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Developing a Cross-Cultural Model of Problem Solving: Comparing U.S. and Indian Engineering Undergraduates

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Conference

2012 ASEE International Forum

Location

San Antonio, Texas

Publication Date

June 9, 2012

Start Date

June 9, 2012

End Date

June 10, 2012

Conference Session

Track 1 - Session 2 - Student Development

Tagged Topic

Track 1 - Student Development

Page Count

7

Page Numbers

17.16.1 - 17.16.7

DOI

10.18260/1-2--17071

Permanent URL

https://peer.asee.org/17071

Download Count

76

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Paper Authors

biography

Roman Taraban Texas Tech University

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Roman Taraban is a Professor in the Department of Psychology at Texas Tech University. He received his Ph.D. in cognitive psychology from Carnegie Mellon University. His interests are in how undergraduate students learn, and especially, how they draw meaningful connections in traditional college content materials. This research was conducted as part of a Fulbright-Nehru Research Award.

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Abstract

Developing a Cross-Cultural Model of Problem-Solving: Comparing U.S. and Indian UndergraduatesEngineering educators have provided a number of useful didactic models for teaching problemsolving, but there are few cognitive models that show how mental processes change as studentsbecome skilled problem solvers in their area of training. The goal of this research was to assessexpert thinking in undergraduates and to contribute to teaching practices. One way to distinguishbetween expert and novice problem solvers is in terms of how they reason about a problem,particularly early in the solution. Expert solvers create an accurate and detailed mental modeland use this to strategically select equations to solve the problem. We refer to this process asforward inferencing. Novice solvers follow a stereotypical algebraic approach. To date, there isessentially no evidence in published studies that undergraduates reason like experts when solvingproblems. Finding evidence that undergraduates could reason like experts would establish i) ameans of assessing problem-solving skill and ii) a useful pedagogical benchmark for engineeringcurricula.The participants in this study were 26 engineering students enrolled in Mechanics I at an IndianInstitute of Technology (IIT). The comparison sample consisted of 23 engineering studentsenrolled in Mechanics I at a private Institute of Technology in India (private-India) and 27engineering students enrolled in Mechanics I at a large public university in the U.S. (public-U.S.). The private-India and public-U.S. institutions were roughly comparable in terms ofnational standings in engineering training. The IIT was one of the very best engineering institutesin India. Because of the quality of students and training at the IIT, we predicted that thesestudents would reason like experts. Volunteer students were recruited through course instructors.They met individually with the experimenter for approximately one hour to solve three problemsin statics and were asked to say what they were thinking as they solved the problems (think-aloud method). Video recordings and paper solutions were used to analyze performance.The findings confirmed the prediction that IIT students would demonstrate forward inferencingand, consistent with the published literature, the private-India students showed no evidence offorward inferencing. Surprisingly, public-U.S. students applied forward inferencing asfrequently as IIT students. In terms of accuracy across all problem solutions, IIT students weresignificantly more accurate than private-India or public-U.S. students; the latter two did notdiffer.This study contributes four crucial elements to engineering education. 1) Detailed analyses of thethink-aloud data and video recordings provide a model of how students might transition fromfollowing stereotypical (habitual) problem-solving strategies to reasoning like experts aboutproblems. 2) The experimental methodology provides an objective and useable method to assessproblem-solving skill levels in students. 3) The evidence for forward inferencing provides a“proof of concept” that contests the currently accepted claim that undergraduates cannot reasonlike experts and establishes an attainable benchmark for engineering curricula. 4) The alignmentof public-U.S. with IIT students on forward inferencing, but with private-India on overallaccuracy, suggests that instructors and curricula make a difference in how students reason andperform. Finally, forward inferencing matters because it is important for students to reasondeeply about problems rather than applying superficial algebraic methods to reach a solution.Table 1. Percent Accuracy Across All Problem Solutions, Percent Application of ForwardInferencing, Mean Grade-Point Averages (GPA). (Percents adjusted for differences in GPA arein parentheses). Institutions Overall Problem Application of GPA (10-point scale) Solution Accuracy Forward Inferencing IIT (India) 65% (71%) 23% (25%) 8.20 Private-India 25% (29%) 0% (1%) 8.35 Public-U.S. 38% (30%) 25% (22%) 9.29

Taraban, R. (2012, June), Developing a Cross-Cultural Model of Problem Solving: Comparing U.S. and Indian Engineering Undergraduates Paper presented at 2012 ASEE International Forum, San Antonio, Texas. 10.18260/1-2--17071

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