In this work, 29 features were defined and implemented to be automatically extracted and analysed in the context of NeuroK, a learning platform within the neurodidactics paradigm. Neurodidactics is an educational paradigm that addresses optimization of the learning and teaching process from the perspective of how the brain functions. In this…

Feedback is critical in providing personalized information about educational processes and supporting their performance in online collaborative learning environments. However, giving effective feedback and monitoring its effects, which is especially important in online environments, is a complex issue. Although providing feedback by analyzing…

This article introduces an ontology-based framework for group assessment analytics that investigates the impact of intra-group interactions on group performance within the context of project-based collaborative learning (PBCL). Additionally, it aims to predict learners' performance based on these interactions. The study involved 312 first-degree…

This study empirically investigates diffusion-based centralities as depictions of student role-based behavior in information exchange, uptake and argumentation, and as consistent indicators of student success in computer-supported collaborative learning. The analysis is based on a large dataset of 69 courses (n = 3,277 students) with 97,173 total…

Due to the pandemic, many students have been forced to study remotely. This study aims to investigate the impact of online collaboration scripts on learning outcomes in virtual reality (VR) co-creation learning activities during distance learning. The collaboration scripts were designed to foster students' remote teamwork. The participants…

As a cutting-edge field of artificial intelligence in education (AIEd) that depends on advanced computing technologies, AI performance prediction model is widely used to identify at-risk students that tend to fail, establish student-centered learning pathways, and optimize instructional design and development. A majority of the existing AI…

Predictors of student academic success do not always replicate well across different learning designs, subject areas, or educational institutions. This suggests that characteristics of a particular discipline and learning design have to be carefully considered when creating predictive models in order to scale up learning analytics. This study…

The flipped classroom has been increasingly employed as a pedagogical strategy in the higher education classroom. This approach commonly involves pre-class learning activities that are delivered online through learning management systems that collect learning analytics data on student access patterns. This study sought to utilize learning…

There has been extensive research using centrality measures in educational settings. One of the most common lines of such research has tested network centrality measures as indicators of success. The increasing interest in centrality measures has been kindled by the proliferation of learning analytics. Previous works have been dominated by…

Purpose: This study aims to uncover divergent collaboration in makerspaces using social network analysis to examine ongoing social relations and sequential data pattern mining to invesitgate temporal changes in social activities. Design/methodology/approach: While there is a significant body of qualitative work on makerspaces, there is a lack of…

"Advances in Accounting Education" is a refereed, academic research publication whose purpose is to help meet the needs of faculty members and administrators who are interested in ways to improve teaching, learning and curriculum development in the accounting area at the college and university level. We publish thoughtful, well-developed…