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An Instrument to Measure Perceived Cognitive, Affective, and Psychomotor (CAP) Learning for Online Laboratory in Technology and Engineering Courses

Sim Tze Ying, Ng Kok Mun, A’zraa Afhzan Ab Rahim, Mitra Mohd Addi and Mashanum Osman

Pertanika Journal of Tropical Agricultural Science, Volume 31, Issue 4, July 2023

DOI: https://doi.org/10.47836/pjst.31.4.28

Keywords: Affective, bloom taxonomy, cognitive, instrument validation, learning domains, learning measurement, online laboratory, psychomotor

Published on: 3 July 2023

The effectiveness of student learning in an online laboratory environment requires appropriate measurements from the cognitive, affective, and psychomotor (CAP) domains. However, current self-reporting perceived CAP instruments are general and focused on non-technical fields, hence unsuitable for comprehensively measuring and evaluating technology and engineering (TE) online laboratory courses. This work aims to develop and validate a new instrument to measure perceived CAP learning domains in technology and engineering (TE) online laboratory courses. An initial instrument with 22 questions to assess CAP attributes was developed based on adaptation and expert consultation. About 1414 questionnaires were deployed and obtained a response rate of 25%, which meets the requirement of a confidence level of 90% with a 5% error. Principal Component Analysis (PCA) and Exploratory Factor Analysis (EFA) were used to further reduce the items to 13. Items reliability was verified using Cronbach Alpha. The finalized items consist of 5 cognitive, 4 affective, and 4 psychomotor items. For cognitive, the five items relate to students’ perception of self-directed learning, reproducing study guides for future students, organizing their tasks and solving problems, relating lab works with fundamental concepts and theories, and completing all tasks. The four affective items are associated with students’ perception of active involvement in learning, communication of findings, collaboration with team members, and awareness of safety and requirements. The four psychomotor items are linked to students’ perceived attainment in performing the experiment, visualizing the procedure, demonstrating technical skills, and operating the equipment. The tool is verified to self-measure CAP attainment for online laboratories.

  • Anderson, L., Krathwohl, D. R., Airasian, P. W., Cruikshank, K. A., Richard, M., Pintrich, P. R., Raths, J. D., & Wittrock, M. C. (2001). A taxonomy for Learning, Teaching and Assessing: A Revision of Bloom’s Taxonomy of Educational Objectives. Longman.

  • Bloom, B. S., Engelhart, M. D., Furst, E. J., Hill, W. H., & Krathwohl, D. R (1956). Taxonomy of Educational Objectives; The Classification of Education Goals - Handbook 1 Cognitive Domain. Longmans.

  • Carpenter-Horning, A. K. (2018). The Effects of Perceived Learning on Open-Sourced Classrooms within the Community Colleges in the South-Eastern Region of the United States. Liberty University.

  • Chan, C., & Fok, W. (2009). Evaluating learning experiences in virtual laboratory training through student perceptions: A case study in electrical and electronic engineering at the University of Hong Kong. Journal of the Higher Education Academy, 4(2), 70-75. https://doi.org/10.11120/ened.2009.04020070

  • Chowdury, H., Alam, F., & Mustary, I. (2019). Development of an innovative technique for teaching and learning of laboratory experiments for engineering courses. Energy Procedia, 160, 806-811. https://doi.org/10.1016/j.egypro.2019.02.154

  • Davies, C. (2008). Laboratory and Practical Work in the Engineering Curriculum: Learning and Teaching in Laboratories. The Higher Educational Academy Engineering.

  • Elif, I. (2018). An overview of problem solving studies in physics education. Journal of Education and Learning, 7(4), 191-200. https://doi.org/10.5539/jel.v7n4p191

  • Gamage, K. A. A., Wijesuriya, D. I., Ekanayake, S. Y., Rennie, A. E. W., Lambert, C. G., & Gunawardhana, N. (2020). Online delivery of teaching and laboratory practices: Continuity of university programmes during COVID-19 pandemic. Education. Sciences, 10(10), Article 291. https://doi.org/10.3390/educsci10100291

  • Jolliffe, I. (2014). Principal component analysis. In N. Balakrishnan, T. Colton, B. Everitt, W. Piegorsch, F. Ruggeri, L. Jozef & Teugels (Eds.), Wiley StatsRef: Statistics Reference Online (pp. 2-29). John Wiley & Sons. https://doi.org/10.1002/0470013192.bsa501

  • Kapilan, N., Vidhya, P., & Gao, X. Z. (2021). Virtual laboratory: A boon to the mechanical engineering education during COVID-19 pandemic. Higher Education for the Future, 8(1), 31-46. https://doi.org/10.1177/2347631120970757

  • Kawasaki, H., Yamasaki, S., Masuoka, Y., Iwasa, M., Fukita, S., & Matsuyama, R. (2021) Remote teaching due to COVID-19: An exploration of its effectiveness and issues. International Journal of Environmental Research and Public Health, 18(5), Article 2672. https://doi.org/10.3390/ijerph18052672

  • Kearney, P. (1994). Affective learning scale. In R. B. Rubin, P. Palmgreen, & H. E. Sypher (Eds.), Communication Research Measures: A Sourcebook (pp. 81-85 & pp. 238-241). The Guilford Press.

  • Krathwohl, D. R., Bloom, B. S., & Masia, B. B. (1964). Taxonomy of Educational Objectives: The Classification of Educational Goals - Handbook II: Affective Domain. David McKay.

  • Laerd Statistics. (2018). Principal component analysis (PCA) using SPSS statistics. Laerd Statistics. https://statistics.laerd.com/spss-tutorials/principal-components-analysis-pca-using-spss-statistics.php/Accessed

  • Lewis, L. D. (2014). The Pedagogical Benefits and Pitfalls of Virtual Tools for Teaching and Learning Laboratory Practices in the Biological Sciences. https://www.advance-he.ac.uk/knowledge-hub/pedagogical-benefits-and-pitfalls-virtual-tools-teaching-and-learning-laboratory

  • MacLeod, J., Yang, H. H., Zhu, S., & Li, Y. (2018). Understanding students’ preferences toward the smart classroom learning environment: Development and validation of an instrument. Computers & Education, 122, 80-91. https://doi.org/10.1016/j.compedu.2018.03.015

  • Martin, F., Stamper, B., & Flowers, C. (2020). Examining student perception of readiness for online learning: Importance and confidence. Online Learning Journal, 24(2), 38-58.

  • Murphy, M. P. (2020). COVID-19 and emergency e-learning: Consequences of the securitisation of higher education for post-pandemic pedagogy. Contemporary Security Policy, 41(3), 492–505. https://doi.org/10.1080/13523260.2020.1761749

  • Nature News. (2020, April 22). Corononavirus: The first three months as it happened. Nature News. https://www.nature.com/articles/d41586-020-00154-w

  • Rachmawati, E., Mufidah, L., Sulistiyani, T., & Ab-Latif, Z. (2019). Examining the students’ cognitive, affective and psychomotor abilities in the bakery industry. Journal of Technology and Operations Management, 14(2), 1-9. https://doi.org/10.32890/jtom2019.14.2.1

  • Rovai, A. P., Wighting, M. J., Baker, J. D., & Grooms, L. D. (2009). Development of an instrument to measure perceived cognitive, affective, and psychomotor learning in traditional and virtual classroom higher education settings. Internet and Higher Education, 12(1), 7-13. https://doi.org/10.1016/j.iheduc.2008.10.002

  • Simpson, E. J. (1974). The classification of educational objectives in the psychomotor domain. In R. J. Kibler, D. J. CegalaL, L. Barker & D. T. Miles (Eds.), Objectives for Instruction and Evaluation (pp. 107-112). Allyn and Bacon.

  • Tan, P. L. (2021, June 1). Online learning: Leave no student behind. The Star. https://www.thestar.com.my/opinion/letters/2021/06/01/online-learning-leave-no-student-behind

  • Triyanti, Murtono, & Sri, U. (2021). Problem-based technology and science development to improve science learning outcomes in elementary schools. ANP Journal of Social Science and Humanities, 2(2), 151-156. https://doi.org/10.53797/anp.jssh.v2i2.21.2021

  • Waltner, E. M., Rieß, W., & Mischo, C. (2019). Development and validation of an instrument for measuring student sustainability competencies. Sustainability, 11(6), Article 1717. https://doi.org/10.3390/su11061717

  • Zhai, G., Wang, Y., & Liu, L. (2012). Design of electrical online laboratory and e-learning. IERI Procedia, 2, 325-330. https://doi.org/10.1016/j.ieri.2012.06.096

ISSN 1511-3701

e-ISSN 2231-8542

Article ID

JST-3886-2022

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