MTEACOGNITIVE APPROACH – A PRACTICAL APPROACH FOR TEACHING COMPUTERS

Authors

  • Payal Sood Research Scholar, Panjab University, Chandigarh
  • Tripta Parmar Principal, SDS College of Education for Women, Lopon, Moga (Pb.)

DOI:

https://doi.org/10.29121/shodhkosh.v5.i1.2024.4374

Keywords:

Metacognitive Interventions, Attitude Of Computers, Classroom Environment, Challenges Of Teaching Computers

Abstract [English]

The paper deals with the concept of Meta Cognitive solutions for teaching computer science. Most beginners at school level face many challenges while learning computers. The paper deals with use of metacognitive interventions for dealing with their challenges like awareness and understanding the metacognitive interventions. The paper also includes a qualitative case study of use of metacognitive interventions by computer teachers. The difference which metacognition makes in the classroom environment has been established in the case study. The improvement in the attitude of teachers as well as that of the students for a better teaching and learning environment has been established in the paper. The teaching of computer science can be made more effective by creating awareness and understanding of metacognitive approach among computer teachers and it can make teaching more entertaining also.

References

Derry, S. J. (1990). Learning strategies for acquiring useful knowledge. In B. F. Jones & L. Idol (Eds.), Dimensions of thinking and cognitive instruction (pp. 347–379). Hillsdale, NJ: Lawrence Erlbaum Associates.

E. Soloway and J. C. Spohrer, Studying the novice programmer: Psychology Press, 2013. DOI: https://doi.org/10.4324/9781315808321

Efklides, A. (2001). Metacognitive experiences in problem solving. In A. Efklides, J. Kuhl, & R. M. Sorrentino (Eds.), Trends and prospects in motivation research (pp. 297–323). Dordrecht, Netherlands: Kluwer Academic Publishers. DOI: https://doi.org/10.1007/0-306-47676-2_16

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

Hattie, J. (2008). Visible learning: A synthesis of over 800 meta-analyses relating to achievement. London, UK: Routledge. DOI: https://doi.org/10.4324/9780203887332

Hofer, B. K., & Pintrich, P. R. (1997). The development of epistemological theories: Beliefs about knowledge and knowing and their relation to learning. Review of Educational Research, 67(1), 88–140. DOI: https://doi.org/10.3102/00346543067001088

J. E. Davidson, R. Deuser, and R. J. Sternberg, "The role of meta- cognition in problem solving," 1994. DOI: https://doi.org/10.7551/mitpress/4561.003.0012

J. H. Flavell, "Metacognition and cognitive monitoring: A new area of cognitive–developmental inquiry," American psychologist, vol. 34, p. 906, 1979. DOI: https://doi.org/10.1037//0003-066X.34.10.906

J.M. Wing, Computational thinking, Communications of the ACM, 49 (3) (2006), pp. 33-35 DOI: https://doi.org/10.1145/1118178.1118215

M. C. Linn and M. J. Clancy, "The case for case studies of pro- gramming problems," Communications of the ACM, vol. 35, pp. 121-132, 1992. DOI: https://doi.org/10.1145/131295.131301

M. Havenga, B. Breed, E. Mentz, D. Govender, I. Govender, F. Dignum, et al., "Metacognitive and problem-solving skills to pro- mote self-directed learning in computer programming: teachers’ experiences," Sa-educ Journal, vol. 10, pp. 1-14, 2013.

M. N. Ismail, N. Azilah, U. Naufal, and U. T. M. C. Kelantan, "In- structional strategy in the teaching of computer programming: a need assessment analyses," TOJET, vol. 9, pp. 125-131, 2010.

M. Richardson, C. Abraham, and R. Bond, "Psychological corre- lates of university students' academic performance: a systematic review and meta-analysis," Psychological bulletin, vol. 138, p. 353, 2012. DOI: https://doi.org/10.1037/a0026838

P. R. Pintrich, "A conceptual framework for assessing motivation and self-regulated learning in college students," Educational psy- chology review, vol. 16, pp. 385-407, 2004. DOI: https://doi.org/10.1007/s10648-004-0006-x

R. E. Mayer, Applying the science of learning: Pearson/Allyn & Bacon Boston, 2011.

Rogoff, B. (1990). Apprenticeship in Thinking: Cognitive Development in Social Context. New York: Oxford University Press. DOI: https://doi.org/10.1093/oso/9780195059731.001.0001

Rum, S.N.M. and Zolkepli, M., ‘Metacognitive Strategies in Teaching and Learning Computer Programming’, International Journal of Engineering & Technology, 7 (4.38) (2018) 788-794 DOI: https://doi.org/10.14419/ijet.v7i4.38.27546

S. Bergin, R. Reilly, and D. Traynor, "Examining the role of self- regulated learning on introductory programming performance," in Proceedings of the first international workshop on Computing education research, 2005, pp. 81-86. DOI: https://doi.org/10.1145/1089786.1089794

S. E. Volet, "Modelling and coaching of relevant metacognitive strategies for enhancing university students' learning," Learning and Instruction, vol. 1, pp. 319-336, 1991. DOI: https://doi.org/10.1016/0959-4752(91)90012-W

Schon, D. (1987). Educating the Reflective Practitioner. San Francisco: Jossey-Bass Publishers.

Schraw, G. (1998). Promoting general metacognitive awareness. Instructional Science, 26(1–2), 113–125. doi:10.1023/A:1003044231033 DOI: https://doi.org/10.1023/A:1003044231033

Umirzakovna, R.M., “The methods of developing the cognitive activity of students based on computer science and information technology”, European Journal of Research and Reflection in Educational Sciences Vol. 7 No. 12, 2019 ISSN 2056-5852

Veenman, M. V., Wilhelm, P., & Beishuizen, J. J. (2004). The relation between intellectual and metacognitive skills from a developmental perspective. Learning and Instruction, 14(1), 89–109. doi:10.1016/j.learninstruc.2003.10.004 DOI: https://doi.org/10.1016/j.learninstruc.2003.10.004

Zimmerman, B. J. (1989). A social cognitive view of self-regulated academic learning. Journal of Educational Psychology, 81(3), 329. DOI: https://doi.org/10.1037//0022-0663.81.3.329

Zohar, A., & Barzilai, S. (2013). A review of research on metacognition in science education: Current and future directions. Studies in Science Education, 49(2), 121–169. DOI: https://doi.org/10.1080/03057267.2013.847261

Downloads

Published

2024-06-30

How to Cite

Sood, P., & Parmar, T. (2024). MTEACOGNITIVE APPROACH – A PRACTICAL APPROACH FOR TEACHING COMPUTERS. ShodhKosh: Journal of Visual and Performing Arts, 5(1), 1488–1492. https://doi.org/10.29121/shodhkosh.v5.i1.2024.4374