AI In Higher Education: Risks and Opportunities From the Academician Perspective DOI
Miray Doğan,

Asena Aslihan Celık,

Hasan Arslan

et al.

European Journal of Education, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 5, 2024

ABSTRACT This research investigates how artificial intelligence (AI) influences higher education, specifically exploring the perspectives of academicians regarding associated risks and opportunities. The study is aimed at implementation AI within university settings its impact on both educators students. Given swift integration AI, notably widespread adoption generative in article emphasises AI's ability to collect detailed data, providing a deeper understanding academicians' learning experiences. This, turn, enables personalised support, allowing respond more effectively students' needs improve overall educational process. Moreover, highlights potential proactively identify students risk failure, offering comprehensive view for effective assessment. On other hand, these advantages growing dependence technology pose challenges, including reduced interaction between students, shifts workforce dynamics, concerns about student privacy disparities access. Acknowledging issues, underscores importance preparing evolving landscape education shaped by AI. It stresses need proactive measures navigate changes effectively, as they are inevitable. findings this significant field provide clear critical assessment transformative advocate effectively.

Language: Английский

Enhancing AI literacy of educators in higher education DOI Creative Commons
Stefanie Schallert,

Charlotte Nüesch,

Konstantin Papageorgiou

et al.

Zeitschrift für Hochschulentwicklung, Journal Year: 2025, Volume and Issue: 20(SH-KI-1), P. 147 - 166

Published: Feb. 27, 2025

As AI becomes integral to students’ learning, educators must adapt this AI-driven landscape. However, there is a notable gap in research focusing on fostering literacy among higher education lecturers. This paper presents design-based project aimed at developing professional development curriculum for the tertiary level through iterative cycles. In first cycle, voluntary internal course was offered as blended learning scenario. Evaluation involved validated performance test and readiness scale items. The results of cycle are going be presented discussed. Based these findings, modifications outlined.

Language: Английский

Citations

0
Von der Hochschule ins Klassenzimmer: Die Rolle der KI in der Lehrer:innenbildung DOI Creative Commons
Nora Cechovsky, Claudia Malli-Voglhuber

Zeitschrift für Hochschulentwicklung, Journal Year: 2025, Volume and Issue: 20(SH-KI-2), P. 143 - 164

Published: Feb. 27, 2025

Künstliche Intelligenz (KI) bietet großes Potenzial für die Tätigkeit als Lehrkraft. Die Lehrer:innenbildung spielt eine entscheidende Rolle dabei, den sinnvollen und verantwortungsvollen Umgang mit KI zu vermitteln. Als Basis zur Weiterentwicklung der hochschulischen Lehre wurde Sicht Studierenden im Bereich Berufspädagogik an einer pädagogischen Hochschule erhoben. Dazu Fragebogenstudie bei 238 durchgeführt. Es Fragen nachgegangen, wie Einsatz von Studium wahrnehmen welche Akzeptanz jene, bereits Schulen tätig sind, in Bezug auf Schule aufweisen. zeigen hohes Interesse, aber auch Unsicherheiten KI. Lehrkräfte stehen positiv gegenüber nutzen sie vorwiegend Unterrichtsvorbereitung.

Citations

0
AI In Higher Education: Risks and Opportunities From the Academician Perspective DOI
Miray Doğan,

Asena Aslihan Celık,

Hasan Arslan

et al.

European Journal of Education, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 5, 2024

ABSTRACT This research investigates how artificial intelligence (AI) influences higher education, specifically exploring the perspectives of academicians regarding associated risks and opportunities. The study is aimed at implementation AI within university settings its impact on both educators students. Given swift integration AI, notably widespread adoption generative in article emphasises AI's ability to collect detailed data, providing a deeper understanding academicians' learning experiences. This, turn, enables personalised support, allowing respond more effectively students' needs improve overall educational process. Moreover, highlights potential proactively identify students risk failure, offering comprehensive view for effective assessment. On other hand, these advantages growing dependence technology pose challenges, including reduced interaction between students, shifts workforce dynamics, concerns about student privacy disparities access. Acknowledging issues, underscores importance preparing evolving landscape education shaped by AI. It stresses need proactive measures navigate changes effectively, as they are inevitable. findings this significant field provide clear critical assessment transformative advocate effectively.

Language: Английский

Citations

0