Generative Artificial Intelligence (GenAI) tools hold significant promises for enhancing teaching and learning outcomes in higher education. However, continues usage behavior and satisfaction of educators with GenAI systems are still less explored. Therefore, this study aims to identify factors influencing academic staff satisfaction and…

While the potential of personalized education has long been emphasized, the practical adoption of adaptive learning environments has been relatively slow. Discussion about underlying reasons for this disparity often centers on factors such as usability, the role of teachers, or privacy concerns. Although these considerations are important, I argue…

The current research is the study of academic buoyancy in relation to emotional intelligence and parenting styles. Academic buoyancy is a strength in a student's life to deal with the routine problems in classroom study like low grades, negative feedback by teachers, and difficulties in understanding of concepts. For the studying the relationship…

ChatGPT has emerged as a transformative technology with its remarkable ability to generate human-like responses, propelling its widespread adoption. While prior research has investigated the general landscape of AI-driven tools such as ChatGPT, the current study focuses specifically on exploring learners' experiences and perceptions regarding the…

This paper surveys research and practice on enhancing peer assessment with artificial intelligence. Its objectives are to give the structure of the theoretical framework underpinning the study, synopsize a scoping review of the literature that illustrates this structure, and provide a case study which further illustrates this structure. The…

Purpose: This study aimed to explore the experiences of female academics and researchers in tertiary institutions in South Africa as a means of bridging the gaps in research productivity. Design/methodology/approach: The study adopted a qualitative research design of a phenomenological type to explore the experiences of purposively selected 20…

Purpose: This registered report aimed to replicate previous findings showing that years of music training predicts speech-perception-in-noise (SPIN) skills in children. In addition, it aimed to investigate whether the musician SPIN advantage is influenced by cognitive factors such as general intelligence or working memory. Method: Following…

A significant tension exists between the necessity for teachers to regulate their emotions and the tendency to overlook these emotions in STEM education. Teachers' emotion regulation is inherently context-sensitive and discipline-specific. Therefore, it is crucial for researchers to explore the particularities of teachers' emotion regulation in…

This paper explores Stanford University's evolution in artificial intelligence (AI) education, emphasizing its interdisciplinary approach and collaboration with Silicon Valley. Building upon the university's foundational integration of liberal arts and industry partnerships, Stanford has facilitated frontier research in AI domains. Key initiatives…

As educational technology advances, the role of artificial intelligence (AI) in enhancing language education becomes increasingly prominent. However, there is a scarcity of empirical research assessing how AI integration influences student engagement and contributes to the language learning performance. This mixed-methods study seeks to fill the…

Explainable Artificial Intelligence (XAI) refers to systems that make AI models more transparent, helping users understand how outputs are generated. XAI algorithms are considered valuable in educational research, supporting outcomes like student success, trust, and motivation. Their potential to enhance transparency and reliability in online…

Collective Intelligence (CI) is important for groups that seek to address shared problems. CI in human groups can be mediated by educational technologies. The current paper presents a framework to support design thinking in relation to CI educational technologies. Our framework is grounded in an organismic-contextualist developmental perspective…

This study proposes a Bayesian method for diagnostic classification models (DCMs) for a partially known Q-matrix setting between exploratory and confirmatory DCMs. This Q-matrix setting is practical and useful because test experts have pre-knowledge of the Q-matrix but cannot readily specify it completely. The proposed method employs priors for…

Teacher education increasingly requires educators to engage with generative AI technologies, yet critical and reflective engagement opportunities remain scarce. While AI is often framed as a tool for automation, its broader pedagogical and ethical implications receive less attention. To address this gap, we implemented a critical co-discovery…

In this analysis, we review artificial intelligence (AI)-supported personalized learning (PL) systems, with an emphasis on pedagogical approaches and implementation challenges. We searched the Web of Science and Scopus databases. After the preliminary review, we examined 30 publications in detail. ChatGPT and machine learning technologies are…