Recently, deep learning has become a pervasive tool in prediction problems for structured and/or unstructured big data in various areas including science and engineering. In particular, deep neural network models (i.e. a basic core model of deep learning) can be viewed as an extension of statistical models by going through the incorporation of…

This study explores various approaches to investigate participants' testing performance and learning behaviors in a computer-based spatial rotation learning program. Using multivariate learning and assessment data, including responses, response times, learning times and selected covariates, a comprehensive data analytic framework is developed that…

Although the critical research cannon is often associated with qualitative scholars, there is a growing number of critical scholars who are refusing positivist-informed quantitative analyses. However, as a growing number of education scholars engaged in critical approaches to quantitative inquiry, instances of conflation began to surface. We…

Background: Learner profiles detected from digital trace data are typically triangulated with survey data to explain those profiles based on learners' internal conditions (e.g., motivation). However, survey data are often analysed with limited consideration of the interconnected nature of learners' internal conditions. Objectives: Aiming to enable…

Estimating and accounting for statistical uncertainty have become essential in today's information age, and crucial for cultivating a sound decision making citizenry. Engaging with statistical uncertainty early on can support the gradual development of uncertainty-related considerations that are often challenging to foster at any age. Statistical…

Learning analytics needs to pay more attention to the temporal aspect of learning processes, especially in self-regulated learning (SRL) research. In doing so, learning analytics models should incorporate both the duration and frequency of learning activities, the passage of time, and the temporal order of learning activities. However, where this…

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…

This position paper examines the phenomenon of the McNamara Fallacy to analyse flawed conceptions of "success" in mathematics learning, normalised assessment structures and their implications for mathematics education. The established presence of the McNamara Fallacy and the ramifications of this statistical fallacy provide a foundation…

Given the inadequacy of assessed outcomes (e.g., final exam) and the importance of evaluating the learning process in STEM education, we use deep learning to develop the STEM learning behavior analysis system (SLBAS) to assess the behavior of learners in STEM education. We map learner behavior to the ICAP (interactive, constructive, active,…

National standards that centre on the underpinning epistemic practices of the discipline has emphasised the need for teachers to focus much more on knowledge generation approaches to learning. Adopting a complexity perspective, we attempt to understand how teachers shift over time by examining their epistemic orientation to knowledge generation…

This study aims to find a simulation project-based learning model for the Minangkabau Natural Culture subject in higher education. This research method uses the research and development (R and D) development procedure using the Plomp development design that goes through 3 steps, namely: Preliminary Research, Prototyping Phase, and Assessment…

The latest version of the connectionist dual process model of reading (CDP++.parser) was tested on a set of nonwords, many of which were orthographically strange (e.g., PSIZ). A grapheme-by-grapheme read-out strategy was used because the normal strategy produced many poor responses. The new strategy allowed the model to produce results similar to…

Learners' self-initiated language learning with mobile technology occurring outside the classroom is often contextualized, heterogeneous, and idiosyncratic. In this study, we propose a time-series clustering methodology for researching informal mobile language learners' learning and development of another language, with a view to unravelling the…

This paper offers a defense of Robin Barrow's main arguments in "Giving Teaching Back to Teachers", including additional material concerning the inability of the aggregate data and statistical methods employed in research in education (and research on teaching) to speak to individual teachers and students or to particular classrooms.…

This study aims to reveal the main trends and findings of the studies examining the use of learning analytics in distance education. For this purpose, journal articles indexed in the SSCI index in the Web of Science database were reviewed, and a total of 400 journal articles were analysed within the scope of this study. The systematic review…