Investigating the Academic Experience of Science Education Students with Virtual Laboratory Classes: A Convergent Parallel Approach
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Abstract
Virtual laboratories are operative platforms utilised by science education students during the pandemic. The study was designed to determine the virtual laboratory experiences of science education students in terms of usability, quality of service, and sense of reality with an exploration of the contributing factors that affect their experiences. The outcomes were supported by John Dewey’s Social Constructivist Learning Theory, Dave Kolb’s Experiential Learning, and Edgar Dale’s Cone of Experience. This study used a convergent parallel design to understand the subject thoroughly. In the quantitative approach, 100 respondents met the inclusion through a purposive sampling technique. In the qualitative approach, six participants are purposely selected by the snowball sampling technique. Quantitative data in the study were analysed through statistical analysis of Frequency, Mean, Independent T-test, and ANOVA. Moreover, qualitative data were analysed using Thematic Analysis performed through Colaizzi’s Method. Quantitative and qualitative data were integrated using Joint Display Analysis. In quantitative key findings, virtual laboratories for science education students are helpful. The results also revealed that there is no significant difference in the level of assessment of science education students on their academic experience with virtual laboratories when grouped according to gender and year level. On the other hand, qualitative results revealed that science education students have eight contributing factors affecting their assessment of their academic experience with virtual laboratories. The results of this mixed method research design can be a basis for future researchers to undertake either pure qualitative or quantitative research design.
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References
Akaygun, S., & Adadan, E. (2019). Revisiting the understanding of redox reactions through critiquing animations in variance. In M, Schultz, S. Schmid, & G. A. Lawrie (Eds.), Research and Practice in Chemistry Education (pp. 7–29). Springer. https://doi.org/10.1007/978-981-13-6998-8_2
Almohammed, O. A., Alotaibi, L. H., & Ibn Malik, S. A. (2021). Student and educator perspectives on Virtual Institutional Introductory Pharmacy Practice Experience (IPPE). BMC Medical Education, 21, Article 257. https://doi.org/10.1186/s12909-021-02698-5
Amornrit, P., Suwansumrit, C., & Thubthimthong, T. (2022). Usage a blended learning model to promote the career of Thai massage for health for adult students. Suranaree Journal of Social Science, 16(2), 1–10. https://doi.org/10.55766/nsfc3577
Bauer, J. M., Hampton, K. N., Fernandez, L., & Robertson, C. (2020). Overcoming Michigan’s homework gap: The role of broadband internet connectivity for student success and career outlooks. Quello Center Working Paper No. 06-20. SSRN. https://doi.org/10.2139/ssrn.3714752
Beazer, K., & Cummins, K. (2020). Effective marketing strategies for a medical laboratory science program. American Society for Clinical Laboratory Science. https://doi.org/10.29074/ascls.119.002154
Cherry C. Cereno, A., & G. Borlio, J. (2021). Surmounting digital divide in the time of pandemic by teacher education science major students. International Journal of Research Publications, 85(1). https://doi.org/10.47119/ijrp100851920212293
Cyril, A. V. (2015). Time Management and academic achievement of Higher Secondary students. i-Manager’s Journal on School Educational Technology, 10(3), 38–43. https://doi.org/10.26634/jsch.10.3.3129
Dawadi, S., Shrestha, S., & Giri, R. A. (2021). Mixed-methods research: A discussion on its types, challenges, and criticisms. Journal of Practical Studies in Education, 2(2), 25–36. https://doi.org/10.46809/jpse.v2i2.20
Dhawan, S. (2020). Online learning: A panacea in the time of Covid-19 crisis. Journal of Educational Technology Systems, 49(1), 5–22. https://doi.org/10.1177/0047239520934018
Duffy, T. M., & Jonassen, D. H. (2013). Constructivism and the technology of instruction. Routledge. https://doi.org/10.4324/9780203461976
Duping, A. M., Decano, R. S., & Borlio, J. G. (2021). Adaptive capacity on flexible learning in the new normal: The case of Davao Del Norte State college. International Journal of Research and Innovation in Social Science, 05(12), 85–99. https://doi.org/10.47772/ijriss.2021.51208
Efstathiou, C., Hovardas, T., Xenofontos, N. A., Zacharia, Z. C., deJong, T., Anjewierden, A., & van Riesen, S. A. (2018). Providing guidance in virtual lab experimentation: The case of an experiment design tool. Educational Technology Research and Development, 66(3), 767–791. https://doi.org/10.1007/s11423-018-9576-z
Ekka, S., & Singh, P. (2022). Predicting HR professionals’ adoption of HR analytics: An extension of Utaut Model. Organizacija, 55(1), 77–93. https://doi.org/10.2478/orga-2022-0006
Fàbregues, S., Molina-Azorin, J. F., & Fetters, M. D. (2021). Virtual special issue on “quality in mixed methods research.” Journal of Mixed Methods Research, 15(2), 146–151. https://doi.org/10.1177/15586898211001974
Guetterman, T. C., Fàbregues, S., & Sakakibara, R. (2021). Visuals in joint displays to represent integration in mixed methods research: A methodological review. Methods in Psychology, 5, 100080. https://doi.org/10.1016/j.metip.2021.100080
Healey, M., & Jenkins, A. (2007). Linking teaching and research in national systems. International Policies and Practices for Academic Enquiry. Paper presented at the International Colloquium Held At Marwell Conference Centre, Winchester, UK, 19–21 April.
Hill, J. R., & Hannafin, M. J. (2001). Teaching and learning in digital environments: The resurgence of resource-based learning. Educational Technology Research and Development, 49(3), 37–52. https://doi.org/10.1007/bf02504914
Kolb, D. A., Boyatzis, R. E., & Mainemelis, C. (2014). Experiential learning theory: Previous research and new directions. In R. J. Sternberg, & L. F., Zhang (Eds.), Perspectives on thinking, learning, and cognitive styles (pp. 227–248). Routledge. https://doi.org/10.4324/9781410605986-9
LeBaron, J. F., & Bragg, C. A. (1994). Practicing what we preach: Creating distance education models to prepare teachers for the twenty?first century. American Journal of Distance Education, 8(1), 5–19. https://doi.org/10.1080/08923649409526842
Lindgren, R., Tscholl, M., Wang, S., & Johnson, E. (2016). Enhancing learning and engagement through embodied interaction within a mixed reality simulation. Computers & Education, 95, 174–187. https://doi.org/10.1016/j.compedu.2016.01.001
Mann, K., & MacLeod, A. (2015). Constructivism: Learning theories and approaches to research. In J. Cleland, & S. J. Durning (Eds.), Researching Medical Education (pp. 49–66). Wiley. https://doi.org/10.1002/9781118838983.ch6
McElhaney, K. W., Chang, H.-Y., Chiu, J. L., & Linn, M. C. (2015). Evidence for effective uses of dynamic visualisations in science curriculum materials. Studies in Science Education, 51(1), 49–85. https://doi.org/10.1080/03057267.2014.984506
Milosievski, M., Zemon, D., Stojkovska, J., & Ppovski, K. (2020, 19 May). Learning online: Problems and solutions. UNICEF global. Retrieved 10 December 2022, from https://www.unicef.org/northmacedonia/stories/learning-online-problems-and-solutions
Morgan, H. (2020). Best practices for implementing remote learning during a pandemic. The Clearing House: A Journal of Educational Strategies, Issues and Ideas, 93(3), 135– 141. https://doi.org/10.1080/00098655.2020.1751480
Morse, J. (2021). Editorial farewell. Qualitative Health Research, 31(14), 2559–2561. https://doi.org/10.1177/10497323211055466
Muller, D., & Ferreira, J. M. (2005). Online labs and the MARVEL experience. International Journal of Online Engineering. 1(1), 1–5.
Nurpratiwi, S., Amaliyah, A., & Romli, N. A. (2022). Learning by project: Develop students’ self-reflection and collaboration skills using team-based project. Hayula: Indonesian Journal of Multidisciplinary Islamic Studies, 6(2), 267–284. https://doi.org/10.21009/hayula.006.02.07
Papaconstantinou, M., Kilkenny, D., Garside, C., Ju, W., Najafi, H., & Harrison, L. (2020). Virtual lab integration in undergraduate courses: Insights from course design and implementation. Canadian Journal of Learning and Technology, 46(3), 1–18. https://doi.org/10.21432/cjlt27853
Saniie, J., Oruklu, E., Hanley, R., Anand, V., & Anjali, T. (2015). Transforming computer engineering laboratory courses for distance learning and collaboration. International Journal of Engineering Education, 31(1), 106–120.
Savin-Baden, M., & MacKenzie, A. (2022). Finding and creating spaces of innovation. Postdigital Science and Education, 4(2), 540–556. https://doi.org/10.1007/s42438-021-00266-0
Smith, C. L., Coleman, S. K., & Ferrier, C. (2019).Employer and work-based student perceptions of virtual laboratory teaching and assessment resources. Work Based Learning e-Journal International, 8(1), 53–70.
Somosot, I. S. (2018). ). Instructional practices of beginning TLE teachers and student satisfaction among secondary schools of Sto. Tomas, Davao del Norte. Asian Journal of Multidisciplinary Studies, 1(3), 6–13.
Somosot, I. S. (2022). We can make it: A probabilistic analysis on the satisfaction in flexible learning. Journal of Research, Policy & Practice of Teachers & Teacher Education, 12(2), 1–11. https://doi.org/10.37134/jrpptte.vol12.2.1.2022
Somosot, I. S., Duran, J. R. V., & Rodriguez, B. T. (2022). Success under pressure: A probabilistic analysis of the predictors of the Licensure Examination for Teachers (LET) results. International Journal of Scientific Research in Multidisciplinary Studies, 8(4), 15–20.
Soni, N. D., & Bhola, J. (2022). A comparative study on the use of physical and e-labs: A case study at University of Delhi. SAMRIDDHI: A Journal of Physical Sciences, Engineering and Technology, 14(01), 10–16. https://doi.org/10.18090/samriddhi.v14i01.2
Szopi?ski, T., & Bachnik, K. (2022). Student evaluation of online learning during the COVID-19 pandemic. Technological Forecasting and Social Change, 174, 121203. https://doi.org/10.1016/j.techfore.2021.121203
Tatli, Z., & Ayas, A. (2013). Effect of a virtual chemistry laboratory on students’ achievement. Journal of Educational Technology & Society, 16(1), 159–170.
Thoms, L.-J., & Girwidz, R. (2017). Virtual and remote experiments for radiometric and photometric measurements. European Journal of Physics, 38(5), 055301. https://doi.org/10.1088/1361-6404/aa754f
Torun, F., Dargut Güler, T., & Özer ?anal, S. (2021). Learning theories, motivation, and distance education. In H. Ucar, & A. T. Kumtepe (Eds.), Motivation, volition, and engagement in online distance learning (pp. 210–229). IGI Global. https://doi.org/10.4018/978-1-7998-7681-6.ch010
Usman, H., Emmanuel, O., Usman, Z. N., & Abubakar, H. (2021). Enhancing secondary school students’ retention in geography through physical and virtual laboratories in North Central Nigeria. International Journal of Educational Research, 4(02), 76–90.
Vasiliadou, R. (2020). Virtual laboratories during coronavirus (Covid?19) pandemic. Biochemistry and Molecular Biology Education, 48(5), 482–483. https://doi.org/10.1002/bmb.21407
Verawati, N. N., Handriani, L. S., & Prahani, B. K. (2022). The experimental experience of motion kinematics in biology class using PHET virtual simulation and its impact on learning outcomes. International Journal of Essential Competencies in Education, 1(1), 11–17. https://doi.org/10.36312/ijece.v1i1.729