Faculty Lend a Helping Hand to Student Success: Measuring Student-Faculty InteractionsAmber D. Lambert, Ph.D.Louis M. Rocconi, Ph.D.Amy K. Ribera , Ph.D.Angie L. Miller, Ph.D.

Yiran Dong Center for Postsecondary ResearchIndiana University

Outline

0Literature Review

0Current Study

0Methods

0Results

0Discussion

Literature Review

0Student-faculty interactions generally have a positive influence on educational outcomes, such as:0 Cognitive growth and development of college students

(Astin, 1993; Pascarella & Terenzini, 2005)0 Retention (Lau, 2003; Pascarella & Terenzini, 1977)

0Recent researchers have found that not all kinds of interaction have the same impact on student outcomes

Literature Review (cont.)

0 Teaching Clarity0 Refers to teaching methods where “faculty demonstrate a level of

transparency in their approach to instruction and goal setting in an effort to help students better understand expectations and comprehend subject matter” (BrckaLorenz, Ribera, Kinzie, & Cole, p. 2)

0 Positive relationship with various educational outcomes such as student achievement and satisfaction (Hativa, 1998; Pascarella & Terenzini, 2005; Chesebro & McCroskey, 2001).

0 Good Faculty Practices0 Relationship between student and faculty that moves beyond the

formal instruction that takes place during class (Crisp, 2009)

The Current Study

0Main purpose: To explore how to measure student interactions with faculty in a concise way as part of a larger survey.

0 In particular, we are interested in: 0 whether the student-faculty interaction items load onto

two distinct components, 0 if these two components have good measurement

properties, 0 whether these components are good predictors of GPA and

persistence into the second year.

Method: Participants

0Data from the National Survey of Student Engagement (NSSE) 2011 pilot study (NSSE 2.0)

01,006 first-year and 2,578 senior students attending 19 U.S. institutions

0 Institutions represented variety of regions, Carnegie classifications, and enrollment sizes

034% males and 66% females

079% with full-time enrollment status

Method: Measures

0All relevant survey items from the 2011 NSSE 2.0 pilot administration were included in the EFA.

0CFA analyses were done for those items that fell into the student-faculty interactions components.

0For the predicative validity analyses, survey responses were also merged with institution-provided grade-point-average (GPA) and persistence outcome.0 Controls: gender, ethnicity, parental education level, and

prior academic ability (composite SAT and ACT scores)

Method: Analyses

0 A variable was created using a random number generator that put each student into one of two groups.

0 The first group consisting of half of the sample was used to conduct the exploratory factor analyses. 0 Direct oblimin rotation (oblique) used

0 The second half was used in the confirmatory factor analysis. 0 AMOS used to build the model

0 The entire sample was used for the predictive validity analyses.0 Ordinary least squares (OLS) regression models for academic year GPA 0 Logistic regression models for persistence

Confirmatory Factor Analysis: Model-fit Results

Note: Strong model fit is reflected by GFI greater than .85, CFI greater than .90, RMSEA less than .06, and PCLOSE greater than .05.

Model statistics N GFI CFI RMSEA PCLOSE

First-year 306 .999 .999 .0003 .90

Seniors 631 .999 .999 .0140 .93

Path Model for Good Faculty Practices and Teaching Clarity Subscales

Items, CFA Factor Loadings, and Cronbach’s Alphas for First-Year and

Senior StudentsItem FY Factor Loading SR Factor Loading

GFP1 Got to know you and your background .57 .66

GFP2 Taught in ways that encouraged your active participation .71 .86

GFP3 Created an atmosphere conducive to your learning .99 .93

Cronbach’s α .817 .857

TC1 Clearly explained course goals and requirements .66 .78

TC2 Taught course sessions in an organized way .79 .84

TC3 Used examples or illustrations to explain difficult points .76 .83

Cronbach’s α .832 .862

Predicting GPAR2 ΔR2 Beta

First-year

Control Variables .247 -- --

Teaching Clarity .263 .016 .127

Good Faculty Practices .280 .033 .184

Seniors

Control Variables .164 -- --

Teaching Clarity .177 .013 .114

Good Faculty Practices .210 .046 .217

Predicting Persistence

0Those in the middle 50% on Teaching Clarity have 79% greater odds of being retained than those in the bottom quartile of Teaching Clarity

0Those in the top quartile of Teaching Clarity have 53% greater odds of being retained than those in the bottom quartile of Teaching Clarity

0The average persistence rate difference between those in the top and bottom quartile in Good Faculty Practices was 7%

Limitations

0NSSE is limited to those institutions that choose to participate

0Not all of the possible predictors of GPA and persistence were available to us

0Relied on self-reported perceptions of student experiences

Discussion

0These items included in a larger survey serve as a good proxy for student-faculty interactions

0Both the EFA and CFA suggest that these items make two strong scales for teaching clarity and good faculty practices that are also related to one another

0As theorized from the literature, these measures for teaching clarity and good faculty practices also influence students’ GPA and persistence

Discussion (cont.)

0 These results would suggest that the more personal interactions found in the good faculty practices scale, such as got to know you and your background, that are much less likely to be found on course evaluations might be a more important predictor of student success

0 Measures like the short sets of items described previously could provide additional information on some aspects of classroom practices that are not being measured by course evaluations, especially in light of the problems with course evaluations and other assessments of instructor quality

Questions? Comments?

Contact Information

0Amber D. Lambert – email: adlamber@indiana.edu0Louis M. Rocconi – email: lrocconi@indiana.edu0Amy K. Ribera – email: agarver@indiana.edu0Angie L. Miller – email: anglmill@indiana.edu0Yiran Dong – email: yidong@indiana.edu

References0 Astin, A. (1993). What matters in college? Four critical years revisited. San Francisco: Jossey-

Bass.0 BrckaLorenz, A., Ribera, A., Kinzie, J., & Cole, E. (in press). Examining effective faculty

practice: Teaching clarity and student engagement. To Improve the Academy, 31.     0 Chesebro, J. L., & McCroskey, J. C. (2001). The relationship of teacher clarity and immediacy

with student state receiver apprehension, affect and cognitive learning. Communication Education, 50(1), 59-68.

0 Crisp, G. (2009). Conceptualization and initial validation of the college student mentoring scale. Journal of College Student Development, 50(2), 177-191.

0 Hativa, N. (1998). Lack of clarity in university teaching: A case study. Higher Education, 36(3), 353-381.

0 Lau, L. K. (2003). Institutional factors affecting student retention. Education, 124(1), 126–136.

0 Pascarella, E. T., Terenzini, P. T. (1977). Patterns of student-faculty informal interaction beyond the classroom and voluntary freshman attrition. Journal of Higher Education, 48(5), 540-552.

0 Pascarella, E. T., & Terenzini, P. T. (2005). How college affects students(Vol. 2): A third decadeof research. San Francisco: Jossey-Bass.

Introducing Updated NSSE

0Retains NSSE’s focus on diagnostic & actionable information

0New Engagement Indicators0 Academic challenge0 Deep approaches to learning0 Collaborative learning0 Quantitative reasoning0 Experiences with faculty0 Campus environment0 Interactions with diversity

0Modules0New & Updated Items0 Comparisons to Prior-Year Results0 FSSE & BCSSE Updates

Register Now for NSSE 2013(deadline Sept.

25)