The Classroom Learning Partner Promoting Meaningful Instructor-Student Interactions in Large Classes

Kimberle Koile, Howard ShrobeJessie Chen, Karin Iancu, Michel Rbeiz, Amanda Smith

MIT CS and AI Lab

Overview

• Problem– Personal interaction impossible in large classes

– How to increase interaction for two-way conversation

• Project Goal– Improve student experiences and learning in large classes by:

* supporting the use of in-class exercises

* without overwhelming the instructor

* maintaining student anonymity

• Two months into two year project– Tablet-PC-based system

– corpus of in-class exercises for MIT introductory CS class (6.001)

– design, implementation of system components

Overview (cont’d)

• Planned Evaluation– 3 terms in 6.001 recitations (~25 students)

* how to test in much smaller class than target?

– 1 term in lecture (~150 fall, 300 spring)

* how to test without Tablets for all students?

• Faster learning for others– learn more– learn quickly: less study time => less stress => happier students

Potential Benefits

• Improved learning for struggling students– help with keeping up – formative assessment useful– organizing notes, example problems

CLP combines two active learning approaches:

• Large classes: Personal Response System (PRS)

– Wireless polling system; students use transmitter to submit answers to multiple-choice or T/F questions in class

– Successful in large classrooms

What

• Small classes: Wide variety of in-class exercises– Instructor only has to evaluate small number of answers

2

CLP will let instructors use wide variety of exercises without being overwhelmed

CLP will let instructors use non-multiple-choice exercises

How

Start with existing Tablet-PC-based Classroom Presenter system

• Wireless presentation system, instructor slides displayed on large screen and students’ Tablet PCs

[ R. Anderson, et. al. 2004]

• Student anonymous submission of digital ink answers to exercises [ B. Simon, et. al. 2004]

[ R. Anderson, www.cs.washington.edu/education/dl/presenter/]

[ B. Simon, et. al. 2004]

How (cont’d)

Extend it to work in large classes• Aggregate student answers into equivalence classes

– interpret handwritten text (e.g. number), selected items (e.g. links in a graph)– lay groundwork for matching sketches (a la Magic Paper)

Instructor’s machine

Screen

Students’ machines

Student answers

Extend it to work in large classes• Aggregate student answers into equivalence classes• Display results to instructor (and students)

How (cont’d)

Instructor’s machine

Screen

Students’ machines

Summary

System ComponentsThree components • Instructor authoring tool: create presentation with expected answer type, correct, incorrect answers (plus pointers to additional study

material)

• Interpreter: student ink answers interpreted answers

• Aggregator: interpreted answers equivalence classes and summary of results

Authoring

toolPresentation

repositoryInstructor’s machine

Stud ent’s machine

Ink

interpreter

Answer

repository

answers interpreted answers

Answer

repository

Instructor’s machine

Aggregatoranswers summary

Screen Mock-ups (a la Classroom Presenter)

Instructor Student

Student

Screen Mock-ups (a la Classroom Presenter)

Instructor Instructor

Classroom Learning Partner

?

Problem

AnswerAggregator

Correct AnswerScopingMistake

RecursionMistake

Tablet-PC-equipped Students

Summary