The traditional system focuses excessively on physical skills and physical fitness assessment, with problems such as single indicator, static approach, subject limitation and inefficient data utilization, making it difficult to assess students in a comprehensive and fair manner. The rise of big data technology has brought about a turnaround, from…

With Open Data becoming more popular and more public bodies publishing their datasets, the need for educating prospective graduates on how they can use them has become prominent. This study examines the use of the Problem Based Learning (PBL) method and educational technologies to support the development of Open Data skills in university students.…

Surveys are typical for student evaluation of teaching (SET). Survey research consistently confirms the negative impacts of careless responses on research validity, including low data quality and invalid research inferences. SET literature seldom addresses if careless responses are present and how to improve. To improve evaluation practices and…

Colleges and universities are increasingly turning to algorithms that predict college-student success to inform various decisions, including those related to admissions, budgeting, and student-success interventions. Because predictive algorithms rely on historical data, they capture societal injustices, including racism. In this study, we examine…

Colleges and universities are increasingly turning to algorithms that predict college-student success to inform various decisions, including those related to admissions, budgeting, and student-success interventions. Because predictive algorithms rely on historical data, they capture societal injustices, including racism. In this study, we examine…

Background: Maintaining cohesion is critical for teams to achieve shared goals and performance outcomes within a work-integrated learning (WIL) environment. Cohesion is an emergent state that develops over time, representing the synchrony of different behavioural interactions. Cohesive teams will exhibit such phenomena by their temporal…

In this study, an interactive science learning app on the topic of plate tectonics was developed for tablets to promote argumentative reasoning. The app guided learners through learning stages that required them to propose arguments, identify relevant evidence, acquire background knowledge, and engage in argumentative reasoning in different…

Academic dropout remains a significant challenge for education systems, necessitating rigorous analysis and targeted interventions. This study employs machine learning techniques, specifically random forest (RF) and feature tokenizer transformer (FTT), to predict academic attrition. Utilizing a comprehensive dataset of over 40 000 students from an…

Purpose: The datafication of teaching and learning settings continues to be of broad interest to the learning sciences. In response, this study aims to explore a non-traditional learning setting, specifically two Golf Teaching and Research Programs, to investigate how athletes and coaches capture, analyze and use performance data to improve their…

Pragmatically, machine learning techniques can improve educators' capacity to monitor students' learning progress when applied to quality data. For developing countries, the major obstacle has been the unavailability of quality data that fits the purpose. This is partly because the in-use information systems are either not properly managed or not…

Since 2010, the State Higher Education Executive Officers Association's (SHEEO) Strong Foundations survey has reported on the evolution and value of postsecondary student unit record systems (PSURSs) by illuminating the condition of state postsecondary data in the U.S. In the "Strong Foundations 2023" survey, which was administered from…

The rapid recent use of learning analytics (LA) in higher education, specifically during the COVID-19 pandemic, allows the monitoring of users' behavior while learning. Using LA may promote students' learning outcomes but also intrude into their privacy. This study aimed to explore students' behaviour and perceptions towards privacy and data…

For decades, assessing income has served as the tried-and-true method for creating financial aid packages--scholarships, grants, and loans--for the nation's college students. Each year, students and families living with low and moderate incomes submit income documentation to colleges, states, and the federal government in hopes of qualifying for…

In this paper, we present an extended evaluation of a course recommender system designed to support students who struggle in the first semesters of their studies and are at risk of dropping out. The system, which was developed in earlier work using a student-centered design, is based on the explainable k-nearest neighbor algorithm and recommends a…

The expansion of online learning in higher education has both contributed to researchers exploring innovative ways to develop learning environments and created challenges in identifying student interactions with course material. Learning analytics is an emerging field that can identify student interactions and help make data-informed course design…