Problem Framing Behavior in Statics and Thermodynamics

John Jackman; Stephen B. Gilbert; Gloria Starns; Mathew Hagge; LeAnn E Faidley

Download Paper | Permalink

Conference: 2013 ASEE Annual Conference & Exposition
Location: Atlanta, Georgia
Publication Date: June 23, 2013
Start Date: June 23, 2013
End Date: June 26, 2013
ISSN: 2153-5965
Conference Session: Thermal Sciences
Tagged Division: Mechanical Engineering
Page Count: 10
Page Numbers: 23.984.1 - 23.984.10
DOI: 10.18260/1-2--22369
Permanent URL: https://peer.asee.org/22369
Download Count: 562

Paper Authors

biography

John Jackman Iowa State University

visit author page

Dr. John Jackman, Associate Professor, Industrial and Manufacturing Systems Engineering at Iowa State University conducts research in engineering education. His work in engineering problem solving has appeared in the Journal of Engineering Education and the International Journal of Engineering Education. He is currently investigating how to improve students’ problem framing skills using formative assessment.

visit author page

author page

Stephen B. Gilbert Iowa State University

biography

Gloria Starns Iowa State University

visit author page

Senior Lecturer, Mechanical Engineering.

Ph.D., Mechanical Engineering, Iowa State University, 1996

M.S., Mechanical Engineering, Iowa State University, 1990

B.S.M.E, University of Kentucky, 1986.

visit author page

biography

Mathew Hagge Iowa State University

visit author page

PhD "Computational modeling of biomass pyrolysis" 2005

Areas of Teaching: Thermodynamics, Power Plants, Freshman Engineering

Actively working on improving student learning by designing class structure/activities that require student understanding to be successful.

Actively working on teaching in a way that uses/develops existing student understanding rather than the traditional method (starting with professor expertise and working backwards) of presenting broad statements important to a field.

visit author page

biography

LeAnn E Faidley Wartburg College

visit author page

LeAnn Faidley is an Assistant Professor of Engineering Science at Wartburg College in Waverly, IA. She teaches the freshman engineering sequence, the mechanics sequence, the design sequence, and materials. She is interested in a number of pedagogical research questions including how students can be helped to better formulate questions, the development of scenario based laboratories, and the use of service based learning in the engineering classroom.

visit author page

Download Paper | Permalink

Abstract

Problem Framing Behavior in Statics and Thermodynamics When engineering students struggle with problems, it usually occurs in the problemframing stage when they are trying to identify the relevant principles and concepts and how theyare related to each other (e.g., a free body diagram, vapor dome graph, state diagram). We areinterested in identifying when students are experiencing difficulty in this problem framing stageso that we can provide meaningful formative assessment in terms of hints that helps themdevelop better problem solving skills. The problem contexts for this study include statics,materials, and thermodynamics. Participants in this study were freshmen (20 students) andsophomore (20 students) undergraduates in engineering (primarily mechanical engineering) atIowa State University and Wartburg College. To identify when students are experiencingdifficulty in problem framing, we collected data on student behavior as they solved problemswith different levels of complexity. We used Smartpens to record students’ writing/sketchingand voice as they used a think-aloud protocol to describe their thought processes. The problemdescriptions and information resources were provided within a web-based problem solvingenvironment, ThinkSpace. Students’ information seeking behavior was captured by recording thecomputer screen. Using protocol analysis, we analyzed student cognitive activities related toreasoning, metacognition, and information seeking so that we could classify the different typesof behaviors. Students and instructors were surveyed on problem complexity for the problem set usinga Likert scale from 1 to 5 (5 being most complex). These results were used to calibrate ourresults so that we could determine any differences in behavior between simple and complexproblems. Instructor results were consistent with student complexity ratings. To characterize thepossible factors that contribute to this complexity, we developed a set of factors based onprevious research and rated each of the problems. Using the complexity ratings, we calculatedthe correlation coefficient between each of the factors and the rating. Five factors had acorrelation coefficient greater than 0.5 and therefore, are likely contributing to problemcomplexity. Our protocol analysis of student cognitive activities during problem solving showedsignificant differences in activities between good and poor performing students. Thesedifferences can be seen first of all in the timing of activities in that poorer performance isassociated with longer and more frequent pauses in student activity. It also appears that thebetter performing student has an integrated set of metacognitive and reasoning activities early onin the process. Poorer performance tends to be linked with limited reasoning activities early inthe problem framing stage. Information seeking occurs after some initial metacognitive andreasoning activities for better performing students. For poor performing students, we observedmore frequent information activities and they typically begin before metacognitive and reasoningactivities.

Citation
Format

Jackman, J., & Gilbert, S. B., & Starns, G., & Hagge, M., & Faidley, L. E. (2013, June), Problem Framing Behavior in Statics and Thermodynamics Paper presented at 2013 ASEE Annual Conference & Exposition, Atlanta, Georgia. 10.18260/1-2--22369

TY - CPAPER
AB - Problem Framing Behavior in Statics and Thermodynamics When engineering students struggle with problems, it usually occurs in the problemframing stage when they are trying to identify the relevant principles and concepts and how theyare related to each other (e.g., a free body diagram, vapor dome graph, state diagram). We areinterested in identifying when students are experiencing difficulty in this problem framing stageso that we can provide meaningful formative assessment in terms of hints that helps themdevelop better problem solving skills. The problem contexts for this study include statics,materials, and thermodynamics. Participants in this study were freshmen (20 students) andsophomore (20 students) undergraduates in engineering (primarily mechanical engineering) atIowa State University and Wartburg College. To identify when students are experiencingdifficulty in problem framing, we collected data on student behavior as they solved problemswith different levels of complexity. We used Smartpens to record students’ writing/sketchingand voice as they used a think-aloud protocol to describe their thought processes. The problemdescriptions and information resources were provided within a web-based problem solvingenvironment, ThinkSpace. Students’ information seeking behavior was captured by recording thecomputer screen. Using protocol analysis, we analyzed student cognitive activities related toreasoning, metacognition, and information seeking so that we could classify the different typesof behaviors. Students and instructors were surveyed on problem complexity for the problem set usinga Likert scale from 1 to 5 (5 being most complex). These results were used to calibrate ourresults so that we could determine any differences in behavior between simple and complexproblems. Instructor results were consistent with student complexity ratings. To characterize thepossible factors that contribute to this complexity, we developed a set of factors based onprevious research and rated each of the problems. Using the complexity ratings, we calculatedthe correlation coefficient between each of the factors and the rating. Five factors had acorrelation coefficient greater than 0.5 and therefore, are likely contributing to problemcomplexity. Our protocol analysis of student cognitive activities during problem solving showedsignificant differences in activities between good and poor performing students. Thesedifferences can be seen first of all in the timing of activities in that poorer performance isassociated with longer and more frequent pauses in student activity. It also appears that thebetter performing student has an integrated set of metacognitive and reasoning activities early onin the process. Poorer performance tends to be linked with limited reasoning activities early inthe problem framing stage. Information seeking occurs after some initial metacognitive andreasoning activities for better performing students. For poor performing students, we observedmore frequent information activities and they typically begin before metacognitive and reasoningactivities.
AU - John Jackman
AU - Stephen B. Gilbert
AU - Gloria Starns
AU - Mathew Hagge
AU - LeAnn E Faidley
CY - Atlanta, Georgia
DA - 2013/06/23
PB - ASEE Conferences
TI - Problem Framing Behavior in Statics and Thermodynamics
UR - https://peer.asee.org/22369
DO - 10.18260/1-2--22369
ER -