Micro:bit Robotics Course: Infusing Logical Reasoning and Problem-Solving Ability in Fifth Grade Students Through an Online Group Study System

  • Po-Jen Cheng Dep. of Computer Science and Information Engineeing, National Chung Cheng University
  • Yuan-Hsun Liao Master Program of Digital Innovation, Tunghai University, Taiwan
  • Pao-Ta Yu Dep. of Computer Science and Information Engineeing, National Chung Cheng University
Keywords: logical reasoning, problem solving, micro:bit robot, gender difference, STEAM

Abstract

With rising societal interest in the subject areas of science, technology, engineering, art and mathematics (STEAM), a micro:bit robotics course with an online group study (OGS) system was designed to foster student learning anytime and anywhere. OGS enables the development of a learning environment that combines real-world and digital-world resources, and can enhance the effectiveness of learning among students from a remote area. In this pre- and post-test experiment design, we studied 22 (8 males and 14 females) 5th grade students from a remote area of Taiwan. A t test performed before and after the robotics course showed a positive increase in students’ proportional reasoning, probabilistic reasoning, and ability to analyze a problem. Results also revealed a gender difference in the association between students’ logical reasoning and problem-solving ability.

Author Biographies

Po-Jen Cheng, Dep. of Computer Science and Information Engineeing, National Chung Cheng University

Po-Jen Cheng received the PhD degree in the Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, Taiwan, in 2020. He has been with the computer science teacher of Da Ciao Elementary School, Tainan, Taiwan. His research interests include e-learning and computer education.

Yuan-Hsun Liao, Master Program of Digital Innovation, Tunghai University, Taiwan

Yuan-Hsun Liao received the Master of Engineering degree from Tunghai University, Taichung, Taiwan, in 2006, and the Ph.D. degree in computer science from National Chung Cheng University, Chia-Yi, Taiwan, in 2013. His research interests include machine learning, image processing, education application, and e-Learning.

Pao-Ta Yu, Dep. of Computer Science and Information Engineeing, National Chung Cheng University

Pao-Ta Yu received the PhD degree in electrical engineering from Purdue University, West Lafayette, IN, U.S.A., in 1989. Since 1990, he has been with the Department of Computer Science and Information Engineering at National Chung Cheng University, Chiayi, Taiwan, where he is currently a professor. His research interests include e-Learning, m-Learning, neural networks and fuzzy systems, ecommerce, web services, and semantic web.

References

Arlin, P. K. (1975). Cognitive development in adulthood: A fifth stage? Developmental Psychology, 11(5), 602–606. https://doi.org/10.1037/0012-1649.11.5.602

Axten, N., Newell, A., & Simon, H. A. (1973). Human problem solving. Contemporary sociology , 2(2), 169-170. https://doi.org/10.2307/2063712

Bers, M. U. (2012). Designing digital experiences for positive youth development: From playpen to playground. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199757022.001.0001

Birkerts., S. (1994). The Gutenberg elegies: The fate of reading in an electronic age. Faber and Faber.

Bitner, B. L. (1991). Formal operational reasoning modes: Predictors of critical thinking abilities and grades assigned by teachers in science and mathematics for students in grades nine through twelve. Journal of Research in Science Teaching, 28(3), 265–274. https://doi.org/10.1002/tea.3660280307

Bolter, J., & Grusin, R. (2000). Remediation: Understanding new media. The MIT Press.

Bransford, J., & Stein, B. S. (1984). The ideal problem solver: A guide for improving thinking, learning, and creativity. Freeman.

British Broadcasting Corporation. (2017, July 7). BBC micro:bit celebrates huge impact in first year, with 90% of students saying it helped show that anyone can code. https://www.bbc.co.uk/mediacentre/latestnews/2017/microbit-first-year

Chiappetta, E. L. (1976). A review of Piagetian studies relevant to science instruction at the secondary and college level. Science Education, 60(2), 253–261. https://doi.org/10.1002/sce.3730600215

Cohen, J.. (1988). Statistical power analysis for the behavioral sciences. New York, NY: Routledge Academic [Google Scholar] http://www.utstat.toronto.edu/~brunner/oldclass/378f16/readings/CohenPower.pdf

Conradty, C., & Bogner, F. X. (2018). From STEM to STEAM: How to monitor creativity. Creativity Research Journal, 30(3), 233–240. https://doi.org/10.1080/10400419.2018.1488195

Dewey, J. (1910). How we think. D. C. Heath. https://doi.org/10.1037/10903-000

Farrell, M. A. (1969). The formal stage: A review of the research. Journal of Research and Development in Education, 3, 111–118.

Flavell, J. H. (2007). The developmental psychology of Jean Piaget. D. Van Nostrand Company. https://doi.org/10.1037/11449-000

Gagné, R. M. (1985). The conditions of learning and theory of instruction. Holt, Rinehart and Winston.

Hacıömeroğlu, G., & Hacıömeroğlu, E. S. (2017). Examining the relationship between gender, spatial ability, logical reasoning ability, and preferred mode of processing. Adıyaman Üniversitesi Eğitim Bilimleri Dergisi, 7(1), 116–131. https://doi.org/10.17984/adyuebd.310833

Huang, Y. M., Chiu, P. S., Liu, T. C., & Chen, T. S. (2011). The design and implementation of a meaningful learning-based evaluation method for ubiquitous learning. Computers and Education, 57(4), 2291–2302. https://doi.org/10.1016/j.compedu.2011.05.023

Huang, Y. M., Huang, Y. M., Liu, C. H., & Tsai, C. C. (2013). Applying social tagging to manage cognitive load in a Web 2.0 self-learning environment. Interactive Learning Environments, 21(3), 273–289. https://doi.org/10.1080/10494820.2011.555839

Huang, Y. M., & Wu, T. T. (2011). A systematic approach for learner group composition utilizing u-learning portfolio. Educational Technology and Society, 14(3), 102–117. https://doi.org/10.1049/cp.2010.0563

Jung, I. (2012). Asian learners’ perception of quality in distance education and gender differences. The International Review of Research in Open and Distributed Learning, 13(2), 1–25. https://doi.org/10.19173/irrodl.v13i2.1159

Khine, M. S. (2017). Robotics in STEM education: Redesigning the learning experience. Springer. https://doi.org/10.1007/978-3-319-57786-9

Kuhn, D. (1991). The skills of argument. Cambridge University Press. https://doi.org/10.1017/cbo9780511571350

Lawson, A. E. (1978). The development and validation of a classroom test of formal reasoning. Journal of Research in Science Teaching, 15(1), 11–24. https://doi.org/10.1002/tea.3660150103

Lawson, A. E., Adi, H., & Karplus, R. (1979). Development of correlational reasoning in secondary schools: Do biology courses make a difference? The American Biology Teacher, 41(7), 420–430. https://doi.org/10.2307/4446678

Lin, Y.-C., Lin, Y.-T., & Huang, Y.-M. (2011). Development of a diagnostic system using a testing-based approach for strengthening student prior knowledge. Computers & Education, 57, 1557–1570. https://doi.org/10.1016/j.compedu.2011.03.004

Lin, Y.-T., Huang, Y.-M., & Cheng, S.-C. (2010). An automatic group composition system for composing collaborative learning groups using enhanced particle swarm optimization. Computers & Education, 55(4), 1483–1493. https://doi.org/https://doi.org/10.1016/j.compedu.2010.06.014

Liu, H., Ludu, M., & Holton, D. (2015). Can K–12 math teachers train students to make valid logical reasoning? In X. Ge, D. Ifenthaler, & J. Spector (Eds.) Emerging technologies for STEAM education (pp. 331–353). Springer. https://doi.org/10.1007/978-3-319-02573-5_18

Liu, Z. (2005). Reading behavior in the digital environment: Changes in reading behavior over the past ten years. Journal of Documentation, 61(6), 700–712. https://doi.org/10.1108/00220410510632040

Lovell, K. (1961). A follow‐up study of inhelder and Piaget’s: The growth of logical thinking. British Journal of Psychology, 52(2), 143–153. https://doi.org/10.1111/j.2044-8295.1961.tb00776.xMicro:bit. (n.d.). Let’s code. https://microbit.org/code/

O’Hara, K., & Sellen, A. (1997, March). Comparison of reading paper and on-line documents. In CHI ’97: Proceedings of the ACM SIGCHI conference on human factors in computing systems (pp. 335–342). https://doi.org/10.1145/258549.258787

Peters, O. (2000). Digital learning environments: New possibilities and opportunities. The International Review of Research in Open and Distributed Learning, 1(1). https://doi.org/10.19173/irrodl.v1i1.3

Preacher, K. J. (2002, May). Calculation for the test of the difference between two independent correlation coefficients [Computer software]. Available from http://quantpsy.org.

Remmele, B., & Holthaus, M. (2013). De-gendering in the use of e-learning. The International Review of Research in Open and Distributed Learning, 14(3), 27–42. https://doi.org/10.19173/irrodl.v14i3.1299

Roberge, J. J., & Craven, P. A. (1982). Developmental relationships between reading comprehension and deductive reasoning. The Journal of General Psychology, 107(1), 99–105. https://doi.org/10.1080/00221309.1982.9709912

Sentance, S., Waite, J., Hodges, S., MacLeod, E., & Yeomans, L. (2017, March). “Creating cool stuff”: Pupils’ experience of the BBC micro:bit. In SIGCSE '17: Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education (pp. 531–536). https://doi.org/10.1145/3017680.3017749

Siegler, R. S. (1991). Children’s thinking (2nd ed.). Prentice-Hall.

Sullivan, A., Strawhacker, A., & Bers, M. U. (2017). Dancing, drawing, and dramatic robots: Integrating robotics and the arts to teach foundational STEAM concepts to young children. In M. Khine (Ed.), Robotics in STEM education: Redesigning the learning experience (pp. 231–260). Springer. https://doi.org/10.1007/978-3-319-57786-9_10

Sungur, S., & Tekkaya, C. (2003). Students’ achievement in human circulatory system unit: The effect of reasoning ability and gender. Journal of Science Education and Technology, 12(1), 59–64. https://doi.org/10.1023/A:1022111728683

Tobin, K., & Capie, W. (1984). Application of the Test of Logical Thinking. Journal of Science and Mathematics Education in Southeast Asia, 7(1), 5–9.

United Nations Educational Scientific and Cultural Organization. (n.d.). Education: From disruption to recovery. https://en.unesco.org/covid19/educationresponse

Valanides, N. C. (1996). Formal reasoning and science teaching. School Science and Mathematics, 96(2), 99–107. https://doi.org/10.1111/j.1949-8594.1996.tb15818.x

Valanides, N. C. (1997). Cognitive abilities among twelfth‐grade students: Implications for science teaching. Educational Research and Evaluation, 3, 160–186. https://doi.org/10.1080/1380361970030204

Voogt, J., Erstad, O., Dede, C., & Mishra, P. (2013). Challenges to learning and schooling in the digital networked world of the 21st century. Journal of Computer Assisted Learning, 29(5), 403–413. https://doi.org/10.1111/jcal.12029

Wright, B., & Dowker, A. (2002). The role of cues to differential absolute size in children’s transitive inferences. Journal of Experimental Child Psychology, 81, 249–275. https://doi.org/10.1006/jecp.2001.2653

Yenilmez, A., Sungur, S., & Tekkaya, C. (2005). Investigating students’ logical thinking abilities: The effects of gender and grade level. Hacettepe University Journal of Education, 28, 219–225.

Yu, P. T., Su, M. H., Cheng, P. J., & Liao, Y. H. (2012). Utilizing an online group study environment to enhance student reading ability and learning effectiveness. Journal of Internet Technology, 13(6), 981–988. https://doi.org/10.6138/JIT.2012.13.6.12

Yurdugül, H., & Aşkar, P. (2013). Learning programming, problem solving and gender: A longitudinal study. Procedia - Social and Behavioral Sciences, 83, 605–610. https://doi.org/10.1016/j.sbspro.2013.06.115

Published
2021-03-11
How to Cite
Cheng, P.-J., Liao, Y.-H., & Yu, P.-T. (2021). Micro:bit Robotics Course: Infusing Logical Reasoning and Problem-Solving Ability in Fifth Grade Students Through an Online Group Study System . The International Review of Research in Open and Distributed Learning, 22(1), 21-40. https://doi.org/10.19173/irrodl.v22i1.4844
Section
Research Articles