Successful computer-based assessments for learning greatly rely on an effective learner modeling approach to analyze learner data and evaluate learner behaviors. In addition to explicit learning performance (i.e., product data), the process data logged by computer-based assessments provide a treasure trove of information about how learners solve…

Learning programming is a complex process that requires understanding abstract concepts and solving problems efficiently. To support and motivate students, educators can use technology-enhanced learning (TEL) in the form of visual tools for knowledge mapping. Mytelemap, a prototype tool, uses TEL to organize and visualize information, enhancing…

This study aimed to develop and validate the Metacognitions about Generative AI Use Scale (MGAUS) to assess college students' metacognitive beliefs about generative AI and to explore these metacognitions as predictors of generative AI addiction risk. A total of 1229 college students from China participated in the study, providing data through an…

Research on online learning effectiveness has experienced a shift towards focusing on learner characteristics or differences. However, little attention has been paid to learners' personality traits, especially those that highly match with the environmental characteristics of online learning. Guided by recent active learning approach and Model of…

The current study investigates the interaction of Gamification, and Instructional Design to enhance the Usability of e-Learning in higher education programs. The study also examines the mediating role of Instructional design. Data were collected from a self-structured questionnaire from the academicians and was analyzed through Structural Equation…

This study explored factors influencing ChatGPT adoption among higher education students in five Nordic countries (Sweden, Finland, Denmark, Norway, and Iceland) and the USA. The unified theory of acceptance and use of technology 2 (UTAUT2) framework was employed and extended to incorporate personal innovativeness. Data was collected from 586…

It is pointed out that one of the main problems of online learning environments is determining whether students engage or not. As engagement is a complex and multifaceted concept, researchers have stated that engagement is effected by many factors (environmental conditions and learner characteristics) and changes according to the context. Among…

Teaching computer programming language remotely presents particular difficulties due to its requirement for abstract and logical thinking. There is a dearth of research specifically examining the potential factors that determine student performance when distance self-learning is conducted for programming language education. This study aims to…

In recent years, there has been a growing emphasis on integrating Artificial Intelligence (AI) applications in educational settings. As a result, it is essential to assess teachers' competencies in Technological, Pedagogical, and Content Knowledge (TPACK) as it pertains to AI and examine the factors that influence these competencies. This study…

The integration of AI-chatbots into higher education offers the potential to enhance learning practices. This research aims to explore the factors influencing AI-chatbots adoption within higher education, with a focus on the moderating roles of technological proficiency and academic discipline. Utilizing a survey-based approach and advanced…

The main objectives of this research were to analyze the impact of the use of augmented reality (AR) for analyzing the safety of sport equipment, on the motivational climate, behavior, and intention to use, and to validate a theoretical model for predicting continuance intention to use AR among students. The sample consisted of 254 university…

This study explores the role of Artificial Intelligence Generated Content (AIGC) in undergraduates' learning and research, and its increasing significance in higher education. Against this backdrop, understanding college students' attitudes, behaviors, and intentions towards AIGC is beneficial for better guiding their learning under the support of…

The successful completion of remedial mathematics is widely recognized as a crucial factor for college success. However, there is considerable concern and ongoing debate surrounding the low completion rates observed in remedial mathematics courses across various parts of the world. This study applies explainable artificial intelligence (XAI) tools…

This study aims to employ the supervised machine learning algorithms to examine factors that negatively impacted academic performance among college students on probation (underperforming students). We used the Knowledge Discovery in Databases (KDD) methodology on a sample of N = 6514 college students spanning 11 years (from 2009 to 2019) provided…

This study, anchored in the empirical domain of student learning experiences, employs the Chaoxing Fanya network teaching platform to delineate a comprehensive model of factors that influence student learning experiences within the framework of blended collaborative learning. Through a rigorous synthesis of extant literature and qualitative…