This study explored the perceptions of principal candidates and their field supervisors regarding the impact of coherently sequenced practicum tasks on candidates' instructional leadership skills. The findings revealed that the quality of practicum experiences and the development of professional relationships between candidates and supervisors are…

Traditional education, characterized by rigid curricula and inflexible teaching methods, often fails to accommodate the diverse cognitive profiles of neurodivergent learners, including those with Autism Spectrum Disorder (ASD), Attention Deficit Hyperactivity Disorder (ADHD), and dyslexia. Although e-Learning has introduced greater flexibility and…

The increasing number of students in higher education has led to the formation of large class teaching and learning environments, which is a threat to quality education. The Department of Fashion Design and Textiles Studies of Kumasi Technical University is one such department that is facing this challenge. Computer-based technology has…

Purpose: This study aims to investigate the futuristic visions of PhD students at Distance Education department of Anadolu University on the use of learning analytics (LA) and mobile technologies together. Design/methodology/approach: This qualitative research study, designed in the single cross-section model, aimed to reveal futuristic visions of…

This study examines the extent to which the learning orientations identified by student self-reports and the observation of their online learning events were related to each other and to their academic performance. The participants were 322 first-year engineering undergraduates, who were enrolled in a blended course. Using students' self-report on…

There is a growing interest in the use of learning analytics in higher education institutions. Learning analytics also appear to have the potential to be used to provide personalized feedback and support in online learning. However, when the literature is examined, the use of learning analytics for this purpose appears as a gap to be investigated.…

Study success includes the successful completion of a first degree in higher education to the largest extent, and the successful completion of individual learning tasks to the smallest extent. Factors affecting study success range from individual dispositions (e.g., motivation, prior academic performance) to characteristics of the educational…

With the emergence of technology, the personalization of e-learning systems is enhanced. These systems use a set of parameters for personalizing courses. However, in literature, these parameters are not based on classification and optimization algorithms to implement them in the cloud. Cloud computing is a new model of computing where standard and…

The learning analytics (LA) field seeks to analyze data about students' interactions, and it has been applied in the development of tools for supporting both learning and teaching processes. Recent research has paid attention on how LA may benefit teachers in the creation of educational resources. However, most of the research on LA solutions is…

This study uses the log data from Moodle learning management system for predicting student learning performance in the first third of a semester. Since the quality of the data has great influence on the accuracy of machine learning, five major data transmission methods are used to enhance data quality of log file in the data preprocessing stage.…

To assist higher education institutions in meeting the challenge of limited student engagement in the implementation of Learning Analytics services, the Questionnaire for Student Expectations of Learning Analytics (SELAQ) was developed. This instrument contains 12 items, which are explained by a purported two-factor structure of "Ethical and…

Both educational data mining and learning analytics aim to understand learners and optimise learning processes of educational settings like Moodle, a learning management system (LMS). Analytics in an LMS covers many different aspects: finding students at risk of abandoning a course or identifying students with difficulties before the assessments.…

Intelligent tutoring systems for programming education can support students by providing personalized feedback when a student is stuck in a coding task. We study the problem of designing a hint policy to provide a next-step hint to students from their current partial solution, e.g., which line of code should be edited next. The state of the art…

Research has shown assistance can provide many benefits to novices lacking the mental models needed for problem solving in a new domain. However, varying approaches to assistance, such as subgoals and next-step hints, have been implemented with mixed results. Next-Step hints are common in data-driven tutors due to their straightforward generation…

This paper introduces a novel approach to identify at-risk students with a focus on output interpretability through analyzing learning activities at a finer granularity on a weekly basis. Specifically, this approach converts the predicted output from the former weeks into meaningful probabilities to infer the predictions in the current week for…