Examining Students' Academic Motivation for Studying Programming Languages

Autor/inn/en	Ankora, Carlos; Bolatimi, Stephen Oladagba; Bensah, Lily; Mahama, Francois; Kuadey, Noble Arden; Adu, Adolph Sedem Yaw; Adjei, Laurene
Titel	Examining Students' Academic Motivation for Studying Programming Languages
Quelle	In: Journal of Computer Assisted Learning, 39 (2023) 6, S.2025-2034 (10 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Ankora, Carlos) ORCID (Kuadey, Noble Arden)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0266-4909
DOI	10.1111/jcal.12862
Schlagwörter	College Students; Student Motivation; Course Selection (Students); Programming Languages; Computer Software; Career Choice; Learning Motivation; Measures (Individuals); Prior Learning; Control Groups; Work Experience; Occupational Aspiration; Academic Motivation Scale + Suchen Sie Ihr Suchwort? Collegestudent; Schulische Motivation; Course selection; Student; Students; Kurswahl; Motivation for studies; Lernmotivation; Messdaten; Vorkenntnisse; Employment experience; Job experience; Occupational experience; Berufserfahrung; Berufsneigung; Berufsziel
Abstract	Background: The degree to which Computer Science (CS) and Information Communication Technology (ICT) students are motivated to learn greatly impacts their study habits, academic achievement in school and ultimately their job prospects. In recent times, skills in programming languages have become vital in searching for employment. Objective: This study sought to examine the academic motivation of students to study programming languages and their pursuit of job prospects in the software development field. Methods: The study adopted the Academic Motivation Scale (AMS) to measure students' motivation. Data was collected from 244 CS and ICT students at different levels of study at Ho Technical University (HTU) who responded to an online questionnaire. Exploratory factor analysis (EFA), reliability analysis, independent samples t-test and confirmatory factor analysis (CFA) were conducted using IBM statistical package for social sciences (SPSS) and IBM analysis of moment structure (AMOS), respectively. Results and Conclusions: The results showed no significant difference in students' motivation to study programming languages in the university between those who had prior programming languages and those who had none. Also, the results showed no significant difference in the motivation of students to study programming languages between those with and without working experience. The results showed a significant difference between those who want to and do not want to pursue a career in software development and their study motivation of programming languages. Takeaway: Course instructors should emphasize connections between course goals and future employment opportunities. (As Provided).
Anmerkungen	Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01