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Journal of Science Education and Technology
Erschienen in: Journal of Science Education and Technology 1/2018

29.08.2017

How Does the Degree of Guidance Support Students’ Metacognitive and Problem Solving Skills in Educational Robotics?

verfasst von: Soumela Atmatzidou, Stavros Demetriadis, Panagiota Nika

Erschienen in: Journal of Science Education and Technology | Ausgabe 1/2018

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Abstract

Educational robotics (ER) is an innovative learning tool that offers students opportunities to develop higher-order thinking skills. This study investigates the development of students’ metacognitive (MC) and problem-solving (PS) skills in the context of ER activities, implementing different modes of guidance in two student groups (11–12 years old, N1 = 30, and 15-16 years old, N2 = 22). The students of each age group were involved in an 18-h group-based activity after being randomly distributed in two conditions: “minimal” (with minimal MC and PS guidance) and “strong” (with strong MC and PS guidance). Evaluations were based on the Metacognitive Awareness Inventory measuring students’ metacognitive awareness and on a think-aloud protocol asking students to describe the process they would follow to solve a certain robot-programming task. The results suggest that (a) strong guidance in solving problems can have a positive impact on students’ MC and PS skills and (b) students reach eventually the same level of MC and PS skills development independently of their age and gender.
Vorheriger Artikel The Development of an Instrument to Measure the Project Competences of College Students in Online Project-Based Learning
Nächster Artikel Missed Opportunities for Science Learning: Unacknowledged Unscientific Arguments in Asynchronous Online and Face-to-Face Discussions

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Literatur
Akin, A., Abaci, R., & Çetin, B. (2007). The validity and reliability of the Turkish version of the metacognitive awareness inventory. Educational Sciences: Theory & Practice, 7(2), 671–678.
Alimisis, D. (2009). Teacher education on robotics-enhanced constructivist pedagogical methods. Αthens: School of Pedagogical and Technological Education.
Alimisis, D. (2014). Educational robotics in teacher education: An innovative tool for promoting quality Educatio. In L. Daniela, I. Lūka, L. Rutka, & I. Žogla (Eds.), Teacher of the 21st Century: Quality Education for Quality Teaching (pp. 14–27). Cambridge: Cambridge scholars publishing.
Anewalt, K. (2002). Experiences teaching writing in a computer science course for the first time. Journal of Computing Sciences in Colleges, 18(2), 346–355.
Atmatzidou, S., & Demetriadis, S. N. (2012). Evaluating the role of collaboration scripts as group guiding tools in activities of educational robotics: Conclusions from three case studies. In IEEE 12th International Conference on Advanced Learning Technologies (ICALT), 2012 (pp. 298-302).
Atmatzidou, S., & Demetriadis, S. (2016). Advancing students’ computational thinking skills through educational robotics: A study on age and gender relevant differences. Robot Auton Syst, 75, 661–670.CrossRef
Atmatzidou, S., Markelis, I., & Demetriadis, S. (2008). The use of LEGO Mindstorms in elementary and secondary education: Game as a way of triggering learning. In Workshop Proceedings of International Conference on Simulation, Modelling, and Programming for Autonomous Robots (pp. 22-30).
Barkley, E. F., Cross, K. P., & Major, C. H. (2014). Collaborative learning techniques: A handbook for college faculty. Hoboken: John Wiley & Sons.
Barrows, H. S. (1996). Problem-based learning in medicine and beyond: A brief overview. New directions for teaching and learning, 1996(68), 3–12.CrossRef
Benitti, F. B. V. (2012). Exploring the educational potential of robotics in schools: A systematic review. Comput Educ, 58(3), 978–988.CrossRef
Bers, M. U. (2007). Project InterActions: A multigenerational robotic learning environment. J Sci Educ Technol, 16(6), 537–552.CrossRef
Bers, M. U., Flannery, L., Kazakoff, E. R., & Sullivan, A. (2014). Computational thinking and tinkering: Exploration of an early childhood robotics curriculum. Comput Educ, 72, 145–157.CrossRef
Blanchard, S., Freiman, V., & Lirrete-Pitre, N. (2010). Strategies used by elementary schoolchildren solving robotics-based complex tasks: Innovative potential of technology. Procedia-SocialandBehavioral Sciences, 2(2), 2851–2857.CrossRef
Brown, A. L. (1978). Knowing when, where, and how to remember: A problem of metacognition. In R. Glaser (Ed.), Advances in instructional psychology (pp. 77–165). Hillsdale: Erlbaum.
Çalik, M., Özsevgeç, T., Ebenezer, J., Artun, H., & Küçük, Z. (2014). Effects of ‘environmental chemistry’ elective course via technology-embedded scientific inquiry model on some variables. J Sci Educ Technol, 23(3), 412–430.CrossRef
Çalik, M., Ebenezer, J., Özsevgeç, T., Küçük, Z., & Artun, H. (2015). Improving science student teachers’ self-perceptions of fluency with innovative technologies and scientific inquiry abilities. J Sci Educ Technol, 24(4), 448–460.CrossRef
Castledine, A. R., & Chalmers, C. (2011). LEGO robotics: An authentic problem solving tool? Design and Technology Education, 16(3), 19–27.
Chi, M. T., & Bassok, M. (1989). Learning from examples via self-explanations. In L.B. Resnick (Ed.), Knowing, learning, and instruction: Essays in honor of Robert Glaser (pp. 251–282). Hillsdale: Erlbaum.
Chin, C., & Brown, D. E. (2000). Learning in science: A comparison of deep and surface approaches. J Res Sci Teach, 37(2), 109–138.CrossRef
Dennison, R. S. (1997). Relationships among measures of metacognitive monitoring. In annual meeting of the American Educational Association, Chicago, IL.
Druin, A., & Hendler, J. A. (2000). Robots for kids: Exploring new technologies for learning. San Francisco: Morgan Kaufmann.
Du Toit, S., & Kotze, G. (2009). Metacognitive strategies in the teaching and learning of mathematics. Pythagoras, 2009(70), 57–67.
Eguchi, A. (2014, July). Robotics as a learning tool for educational transformation.In Proceeding of 4th International Workshop Teaching Robotics, Teaching with Robotics & 5th International Conference Robotics in Education Padova (Italy).
Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive–developmental inquiry. Am Psychol, 34(10), 906.CrossRef
Fülöp, E. (2015). Teaching problem-solving strategies in mathematics. LUMAT (2013–2015 Issues), 3(1), 37–54.
Gama, C. (2004). Metacognition in interactive learning environments: The reflection assistant model, In Intelligent Tutoring Systems (pp. 668–677). Berlin: Springer.
Gaudiello, I., & Zibetti, E. (2013). Using control heuristics as a means to explore the educational potential of robotics kits. Themes in Science and Technology Education, 6(1), 15–28.
Goos, M., & Galbraith, P. (1996). Do it this way! Metacognitive strategies in collaborative mathematical problem solving. Educ Stud Math, 30(3), 229–260.CrossRef
Gura, M. (2007). In K. King & M. Gura (Eds.), Classroom robotics: Case stories of 21st century instruction for millennial students (pp. 11–31). Charlotte: Information age publishing.
Huang, L., Varnado, T., & Gillan, D. (2014).Exploring reflection journals and self-efficacy in robotics education. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting (Vol. 58, no. 1, pp. 1939-1943).SAGE publications.
Hussain, S., Lindh, J., & Shukur, G. (2006). The effect of LEGO training on pupils' school performance in mathematics, problem solving ability and attitude: Swedish data. Educational Technology & Society, 9(3), 182–194.
Ishii, N., Suzuki, Y., Fujiyoshi, H., Fujii, T., &Kozawa, M. (2006). A framework for designing learning environments fostering creativity. In A. Mendez-Vilas, A. Solano Martın, J.A. Mesa Gonzalez, & J. Mesa Gonzalez (Eds.), Current developments in technology-assisted education (pp. 228–232). Badajoz: Formatex. 
Jacobse, A. E., & Harskamp, E. G. (2012). Towards efficient measurement of metacognition in mathematical problem solving. Metacognition and Learning, 7(2), 133–149.CrossRef
Jonassen, D. H. (2000). Toward a design theory of problem solving. Educ Technol Res Dev, 48(4), 63–85.CrossRef
Keren, G., & Fridin, M. (2014). Kindergarten social assistive robot (KindSAR) for children’s geometric thinking and metacognitive development in preschool education: A pilot study. Comput Hum Behav, 35, 400–412.CrossRef
Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educ Psychol, 41(2), 75–86.CrossRef
Kramarski, B., & Mevarech, Z. R. (1997). Cognitive-metacognitive training within a problem-solving based logo environment. Br J Educ Psychol, 67(4), 425–445.CrossRef
La Paglia, F., Caci, B., La Barbera, D., & Cardaci, M. (2010). Using robotics construction kits as metacognitive tools: A research in an Italian primary school. Studies in Health Technology and Informatics, 154, 110–114.
La Paglia, F., Rizzo, R., & La Barbera, D. (2011). Use of robotics kits for the enhancement of metacognitive skills of mathematics: A possible approach. Studies in Health Technology and Informatics, 167, 26–30.
Lai, K. W. (1990). Problem solving in a Lego-logo learning environment: Cognitive and metacognitive outcomes, Computers in Education (pp. 403–408). Amsterdam: Elsevier.
Lai, K. W. (1993). Lego-logo as a learning environment. J Comput Child Educ, 4(3), 229–245.
Leonard, J., Buss, A., Gamboa, R., Mitchell, M., Fashola, O. S., Hubert, T., & Almughyirah, S. (2016). Using robotics and game design to enhance Children’s self-efficacy, STEM attitudes, and computational thinking skills. J Sci Educ Technol, 25(6), 860–876.CrossRef
Lin, C. H., & Liu, E. Z. F. (2011). A pilot study of Taiwan elementary school students learning motivation and strategies in robotics learning. In International Conference on Technologies for E-Learning and Digital Entertainment (pp. 445–449). Springer Berlin Heidelberg.
Lorenzo, M. (2005). The development, implementation, and evaluation of a problem solving heuristic. Int J Sci Math Educ, 3(1), 33–58.CrossRef
Martin, K. J., Chrispeels, J. H., & D'Emidio-Caston, M. (1998). Exploring the use of problem-based learning for developing collaborative leadership skills. Journal of School Leadership, 8, 470–500.
McWhorter, W. (2008). The effectiveness of using LEGO Mindstorms robotics activities to influence self-regulated learning in a university introductory computer programming course.(doctoral dissertation).University of NorthTexas.
Miller, P. H., Kessel, F. S., & Flavell, J. H. (1970). Thinking about people thinking about people thinking about...: A study of social cognitive development. Child Development, 41(3), 613–623.
Nosratinia, M., Saveiy, M., & Zaker, A. (2014). EFL learners' self-efficacy, metacognitive awareness, and use of language learning strategies: How are they associated? Theory and Practice in Language Studies, 4(5), 1080.CrossRef
Panaoura, A., & Philippou, G. (2003). The construct validity of an inventory for the measurement of young Pupils' metacognitive abilities in mathematics. International Group for the Psychology of Mathematics Education, 3, 437–444.
Papadopoulos, P. M., Demetriadis, S. N., Stamelos, I. G., & Tsoukalas, I. A. (2011). The value of writing-to-learn when using question prompts to support web-based learning in ill-structured domains. Educ Technol Res Dev, 59(1), 71–90.CrossRef
Papert, S. (1991). Situating constructionism. In S. Papert & I. Harel (Eds.), Constructionism (pp. 1–11). Norwood: Ablex Publishing.
Polya, G. (1945). How to solve it: A new aspect of mathematical model. New Jersey: Princeton University Press.
Pugalee, D. K. (2001). Writing, mathematics, and metacognition: Looking for connections through students' work in mathematical problem solving. Sch Sci Math, 101(5), 236–245.CrossRef
Rusk, N., Resnick, M., Berg, R., & Pezalla-Granlund, M. (2008). New pathways into robotics: Strategies for broadening participation. J Sci Educ Technol, 17(1), 59–69.CrossRef
Schmidt, H. G., Loyens, S. M., Van Gog, T., & Paas, F. (2007). Problem-based learning is compatible with human cognitive architecture: Commentary on Kirschner, Sweller, and Clark (2006). Educ Psychol, 42(2), 91–97.CrossRef
Schoenfeld, A. H. (1992). Learning to think mathematically: Problem solving, metacognition, and sense making in mathematics. In D. A. Grouws (Ed.), Handbook of research on mathematics teaching and learning (pp. 334–370). New York: Macmillan. 
Schraw, G., & Dennison, R. S. (1994). Assessing metacognitive awareness. Contemp Educ Psychol, 19(4), 460–475.CrossRef
Siegel, M. A. (2012). Filling in the distance between us: Group metacognition during problem solving in a secondary education course. J Sci Educ Technol, 21(3), 325–341.CrossRef
Sperling, R. A., Howard, B. C., Staley, R., & DuBois, N. (2004). Metacognition and self-regulated learning constructs. Educ Res Eval, 10(2), 117–139.CrossRef
Stillman, G. A., & Galbraith, P. L. (1998). Applying mathematics with real world connections: Metacognitive characteristics of secondary students. Educ Stud Math, 36(2), 157–194.CrossRef
Sweller, J., Kirschner, P. A., & Clark, R. E. (2007). Why minimally guided teaching techniques do not work: A reply to commentaries. Educ Psychol, 42(2), 115–121.CrossRef
Lo Ting-kau. (1992). Lego TC logo as a learning environment in problem- solving in advanced supplementary level design & technology with pupils aged 16–19.(Master’s thesis).University of Hong Kong, Pokfulam.
Turner, S., & Hill, G. (2007). Robots in problem-solving and programming. In 8th Annual Conference of the Subject Centre for Information and Computer Sciences (pp. 82–85).
Van der Stel, M., & Veenman, M. V. (2010). Development of metacognitive skillfulness: A longitudinal study. Learn Individ Differ, 20(3), 220–224.CrossRef
Vickers, A. J. (2005). Parametric versus non-parametric statistics in the analysis of randomized trials with non-normally distributed data. BMC medical research methodology, 5(1), 35.CrossRef
Metadaten
Titel
How Does the Degree of Guidance Support Students’ Metacognitive and Problem Solving Skills in Educational Robotics?
verfasst von
Soumela Atmatzidou
Stavros Demetriadis
Panagiota Nika
Publikationsdatum
29.08.2017
Verlag
Springer Netherlands
Erschienen in
Journal of Science Education and Technology / Ausgabe 1/2018
Print ISSN: 1059-0145
Elektronische ISSN: 1573-1839
DOI
https://doi.org/10.1007/s10956-017-9709-x

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