The innovation capability largely determines the initiative for future development of a region. Higher school is the main position for training innovative talents. Accurate and comprehensive assessment of innovation cultivation capability is an important basis of higher schools for continuous improvement. Thus, this paper focuses on assessing…

Knowledge tracing (KT) models have been a commonly used tool for tracking students' knowledge status. Recent advances in deep knowledge tracing (DKT) have demonstrated increased performance for knowledge tracing tasks in many datasets. However, interpreting students' states on single knowledge components (KCs) from DKT models could be challenging…

In category learning, a growing body of literature has increasingly focused on exploring the impacts of interleaving in contrast to blocking. The sequential attention hypothesis posits that interleaving draws attention to the differences between categories while blocking directs attention toward similarities within categories [4, 5]. Although a…

The PageRank model has been applied in sport ranking systems; however, prior implementations exhibited limitations and failed to produce valid rankings. This study analyzed 1,466 National Collegiate Athletic Association (NCAA) Division 1 football games and developed a novel, modified PageRank model. We also proposed an artificial…

Knowledge Tracing (KT) models predicting student performance in intelligent tutoring systems have been successfully deployed in several educational domains. However, their usage in open-ended programming problems poses multiple challenges due to the complexity of the programming code and a complex interplay between syntax and logic requirements…

This paper develops a spreadsheet simulation methodology for teaching simulation and performance analysis of priority queues with multiple servers, without resorting to macros, add-ins, or array formula. The approach is made possible by a "single overtaking" simplifying assumption under which any lower-priority customer may be passed in…

The world's move to a global economy has an impact on the high rate of student academic failure. Higher education, as the affected party, is considered crucial in reducing student academic failure. This study aims to construct a prediction (predictive model) that can forecast students' time to graduation in developing countries such as Indonesia,…

In this study, we introduced a cross-classified multidimensional nominal response model (CC-MNRM) to account for various response styles (RS) in the presence of cross-classified data. The proposed model allows slopes to vary across items and can explore impacts of observed covariates on latent constructs. We applied a recently developed variant of…

Whether machine learning algorithms effectively predict college students' course outcomes using learning management system data is unknown. Identifying students who will have a poor outcome can help institutions plan future budgets and allocate resources to create interventions for underachieving students. Therefore, knowing the effectiveness of…

This article examines the work of predictive analytics in shaping the social worlds in which they thrive, and in particular the world of the first year of Great State University's student success initiative. Specifically, this article investigates the following research paradox: predictive analytics, as driven by a logic premised on predicting the…

While high-accuracy machine learning (ML) models for predicting student learning performance have been widely explored, their deployment in real educational settings can lead to unintended harm if the predictions are biased. This study systematically examines the trade-offs between prediction accuracy and fairness in ML models trained on the…

Every year, the national high school graduation rate is declining and impacting the number of students applying to colleges. Moreover, the majority of students are applying to more than one college. This makes a lot of colleges to be highly competitive in student recruitment for enrollment and thus, the necessity for institutions to anticipate…

Predictive student models are increasingly used in learning environments due to their ability to enhance educational outcomes and support stakeholders in making informed decisions. However, predictive models can be biased and produce unfair outcomes, leading to potential discrimination against certain individuals and harmful long-term…

Background/purpose: Mobile learning (M-learning) has become a crucial component of higher education due to the increasing demand for flexible and adaptive learning environments. However, ensuring personalized and effective M-learning experiences remains a challenge. This study aims to enhance M-learning effectiveness by introducing an AI-driven…

Learning interaction activities are the key part of tracking and evaluating learning behaviors, that plays an important role in data-driven autonomous learning and optimized learning in interactive learning environments. In this study, a big data set of learning behaviors with multiple learning periods is selected. According to the instance…