The Moderating Effect of Computational Thinking and Multirepresentation on the Relationship of Academic Resilience and Biology Literacy in Indonesian High School Students
), Asham Bin Jamaluddin(2), Saidil Mursali(3), Ika Nurani Dewi(4)
| 
Country:
(1) Teacher Professional Education Study Program, Universitas Pendidikan Mandalika, Indonesia, Indonesia
(2) Biology Education Study Program, Universitas Negeri Makassar, Indonesia, Indonesia
(3) Biology Education Study Program, Universitas Pendidikan Mandalika, Indonesia, Indonesia
(4) Biology Education Study Program, Universitas Pendidikan Mandalika, Indonesia, Indonesia
Corresponding Author
10.23960/jpmipa.v26i2.pp1007-1024
| Metrics→ |
| Indexing Site→ |  |
 |
 |
 |
Copyright (c) 2025 Any Fatmawati, Asham Bin Jamaluddin, Saidil Mursali, Ika Nurani Dewi
Academic resilience helps students overcome learning challenges and stay motivated in understanding complex biology materials. Computational thinking skills enable students to break down complex biology problems logically and structured, while the use of multirepresentations such as diagrams and graphs facilitates the understanding of abstract concepts. Biological literacy has a very important urgency for students because it plays a role in equipping them with the ability to understand, analyze, and apply biological concepts in everyday life. In the era of globalization and rapid development of science, biological literacy is an important basis for making intelligent decisions, especially related to environmental, health, and sustainability issues. The objective of this study is to investigate the influence of academic resilience on the biological literacy of students by means of computational thinking and multirepresentations. It is hypothesized that students' capacity to surmount intricate biology learning obstacles is enhanced by their high academic resilience. This study examines the correlation between academic resilience, computational thinking, multirepresentations, and biological literacy in high school pupils in Mataram City, Indonesia, utilizing quantitative methods and Structural Equation Modeling (SEM) analysis. The findings indicated that academic resilience has a substantial impact on the biological literacy of students (p < 0.05), both directly and through the mediation of computational thinking abilities and the use of multirepresentations. Computational thinking assists students in the deconstruction of intricate biological problems, while multirepresentations, such as diagrams and graphs, facilitate comprehension of abstract biological concepts. This study underscores the significance of fostering academic resilience, computational thinking, and visual representations in order to enhance students' biological literacy, thereby facilitating the development of more effective and adaptive biology learning strategies.
Keywords: academic resilience, biology literacy, computational thinking, multirepresentation, students.
Abdillah, H. Z., & Marleni. (2023). Cultivating resilience: a key to managing academic stress among health students in online learning. Psyche 165 Journal. https://doi.org/10.35134/jpsy165.v16i4.294
Acosta-Gonzaga, E., & Ruiz-Ledesma, E. F. (2022). Students’ emotions and engagement in the emerging hybrid learning environment during the COVID-19 Pandemic. Sustainability, 14(16), 1–14. https://doi.org/10.3390/su141610236
Anierobi, E. I., Nwikpo, M. N., Okeke, N. U., & Ezennaka, A. O. (2024). Students’ academic engagement in secondary schools: parental involvement and academic resilience as predictor variables. Ijeps. https://doi.org/10.59890/ijeps.v2i1.1207
Bahri, A., Palennari, M., Hardianto, Muharni, A., & Arifuddin, M. (2021). Problem-based learning to develop students’ character in biology classroom Problem-based learning to develop students’ character in biology classroom. Asia-Pacific Forum on Science Learning and Teaching, 20(2).
Cassidy, S. (2016). The academic resilience scale (ARS-30): A new multidimensional construct measure. Frontiers in Psychology. https://doi.org/10.3389/ fpsyg.2016.01787
Demir, B. (2023). The mediating effect of academic resilience on the relationship between psychological resilience and academic achievement. E-International Journal of Educational Research. https://doi.org/10.19160/e-ijer.1253101
Dhani, A. R., & Agustinah, A. (2023). Being a young scientist : does guided inquiry affect students’ scientific literacy skills? International Research-Based Education Journal. https://doi.org/10.17977/um043v5i2p222-227
Disastra, G. M., Noermijati, N., Irawanto, D. W., & Moko, W. (2024). Digital skills and self-efficacy: unpacking their influence on faculty research engagement. Edelweiss Applied Science and Technology. https://doi.org/10.55214/25768484.v8i6.2374
Fachmi, T., & Kustiwa, D. R. (2022). Construct validity test of academic resilience inventory (ari): a potential scale for assessing students’ academic resilience during pandemic COVID-19. Ijip Indonesian Journal of Islamic Psychology. https://doi.org/10.18326/ijip.v4i2.14
Fathonah, S., Cahyono, E., Haryani, S., Sarwi, S., & Lestari, N. hayati. (2024). Application of multirepresentation-based creative problem-solving learning models to improve critical and creative thinking skills for students. International Journal of Cognitive Research in Science Engineering and Education. https://doi.org/10.23947/2334-8496-2024-12-1-185-200
Fatmawati, A., Zubaidah, S., Malang, U. N., & Mahanal, S. (2019). Critical thinking , creative thinking , and learning achievement : how they are related critical thinking, creative thinking, and learning achievement : how they are related. December. https://doi.org/10.1088/1742-6596/1417/1/012070
Fauzi, A., Rosyida, A. M., Rohma, M., & Khoiroh, D. (2021). The difficulty index of biology topics in indonesian senior high school: biology undergraduate students’ perspectives. Jpbi (Jurnal Pendidikan Biologi Indonesia). https://doi.org/10.22219/jpbi.v7i2.16538
Fenwick, L., & Unsworth, L. (2022). Including visual representations within senior high school biology assessment: considerations of grammatical complexity. The Curriculum Journal. https://doi.org/10.1002/curj.181
Fitrah Ishak, N. H., Binti Yusoff, N. F., & Madihie, A. (2020). Resilience in mathematics, academic resilience, or mathematical resilience?: an overview. Universal Journal of Educational Research. https://doi.org/10.13189/ujer.2020.081905
Guo, W., Wang, J., Li, N., & Wang, L. (2025). The impact of teacher emotional support on learning engagement among college students mediated by academic self-efficacy and academic resilience. Scientific Reports. https://doi.org/10.1038/s41598-025-88187-x
Hahn, L., & Klein, P. (2023). The impact of multiple representations on students’ understanding of vector field concepts: implementation of simulations and sketching activities into lecture-based recitations in undergraduate physics. Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2022.1012787
Hair, J. F., Ringle, C. M., Hult, G. T. M., & Sarstedt, M. (2021). Partial least squares structural equation modeling (PLS-SEM) Using R. In Cham: Springer (Issue November). https://doi.org/10.1007/978-3-319-57413-4_15
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24.
Hair, J. F., Sarstedt, M., Pieper, T. M., & Ringle, C. M. (2012). The use of partial least squares structural equation modeling in strategic management research: a review of past practices and recommendations for future applications. Long Range Planning, 45(5–6), 320–340. https://doi.org/10.1016/j.lrp.2012.09.008
Henseler, J. (2012). PLS-MGA: A non-parametric approach to partial least squares-based multi-group analysis. In W. A. Gaul, A. Geyer-Schulz, L. Schmidt-Thieme, & J. Kunze (Eds.), Challenges at the Interface of Data Analysis, Computer Science, and Optimization (pp. 495–501). Springer Berlin Heidelberg.
Hindun, I., Nurwidodo, N., & Candra Wicaksono, A. G. (2020). Metacognitive awareness components of high-academic ability students in biology hybrid learning: profile and correlation. Jpbi (Jurnal Pendidikan Biologi Indonesia). https://doi.org/10.22219/jpbi.v6i1.11097
Husna, H., Nerita, S., & Safitri, E. (2023). Analysis of student difficulties in learning biology. Journal of Biology Education Research (Jber). https://doi.org/10.55215/jber.v4i1.5963
Jumraeni, J., Suarja, S., Galugu, N. S., & Zainuri, Muh. I. (2023). Academic resilience: the roles of parent support and peer support. Jurnal Psikologi Pendidikan Dan Konseling Jurnal Kajian Psikologi Pendidikan Dan Bimbingan Konseling. https://doi.org/10.26858/jppk.v0i0.38854
Junpho, M., Songsriwittaya, A., & Tep, P. (2022). Reliability and construct validity of computational thinking scale for junior high school students: thai adaptation. International Journal of Learning Teaching and Educational Research. https://doi.org/10.26803/ijlter.21.9.9
Korkmaz, Ö., & Bai, X. (2019). Adapting computational thinking scale (CTS) for chinese high school students and their thinking scale skills level. Participatory Educational Research, 6(1), 10–26. https://doi.org/10.17275/per.19.2.6.1
Kusuma, A. S. H. M. (2023). Correlation in biological literacy and critical thinking skills of science students through problem-based learning model integrated by macromedia flash. Jurnal Pijar Mipa. https://doi.org/10.29303/jpm.v18i3.4928
Ledesma, J., & Linaugo, J. D. (2023). Mathematics anxiety, resiliency, and chemistry performance of grade 9 students. Technium Social Sciences Journal. https://doi.org/10.47577/tssj.v42i1.8712
Lim, M. L., & Chue, K. L. (2023). Academic resilience and test anxiety: the moderating role of achievement goals. School Psychology International. https://doi.org/10.1177/01430343231162876
Listiana, L., & Bahri. (2019). Empowering student’s creative thinking skill in biology classroom: potential of group investigation combined with think talk write (GITTW) Strategy. Humanities & Social Sciences Reviews, 7(3), 477–483.
Liu, T., Fan, S. C., & Jiang, X. (2025). How can qualitative in-depth interviews optimize cross-cultural measurement of academic resilience? Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2025.1444978
Madjid, Abd., Sutoyo, D. A., & Shodiq, S. F. (2021). Academic procrastination among students: the influence of social support and resilience mediated by religious character. Jurnal Cakrawala Pendidikan. https://doi.org/10.21831/cp.v40i1.34641
Mallick, M. K., & Kaur, S. (2016). Academic resilience among senior secondary school students: influence of learning environment. Rupkatha Journal on Interdisciplinary Studies in Humanities. https://doi.org/10.21659/rupkatha.v8n2.03
Maryanti, S., Nuryantini, A. Y., Pitriana, P., & Kurniawan, D. T. (2024). Implementation of an online programming software to explore the computational thinking ability of biological education students. Kne Social Sciences. https://doi.org/10.18502/kss.v9i8.15481
Masten, A. S., Lucke, C. M., Nelson, K. M., & Stallworthy, I. C. (2021). Resilience in development and psychopathology: multisystem perspectives. Annual Review of Clinical Psychology. https://doi.org/10.1146/annurev-clinpsy-081219-120307
Mohamad, E., Paputungan, M., & Dahiba, A. (2023). The effect of the problem-based learning (pbl) model with a multi-representation approach on students’ critical thinking skills in the buffer solution concept. E3s Web of Conferences. https://doi.org/10.1051/e3sconf/202340004001
Montas, M., Rao, S. R., Atassi, H. Al, Shapiro, M. C., Dean, J. R., & Salama, A. (2020). Relationship of grit and resilience to dental students’ academic success. Journal of Dental Education. https://doi.org/10.1002/jdd.12414
Najmah, N., Rusdi, R., & Ristanto, Rizhal H. (2024). Correlational between: biological literacy and metacognitive abilities with critical thinking in junior high school students. Jpbi (Jurnal Pendidikan Biologi Indonesia). https://doi.org/10.22219/jpbi.v10i3.35137
Ningsih, K. (2020). Analysis of prospective biology teacher capabilities in acquiring the learning concepts and biology science materials in junior high schools. Jurnal Pendidikan Matematika Dan Ipa. https://doi.org/10.26418/jpmipa.v11i1.31027
Omoyajowo, K., Danjin, M., Omoyajowo, K., Odipe, O., Mwadi, B., May, A., Amos Ogunyebi, & Rabie, M. (2023). Exploring the interplay of environmental conservation within spirituality and multicultural perspective: insights from a cross-sectional study. Environment, Development and Sustainability, May. https://doi.org/10.1007/s10668-023-03319-5
Paradise, C. J., & Bartkovich, L. (2021). Integrating citizen science with online biological collections to promote species and biodiversity literacy in an entomology course. Citizen Science Theory and Practice. https://doi.org/10.5334/cstp.405
Rudd, G., Meissel, K., & Meyer, F. (2022). Investigating the measurement of academic resilience in aotearoa new zealand using international large-scale assessment data. Educational Assessment Evaluation and Accountability. https://doi.org/10.1007/s11092-022-09384-0
Rukmana, D., Suhandi, A., Ramalis, T. R., & Samsudin, A. (2022). Religious values-based learning materials on earth and space science: analysis spirituality and conceptual understanding levels. Indonesian Journal of Science and Mathematics Education. https://doi.org/10.24042/ijsme.v5i3.12489
Salman, H. D., Mahdad, A., Khalifa Al-Hashmy, R. N., & Manshaee, G. (2024). The impact of academic self-concept, academic resilience, and academic engagement on the academic performance of wasit university students: the mediating role of emotional self-regulation and the moderating role of self-esteem. Jsied. https://doi.org/10.61838/jsied.4.1.1
Setiawan, A., Wardono, Wijayanti, K., Mulyono, M., & Bishtawi, H. O. (2024). The mathematical literacy process based on the students’ mathematical resilience. Journal of Ecohumanism. https://doi.org/10.62754/joe.v3i7.4420
Shao, Y., & Kang, S. (2022). The association between peer relationship and learning engagement among adolescents: the chain mediating roles of self-efficacy and academic resilience. Frontiers in Psychology. https://doi.org/10.3389/ fpsyg.2022.938756
Sirakaya, D. A. (2020). Investigation of computational thinking in the context of ict and mobile technologies. International Journal of Computer Science Education in Schools, 3(4), 50–59. https://doi.org/10.21585/ijcses.v3i4.73
Snow, E., Rutstein, D., Basu, S., Bienkowski, M., & Everson, H. T. (2019). Leveraging evidence-centered design to develop assessments of computational thinking practices. International Journal of Testing, 19(2), 103–127. https://doi.org/10.1080/15305058.2018.1543311
Sulsilah, H., Hidayat, A., & Ramalis, T. R. (2023). Analysis of computational thinking instrument for high school student using rasch model. Jurnal Penelitian Pendidikan Ipa. https://doi.org/10.29303/jppipa.v9i3.2771
Syamsiah, Jamaluddin, A. Bin, & Pratiwi, A. C. (2024). Exploring the impact of educational background, spiritual beliefs, and media exposure on environmental knowledge and attitudes. Eurasia Journal of Mathematics, Science and Technology Education, 20(11). https://doi.org/10.29333/ejmste/15644
Tangkui, R. (2023). Integrating computational thinking and the polya’s model in minecraft: the effects on learners’ fractions achievement. Indonesian Journal of Science and Mathematics Education. https://doi.org/10.24042/ijsme.v6i2.16033
Utami, R. K., & Subiantoro, A. W. (2021). Visual representations analysis of senior high school biology textbooks about plants’ structure and function. https://doi.org/10.2991/assehr.k.210305.019
Wang, H. H., & Wang, C. H. A. (2024). Teaching design students machine learning to enhance motivation for learning computational thinking skills. Acta Psychologica, 251(November), 104619. https://doi.org/10.1016/j.actpsy.2024.104619
Wright, L. K., Fisk, J. N., & Newman, D. L. (2014). DNA → RNA: What do students think the arrow means? Cbe—Life Sciences Education. https://doi.org/10.1187/cbe.cbe-13-09-0188
Wu, T., Silitonga, L. M., Dharmawan, B., & Murti, A. T. (2024). Empowering students to thrive: the role of ct and self-efficacy in building academic resilience. Journal of Educational Computing Research. https://doi.org/10.1177/07356331231225468
Yusupov, M. G., Prokhorov, A. O., & Chernov, A. V. (2020). Self-regulation of cognitive states: a conceptual perspective. https://doi.org/10.3897/ap.2.e2805
Refbacks
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.