Survey on students’ perceptions and content analysis in developing Virtual Blended Learning Lab amongs teacher trainess of Malaysian Institute of Teacher Educations
Kajian persepsi dan keperluan kandungan untuk membangunkan Makmal Maya Teradun (MMT) dalam kalangan guru pelatih Institut Perguruan Malaysia (IPG)
DOI:
https://doi.org/10.37134/jpsmm.vol11.2.2.2021Keywords:
Virtual Blended Learning Laboratory, Blended Learning, Trainee Teacher Archievement, Science online learning, 21st century pedagogyAbstract
This research is carried out to analyse the needs of trainee teachers to develop an online learning medium for biology subject used by teacher trainees in Malaysia Institute of Teacher Education (MITE) majoring in Science Education. This study focused on teacher trainee belief and confidence towards biology online learning. Data collecting process involved male and female science trainee teachers in Malaysia Institute of Teacher Education. A total of 167 respondents. Respondents’ feedbacks were collected through Questionnaire surveys consists of 21 items Likert Scale. This quantitative study was analysed by using Statistical Package for the Social Sciences (SPSS) version 25 involving mean value, standard deviation, percentage and frequency. Construct of the survey consists of belief, confidence, learning approach and choose of media.
Result of this study showed that teacher trainees agreed online learning should not burdensome, well planned and systematically organized. Learning materials should be equipped including notes, videos and exercises. Meanwhile, analysis from construct of confidence, teacher trainee agreed that online learning is less time consume and easy to explore as self-regulated learning. Online learning content analysis based on students’ preference showed that three main aspects need to be used as useful guidelines such as user friendly, topical and interactive. The virtual blended learning laboratory also must promote thinking skills, active learning process, enhance interest, repeatable for difficult topic, unlimited time and schedule. Web based were found to be the suitable medium for blended learning. These findings will be useful in developing a focused, directed, interactive and eligable virtual bleanded learning laboratory.
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American Association of Colleges for Teacher Education. (2013). About edTPA: Overview. American Association of Colleges for Teacher Education. http://edtpa.aacte.org/about-edtpa.
Adeyemo, S.A., & Sreelekha,J. K. (2018). Effects of computer simulation and video based instructional strategies on students’ acquisition of skills in practical physics. Journal of Education in Developing Area, 26(2), 1–8.
Al-Azawei, A., Parslow, P., & Lundqvist, K. (2017). Investigating the effect of learning styles in a blended e-learning system: An extension of the technology acceptance model (TAM). Australasian Journal of Educational Technology, 33(2), 1–23. https://doi.org/10.14742/ajet.2741
Al-Balushi, S. M., Al-Musawi, A. S., Ambusaidi, A. K., & Al-Hajri, F. H. (2017). The Effectiveness of Interacting with Scientific Animations in Chemistry Using Mobile Devices on Grade 12 Students’ Spatial Ability and Scientific Reasoning Skills. Journal of Science Education and Technology, 26(1), 70–81. https://doi.org/10.1007/s10956-016-9652-2
Annetta, L. A., Cheng, M. T., & Holmes, S. (2010). Assessing twenty-first century skills through a teacher created video game for high school biology students. Research in Science and Technological Education, 28(2), 101–114.
Asirvatham, D., Kaur, A., & Abas, Z. W. (2005). Country Report : E-learning in Malaysia Malaysia. Asia E-Learning Network Conference, September. http://203.183.1.152/aen/content/conference/2005/file/Malaysia_Country Report v5.2.pdf
Ayub, A. F. (2017, Ogos). Anjakan 4 mentransformasi profesion keguruan menjadi profesion pilihan. Pendidik Pendidikan untuk semua. https://www.pendidik.com.my/2017/08/07/anjakan-4-mentransformasi-profesion-keguruan-menjadi-profesion-pilihan/
Belland, B. R. (2017). Instructional scaffolding in STEM education.: instructional scaffolding in STEM education. Springer Open.
Belland, B. R., Kim, C., & Hannafin, M. (2013). A framework for designing scaffolds that improve motivation and cognition. Educational Psychologist, 48(4), 243–270. http://doi.org/10.1080/00461520.2013.838920.
Brush, T., & Saye, J. (2008). The effects of multimedia-supported problem-based inquiry on student engagement, empathy, and assumptions about history. Interdisciplinary Journal of Problem-Based Learning, 2(1), 21-56.
Boelens, R., Voet, M., & De Wever, B. (2018). The design of blended learning in response to student diversity in higher education: Instructors’ views and use of differentiated instruction in blended learning. Computers and Education, 120, 197-212.
Carmona, C., Castillo, G., & Millán, E. (2007). Discovering student preferences in e-learning. CEUR Workshop Proceedings, 305, 33–42.
Chai Lee Goi & Poh Yen Ng. (2009). E-learning in Malaysia: Success factors in implementing e-learning program. International Journal of Teaching and Learning in Higher Education. 20(2), 237-246.
Che Ahmad, C. N., Yahaya, A., & Sani, S. S. (2020). Development of Practical Video Module (V-Lab) to enhance teaching and facilitation of form four biology. Jurnal Pendidikan Sains Dan Matematik Malaysia, 10(2), 1-7. https://doi.org/10.37134/jpsmm.vol10.2.1.2020
Cimer, S.O. (2018). What makes a change unsuccessful through the eyes of teachers? International Education Studies, 11(1), 81-88.
Chan, Y., & Sidhu, G. (2009). Integrating information and communication technology (ict) into university teaching and learning: a case study. Asian Journal of University Education, 5(1), 71–94.
Clark, R. C., & Mayer, R. E. (2016). E-learning and the Science of Instruction important: Fourth Edition. John Wiley & Sons, Inc., Hoboken.
Corbeil, M., Corbeil, J., & Khan, B. (2017). A framework for identifying and analyzing major issues in implementing big data and data analytics in e-learning: introduction to special issue on big data and data analytics. Educational Technology, 57(1), 3-9.
Dix, A. (2010). Human-computer interaction: A stable discipline, a nascent science, and the growth of the long tail. Interacting with Computers, 22(1), 13–27.
Dalgarno, B., A. G. Bishop, W. Adlong, & D. R. Bedgood, Jr. (2009). Effectiveness of a virtual laboratory as a preparatory resource for distance education chemistry students. Computers & Education, 53, 853-865.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35(8), 982–1003. https://doi.org/10.1287/mnsc.35.8.982
Hassan, M. A., Habiba, U., Majeed, F., & Shoaib, M. (2019). Adaptive gamification in e-learning based on students’ learning styles. Interactive Learning Environments, 0(0), 1–21. https://doi.org/10.1080/10494820.2019.1588745
Rasheed, R. A., Kamsin, A., & Abdullah, N. A. (2020). Challenges in the online component of blended learning: A systematic review. Computers and Education, 144(September 2019), 103701. https://doi.org/10.1016/j.compedu.2019.103701
El Bachari, E., Abdelwahed, E., & El Adnani, M. (2010). Design of an adaptive e-learning model based on learner’s personality. Ubiquitous Computing and Communication Journal, 5(3), 1–8.
Gill, S. E., Marcum-Dietrich, N., & Fraser, J. (2013). Developing a web application for the integration of real-world, scientific, problem-solving into the secondary classroom. Cases on educational technology implementation for facilitating learning. 146-160
Ghirardini, B. (2011). E-learning methodologies: A guide for designing and developing e-learning courses. Rome: Food and Agriculture Organization of the United Nations (FAO).
Hassan, M. A., Habiba, U., Majeed, F., & Shoaib, M. (2019). Adaptive gamification in e-learning based on students’ learning styles. Interactive Learning Environments, 0(0), 1–21. https://doi.org/10.1080/10494820.2019.1588745
Honey, P., & Mumford, A. (1992). The manual of learning styles. Maidenhead: Peter Honey
Hawkins, I., & Phelps, A. J. (2013). Virtual laboratory vs. traditional laboratory: Which is more effective for teaching electrochemistry? Chemistry Education Research and Practice, 14(4), 516–523.
Iqbal, M. J., & Ahmad, M. (2010). E-Learning: The case study of Allama Iqbal Open University. Turkish Online Journal of Distance Eduaction, 11(1), 84-97.
Jong, T. De, Sotiriou, S., & Gillet, D. (2014). Innovations in STEM education: The Go-Lab federation of online labs. Smart Learning environments. 1–16.
Johnstone, A. H. & Al-Shuaili, A. (2001). Learning in the laboratory; some thoughts from the literature. University Chemistry Education, 5 (2), 42-51.
Khan, B.H., & Joshi. V. (2006). " E-learning Who, What and How? Journal of Creative Communication, 1(1), 61-74.
Khan, B. H., & Ally, M. (2015) Theoretical perspectives and research, International handbook of e-learning Volume 1. Routledge.
Krejcie, R.V & Morgan, D.W. (1970). Determining sampel size for research activities. Journal of Educational and Psychological Measurement, (30) -607-610.
Koretsky, M., Kelly, C., & Gummer, E. (2011). Student perceptions of learning in the laboratory: Comparison of industrially situated virtual laboratories to capstone physical laboratories. Journal of Engineering Education, 100(3), 540-573.
Ma, J., & J. V. Nickerson. (2006). “Hands-on, simulated, and remote laboratories: A comparative literature review. ACM Computing Surveys. 38(3), 1-24.
Mayer, R. E., & Chandler, P. (2001). When learning is just a click away: Does simple user interaction foster deeper understanding of multimedia messages? . Journal of Educational Psychology, 93, 390-397.
Merchant, Z., Goetz, E. T., Cifuentes, L., Keeney-Kennicutt, W., & Davis, T. J. (2014). Effectiveness of virtual reality-based instruction on students’ learning outcomes in K-12 and higher education: A meta-analysis. Computers and Education, 70, 29-40.
Means, B., Murphy, R., Ginsburg, A., Goodwin, D., & Johns, L. (2009). Evaluation of evidence-based practices in online learning: a meta-analysis and review of online learning studies. In Report Program and Analytic Studies Division Office of Educational Technology. U.S. Department of Education. www.ed.gov/about/offices/list/opepd/ppss/reports.html.
Meredith, T. R. (2016). Game-based learning in professional development for practicing educators. A Review of the Literature. TechTrends, 60(5), 496–502. https://doi.org/10.1007/s11528-016-0107-7
Mohd Noor, L., Mohamad Nasri, N., & Jumal, J. (2020). Synchronous communication in Collaborative learning among first year students for Hydrocarbon course. Jurnal Pendidikan Sains Dan Matematik Malaysia, 10(2), 15-28. https://doi.org/10.37134/jpsmm.vol10.2.3.2020
Muhamad, M., Badioze Zaman, H., & Ahmad, A. (2011, November 9-11). Scenario-based learning approach for virtual biology laboratory (VLab-Bio). IVIC 2011 Second International Visual Informatics Conference. Selangor, Malaysia.
Nunnally, (1978), Psychometric Theory, 2nd edition. McGraw-Hill.
Patel, F. Afram, S. Chen and K. Ghose, (2011). MARSS: A full system simulator for multicore x86 CPUs. 2011 48th ACM/EDAC/IEEE Design Automation Conference, New York, 1050-1055.
Peat, M., & Fernandez, A. (2000). The role of information technology in biology education: An Australian perspective. Journal of Biological Education, 34(2), 69-73.
Polly, P., Marcus, N., & Maguire, D. (2014). Evaluation of an adaptive virtual laboratory environment using western blotting for diagnosis of disease. BMC Medical Education .14(222), 1-9
Kementerian Pelajaran Malaysia (2012). Pelan Pembangunan Pendidikan Malaysia 2013-2025 (2012). Laporan Awal-Ringkasan Eksekutif Pelan Pembangunan Pendidikan Malaysia, 2013-2025.
Rasheed, R. A., Kamsin, A., & Abdullah, N. A. (2020). Challenges in the online component of blended learning: A systematic review. Computers and Education, 144(September 2019), 103701. https://doi.org/10.1016/j.compedu.2019.103701
Raineri, D. (2001). Virtual laboratories enhance traditional undergraduate biology laboratories. Biochemistry and Molecular Biology Education, 29, 160-162.
Rissi, J. R. (2010). Efficacy of problem based learning in a High School Science Classroom. Michigan State University.
Rosemaliza, K., Hassan, A., Sakinah, N., & Nasaruddin, A. (2016). Student usage patterns of VLE-Frog. Journal of Personalized Learning, 2(21), 86–94.
Sanger, M. J., & Badger, S. M. (2001). Using computer-based visualization strategies to improve students’ understanding of molecular polarity and miscibility. Journal of Chemical Education, 78(10), 1412.
Shegog, R., Lazarus, M. M., Murray, N. G., Diamond, P. M., Sessions, N., & Zsigmond, E. (2012). Virtual transgenics: using a molecular biology simulation to impact student academic achievement and attitudes. Research in Science Education, 42(5), 875–890. https://doi.org/10.1007/s11165-011-9216-7
Saye, J. W., & Brush, T. (2002). Scaffolding critical reasoning about history and social issues. Multimedia-Supported Learning Environments. Educational Technology Research and Development, 50(3), 77-96.
Salter, S., & Gardner, C. (2016). Online or face-to-face microbiology laboratory sessions? First Year Higher Education Student Perspectives and Preferences. Creative Education, 7: 1869-1880.
Schwartz, D.L., & Bransford, J.D. (1998). A time for telling. Cognition and Instruction, 16(4), 475-522.
Sharples, M., Arnedillo Sánchez, I., Milrad, M., Vavoula, G. (2007). Mobile learning: small devices, big issues. In Technology enhanced learning: Principles and products, Kaleidoscope Legacy Book. Springer.
Shegog, R., Lazarus, M. M., Murray, N. G., Diamond, P. M., Sessions, N., & Zsigmond, E. (2012). Virtual transgenics: Using a molecular biology simulation to impact student academic achievement and attitudes. Research in Science Education, 42(5), 875–890.
Smaldino, S. E., Russell, J. D., Heinich, R., & Molenda, M. (2006). Instructional Technology and Media for Learning, 8th Edition. Columbia: Pearson Merrill Prentice Hall.
Sitzmann, T., & Weinhardt, J. M. (2018). Training engagement theory: A multilevel perspective on the effectiveness of work-related training. Journal of Management, 44(2), 732-756
Sungur, S., Tekkaya, C., & Geban, 0. (2001). The contribution of conceptual change texts accompanied by concept mapping to students' understanding of the circulatory system. School Science and Mathematics, 101(2), 91-101.
Sungur Gül, K. & Marulcu, İ. (2014). Investigation of in service and pre-service science teachers’ perspectives about engineering-design as an instructional method and legos as an instructional material. International Periodical for The Languages, Literature and History of Turkish or Turkic, 9(2), 761-786
Savin-Baden, M., & Kay, W. (2004). Challenging Research in Problem-based Learning Online. Open University Press.
Tham, K. O., & Tham, C. K. (2011). Blended learning – A focus study on Asia. International Journal of Computer Science Issues, 8(2), 136-142.
Tallent-Runnels, Thomas, Lan, Cooper, Ahern, Shaw dan Liu, Tallent-Runnels, M.K., Thomas, J.A., Lan, W.Y., Cooper, S., Ahern, T.C., Shaw, S.M., & Liu, X. (2006). Teaching courses online: A review of the research. Review of Educational Research, 76(1), 93-135.
Vygotsky, L.S. (1978). Mind in society: The development of higher psychological processes (M. Cole, V. John-Steiner, S. Scribner, & E. Souberman, Eds. & Trans.). Cambridge, MA: Harvard University Press.
Wood, D., Bruner, J. S., & Ross, G. (1976). The role of tutoring in problem solving. Journal of Child Psychology and Psychiatry, 17, 89–100. doi:10.1111/j.1469-7610.1976. tb00381.x
Wang, J., Duncan, D., Shi, Z., & Zhang, B. (2013). WEB-based GEne SeT AnaLysis Toolkit (WebGestalt): Nucleic Acids Research, Web Server Issue (41). W77-W83. https://academic.oup.com/nar/article/41/W1/W77/1105552?login=true
Wirkala, C., & Kuhn, D. (2011). Problem-based learning in K-12 education: Is it effective and how does it achieve its effects? American Educational Research Journal, 48(5), 1157-1186.
Yeung, S. (2010). Problem-based learning for promoting student learning in high school geography. Journal of Geography, 109(5), 190-200.
