Teaching Machine Learning in Robotics Interactively: The Case of Reinforcement Learning with Lego® Mindstorms

Autor/inn/en	Martínez-Tenor, Ángel; Cruz-Martín, Ana; Fernández-Madrigal, Juan-Antonio
Titel	Teaching Machine Learning in Robotics Interactively: The Case of Reinforcement Learning with Lego® Mindstorms
Quelle	In: Interactive Learning Environments, 27 (2019) 3, S.293-306 (14 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Martínez-Tenor, Ángel) ORCID (Cruz-Martín, Ana) ORCID (Fernández-Madrigal, Juan-Antonio)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1049-4820
DOI	10.1080/10494820.2018.1525411
Schlagwörter	Teaching Methods; Robotics; Masters Programs; Reinforcement; Decision Making; Interaction; Educational Technology; Technology Uses in Education; Graduate Students; Student Attitudes; Teacher Attitudes; Foreign Countries; Spain + Suchen Sie Ihr Suchwort? Teaching method; Lehrmethode; Unterrichtsmethode; Robotertechnik; Magister course; Magisterstudiengang; Positive Verstärkung; Decision-making; Entscheidungsfindung; Interaktion; Unterrichtsmedien; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen; Graduate Study; Student; Students; Aufbaustudium; Graduiertenstudium; Hauptstudium; Studentin; Schülerverhalten; Lehrerverhalten; Ausland; Spanien
Abstract	Preparing students for dealing with a world more and more densely populated with physical machines that possess learning capabilities, e.g. intelligent robots, is of the utmost importance in engineering. In this paper, we describe and analyse a design of interactive sessions devoted to the application of some machine learning (ML) methods within a master degree subject named "Cognitive Robotics", in particular, reinforcement learning (RL), a technique that allows the machine to autonomously learn decision-making in a physical environment. The paper contains a complete depiction of the interactive teaching sessions, implemented with reasonable cost and resources thanks to a suitable mixture of the constructivist and instructivist paradigms. It also gathers the experiences of students and teachers through both qualitative and quantitatively indicators. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01