Using artificial intelligence to help bridge students from...

IntroductionAcademic ActivitiesAI-centric Curricula

EvaluationConclusion

Using artificial intelligence to help bridge studentsfrom high school to college

Elizabeth Sklar, Simon Parsons, Sheila Tejada, Susan Lowes,M Q Azhar, Samir Chopra, Richard Jansen, and Ira Rudowsky

Dept of Computer and Information ScienceBrooklyn College, City University of New York

Brooklyn, NY 11210 USAPresenter :

M. Q. [email protected]

Elizabeth Sklar, Simon Parsons, Sheila Tejada, Susan Lowes, M Q Azhar, Samir Chopra, Richard Jansen, and Ira Rudowsky Dept of Computer and Information Science Brooklyn College, City University of New York Brooklyn, NY 11210 USA Presenter : M. Q. Azhar [email protected] artificial intelligence to help bridge students from high school to college



Introduction

we will present our work from the Bridges to Computing project atBrooklyn College of the City University of New York

primary target population:hs students who are in transition from high school to collegeundergraduate students

primary project goal:encourage more students to study some aspect of computer science

curriculum development:introduced new undergraduate courses into our computer sciencecurriculum and revised existing coursesdeveloped activities for high school students to help better preparethem for college-level computer science

here, we report on the use of ideas from artificial intelligenceimplemented within several of these interventions




Project Activities

formal training—(traditional course with exams) via context-basedintroductory and interdisciplinary undergraduate courses

1091 studentsupdated 15 sections context-based Undergraduate Courses ( 3 UG(CS0,CS1,CS2) courses * 5 flavors )2 newly developed interdisciplinary courses

Exploring Robotics (CC30.03)Honors Course (SCP50)

informal training—(no exams) through after-school and summerprograms for high school students

mentoring—from high school students to undergraduates tograduate students and faculty

community outreach—to the College community and beyond




Formal Training: Introductory ComputingFormal training: Interdisciplinary ComputingInformal training: Summer InstituteInformal training: Computing Preparatory Course

1 Introduction

2 Academic ActivitiesFormal Training: Introductory ComputingFormal training: Interdisciplinary ComputingInformal training: Summer InstituteInformal training: Computing Preparatory Course

3 AI-centric CurriculaRobotics and AgentsBiologically-inspired SimulationsMulti-agent Games

4 EvaluationPurposeGender and LanguageLessons Learned

5 ConclusionElizabeth Sklar, Simon Parsons, Sheila Tejada, Susan Lowes, M Q Azhar, Samir Chopra, Richard Jansen, and Ira Rudowsky Dept of Computer and Information Science Brooklyn College, City University of New York Brooklyn, NY 11210 USA Presenter : M. Q. Azhar [email protected] artificial intelligence to help bridge students from high school to college




Academic Activities

formal and informal training components of the Bridges project arestructured around five context-based “flavors”, emphasizing theintersection between computer science and:

1 business2 law3 medicine4 graphics5 robotics

the last three flavors (e.g., medicine, graphics and robotics) inparticular have produced curricula that take advantage of AI-basedsolutions





Formal Training: Introductory Computing (CS0)

CS0

part of Brooklyn College “lower tier” core curriculum requirements incomputing and mathematicsapprox. 400-500 students per semestergives students with no computing background an introductory-levelexposure to a cross section of topics within computer science andprovide them with some hands-on experience with computers andprogramminggoal: to increase the number of students who take CS1 aftersuccessfully completing CS0





Formal Training: CS1 and CS 2

CS1: Introductory Computing

first programming course for CS majorsaccording to our survey, students are ill-informed about thedifferences between CS0 and CS1goal: to improve retention of students in CS1 and also increasing thenumber of students who subsequently complete CS2

CS2: Advanced Programming Techniques

second programming course for CS majorstaught in C++, introduces UNIXgoal: to improve retention of students through CS2 and into the restof the computer science major.





Retention: CS1 to CS2





Retention: CS2 to CS3





Formal training: Interdisciplinary Computing

Exploring Robotics

part of the Brooklyn College “upper tier” core curriculum (advancedstudents who have already chosen their major are required to taketwo interdisciplinary courses)

offered first time in Fall 2006 and has proven to be tremendouslypopular.

Fall 2006 Spring 2007 Fall 2007 Spring 200891 89 115 158





Informal training: Summer Institute

two-week free summer program HS (July 2006, July 2007)

recruited students from local public high schools in Brooklyn

approximately 35 students attended each summer

goal: to give students who have limited or no access to computerscience courses in their high schools an opportunity to learn aboutthe field, its broad applications and interdisciplinary nature, and togain hands-on experience with 1-2 technologies

3 “taster” days and 5 “pick” days. During the taster days, studentsattended 5 half-day sessions, one for each of the five Bridges flavors

a showcase was organized during last day:





Informal training: Computing Preparatory Course

in Fall 2006 and Fall 2007, high school students were invited toattend a Computing Preparatory Course after school

give students more in-depth experience with the topics introducedduring the summer

lab-based, so students can work at their own pace

approximately every 6-8 weeks a new topic is introduced, againfollowing the five Bridges flavors

topics covered include: HTML and Javascript, cryptography,simulations using NetLogo, robotics using RoboLab, games usingScratch, Game Maker or Alice




Robotics and AgentsBiologically-inspired SimulationsMulti-agent Games

Robotics and Agents

at all levels, undergraduate and high school, students are introducedto the notion of artificial intelligence through the intelligent agentparadigm

Definition

agent is an automonous entity that exists in some kind of environment,either virtual or physical. It receives inputs through sensors that perceiveproperties of their environment and/or themselves, and it generatesoutput through actuators that effect change on their environment and/orthemselves.

The AI is the part that comes in between receiving input andgenerating output—this is where something intelligent shouldhappen

Students are intrigued by the notion that they can construct sets ofrules that govern the behavior of an agent





Robotics and Agents in HS and CS0

LEGO Mindstorms robots: HS components and the CS0 course.

taught about simple sensor inputs (e.g., light level and bump)

sensors convert physical properties to numeric values – numericvalues as input to a program that emulates intelligent behavior onthe part of their agent

They are given a variety of tasks designed to introduce them to:

the RoboLab1 programming environmentthe design-write-test-debug software development cyclebasic programming concepts such as branching, looping and datastoragebasic computer and robot hardware concepts such as memory, power,sensors and motors

1http://www.ceeo.tufts.edu/robolabatceeo/


http://www.ceeo.tufts.edu/robolabatceeo/




Robotics and Agents in CS1 and CS2

in the CS1 and CS2 courses, students’ exposure to robotics isprimarily through examples and simulated robots (virtual agents),though both classes are given at least one assignment using aphysical robot

Surveyor SRV-12 is currently being used

small, reasonably-priced robot has an on-board web camera and iscontrolled from a laptop via radio communication (see figure 2)

Students are exposed to basic AI concepts, such as state, decisiontrees and search strategies

2http://www.surveyor.com/


http://www.surveyor.com/




Robotics and Agents in CS1 and CS2

an example of a task for a simulated robot is one in which

devise a control algorithm for a robot that can move around in avirtual 2-dimensional grid, using commands such as “left”, “right”,“up” and “down”robot has a fixed amount of “fuel” and expends some of its energywith every commandthe robot’s world is inhabited with randomly placed pieces of“treasure”students’ controllers should maximize the amount of treasurecaptured by the robot before it runs out of energy

this task is assigned in both CS1 and CS2 courses, but theprogramming requirements are different.

in CS1, students use a 2-dimensional array of characters to store therobot’s worldin CS2, students must create several classes to represent the robotand its world





Biologically-inspired Simulations

across all three courses (CS0, CS1 and CS2), the bulk of theexamples that the students work on are agent-based simulations ofsmall biological worlds

deal with simple agent models, and so this work is closer to artificiallife than classic artificial intelligence

In CS0 and the high school components,

use NetLogo3

following the NetLogo exploration period, students are encouraged tocreate their own models

In CS1 and CS2,

the students write the simulations from scratch in C++, and withoutthe support that NetLogo providesstudents produce small ecosystem examples with simple rules guidingthe behavior of the agents

3http://ccl.northwestern.edu/netlogo/


http://ccl.northwestern.edu/netlogo/




Multi-agent Games

Used in CS0

games are an excellent motivational tool for encouraging students atall levels.

provide a method to introduce basic concepts in computer science,programming and artificial intelligence.

For creating games we have adopted the Scratch4, environment inCS0

4http://scratch.mit.edu/


http://scratch.mit.edu/



PurposeGender and LanguageLessons Learned

Evaluation

data collected: pre and post surveys, enrollment data

purpose of the surveys (primarily):1 identify the demographics of the student populations, particularly

focusing on gender, language spoken at home, higher educationobtained by family members

2 determine if students’ perception of the field of computer science,and of computer scientists, changes by participating in interventionsthat are actively interdisciplinary

data presented in the following slide summarizes nearly 500undergraduate and high school students who completed surveysbetween Fall 2006 and Summer 2007





Gender breakdown





Analyzing data

word all bridges word all bridges

smart* -5% 11% solv* 2% 1%educat* -2% -4% patient -1% 5%math* -2% -5% methodical 1% 0%logic* 4% 6% determined 0% -2%program* 1% 3% precise 2% 2%

geek -4% -6% creative -2% -3%anti-social -1% 0% innovative 2% 1%cool 0% 2% interest* 1% -1%boring 1% 0% curious -1% -4%

Table: “Write down 3 words that describe a computer scientist”, undergradSpring’07 and Fall 2007





Lessons Learned!

1 change schedule for high school computing preparatory class

2 considering multi-flavored sections

3 context should be easily explainable

4 some training may be needed in order to adapt such a methodologywidely across a department so that instructors understand how touse lab time effectively

5 hands-on instruction not only has pedagogical gains, but alsosocial gains—faculty get to know students better and vice versaStudents feel less threatened by faculty and view them as moreapproachable.




Integration!!




Can Learning be fun?




Conclusions

goal:broaden the demographic of students participating in computingcoursesfocusing on the introductory level and bridging studentswho are under-prepared in high school into computer science majorcourses in college.

methodology:hands-on cross-disciplinary approach to teachingcontext-basedlab classes at the undergraduate level and after-school programs atthe high school levelcentering on five flavored areas within computer science

AI-centric Curricula:introduced concepts from artificial intelligence within at least threeof these “flavored” areas (e.g., robotics, simulation, and games)engage students early on with problem-solving and understandingthat AI is not just the name of a Hollywood movie!!




Q and A

THANK YOU :-)

CONTACTM. Q. Azhar [[email protected]]

project PI: Prof. Sklar [[email protected]]

WEBSITESproject webstie: bridges.brooklyn.cuny.edu

robotics.edu: agents.sci.brookyln.cuny.edu/robotics.edu


Using artificial intelligence to help bridge students from...

Documents

Transcript of Using artificial intelligence to help bridge students from...