Metacognitive Skills Evaluation Based on Programming Actions

Authors

DOI:

https://doi.org/10.15517/ap.v40i140.64022

Keywords:

Metacognitive skills, regulation, planning, organization, programming

Abstract

Objective. To establish the possibility of online evaluating metacognitive skills of planning, regulation and organization, based on actions at the time of programming. Method. Metacognitive skills of students programming were measured using a fuzzy expert system with inference rules relating concrete actions on code with skills, as defined with information from experts (systematically with thematic analysis) and theory. Evaluations were then compared with MAI evaluations. Results. A positive correlation was found (r = .72, p = .1) between the evaluation for planning skills given by the expert system and the MAI instrument.  This correlation is stronger when only the regulations components of MAI are considered (r = .77, p = .1).  Similarly, a positive correlation was found when comparing the evaluation from the expert system with the evaluation regulation skills with MAI (Spearman r = .40, p = .1), and with organization but without reaching significance threshold.

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Author Biography

  • Ricardo Gang Vincenzi, Universidad de Costa Rica, San José, Costa Rica

     Escuela de Ciencias de Computación e Informática, Universidad de Costa Rica, San José, Costa Rica

References

Adiansyah, R., Corebima, A. D., Zubaidah, S., & Rohman, F. (2021). The correlation between metacognitive skills and scientific attitudes towards the retention of male and female students in South Sulawesi, Indonesia. International Journal of Evaluation and Research in Education, 10(4), 1272-1281. http://doi.org/10.11591/ijere.v10i4.21597 DOI: https://doi.org/10.11591/ijere.v10i4.21597

Allan, V. H., & Kolesar, M. V. (1996). Teaching computer science: A problem solving approach that works. In D. Ingham (Ed.), Proceedings of the Annual National Educational Computing Conference ’96 (pp. 9-15). The International Society for Technology in Education.

Bannert, M., & Mengelkamp, C. (2008). Assessment of metacognitive skills by means of instruction to think aloud and reflect when prompted. Does the verbalisation method affect learning? Metacognition and Learning, 3, 39-58. https://doi.org/10.1007/s11409-007-9009-6 DOI: https://doi.org/10.1007/s11409-007-9009-6

Bergin, S., Reilly, R., & Traynor, D. (2005). Examining the role of self-regulated learning on introductory programming performance. In ICER ’05: Proceedings of the First International Workshop on Computing Education Research (pp. 81-86). Association for Computing Machinery. https://doi.org/10.1145/1089786.1089794 DOI: https://doi.org/10.1145/1089786.1089794

Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77-101. https://doi.org/10.1191/1478088706qp063oa DOI: https://doi.org/10.1191/1478088706qp063oa

Brown, A. L. (1987). Metacognition, executive control, self-regulation, and other more mysterious mechanisms. In Metacognition, Motivation, and Understanding (pp. 65-116). L. Erlbaum Associates. DOI: https://doi.org/10.4324/9781003758167-5

Chaparro, E., Restrepo-Calle, F., & Ramírez-Echeverry, J. J. (2021, October 19-21). Learning analytics in computer programming courses [Conference session]. LALA ’21: IV Latin American Conference on Learning Analytics, Arequipa, Perú. https://api.semanticscholar.org/CorpusID:245635411

Efklides, A. (2006). Metacognition and affect: What can metacognitive experiences tell us about the learning process? Educational Research Review, 1(1), 3-14. http://dx.doi.org/10.1016/J.EDUREV.2005.11.001 DOI: https://doi.org/10.1016/j.edurev.2005.11.001

Efklides, A. (2008). Metacognition: Defining its facets and levels of functioning in relation to self-regulation and co-regulation. European Psychologist, 13(4), 277-287. https://doi.org/10.1027/1016-9040.13.4.277 DOI: https://doi.org/10.1027/1016-9040.13.4.277

Ericsson, K. A. (1987). Verbal reports on thinking. En H. Simon (Ed.), Introspection in Second Language Research (pp. 24-54). Multilingual Matters.

Ericsson, K. A., & Simon, H. A. (1993). Protocol Analysis: Verbal Reports as Data. The MIT Press. DOI: https://doi.org/10.7551/mitpress/5657.001.0001

Ericsson, K. A., & Simon, H. A. (1980). Verbal reports as data. Psychological Review, 87(3), 215-251. https://acs.ist.psu.edu/ist597/papers/ericssonS80.pdf DOI: https://doi.org/10.1037/0033-295X.87.3.215

Estey, A., & Coady, Y. (2016). Can Interaction Patterns with Supplemental Study Tools Predict Outcomes in CS1? In ITiCSE ’16: Proceedings of the 2016 ACM Conference on Innovation and Technology in Computer Science Education (pp. 236-241). Association for Computing Machinery. https://doi.org/10.1145/2899415.2899428 DOI: https://doi.org/10.1145/2899415.2899428

Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive–developmental inquiry. American Psychologist, 34(10), 906-911. https://doi.org/10.1037/0003-066X.34.10.906 DOI: https://doi.org/10.1037/0003-066X.34.10.906

Jain, Y. R., Callaway, F., Griffiths, T. L., Dayan, P., He, R., Krueger, P. M., & Lieder, F. (2023). A computational process-tracing method for measuring people’s planning strategies and how they change over time. Behavior Research Methods, 55, 2037-2079. https://doi.org/10.3758/s13428-022-01789-5 DOI: https://doi.org/10.3758/s13428-022-01789-5

Loksa, D., Margulieux, L., Becker, B. A., Craig, M., Denny, P., Pettit, R., & Prather, J. (2022). Metacognition and self-regulation in programming education: Theories and exemplars of use. ACM Transactions on Computing Education, 22(4), 1-31. https://doi.org/10.1145/3487050 DOI: https://doi.org/10.1145/3487050

Mai, T. T., Crane, M., & Bezbradica, M. (2023). Students’ learning behaviour in programming education analysis: Insights from entropy and community detection. Entropy, 25(8), Article 1225. https://doi.org/10.3390/e25081225 DOI: https://doi.org/10.3390/e25081225

Prather, J., Becker, B. A., Craig, M., Denny, P., Loksa, D., & Margulieux, L. (2020). What do we think we think we are doing?: Metacognition and self-regulation in programming. En ICER ‘20: Proceedings of the 2020 ACM Conference on International Computing Education Research (pp. 2-13). Association for Computing Machinery. https://doi.org/10.1145/3372782.3406263 DOI: https://doi.org/10.1145/3372782.3406263

Rakovic, M., Fan, Y., van der Graaf, J., Singh, S., Kilgour, J., Lim, L., Moore, J., Bannert, M., Molenaar, I., & Gasevic, D. (2022). Using learner trace data to understand metacognitive processes in writing from multiple sources. En LAK22: 12th International Learning Analytics and Knowledge Conference (pp. 130-141). Association for Computing Machinery. https://doi.org/10.1145/3506860.3506876 DOI: https://doi.org/10.1145/3506860.3506876

Schraw, G. (1998). Promoting general metacognitive awareness. Instructional Science, 26(1), 113-125. https://doi.org/10.1023/A:1003044231033 DOI: https://doi.org/10.1023/A:1003044231033

Schraw, G., & Sperling, D. R. (1994). Assessing metacognitive awareness. Contemporary Educational Psychology, 19(4), 460-475. https://doi.org/10.1006/ceps.1994.1033 DOI: https://doi.org/10.1006/ceps.1994.1033

Veenman, M. (2005). The assessment of metacognitive skills: What can be learned from multi method designs? In C. Artelt & B. Moschner (Eds.), Lernstrategien und Metakognition: Implikationen für Forschung und Praxis (pp. 77-99). Waxmann.

Veenman, M., & Elshout, J. J. (1999). Changes in the relation between cognitive and metacognitive skills during the acquisition of expertise. European Journal of Psychology of Education, 14, 509-523. https://doi.org/10.1007/BF03172976 DOI: https://doi.org/10.1007/BF03172976

Vrugt, A., & Oort, F. J. (2008). Metacognition, achievement goals, study strategies and academic achievement: Pathways to achievement. Metacognition and Learning, 3(2), 123-146. https://doi.org/10.1007/s11409-008-9022-4 DOI: https://doi.org/10.1007/s11409-008-9022-4

Watson, C., Li, F. W. B., & Godwin, J. L. (2013). Predicting Performance in an Introductory Programming Course by Logging and Analyzing Student Programming Behavior. In Proceedings of the 2013 IEEE 13th International Conference on Advanced Learning Technologies (pp. 319-323). Institute of Electrical and Electronics Engineers. DOI: https://doi.org/10.1109/ICALT.2013.99

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Published

2026-06-03

How to Cite

Gang Vincenzi, R. (2026). Metacognitive Skills Evaluation Based on Programming Actions. Actualidades En Psicología, 40(140), 50-63. https://doi.org/10.15517/ap.v40i140.64022