Online collaborative learning (OCL) has been a mainstream pedagogy in the field of higher education. However, learners often produce off-topic information and engage less during online collaborative learning compared to other approaches. In addition, learners often cannot converge in knowledge, and they often do not know how to coregulate with…

Purpose: The purpose of this study is to set up an evaluation model to predict massive open online courses (MOOC) learning performance by analyzing MOOC learners' online learning behaviors, and comparing three algorithms -- multiple linear regression (MLR), multilayer perceptron (MLP) and classification and regression tree (CART).…

Purpose: This study leverages social network analysis (SNA) to visualise the way students interacted with online resources and uses the data obtained from SNA as features for supervised machine learning algorithms to predict whether a student will successfully complete a course. Design/methodology/approach: The exploration and visualisation of the…

This methodological-theoretical synergy provides an integrative framework of learning analytics through the development of the human-and-machine symbiotic reinforcement learning. The framework intends to address the challenges of the current learning analytics model, including a lack of internal validity, generalizability, immediacy,…

This study aims to examine e-learning experiences of the learners by using learner system interaction metrics. In this context, an e-learning environment has been structured within the scope of a course. Learners interacted with learning activities and leave various traces when they interact with others, contents, and assessment tasks. Log data…

Educational research suggests that interactivity is one of the most important tools for learning. This paper analyses the learning process in online communities by examining three types of interactions among learners: (1) interactions involving the active contribution of content ('digitally speaking'); (2) interactions involving the consumption of…

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…

In this research, the effect of the use of learning analytics (LA) based feedback as a metacognitive tool on the learners' transactional distance and motivation was examined. The research was carried out according to experimental design and was carried out on 81 university students. The students were randomly assigned to the experimental and…

Emerging technological advancements can play an essential role in overcoming challenges caused by the COVID-19 pandemic. As a promising educational technology field, Learning Analytics (LA) tools or systems can offer solutions to COVID-19 pandemic-related needs, obstacles, and expectations in higher education. In the current study, we…

Sharing the same philosophy of "relations matter" with computer-supported collaborative learning (CSCL), social network analysis (SNA) has become a common methodology in the CSCL research. In this research, I use SNA methods from "relational ties," "network modes," and "integrated methods" perspectives to…

Sentiment evolution is a key component of interactions in blended learning. Although interactions have attracted considerable attention in online learning contexts, there is scant research on examining sentiment evolution over different interactions in blended learning environments. Thus, in this study, sentiment evolution at different interaction…

In this study, students' interactions with different learning activities are examined and the relation among learning performance with different interaction patterns, learning performance, self-regulated learning (SRL) strategies and motivation is presented. Learning materials including different kinds of activities are prepared and presented to…

A major criticism brought to digital learning environments was that the individual learning activities cannot be monitored consistently. However, recent advancements of educational data mining and learning analytics allow a precise tracking of learner activities. Previous studies focused on learners' navigation profiles, academic achievements, or…

E-learning platforms and processes face several challenges, among which is the idea of personalizing the e-learning experience and to keep students motivated and engaged. This work is part of a larger study that aims to tackle these two challenges using a variety of machine learning techniques. To that end, this paper proposes the use of k-means…

Purpose: With the growth of digital education, students increasingly interact in a variety of ways. The potential effects of these interactions on their learning process are not fully understood and the outcomes may depend on the tool used. This study explores the communication patterns and learning effectiveness developed by students using two…