The initial learning experience is a critical opportunity to support conceptual understanding of abstract STEM concepts. Although hands-on activities and physical three-dimensional models are beneficial, they are seldom utilized and are replaced increasingly by digital simulations and laboratory exercises presented on touchscreen tablet computers.…

Dropout refers to the phenomenon of students leaving school before completing their degree or program of study. Dropout is a major concern for educational institutions, as it affects not only the students themselves but also the institutions' reputation and funding. Dropout can occur for a variety of reasons, including academic, financial,…

In the profession of education, predicting students' academic success is an essential responsibility. This study introduces a novel methodology for predicting students' pass or fail outcome in certain courses. The system utilises academic, demographic, emotional, and VLE sequence information of students. Traditional prediction methods often…

Knowledge tracing (KT), the task of tracking the knowledge state of a student over time, has been assessed actively by artificial intelligence researchers. Recent reports have described that Deep-IRT, which combines item response theory (IRT) with a deep learning method, provides superior performance. It can express the abilities of each student…

Background: The Wechsler Intelligence Scale for Children (WISC) employs a hierarchical model of general intelligence in which index scores separate out different clinically-relevant aspects of intelligence; the test is designed such that index scores are statistically independent from one another within the normative sample. Whether or not the…

This Perspective article expands on a working memory-dependent dual-process model, originally proposed by Zheng et al., to elucidate individual differences in the testing effect. This model posits that the testing effect comprises two processes: retrieval-attempt and post-retrieval re-encoding. We substantiate this model with empirical evidence…

Converging evidence suggests that traditional domain-general working memory (WM) training does not have reliable far-transfer effects, but produces reliable, modest near-transfer effects on structurally similar untrained tasks. Given the critical role of WM in academic development, WM training that incorporates task-specific features may maximize…

A key goal in cognitive training research is understanding whether cognitive training enhances general cognitive capacity or provides only task-specific improvements. Here, we developed a quantitative model for describing the temporal dynamics of these two processes. We analyzed data from 1300 children enrolled in an 8 week working memory training…

Participants gave recognition judgments for short lists of pictures of everyday objects. Pictures in a given list were an equal mixture of three types that varied according to the way they were used as targets and foils earlier in the same session. Under consistent-mapping (CM), targets and foils never switch roles; under varied-mapping (VM),…

This article reports on a comprehensive synthesis of the literature on the role of working memory in second language (L2) writing. It starts with an overview and clarification of the construct and measurement of working memory, followed by an elaboration of major theoretical models informing the synthesized research. The article then presents a…

Models of self-regulated learning emphasize the active and intentional role of learners and, thereby, focus mainly on conscious processes in working memory and long-term memory. Cognitive load theory supports this view on learning. As a result, both fields of research ignore the potential role of unconscious processes for learning. In this review…

Cognitive Load Theory has emerged as an important approach to improving instruction in the health professions workplace, including patient handovers. At the same time, there is growing recognition that emotion influences learning through numerous cognitive processes including motivation, attention, working memory, and long-term memory. This study…

This study compared physical and digital models of a scientific topic in order to determine representational competence, short- and long-term cognition, and the extent to which physical or digital interfaces enhance spatial ability. The DNA molecule was used as a representative spatial topic to investigate conceptual and spatial understanding.…

Understanding student cognitive states is essential for assessing human learning. The deep neural networks (DNN)-inspired cognitive state prediction method improved prediction performance significantly; however, the lack of explainability with DNNs and the unitary scoring approach fail to reveal the factors influencing human learning. Identifying…

The authors argue that Ambridge's radical exemplar account of language cannot clearly explain all syntactic priming evidence, such as inverse preference effects ("greater" priming for less frequent structures), and the contrast between short-lived lexical boost and long-lived abstract priming. Moreover, without recourse to a level of…