Emotions and programming learning: systematic mapping

Coto, Mayela; Mora, Sonia; Grass, Beatriz Eugenia; Murillo-Morera, Juan

doi:10.1080/08993408.2021.1920816

Cited by 17 publications

(10 citation statements)

References 63 publications

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“…One major contribution of this study is that it provides fine-grained understanding of the emotions that students experience as they work on a programming task, and the reasons they provide for experiencing those emotions, which most literature does not explain. Similarly, most literature on emotions in the context of programming focuses on frustration [26]. This study provides an understanding of other emotions (e.g., shame, pride) during programming tasks and the nuanced reasons why they experience those emotions.…”

Section: Discussionmentioning

confidence: 92%

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A Qualitative Study of Emotions Experienced by First-year Engineering Students during Programming Tasks

Atiq

Loui

2022

ACM Trans. Comput. Educ.

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In introductory computer programming courses, students experience a range of emotions. Students often experience anxiety and frustration when they encounter difficulties in writing programs. Continued frustration can discourage students from pursuing engineering and computing careers. Although prior research has shown how emotions affect students’ motivation and learning, little is known about students’ emotions in programming courses. In this qualitative study of first-year engineering students taking an introductory programming course, we examined the emotions that these students experienced during programming tasks, and the reasons for experiencing those emotions. Our study was grounded in the control-value theory of achievement emotions. Each research participant came to two laboratory sessions: a programming session and a retrospective think-aloud interview session. In the programming session, each participant worked individually on programming problems. We collected screen capture, biometrics, and survey responses. In the interview session, each participant watched a video of their actions during the programming session. After every two minutes of viewing, the participants reported the emotions that they had experienced during this two-minute period. We performed a thematic analysis of the interview data. Our results indicate that the participants experienced frustration most frequently. Sometimes they experienced multiple emotions. For example, one participant felt annoyed because she had made a mistake, but she felt joy and pride when she fixed the mistake. To promote student learning, educators should take students’ emotions into account in the design of curriculum and pedagogy for introductory programming courses.

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Section: Discussionmentioning

confidence: 92%

“…Most previous studies identified certain frequently occurring emotions like frustration [8], [10], [26], and patterns of emotions like confusion followed by frustration [11]. Most of these studies focused on the impact of negative emotions (e.g., frustration) on learning outcomes or self-efficacy.…”

Section: Summary and Critique Of Prior Researchmentioning

confidence: 99%

A Qualitative Study of Emotions Experienced by First-year Engineering Students during Programming Tasks

Atiq

Loui

2022

ACM Trans. Comput. Educ.

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“…O presente estudo tem interesse em modelos computacionais que detectam a confusão do aluno durante tarefas de aprendizagem de programac ¸ão de computadores. A confusão é uma emoc ¸ão propensa de ocorrer neste contexto [Bosch and D'Mello 2017, Bosch et al 2013, Coto et al 2021, pois o aluno precisa entender o problema subjacente à tarefa de programac ¸ão, e mobilizar esforc ¸os cognitivos para identificar e relacionar conhecimentos e estratégias de resoluc ¸ão de problemas [Lehman et al 2013, Chi andOhlsson 2005]. Quando o aluno está confuso, ele entra em um estado de desequilíbrio cognitivo, resultante de contradic ¸ões, conflitos ou informac ¸ões erradas apresentadas a ele .…”

Section: Introduc ¸ãOunclassified

O uso de estimativas de conhecimento do aluno em programação de computadores em modelos de detecção da emoção confusão livres de sensores

Kautzmann

Ramos

Jaques

2022

Anais Do XXXIII Simpósio Brasileiro De Informática Na Educação (SBIE 2022)

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Detectar a confusão do aluno permite ao ambiente computacional de aprendizagem realizar ações que ajudem o aluno a regular sua confusão e a se beneficiar dela. O artigo apresenta evidências sobre os efeitos de usar dados sobre estimativas de conhecimento do aluno, além de dados sobre a interação dele com o ambiente, no desempenho de modelos de detecção da confusão do aluno livres de sensores em tarefas de programação de computadores. Modelos de aprendizado de máquina foram treinados com amostras compostas por dados coletados de 62 alunos, durante cinco meses, em turmas de programação. Os resultados apresentaram evidências positivas que suportam a abordagem do estudo. O artigo também descreve cenários onde a abordagem é mais vantajosa.

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“…However, debugging is also exacting and can be difficult for students to learn and challenging for teachers to teach (McCauley et al, 2008;Hennessy Elliott, 2023). For many students, encountering bugs can generate fear and anxiety that can lead to disengagement and the avoidance of computing (Scott & Ghinea, 2013;Coto et al, 2022). Yet, few studies have treated debugging holistically, considering the "inextricable relationship between thinking and emotion" in learning to persevere and handle failure (DeLiema et al, 2020, p. 210).…”

Section: Introductionmentioning

confidence: 99%

“…Traditional debugging pedagogies involve linear strategies to find bugs in code in constrained programming contexts with timely feedback (Silva, 2011;Luxton-Reilly et al, 2018). These approaches only address isolated cognitive aspects of debugging in limited scenarios, failing to address the "emotional toll" (Kinnunen & Simon, 2010;Coto et al, 2022) that debugging may have on learners in open-ended design contexts.…”

Section: Introductionmentioning

confidence: 99%

Is Computational Empowerment Promoted in the Hour of Code? Analyzing Opportunities for Conceptual, Creative, and Critical Engagement in the Design of Introductory Computing Activities

Morales-Navarro

Kafai

Gregory

2022

Proceedings of the 22nd Koli Calling International Conference on Computing Education Research

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Background and Context: While debugging is recognized as an essential practice, for many students, encountering bugs can generate emotional responses such as fear and anxiety that can lead to disengagement and the avoidance of computer programming. Growth mindsets can support perseverance and learning in these situations, yet few studies have investigated how growth mindsets emerge in practice amongst K-12 computing students facing physical computing debugging challenges. Objective: We seek to understand what (if any) growth mindset practices high school students exhibited when creating and exchanging buggy physical computing projects for their peers to solve during a Debugging by Design activity as part of their introductory computing course. Method: We focused on moment-to-moment microgenetic analysis of student interactions in designing and solving bugs for others to examine the practices students exhibited that demonstrated the development of a growth mindset and the contexts in which these practices emerged. Findings: We identified five emergent growth mindset practices: choosing challenges that lead to more learning, persisting after setbacks, giving and valuing praise for effort, approaching learning as constant improvement, and developing comfort with failure. Students most often exhibited these practices in peer-to-peer interactions and while making buggy physical computing projects for their peers to solve. Implications: Our analysis contributes to a more holistic understanding of students' social, emotional, and motivational approaches to debugging physical computing projects through the characterization of growth mindset practices. The presented inventory of growth mindset practices may be helpful to further study growth mindset in action in other computing settings.

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Emotions and programming learning: systematic mapping

Cited by 17 publications

References 63 publications

A Qualitative Study of Emotions Experienced by First-year Engineering Students during Programming Tasks

A Qualitative Study of Emotions Experienced by First-year Engineering Students during Programming Tasks

O uso de estimativas de conhecimento do aluno em programação de computadores em modelos de detecção da emoção confusão livres de sensores

Is Computational Empowerment Promoted in the Hour of Code? Analyzing Opportunities for Conceptual, Creative, and Critical Engagement in the Design of Introductory Computing Activities

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