Robotic Construction Kits as Computational Manipulatives for Learning in the STEM Disciplines

Autor/inn/en	Sullivan, Florence R.; Heffernan, John
Titel	Robotic Construction Kits as Computational Manipulatives for Learning in the STEM Disciplines
Quelle	In: Journal of Research on Technology in Education, 48 (2016) 2, S.105-128 (24 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1539-1523
DOI	10.1080/15391523.2016.1146563
Schlagwörter	Robotics; Manipulative Materials; STEM Education; Elementary Secondary Education; Literature Reviews; Qualitative Research; Mixed Methods Research; Feedback (Response); Learning Processes; Problem Solving; Computation; Sequential Learning; Heuristics; Physics; Biology; Constructivism (Learning); Engineering; Design; Technology Uses in Education; Thinking Skills; Programming; Scientific Literacy; Abstract Reasoning + Suchen Sie Ihr Suchwort? Robotertechnik; Hilfsmittel; STEM; Qualitative Forschung; Learning process; Lernprozess; Problemlösen; Didaktische Sequenzierung; Lernsequenz; Heuristik; Physik; Biologie; Maschinenbau; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen; Denkfähigkeit; Programmierung; Abstraktes Denken; Denken
Abstract	This article presents a systematic review of research related to the use of robotics construction kits (RCKs) in P-12 learning in the STEM disciplines for typically developing children. The purpose of this review is to configure primarily qualitative and mixed methods findings from studies meeting our selection and quality criterion to answer the review question: How do robotic construction kits function as computational manipulatives in P-12 STEM education? Our synthesis of the literature has resulted in four key insights that are new to the field. First, RCKs have a unique double application: They may be used for direct instruction in robotics (first-order uses) or as analogical tools for learning in other domains (second-order uses). Second, RCKs make possible additional routes to learning through the provision of immediate feedback and the dual modes of representation unique to RCKs. Third, RCKs support a computational thinking learning progression beginning with a lower anchor of sequencing and finishing with a high anchor of systems thinking. And fourth, RCKs support evolving problem-solving abilities along a continuum, ranging from trial and error to heuristic methods associated with robotics study. Furthermore, our synthesis provides insight into the second-order (analogical) uses of RCKs as computational manipulatives in the disciplines of physics and biology. Implications for practice and directions for future research are discussed. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01