The Frontier Areas’ Student Acceptance of Physics Fun-based Mobile Application: Incorporating the Process-Oriented Guided-Inquiry Learning (POGIL) Strategy

Year 2024, Volume: 11 Issue: 6, 152 - 171, 01.11.2024

Irfan Yusuf , Punaji Setyosari Dedi Kuswandi Saida Ulfa

https://doi.org/10.17275/per.24.84.11.6

Abstract

The acceptability of technology is an essential factor to consider, particularly in frontier areas that encounter challenges related to availability and limited educational resources. This study aims to evaluate the acceptance of physics learning tools in a virtual laboratory (V-Lab) platform, utilizing the POGIL strategy, referred to as the Physics Fun-based mobile application. Mobile learning refers to the learning process carried out through mobile devices such as smartphones. The implementation took place at a senior high school located in West Papua Province, one of Indonesia's frontier areas, with 136 students participating. The Technology Acceptance Model (TAM) and Theory of Reasoned Action (TRA) were employed in this quantitative study. Structural Equation Modeling (SEM) was implemented for data analysis. The findings indicated that Attitude (ATT) and Behavioral Intention (BI) were significantly influenced by Perceived Ease of Use (PEU) and Subjective Norm (SN), respectively, while Perceived Usefulness (PU) did not have a direct effect on ATT. As a result, to enhance the acceptance of technology, teachers and technology developers should prioritize enhancing ease of use and reinforcing social factors. This should be done with a particular emphasis on the social benefits and simple accessibility of technology in the learning process, particularly in frontier areas.

Keywords

POGIL, Physics Fun, TAM, TRA, V-Lab

Supporting Institution

Lembaga Pengelola Dana Pendidikan (LPDP) Indonesia

Thanks

The author expresses his gratitude to the Lembaga Pengelola Dana Pendidikan (LPDP) Indonesia, Decree Number: SKPB541/LPDP/LPDP.3/2023, for the funding assistance provided during the main author's doctoral studies at the Learning Technology Study Program, Universitas Negeri Malang.

References

• Abidin, D., Mayasari, N., Muamar, A., Satria, E., & Aziz, F. (2023). Development of android-based interactive mobile learning to learn 2D animation practice. Scientia, 12(1), 138–142. Retrieved from http://infor.seaninstitute.org/index.php
• Ajzen, I. & Fishbein, M. (1980). Understanding Attitudes and Predicting Social Behaviour. Englewood Cliffs, N.J.: Prentice-Hall.
• Alatas, F., & Fachrunisa, Z. (2018). An effective of POGIL with virtual laboratory in improving science process skills and attitudes: Simple harmonic motion concept. Edusains, 10(2), 327–334. doi:10.15408/es.v10i2.10239
• Alfalah, A. A. (2023). Factors influencing students’ adoption and use of mobile learning management systems (m-LMSs): A Quantitative Study of Saudi Arabia. International Journal of Information Management Data Insights, 3(1), 100143. doi:10.1016/j.jjimei.2022.100143
• Andoh, C. B. (2018). Predicting students’ intention to adopt mobile learning. Journal of Research in Innovative Teaching & Learning, 11(2), 178–191. doi:10.1108/jrit-03-2017-0004
• Ardıç, M. A. (2021). Opinions and attitudes of secondary school mathematics teachers towards technology. Participatory Educational Research, 8(3), 136–155. doi:10.17275/per.21.58.8.3
• Baki, R., Birgoren, B., & Aktepe, A. (2018). A meta analysis of factors affecting perceived usefulness and perceived ease of use in the adoption of e-learning systems. Turkish Online Journal of Distance Education, 19(4), 4–42. doi:10.17718/tojde.471649
• Bancoro, J. C. (2024). Exploring the influence of perceived usefulness and perceived ease of use on technology engagement of business administration instructors. International Journal of Asian Business and Management, 3(2), 149–167. doi:10.55927/ijabm.v3i2.8714
• Caratiquit, K., & Caratiquit, L. J. (2022). Influence of technical support on technology acceptance model to examine the project PAIR e-learning system in distance learning modality. Participatory Educational Research, 9(5), 468–485. doi:10.17275/per.22.124.9.5
• Cempaka, G., Mujasam, M., Widyaningsih, S. W., & Yusuf, I. (2018). Efektivitas pemanfaatan laboratorium IPA dalam pembelajaran fisika di SMA YAPIS Manokwari [Effectiveness of using the science laboratory in physics learning at YAPIS Manokwari high school]. Prosiding Seminar Nasional UNCOK [UNCOK National Seminar Proceedings], 3(1), 166–176. Retrieved from http://www.journal.uncp.ac.id/index.php/proceding/article/view/785
• Criollo, S., Arias, A. G., Alcázar, Á. J., & Mora, S. L. (2021). Mobile learning technologies for education: Benefits and pending issues. Applied Sciences, 11(9), 1–17. doi:10.3390/app11094111
• Crompton, H., Burke, D., Gregory, K. H., & Gräbe, C. (2016). The use of mobile learning in science: A systematic review. Journal of Science Education and Technology, 25(2), 149–160. doi:10.1007/s10956-015-9597-x
• Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly: Management Information Systems, 13(3), 319–339. doi:10.2307/249008
• DeMatteo, M. P. (2019). Combining POGIL and a flipped classroom methodology in organic chemistry. In ACS Symposium Series: Vol. 1336. Active Learning in Organic Chemistry: Implementation and Analysis (pp. 13–217). American Chemical Society. doi:doi:10.1021/bk-2019-1336.ch013
• Diwakar, S., Kolil, V. K., Francis, S. P., & Achuthan, K. (2023). Intrinsic and extrinsic motivation among students for laboratory courses - assessing the impact of virtual laboratories. Computers and Education, 198(February), 104758. doi:10.1016/j.compedu.2023.104758
• Dong, Z., Chiu, M. M., Zhou, S., & Zhang, Z. (2023). The effect of mobile learning on school-aged students’ science achievement: A meta-analysis. Education and Information Technologies, (0123456789). doi:10.1007/s10639-023-12240-3
• Donnelly, D., O’Reilly, J., & McGarr, O. (2013). Enhancing the student experiment experience: Visible scientific inquiry through a virtual chemistry laboratory. Research in Science Education, 43(4), 1571–1592. doi:10.1007/s11165-012-9322-1
• Durkaya, F. (2023). Virtual laboratory use in science education with digitalization. Hungarian Educational Research Journal, 13(2), 189–211. doi:10.1556/063.2022.00141
• Elmoazen, R., Saqr, M., Khalil, M., & Wasson, B. (2023). Learning analytics in virtual laboratories: A systematic literature review of empirical research. Smart Learning Environments, 10(23), 1–20. doi:10.1186/s40561-023-00244-y
• Götz, O., Liehr-Gobbers, K., & Krafft, M. (2010). Evaluation of structural equation models using the partial least squares (PLS) approach BT-handbook of partial least squares: Concepts, methods, and applications (V. Esposito Vinzi, W. W. Chin, J. Henseler, & H. Wang, eds.). Berlin, Heidelberg: Springer Berlin Heidelberg. doi:10.1007/978-3-540-32827-8_30
• Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial least squares structural equation modeling (PLS-SEM) using R. doi:10.1007/978-3-030-80519-7_5
• Hamid, A., Setyosari, P., Kuswandi, D., & Ulfa, S. (2019). The implementation of mobile seamless learning strategy in mastering students’ concepts for elementary school. Journal for the Education of Gifted Young Scientists, 7(4), 967–982. doi:10.17478/jegys.622416
• Handayani, V., Budiono, F. L., Rosyada, D., Amriza, R. N. S., Zulkifli, & Masruroh, S. U. (2020). Gamified learning platform analysis for designing a gamification-based UI / UX of e-learning applications: A systematic literature review. 2020 8th International Conference on Cyber and IT Service Management (CITSM), 1–5. doi:10.1109/CITSM50537.2020.9268791
• Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In R. R. Sinkovics & P. N. Ghauri (Eds.), New Challenges to International Marketing (pp. 277–319). Emerald Group Publishing Limited. doi:10.1108/S1474-7979(2009)0000020014
• Husnaini, S. J., & Chen, S. (2019). Effects of guided inquiry virtual and physical laboratories on conceptual understanding, inquiry performance, scientific inquiry self-efficacy, and enjoyment. Physical Review Physics Education Research, 15(010119), 1–16. doi:10.1103/PhysRevPhysEducRes.15.010119
• Iksan, Z., & Saufian, S. (2017). Mobile learning: Innovation in teaching and learning using telegram. IJPTE : International Journal of Pedagogy and Teacher Education, 1(1). doi:10.20961/ijpte.v1i1.5120
• Jurayev, T. N. (2023). The use of mobile learning applications in higher education institutes. Advances in Mobile Learning Educational Research, 3(1), 610–620. doi:10.25082/amler.2023.01.010
• Karoror, I., Widyaningsih, S. W., Sebayang, S. R. B., & Yusuf, I. (2020). Upaya meningkatkan hasil belajar peserta didik melalui penerapan model kooperatif tipe the power of two berbasis alat peraga di kelas VII SMP YAPIS Manokwari [Efforts to improve student learning outcomes through the implementation of the power of two type cooperative model based on teaching aids in class VII YAPIS Manokwari middle school]. Silampari Jurnal Pendidikan Ilmu Fisika [Silampari Journal of Physical Science Education], 2(1), 66–76. doi:10.31540/sjpif.v2i1.937
• Kolil, V. K., & Achuthan, K. (2024). Virtual labs in chemistry education: A novel approach for increasing student’s laboratory educational consciousness and skills. Education and Information Technologies. doi:10.1007/s10639-024-12858-x
• Kurniawan, R. B., Mujasam, M., Yusuf, I., & Widyaningsih, S. W. (2019). Development of physics learning media based on lectora inspire software on the elasticity and hooke’s law material in senior high school. Journal of Physics: Conference Series, 1157(3). doi:10.1088/1742-6596/1157/3/032022
• Maritasari, D. B., Setyosari, P., Kuswandi, D., & Praherdhiono, H. (2022). The effect of project based learning assisted by mobile learning applications and learning motivation on the competence and performance of teachers. Al-Ishlah: Jurnal Pendidikan [Al-Ishlah: Journal of Education], 14(3), 3303–3316. doi:10.35445/alishlah.v14i3.1116
• Maulidah, S. S., & Prima, E. C. (2018). Using physics education technology as virtual laboratory in learning waves and sounds. Journal of Science Learning, 1(3), 116–121. doi:10.17509/jsl.v1i3.11797
• Miya, T. K., & Govender, I. (2022). UX/UI design of online learning platforms and their impact on learning: A review. International Journal of Research in Business and Social Science (2147- 4478), 11(10), 316–327. doi:10.20525/ijrbs.v11i10.2236
• Mulyanto, A., Sumarsono, S., Niyartama, T. F., & Syaka, A. K. (2020). Penerapan technology acceptance model (TAM) dalam pengujian model penerimaan aplikasi MasjidLink [Application of the technology acceptance model (TAM) in testing the MosqueLink application acceptance model]. Semesta Teknika, 23(1), 27–38. doi:10.18196/st.231253
• Nasrullah, M., Degeng, I. N. S., Murtadho, N., Ulfa, S., & Nugrawiyati, J. (2024). Mobile application development using semantic mapping in learning vocabulary arabic for spesific purposes (ASP). Ijaz Arabi: Journal of Arabic Learning, 7(1), 221–235. doi:10.18860/ijazarabi.v7i1.24847
• Navarro, G. V., Dávila, A. C., Lengua, M. A. C., & Arenas, L. A. (2023). Design of a mobile app for the learning of algorithms for university students. Advances in Mobile Learning Educational Research. doi:10.25082/amler.2023.01.021
• Park, S. Y. (2009). An analysis of the technology acceptance model in understanding university students’ behavioral intention to use e-learning. Journal of Educational Technology & Society, 12(3), 150–162. Retrieved from http://www.jstor.org/stable/jeductechsoci.12.3.150
• Poo, M. C. P., Lau, Y. Y., & Chen, Q. (2023). Are virtual laboratories and remote laboratories enhancing the quality of sustainability education? Education Sciences, 13(11), 1–13. doi:10.3390/educsci13111110
• Purkayastha, S., Surapaneni, A. K., Maity, P., Rajapuri, A. S., & Gichoya, J. W. (2019). Critical components of formative assessment in process-oriented guided inquiry learning for online labs. Electronic Journal of E-Learning, 17(2), 79–92. doi:10.34190/JEL.17.2.02
• Rivas, M. R., Martínez, S. S., Ferreiro, A. A., Fuentes, O. G., & Cerdeiriña, A. Z. (2023). The rural school from child ’ s point of view : A participatory research through photovoice. Participatory Educational Research, 10(6), 208–228.
• Santos, M. L., & Prudente, M. (2022). Effectiveness of virtual laboratories in science education: A meta-analysis. International Journal of Information and Education Technology, 12(2), 150–156. doi:10.18178/ijiet.2022.12.2.1598
• Setyosari, P., Wibawati, D. O. A., Fitriyah, C. Z., & Wardani, R. P. (2023). Learning loss: How does technology facilitate learner learning? AIP Conference Proceedings, 2679(1), 70016. doi:10.1063/5.0112882
• Shea, P., & Bidjerano, T. (2010). Learning presence: Towards a theory of self-efficacy, self-regulation, and the development of a communities of inquiry in online and blended learning environments. Computers and Education, 55(4), 1721–1731. doi:10.1016/j.compedu.2010.07.017
• Suartama, I. K., Setyosari, P., Sulthoni, & Ulfa, S. (2019). Development of an instructional design model for mobile blended learning in higher education. International Journal of Emerging Technologies in Learning, 14(16), 4–22. doi:10.3991/ijet.v14i16.10633
• Sunarto, M. J. D., Hariadi, B., Sagirani, T., Amelia, T., & Lemantara, J. (2020). MoLearn, a web-and android-based learning application as an alternative for teaching-learning process in high schools. International Journal of Instruction, 13(1), 53–70. doi:10.29333/iji.2020.1314a
• Tang, Y., Liu, H., Zhou, K., Zhang, T., & Sun, C. (2020). Implementation of the POGIL-based flipped classroom learning: An approach to promote learning in emergency medicine. Research Square, 1–9. doi:10.21203/rs.3.rs-29069/v1
• Turan, Z., Kucuk, S., & Karabey, S. C. (2022). Investigating pre-service teachers’ behavioral intentions to use web 2.0 gamification tools. Participatory Educational Research, 9(4), 172–189. doi:10.17275/per.22.85.9.4
• Ulfa, S., Surahman, E., Fatawi, I., & Tsukasa, H. (2024). Task-technology fit analysis: measuring the factors that influence behavioural intention to use the online summary-with automated feedback in a MOOCs platform. Electronic Journal of E-Learning, 22(1), 63–77. doi:10.34190/ejel.22.1.3094
• Ulfa, S., Surahman, E., & Octaviani, H. I. (2020). Mobile seamless language learning framework to improving students’ speaking skills for junior high students during pandemic covid-19: A case study in Indonesian Context. Advances in Social Science, Education and Humanities Research, 508(ICITE), 497–500. doi:10.2991/assehr.k.201214.284
• Venkatesh, V., Thong, J. Y. L., & Xu, X. (2016). Unified theory of acceptance and use of technology: A synthesis and the road ahead. Journal of the Association for Information Systems, 17(5), 328–376. doi:10.17705/1jais.00428
• Vlachy, L. G., Buhtz, K., & König, A. (2018). Social influence in technology adoption: Taking stock and moving forward. Management Review Quarterly, 68(1), 37–76. doi:10.1007/s11301-017-0133-3
• Voicu, M. C., & Muntean, M. (2023). Factors that influence mobile learning among university students in romania. Electronics (Switzerland), 12(4), 1–18. doi:10.3390/electronics12040938
• Yosiana, Y., Djuandi, D., & Hasanah, A. (2021). Mobile learning and its effectiveness in mathematics. Journal of Physics: Conference Series, 1806(012081), 1–6. doi:10.1088/1742-6596/1806/1/012081
• Youssef, M. M., Mousa, S. A., Baloola, M. O., & Fouda, B. M. (2020). The impact of mobile augmented reality design implementation on user engagement. ICACDS. doi:10.1007/978-981-15-6634-9_10
• Yusuf, I., Setyosari, P., Kuswandi, D., & Ulfa, S. (2024). Development of integrated physics learning tools in virtual laboratory platform: Its implementation through the POGIL strategy in Indonesian frontier areas. TEM Journal, 13(3), 2568–2580. doi:10.18421/TEM133-82
• Yusuf, I., & Widyaningsih, S. W. (2020). Implementing e-learning-based virtual laboratory media to students’ metacognitive skills. International Journal of Emerging Technologies in Learning (IJET), 15(05), 63–74. doi:10.3991/ijet.v15i05.12029