Vision, challenges, roles and research issues of Artificial Intelligence in Education

TLDR

Rapid advances in computing have enabled AI in Education (AIED) to provide personalized guidance, support, and decision‑making in learning environments, yet its interdisciplinary nature poses unique research challenges. The paper aims to define AIED and outline its roles to meet educational needs. We propose a framework for implementing AIED across diverse learning settings, identify ten promising research topics, and describe the article types and submission management the journal seeks. The proposed framework serves as a guide for interdisciplinary researchers conducting AIED studies.

Abstract

The rapid advancement of computing technologies has facilitated the implementation of AIED (Artificial Intelligence in Education) applications. AIED refers to the use of AI (Artificial Intelligence) technologies or application programs in educational settings to facilitate teaching, learning, or decision making. With the help of AI technologies, which simulate human intelligence to make inferences, judgments, or predictions, computer systems can provide personalized guidance, supports, or feedback to students as well as assisting teachers or policymakers in making decisions. Although AIED has been identified as the primary research focus in the field of computers and education, the interdisciplinary nature of AIED presents a unique challenge for researchers with different disciplinary backgrounds. In this paper, we present the definition and roles of AIED studies from the perspective of educational needs. We propose a framework to show the considerations of implementing AIED in different learning and teaching settings. The structure can help guide researchers with both computers and education backgrounds in conducting AIED studies. We outline 10 potential research topics in AIED that are of particular interest to this journal. Finally, we describe the type of articles we like to solicit and the management of the submissions.