Enhancing reflective practices in pre-service educators : a case study on the role of GenAI in assessment as learning

Abstract

The advent of generative artificial intelligence (AI) has introduced transformative potential in various educational contexts, promising enhanced learning experiences and novel assessment methodologies[1–3]. Research highlights the concern that generative AI can compromise the integrity of current assessment methods, creating challenges that must be addressed through policy development, ethical guidelines, and innovative assessment strategies[4–6].This paper explores the challenges and opportunities presented by generative AI in education, with a specific focus on student assessment. Assessment in education is a critical component that serves multiple purposes, ranging from measuring student achievement to enhancing the learning process. There are three primary types of assessment commonly used in educational settings: Assessment of Learning (AoL), Assessment for Learning (AfL), and Assessment as Learning (AaL). Each type of assessment plays a unique role in the educational landscape and serves distinct functions [7–9].