Complex Instruction (CI) is a set of principles and practices for designing and facilitating equitable groupwork. Originally developed to advance racial equity in United States primary schools, CI is now used to support students of many ages across many disciplines. We report on a systematic review of CI-focused research in the U.S. up to the year…

Purpose: The purpose of this systematic literature review is to identify the antecedents that have enabled the adoption of artificial intelligence (AI) in Higher Education (HE) institutions at both a macro and micro level. The term adoption is in reference to the diffusion of technology that is actively chosen for use by the targeted demographic.…

Recent advancements in generative Artificial Intelligence (GenAI) were accompanied by both hype and fear regarding the ways in which such technologies of automation would replace human labor in various fields, including education. Rather than focusing on the replacement of humans in teaching, this piece uses new materialist thought [Barad, Karen.…

As artificial intelligence (AI) is becoming more integrated into the field of healthcare, medical students need to learn foundational AI literacy. Yet, traditional, descriptive teaching methods of AI topics are often ineffective in engaging the learners. This article introduces a new application of cinema to teaching AI concepts in medical…

GPT-3 is a neuronal language model that performs tasks such as classification, question-answering and text summarization. Although chatbots like BlenderBot-3 work well in a conversational sense, and GPT-3 can assist experts in evaluating questions, they are quantifiably worse than real teachers in several pedagogical dimensions. We present the…

Argumentation-based classroom interventions are a growing alternative for stimulating conceptual learning, thinking, and communicative skills. However, not all classroom argumentation is desired, nor does every argumentation design lead students to develop their abilities and understanding. In the educational literature, productive argumentation…

Artificial intelligence (AI) and machine learning have become increasingly important in modern society and are poised to play an increasingly prominent role in education. This paper seeks to provide a theoretical framework for interrogating the integration of AI in education spaces. The paper argues that the eventual response of educators to…

Four General Chemistry instructors investigated the use of ChatGPT-4 to improve their lessons plans for the historical experiments of Thomson, Millikan, and Rutherford. The instructors varied in their prior knowledge for these experiments and their initial lessons addressed somewhat different learning objectives. This led to different…

We presented two empirical studies to assess the efficacy of two Deep Reinforcement Learning (DRL) frameworks on two distinct Intelligent Tutoring Systems (ITSs) to exploring the impact of Worked Example (WE) and Problem Solving (PS) on student learning. The first study was conducted on a probability tutor where we applied a classic DRL to induce…

The emotional intelligence models have helped to develop different tools for construct assessment. Each theoretical paradigm conceptualizes emotional intelligence from one of two perspectives: ability or mixed model. Ability models consider emotional intelligence as a pure form of mental ability and therefore as pure intelligence. Mixed models of…

The aim of this article is to use decolonial thinking, as applied in the field of AI, to explore the ethical and pedagogical implications for higher education teaching and learning. The questions driving this article are: What does a decolonial approach to AI imply for higher education teaching and learning? How can educators, researchers and…

While Reinforcement learning (RL), especially Deep RL (DRL), has shown outstanding performance in video games, little evidence has shown that DRL can be successfully applied to human-centric tasks where the ultimate RL goal is to make the "human-agent interactions" productive and fruitful. In real-life, complex, human-centric tasks, such…

Neural networks are ubiquitous in applied machine learning for education. Their pervasive success in predictive performance comes alongside a severe weakness, the lack of explainability of their decisions, especially relevant in humancentric fields. We implement five state-of-the-art methodologies for explaining black-box machine learning models…

Based on the UTAUT model, many studies have analyzed the factors influencing the use of artificial intelligence by teachers and students, but the conclusions are not uniform. This study chose high quality studies and encoded them to do meta analysis. After heterogeneity testing, sensitivity analysis and publication bias test, it has been found…

The concept of the Metaverse, viewed as the ultimate manifestation of the Internet, has gained significant attention due to rapid advances in technologies such as the Internet of Things (IoT) and blockchain. Acting as a bridge between the physical and virtual worlds, the Metaverse has the potential to offer remarkable experiences to its users.…