Cognitive Load Theory: Advances in Research on Worked Examples, Animations, and Cognitive Load Measurement

The contributions to this special issue document some recent advances of cognitive load theory, and are based on contributions to the Third International Cognitive Load Theory Conference (2009), Heerlen, The Netherlands. The contributions focus on developments in example-based learning, amongst others on the effects of integrating worked examples in cognitive tutoring systems; specify the effects of transience on cognitive load and why segmentation may help counteract these effects in terms of the role of time in working memory load; and discuss the possibilities offered by electroencephalography (EEG) to provide a continuous and objective measure of cognitive load. This article provides a short introduction to the contributions in this issue

Attention to the model's face when learning from video modeling examples in adolescents with and without autism spectrum disorder

We investigated the effects of seeing the instructor's (i.e., the model's) face in video modeling examples on students' attention and their learning outcomes. Research with university students suggested that the model's face attracts students' attention away from what the model is doing, but this did not hamper learning. We aimed to investigate whether we would replicate this finding in adolescents (prevocational education) and to establish how adolescents with autism spectrum disorder, who have been found to look less at faces generally, would process video examples in which the model's face is visible. Results showed that typically developing adolescents who did see the model's face paid significantly less attention to the task area than typically developing adolescents who did not see the model's face. Adolescents with autism spectrum disorder paid less attention to the model's face and more to the task demonstration area than typically developing adolescents who saw the model's face. These differences in viewing behavior, however, did not affect learning outcomes. This study provides further evidence that seeing the model's face in video examples affects students' attention but not their learning outcomes

Excitonic quasiparticles in a spin-orbit Mott insulator

In condensed matter systems, out of a large number of interacting degrees of freedom emerge weakly coupled particles, in terms of which most physical properties are described. For example, Landau quasiparticles (QP) determine all electronic properties of a normal metal. The lack of identification of such QPs is major barrier for understanding myriad exotic properties of correlated electrons, such as unconventional superconductivity and non-Fermi liquid behaviours. Here, we report the observation of a composite particle in a Mott insulator Sr2IrO4---and exciton dressed with magnons---that propagates with the canonical characteristics of a QP: a finite QP residue and a lifetime longer than the hopping time scale. The dynamics of this charge-neutral bosonic excitation mirrors the fundamental process of the analogous one-hole propagation in the background of ordered spins, for which a well-defined QP has never been observed. The much narrower linewidth of the exciton reveals the same intrinsic dynamics that is obscured for the hole and is intimately related to the mechanism of high temperature superconductivity.Comment: submitted versio

When closeness is effortful: teachers’ physiological activation undermines positive effects of their closeness on student emotions

Education and Child Studie

Can We Teach Reflective Reasoning in General-Practice Training Through Example-Based Learning and Learning by Doing?

Purpose: Flaws in physicians’ reasoning frequently result in diagnostic errors. The method of deliberate reflection was developed to stimulate physicians to deliberately reflect upon cases, which has shown to improve diagnostic performance in complex cases. In the current randomised controlled trial, we investigated whether deliberate reflection can be taught to general-practice residents. Additionally, we investigated whether engaging in deliberate reflection or studying deliberate-reflection models would be more effective. Methods: The study consisted of one learning session and two test sessions. Forty-four general-practice residents were randomly assigned to one of three study conditions in the learning session: (1) control without reflecting (n = 14); (2) engaging in deliberate reflection (n = 11); or (3) studying deliberate-reflection models (n = 19). To assess learning, they diagnosed new cases in both a same-day test and a delayed test one week later. In the delayed test, participants were additionally asked to elaborate on their decisions. We analysed diagnostic accuracy and whether their reasoning contained key elements of deliberate reflection. Results: We found no significant differences between the study conditions in diagnostic accuracy on the same-day test, p = .649, or on diagnostic accuracy, p = .747, and reflective reasoning, p = .647, on the delayed test. Discussion: Against expectations, deliberate reflection did not increase future reflective reasoning. Future studies are needed to investigate whether residents either did not sufficiently learn the procedure, did not adopt it when diagnosing cases without instructions to reflect, or whether the reflective-reasoning process as itself cannot be taught

Do social cues in instructional videos affect attention allocation, perceived cognitive load, and learning outcomes under different visual complexity conditions?

Background:There are only few guidelines on how instructional videos should be designed to optimize learning. Recently, the effects of social cues on attention allocation and learning in instructional videos have been investigated. Due to inconsistent results, it has been suggested that the visual complexity of a video influences the effect of social cues on learning.Objectives:Therefore, this study compared the effects of social cues (i.e., gaze & gesture) in low and high visual complexity videos on attention, perceived cognitive load,and learning outcomes.Methods:Participants (N=71) were allocated to a social cue or no social cue condition and watched both a low and a high visual complexity video. After each video, participants completed a knowledge test.Results and Conclusions: Results showed that participants looked faster at referenced information and had higher learning outcomes in the low visual complexity condition. Social cues did not affect any of the dependent variables, except when including prior knowledge in the analysis: In this exploratory analysis, the inclusion of gaze and gesture cues in the videos did lead to better learning outcomes.Takeaways: Our results show that the visual complexity of instructional videos and prior knowledge are important to take into account in future research on attention and learning from instructional videos

Inverse Classification for Comparison-based Interpretability in Machine Learning

In the context of post-hoc interpretability, this paper addresses the task of explaining the prediction of a classifier, considering the case where no information is available, neither on the classifier itself, nor on the processed data (neither the training nor the test data). It proposes an instance-based approach whose principle consists in determining the minimal changes needed to alter a prediction: given a data point whose classification must be explained, the proposed method consists in identifying a close neighbour classified differently, where the closeness definition integrates a sparsity constraint. This principle is implemented using observation generation in the Growing Spheres algorithm. Experimental results on two datasets illustrate the relevance of the proposed approach that can be used to gain knowledge about the classifier.Comment: preprin

Training self-regulated learning skills with video modeling examples: Do task-selection skills transfer?

Self-assessment and task-selection skills are crucial in self-regulated learning situations in which students can choose their own tasks. Prior research suggested that training with video modeling examples, in which another person (the model) demonstrates and explains the cyclical process of problem-solving task performance, self-assessment, and task-selection, is effective for improving adolescents’ problem-solving posttest performance after self-regulated learning. In these examples, the models used a specific task-selection algorithm in which perceived mental effort and self-assessed performance scores were combined to determine the complexity and support level of the next task, selected from a task database. In the present study we aimed to replicate prior findings and to investigate whether transfer of task-selection skills would be facilitated even more by a more general, heuristic task-selection training than the task-specific algorithm. Transfer of task-selection skills was assessed by having students select a new task in another domain for a fictitious peer student. Results showed that both heuristic and algorithmic training of self-assessment and task-selection skills improved problem-solving posttest performance after a self-regulated learning phase, as well as transfer of task-selection skills. Heurist