Exploring the association between deep learning approach, problem-solving skills, digital literacy, and student learning outcomes: a data-driven nonparametric study in science education
DOI:
https://doi.org/10.58524/jasme.v6i2.1188Keywords:
Deep Learning Approach, Problem Solving Skills, Digital Literacy, Learning Outcomes, Nonparametric CorrelationAbstract
Background: The demands of 21st-century education require students to possess higher-order thinking skills, particularly problem-solving abilities, along with adequate digital literacy and optimal academic achievement. However, these competencies are often underdeveloped due to the continued use of surface-level instructional approaches that limit meaningful learning engagement.
Aims: This study aims to examine the association between the deep learning approach, problem-solving skills, digital literacy, and student learning outcomes, as well as to provide empirical evidence of the interrelationships among these variables in the context of science education.
Method: A quantitative correlational design was employed involving 121 tenth-grade students selected through proportionate random sampling from a population of 199 students. Data were collected using validated questionnaires measuring the deep learning approach, problem-solving skills, digital literacy, and learning outcomes. Prior to analysis, validity and reliability tests were conducted. Due to the non-normal distribution of one variable, Spearman’s Rho correlation analysis was applied.
Results: The findings revealed significant positive correlations between the deep learning approach and problem-solving skills, as well as digital literacy, both indicating moderate relationships. A weaker but statistically significant correlation was found between the deep learning approach and learning outcomes. Additionally, problem-solving skills and digital literacy demonstrated the strongest relationship among the variables.
Conclusion: These findings suggest that the deep learning approach is closely associated with the development of higher-order thinking and digital competencies, although its direct relationship with learning outcomes is limited. Therefore, integrating deep learning strategies with problem-solving and digital literacy activities is essential to enhance students’ readiness for 21st-century learning.
References
Akben, N. (2020). Effects of the problem-posing approach on students’ problem solving skills and metacognitive awareness in science education. Research in Science Education, 50(3), 1143–1165. https://doi.org/10.1007/s11165-018-9726-7
Alakrash, H. M., & Razak, N. A. (2021). Technology-based language learning: Investigation of digital technology and digital literacy. Sustainability, 13(21). https://doi.org/10.3390/su132112304
AlAli, R., & Wardat, Y. (2024). Innovative teaching: Building engagement, critical thinking, and lifelong learning skills. International Journal of Religion, 5(10), 2152–2163. https://doi.org/10.61707/fdpxd919
Almulla, M. A. (2023). Constructivism learning theory: A paradigm for students’ critical thinking, creativity, and problem solving to affect academic performance in higher education. Cogent Education, 10(1), 2172929. https://doi.org/10.1080/2331186X.2023.2172929
Almulla, M. A., & Al-Rahmi, W. M. (2023). Integrated social cognitive theory with learning input factors: The effects of problem-solving skills and critical thinking skills on learning performance sustainability. Sustainability, 15(5). https://doi.org/10.3390/su15053978
Amalina, I. K., & Vidákovich, T. (2023). Cognitive and socioeconomic factors that influence the mathematical problem-solving skills of students. Heliyon, 9(9). https://doi.org/10.1016/j.heliyon.2023.e19539
Anthonysamy, L., Koo, A. C., & Hew, S. H. (2020). Self-regulated learning strategies in higher education: Fostering digital literacy for sustainable lifelong learning. Education and Information Technologies, 25(4), 2393–2414. https://doi.org/10.1007/s10639-020-10201-8
Basid, A., Sutrisno, E., & Aliyeva, L. R. (2024). Analysis of the effect of contextual problem solving on students’ mathematical reasoning ability. International Journal of Science and Mathematics Education, 1(3), 24–33. https://doi.org/10.62951/ijsme.v1i3.258
Blau, I., Shamir-Inbal, T., & Avdiel, O. (2020). How does the pedagogical design of a technology-enhanced collaborative academic course promote digital literacies, self-regulation, and perceived learning of students? The Internet and Higher Education, 45, 100722. https://doi.org/10.1016/j.iheduc.2019.100722
Braßler, M. (2024). Students’ digital competence development in the production of open educational resources in education for sustainable development. Sustainability, 16(4). https://doi.org/10.3390/su16041674
Brink, H. W., Loomans, M. G. L. C., Mobach, M. P., & Kort, H. S. M. (2021). Classrooms’ indoor environmental conditions affecting the academic achievement of students and teachers in higher education: A systematic literature review. Indoor Air, 31(2), 405–425. https://doi.org/10.1111/ina.12745
Buchan, M. C., Bhawra, J., & Katapally, T. R. (2024). Navigating the digital world: Development of an evidence-based digital literacy program and assessment tool for youth. Smart Learning Environments, 11(1), 8. https://doi.org/10.1186/s40561-024-00293-x
Carroll, M., Lindsey, S., Chaparro, M., & Winslow, B. (2021). An applied model of learner engagement and strategies for increasing learner engagement in the modern educational environment. Interactive Learning Environments, 29(5), 757–771. https://doi.org/10.1080/10494820.2019.1636083
Cayubit, R. F. O. (2022). Why learning environment matters? An analysis on how the learning environment influences the academic motivation, learning strategies and engagement of college students. Learning Environments Research, 25(2), 581–599. https://doi.org/10.1007/s10984-021-09382-x
Ceballos, H., van den Bogaart, T., van Ginkel, S., Spandaw, J., & Drijvers, P. (2026). How collaborative problem solving promotes higher-order thinking skills: A systematic review of design features and processes. Thinking Skills and Creativity, 59, 102001. https://doi.org/10.1016/j.tsc.2025.102001
Dixit, B., Bedekar, M., Jahagirdar, A., & Sathe, N. (2021). Role of active learning techniques in development of problem solving skills. Journal of Engineering Education Transformations, 670–674. https://doi.org/10.16920/jeet/2021/v34i0/157241
Falloon, G. (2020). From digital literacy to digital competence: The teacher digital competency (TDC) framework. Educational Technology Research and Development, 68(5), 2449–2472. https://doi.org/10.1007/s11423-020-09767-4
Forthmann, B., Szardenings, C., & Holling, H. (2020). Understanding the confounding effect of fluency in divergent thinking scores: Revisiting average scores to quantify artifactual correlation. Psychology of Aesthetics, Creativity, and the Arts, 14(1), 94–112. https://doi.org/10.1037/aca0000196
Gomez, M. J. (2025). The impact of inquiry-based learning in science education: A systematic review of student engagement and achievement. Journal of Education, Learning, and Management, 2(2), 353–363. https://doi.org/10.69739/jelm.v2i2.1143
Hooshyar, D., Tammets, K., Ley, T., Aus, K., & Kollom, K. (2023). Learning analytics in supporting student agency: A systematic review. Sustainability, 15(18). https://doi.org/10.3390/su151813662
Huang, S.-Y., Kuo, Y.-H., & Chen, H.-C. (2020). Applying digital escape rooms infused with science teaching in elementary school: Learning performance, learning motivation, and problem-solving ability. Thinking Skills and Creativity, 37, 100681. https://doi.org/10.1016/j.tsc.2020.100681
Indah, R. N., Toyyibah, T., Budhiningrum, A. S., & Afifi, N. (2022). The research competence, critical thinking skills and digital literacy of Indonesian EFL students. Journal of Language Teaching and Research, 13(2), 315–324. https://doi.org/10.17507/jltr.1302.11
Kania, N., & Kusumah, Y. S. (2025). The measurement of higher-order thinking skills: A systematic literature review. Malaysian Journal of Learning and Instruction, 22(1), 97–116. https://doi.org/10.32890/mjli2025.22.1.6
Kanphukiew, S., & Nuangchalerm, P. (2024). Enhancing scientific problem-solving and learning achievement of lower secondary students through active learning management. Jurnal Pendidikan IPA Indonesia, 13(1), 172–181. https://doi.org/10.15294/jpii.v13i1.47672
Kaya, M., & Erdem, C. (2021). Students’ well-being and academic achievement: A meta-analysis study. Child Indicators Research, 14(5), 1743–1767. https://doi.org/10.1007/s12187-021-09821-4
Khodadad, D. (2023). Creating a supportive and effective learning environment for engineering students: Pedagogical strategies, engagement, and enhanced outcomes. International Journal of Engineering Pedagogy, 13(8), 33. https://doi.org/10.3991/ijep.v13i8.41755
Kim, J., Gilbert, J., Yu, Q., & Gale, C. (2021). Measures matter: A meta-analysis of the effects of educational apps on preschool to grade 3 children’s literacy and math skills. AERA Open, 7, 23328584211004183. https://doi.org/10.1177/23328584211004183
Kristanto, W., Harun, H., Syamsudin, A., & Hendrowibowo, L. (2024). Student engagement and digital literacy in knowledge acquisition in seamless learning. Ubiquitous Learning: An International Journal, 18(1), 113–133. https://doi.org/10.18848/1835-9795/CGP/v18i01/113-133
Lee, D.-C., & Chang, C.-Y. (2025). Evaluating self-directed learning competencies in digital learning environments: A meta-analysis. Education and Information Technologies, 30(6), 6847–6868. https://doi.org/10.1007/s10639-024-13083-2
Li, J., & Xue, E. (2023). Dynamic interaction between student learning behaviour and learning environment: Meta-analysis of student engagement and its influencing factors. Behavioral Sciences, 13(1). https://doi.org/10.3390/bs13010059
Lugosi, E., & Uribe, G. (2022). Active learning strategies with positive effects on students’ achievements in undergraduate mathematics education. International Journal of Mathematical Education in Science and Technology, 53(2), 403–424. https://doi.org/10.1080/0020739X.2020.1773555
Ma, W., Motevalli, S., Kuang, X., & Song, R. (2025). The mediating role of emotion regulation and cognitive flexibility in the relationship between cooperative learning and social skills of students: A cross-sectional study. BMC Psychology, 13(1), 1302. https://doi.org/10.1186/s40359-025-03649-1
Mahanal, S., Zubaidah, S., Setiawan, D., Maghfiroh, H., & Muhaimin, F. G. (2022). Empowering college students’ problem-solving skills through RICOSRE. Education Sciences, 12(3). https://doi.org/10.3390/educsci12030196
Martin, F., Dennen, V. P., & Bonk, C. J. (2020). A synthesis of systematic review research on emerging learning environments and technologies. Educational Technology Research and Development, 68(4), 1613–1633. https://doi.org/10.1007/s11423-020-09812-2
Nguyen, L. A. T., & Habók, A. (2024). Tools for assessing teacher digital literacy: A review. Journal of Computers in Education, 11(1), 305–346. https://doi.org/10.1007/s40692-022-00257-5
Nikou, S., De Reuver, M., & Mahboob Kanafi, M. (2022). Workplace literacy skills: How information and digital literacy affect adoption of digital technology. Journal of Documentation, 78(7), 371–391. https://doi.org/10.1108/JD-12-2021-0241
Nopas, D. (2025). Algorithmic learning or learner autonomy? Rethinking AI’s role in digital education. Qualitative Research Journal. https://doi.org/10.1108/QRJ-11-2024-0282
Oh, S. S., Kim, K.-A., Kim, M., Oh, J., Chu, S. H., & Choi, J. (2021). Measurement of digital literacy among older adults: Systematic review. Journal of Medical Internet Research, 23(2), e26145. https://doi.org/10.2196/26145
Perrotta, C., & Selwyn, N. (2020). Deep learning goes to school: Toward a relational understanding of AI in education. Learning, Media and Technology, 45(3), 251–269. https://doi.org/10.1080/17439884.2020.1686017
Rahimi, R. A., & Oh, G. S. (2024). Rethinking the role of educators in the 21st century: Navigating globalization, technology, and pandemics. Journal of Marketing Analytics, 12(2), 182–197. https://doi.org/10.1057/s41270-024-00303-4
Rui, L., Nasri, N. M., & Mahmud, S. N. D. (2024). The role of self-directed learning in promoting deep learning processes: A systematic literature review. F1000Research. https://doi.org/10.12688/f1000research.150612.1
Sandbrink, K., & Summerfield, C. (2024). Modelling cognitive flexibility with deep neural networks. Current Opinion in Behavioral Sciences, 57, 101361. https://doi.org/10.1016/j.cobeha.2024.101361
Sarker, I. H. (2021). Data science and analytics: An overview from data-driven smart computing, decision-making and applications perspective. SN Computer Science, 2(5), 377. https://doi.org/10.1007/s42979-021-00765-8
Scheel, L., Vladova, G., & Ullrich, A. (2022). The influence of digital competences, self-organization, and independent learning abilities on students’ acceptance of digital learning. International Journal of Educational Technology in Higher Education, 19(1), 44. https://doi.org/10.1186/s41239-022-00350-w
Sedrakyan, G., Malmberg, J., Verbert, K., Järvelä, S., & Kirschner, P. A. (2020). Linking learning behavior analytics and learning science concepts: Designing a learning analytics dashboard for feedback to support learning regulation. Computers in Human Behavior, 107, 105512. https://doi.org/10.1016/j.chb.2018.05.004
Shanta, S., & Wells, J. G. (2022). T/E design based learning: Assessing student critical thinking and problem solving abilities. International Journal of Technology and Design Education, 32(1), 267–285. https://doi.org/10.1007/s10798-020-09608-8
Sholihah, T. M., & Lastariwati, B. (2020). Problem based learning to increase competence of critical thinking and problem solving. Journal of Education and Learning (EduLearn), 14(1), 148–154. https://doi.org/10.11591/edulearn.v14i1.13772
Smith, R., Snow, P., Serry, T., & Hammond, L. (2021). The role of background knowledge in reading comprehension: A critical review. Reading Psychology, 42(3), 214–240. https://doi.org/10.1080/02702711.2021.1888348
Tan, A.-L., Ong, Y. S., Ng, Y. S., & Tan, J. H. J. (2023). STEM problem solving: Inquiry, concepts, and reasoning. Science & Education, 32(2), 381–397. https://doi.org/10.1007/s11191-021-00310-2
Taye, M. M. (2023). Understanding of machine learning with deep learning: Architectures, workflow, applications and future directions. Computers, 12(5). https://doi.org/10.3390/computers12050091
Tinmaz, H., Fanea-Ivanovici, M., & Baber, H. (2022). A snapshot of digital literacy. Library Hi Tech News, 40(1), 20–23. https://doi.org/10.1108/LHTN-12-2021-0095
Triana, H., & Suryadi. (2025). The relationship of digital literacy and student engagement on student English learning. IDEAS: Journal on English Language Teaching and Learning, Linguistics and Literature, 13(1), 1482–1490. https://doi.org/10.24256/ideas.v13i1.7040
Tusino, & Dewi, P. (2025). The effects of technology-enhanced deep learning on autonomy of EFL learners with disabilities. The New Educational Review, 82, 158–170. https://doi.org/10.15804/tner.2025.82.4.11
Usfandi Haryaka, N. K. R. (2025). Integrating digital literacy, critical thinking, and collaborative learning: Addressing contemporary challenges in 21st century education. Journal of Hunan University Natural Sciences, 52(3). https://doi.org/10.55463/issn.1674-2974.52.3.9
von Rueden, L., Mayer, S., Beckh, K., Georgiev, B., Giesselbach, S., Heese, R., Kirsch, B., Pfrommer, J., Pick, A., Ramamurthy, R., Walczak, M., Garcke, J., Bauckhage, C., & Schuecker, J. (2023). Informed machine learning: A taxonomy and survey of integrating prior knowledge into learning systems. IEEE Transactions on Knowledge and Data Engineering, 35(1), 614–633. https://doi.org/10.1109/TKDE.2021.3079836
Weng, C., Chen, C., & Ai, X. (2023). A pedagogical study on promoting students’ deep learning through design-based learning. International Journal of Technology and Design Education, 33(4), 1653–1674. https://doi.org/10.1007/s10798-022-09789-4
Wu, H., & Molnár, G. (2022). Analysing complex problem-solving strategies from a cognitive perspective: The role of thinking skills. Journal of Intelligence, 10(3). https://doi.org/10.3390/jintelligence10030046
Yang, Y., Luo, J., Yang, M., Yang, R., & Chen, J. (2024). From surface to deep learning approaches with generative AI in higher education: An analytical framework of student agency. Studies in Higher Education, 49(5), 817–830. https://doi.org/10.1080/03075079.2024.2327003
Yasa, A. D., Rahayu, S., Handayanto, S. K., & Ekawati, R. (2024). Evaluating the impact of smart learning-based inquiry on enhancing digital literacy and critical thinking skills. Ingénierie des Systèmes d’Information, 29(1), 219–233. https://doi.org/10.18280/isi.290122
Yaseen, H., Mohammad, A. S., Ashal, N., Abusaimeh, H., Ali, A., & Sharabati, A.-A. A. (2025). The impact of adaptive learning technologies, personalized feedback, and interactive AI tools on student engagement: The moderating role of digital literacy. Sustainability, 17(3). https://doi.org/10.3390/su17031133
Young, F., Cleveland, B., & Imms, W. (2020). The affordances of innovative learning environments for deep learning: Educators’ and architects’ perceptions. The Australian Educational Researcher, 47(4), 693–720. https://doi.org/10.1007/s13384-019-00354-y
Yuan, N., Yu, Q., & Liu, W. (2025). The impact of digital literacy on learning outcomes among college students: The mediating effect of digital atmosphere, self-efficacy for digital technology and digital learning. Frontiers in Education, 10. https://doi.org/10.3389/feduc.2025.1641687
Yuniarti, N., Rahmawati, Y., Anwar, M., Al Hakim, V. G., Hidayat, H., Hariyanto, D., Husna, A. F., & Wang, J.-H. (2024). Augmented reality-based higher order thinking skills learning media: Enhancing learning performance through self-regulated learning, digital literacy, and critical thinking skills in vocational teacher education. European Journal of Education, 59(4), e12725. https://doi.org/10.1111/ejed.12725
Zhang, F., Wang, X., & Zhang, X. (2025). Applications of deep learning method of artificial intelligence in education. Education and Information Technologies, 30(2), 1563–1587. https://doi.org/10.1007/s10639-024-12883-w
Zhao, Y., Lin, S., Liu, J., Zhang, J., & Yu, Q. (2021). Learning contextual factors, student engagement, and problem-solving skills: A Chinese perspective. Social Behavior and Personality: An International Journal, 49(2), 1–18. https://doi.org/10.2224/sbp.9796
Zhou, Q., Zhang, H., & Li, F. (2024). The impact of online interactive teaching on university students’ deep learning: The perspective of self-determination. Education Sciences, 14(6). https://doi.org/10.3390/educsci14060664
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Eviana, Achmadi, Afandi
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
