Online education has been expected to be the future of learning; it will never replace the value of traditional classroom experiences fully. Technical problems have less impact on offline education, which gives students more freedom to plan their time and stick to it. In addition, teachers cannot observe their students' behavior and activities…

Classroom engagement is a critical factor for evaluating students' learning outcomes and teachers' instructional strategies. Traditional methods for detecting classroom engagement, such as coding and questionnaires, are often limited by delays, subjectivity, and external interference. While some neural network models have been proposed to detect…

This qualitative study examines the risks educators in Jordan face with the integration of ChatGPT, an emerging AI technology, into academic settings. While considerable attention has been given to risks affecting university students, there remains a gap in understanding the specific challenges encountered by educators themselves. Through…

Despite extensive research on the concerns with the use of ChatGPT that evolve around cheating, academic integrity, and plagiarism, very little is known on the assessment practices in school history, obscuring our understanding on how history teachers can assess students amid ChatGPT driven challenges. This conceptual paper discusses the…

This paper contributes to the ongoing efforts aimed at enhancing Outcome-Based Education (OBE) assessment methodologies by addressing some critical gaps and exploring new solutions. Our work focuses on two main areas: firstly, this study proposes an improved assessment method for OBE. It refines traditional approaches by classifying course…

Predicting learner performance with precision is critical within educational systems, offering a basis for tailored interventions and instruction. The advent of big data analytics presents an opportunity to employ Machine Learning (ML) techniques to this end. Real-world data availability is often hampered by privacy concerns, prompting a shift…

Overview: This systematic review explores the utilization of artificial intelligence (AI) for assessment, grading, and feedback in higher education. The review aims to establish how AI technologies enhance efficiency, scalability, and personalized learning experiences in educational settings, while addressing associated challenges that arise due…

This paper discusses the ethical challenges presented by artificial intelligence (AI) within the instructional process for students with disabilities. The authors briefly overview technological changes in education and applications of AI in education in addition to policy. Discussion is directed toward the development of an ethical pedagogy using…

This research was conducted to obtain students' views on the evaluation of artificial intelligence (AI)-supported design applications in art and design education using the fuzzy logic method. It aims to provide a new perspective for educators in identifying real learning situations and deficiencies in art and design education. The study utilized…

Artificial Intelligence (AI) based assessments are commonly used in a variety of settings including business, healthcare, policing, manufacturing, and education. In education, AI-based assessments undergird intelligent tutoring systems as well as many tools used to evaluate students and, in turn, guide learning and instruction. This chapter…

The purpose of this paper is to describe the development of a new framework for understanding technology-integrated assessment in higher education based on a review of the literature using the assessment design in a digital world framework (Bearman et al., 2022) as a lens. Our review (Madland et al., 2024) revealed both congruities and…

The emergence of Large Language Models (LLMs) has marked a significant change in education. The appearance of these LLMs and their associated chatbots has yielded several advantages for both students and educators, including their use as teaching assistants for content creation or summarisation. This paper aims to evaluate the capacity of LLMs…

Purpose: This paper aims to consolidate empirical studies between 2013 and 2022 to investigate the impact of artificial intelligence (AI) in higher education. It aims to examine published research characteristics and provide insights into the promises and challenges of AI integration in academia. Design/methodology/approach: A systematic…

Instructional strategies employing complex problem-solving examine how learners represent the problem space and argue for decisions. Unlike problems with few solutions (e.g., multiple choices), instructors struggle to evaluate solutions to ill-structured problems quickly and consistently across students. This prevents instructors to provide timely…

Exploring the role of artificial intelligence (AI) in education is important as it challenges traditional teaching practices and shapes how educators may approach them in the future. In this article, we document the transformative integration of AI in special education teacher preparation, highlighting how we, as early adopter professors,…