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Background: Though pedagogical artificial agents are expected to play a crucial role in the years to come, earlier studies provide inconsistent results regarding their effect on learning. This might be because their potential for exhibiting subtle nonverbal behaviours we know from human teachers has been untapped. What is more, there is little evidence of the processes underlying the effect of nonverbal behaviours of teachers (either human or artificial) on learning, so as to better guide their practical application. Objectives: The aims of the current research were threefold: firstly, to examine the effect of an artificial agent's vocal expressiveness on non‐verbal immediacy (teachers' ability to increase psychological closeness through nonverbal communication). Secondly, to test whether an artificial agent showing strong vocal expressiveness will enhance affective and cognitive learning (perceived and actual), as compared to an artificial agent that shows weak vocal expressiveness. Thirdly, to examine whether the underlying mechanisms of motivation and attention explain the effect of immediacy (and thereby also of vocal expressiveness) on the two learning outcomes. Methods: The study used a between‐participants design, with the participants being randomly assigned to one of the two experimental conditions: artificial modelling with strong expressiveness and artificial modelling with weak vocal expressiveness. Results and conclusions: Results showed that an artificial agent with strong vocal expressiveness increased affective and perceived cognitive learning. Partial support was found for actual cognitive learning. What is more, our findings revealed that vocal expressiveness is related to affective and perceived cognitive learning because it promotes nonverbal immediacy. Finally, results provided evidence of motivation as a mediator of the path from immediacy to affective learning. Major takeaways: The current findings verify the important role of nonverbal immediacy found in traditional educational settings. However, showing that these results also apply to artificial teachers is essential, given that the educational landscape is changing and reshaping by artificial intelligence. Thus, taking into consideration the role of vocal expressiveness in the development of artificial teachers or voice assistants like Alexa, Siri, and Google assistant, as a way to enhance immediacy and affective experience of learners is of imperative value, since they will be found more and more in our societies. Lay Description: What is currently known about the subject matter: There is a positive effect of nonverbal cues of human teachers on students' learningThe artificial agent's voice is important for learning. What their paper adds to this: Provides strong evidence of the positive effect of vocal expressiveness of artificial agents on learning outcomes.Reveals that vocal expressiveness is related to learning outcomes because it enhances immediacy.Examines the proposed mechanisms of motivation and attention as mediators of the path from immediacy to affective and cognitive learning. Implications of study findings for practitioners: Taking into consideration vocal expressiveness of artificial agents during the design process is essential for increased learning.The combination of the vocal parameters of pitch and speech rate is effective for constructing vocal expressiveness.By showing the underlying mechanisms of artificial agents' nonverbal cues (i.e., vocal cues) on learning, it helps designers to make a better decisions during construction.The study's findings are also pertinent for human teachers in improving students' learning in traditional educational settings. [ABSTRACT FROM AUTHOR]

Objectives: The aim of the current study was to investigate the robustness of the human movement effect and its stability over time by comparing the effectiveness of dynamic and static presentations on acquisition and retention of a gross motor skill. Methods: One hundred and seven first‐year students studying for the certificate in Physical Education course were randomly divided into three groups: (i) static pictures (N = 32), (ii) enriched static pictures with arrows (N = 34), and (iii) video (N = 41). They were instructed to observe the demonstration of the Ippon‐Seoi‐Nage (a Judo technique) and reproduce it during the acquisition phase or after a delay of 1 week during the retention phase. Results and Conclusions: The results showed that enriched static pictures (with arrows) resulted in more efficient learning than the static pictures (without arrows). Most importantly, it was shown that learners receiving the video presentation outperformed learners receiving the static presentations, with regard to acquisition and retention, indicating therefore a robust human movement effect. Implications: These findings provide confirmation of the superiority of video presentations for teaching and learning motor skills involving the entire human body. Lay Description: What is already known about this topic:External visualizations are broadly used in Physical education (PE) and sport context.Static visualizations are regarded as the fundamental tools used by PE teachers to communicate visual information that is difficult to verbally describe.Increasing use of dynamic visualizations such as videos largely supplanted the use of static pictures in PE contextWhat this paper adds:Comparing the effectiveness of static pictures and digital videos in tactical learningExploring the human movement effect and its stability over timeImplications for practice and/or policy:The human movement effect is a robust phenomenon not only when it is evaluated immediately after the learning phase but also after a notable delay.Dynamic visualizations remain the most powerful computer‐based technique by which people can learn complex motor skills. [ABSTRACT FROM AUTHOR]

A promising method to support game‐based learning is to facilitate learners' externalization of cognitive and metacognitive processes. Externalizing Problem Representation (EPR) refers to a cognitive behaviour in which a learner constructs her own representations overtly. The purpose of this study is to investigate whether learning supports promoting EPR enhance qualitative understanding and quantitative proficiency in ratios and proportional relationships in a learning game (i.e., E‐Rebuild) context. Specifically, this study investigated the effects of representation format in problem representation on qualitative understanding and quantitative proficiency in a learning game context. The results of this study indicate that (a) symbolic learning supports better facilitate comprehension of math concepts and their relations than iconic learning supports in video game contexts, (b) symbolic learning supports better facilitate players' reflection for implicit understanding and promote their math problem‐solving skills, (c) participants in the symbolic learning support group increased significantly in qualitative understanding but not in quantitative proficiency after gameplay, and (d) participants in the iconic learning support group experienced significant growth in quantitative proficiency but not in qualitative understanding after gameplay. Lay Description: What is already known about this topic: Video games potentially facilitate implicit qualitative understanding more than quantitative knowledge test performance.Educational game designers lack a good understanding of the design and development of effective learning supports in educational games. What this paper adds: Symbolic learning supports for problem representation better facilitate comprehension of math concepts and their relations than iconic learning supports in video game contexts.Participants experienced significant growth in quantitative proficiency after they processed the iconic in‐game learning supports in game‐based math tasks.Participants' qualitative understanding in the symbolic learning support group increased significantly after playing E‐Rebuild‐based math game task. Implications for practice and/or policy: This study informs scholars and designers of game‐based learning about designing learning support and its properties in video game contexts: Learning support design to promote math problem representation across problem translation and problem integration.This study provides design principles for learning supports in math learning game; symbolic learning supports facilitate qualitative understanding whereas iconic learning supports facilitate quantitative proficiency in math learning game. [ABSTRACT FROM AUTHOR]