Gestures in Educational Behavior Coordination. Grounding an Enactive Robot-Assisted Approach to Didactics

Lehmann, Hagen; Rossi, Pier Giuseppe

doi:10.1007/978-3-030-46732-6_15

Cited by 3 publications

(6 citation statements)

References 62 publications

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“…Robot tutors should be able to properly analyse the user's reactions to instructional content, but they should also be able to comprehend the rapid and complicated social indicators that indicate task involvement, confusion, and attention (23). There is still not enough development for everyone, despite recent advancements in voice recognition and social signal processing (24). Speech recognition for young users, for example, is currently insufficiently robust for the majority of interactions (25).…”

Section: Technological Hurdles While Developing Robot Instructorsmentioning

confidence: 99%

Social Robots in Education for Long-Term Human-Robot Interaction : Socially Supportive Behaviour of Robotic Tutor for Creating Robo-Tangible Learning Environment in a Guided Discovery Learning Interaction

Alam¹

2022

ECS Trans.

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The article discusses the possible applications of social robots in education, the technological and pedagogical challenges they possess, and the ways in which they may affect learning outcomes, concentrating only on robots intended to assist students in learning via social interaction. Author has highlighted three significant research problems : 1) Does robot tutors help improve students’ learning outcomes? 2) Does appearance and behaviour of robots have a significant role to play on academic engagement of learners? 3) What could be the potential roles of a robot in an educational setting? A statistical meta-analysis of previously published research articles is used to substantiate author’s claims. The larger aim of this article is to provide effective groundwork for future research by describing the expected outcomes of using social robots to offer education and identifying potential research areas for further inquiry.

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Section: Technological Hurdles While Developing Robot Instructorsmentioning

confidence: 99%

Social Robots in Education for Long-Term Human-Robot Interaction : Socially Supportive Behaviour of Robotic Tutor for Creating Robo-Tangible Learning Environment in a Guided Discovery Learning Interaction

Alam¹

2022

ECS Trans.

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“…In this perspective it is no longer possible to distinguish between the content that is to be taught, the way this content is taught, as well as by whom and to whom it is taught. Lehmann and Rossi, 2020b) As Rossi (2011) points out, the role of the teacher in the enactive didactics approach is to raise the awareness of a problem in the students. This serves to activate a cognitive conflict in the students that connects the students' experiential knowledge with the new problem and the related new knowledge.…”

Section: Enactive Didacticsmentioning

confidence: 99%

“…As discussed in (Lehmann, 2020;Lehmann & Rossi, 2020a), the classic feedback is the teacher's response and correction to the questions and actions of the students. This feedback is based on the comparison between the results expected by the teacher, the results achieved by the student, and the ability of the teacher to identify the reason for any potential misalignment.…”

Section: The Role Of Feedback In Teaching and Learning Processesmentioning

confidence: 99%

“…This kind of approach can be sufficient when the result of the assignment is rigidly predefined. However, in the case of open results, the comments of the teacher need to be personalized, as they are strictly related to the choices and decisions of the students, and also need to involve the method that was used to arrive at the result (Lehmann, 2020).…”

Section: The Role Of Feedback In Teaching and Learning Processesmentioning

confidence: 99%

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Deep Understanding. Control of student understanding in university during distance and face-to-face learning

Marzano¹,

Miranda²,

Trinchero³

2021

Education Sciences and Society

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The health emergency of 2020 has led many university professors to wonder about how to check that the information presented in their lessons generates a correct conceptual representation in their students and, above all, to ask themselves if they have carried out the right training actions capable of triggering what is called deep understanding, that is a set of cognitive processes that produce durable and meaningful learning. This paper describes two experiences conducted in two different Italian universities that have been designed and implemented precisely with these objectives. The achieved results are very encouraging and could represent a starting point to reflect on the methodologies, teaching practices and tools to be used in distance and face-to-face university courses.

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“…For example, the iCat robot has been used to teach children to play chess [21] and the Keepon robot for robot-assisted therapy with children on the autistic spectrum [22,23]. Research with the NAO, RoboVie and Tiro humanoid robots have provided insights into the psychological dynamics characterizing social human-robot interaction (HRI) in educational settings [24]. However, multiple studies [25,26] have acknowledged a lack of understanding of the efficacy of humanoid robots in school learning environments (SLEs).…”

Section: Introductionmentioning

confidence: 99%

A Framework for Using Humanoid Robots in the School Learning Environment

et al. 2021

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With predictions of robotics and efficient machine learning being the building blocks of the Fourth Industrial Revolution, countries need to adopt a long-term strategy to deal with potential challenges of automation and education must be at the center of this long-term strategy. Education must provide students with a grounding in certain skills, such as computational thinking and an understanding of robotics, which are likely to be required in many future roles. Targeting an acknowledged gap in existing humanoid robot research in the school learning environment, we present a multidisciplinary framework that integrates the following four perspectives: technological, pedagogical, efficacy of humanoid robots and a consideration of the ethical implications of using humanoid robots. Further, this paper presents a proposed application, evaluation and a case study of how the framework can be used.

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Gestures in Educational Behavior Coordination. Grounding an Enactive Robot-Assisted Approach to Didactics

Cited by 3 publications

References 62 publications

Social Robots in Education for Long-Term Human-Robot Interaction : Socially Supportive Behaviour of Robotic Tutor for Creating Robo-Tangible Learning Environment in a Guided Discovery Learning Interaction

Social Robots in Education for Long-Term Human-Robot Interaction : Socially Supportive Behaviour of Robotic Tutor for Creating Robo-Tangible Learning Environment in a Guided Discovery Learning Interaction

Deep Understanding. Control of student understanding in university during distance and face-to-face learning

A Framework for Using Humanoid Robots in the School Learning Environment

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