In tutoring systems, a pedagogical policy, which decides the next action for the tutor to take, is important because it determines how well students will learn. An effective pedagogical policy must adapt its actions according to the student's features, such as knowledge, error patterns, and emotions. For adapting difficulty, it is common to…

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…

Errors are inevitable in most learning contexts, but under the right conditions, they can be beneficial for learning. Prior research indicates that generating and learning from errors can promote retention of knowledge, higher-level learning, and self-regulation. The present review proposes an integrated theoretical model to explain two major…

The past thirty years have shown a rise in models of language acquisition in which the state of the learner is characterized as a probability distribution over a set of non-stochastic grammars. In recent years, increasingly powerful models have been constructed as earlier models have failed to generalize well to increasingly complex and realistic…

Hiring practitioners as faculty is not a novel practice in higher education. In their decision to shift from the private sector to the classroom, many practitioners enter the professoriate with little to no formal training in pedagogy. The question for faculty developers is how might Teaching and Learning Centers (TLCs) bridge this gap from…

Emotions can influence online teaching and learning, according to existing studies. PERMA theory enjoys great fame in both positive psychology field and English foreign language context since it was proposed by Seligman, which includes five domains, namely positive emotions, engagement, relationship, meaning, and achievement. Although there is a…

Previous research has been limited regarding the measurement of computational thinking, particularly as a learning progression in K-12. This study proposes to apply a multidimensional item response theory (IRT) model to a newly developed measure of computational thinking utilizing both selected response and open-ended polytomous items to establish…

Who should evaluate the originality and task-appropriateness of a given idea has been a perennial debate among psychologists of creativity. Here, we argue that the most relevant evaluator of a given idea depends crucially on the level of expertise of the person who generated it. To build this argument, we draw on two complimentary theoretical…

Learning progressions (LPs) are "descriptions of the successively more sophisticated ways of thinking about a topic that can follow one another as children learn about and investigate a topic over a broad span of time" (National Research Council, 2007). One challenge that arises in LP research is the collection of evidence to ensure that…

Purpose: The aim of this paper is to examine the usefulness of the stimulus-organism-response (S-O-R) model for systematizing and further exploring the knowledge of the role of entrepreneurship education (EE) in fostering students' entrepreneurial mindset (EM). Current research studying the EM in an educational setting often fails to conceptualize…

Dynamic personalization of learning trajectories that integrate different perspectives and variable scenarios is a viable way to improve the effectiveness and efficiency of training and education. Serious games offer a designated platform for this, by aggregating learner interactions, and using these to dynamically configure, adjust and tailor the…

The rapid adoption of deep learning models has resulted in many business services becoming model services, yet most AI systems lack the necessary automation and industrialization capabilities. This leads to heavy reliance on manual operation and maintenance, which not only consumes power but also causes resource wastage and stability issues during…

The increased Simon effect with increasing the ratio of congruent trials may be interpreted by both attention modulation and irrelevant stimulus-response (S-R) associations learning accounts, although the reversed Simon effect with increasing the ratio of incongruent trials provides evidence supporting the latter account. To investigate if…

New knowledge tracing models are continuously being proposed, even at a pace where state-of-the-art models cannot be compared with each other at the time of publication. This leads to a situation where ranking models is hard, and the underlying reasons of the models' performance -- be it architectural choices, hyperparameter tuning, performance…

We propose a novel model, Wide & Deep Item Response Theory (Wide & Deep IRT), to predict the correctness of students' responses to questions using historical clickstream data. This model combines the strengths of conventional Item Response Theory (IRT) models and Wide & Deep Learning for Recommender Systems. By leveraging clickstream…