Tertiary institutions are migrating away from didactic and teacher-centred approaches, and instead, pivoting to lesson designs that encourage hands-on learning and student engagement. However, this practice is often "try and see", with few frameworks providing evidence-based approaches for practical application that demonstrates how…

Effective analysis and demonstration of these data features is of great significance for the optimization of interactive learning environment and learning behavior. Therefore, we take the big data set of learning behavior generated by an online interactive learning environment as the research object, define the features of learning behavior, and…

The purpose of this study is to develop and validate an authentic contextual learning framework with six constructs to model the relationships among essential factors of authentic contextual learning. In particular, this framework explores the relationships across six constructs, i.e. learning by applying, healthy learning, collaborative learning,…

On e-learning platforms, most e-learners didn't complete the course successfully. It means that reducing dropout is a critical problem for the sustainability of e-learning. This paper aims to establish a predictive model to describe e-learners' dropout behavior, which can help the commercial e-learning platforms to make appropriate interventions…

Computer-Supported Collaborative Learning is a promising innovation that ameliorates tutoring through modern technologies. However, the way of recommending collaborative activities to learners, by taking into account their learning needs and preferences, is an important issue of increasing interest. In this context, this paper presents a framework…

Learning interaction activities are the key part of tracking and evaluating learning behaviors, that plays an important role in data-driven autonomous learning and optimized learning in interactive learning environments. In this study, a big data set of learning behaviors with multiple learning periods is selected. According to the instance…

Virtual Reality (VR) has been widely adopted in educational research; however, its implementation in the classroom is still not as well known as in the research field. In other words, there is a gap between researchers and practitioners regarding the pedagogical issue. This study aimed to explore how VR could be applied in science classrooms using…

Presently, learning is more flexible, personal and has richer learning resources. In the digital era, students use digital tools in almost all aspects of learning, such as seeking information, note-taking, discussion and communication, which is in line with personal learning environments. Therefore, this study proposes a conceptual model of the…

With the emergence of the Industrial Revolution 4.0, modern technologies such as cloud computing, artificial intelligence, and big data are profoundly transforming the education ecosystem. The development of education is not only faced with huge challenges but also contains rare opportunities. New concepts such as deep learning, adaptive learning,…

The HyFlex learning model has gained popularity in recent years and, with the outbreak of COVID-19, the demand has increased. However, there are challenges associated with the model, especially related to equity and engagement. A HyFlex model known as Interactive Synchronous HyFlex is being developed and practised by the researchers in their…

Kolb's experiential learning cycle is perhaps the most scholarly influential and cited model regarding experiential learning theory. However, a key issue in interpreting Kolb's model concerns a lack of clarity regarding what constitutes a "concrete experience," exactly. A systematic literature review was conducted in order to examine:…

The paper proposes EXPLODE, a new model of exploratory learning environment for teaching and learning neural networks. The EXPLODE model is about pedagogically instrumenting a software development environment to transform it into an exploratory learning environment for neural networks. Such an environment is particularly aimed for students who are…

Churn in e-learning refers to learners who gradually perform less and become lethargic and may potentially drop out from the course. Churn prediction is a highly sensitive and critical task in an e-learning system because inaccurate predictions might cause undesired consequences. A lot of approaches proposed in the literature analyzed and modeled…

Social Learning Analytics (SLA) seeks to obtain hidden information in large amounts of data, usually of an educational nature. SLA focuses mainly on the analysis of social networks (Social Network Analysis, SNA) and the Web, to discover patterns of interaction and behavior of educational social actors. This paper incorporates the SLA in a smart…

The research of multi-category learning behaviors is a hot issue in interactive learning environment, and there are many challenges in data statistics and relationship modeling. We select the massive learning behaviors data of multiple periods and courses and study the decision application of regression analysis. First, based on the definition of…