Assessment of a Survey Instrument for Measuring Affective Pathways

Emma Treadway; Kailey Tubbs; Melissa Joan Caserto; Michelle Lee; Jessica E. S. Swenson

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Conference: 2023 ASEE Annual Conference & Exposition
Location: Baltimore , Maryland
Publication Date: June 25, 2023
Start Date: June 25, 2023
End Date: June 28, 2023
Conference Session: Investigating Student Pathways to and through Undergraduate and Graduate Programs
Tagged Division: Educational Research and Methods Division (ERM)
Page Count: 16
DOI: 10.18260/1-2--42328
Permanent URL: https://strategy.asee.org/42328
Download Count: 164

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Paper Authors

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Emma Treadway Trinity University orcid.org/0000-0002-2986-7674

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Emma Treadway received the B.S. degree in Engineering Science from Trinity University in 2011, and her M.S.E. and Ph.D. degrees in Mechanical Engineering from the University of Michigan, Ann Arbor in 2017 and 2019, respectively. She is an Assistant Professor in the Department of Engineering Science at Trinity University.

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Kailey Tubbs Trinity University

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Kailey Tubbs is a sophomore undergraduate student researcher at Trinity University. She is pursuing a B.S. in Engineering Science and is expected to graduate in May 2025. Her previous research includes studies in astrophysics, chemical and biological engineering, and engineering affect and identity. She wants to pursue a future career in aerospace engineering.

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Melissa Joan Caserto University at Buffalo, The State University of New York

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Michelle Lee Trinity University

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Michelle Lee is pursuing a B.A. in Mathematics and a B.S. in Computer Science at Trinity University. They are expected to graduate in 2025, after which they would like to pursue a Ph.D. in Mathematics.

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Jessica E. S. Swenson University at Buffalo, The State University of New York

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Jessica Swenson is an Assistant Professor at the University at Buffalo. She was awarded her doctorate and masters from Tufts University in mechanical engineering and STEM education respectively, and completed postdoctoral work at the University of Michigan

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Abstract

This work-in-progress paper analyzes the emotions that students experience while completing ill-defined complex problems in their engineering courses. Students are asked to make their own modeling decisions, rather than being given those assumptions, as is the case in most textbook problems. There are many approaches they can take, and having to make decisions and assumptions that impact the problem has been found to generate strong emotions.

Goldin’s research on mathematics education (2000) asserts that students tend toward affective pathways while completing problems. An affective pathway is the sequence of emotions that a student goes through while solving a problem. Goldin theorizes that there are two main categories of affective pathways that students fall into: positive pathways and negative pathways. This paper builds on our previous work on the development of a survey instrument to quantitatively measure affective pathways. The survey asked students to drag and drop emotions into the order they experienced them during their problem solving process.

In this study, we sought to improve upon our survey instrument. Based on our previous research, we added several emotions and alphabetized the list to see whether the order of words impacted the reponses. Here, we examine the results from an updated survey question as well as a small set of interviews conducted to investigate how students approach answering the survey question. The survey was sent to six classes at five universities, and interviews were conducted with six students at two of those universities. The interview covered several aspects of the modeling problem, but we are only looking at the interview question that asked the student to think aloud while completing the affective pathways survey instrument.

The main research questions we consider are: 1) What patterns are present in the affective pathways in the survey responses, and how do they compare to previous results? 2) Does the verbal affective pathway described in the interviews differ from the recorded survey response for that student? 3) What additional changes to the survey instrument are suggested by the results from the survey responses and interviews?

Through our analysis of the survey responses, we found that most students feel frustrated at some stage in the process, and their emotions change as they continue from start to finish, which is in line with the findings of the previous version of the survey instrument. We are looking further into if the students turned their frustrations into the positive or negative pathways that Goldin describes. From the interviews, we found most of the verbalized pathways matched what was submitted through the survey instrument. However, there were occasional instances where the submitted and verbalized pathway did not match.

Developing a reliable method for measuring affective pathways will enable future study of why and when positive or negative pathways occur, as well as potential actions that engineering educators can take to help students interrupt negative pathways. Goldin’s work suggests that negative pathways influence students’ global affect, which could impact retention in engineering.

Citation
Format

Treadway, E., & Tubbs, K., & Caserto, M. J., & Lee, M., & Swenson, J. E. S. (2023, June), Assessment of a Survey Instrument for Measuring Affective Pathways Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1-2--42328

TY - CPAPER
AB - This work-in-progress paper analyzes the emotions that students experience while completing ill-defined complex problems in their engineering courses. Students are asked to make their own modeling decisions, rather than being given those assumptions, as is the case in most textbook problems. There are many approaches they can take, and having to make decisions and assumptions that impact the problem has been found to generate strong emotions.

Goldin’s research on mathematics education (2000) asserts that students tend toward affective pathways while completing problems. An affective pathway is the sequence of emotions that a student goes through while solving a problem. Goldin theorizes that there are two main categories of affective pathways that students fall into: positive pathways and negative pathways. This paper builds on our previous work on the development of a survey instrument to quantitatively measure affective pathways. The survey asked students to drag and drop emotions into the order they experienced them during their problem solving process.

In this study, we sought to improve upon our survey instrument. Based on our previous research, we added several emotions and alphabetized the list to see whether the order of words impacted the reponses. Here, we examine the results from an updated survey question as well as a small set of interviews conducted to investigate how students approach answering the survey question. The survey was sent to six classes at five universities, and interviews were conducted with six students at two of those universities. The interview covered several aspects of the modeling problem, but we are only looking at the interview question that asked the student to think aloud while completing the affective pathways survey instrument.

The main research questions we consider are:
1) What patterns are present in the affective pathways in the survey responses, and how do they compare to previous results?
2) Does the verbal affective pathway described in the interviews differ from the recorded survey response for that student?
3) What additional changes to the survey instrument are suggested by the results from the survey responses and interviews?

Through our analysis of the survey responses, we found that most students feel frustrated at some stage in the process, and their emotions change as they continue from start to finish, which is in line with the findings of the previous version of the survey instrument. We are looking further into if the students turned their frustrations into the positive or negative pathways that Goldin describes. From the interviews, we found most of the verbalized pathways matched what was submitted through the survey instrument. However, there were occasional instances where the submitted and verbalized pathway did not match.

Developing a reliable method for measuring affective pathways will enable future study of why and when positive or negative pathways occur, as well as potential actions that engineering educators can take to help students interrupt negative pathways. Goldin’s work suggests that negative pathways influence students’ global affect, which could impact retention in engineering.
AU - Emma Treadway
AU - Kailey Tubbs
AU - Melissa Joan Caserto
AU - Michelle Lee
AU - Jessica E. S. Swenson
CY - Baltimore , Maryland
DA - 2023/06/25
PB - ASEE Conferences
TI - Assessment of a Survey Instrument for Measuring Affective Pathways
UR - https://strategy.asee.org/42328
DO - 10.18260/1-2--42328
ER -