ACM. (2023). Bloom’s for Computing: Enhancing Bloom’s Revised Taxonomy with Verbs for Compu-ting Discipline. ACM Comm. Comp. Educ. Community Colleges (CCECC). Recuperado de https://ccecc.acm.org
Altun, S., & Morkoyunlu, Z. (2023). The use of error based activities to improve the mathematization competency. International Journal of Progressive Education, 19(3), 134–148. https://doi.org/10.29329/ijpe.2023.546.8
Aondofa, A., & Atindi, V. (2022). Effectiveness of the use of gamification by teachers of physics in secondary schools in Buruku Benue State. International Journal of Academic Multidisciplinary Re-search, 6(8), 6–11.
Aprilia, A., et al. (2023). Attitudes and beliefs toward physics: A mini review. Revista Mexicana de Física, E 20(1), 1–8.
Azzouzi, A., et al. (2022). Physics mathematization: Teachers’ observations on the application of ICT. International Conference on Intelligent Systems and Computer Vision (ISCV), 1–5. https://doi.org/10.1109/ISCV54655.2022.9806103
Ben Rebah, H., & Ben Slama, R. (2019). The educational effectiveness of serious games. Mediations and Mediatizations, 2(1), 131–155. https://doi.org/10.52358/mm.vi2.97
Bilbao, J., et al. (2024). Introducing computational thinking and algebraic thinking in the European educational systems. International Journal of Education and Information Technologies, 18, 11–19.
Chen, O., et al. (2023). The effect of worked examples on learning solution steps and knowledge transfer. Educational Psychology. https://doi.org/10.1080/01443410.2023.2273762
Chi, M., et al. (1989). Self-explanations: How students study and use examples in learning to solve problems. Cognitive Science, 13(1), 145–182.
Clark, D., & Sengupta, P. (2019). Reconceptualizing games for integrating computational thinking and science as practice. Interactive Learning Environments, 28(3), 328–346. https://doi.org/10.1080/10494820.2019.1636071
Clark, R., Nguyen, F., & Sweller, J. (2006). Efficiency in learning: Evidence-based guidelines to manage cognitive load. Pfeiffer Wiley.
Collins, A., et al. (1987). Cognitive apprenticeship. Technical Report No. 403.
Espinal, A., et al. (2024). Professional development in computational thinking: A systematic literatu-re review. ACM Transactions on Computing Education, 24(2), 27. https://doi.org/10.1145/3648477
Furuta, T., & Knezek, G. (2023). Text mining analyses of programming education articles since the 1970s. Information and Technology in Education and Learning, 3(1). https://doi.org/10.12937/itel.3.1.Reg.p001
Gazis, A., & Katsiri, E. (2023). Serious games in digital gaming: A comprehensive review of applica-tions. WSEAS Transactions on Computer Research, 11, 10–22. https://doi.org/10.37394/232018.2023.11.2
Godot. (2024). Motor de juegos de código abierto Godot. Recuperado de https://godotengine.org
Gurbuz, S., & Celik, M. (2022). Serious games in future skills development: A systematic review of the design approaches. Computer Applications in Engineering Education, 30(5), 1591–1612. https://doi.org/10.1002/cae.22557
Hake, R. (1998). Interactive-engagement versus traditional methods: A six-thousand-student survey of mechanics test data for introductory physics courses. American Journal of Physics, 66(1), 64–74. https://doi.org/10.1119/1.18809
Hamidi, A., et al. (2023). A complementary view to computational thinking and its interplay with systems thinking. Educational Sciences, 13(2), 201. https://doi.org/10.3390/educsci13020201
Hestenes, D. (1992). Modeling games in the Newtonian world. American Journal of Physics, 60(8), 732–748.
Hidayat, R., et al. (2022). Achievement goals, metacognition and horizontal mathematization: A me-diational analysis. TEM Journal, 11(4), 1537–1546. https://doi.org/10.18421/TEM114-14
Ivanjek, L., et al. (2024). Enhancing mathematization in physics education by digital tools. Physics Education Today, 35–53. Springer Nature.
Jácome, L., et al. (2021). Gamification as an educational strategy to strengthen cognitive abilities of mathematics in school children. Advances in Intelligent Systems and Computing, 1277, 142–150. https://doi.org/10.1007/978-3-030-60467-7_12
Kılıç, S. (2022). Tendencies towards computational thinking: A content analysis study. Participatory Educational Research, 9(5), 288–304. https://doi.org/10.17275/per.22.115.9.5
Kotsis, S., & Chung, K. (2013). Application of the “See One, Do One, Teach One” concept in surgical training. Plastic and Reconstructive Surgery, 131(5), 1194–1201. https://doi.org/10.1097/PRS.0b013e318287a0b3
Lukman, H., et al. (2023). Gamification of mathematics teaching materials: Its validity, practicality and effectiveness. International Journal of Emerging Technologies in Learning (iJET), 18(20), 4–22. https://doi.org/10.3991/ijet.v18i20.36189
Marusic, M., & Slisko, J. (2012). Increasing the attractiveness of school physics: The effects of two different designs of physics learning. Revista Mexicana de Física, E 58(1), 75–83.
Ngadengon, Z., et al. (2024). Theory on computational thinking in education: A systematic review. International Journal of Education, Psychology and Counseling, 9(53), 488–507.
Pacheco, A. (2024). Juegos serios: Matematizando la física de forma lúdica. Electro, arXiv [por publi-car]. https://doi.org/10.48550/arXiv.2407.10057
Prince, M., & Felder, R. (2006). Inductive teaching and learning methods: Definitions, comparisons, and research bases. Journal of Engineering Education, 95(2), 123–138. https://doi.org/10.1002/j.2168-9830.2006.tb00884.x
Rowley, J. (1999). The good mentor. Educational Leadership, 56(1), 20–22.
Spieler, B., et al. (2020). Reducing cognitive load through the worked example effect within a serious game environment. IEEE International Conference on Interactive Learning Environments (iLRN), 1–8. https://doi.org/10.23919/iLRN47897.2020.9155187
Tomalá, J., et al. (2020). Serious games: Review of methodologies and game engines for their develo-pment. Iberian Conference on Information Systems and Technologies (CISTI), 1–6. https://doi.org/10.23919/CISTI49556.2020.9140827
Van der Linden, A., et al. (2024). Learning Newtonian mechanics with an intrinsically integrated educational game. Journal of Computer Assisted Learning, 1–11. https://doi.org/10.1111/jcal.12966
Van Hemmen, J. (2021). Mathematization of nature: How it is done. Biological Cybernetics, 115, 655–664.
Vorhölter, K. (2021). Metacognition in mathematical modeling: The connection between metacogni-tive individual strategies, metacognitive group strategies and modeling competencies. Mathema-tical Thinking and Learning, 25(3), 317–334. https://doi.org/10.1080/10986065.2021.2012740
Wells, M., Hestenes, D., & Swackhamer, G. (1995). A modeling method for high school physics instruc-tion. American Journal of Physics, 63(7), 606–619.
Widiningrum, W., et al. (2024). Effect of PBL-based Scratch e-module in improving computational thinking and physics concepts. International Journal on Studies in Education and Science (IJSES), 5(2), 124–139. https://doi.org/10.46328/ijres.76
Wilson, J., & Clarke, D. (2003). Towards the modelling of mathematical metacognition. Mathematics Education Research Journal, 16(2), 25–48. https://doi.org/10.1007/BF03217394
Wing, J. (2006). Computational thinking. Communications of the ACM, 49(3), 33–35. https://doi.org/10.1145/1118178.1118215
