Artificial Intelligence – Enhanced Teacher Evaluation in Open and Distance Education: A Formative Model for Professional Learning

Abstract Book of the 10th World Conference on Future of Education

Year: 2026

[PDF]

Artificial Intelligence – Enhanced Teacher Evaluation in Open and Distance Education: A Formative Model for Professional Learning

Theognosia Kounatidou, Nektaria Sakkoula, Despoina Dionysiou, Georgia Konstantia Karagianni, Antonis Lionarakis

ABSTRACT:

Student evaluation of teaching constitutes a critical component of quality assurance in higher education, particularly in open and distance learning contexts, where supportive relationships and meaningful interaction are key determinants of learning. However, existing evaluation systems in open and distance learning institutions are often confined to quantitative reporting, offering limited potential for improvement and failing to utilize evaluation data as a basis for teacher reflection and professional development. This paper explores how the integration of artificial intelligence tools can support the transformation of teacher evaluation into a genuinely improvement-oriented process. It examines how AI can assist in the interpretation of student feedback, the identification of teaching patterns, and the provision of timely insights that may inform reflective teaching practices. The paper argues that, when implemented within clear pedagogical and ethical frameworks, artificial intelligence can enhance teachers’ self-regulated learning, empower students as co-creators of the educational process, and reinforce a core principle of open education: the continuous, democratic, and transparent improvement of teaching. Finally, the paper proposes a conceptual evaluation model that employs artificial intelligence as a mechanism for learning, feedback, and professional development, contributing both to the enhancement of teaching practice and to the implementation of the philosophy of open education. The model integrates four core components—AI-supported analysis of student feedback, structured interpretation of evaluation results, mentor-supported teacher reflection, and formative follow-up processes—aiming to strengthen teachers’ self-regulated learning and enable students to participate more actively as co-creators of the educational process.

Keywords: Artificial Intelligence in Education; Formative Assessment; Open and Distance Education; Professional Learning; Teacher Evaluation