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Programming can be an emotional experience, particularly for undergraduate students who are new to computer science. While researchers have interviewed novice programmers about their emotional experiences, it can be difficult to pinpoint the specific emotions that occur during a programming session. In this paper, we argue that electrodermal activity (EDA) sensors, which measure the physiological changes that are indicative of an emotional reaction, can provide a valuable new data source to help study student experiences. We conducted a study with 14 undergraduate students in which we collected EDA data while they worked on a programming problem. This data was then used to cue the participants’ recollections of their emotions during a retrospective interview about the programming experience. Using this methodology, we identified 21 distinct events that triggered student emotions, such as feeling anxiety due to a lack of perceived progress on the problem. We also identified common patterns in EDA data across multiple participants, such as a drop in their physiological reaction after developing a plan, corresponding with a calmer emotional state. These findings provide new information about how students experience programming that can inform research and practice, and also contribute initial evidence of the value of EDA data in supporting studies of emotions while programming.
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How Do First-Year Engineering Students’ Emotions Change while Working on Programming Problems?
Emotions are a complex multi-faceted phenomenon. To assess the complexity of emotions from different facets, multi-modal approaches are necessary. However, multi-modal approaches are rarely used for assessing emotions, especially in the context of computer programming. This study adopts a multi-modal approach to understand the changes in students’ perception of emotions before and after working on programming problems. Understanding these changes in students’ perceptions may enable educators to devise interventions that help students adjust their perceptions and regulate their emotions as per their skills. We conducted a one-on-one programming session and retrospective think-aloud interview with 17 students from an introductory programming course. During the programming session, students filled surveys and performed four programming tasks. While working on these tasks, students’ eye gaze, video of face and screen, and electrodermal activity data were also collected using a non-invasive device. The data collection for this study was multi-modal, with a mix of both qualitative and quantitative data collection methods. Data analysis was primarily qualitative, with additional triangulation of qualitative and biometric data for select exemplars. The findings of this study suggest that students experience changes in emotions because of many reasons, for instance, they encountered repeated errors, they set high standards for their performance, or they could not manage time. For some students, negative emotions changed to positive emotions when they solved errors without any external help or achieved more than what they expected going into the task. Moreover, the triangulation of qualitative and biometric data of two participants provides a fine-grained analysis of their emotions and behaviors and confirmed the change in the perception of their emotions while performing the programming tasks.
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- Award ID(s):
- 2104729
- PAR ID:
- 10627664
- Publisher / Repository:
- ACM
- Date Published:
- Journal Name:
- ACM Transactions on Computing Education
- Volume:
- 24
- Issue:
- 2
- ISSN:
- 1946-6226
- Page Range / eLocation ID:
- 1 to 30
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1145/3643865
