Revisiting Self-Efficacy in Introductory Programming

Steinhorst, Phil; Petersen, Andrew; Vahrenhold, Jan

Forschungsartikel in Sammelband (Konferenz) | Peer reviewed

Zusammenfassung

For many years, the C++-based Computer Programming Self-Efficacy Scale by Ramalingam and Wiedenbeck has been the de facto standard for assessing self-efficacy in introductory programming. Since the development of this instrument, however, both the landscape as well as the intended audience of introductory programming courses has changed beyond the use of a particular programming language. We revisit this instrument and its factorization in light of curricular developments and research results regarding concepts and competences taught in introductory courses. We report on the development and validation of a new instrument that covers most paradigms and languages used in CS1 and present exploratory and confirmatory factor analyses across different populations. Our validation and factor analyses suggest that the new instrument indeed measures self-efficacy with an acceptable fit of the model. In contrast, the factorization of the Computer Programming Self-Efficacy Scale was found to be less robust. Nonetheless, and in line with self-efficacy theory, our analyses suggest that researchers should take into account the educational context of the study population when reporting or comparing results at the level of factors.

Details zur Publikation

Herausgeber*innenRobins, Anthony V.; Ko, Amy J.
BuchtitelICER '20: Proceedings of the 2020 ACM Conference on International Computing Education Research
Seitenbereich158-169
VerlagACM Press
ErscheinungsortNew York, NY
StatusVeröffentlicht
Veröffentlichungsjahr2020
Sprache, in der die Publikation verfasst istEnglisch
KonferenzICER '20: International Computing Education Research Conference, Dunedin and Virtual Event, Neuseeland
ISBN978-1-4503-7092-9
DOI10.1145/3372782.3406281
Link zum Volltexthttps://dl.acm.org/doi/10.1145/3372782.3406281?cid=99659571006
StichwörterSelf-efficacy; Introductory Programming; Factor Analysis

Autor*innen der Universität Münster

Steinhorst, Phil
Professur für Praktische Informatik (Prof. Vahrenhold)
Vahrenhold, Jan
Professur für Praktische Informatik (Prof. Vahrenhold)