSR operational staff (usually 5‐7 half‐time). All are paid.

3 full time librarians; 2 full time statistical consultants; 1/2 FTE support staff member; 40 hours Graduate Assistants per week. All are paid. No volunteers. While not part of DSS, we receive assistance from Systems for server support; time from a high level cataloger for cataloging of microdata; and several other librarians also help with finding data

The Census disseminates data to me and I pass along to the affiliates and/or the public.

There are 19 affiliates in the state of TN (http://tndata.utk.edu/sdcaffiliates.htm) that work with me as a small portion of their regular jobs. I’m not sure if they are paid as an affiliate or if they volunteer for this. I imagine the 19 have different arrangements. They assist me big time! They know what is happening in their respective communities and relay that information to me.

A board of directors is composed of administrators and faculty from the institutions, representatives of NIFA, and the Economic Research Service (ERS) ‐‐USDA, and representatives from public and private agencies and organizations establishes policies and programming emphases.

Staff consists of a program director, four administrative staffers, two postdoctoral scholars, and five graduate assistants.

168 staff ‐ Infrastructure awards by grants, 75 of which are non‐students. (i.e. research staff, software developers)

6‐7 University Funded Employees.

8) What methods are used to raise awareness of your program?

In progressEmail newsletters, departmental mailing lists, participation in meetings and projects, facebook, twitter, website.

We can't keep up with demand so not a lot of promotion. We are very heavily used. We do regular classes.

We have an annual data users conference as well as other workshops across the state to help get data users be more efficient and more aware of what the Census is working on and what data is available. Starting this year, we are pushing social media more than before. We have a TN SDC twitter account, TN SDC facebook account, TN SDC website, TN SDC E‐newsletter, TN SDC listserv, and I’ve got linked in to communicate with other SDC leads. Press releases are another way to get information out. One of the perks of being housed at a University is that we can use the UTK communications department to do a press release when something exciting is released by the Census and tell why it is important/what happened in our state.

Assists Northeast states in responding to rural development needs.Initiates and facilitates workshops and conferences on current rural development issues.Provides grant to support outcome focused activities.Initiates and coordinates networking among rural development partners.Produces and distributes research and educational materials through newsletters, annual reports, other publications, and its web page.

Academic researchers exhibit at special events for professional societies.

Articles get cited using MPC data.

University hosted publicized events and data workshops.

9) How would you assess the data literacy in your community?

Poor, which is why the need was established for CADRA in the first place

Varies – we emphasize openness to researchers at all levels (IOKN2K! – It’s OK Not to Know!) – but it is a big community.

Among the social sciences extremely high. Economics, Finance, Politics and Sociology are extremely quantitative departments. Public policy becoming increasingly so. Sciences less so (largely lab focused); humanities increasing but low.

At the moment, this is hard for me to answer. Since I am new to this job, I am not aware of how data literate the community is. This also depends on what you mean by “community”. Since I’m at a University in a research department, I’m surrounded by very literate folks. Further than that is hard for me to say. I would have a better idea after I get through my first workshop or conference.

We provide workshops and conferences that are designed to aid the community in accessing the data. We are also trying to get the word out that the TN SDC exists as a resource for people to come to with questions.

Must have high data literacy to use interface. Target audience are research staff and student researchers who are familiar with data and queries for the system's interface.

10) What advice or lessons learned would you give to a University beginning implementation of a Community Assessment and Data Analysis lab?

N/A

Build partnerships with faculty and listen to their needs. Rely on graduate students heavily – they are more in tune with needs and frustrations, they are eager to help other graduate students, they bring lots of energy, and they have networks you can use for offering and building services around. Don’t reinvent wheels – collaborate with campus partners. Build in feedback and evaluation mechanisms while building your program. Create buzz, but try not to over‐promise. Accept failures, learn, cut your losses and move on.

Focus on your actual university not the trends out there. Don't jump on band wagons without seeing what is really needed. Have subject experts that understand the actual fields they represent (economics, politics, sociology, etc.). Don't expect one person to know all data content and multiple statistical packages. Take advantage of graduate students knowledge. Attend the biennial summer workshop at ICPSR on managing a social science data service.

N/APay attention to mission. Pay what is necessary for quality employees. Trickle‐up good ideas. Take energy and successes and build off of them.

11) How do you measure data needs and type of data needed?

Via customers and clients that request CADRA services

By working directly with students and faculty. By being an expert in one's subject area to know what is out there and possible.

We keep a record of the data requests that come in. The affiliates also keep me informed with what people need in their communities.

Based on grants received and professional research staff needs.

Qualitative Interview Comparison Matrix

CADRA Project - Program Evaluation Final Report 2015

Documents

Transcript of CADRA Project - Program Evaluation Final Report 2015