Background: Deep learning methods, where models do not use explicit features and instead rely on implicit features estimated during model training, suffer from an explainability problem. In text classification, saliency maps that reflect the importance of words in prediction are one approach toward explainability. However, little is known about…

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 literature on cognitive processing and strategic processing is murky with regard to how these types of processing influence learning. One reason for this is that the frameworks used to investigate these relations have separately focused on different aspects related to cognitive processing with little integration between them. To address these…

Efklides and colleagues developed the Metacognitive and Affective model of Self-Regulated Learning (MASRL) to provide a comprehensive theoretical framework of self-regulated learning (SRL). The distinguishing feature of MASRL is that it stresses metacognitive experiences and other subjective experiences (e.g., motivational, affective) as critical…

As the articles in this special issue on "Psychological Perspectives on the Effects and Effectiveness of Assessment Feedback" have shown, feedback is a key factor in education. Although there exists a substantial body of research on the topic, it is imperative to continue advancing the field. My aim is to outline five steps to solidify…

In this study, 210 articles were reviewed from two databases--Web of Science and Scopus--using the systematic literature review method, following the PRISMA (preferred reporting items for systematic reviews and meta-analyses) selection and analysis process. Through systematic literature review and statistical analysis of empirical research…

Example-generation tasks have been suggested as an effective way to both promote students' learning of mathematics and assess students' understanding of concepts. E-assessment offers the potential to use example-generation tasks with large groups of students, but there has been little research on this approach so far. Across two studies, we…

This paper develops a spreadsheet simulation methodology for teaching simulation and performance analysis of priority queues with multiple servers, without resorting to macros, add-ins, or array formula. The approach is made possible by a "single overtaking" simplifying assumption under which any lower-priority customer may be passed in…

For students taking higher level mathematics courses, the transition from computational to proof-based courses such as analysis and algebra not only introduces a new format of writing and communication, but also a new level of abstraction. This study examines the affordances of one particular tool to aid students in this transition: a proof…

Purpose: This study aims to understand how practitioners use their insights in software development models to share experiences within and between organizations. Design/methodology/approach: This is a qualitative study of practitioners in software development projects, in large-, medium- or small-size businesses. It analyzes interview material in…

The virtual interactive learning model using imagineering process as a tool to promote happy learning for digital age learners. The concept is based on the combination of virtual learning environment and metaverse in order to create learning experience via virtual community. The objectives of this research are (1) to study and synthesise the…

Deep learning techniques are being unified for decision support in various applications. However, it remains challenging to train robust deep learning models, due to the inherent insufficient labeled data that is usually time-consuming and labor-intensive. Self-supervised learning is a feature representation learning paradigm to learn robust…

The goal of ITS is to support learning content, activities, and resources, adapted to the specific needs of the individual learner and influenced by learner's motivation. One of the major challenges to the mainstream adoption of adaptive learning is the complexity and time involved in guiding the learning process. To tackle these problems, this…

This study aims to explore college students' learning and academic self-efficacy in self-regulated learning and the effectiveness of learner-centered education by integrating the bridge-in, objective, pre-assessment, participatory learning, post-assessment, and summary (BOPPPS) model and interactive response system (IRS) tool. Accordingly,…

Self-explanation prompts in example-based learning are usually directed backwards: Learners are required to self-explain problem-solving steps just presented ("retrospective" prompts). However, it might also help to self-explain upcoming steps ("anticipatory" prompts). The effects of the prompt type may differ for learners with…