Emotions and Programming Learning: Systematic Mapping

Autor/inn/en	Coto, Mayela; Mora, Sonia; Grass, Beatriz; Murillo-Morera, Juan
Titel	Emotions and Programming Learning: Systematic Mapping
Quelle	In: Computer Science Education, 32 (2022) 1, S.30-65 (36 Seiten) PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Coto, Mayela) ORCID (Mora, Sonia) ORCID (Grass, Beatriz) ORCID (Murillo-Morera, Juan)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0899 3408
DOI	10.1080/08993408.2021.1920816
Schlagwörter	Programming; Computer Science Education; Psychological Patterns; Emotional Response; Learning Processes; Novices; Student Behavior; Student Motivation; College Students + Suchen Sie Ihr Suchwort? Programmierung; Computer science lessons; Informatikunterricht; Emotionales Verhalten; Learning process; Lernprozess; Student behaviour; Schülerverhalten; Schulische Motivation; Collegestudent
Abstract	Background and context: Emotions are ubiquitous in academic settings and affect learning strategies, motivation to persevere, and academic outcomes, however they have not figured prominently in research on learning to program at the university level. Objective: To summarize the current knowledge available on the effect of emotions on students while they learn to program. We were interested in what emotions have been studied, what kind of tools researchers have used to measure students' emotions, what emotions arise most frequently when students learn to program, and how researchers use this knowledge. Method: A search of academic databases was performed using a search string constructed using PICo as a framework. A group of 29 studies that met the inclusion criteria were analyzed to answer a set of research questions derived from the study objective. Findings: Few studies have been conducted on the influence of emotions on learning programming. Research studies do not address gender differences. Research has been oriented along three main lines (a) determining what emotions are involved in the process of learning to program; (b) determining the behavioral patterns of novice students and how from this behavior their emotions can be identified; and (c) developing intelligent systems that respond adaptively to students' emotions. Implications: The results provide an important foundation for researchers and instructors who are willing to recognize that learning to program generates strong emotions in students and that these emotions influence their learning and academic performance. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01