Literaturnachweis - Detailanzeige
| Autor/inn/en | Dan Kohen-Vacs; Maya Usher; Marc Jansen |
|---|---|
| Titel | Integrating Generative AI into Programming Education: Student Perceptions and the Challenge of Correcting AI Errors |
| Quelle | In: International Journal of Artificial Intelligence in Education, 35 (2025) 5, S. 3166-3184Infoseite zur Zeitschrift
PDF als Volltext |
| Zusatzinformation | ORCID (Dan Kohen-Vacs) ORCID (Maya Usher) |
| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
| ISSN | 1560-4292 |
| DOI | 10.1007/s40593-025-00496-4 |
| Schlagwörter | Forschungsbericht; Artificial Intelligence; Technology Uses in Education; Programming; Computer Science Education; Student Attitudes; Error Correction; Undergraduate Students; Coding; Natural Language Processing; Problem Solving; Intention; Skill Development; Technology Integration |
| Abstract | This paper presents two complementary quantitative studies examining the integration of generative AI (GenAI) tools into programming courses in higher education. Study 1 investigated undergraduate students' perceptions of GenAI tools, focusing on usefulness in coursework, creativity enhancement, behavioral intention to use, and concerns and critiques. Study 2 evaluated undergraduate students' performance in correcting code generated by large language models (LLMs) during programming exams, comparing this performance to their results on instructor-designed programming tasks. Findings from Study 1 revealed generally favorable student perceptions of GenAI. Participants reported medium-to-high levels of perceived usefulness, particularly emphasizing GenAI's potential to enhance learning efficiency and support creative problem-solving. Students also expressed strong intentions to continue using GenAI tools in their studies, while reported concerns were relatively low and centered primarily on the risk of over-reliance. Findings from Study 2 showed that students encountered significantly greater difficulty when correcting LLM-generated code compared to traditional exam tasks, highlighting the unique challenges posed by AI-generated outputs in assessment contexts. Taken together, the results suggest that while students recognize the value of GenAI tools in supporting learning and creative exploration, programming education must also focus on developing students' skills in critically evaluating and correcting AI-generated content to ensure effective and responsible integration. (As Provided). |
| Anmerkungen | Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/ |
| Begutachtung | Peer reviewed |
| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
| Update | 2026/2/04 |
Literaturbeschaffung und Bestandsnachweise in Bibliotheken prüfen
Permalink als QR-Code
Inhalt auf sozialen Plattformen teilen (nur vorhanden, wenn Javascript eingeschaltet ist)
Teile diese Seite:
