Robotics Curriculum as a Learner-Centric Model for Integrating Science, Technology, Engineering, and Mathematics Disciplines in K-12 Contexts
DOI:
https://doi.org/10.33830/ijrse.v7i2.1806Keywords:
control system, Industry 4.0, integrated curriculum, learner-centric, systems thinking, roboticsAbstract
Robotics is increasingly essential in 21st-century education, fostering skills like critical thinking, creativity, and collaboration while integrating STEM subjects through systems and computational thinking. However, many K -12 STEM programs lack engineering components and rely heavily on teachers for implementation, limiting direct learner engagement. This paper argues that incorporating robotics into curricula shifts the focus to learners, emphasizing systems thinking and engineering design elements often missing in high school programs. It highlights the role of robotics in STEM skill development, critiques teacher-centric models, and advocates for learner-centric approaches. Additionally, it outlines a future trajectory for robotics curricula in developing nations, emphasizing the need to align with Industry 4.0 advancements. By analyzing robotics' potential to integrate STEM disciplines, the paper aims to empower curriculum planners, educators, and learners to harness technological innovations effectively. Insights from literature are used to support this proposition across four sections: robotics and STEM skills development, challenges of teacher-centric models, robotics as a learner-centric tool, and the future of robotics education. This approach addresses gaps in current STEM integration and equips learners with the skills needed to thrive in a technology-driven world.
References
Alam, A., & Mohanty, A. (2024). Integrated constructive robotics in education (ICRE) model: A paradigmatic framework for transformative learning in educational ecosystem. Cogent Education, 11(1). https://doi.org/10.1080/2331186X.2024.2324487
Alfredo, R., Echeverria, V., Jin, Y., Yan, L., Swiecki, Z., Gasevic, D., & Martinez-Maldonado, R. (2024). Human-centred learning analytics and AI in education: A systematic literature review. Computers and Education: Artificial Intelligence, 6. https://doi.org/10.1016/j.caeai.2024.100215
Angel-Fernandez, J., Vincze, M., & Zech, P. (2018). Towards a definition of educational robotics. In: P. Zech & J. Piater (Eds). Proceedings of the Austrian Robotics, 37–42.
Atmatzidou, S., & Demetriadis, S. (2016). Advancing students’ computational thinking skills through educational robotics: A study on age and gender relevant differences. Robotics and Autonomous Systems, 75, 661–670. https://doi.org/10.1016/j.robot.2015.10.008
Basu, S., Biswas, G., Sengupta, P., Dickes, A., Kinnebrew, J. S., & Clark, D. (2016). Identifying middle school students’ challenges in computational thinking-based science learning. Research and Practice in Technology Enhanced Learning, 11(1), 13. https://doi.org/10.1186/s41039-016-0036-2
Berry, C. A., Remy, S. L., & Rogers, T. E. (2016). Robotics for All Ages: A Standard Robotics Curriculum for K-16. IEEE Robotics & Automation Magazine, 23(2), 40–46. https://doi.org/10.1109/MRA.2016.2534240
Brown, D. F. (2011). Curriculum Integration: Meaningful Learning Based on Students’ Questions. Middle Grades Research Journal, 6(4), 193–206.
Buckingham, D. (2013). Beyond Technology: Children’s Learning in the Age of Digital Culture. John Wiley & Sons.
Cheng, Y. C., & So, W. W. M. (2020). Managing STEM learning: A typology and four models of integration. International Journal of Educational Management, 34(6), 1063–1078. https://doi.org/10.1108/IJEM-01-2020-0035
Czerniak, C. M., Weber Jr, W. B., Sandmann, A., & Ahern, J. (1999). A literature review of science and mathematics integration. School Science and Mathematics, 99(8), 421–430. https://doi.org/10.1111/j.1949- 8594.1999.tb17504.x
Dalenogare, L. S., Benitez, G. B., Ayala, N. F., & Frank, A. G. (2018). The expected contribution of Industry 4.0 technologies for industrial performance. International Journal of Production Economics, 204, 383–394. https://doi.org/10.1016/j.ijpe.2018.08.019
De Meester, J., De Cock, M., Langie, G., & Dehaene, W. (2021). The Process of Designing Integrated STEM Learning Materials: Case Study towards an Evidence-based Model. European Journal of STEM Education, 6(1), 10. https://doi.org/10.20897/ejsteme/11341
Dong, Y., Wang, J., Yang, Y., & Kurup, P. M. (2020). Understanding intrinsic challenges to STEM instructional practices for Chinese teachers based on their beliefs and knowledge base. International Journal of STEM Education, 7(1), 47. https://doi.org/10.1186/s40594-020-00245-0
Dupont, P. E., Nelson, B. J., Goldfarb, M., Hannaford, B., Menciassi, A., O’Malley, M. K., Simaan, N., Valdastri, P., & Yang, G.-Z. (2021). A decade retrospective of medical robotics research from 2010 to 2020. Science Robotics, 6(60), eabi8017. https://doi.org/10.1126/scirobotics.abi8017
Eguchi, A. (2014). Robotics as a learning tool for educational transformation. 1, 1–6.
English, L. D., King, D., & Smeed, J. (2017). Advancing integrated STEM learning through engineering design: Sixth-grade students’ design and construction of earthquake resistant buildings. The Journal of Educational Research, 110(3), 255–271. https://doi.org/10.1080/00220671.2016.1264053
Fan, S.-C., & Yu, K.-C. (2017). How an integrative STEM curriculum can benefit students in engineering design practices. International Journal of Technology and Design Education, 27(1), 107–129. https://doi.org/10.1007/s10798-015-9328-x
Fuertes, J. J., Prada, M. Á., Rodríguez-Ossorio, J. R., González-Herbón, R., Pérez, D., & Domínguez, M. (2021). Environment for Education on Industry 4.0. IEEE Access, 9, 144395–144405. https://doi.org/10.1109/ACCESS.2021.3120517
Greenhalgh, T., Glenn R., Fraser M., Paul B., Olympia K., & Richard P. (2005). Storylines of research in diffusion of innovation: a meta-narrative approach to systematic review. Social Science & Medicine, 61(2), 417-430.
Grift, T. E., Zhang, Q., Kondo, N., & Ting, K. C. (2008). A review of automation and robotics for the bio-industry. https://api.semanticscholar.org/CorpusID:13511513
Guzey, S. S., Moore, T. J., & Harwell, M. (2016). Building up STEM: An analysis of teacher-developed engineering design-based STEM integration curricular materials. Journal of Pre-College Engineering Education Research (J-PEER), 6(1), 11–29. https://doi.org/10.7771/2157-9288.1129
Haidegger, T. (2021). Taxonomy and standards in robotics. In H. Ang, O. Khatib, & B. Siciliano (Eds.), Encyclopedia of Robotics. Springer Nature.
Hartelt, T., & Martens, H. (2024). Self-regulatory and metacognitive instruction regarding student conceptions: Influence on students’ self-efficacy and cognitive load. Frontiers in Psychology, 15, 1450947. https://doi.org/10.3389/fpsyg.2024.1450947
Himmetoglu, B., Aydug, D., & Bayrak, C. (2020). Education 4.0: Defining the teacher, the student, and the school manager aspects of the revolution. Turkish Online Journal of Distance Education, 21(Special Issue-IODL), 12–28.
Hong, Q. N., Pluye, P., Fabregues, S., Bartlett, G., Boardman, F., Cargo, M., & Vedel, I. (2018). Mixed methods appraisal tool (MMAT), version 2018. Registration of copyright, 1148552(10), 1-7.
Hurley, M. M. (2001). Reviewing integrated science and mathematics: The search for evidence and definitions from new perspectives. School Science and Mathematics, 101(5), 259–268.
Hussin, H., Jiea, P. Y., Rosly, R. N. R., & Omar, S. R. (2019). Integrated 21st century science, technology, engineering, mathematics (STEM) education through robotics project-based learning. Humanities & Social Sciences Reviews, 7(2), 204–211.
Jung, S. E., & Won, E. (2018). Systematic review of research trends in robotics education for young children. Sustainability, 10(4), 905.
Karypi, S. (2018). Educational robotics application in primary and secondary education. A challenge for the Greek teachers society. Journal of Contemporary Education, Theory & Research, 2(1), 9–14. https://doi.org/10.25656/01:19094
Keisner, A., Raffo, J., & Wunsch-Vincent, S. (2016). Robotics: Breakthrough technologies, innovation, intellectual property. Foresight, 10(2 (eng)), 7–27.
Kelley, T. R., & Knowles, J. G. (2016). A conceptual framework for integrated STEM education. International Journal of STEM Education, 3(1), 1–11. https://doi.org/10.1186/s40594-016-0046-z
Kusmawan, U. (2024). Transforming digital learning and assessment strategies in higher education. Multidisciplinary Reviews, 8(1), 2025016. https://doi.org/10.31893/multirev.2025016
Kusmawan, U., & Sukmayadi, D. (2024). Desarrollo de una escala de competencias digitales y en línea para estudiantes. Edutec, Revista Electrónica De Tecnología Educativa, (90), 74–91. https://doi.org/10.21556/edutec.2024.90.3265
LEE, S.-G. (2022). VOCABULARY STANDARD FOR ROBOTICS IN ISO. Value-Sharing between Humans and Robots, 184–190.
Lesort, T., Lomonaco, V., Stoian, A., Maltoni, D., Filliat, D., & Díaz-Rodríguez, N. (2020). Continual learning for robotics: Definition, framework, learning strategies, opportunities and challenges. Information Fusion, 58, 52–68.
Margot, K. C., & Kettler, T. (2019). Teachers’ perception of STEM integration and education: A systematic literature review. International Journal of STEM Education, 6(2), 1–16. https://doi.org/10.1186/s40594-018-0151-2
Mason, T. C. (1996). Integrated curricula: Potential and problems. Journal of Teacher Education, 47(4), 263–270. https://doi.org/10.1177/0022487196474004
Master, P. (2023). First Lego League challenge: Engineering Notebook. First Lego. https://www.first-lego-league.org>files>PDFs
McFadden, J. R., & Roehrig, G. H. (2017). Exploring teacher design team endeavors while creating an elementary-focused STEM-integrated curriculum. International Journal of STEM Education, 4, 1–22. https://doi.org/10.1186/s40594-017-0084-1
McGrath, B., Sayres, J., Lowes, S., & Lin, P. (2008). Underwater LEGO robotics as the vehicle to engage students in STEM: The BUILD IT project’s first year of classroom implementation. American Society for Engineering Education Mid-Atlantic, Hoboken, NJ.
Mihelj, M., Bajd, T., Ude, A., Lenarcic, J., Stanovnik, A., Slajpah, S., & Rejc, J. (2019). Robotics. Springer.
Montiel, H., & Gomez-Zermeño, M. G. (2021). Educational Challenges for Computational Thinking in K-12 Education: A Systematic Literature Review of “Scratch” as an Innovative Programming Tool. Computers, 10(6), 69. https://doi.org/10.3390/computers10060069
Moraes, E. B., Kipper, L. M., Hackenhaar Kellermann, A. C., Austria, L., Leivas, P., Moraes, J. A. R., & Witczak, M. (2023). Integration of Industry 4.0 technologies with Education 4.0: Advantages for improvements in learning. Interactive Technology and Smart Education, 20(2), 271–287. https://doi.org/10.1108/ITSE-11-2021-0201
Mutseekwa, C., Moyo, P. V., & Mudavanhu, A. (2024). Improving the Flipped Classroom efficacy using the ballot box model: A study of innovative learning situations in Higher Education in Zimbabwe. In S. Muchemwa & M. Mawere (Eds.), Contemporary Innovation Trends in the Zimbabwean Education System (pp. 165–186). Bamenda: Langaa Research & Publishing Common Initiative Group.
Nadelson, L. S., & Seifert, A. L. (2017). Integrated STEM defined: Contexts, challenges, and the future. The Journal of Educational Research, 110(3), 221–223. https://doi.org/10.1080/00220671.2017.1289775
Niku, S. B. (2019). Introduction to robotics: Analysis, control, applications (3rd ed.). John Wiley & Sons.
Nollmeyer, G. E., Kelting-Gibson, L., & Graves, C. J. (2016). Mapping the Domain of Subject Area Integration: Elementary Educators’ Descriptions and Practices. International Journal of Learning, Teaching And Educational Research, 15(9), 1–27.
Osabwa, W., Murira, F., & Malenya, F. (2022). Essentialist education as foundation for lifelong learning: A case for development of a versatile, skilled human resource in Kenya. International Journal of Recent Research in Thesis and Dissertation, 3(2), 131–136. https://doi.org/10.5281/zenodo.7153007
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., & Moher, D. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Bio Medical Journal, 372.
Papadakis, S. (2020). Robots and robotics kits for early childhood and first school age. International Journal of Interactive Mobile Technologies. 14(18), 34–56. https://doi.org/10.3991/ijim.v14i18.16631
Pilley, A. J. (2016). The role of technology in personalized learning and the effect on student achievement. Lindenwood University.
Putnik, G., & Alves, C. (2022). Social Network-based Education and Education 3.0: Application for education on Design and teaching of Industry 4.0 concepts. Procedia CIRP, 109, 659–665. https://doi.org/10.1016/j.procir.2022.05.310
Royakkers, L., & van Est, R. (2015). A Literature Review on New Robotics: Automation from Love to War. International Journal of Social Robotics, 7(5), 549–570. https://doi.org/10.1007/s12369-015-0295-x
Saritepeci, M. (2020). Developing Computational Thinking Skills of High School Students: Design-Based Learning Activities and Programming Tasks. The Asia-Pacific Education Researcher, 29(1), 35– 54. https://doi.org/10.1007/s40299-019-00480-2
Screpanti, L., Miotti, B., & Monteriù, A. (2021). Robotics in education: A smart and innovative approach to the challenges of the 21st century. In J. Kacprzyk (Ed.), Makers at School, Educational Robotics and Innovative Learning Environments: Research and Experiences from FabLearn Italy 2019, in the Italian Schools and Beyond (pp. 17–26). Springer International Publishing Cham. https://doi.org/10.1007/978-3-030-77040-2
Selcen Guzey, S., Harwell, M., Moreno, M., Peralta, Y., & Moore, T. J. (2017). The impact of design-based STEM integration curricula on student achievement in engineering, science, and mathematics. Journal of Science Education and Technology, 26, 207–222.
Sembey, R., Hoda, R., & Grundy, J. (2024). Emerging technologies in higher education assessment and feedback practices: A systematic literature review. Journal of Systems and Software, 211, 111988. https://doi.org/10.1016/j.jss.2024.111988
Shemshack, A., & Spector, J. M. (2020). A systematic literature review of personalized learning terms. Smart Learning Environments, 7(1), 33. https://doi.org/10.1186/s40561-020-00140-9
Shernoff, D. J., Sinha, S., Bressler, D. M., & Ginsburg, L. (2017). Assessing teacher education and professional development needs for the implementation of integrated approaches to STEM education. International Journal of STEM Education, 4(1), 13. https://doi.org/10.1186/s40594-017-0068-1
Siew, N. M., Goh, H., & Sulaiman, F. (2016). INTEGRATING STEM IN AN ENGINEERING DESIGN PROCESS: THE LEARNING EXPERIENCE OF RURAL SECONDARY SCHOOL STUDENTS IN AN OUTREACH CHALLENGE PROGRAM. In Journal of Baltic Science Education (Vol. 15, p. Continuous). https://doi.org/10.33225/jbse/16.15.477
Sisman, B., Kucuk, S., & Yaman, Y. (2021). The Effects of Robotics Training on Children’s Spatial Ability and Attitude Toward STEM. International Journal of Social Robotics, 13(2), 379–389. https://doi.org/10.1007/s12369-020-00646-9
Souza, I. M., Andrade, W. L., & Sampaio, L. M. (2022). Educational robotics applications for the development of computational thinking in a Brazilian technical and vocational high school. Informatics in Education, 21(1), 147–177. https://doi.org/10.15388/infedu.2022.06
Sullivan, A., & Bers, M. U. (2016). Robotics in the early childhood classroom: Learning outcomes from an 8-week robotics curriculum in pre-kindergarten through second grade. International Journal of Technology and Design Education, 26(1), 3–20. https://doi.org/10.1007/s10798-015-9304-5
Theodoropoulos, A., Antoniou, A., & Lepouras, G. (2017). Teacher and student views on educational robotics: The Pan-Hellenic competition case. Application and Theory of Computer Technology, 2(4), 1–23.
Trowler, P. (2014). Depicting and researching disciplines: Strong and moderate essentialist approaches. Studies in Higher Education, 39(10), 1720–1731. https://doi.org/10.1080/03075079.2013.801431
Tsianos, K. I. (2008). Replanning: A powerful planning strategy for systems with differential constraints. Rice University.
Wang, M.-T., Ye, F., & Degol, J. L. (2017). Who Chooses STEM Careers? Using A Relative Cognitive Strength and Interest Model to Predict Careers in Science, Technology, Engineering, and Mathematics. Journal of Youth and Adolescence, 46(8), 1805–1820. https://doi.org/10.1007/s10964-016-0618-8
Wang, W., & Siau, K. (2019). Artificial intelligence, machine learning, automation, robotics, future of work and future of humanity: A review and research agenda. Journal of Database Management, 30(1), 61–79. https://doi.org/10.4018/JDM.2019010104
Webb, M., & Reynolds, N. (2013). Current and future research issues for ICT in education. Journal of Computer Assisted Learning, 29(1), 106–108. https://doi.org/10.1111/j.1365-2729.2011.00468.x
Wedeward, K., & Bruder, S. (2002). Incorporating robotics into secondary education. 14, 411–416.
Xu, X., Wang, X., Zhang, Y., & Zheng, R. (2024). Applying ChatGPT to tackle the side effects of personal learning environments from learner and learning perspective: An interview of experts in higher education. PloS One, 19(1). https://doi.org/10.1371/journal.pone.0295646
Zainuddin, Z., & Perera, C. J. (2019). Exploring students’ competence, autonomy and relatedness in the flipped classroom pedagogical model. Journal of Further and Higher Education, 43(1), 115–126. https://doi.org/10.1080/0309877X.2017.1356916
Zanker, M., Rook, L., & Jannach, D. (2019). Measuring the impact of online personalisation: Past, present and future. International Journal of Human-Computer Studies, 131, 160–168. https://doi.org/10.1016/j.ijhcs.2019.06.006
Zheng, T., Ardolino, M., Bacchetti, A., & Perona, M. (2021). The applications of Industry 4.0 technologies in manufacturing context: A systematic literature review. International Journal of Production Research, 59(6), 1922–1954. https://doi.org/10.1080/00207543.2020.1824085
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