Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
The Impact of the Usage of Generative AI on Academic Engagement of Students: A Case Study at a College of Education in Ghana
0
Zitationen
4
Autoren
2025
Jahr
Abstract
This study investigated the impact of generative AI usage on academic engagement among students at a selected College of Education in Ghana. The study aimed to examine the kinds of generative AI tools, identify the different ways students utilize these GenAI in their learning, and assess the overall influence on their academic engagement by employing a sequential explanatory mixed-methods design. This design was chosen to provide a comprehensive understanding through both quantitative and qualitative data. Ninety-four students participated in the quantitative phase via purposive sampling and completed a survey examining the types of generative AI tools they use and the effects on their academic engagement. Additionally, twelve students were interviewed to gather in-depth qualitative insights that could not be captured by the survey. Findings Revealed that generative AI positively influences students’ academic engagement and improves their learning environment. It serves as an effective tool to enhance learning and engagement. However, findings from some respondents via qualitative interview reveal that, excessive reliance on generative AI also poses risks by encouraging laziness and overdependence, less creativity and immersive engagement due to easy access to the AI tools, which may affect academic integrity. The implication for this study is that generative AI tools like ChatGPT spark curiosity by offering instant feedback, tailored learning journeys, and interactive experiences that turn complex concepts into manageable insights. The study highlights generative AI as a double-edged tool: while it empowers students with efficiency, creativity, and deeper engagement, it also risks encouraging shortcuts, dependency, and ethical breaches. Ensuring responsible and ethical integration of AI is therefore vital, with academic integrity anchored in fairness, honesty, and originality remaining at the heart of scholarly practice.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.339 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.211 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.614 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.478 Zit.