Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Lecturer’s Perspective on the Role of AI in Personalized Learning: Benefits, Challenges, and Ethical Considerations in Higher Education
11
Zitationen
2
Autoren
2025
Jahr
Abstract
Abstract This qualitative study explores lecturers’ perspectives on the role of artificial intelligence (AI) in personalised learning within higher education. The rapid proliferation of AI has introduced numerous ethical challenges, including the potential for academic dishonesty and misuse. One concern highlighted in this study is maintaining academic integrity while fostering responsible and ethical AI use in educational contexts. Grounded in the Technology Acceptance Model, the research examines how lecturers navigate these complexities through innovative teaching and assessment strategies. Data were collected from 16 lecturers via open-ended questionnaires, and thematic analysis, guided by Braun and Clarke’s six-step framework, was employed to identify recurring themes. The study is limited in its reliance on self-reported data, which may not fully capture the nuances of lecturers’ experiences or practices. Additionally, the study is context-specific, focusing on a limited sample size, which may restrict the generalizability of the findings to broader contexts. Findings reveal that lecturers employ strategies such as using AI-detection tools like Turnitin to uphold academic integrity, redesigning assessments to include in-class components, and encouraging transparency by having students declare AI use. Another significant finding is the emphasis on fostering critical thinking skills to enable students to engage ethically with AI tools. The study recommends that higher education institutions train lecturers and students on ethical AI use, promote transparency in AI-assisted academic work, and invest in technologies that support these objectives. Revising assessment strategies to incorporate innovative, controlled formats is also suggested to mitigate misuse, ensuring the responsible integration of AI into educational practices.
Ähnliche Arbeiten
Determining Sample Size for Research Activities
1970 · 17.665 Zit.
Scale Development : Theory and Applications
1991 · 14.735 Zit.
Online Learning: A Panacea in the Time of COVID-19 Crisis
2020 · 4.917 Zit.
Systematic review of research on artificial intelligence applications in higher education – where are the educators?
2019 · 4.439 Zit.
Blended learning: Uncovering its transformative potential in higher education
2004 · 4.406 Zit.