Background: Undergraduates' collective epistemic agency is critical for their productive collaborative inquiry and knowledge building (KB). However, fostering undergraduates' collective epistemic agency is challenging. Studies have demonstrated the potential of computer-supported collaborative inquiry approaches, such as KB--the focus of this…

Background: Measuring students' self-regulation skills is essential to understand how they approach their learning tasks in order to identify areas where they might need additional support. Traditionally, self-report questionnaires and think aloud protocols have been used to measure self-regulated learning skills (SRL). However, these methods are…

Background: Select and enact appropriate learning tactics that advance learning has been considered a critical set of skills to successfully complete highly flexible online courses, such as Massive open online courses (MOOCs). However, limited by analytic methods that have been used in the past, such as frequency distribution, sequence mining and…

As educators turn to technology to supplement classroom instruction, the integration of natural language processing (NLP) into educational technologies is vital for increasing student success. NLP involves the use of computers to analyze and respond to human language, including students' responses to a variety of assignments and tasks. While NLP…

Analyzing how participants learn from each other during online forums on discussion boards or social media platforms is often challenging. One of the predominant methods of analyzing such learning is through qualitative content analysis or interaction analysis. The Interaction Analysis Model (IAM), developed by Gunawardena, Lowe and Anderson which…

The e-learning domain has witnessed a shift from the traditional behavioral approach to an individual centered learning approach based on learning analytics, with the aim of creating personalized and learner sensitive designs. A systematic literature review of 284 articles published between 2011 and 2022 in 133 different journals was conducted to…

Helping students gradually develop collective knowledge is critical but generally faces great challenges. Employing a quasi-experimental design, this study investigated the impacts and mechanisms of analytics-supported reflective assessment on the collective knowledge advancement of undergraduates. The experimental group (n = 55) engaged in…

During the past years scholars have shown an increasing interest in supporting students' self-regulated learning (SRL). Learning analytics (LA) can be applied in various ways to identify a learner's current state of self-regulation and support SRL processes. It is important to examine how LA has been used to identify the need for support in…

"Learning engineering" has gained popularity as a term connected to the work of learning sciences. However, the nature of that connection is not entirely clear. For some, learning engineering represents distinct, industry-inspired practices enabled by data abundance and digital platformization of learning technologies. That view is…

The temporal sequence of learning behavior is multidimensional and continuous in MOOCs. On the one hand, it supports personalized learning methods, achieves flexible time and space. On the other hand, it also makes MOOCs produce a large number of dropouts and incomplete learning behaviors. Dropout prediction and decision feedback have become an…

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…

Mining problems and exploring rules are the key problems in the learning process, and also the difficulties in education big data. Therefore, taking learning behavior as the research objective, this study demonstrates the collaborative training method of multi view learning interaction process driven by big data, so as to realize the tendency…

Understanding student cognitive states is essential for assessing human learning. The deep neural networks (DNN)-inspired cognitive state prediction method improved prediction performance significantly; however, the lack of explainability with DNNs and the unitary scoring approach fail to reveal the factors influencing human learning. Identifying…

The rise of precision education has encouraged teachers to use intelligent diagnostic systems to understand students' learning processes and provide immediate guidance to prevent students from giving up when facing learning difficulties. However, current research on precision education rarely employs multimodal learning analytics approaches to…

Researchers in learning analytics have created indicators with learners' trace data as a proxy for studying learner behaviour in a college course. Student Approaches to Learning (SAL) is one of the theories used to explain these behaviours, distinguishing between deep, surface, and organized study. In Latin America, researchers have demonstrated…