Generative AI systems, such as ChatGPT and Bard, can significantly enhance education by providing personalized learning experiences. They can tailor content, quizzes, and explanations to individual students; act as virtual tutors, and offer instant feedback. However, privacy concerns have arisen because of the need for personal data. Ensuring…

Mastering SQL programming skills is fundamental in computer science education, and Online Judging Systems (OJS) play a critical role in automatically assessing SQL codes, improving the accuracy and efficiency of evaluations. However, these systems are vulnerable to manipulation by students who can submit "cheating codes" that pass the…

This study introduces an optimized ensemble deep neural network (Optimized Ensemble Deep-NN) to enhance the accuracy of predicting student grades. This model solves the problem of different and complicated student performance data by using deep neural networks, ensemble learning, and a number of optimization algorithms, such as Adam, SGD, and RMS…

While behavioral, contextual, and physiological data streams have long been used to investigate self-regulated learning (SRL), a systematic understanding of the current state how different data streams and modalities contribute to measuring regulation processes across diverse learning contexts remains limited. This systematic literature review…

In this study, the performance of artificial intelligence chatbots--OpenAI's ChatGPT, Google Gemini, and Microsoft's Copilot--was evaluated and compared based on their responses to questions from the Turkish Higher Education Entrance Physics Examination over the past three years. Analysis of the chatbots' responses to TYT Physics questions showed…

Appreciative inquiry has become increasingly popular as a method for facilitating organisational or systemic change through focusing on the positive aspects and 'life giving properties of a system' as opposed to traditional 'deficit-based' approaches. However, there has been criticism that this process could invalidate negative experiences of…

The growing popularity of generative artificial intelligence (AI) tools presents new challenges for data quality in online surveys and experiments. This study examines participants' use of large language models to answer open-ended survey questions and describes empirical tendencies in human versus large language model (LLM)-generated text…

In recent years, remarkable advancements in artificial intelligence technology have created new opportunities for transforming educational systems and enhancing student learning. This study focuses on designing a model for an AI-based intelligent assistant to provide a personalized learning experience in higher education. A qualitative approach…

There is a pressing need to reform governance of higher education to ensure the academic integrity in response to the contemporary implications of generative artificial intelligence. The aim of this paper is to articulate research which reveals ways in which this can be done. First, it considers what new information would help academic governors…

Academic integrity is a critical ethical issue in the use of generative artificial intelligence (AI) for writing assistance. Disclosure of AI-generated content is essential to maintain the authenticity and reliability of information. This study employs a moderated mediation model to examine the mediating role of AI ethics attention in the…

Artificial Intelligence (AI) is reshaping all sectors of society, including libraries. AI adoption in libraries has been gradual due to concerns and challenges, including ethical issues, maturity of the technology, insufficient AI education and training designed for library and information professionals, and gaps in AI education in library and…

Educators evaluate student knowledge using knowledge component (KC) models that map assessment questions to KCs. Still, designing KC models for large question banks remains an insurmountable challenge for instructors who need to analyze each question by hand. The growing use of Generative AI in education is expected only to aggravate this chronic…

When tutoring students it is useful to be able to predict whether they are succeeding as early as possible. This paper compares multiple methods for predicting from sequential interaction data whether a student is on a successful path. Predicting students' future performance and intervening has shown promise in improving learner outcomes and…

Purpose: This research employs machine learning and mediation analysis, along with path analysis, to investigate the correlations between factors such as body mass index (BMI) and the occurrence of diabetes and heart disease among the Indian population. The objective is to enhance models that are specifically designed to accommodate lifestyles,…

Academic mentorship is essential for faculty development, yet mid-career researchers have limited resources. This study explores AI-assisted mentorship models using biosketch analysis, AI mapping, and human expertise to enhance mentor selection. Tools like Google NotebookLM and Mural streamlined coding, visualization, and theme identification,…