Assessment of a Survey Instrument for Measuring Affective Pathways

This research paper analyzes the emotions that students experience while completing ill-defined complex problems called Open-Ended Modeling 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 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 responses. 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 by having them think aloud while completing it. The survey was sent to six classes at five universities, and interviews were conducted with six students at two of those universities. Through our analysis, we found that most students feel confused or frustrated at some stage, and that 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 whether 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 instances where the submitted and verbalized pathway did not match, suggesting further changes to the question's implementation. 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.