Identifikasi Extranous Cognitive Load Siswa Dalam Mengembangkan Computational Thinking Skill Melalui Pembelajaran Jaring-Jaring Makanan Berbasis Snap!

Eni Nuraeni*, Tika Nurwahyuni, Amprasto Amprasto, Irvan Permana


Food webs learning using the Snap! is one of the learning strategies that are expected to help improve students' computational thinking. For students, this learning strategy were something new and can cause Extraneous Cognitive Load (ECL). The purpose of this study was to identify students' ECL in food web learning using the Snap! to develop computational thinking skills. The research method used in this study was a pre-experimental design with a modified research design from an iterative action design. The sampling technique was purposive sampling. The sample in this study consisted of 30 seventh grade students at SMPN 2 Bandung. The research instrument used in this study was a student mental effort questionnaire to measure ECL, field notes, and a computational thinking test. Based on the results of the study, students' ECL was relatively low and increased at each meeting, except for the second meeting. Students experience an increase in their computational thinking skills after participating in food web learning using the Snap! computational model. The results of the N-Gain analysis also show that the improvement of students' computational thinking is in the moderate category and is quite effective.


Extranous Cognitive Load;computational thingking; jaring jaring makanan; model komputasi; snap!

Full Text:



Bers, M.U. 2018. Coding and computational thinking in early childhood: the impact of scratchjr in Europe. European Journal of STEM Education, 3(3):1-13.

Cotton, K. 1991. Teaching thinking skills. Northwest Regional Educational Laboratory, School Improvement Program, Portland.

Lim, B.L. & Chen, C.J. 2021. Computational thinking (algorithms) through unplugged programming activities: exploring upper primary students’ learning experiences. International Journal of Academic Research in Business and Social Sciences, 11(14):384-403.

José, F. & Francisco, G.P . 2017. Improving computational thinking using follow and give instructions. Proceedings of the 5th International Conference on Technological Ecosystems for Enhancing Multiculturality, 2017 October, p.1-7.

Hake, R.R. 1999. Analyzing change/gain score. [Online] Tersedia: (2 Juli 2021).

Hui, D. 2012. Food web: concept and applications. Nature Education Knowledge, 3(12):612.

Kirschner, P.A. & Kirschner F. 2012. Mental effort, dalam Seel, N.M. (eds), Encyclopedia of the sciences of learning, Springer, Boston.

Moon, J., Do, J., Lee, D., & Choi, G.W. 2020. A conceptual framework for teaching computational thinking in personalized OERs. Smart Learning Environments, 7(6):1-19.

Paas, F. 1992. Training strategies for attaining transfer of problem-solving skill in statistics: A cognitive-load approach. Journal of Educational Psychology, 84(4):429–434.

Peel, A., Sadler, T. D., & Friedrichsen, P. 2021. Using unplagged computational thinking to scaffold natural selection learning. The American Biology Teacher, 83(2):112–117.

Peel, A. & Friedrichsen, P. 2018. Algorithms, abstractions, and iterations: teaching computational thinking using protein synthesis translation. The American Biology Teacher, 80(1):21–28.

Preston, C. 2018. Food webs: Implications for instruction. The American Biology Teacher, 80(5):331-338.

Rahmat, A., Soesilawaty, S.A., Nuraeni, E., & Hidayat, T. 2017. Controlling cognitive load of high school student in biology class. Journal of Science Education, 2(18):105-108.

Romagosa, B. 2019. The Snap! programming system. Encyclopedia of Education and Information Technologies, p.1–10.

Rubinstein, A. & Chor, B. 2014. Computational thinking in life science education. PLOS Computational Biology, 10(11):1-5.

Scharfenberg, F.J. & Bogner, F.X. 2010. Instructional efficiency of changing cognitive in an out-of-school laboratory. International Journal of Science Education, 32(6):829-824.

Wiebe, E., London, J., Aksit, O., Mott, B., Boyer, K., & Lester, J. 2019. Development of a lean computational thinking abilities assessment for middle grades students. Pro-ceeding of SIGCSE, 2019 February, p.456-461.

Yasin, M. 2020. Computational thinking untuk pembelajaran dasar-dasar pemrograman komputer. [Online]. Diakses dari: 340637723_computational_thinking_untuk_pembelajaran_dasar-dasar_pemrograman_komputer (10 Januari 2021).



  • There are currently no refbacks.

Copyright (c) 2021 Eni Nuraeni

Jurnal Pendidikan Sains Indonesia

ISSN 2338-4379  (print) | 2615-840X (online)
Organized by Universitas Syiah Kuala 
Published by Program Studi Magister Pendidikan IPA Program Pascasarjana Universitas Syiah Kuala
Website :
Email     :

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.