Emerging educational technologies
Z. Vazifeh; Sh. Tahmasebi Boroujeni; E. Arabameri
Abstract
Background and Objectives: High-level competitions require exceptional physical and cognitive abilities. Decision-making, as a key cognitive skill, plays a crucial role in sports activities. If this skill improves in any of the players, it will contribute to the success of the team and the group. Accordingly, ...
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Background and Objectives: High-level competitions require exceptional physical and cognitive abilities. Decision-making, as a key cognitive skill, plays a crucial role in sports activities. If this skill improves in any of the players, it will contribute to the success of the team and the group. Accordingly, identifying effective training methods and technologies that can enhance decision-making is essential, as such improvements may indirectly boost athletic performance. These methods should include a variety of exercises along with environmental control. Among emerging technologies, virtual reality (VR) has shown mixed effects on athletes’ performance, while video simulation also presents both strengths and limitations that warrant further exploration. Therefore, the present study aimed to examine the impact of virtual reality and video simulation training on the decision-making abilities of novice basketball players.Methods: Participants included 51 novice female basketball players (mean age: 19.88 ± 0.68 years), who were randomly assigned to three equal groups: virtual reality (VR), video simulation, and a control group. The study consisted of two phases: a pre-test and a post-test. During the tests, participants viewed 10 video clips, each lasting 10 seconds, extracted from critical moments in basketball games involving changes in direction and course. At the 8th second of each clip, an auditory cue was played, and the screen went black for 2 seconds, signaling the participant to respond. At the end of this interval, the same cue indicated the end of the response period, and the next clip was displayed without interruption.Participants were instructed to indicate their predicted directional decision - right, left, forward, or backward — as the next move of the player in the scene. Throughout three training sessions, the VR and video simulation groups each watched 20 specialized clips containing critical scenarios and decision-making situations. The control group, by contrast, watched a regular basketball game for 15 minutes in each session. In the post-test phase, participants were again shown 10 clips similar to the pre-test and asked to make decisions regarding the next move. For statistical analysis, the Wilcoxon signed-rank test was used to compare pre- and post-test results within each group, and the Kruskal–Wallis test was employed to examine differences between the groups.Findings: Indicated that within-group comparisons revealed a significant increase in decision-making scores from pre-test to post-test in both the virtual reality and video simulation groups (P < 0.05). However, no significant change was observed in the control group (p > 0.05). Post-test comparisons between groups revealed that the virtual reality group scored significantly higher than the control group (p = 0.039). However, there were no significant differences between the video simulation group and the control group (p = 1.00), nor between the virtual reality and video simulation groups (p = 0.066).Conclusion: The findings of this study suggest that training with virtual reality and video simulation technologies can significantly enhance decision-making abilities in novice basketball players. Both methods led to improvements compared to the control group; however, virtual reality demonstrated a stronger effect than video simulation, although the difference between the two experimental groups was not statistically significant at the post-test stage. These findings suggest that emerging technologies, especially virtual reality, hold promise as effective tools for training and improving sport-specific cognitive performance.
Educational Technology
A. M. Mousavi Harris; R. Ebrahimpour
Abstract
Background and Objectives: Methods of pedagogy, for a long time, have been a social practice based on direct experiences from the past, and many of teaching methods have been traditionally formed. These methods were not supported by a scientific theory-based system and failed to keep up with the rapidly ...
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Background and Objectives: Methods of pedagogy, for a long time, have been a social practice based on direct experiences from the past, and many of teaching methods have been traditionally formed. These methods were not supported by a scientific theory-based system and failed to keep up with the rapidly changing social needs. Neuroeducation is an experimental science and an interdisciplinary field that applies the latest theoretical advances in the human brain and psychology to education. By studying the theories in neuroeducation, it enables us to improve optimal presentation of contents for a course, teaching strategy and teaching methods of new subjects, and simultaneously improve students' computational thinking ability. One way that these theories can be tested is to study how decision-making is formed in the human brain. Goal-based decisions and behaviors depend on both sensory evidence mechanisms that collect perceptual information from the outside and mechanisms that select appropriate behaviors based on that sensory information which is decision-making mechanisms. Behaviorism is one of the basic foundations of theories of learning and behavior. One way to study behavior in detail is to use computational models based on brain biology that have been developed by neuroscientists in recent years. In this paper we try to explore the relationship between neuroeducation and pedagogy by studying theoretical achievements in computational neuroscience, cognitive neuroscience and psychology.Methods: To investigate this issue, a neural-computational model of brain-based for decision making was used. This model consists of two recurrent dynamic neurons that can explore how perceptual decisions are formed in complex behavioral spaces and show the key parameters of decision-making process. In this study, we designed three different experiments in the model that included the accuracy-speed trade-off when responding, the effect of attention on decision making, and the impact of the confidence of decision, and then analyzed how the parameters and model's behavior change then we map the parameters to the classroom and changes in student’s brain. Finally, we used linear regression model to study the relationships and correlations between the parameters of the model’s behavior.Findings: The results showed that using this decision-making computational model opened a way to study the speed-accuracy trade-off of students while answering exam questions and then, by using the model, an optimal trade-off could be found to answer the questions. Also, the analysis of model parameters showed that the level of students' attention in the classroom could be measured by the model and it had an important effect on decision making and answering the questions. Finally, the model could show the effect of students’ confidence on their performance and based on the fitted data of the model to students' behavioral data, we could make optimal suggestions from the perspective of educational psychology.Conclusion: In this study, we show that by using decision-making neural-computational models, students' behavior in the classroom can be modeled. Educational science experts and psychologists in the field of pedagogy can use the findings to provide the best and most optimal teaching methods for teaching easily and the flourishing of students' creativity.
