Information and Communication Technology Literacy and Science Academic Performance of Grade 10 Students
DOI:
https://doi.org/10.5281/zenodo.21459569Keywords:
ICT literacy, science academic performance, Grade 10 students, digital competence, technology acceptance, predictive analysisAbstract
This study determined the Information and Communication Technology (ICT) literacy and science academic performance of Grade 10 students and identified the variables that predicted achievement in science. A quantitative descriptive-predictive design was employed among 300 Grade 10 students selected through simple random sampling from eight medium to very large public secondary schools in Northern Nueva Vizcaya. Data were obtained through a researcher-made ICT literacy questionnaire patterned after Fekete (2020), validated by five experts, translated into Filipino, and pilot-tested with 100 students, yielding a Cronbach’s alpha of .921. Science final grades were retrieved from school records. Frequency, percentage, mean, standard deviation, independent-samples t-test, analysis of variance with Tukey post hoc test, Pearson correlation, and multiple linear regression were used. Most respondents were female, used one gadget—primarily a smartphone—accessed the internet through Wi-Fi, reported stable connectivity, had used the internet for learning for four to five years, and spent less than two hours daily on a computer. Overall ICT literacy was very satisfactory (M = 2.95, SD = 0.87), with willingness for skills development rated highest and information creation lowest. Science performance was also very satisfactory (M = 86.60, SD = 5.65). ICT literacy was positively related to science performance (r = .44, p < .01), with information creation showing the strongest component-level association (r = .57, p < .01). The regression model explained 38% of the variance in science achievement, F(14, 285) = 12.63, p < .001. Sex, acceptance of ICT devices, ICT use for science learning, and ability to create information were significant predictors. The findings indicate that meaningful, productive, and subject-specific use of technology is more influential than access alone, supporting targeted instruction in digital content creation, science-focused technology use, and equitable connectivity.
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Aesaert, K., & van Braak, J. (2015). Gender and socioeconomic related differences in performance-based ICT competences. Computers & Education, 84, 8–25. https://doi.org/10.1016/j.compedu.2014.12.017
Asio, J. M. R., Gadia, E., Abarintos, E., Paguio, D., & Balce, M. (2021). Internet connection and learning device availability of college students: Basis for institutionalizing flexible learning in the new normal. Studies in Humanities and Education, 2, 56–69. https://doi.org/10.48185/she.v2i1.224
Battelle for Kids. (2019). Framework for 21st century learning. https://static.battelleforkids.org/documents/p21/P21_Framework_Brief.pdf
Bayanova, A. R., Kuznetsov, V. V., Merculova, L. V., Gorbunova, L. N., Pervozvanskaya, O. A., Shalamova, O. O., & Vorobyova, C. I. (2019). Student performance interrelation with gadget use at lessons. Journal of Environmental Treatment Techniques, 7(3), 432–437.
Boruah, N. (2022). Impact of ICT in education. International Journal of Health Sciences, 6(S2). https://doi.org/10.53730/ijhs.v6nS2.5397
Cabellos, B., Siddiq, F., & Scherer, R. (2024). The moderating role of school facilitating conditions and attitudes towards ICT on teachers’ ICT use and emphasis on developing students’ digital skills. Computers in Human Behavior, 150, Article 107994. https://doi.org/10.1016/j.chb.2023.107994
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
Department of Education. (2018). DepEd computerization program orientation handbook.
Department of Education. (2023). MATATAG curriculum. https://www.deped.gov.ph/matatag-curriculum/
Dulaney, C. L., Davlin-Pater, C., & Cagle, J. A. B. (2023). Academic performance: Prompting strategic selection of resource use. College Teaching, 73(1), 46–54. https://doi.org/10.1080/87567555.2023.2226383
Fekete, I. (2020). Information and communications technology literacy of Hungarian English majors: A validation study. Learning, Knowledge and Innovation, 4(1), 31–39.
Fu, J. S. (2013). ICT in education: A critical literature review and its implications. International Journal of Education and Development Using Information and Communication Technology, 9(1), 112–125.
Guo, Q., Qiao, C., & Ibrahim, B. (2022). The mechanism of influence between ICT and students’ science literacy: A hierarchical and structural equation modelling study. Journal of Science Education and Technology, 31, 272–288. https://doi.org/10.1007/s10956-021-09954-9
Hero, J. L. (2022). Information and communications technology literacy and self-efficacy of junior high school students: Basis for an ICT enhancement program. International Journal of Multidisciplinary: Applied Business and Education Research, 3(3), 393–403.
Keya, N. K., & Uddin, M. K. (2020). Perception of secondary school students towards ICT education. Perception, 47, 21–32.
Lei, H., Xiong, Y., Chiu, M. M., Zhang, J., & Cai, Z. (2021). The relationship between ICT literacy and academic achievement among students: A meta-analysis. Children and Youth Services Review, 127, Article 106123. https://doi.org/10.1016/j.childyouth.2021.106123
Limniou, M. (2021). The effect of digital device usage on student academic performance: A case study. Education Sciences, 11(3), Article 121. https://doi.org/10.3390/educsci11030121
Organisation for Economic Co-operation and Development. (2022). Skills for the digital transition: Assessing recent trends using big data. OECD Publishing. https://doi.org/10.1787/38c36777-en
Organisation for Economic Co-operation and Development. (2024). PISA 2022 results: Factsheets—Philippines. OECD Publishing. https://doi.org/10.1787/dfe0bf9c-en
Rafiq, S., Iqbal, S., & Afzal, A. (2024). The impact of digital tools and online learning platforms on higher education learning outcomes. Al-Mahdi Research Journal, 5(4), 359–369.
Rahiem, M. D. H. (2020). Technological barriers and challenges in the use of ICT during the COVID-19 emergency remote learning. Universal Journal of Educational Research, 8(11B), 6124–6133. https://doi.org/10.13189/ujer.2020.082248
Scherer, R., Siddiq, F., & Tondeur, J. (2019). The Technology Acceptance Model: A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education. Computers & Education, 128, 13–35. https://doi.org/10.1016/j.compedu.2018.09.009
Selwyn, N. (2004). Reconsidering political and popular understandings of the digital divide. New Media & Society, 6(3), 341–362.
van Deursen, A. J. A. M., & van Dijk, J. A. G. M. (2014). The digital divide shifts to differences in usage. New Media & Society, 16(3), 507–526.
Youssef, A., Dahmani, M., & Ragni, L. (2022). ICT use, digital skills and students’ academic performance: Exploring the digital divide. Information, 13(3), Article 129. https://doi.org/10.3390/info13030129
Zizikova, S., Nikolaev, P., & Levchenko, A. (2023). Digital transformation in education. E3S Web of Conferences, 381, Article 02036. https://doi.org/10.1051/e3sconf/202338102036
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