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 paper, we propose an interactive layers model on self-regulated learning and cognitive load that considers sensory memory, working memory, and long-term memory. The model distinguishes between (a) unconscious self-regulated learning initiated by so-called resonant states in sensory memory and (b) conscious self-regulated learning of scheme construction in working memory. In contrast with conscious self-regulation, unconscious self-regulation induces no cognitive load. The model describes conscious and unconscious self-regulation in three different layers: a content layer, a learning strategy layer, and a metacognitive layer. Interactions of the three layers reflect processes of monitoring and control. We first substantiate the model based on a narrative review. Afterwards, we illustrate how the model contributes to re-interpretation of inconsistent empirical findings reported in the existing literature.

Background: What is redundancy? While most studies confirm that redundancy is harmful to learning, there are two theoretical approaches to redundancy. The first understands redundancy as a contentual overlap that puts demand on the limited cognitive capacities of the learner. The second understands redundancy as an ineffective combination of sources leading to an overload of the limited working memory modalities. Aims: Since these theoretical differences are rarely acknowledged in operation, this study proposes a classification of two distinct types of redundancy to compare these experimentally to investigate their possible main and interaction effects. The first type, content redundancy, is concerned with the contentual overlap of information. The second type, modal redundancy, is concerned with the modalities in which the information is displayed. Methods: We used these two types of redundancy as factors in a 2 × 2 within‐subject design, in which we experimentally compared their effects. Sample: University students ( N = 46) learned from specifically designed domain‐general material which aimed to observe redundancy effects without interference from confounding variables. Results: The results show that content redundancy increases learning outcomes and decreases cognitive load, while modal redundancy decreases learning outcomes and increases cognitive load. Conclusion: On the theoretical level, these findings confirm the usefulness to distinguish content redundancy from modal redundancy. On the practical level, the empirical findings of the different effects of the two types of redundancy provide educators with important insights that can improve the design of multimedia learning materials.

Assessing cognitive demand is crucial for research on self-regulated learning; however, discrepancies in translating essential concepts across languages can hinder the comparison of research findings. Different languages often emphasize various components and interpret certain constructs differently. This paper aims to develop a translingual set of items distinguishing between intentionally invested mental effort and passively perceived mental load as key differentiations of cognitive demand in a broad range of learning situations, as they occur in self-regulated learning. Using a mixed-methods approach, we evaluated the content, criterion, convergent, and incremental validity of this scale in different languages. To establish content validity, we conducted qualitative interviews with bilingual participants who discussed their understanding of mental effort and load. These participants translated and back-translated established and new items from the cognitive-demand literature into English, Dutch, Spanish, German, Chinese, and French. To establish criterion validity, we conducted preregistered experiments using the English, Chinese, and German versions of the scale. Within those experiments, we validated the translated items using established demand manipulations from the cognitive load literature with first-language participants. In a within-subjects design with eight measurements (N = 131), we demonstrated the scale’s criterion validity by showing sensitivity to differences in task complexity, extraneous load manipulation, and motivation for complex tasks. We found evidence for convergent and incremental validity shown by medium-size correlations with established cognitive load measures. We offer a set of translated and validated items as a common foundation for translingual research. As best practice, we recommend four items within a reference point evaluation.

This study explores how receiving identical information from different sources affects learning and cognitive load, focusing on two types of redundancy: modal redundancy, where redundant information comes from two visual sources (images and written text), and codal redundancy, where redundant information comes from two sources of different modalities which utilize the same symbol system (spoken and written text). Using a 2 × 2 between-subjects design involving modal (yes/no) and codal (yes/no) redundancy, 158 participants completed twenty learning tasks, consisting of ten construction and ten recall tasks. Additionally, they rated their cognitive load by indicating their perceived task difficulty and mental load. Overall, results indicate positive main effects of modal redundancy and negative effects of codal redundancy on learning and cognitive load. Furthermore, significant interaction effects suggest that modal redundancy may counterbalance the negative effects of codal redundancy, implying a compensatory mechanism in cognitive processing for construction tasks. These results highlight the importance of considering both modal and codal redundancy and their interaction in instructional design.

In this meta-analysis, we examine the association between teacher well-being and ill-being with student motivation and achievement. Based on 186 articles, 811 effect sizes, and data from 355,637 teachers, we investigate these relationships through the lens of the Job Demands–Resources Model, Transactional Stress Model, Self-Determination Theory, and the PERMA model. Using three-level meta-analytic models, we found small to moderate associations between student outcomes and teacher well-being ( r = .18) and ill-being ( r = –.13). These associations were similarly patterned across student motivation and student achievement, with no significant differences by outcome type. Associations were also comparable across domains of teacher functioning with no significant differences by domain. Moderator analyses indicated stronger associations in secondary school settings. Associations were also larger when teacher and student variables were reported by the same informant, although this difference reached conventional significance only for teacher ill-being and approached significance for teacher well-being. These findings suggest that teacher well-being and ill-being show reliable but modest associations with student motivation and achievement across a diverse body of research, though the evidence remains largely correlational. Given this correlational nature and the influence of measurement source, future longitudinal and intervention research is needed to clarify causal mechanisms and the direction of effects.