Socially shared regulation in learning (SSRL) contributes to successful collaborative learning (CL). Empirical research into SSRL has received considerable attention recently, with increasingly available multimodal data, advanced learning analytics (LA), and artificial intelligence (AI) providing promising research avenues. Yet, integrating these…

Despite the growing use of large language models (LLMs) in educational contexts, there is no evidence on how these can be operationalized by students to generate custom datasets suitable for teaching and learning. Moreover, in the context of network science, little is known about whether LLMs can replicate real-life network properties. This study…

Background: This study aimed to develop and test new analytics for knowledge-building practices from the transactive perspective. Based on a literature review, network analysis was identified as a promising analytical tool for these practices. We observed two aspects of network analysis that could be further developed: the multilayers of networks…

Networked and digital technologies are increasingly being used for learning in formal and informal contexts, and participant engagement occurs primarily via online discussions. In this paper, we describe an ongoing research project that focuses on examining and understanding student engagement in collaborative online discussions within a formal…

Educational researchers have pointed to socioemotional dimensions of learning as important in gaining a more nuanced description of student engagement and learning. However, to date, research focused on the analysis of emotions has been narrow in its focus, centering on affect and sentiment analysis in isolation while neglecting how emotions…

This study explored the dynamics of students' knowledge co-construction in an asynchronous gamified environment in higher education, focusing on peer discussions in college business courses. Utilizing epistemic network analysis, sequence pattern mining, and automated coding, we analyzed the interactions of 1,319 business students. Our findings…

Currently, generative AI has undergone rapid development. Numerous studies have attested to the benefits of Gen AI in programming, mathematics and other disciplines. However, since Gen AI mostly uses English as the intrinsic training parameter, it is more effective in facilitating the teaching of courses that use international common notation, but…

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…

The emergence of Generative Artificial Intelligence (GAI) has caused significant disruption to the traditional educational teaching ecosystem. GAI possesses remarkable capabilities in generating human-like text and boasts an extensive knowledge repository, thereby paving the way for potential collaboration with humans. However, current research on…

The growing use of generative AI (GenAI) has sparked discussions regarding integrating these tools into educational settings to enrich the learning experience of teachers and students. Self-regulated learning (SRL) research is pivotal in addressing this inquiry. One prevalent manifestation of GenAI is the large-language model (LLM) chatbot,…

The global expansion of online language courses is on the rise, offering greater flexibility in the approaches to learning design. This study delves into the exploration of the fundamental learning design patterns within a K-12 synchronous language course. Leveraging a rich array of textual data, including syllabi, textbooks, course outlines,…