This paper offers guidance on employing open and creative methods for co- designing critical data and artificial intelligence (AI) literacy spaces and learning activities, rooted in the principles of Data Justice. Through innovative approaches, we aim to enhance participation in learning, research and policymaking, fostering a comprehensive…

Artificial intelligence (AI) and operations research (OR) have long been intertwined because of their synergistic relationship. Given the increasing popularity of AI and machine learning in particular, we face growing demand for educational offerings in this area from our students. This paper describes two courses that introduce machine learning…

Research on Artificial Intelligence, especially in the field of machine learning, has exploded in the twenty-first century. AI research in universities has long been funded by a combination of government and corporate sources. The funding of AI research in the contemporary university includes technology companies as both funders and generators of…

Purpose: This study aims to investigate the feasibility of developing general predictive models for using the learning management system (LMS) data to predict student performances in various courses. The authors focused on examining three practical but important questions: are there a common set of student activity variables that predict student…

This study explores the use of the Adaptive Neuro-Fuzzy Inference System (ANFIS), a neuro-fuzzy approach, to analyze the log data of technology-based assessments to extract relevant features of student problem-solving processes, and develop and refine a set of fuzzy logic rules that could be used to interpret student performance. The log data that…