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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]

Background: The increased availability of immersive virtual reality (IVR) has led to a surge of immersive technology applications in education. Nevertheless, very little is known about how to effectively design instruction for this new media, so that it would benefit learning and associated cognitive processing. Objectives: This experiment explores if and how traditional instructional design principles from 2D media translate to IVR. Specifically, it focuses on studying the underlying mechanisms of the redundancy‐principle, which states that presenting the same information concurrently in two different sensory channels can cause cognitive overload and might impede learning. Methods: A total of 73 participants learned through a specifically‐designed educational IVR application in three versions: (1) auditory representation format, (2) written representation format, and (3) a redundancy format (i.e. both written and auditory formats). The study utilized advanced psychophysiological methods of Electroencephalography (EEG) and eye‐tracking (ET), learning measures and self‐report scales. Results and Conclusions: Results show that participants in the redundancy condition performed equally well on retention and transfer post‐tests. Similarly, results from the subjective measures, EEG and ET suggest that redundant content was not found to be more cognitively demanding than written content alone. Implications: Findings suggest that the redundancy effect might not generalize to VR as originally anticipated in 2D media research, providing direct implications to the design of IVR tools for education. Lay Description: What is currently known about the topic: Immersive virtual reality (IVR) applications for learning are on the rise, yet little is known about how to effectively design this medium to impact learning and cognition.Even in IVR, many use traditional learning content of text and audio, and ground instructional design decisions in 2D media design guidelines, such as the Redundancy Principle.Redundancy principle states that presenting the same information concurrently in two different sensory channels can cause cognitive overload and might impede learning. What this paper adds to the field: This study examines if and how the Redundancy Principle translates from traditional 2D media to immersive VR.EEG, Eye‐tracking and objective measures were used to study the underlying mechanisms of redundant information processing. The implications of study findings for practitioners: Results show that the redundancy effect might not generalize to VR as originally anticipated in 2D media research.Study shows that the redundancy group performed equally well on learning outcomes and it wasn't found to be more cognitively loading.The study is amongst the first to reveal that participants spend most of their time reading in the redundancy condition. [ABSTRACT FROM AUTHOR]

In the increasing pervasiveness of today's digital society, mobile devices are changing the face of education. Students can interact with mobile devices in context‐aware environment. This paper presents a mobile application based on expert system (Plant‐E) for students to acquire knowledge about plant classification by answering decision‐making questions. In order to study effectiveness of Plant‐E and cognitive load of students who experience different kinds of interaction in learning process, another mobile application (Plant‐G) only providing information pages of plants was developed. A quasi‐experiment was conducted with three classes of 137 seventh graders. The three classes, Class A with 46 students using Plant‐E in campus, Class B with 44 students using Plant‐G in campus, and Class C with 47 students using Plant‐G in a traditional classroom, constitute three groups with different interaction complexity. The research conducted pretest, posttest, and delayed test to evaluate learning performance of students in three classes and used a questionnaire to investigate their perceptions and attitudes towards proposed system. Results show that interaction complexity has an impact on students' learning performance and mental effort in mobile learning; the higher the interaction complexity is, the higher mental effort and the better learning performance in mobile learning will be. Lay Description: What is already known about this topic: Mobile devices can be used to meet the urgency of learning need and can provide guidance and clues for learners in context‐aware environment.During mobile learning in context‐aware environment, students need to interact with mobile devices and environment.Mental effort reflects cognitive load related to interaction complexity, and it can affect learning performance.Self‐efficacy affects the degree of mental effort by affecting the firmness of performance goal.Cognitive load and learning performance are the main concerns that need to be considered when evaluating the effectiveness of mobile learning. What this paper adds: Interaction complexity has an impact on students' learning performance and mental effort in mobile learning.In terms of the three levels of interaction complexity in this study, the higher the interaction complexity is, the better the results that students will get in mobile learning.The higher the interaction complexity is, the higher the mental effort that students invested into in mobile learning would be.The medium self‐efficacy group invested the most mental effort and got the best grades, rather than the high or low group.Rule‐based mobile learning expert system is feasible and effective for students to learn by interacting with learning objects in context‐aware environment. Implications for practice and/or policy: Efforts should be made to make mobile learning systems more interactive; for example, learners can learn more effectively by interacting with mobile system, which can improve the frequency of observing learning objects.Rule‐based mobile learning expert system can give learners more opportunities to know how experts do when solving problems and can provide a potential method for students to learn in context‐aware environment. [ABSTRACT FROM AUTHOR]

The present study investigates affective‐motivational, attention, and learning effects of unexplored emotional design manipulation: Contextual animation (animation of contextual elements) in multimedia learning game (MLGs) for children. Participants (N = 134; Mage = 9.25; Grades 3 and 4) learned either from an experimental version of the MLG with a high amount of contextual animation or from an identical MLG with no contextual animation (control). Children strongly preferred (χ2 = 87.04, p <.001) and found the experimental version more attractive (p <.001, d = −1.11). No significant differences in overall enjoyment and learning outcomes were found. Attention differences, measured by dwell times and fixation durations, were small and reached only borderline significance (p =.035; d = −0.39). The implication is that contextual animation in MLG for children increases such instructional materials' attractiveness without compromising cognitive processes needed for learning; however, it does not lead to their higher instructional efficiency. Lay Description: What is already known about this topic: Contextual animation is frequently used in multimedia learning games (MLGs) for children.Contextual animation is understood to be non‐expository picture motion, which can be added to already existing representational pictures that provide context for target instruction.It is not known whether or not contextual animation, which embellishes already existing representational contextual pictures, harms learning for children in the case of MLGs. What this paper adds: Children (Grades 3 and 4) strongly prefer the game with added contextual animation compared to the game without it.No between‐group differences in overall learning enjoyment and learning outcomes were found.Small attention‐allocation effects of borderline significance were detected. Implications for practice Adding contextual animation (i.e., added non‐expository picture motion) to multimedia learning games for children will increase the attractiveness of the materials and will not hamper learning. Investment into the production of costly contextual animation may be worthwhile in the case of instructional games intended for uncontrolled settings (e.g., at home or during leisure time). In formal contexts (e.g., school), it is less clear whether investment into contextual animation is needed, since children are extraneously motivated to learn and animation does not appear to enhance learning outcomes. [ABSTRACT FROM AUTHOR]

Many researchers argue that students must be meaningfully engaged in the learning resources for effective learning to occur. However, current online learners still report a problematic lack of attractive and challenging learning resources that engage them in the learning process. This endemic problem is even more evident in online collaborative learning approaches whose resources lack of authentic interactivity, user empowerment, social identity and challenge, thus having a negative effect on learners' self-motivation and engagement. To overcome these and other limitations and deficiencies, in this paper, a new type of learning resource named Collaborative Complex Learning Resources ( CC-LR) is presented based on the virtualization of collaborative learning with the aim of leveraging knowledge elicited during live sessions. During the CC-LR execution, the collaborative sessions are animated so learners can observe how avatars discuss and collaborate, how discussion threads grow and how knowledge is been constructed, refined and consolidated. In addition, complex aspects of the learning process can be incorporated in the CC-LRs during their creation, such as cognitive assessment and emotional awareness. The system produced from this research is tested to evaluate the CC-LR enriched with complex information and analyze its effects in the discussion process. The research reported in this paper was undertaken within the Seventh Framework Programme ( FP7) European project called ' Adaptive Learning via Intuitive/ Interactive, Collaborative and Emotional systems'. [ABSTRACT FROM AUTHOR]

Recent government moves in many countries have seen coding included in school curricula, or promoted as part of computing, mathematics or science programmes. While these moves have generally been associated with a need to engage more young people in technology study, research has hinted at possible benefits from learning to program including fostering general thinking skills. However, little research has been carried out exploring these ideas. This study analysed data collected while 5- and 6-year-old students in a New Zealand primary school were using Scratch Jnr. to learn about basic shapes, as part of a numeracy topic. Analysis combined Brennan and Resnick's (2012) computational thinking skills framework and Krathwohl's (2002) revision of Bloom's Taxonomy to evaluate any role general thinking skills played in these students' coding work. Results suggest including basic coding in primary curricula provides teachers with an effective means of exercising their students' general and higher order thinking skills. They build on Brennan and Resnick's (2012) framework by including conceptualization as an important element in students' computational work and highlight the role of predictive thinking in debugging code. Findings support historical arguments that more needs to be done to investigate students' cognitive processes when undertaking computational work. Lay description What is already known about the topic: Computational learning is an emerging area of school curricula;, Limited research exists exploring thinking processes within computational learning;, Early studies challenge more recent claims of thinking skill transfer from computational work., What this paper adds: Computational work supports a range of general and higher order thinking skills;, Task design and teacher skills are critical to achieving higher order thinking outcomes from computational work;, Computational work in teams can support collaborative, cooperative and self-management key competencies., Implications for practice and/or policy: Findings broaden the base of empirical support for including computational work in school curricula;, Coding provides an engaging means of exercising complex thinking skills and key competencies in students;, The data methods used provide teachers with visible evidence of students' thinking processes during computational work. [ABSTRACT FROM AUTHOR]