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

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

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

Psychometric properties of the Actively Open-minded Thinking scale

The Actively Open-minded Thinking scale (AOT; Stanovich & West, 2007) is a questionnaire that is used to measure the disposition towards rational thinking as a single psychological trait. Yet, despite its frequent use, also in abbreviated form, it is still unclear whether sumscores of the AOT can actually be used to order individuals on their disposition towards actively open-minded thinking and whether the questionnaire can be validly shortened. The present study aimed to obtain a valid and shorter AOT. We conducted Mokken scale analyses on the (Dutch) AOT using two samples of higher education students (N = 930; N = 509). Our analyses showed that none of the 41 items could discriminate sufficiently between respondents with varying latent trait levels. Furthermore, no item-set of the AOT could be obtained to validly order individuals on the assumed latent trait, which is a crucial assumption when using it in research. Consequently, it is questionable whether scores on the AOT provide insights into the concept it aims to measure

Fostering clinical reasoning in physiotherapy: Comparing the effects of concept map study and concept map completion after example study in novice and advanced learners

Background: Health profession learners can foster clinical reasoning by studying worked examples presenting fully worked out solutions to a clinical problem. It is possible to improve the learning effect of these worked examples by combining them with other learning activities based on con

Co-thought gesturing supports more complex problem solving in subjects with lower visual working-memory capacity

During silent problem solving, hand gestures arise that have no communicative intent. The role of such co-thought gestures in cognition has been understudied in cognitive research as compared to co-speech gestures. We investigated whether gesticulation during silent problem solving supported subsequent performance in a Tower of Hanoi problem-solving task, in relation to visual working-memory capacity and task complexity. Seventy-six participants were assigned to either an instructed gesture condition or a condition that allowed them to gesture, but without explicit instructions to do so. This resulted in th

A Theoretical Analysis of How Segmentation of Dynamic Visualizations Optimizes Students' Learning

This article reviews studies investigating segmentation of dynamic visualizations (i.e., showing dynamic visualizations in pieces with pauses in between) and discusses two not mutually exclusive processes that might underlie the effectiveness of segmentation. First, cognitive activities needed for dealing with the transience of dynamic visualizations impose extraneous cognitive load, which may hinder learning. Segmentation may reduce the negative effect of this load by dividing animations into smaller units of information and providing pauses between segments that give students time for the necessary cognitive activities after each of those units of information. Second, event segmentation theory states that people mentally segment dynamic visualizations during perception (i.e., divide the information shown in pieces). Segmentation of dynamic visualisation could cue relevant segments to students, which may aid them in perceiving the structure underlying the process or procedure shown