Unit:
Κατεύθυνση Εκπαίδευση STEM και Συστήματα Εκπαιδευτικών Ρομποτικών ΔιατάξεωνLibrary of the School of Education
Author:
Gkountani Dimitra
Supervisors info:
Στεφανίδου Κωνσταντίνα, Ε.ΔΙ.Π, ΠΤΔΕ, ΕΚΠΑ
Σκορδούλης Κωνσταντίνος, Καθηγητής, ΠΤΔΕ, ΕΚΠΑ
Κατσιαμπούρα Ιωάννα, Επικ. Καθηγήτρια, ΠΤΔΕ, ΕΚΠΑ
Original Title:
Ο ρόλος της Τεχνητής Νοημοσύνης στην Εκπαίδευση και η συνδρομή της στην Εκπαίδευση STEM
Translated title:
The role of Artificial Intelligence in Education and its contribution to STEM Education
Summary:
This paper examines the role of AI in education as well as its contribution to STEM education. More generally, with the rapid development of technology, AI appears to be a powerful tool that enables the transformation of the learning experience. This can happen through adapting teaching to the needs of students, offering continuous feedback and improving their performance through adaptive learning environments.
The paper is divided into five chapters, each focusing on different aspects of INT in STEM education. In the first two chapters, the theoretical concepts necessary for a better understanding of the work are presented, while in the second chapter, the perspectives offered by TN in STEM education are also mentioned.
In the third and fourth chapters, specific AI software is mentioned, which uses adaptive learning systems and analytics tools to offer a personalized learning experience. Also, the educational results and methods of evaluating the effectiveness of TN are mentioned. In the fifth and final chapter, the future developments of AI in education are reported as well as the challenges and ethical issues that have arisen.
In conclusion, the work presents the possibility offered by TN in STEM education, to strengthen it and offer learning solutions to students who have learning gaps, but also the challenges that must be faced in order for its integration to be fair and safe.
Main subject category:
Education - Sport science
Keywords:
Artificial Intelligence, STEM, Education, Challenges, Benefits, Software, Adaptive Learning, Machine Learning, Evaluation, Ethics
