Promoting computational and higher-order thinking skills through problem-based learning with digital argumentation in biodiversity

Authors

  • Marheny Lukitasari Universitas PGRI Madiun Author
  • Agita Risma Nurhikmawati Universitas PGRI Madiun Author
  • Wasilatul Murtafiah Universitas Pendidikan Mandalika Author
  • Akhmad Sukri Universitas Pendidikan Mandalika Author
  • Jomar Urbano PHINMA Rizal College of Laguna Author
  • Analiza B. Tanghal Nueva Ecija University of Science and Technology image/svg+xml Author
  • Rusdi Hasan Padjadjaran University image/svg+xml Author

DOI:

https://doi.org/10.36681/tused.2025.033

Keywords:

Problem-based learning, digital argumentation, computational thinking, HOTs

Abstract

Problem-based learning integrated with Digital Argumentation (PBL-DA) is a learning strategy for optimizing innovative learning in the digital era. This research aimed to investigate whether the application of PBL-DA can foster the Computational Thinking (CT) and Higher Order Thinking Skills (HOTs). A quasi-experimental design measured three aspects: skill (decomposition, algorithm design, evaluation), attitude (confidence, communication, flexibility), and approach (tinkering, creating, collaborating). The students' HOTs were measured through eight aspects: critical thinking, argumentation, problem-solving, problem-identifying, understanding concepts, analysing, making decisions, and creative thinking. The students' CT and HOTs scores of control and experimental classes were analyzed using Hotelling’s T² test and Tukey’s post hoc test. The Hotelling’s T² test revealed a significant difference between the experimental and control classes for both CT and HOTs (T² = 0.340, p < 0.001 for CT; T² = 0.718, p < 0.001 for HOTs). Tukey’s test further showed that PBL-DA significantly impacted the CT skill and attitude aspects (p < 0.01), while the approach aspect was not significant (p > 0.05). For HOTs, critical thinking, argumentation, problem-identifying and analyzing were significantly improved (p < 0.01), but problem-solving, understanding concepts, making decisions, and creative thinking showed no significant improvement (p > 0.05). Pearson’s correlation analysis indicated a strong positive correlation (r = 0.651, p < 0.001) between students' CT and HOTs skills. These findings provide evidence of the effectiveness of the PBL-DA model in improving students' CT and HOTs, demonstrating its potential for fostering critical and higher-order thinking skills in the digital era.

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References

Alkhatib, O. J. (2019). A framework for ımplementing higher-order thinking skills (problem-solving, critical thinking, creative thinking, and decision-making) in engineering & humanities. 2019 Advances in Science and Engineering Technology International Conferences (ASET), 1–8. https://doi.org/10.1109/ICASET.2019.8714232

Allchin, D. (2013). Problem and case-based learning in science: An ıntroduction to distinctions , values , and outcomes. CBE—Life Sciences Education, 12, 364–372. https://doi.org/10.1187/cbe.12-11-0190

Anderson, L. W., Krathwohl Peter W Airasian, D. R., Cruikshank, K. A., Mayer, R. E., Pintrich, P. R., Raths, J., & Wittrock, M. C. (2001). A taxonomy for learning, teaching, and assessing a revision of bloom’s taxonomy of educational objectives. Addison Wesley Longman, Inc. https://www.uky.edu/~rsand1/china2018/texts/Anderson-Krathwohl - A taxonomy for learning teaching and assessing.pdf

Andrews, R. (2015). Critical thinking and/or argumentation in higher education. In M. Davies et al. (Ed.), The palgrave handbook of critical thinking in higher education. Palgrave Macmillan. New York. https://doi.org/10.1057/9781137378057

Aryan, Hegade, P., & Shettar, A. (2022). Effectiveness of computational thinking in problem based learning. Journal of Engineering Education Transformations, 36(Special Issue 2), 179–185. https://doi.org/10.16920/jeet/2023/v36is2/23025

Bhaumik, K., Sudhakara Reddy, S., Datta, A., Ismayel, G., & Mabu Sarif, B. (2024). Fostering higher-order thinking: Pedagogical strategies in engineering education. Journal of Engineering Education Transformations, 38(1), 86–99. https://doi.org/10.16920/jeet/2024/v38i1/24177

Cantona, I. G. E., Suastra, I. W., & Ardana, I. M. (2023). HOTS oriented problem-based learning model: Improving critical thinking skills and learning outcomes of fifth grade students in science learning. Thinking Skills and Creativity Journal, 6(1), 19–26. https://doi.org/10.23887/tscj.v6i1.61654

Csizmadia, A., Curzon, P., Dorling, M., Humphreys, S., Ng, T., Selby, C., & Woollard, J. (2015). Computational thinking: A guide for teachers. Hodder Education. Hachette. United Kingdom

Duch, B., D., G., & Allen, D. (2001). The power of problem-based learning: A practical ‘how to’ for teaching undergraduate courses in any discipline. Stylus Publishing LLC

Fan, Y. C., Wang, T. H., & Wang, K. H. (2020). Studying the effectiveness of an online argumentation model for improving undergraduate students’ argumentation ability. Journal of Computer Assisted Learning, 36(4), 526–539. https://doi.org/10.1111/jcal.12420

Fields, D., Lui, D., Kafai, Y., Jayathirtha, G., Shaw, M., Fields, D., Lui, D., Kafai, Y., Jayathirtha, G., Walker, J., & Walker, J. (2021). Communicating about computational thinking : understanding affordances of portfolios for assessing high school students ’ computational thinking and participation practices Communicating about computational thinking : understanding affordances of portfoli. Computer Science Education, 00(00), 1–35. https://doi.org/10.1080/08993408.2020.1866933

Gao, X., & Hew, K. F. (2022). Toward a 5e-based flipped classroom model for teaching computational thinking in elementary school: effects on student computational thinking and problem-solving performance. Journal of Educational Computing Research, 60(2), 512–543. https://doi.org/10.1177/07356331211037757

Giannetto, M. L., & Vincent, L. (2014). Motivating students to achieve higher-order thinking skills through problem solving. Mathematics Teacher Learning and Teaching, 95(9), 718–723

Gilbert, G. E., & Prion, S. (2016). Making sense of methods and measurement: lawshe’s content validity ındex. Clinical Simulation in Nursing, 12(12), 530–531. https://doi.org/10.1016/j.ecns.2016.08.002

Gordillo-tenorio, W., & Cabanillas-carbonell, M. (2023). Information technologies that help ımprove academic performance: A review of the literature. International Journal of Emerging Technologies in Learning (IJET), 18(04), 262–279

Green, B. (2017). The method of successive ıntervals: A sourcebook for behavioral scientists. Routledge. https://doi.org/10.4324/9781315128948-13

Greenbank, P. (2010). Developing decision-making skills in students: An active learning approach. Edge Hill University

Habók, A., & Nagy, J. (2016). In-service teachers’ perceptions of project-based learning. SpringerPlus, 5(1), 1–14. https://doi.org/10.1186/s40064-016-1725-4

Hajj, M. El, & Harb, H. (2023). Rethinking education: An ın-depth examination of modern technologies and pedagogic recommendations. IAFOR Journal of Education, 11(2), 97–113. https://doi.org/10.22492/ije.11.2.05

Haryani, S., Prasetya, A. T., & Permanasari, A. (2014). Developing metacognition of teacher candidates by ımplementing problem based learning within the area of analytical chemistry. International Journal of Science and Research, 3(6), 1223–1229

Hill, S. (2015). Understanding “computational thinking.” 4(3), 74–75. https://www.mendeley.com/catalogue/405e343d-f9e0-3bf2-8422-0848effdbaa9/?utm_source=desktop

Hopson, M. H., Simms, R. L., & Knezek, G. A. (2001). Using a technology-enriched environment to improve higher-order thinking skills. Journal of Research on Technology in Education, 34(2), 109–119. https://doi.org/10.1080/15391523.2001.10782338

Hunsaker, E. (2020). The K-12 educational technology handbook computational thinking. Edtech Books. https://new.edtechbooks.org/k12handbook/author_list

Jawawi, D. N. A., Jamal, N. N., Halim, S. A., Sa’adon, N. A., Mamat, R., Isa, M. A., Mohamad, R., & Hamed, H. N. A. (2022). Nurturing secondary school student computational thinking through educational robotics. International Journal of Emerging Technologies in Learning, 17(3), 117–128.

Jazuli, I., Rahmayanti, H., Purwanto, A., Vivanti, D., Miarsyah, M., & Weslem, P. (2020). HOTS-AEP-COVID-19 and ILMIZI learning model : The 21 st -century environmental learning in senior high. Jurnal Pendidikan Biologi Indonesia, 6(2), 265–272.

Jensen, J. L., Mcdaniel, M. A., Woodard, S. M., & Kummer, T. A. (2014). Teaching to the test or testing to teach : Exams requiring higher order thinking skills encourage greater conceptual understanding. Education Psychology Rev. https://doi.org/10.1007/s10648-013-9248-9

Kale, U., Akcaoglu, M., Cullen, T., Goh, D., Devine, L., Calvert, N., & Grise, K. (2018). Computational what? Relating computational thinking to teaching. TechTrends, 62(6), 574–584. https://doi.org/10.1007/s11528-018-0290-9

Karami, M., Karami, Z., & Attaran, M. (2013). Integrating problem-based learning with ICT for developing trainee teachers’ content knowledge and teaching skill. International Journal of Education & Development Using Information & Communication Technology, 9(1), 36–49. http://search.ebscohost.com/login.aspx?direct=true&db=ehh&AN=88933218&site=ehost-live%5Cnhttp://content.ebscohost.com/ContentServer.asp?T=P&P=AN&K=88933218&S=R&D=ehh&EbscoContent=dGJyMNXb4kSep7I4yNfsOLCmr02eprRSsqe4TLCWxWXS&ContentCustomer=dGJyMPGrski3r7J

Kelly, K. L. (2016). Emergent arguments: Digital media and social argumentation. Journal of Chemical Information and Modeling. https://doi.org/https://doi.org/10.1017/CBO9781107415324.004

Kelly, K. L., Crosswhite, J., & Bivins, T. (2016). Emergent Arguments; Digital Media And Social Argumentation. [Unpublished doctoral dissertation]. University of Oregon

Labak, I., Kujundžić, I., & Bognar, B. (2024). The effect of changes in teaching methods on pupils ’ academic performance in biology. Journal of Turkish Science Education, 21(3), 448–466.

Lawshe, C. H. (1975). A quantitative approach to content validity”.Personnel Psychology. Personnel Psychology, 28, 563–575.

Lee, K., & Cho, J. (2021). Computational thinking evaluation tool development for early childhood software education. International Journal on Informatics Visualization, 5(3), 313–319. https://doi.org/10.30630/joiv.5.3.672

Lee, S. M. (2014). The relationships between higher order thinking skills, cognitive density, and social presence in online learning. The Internet and Higher Education, 21, 41–52. https://doi.org/10.1016/j.iheduc.2013.12.002

Liline, S., Tomhisa, A., Rumahlatu, D., & Sangur, K. (2024). The effect of the Pjb-Hots learning model on cognitive learning , analytical thinking skills , creative thinking skills , and metacognitive skills of biology education students. Journal of Turkish Science Education, 21(1), 175–195. https://doi.org/10.36681/tused.2024.010

Lukitasari, M., Handhika, J., & Murtafiah, W. (2018). Higher order thinking skills : Using e-portfolio in project- based learning. Journal of Physics, 983, 1–7.

Lukitasari, M., Handhika, J., & Murtafiah, W. (2021). Model pembelajaran berdasarkan masalah melalui digital argumentation (PBM-DA). AE Media Grafika

Lukitasari, M., Handika, J., Murtafiah, W., & Nurhikmawati, A. R. (2020). Examining students’ self-assessment of digital argumentation (SADA) in e-biology class: A rasch analysis. JPBI (Jurnal Pendidikan Biologi Indonesia), 6(2), 209–216. https://doi.org/10.22219/jpbi.v6i2.11919

Lye, S. Y., & Koh, J. H. L. (2014). Review on teaching and learning of computational thinking through programming: What is next for K-12? Computers in Human Behavior, 41, 51–61. https://doi.org/10.1016/j.chb.2014.09.012

Milroy, S. P. (2021). Field Methods in Marine Science. Garland Science. https://doi.org/10.1201/9781317302292-8

Montoneri, B. (2014). Teaching ımprovement model designed with DEA method and management matrix. IAFOR Journal of Education, 2(1), 125–156. https://doi.org/10.22492/ije.2.1.05

Mubuuke, A. G., Louw, A. J. N., & Van Schalkwyk, S. (2016). Cognitive and social factors ınfluencing students׳ response and utilization of facilitator feedback in a problem based learning context. Health Professions Education, 3(2), 85–98. https://doi.org/10.1016/j.hpe.2016.09.003

Nantha, C., Pimdee, P., & Sitthiworachart, J. (2022). A quasi-experimental evaluation of classes using traditional methods, problem-based learning, and flipped learning to enhance thai student-teacher problem-solving skills and academic achievement. International Journal of Emerging Technologies in Learning, 17(4), 20–38.

Nilson, L. (2010). Teaching at ıts best teaching at ıts best: A research-based resource for college ınstructors. John Wiley & Sons, Inc.

Nirbita, B. N., Joyoatmojo, S., & Sudiyanto, S. (2018). ICT media assisted problem based learning for critical thinking ability. International Journal of Multicultural and Multireligious Understanding, 5(4), 341. https://doi.org/10.18415/ijmmu.v5i4.295

Pereira, D., Afonso, A., & Medeiros, F. (2015). Overview of Friedman’s test and post-hoc analysis. Communications in Statistics-Simulation and Computation, 44, 2636–2653. https://doi.org/10.1080/03610918.2014.931971

Skelin, S., Schlueter, B., Rolle, D., & Gaedicke, G. (2008). Problem-based learning (PBL). Monatsschrift Kinderheilkunde - Monatsschr Kınderheılk, 156, 452–457.

Srivastava, D. K., & Mudholkar, G. S. (2001). Trimmed T̃2: A robust analog of hotelling’s T2. Journal of Statistical Planning and Inference, 97(2), 343–358. https://doi.org/10.1016/S0378-3758(00)00239-1

Tanujaya, B., Mumu, J., & Margono, G. (2017). The relationship between higher order thinking skills and academic performance of student in mathematics ınstruction. International Education Studies, 10(11), 78. https://doi.org/10.5539/ies.v10n11p78

Tosun, C., & Senocak, E. (2013). The effects of problem-based learning on metacognitive awareness and attitudes toward chemistry of prospective teachers with different academic backgrounds. Australian Journal of Teacher Education, 38(3). https://doi.org/10.14221/ajte.2013v38n3.2

Tsortanidou, X., Daradoumis, T., & Barberá, E. (2019). Connecting moments of creativity, computational thinking, collaboration and new media literacy skills. Information and Learning Science, 120(11–12), 704–722. https://doi.org/10.1108/ILS-05-2019-0042

Viyanti, C., Sunarno, W., & Prasetyo, Z. K. (2020). Reconstruction of higher order thinking skill through enriching student’s argumentation skills. Jurnal Pendidikan Progresif, 10(2), 327–335. https://doi.org/10.23960/jpp.v10.i2.202016

Voon, X. P., Wong, S. L., Wong, L. H., Khambari, M. N. M., & Syed-Abdullah, S. I. S. (2022). Developing computational thinking competencies through constructivist argumentation learning: a problem-solving perspective. International Journal of Information and Education Technology, 12(6), 529–539. https://doi.org/10.18178/ijiet.2022.12.6.1650

Williams, M., Lively, M., & Harper, J. (1994). Higher order thinking skills : tools for bridging the gap. Foreign Language Annals, 27(3), 405–426

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Published

27.11.2025

How to Cite

Lukitasari, M., Risma Nurhikmawati, A., Murtafiah, W. ., Sukri , A., Urbano , J., B. Tanghal , A., & Hasan , R. (2025). Promoting computational and higher-order thinking skills through problem-based learning with digital argumentation in biodiversity. Journal of Turkish Science Education, 22(4), 655-676. https://doi.org/10.36681/tused.2025.033