Learning analytics, located at the intersection of learning science, data science, and computer science, aims to leverage educational data to enhance teaching and learning. However, as educational data increases, distilling meaningful insights presents challenges, particularly concerning individual learner differences. This work introduces a…

Purpose: Highly developed and agile learners who can clearly convey and call on their skills are sought in all walks of life. Diverse demand for these capacities has called attention to how the skills and knowledge gained during doctoral study can be conveyed, translated and leveraged in non-academic settings; however, the complex learning reality…

This study addresses the role of awareness in learning and the variables that may facilitate adult second language (L2) implicit learning. We replicated Williams's (2005) study with a similar group of academic learners enrolled at university as well as a group of non-college-educated adults in order to explore the generalizability of the findings…

In multimedia learning, there is a lot of new information that learners are exposed to, making it a cognitively intensive process. Poorly-designed multimedia lessons can introduce distractions that must be dealt with by the learner. However, learners do not all share the same skill at managing incoming information or holding capacity, which could…

In a range of settings, human operators make decisions with the assistance of automation, the reliability of which can vary depending upon context. Currently, the processes by which humans track the level of reliability of automation are unclear. In the current study, we test cognitive models of learning that could potentially explain how humans…

Statistical learning (SL), the ability to detect and extract regularities from inputs, has been considered as an early-maturing and domain-general mechanism that is critical for typical language development. However, recent evidence in neurotypical adults and children have found that individuals can vary in their SL abilities across linguistic and…

Learning processes that involve cognitive incongruity are closely tied to emotional experiences such as curiosity or confusion. The present study examined how discovering that a confidently held misconception is incorrect influences emotions and in turn the motivation to seek additional information. We asked 275 preservice teachers to judge if…

Learning in a multimedia environment puts many demands on a learner's limited working memory, but this can become even more demanding as the level of distraction increases in a lesson. What has not been investigated much in previous literature is whether higher levels of distraction in lessons are more harmful to some learners than others. This…

In this paper, we report a longitudinal study of the effects of procedural task repetition on learners' task performance (i.e., syntactic complexity in relation to lexical complexity). We investigated how task repetition results in differences at the group and individual level across each task interval (T = 7). Intermediate-level Saudi learners of…

"Self-regulated learning" (SRL) significantly impacts the process and outcome of "programming problem-solving." Studies on SRL behavioural patterns of programming students based on trace data are limited in number and lack of coverage. In this study, hence, the Hidden Markov Model (HMM) was employed to probabilistically mine…

The use of metacognitive prompting to support self-regulated learning is a well-established area of research in education. Despite receiving considerable attention, the precise mechanism of prompting and its effects on the learning process remain unclear, especially in the context of multimedia learning. This study employed a controlled laboratory…

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…

For decades, the field of workplace selection has been dominated by evidence that cognitive ability is the most important factor in predicting performance. Meta-analyses detailing the contributions of a wide-range of factors to workplace performance show that cognitive ability's contribution is partly mediated by the learning of task-relevant…

Neuroplasticity, defined as the brain's "potential" to change in response to its environment, has been extensively studied at the cellular and molecular levels. Work in animal models suggests that stimulation to the ventral tegmental area (VTA) enhances plasticity, and that myelination constrains plasticity. Little is known, however,…

An important component of many Adaptive Instructional Systems (AIS) is a 'Learner Model' intended to track student learning and predict future performance. Predictions from learner models are frequently used in combination with mastery criterion decision rules to make pedagogical decisions. Important aspects of learner models, such as learning…