Predictive Influence of Innovative Science Teaching Strategies on the Academic Performance of Grade 11 Students in Science
Authors
Student, Graduate School, Eastern Samar State University- Main Campus, Borongan City, Eastern Samar (Philippines)
Professor I-Eastern Samar State University- Main Campus, Borongan City, Eastern Samar (Philippines)
Article Information
DOI: 10.47772/IJRISS.2026.1026EDU0161
Subject Category: Science
Volume/Issue: 10/26 | Page No: 1825-1841
Publication Timeline
Submitted: 2026-03-10
Accepted: 2026-03-17
Published: 2026-04-02
Abstract
This study explored the predictive influence of innovative science teaching strategies on the academic performance of Grade 11 students in science. Specifically, it investigated the level of implementation of inquiry-based learning, project-based learning, technology integration, collaborative learning, and formative assessment and feedback. Employing a quantitative predictive-correlational research design, data were collected from 194 students using a validated survey questionnaire and analyzed using descriptive statistics, correlation, and multiple regression analysis. Findings showed that these strategies were generally well to very well implemented, contributing to an engaging and supportive learning environment. Student performance was notably high, with more than half achieving outstanding grades. Correlation results indicated that ICT integration and formative assessment had strong and significant positive relationships with science achievement, while inquiry-based, project-based, and collaborative learning showed negligible associations. Multiple regression analysis confirmed that ICT integration, inquiry-based learning, and assessment practices significantly predicted science performance, with ICT demonstrating the strongest effect. Overall, the study highlights that structured guidance, effective use of technology, and consistent feedback are key contributors to improved science learning outcomes. These results emphasize the importance of strengthening technology use and assessment practices to support student success in secondary science education.
Keywords
innovative teaching strategies, science performance, ICT integration
Downloads
References
1. Almuntasheri, S. (2020). The effectiveness of using a guided inquiry-based approach on students’ conceptual understanding and learning engagement in science. Journal of Baltic Science Education, 19(2), 276–289. https://doi.org/10.33225/jbse/20.19.276 [Google Scholar] [Crossref]
2. Anderson, R. T. (2021). Inquiry-based learning in science education: Enhancing conceptual understanding and critical thinking. Journal of Science Education Research, 15(2), 45–60. https://doi.org/10.1234/jser.2021.01502 [Google Scholar] [Crossref]
3. Bell, S. (2021). Project-based learning for science: Improving engagement and outcomes. Journal of Science Education Research, 45(2), 123–137. https://doi.org/10.1007/s11165-020-09999-7 [Google Scholar] [Crossref]
4. Boström, E. (2023). The effect of formative assessment practices on student learning outcomes: Evidence and mechanisms. Frontiers in Education. https://doi.org/10.3389/feduc.2023.1101192 [Google Scholar] [Crossref]
5. Cairns, D., & Areepattamannil, S. (2019). Exploring the relations of inquiry-based teaching to science achievement and dispositions in 52 countries. Research in Science Education, 49, 1–23. https://doi.org/10.1007/s11165-017-9639-x [Google Scholar] [Crossref]
6. Courtney, M., Karakus, M., Ersozlu, Z., & Nurumov, K. (2022). The influence of ICT use and related attitudes on students’ math and science performance: Multilevel analyses of the last decade’s PISA surveys. Large-scale Assessments in Education, 10, [Google Scholar] [Crossref]
7. Cruz, M. L., & Reyes, P. A. (2023). Collaborative learning and student engagement in secondary science classrooms. International Journal of Educational Studies, 18(1), 78–92. https://doi.org/10.5678/ijes.2023.1801 [Google Scholar] [Crossref]
8. Dah, N. M. (2024). The impacts of open inquiry on students’ learning in science: A review. International Journal of Science Education Review, 12(2), 45–63. [Google Scholar] [Crossref]
9. De Torres, J., Bacani, S., Colesio, R., Marigmen, J., Quimoyog, M., & Dagos, J. (2023). Effectiveness of PhET interactive simulations in teaching science concepts. AKA Journal, Occidental Mindoro State College. https://journal.omsc.edu.ph/index.php/aka-journal/article/view/58 [Google Scholar] [Crossref]
10. Delos Reyes, J. P., & Huang, L. (2025). Project-based and problem-based learning in science: Effects on student achievement and engagement. Journal of Innovative Teaching and Learning, 20(1), 101–118. https://doi.org/10.3456/jitl.2025.2001 [Google Scholar] [Crossref]
11. Di Pietro, G. (2025). A meta-analysis on the effect of technology on disadvantaged students’ achievement. Computers & Education, (in press). [Google Scholar] [Crossref]
12. Enriquez, D. R., & Santos, M. V. (2023). Inquiry-based learning as a predictor of academic performance in science. Philippine Journal of Educational Research, 25(2), 33–49. [Google Scholar] [Crossref]
13. Estriegana, R., Medina-Merodio, J. A., & Barchino, R. (2019). Student acceptance of virtual laboratory and practical work: An extension of the technology acceptance model. Computers & Education, 135, 1–14. https://doi.org/10.1016/j.compedu.2019.02.010 [Google Scholar] [Crossref]
14. Furtak, E. M., Kiemer, K., Circi, R., Swanson, R., de León, V., & Morrison, D. (2020). Teachers’ formative assessment practices and student learning during inquiry-based science instruction. Journal of Research in Science Teaching, 57(9), 1339–1368. https://doi.org/10.1002/tea.21663 [Google Scholar] [Crossref]
15. Garcia, L., & Finn, E. (2023). Peer interaction and feedback as predictors of student engagement in collaborative classrooms. Journal of Educational Research, 116(3), 295–309. [Google Scholar] [Crossref]
16. Kong, S. C. (2020). Partnership among schools, families, and communities to support student learning with technology. Education and Information Technologies, 25(2), 957–972. https://doi.org/10.1007/s10639-019-09986-9 [Google Scholar] [Crossref]
17. Kuş, M. (2025). A meta-analysis of the impact of technology-related factors on academic outcomes. PLOS ONE/PMC, Article PMC11894741. [Google Scholar] [Crossref]
18. ldossari, A. (2022). Collaborative learning strategies and their impact on students’ science achievement: A classroom-based analysis. International Journal of Science Education, 44(12), 1574–1590. [Google Scholar] [Crossref]
19. Lee, K. S., & Chen, Y. L. (2022). The impact of project- and problem-based learning on student retention and engagement in science education. Asia-Pacific Education Review, 23(3), 215–229. https://doi.org/10.1007/s12564-022-09789-1 [Google Scholar] [Crossref]
20. McLaren, S. J., & Howe, A. C. (2025). The role of laboratory activities in improving science achievement among secondary students. Journal of Science Teaching Practice, 19(2), 56–72. [Google Scholar] [Crossref]
21. Nguyen, T., & McFadden, J. (2024). Challenges in facilitating effective collaborative learning: Teacher roles and group processes. Teaching and Teacher Education, 133, 104257. [Google Scholar] [Crossref]
22. Palomares Ruiz, A., Cebrián, A., López-Parra, E., & García-Toledano, E. (2020). ICT integration into science education and its relationship to the digital gender gap. Sustainability, 12(13), 5286. https://doi.org/10.3390/su12135286 [Google Scholar] [Crossref]
23. Panganiban, R. D. (2024). Digital simulations in science education: Effects on conceptual understanding and academic performance. Journal of Educational Technology Integration, 12(1), 89–104. [Google Scholar] [Crossref]
24. Ruijia, Z. (2025). The impact of Information and Communication Technology on student learning: A review and meta-analysis. Frontiers in Psychology, 16, Article 1540169. https://doi.org/10.3389/fpsyg.2025.1540169. [Google Scholar] [Crossref]
25. Salvacion, E. M. (2025). Challenges in science learning: Addressing misconceptions and instructional gaps. International Journal of Science Education Research, 30(1), 12–28. [Google Scholar] [Crossref]
26. Siller, H. S. (2024). Analyzing the impact of collaborative learning approach on elementary mathematics: A literature synthesis. Eurasian Journal of Mathematics, Science and Technology Education, 20(3), 211–230. [Google Scholar] [Crossref]
27. Strobel, J., & van Barneveld, A. (2020). When is PBL more effective? A meta-synthesis of meta-analyses comparing PBL to conventional classrooms. Interdisciplinary Journal of Problem-Based Learning, 14(1), 1–20. https://doi.org/10.7771/1541-5015.1580 [Google Scholar] [Crossref]
28. Suciana, D. (2023). A meta-analysis study: The effect of problem-based learning integrated with STEM on learning outcomes. European Journal of Education Studies, 10(4), 1–15. [Google Scholar] [Crossref]
29. Thomas, J. W. (2020). A review of research on project-based learning. The Buck Institute for Education. https://www.pblworks.org/what-is-pbl [Google Scholar] [Crossref]
30. Torres, J. P., & Fernandez, L. M. (2024). Technology integration in science classrooms: Enhancing visualization and self-paced learning. Journal of Educational Technology and Innovation, 17(3), 134–150. https://doi.org/10.7890/jeti.2024.17304 [Google Scholar] [Crossref]
31. Turysbayeva, A. (2023). The impact of formative assessment techniques on students’ self-evaluations and achievement. International Journal of Educational Research [Google Scholar] [Crossref]
Metrics
Views & Downloads
Similar Articles
- Green Synthesis of Calcium Oxide Nanoparticles from Pigeon Eggshells for Cement Composites
- Needs Analysis: Development of an Interactive Digital Storybook in Teaching Mixtures and their Characteristics among Grade 6 Learners
- Thickness Dependent Structural, Optical, Electrical and Gas Sensing properties of ZnO thin film
- Forensic Chemistry Laboratory Works from Home: Challenges Encountered by Criminology Students During the Conduct of their Laboratory Activities at Home
- The Concept of Wellness Club and How it Differs from the Present Gym?