High dropout rate exists universally in massive open online courses (MOOCs) due to the separation of teachers and learners in space and time. Dropout prediction using the machine learning method is an extremely important prerequisite to identify potential at-risk learners to improve learning. It has attracted much attention and there have emerged…

Higher vocational education has been on a trajectory of rapid development. However, the challenge of fostering effective learning in students persists. In response to this, a study was undertaken to explore the impact of an optimized model of SPOC-based blended learning (SPOC-BL) on student presence, learning satisfaction, learning motivation, and…

With long-term impact of COVID-19 on education, online interactive live courses have been an effective method to keep learning and teaching from being interrupted, attracting more and more attention due to their synchronous and real-time interaction. However, there is no suitable method for predicting academic performance for students…

Inquiry learning is an effective learning approach if learners are properly guided. Its effectiveness depends on learners' prior knowledge, the domain, and their relationship. In a previous study we developed an Experiment Design Tool (EDT) guiding learners in designing experiments. The EDT significantly benefited low prior knowledge learners. For…

Much research on brainstorming has found that the power of a team can stimulate individual creativity, and that this influence is more prominent in computer-mediated online interactions. However, creativity appears to depend on the outcome of combining certain environmental factors with certain kinds of Individual characteristics. Two experiments…

The Proteus effect of exergames has been widely regarded as a factor that influences human performance and learning. Within the context of security and defense exergames, identification with a digital alter-ego affects students' task performance as well as their emotional states. In the present study, we examined the influence of the perceived…

The use of massive open online courses (MOOCs) for teacher professional development (TDP) has increased in the past decades. This study explored the key factors that influenced teachers' online course completion as a significant indicator of their success in a TPD MOOC. Six key influencing factors (self-efficacy, interaction with curriculum…

This study compared the effects of worked example and scripting on students' argumentative peer feedback, essay and learning qualities. Participants were 80 BSc students who were randomly divided over 40 dyads and assigned to two experimental conditions (worked example and scripting). An online peer feedback environment named EduTech was designed…

The study proposes two new measures, time and location entropy, to depict students' physical spatio-temporal contexts when engaged in an online course. As "anytime, anywhere" access has been touted as one of the most attractive features of online learning, the question remains as to the success of students when engaging in online courses…

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…

This study proposed a three-tier test to help students learn English grammar. To reduce students' anxiety, game-based learning was incorporated into the three-tier test, where personalization was also implemented to accommodate students' different needs. More specifically, we developed a Personalized Entertaining Three-Tier Test (PET3), which…

The present study investigates the impact of the educational game Sociopolis on student engagement in the context of tenth-grade social science education. Employing a mixed-methods approach, this research examines engagement behaviors quantitatively and categorically. The participant pool consists of 183 students from four public schools in…

Bayesian knowledge tracing model (BKT) is a typical student knowledge assessment method. It is widely used in intelligent tutoring systems. In the standard BKT model, all knowledge and skills are independent of each other. However, in the process of student learning, they have a very close relation. A student may understand knowledge B better when…

In-class group work activities are found to promote the interpersonal skills of learners. To support the teachers in facilitating such activities, we designed a learning analytics-enhanced technology framework, Group Learning Orchestration Based on Evidence (GLOBE) using data-driven approaches. In this study, we implemented the algorithmic group…

This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined 1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction and 2)…