Open education systems play a significant role in providing flexible and accessible learning opportunities to large student populations, independent of time and location. These systems achieve cost efficiency through the effective implementation of economies of scale, reducing unit costs as student numbers increase. However, decision-making in the…

Metaheuristics are optimization algorithms that efficiently solve a variety of complex combinatorial problems. In psychological research, metaheuristics have been applied in short-scale construction and model specification search. In the present study, we propose a bee swarm optimization (BSO) algorithm to explore the structure underlying a…

The technology of automated short answer grading (ASAG) can efficiently process answers according to human-prepared grading examples. Computer-assisted acquisition of grading examples uses a computer algorithm to sample real student responses for potentially good examples. The process is critical for optimizing the grading accuracy of machine…

University Examination Timetabling Problem is the most important combinational problem to develop a conflict-free timetable to execute all of the exams in and with the limited timeslots and other resources for universities, colleges or schools. It is also an important Nondeterministic Polynomial Time (NP)-hard problem that has no deterministic…

Human anatomy dissection serves as a cornerstone of medical education, fostering not only anatomical knowledge but also teamwork and professionalism. Given the considerable intellectual, physical, and emotional demands of dissection, effective team dynamics are essential for student success. To enhance learning experiences and academic outcomes,…

Learning path generation involves the computation of learning trajectories to personalize academic instruction to prevent school problems. The Educational Planning Problem (EPP) considers generating personalized learning paths by scheduling activities that satisfy expected grades while minimizing plans makespan. In this work, we propose two…

Loop-based intelligent tutoring systems (ITSs) support the learning process using a step-by-step problem-solving approach. A limitation of ITSs is that few contents are compatible with this approach. On the other hand, recommendation systems can recommend different types of content but ignore the fine-grained concepts typical of the step-by-step…

Student assignment algorithms have far reaching implications for families, the education system, and for society as a whole. Motivated by operational challenges faced by the San Francisco Unified School District (SFUSD), we use a mechanism design framework to develop, operationalize, and streamline algorithmic student matching policies in San…

Many organizations utilize some form of automation in the test assembly process; either fully algorithmic or heuristically constructed. However, one issue with heuristic models is that when the test assembly problem changes the entire model may need to be re-conceptualized and recoded. In contrast, mixed-integer programming (MIP) is a mathematical…