When Is Reading More Effective than Tutoring? An Analysis through the Lens of Students' Self-Efficacy among Novices in Computer Science [Konferenzbericht] Paper presented at the 7th Educational Data Mining in Computer Science Education (CSEDM) Workshop, in conjunction with the 13th International Conference on Learning Analytics Knowledge (7th & 13th, Arlington, TX, Mar 13-17, 2023).

Autor/inn/en	Oli, Priti; Banjade, Rabin; Narayanan, Arun Balajiee Lekshmi; Brusilovsky, Peter; Rus, Vasile
Titel	When Is Reading More Effective than Tutoring? An Analysis through the Lens of Students' Self-Efficacy among Novices in Computer Science [Konferenzbericht] Paper presented at the 7th Educational Data Mining in Computer Science Education (CSEDM) Workshop, in conjunction with the 13th International Conference on Learning Analytics Knowledge (7th & 13th, Arlington, TX, Mar 13-17, 2023).
Quelle	(2023), (10 Seiten)Verfügbarkeit
Zusatzinformation	Weitere Informationen
Sprache	englisch
Dokumenttyp	gedruckt; Monographie
Schlagwörter	Computer Science Education; College Students; Self Efficacy; Programming; Interaction; Dialogs (Language); Intelligent Tutoring Systems; Written Language; Achievement Gains; Prior Learning; Educational Strategies; Independent Reading; Scaffolding (Teaching Technique); Novices; Instructional Effectiveness + Suchen Sie Ihr Suchwort? Computer science lessons; Informatikunterricht; Collegestudent; Self-efficacy; Selbstwirksamkeit; Programmierung; Interaktion; Dialog; Dialogs; Dialogue; Dialogues; Intelligentes Tutorsystem; Geschriebene Sprache; Achievement gain; Leistungssteigerung; Vorkenntnisse; Lehrstrategie; Freies Lesen; Unterrichtserfolg
Abstract	Self-efficacy, or the belief in one's ability to accomplish a task or achieve a goal, can significantly influence the effectiveness of various instructional methods to induce learning gains. The importance of self-efficacy is particularly pronounced in complex subjects like Computer Science, where students with high self-efficacy are more likely to feel confident in their ability to learn and succeed. Conversely, those with low self-efficacy may become discouraged and consider abandoning the field. The work presented here examines the relationship between self-efficacy and students learning computer programming concepts. For this purpose, we conducted a randomized control trial experiment with university-level students who were randomly assigned into two groups: a control group where participants read Java programs accompanied by explanatory texts (a passive strategy) and an experimental group where participants self-explain while interacting through dialogue with an intelligent tutoring system (an interactive strategy). We report here the findings of this experiment with a focus on self-efficacy, its relation to students' learning gains (to evaluate the effectiveness, we measure pre/post-test), and other important factors such as prior knowledge or experimental condition/instructional strategies as well as interaction effects. [This paper was published in: "Proceedings of the 7th Educational Data Mining in Computer Science Education (CSEDM) Workshop, In conjunction with The 13th International Conference on Learning Analytics Knowledge (LAK23)," 2023.] (As Provided).
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01