Self-regulated learning (SRL) theory comprises cognitive, metacognitive, and affective aspects that enable learners to autonomously manage their learning processes. This article presents a systematic literature review on the measurement of SRL in digital platforms, that compiles the 53 most relevant empirical studies published between 2015 and…

Technology-enhanced learning supported by virtual learning environments (VLEs) facilitates tutors and students. VLE platforms contain a wealth of information that can be used to mine insight regarding students' learning behaviour and relationships between behaviour and academic performance, as well as to model data-driven decision-making. This…

In this article, we investigate a systematic workflow that supports the learning engineering process of formulating the starting question for a conversational module based on existing learning materials, specifying the input that transformer-based language models need to function as classifiers, and specifying the adaptive dialogue structure,…

This article presents the results of an experiment in personalizing course content and learning activity model tailored for online courses based on students' learning styles. The main research objectives are to design and pilot a model to determine students' learning styles to create personalized online courses. The study also addressed an…

Background: College students need the ability to generalize and apply solutions through reflective practice. University faculty need professional development to use authentic cases to prepare students for the future. Purpose: This study was to explore the experiences of faculty through a year-long professional development program that included a…

In a novel version of the classic dot-pattern prototype-distortion paradigm of category learning, Homa et al. (2019) tested a condition in which individual training instances never repeated, and observed results that they claimed severely challenged exemplar models of classification and recognition. Among the results was a dissociation in which…

In classroom assessments, examinees can often answer test items multiple times, resulting in sequential multiple-attempt data. Sequential diagnostic classification models (DCMs) have been developed for such data. As student learning processes may be aligned with a hierarchy of measured traits, this study aimed to develop a sequential hierarchical…

Higher education institutions have consistently strived to provide students with top-notch education. To achieve better outcomes, machine learning (ML) algorithms greatly simplify the prediction process. ML can be utilized by academicians to obtain insight into student data and mine data for forecasting the performance. In this paper, the authors…

To meet the national and international call for creative and innovative engineers, many engineering departments and classrooms are striving to create more authentic learning spaces where students are actively engaging with design and innovation activities. For example, one model for teaching innovation is Innovation-Based Learning (IBL) where…

With the emergence of technology, the personalization of e-learning systems is enhanced. These systems use a set of parameters for personalizing courses. However, in literature, these parameters are not based on classification and optimization algorithms to implement them in the cloud. Cloud computing is a new model of computing where standard and…

The Learning and Study Strategies Inventory (LASSI; Weinstein et al., "Learning and study strategies inventory." H&H Publishing, 1987) is a prominent instrument used in thousands of institutions worldwide as an educational and research tool. Despite its widespread prevalence, there are inconsistencies regarding the underlying latent…

This article takes a conceptual approach to an issue of pedagogical relevance--the presence of "teaching and learning moments" within educational environments. We suggest sources of philosophical confusions that design patterns for the classification and creation of typologies of classroom events. We identify three foundational…

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…

In this article Antti Moilanen assesses criticisms of Wolfgang Klafki's model of exemplary teaching made by Meinert Meyer and Hilbert Meyer and by Chi-Hua Chu. "Exemplary teaching" is a style of discovery-based teaching in which students study concrete examples of general principles in such a way that they acquire transferable knowledge…

Concepts contain rich structures that support flexible semantic cognition. These structures can be characterized by patterns of feature covariation: Certain features tend to cluster in the same items (e.g., "feathers," "wings," "can fly"). Existing computational models demonstrate how this kind of structure can be…