The Integration of Augmented Reality and Virtual Laboratory based on the 5E Model and Vark Assessment: A Conceptual Framework

D. A. Purwaningtyas, H. Prabowo, T. A. Napitupulu, B. Purwandari

Abstract

Engineering education in aviation vocational education builds up skills and attitudes. Students must deal with the laboratory complexity, especially in radar training. Students must understand so much basic knowledge and enhance their skills. The high equipment cost and inflexibility of current learning make radar training less effective and cognitive. Augmented Reality (AR) integrated with laboratory activities is an opportunity to improve learning outcomes for vocational education training in an online learning platform. This study aims to find student learning problems in radar training and propose a framework for integrating virtual radar laboratories with Augmented Reality. This research used a descriptive analysis approach and a literature study. A survey at four Aviation Polytechnics in Indonesia results in cognitive load and troubleshooting skills as the main problem in radar training. The proposed framework concept for laboratory integration with Augmented Reality is added a learning style: the VARK framework and Augmented Reality design with a 5E-based model to make laboratory interaction design. Virtual laboratory integration with Augmented Reality with learning style proposed to enhance laboratory activity to achieve the troubleshooting capability on radar laboratory and make this learning more flexible and personalized.

Keywords

5E-based model; augmented reality; learning style; radar training; virtual laboratory

Full Text:

PDF

References

Ahmed, S., Mehrab Hossain, M., & Ikramul Hoque, M. (2017). A Brief Discussion on Augmented Reality and Virtual Reality in Construction Industry. Online) Journal of System and Management Sciences, 7(3), 1–33.

Akçayir, M., Akçayir, G., Pektaş, H. M., & Ocak, M. A. (2016). Augmented reality in science laboratories: The effects of augmented reality on university students' laboratory skills and attitudes toward science laboratories. Computers in Human Behavior, 57, 334–342.

Aljohani, N. R., Daud, A., Abbasi, R. A., Alowibdi, J. S., Basheri, M., & Aslam, M. A. (2019). An integrated framework for course adapted student learning analytics dashboard. Computers in Human Behavior, 92, 679–690.

Altmeyer, K., Kapp, S., Thees, M., Malone, S., Kuhn, J., & Brünken, R. (2020). The use of augmented reality to foster conceptual knowledge acquisition in STEM laboratory courses—Theoretical background and empirical results. British Journal of Educational Technology, 51(3), 611–628.

Antera, S. (2021). Professional Competence of Vocational Teachers: a Conceptual Review. Vocations and Learning, 14(3), 459–479.

Augustsson, D. (2021). Expansive learning in a change laboratory intervention for teachers. Journal of Educational Change, 22(4), 475–499.

Bandura, A., Freeman, W. H., & Lightsey, R. (1999). Self-Efficacy: The Exercise of Control. In Journal of Cognitive Psychotherapy (Vol. 13, Issue 2, pp. 158–166).

Borgen, K. B., Ropp, T. D., & Weldon, W. T. (2021). Assessment of Augmented Reality Technology's Impact on Speed of Learning and Task Performance in Aeronautical Engineering Technology Education. International Journal of Aerospace Psychology, 31(3), 219–229.

Bryan, S. J., Campbell, A., & Mangina, E. (2018). Scenic Spheres-An AR/VR Educational Game. 2018 IEEE Games, Entertainment, Media Conference, GEM 2018, 367–374.

Cekus, D., Gnatowska, R., Kwiatoń, P., & Šofer, M. (2019). Simulation research of a wind turbine using SolidWorks software. Journal of Physics: Conference Series, 1398(1), 0–6.

Chang, R. C., & Yu, Z. S. (2018). Using augmented reality technologies to enhance students' engagement and achievement in science laboratories. International Journal of Distance Education Technologies, 16(4), 54–72.

Chen, X., Gao, Z., & Chai, Y. (2017). The development of air traffic control surveillance radars in China. 2017 IEEE Radar Conference, RadarConf 2017, 1776–1784.

Cieza, E., & Lujan, D. (2018). Educational Mobile Application of Augmented Reality Based on Markers to Improve the Learning of Vowel Usage and Numbers for Children of a Kindergarten in Trujillo. Procedia Computer Science, 130, 352–358.

Creswell, J. W., & Plano Clark, V. L. (2018). Core Mixed Methods Design. Designing and Conducting Mixed Methods Research Approach, 77–84.

Daoruang, B., Sintanakul, K., & Mingkhwan, A. (2019). The study of learning achievement of learners classified vark learning style in blended learning. ACM International Conference Proceeding Series, 34–38.

Dayagdag, C. V., Catanghal, R. A., & Palaoag, T. D. (2019). Improving vocational training in the philippines using AR. ACM International Conference Proceeding Series, 253–257.

de Paiva Guimarães, M., Alves, B., Martins, V. F., dos Santos Baglie, L. S., Brega, J. R., & Dias, D. C. (2017). Embedding augmented reality applications into learning management systems. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10404(July), 585–594.

Demircioğlu, G., & Çağatay, G. (2014). The Effect of Laboratory Activities based on 5e Model of Constructivist Approach on 9th Grade Students' Understanding of Solution Chemistry. Procedia - Social and Behavioral Sciences, 116, 3120–3124.

Dempo, A., Kimura, T., & Shinohara, K. (2022). Perceptual and cognitive processes in augmented reality – comparison between binocular and monocular presentations. Attention, Perception, and Psychophysics, 84(2), 490–508.

Douglas, D. B., Wilke, C. A., Gibson, J. D., Boone, J. M., & Wintermark, M. (2017). Augmented reality: Advances in diagnostic imaging. Multimodal Technologies and Interaction, 1(4), 1–12.

Dutsinma, L. I. F., & Temdee, P. (2020). VARK Learning Style Classification Using Decision Tree with Physiological Signals. Wireless Personal Communications, 115(4), 2875–2896.

Elfeky, A. I. M., Masadeh, T. S. Y., & Elbyaly, M. Y. H. (2020). Advance organizers in flipped classroom via e-learning management system and the promotion of integrated science process skills. Thinking Skills and Creativity, 35(November 2019), 100622.

Fatahi, S., Moradi, H., & Farmad, E. (2015). Behavioral feature extraction to determine learning styles in e-learning environments. Proceedings of the International Conference on E-Learning 2015, E-LEARNING 2015 - Part of the Multi Conference on Computer Science and Information Systems 2015, 66–72.

Fowler, F. J. (2014). Survey Research Methods (5th edition). In Sage Publications, Inc.

Gangabissoon, T., Bekaroo, G., & Moedeen, W. (2020). Application of augmented reality in aviation: Improving engagement of cabin crew during emergency procedures training. In ACM International Conference Proceeding Series (p. 8).

Hernández-Chávez, M., Cortés-Caballero, J. M., Pérez-Martínez, Á. A., Hernández-Quintanar, L. F., Roa-Tort, K., Rivera-Fernández, J. D., & Fabila-Bustos, D. A. (2021). Development of virtual reality automotive lab for training in engineering students. Sustainability (Switzerland), 13(17).

Idrizi, E., Filiposka, S., & Trajkovik, V. (2018). VARK Learning Styles and Online Education: Case Study. September, 1–6.

International Air Transport Association. (2009). Need for air traffic services. Transport, January, 56.

Karagozlu, D. (2018). Determination of the impact of augmented reality application on the success and problem-solving skills of students. Quality and Quantity, 52(5), 2393–2402.

Ministry of Transportation (Kemenhub). (2021). Peraturan Menteri Perhubungan 87 TAHUN 2021. Ministry of Transportation.

Khalaj, M. H. M. A., & Shirazi, S. M. H. A. (2020). Is Skill a Kind of Disposition to Action-Guiding Knowledge? Erkenntnis, 0123456789.

Khan, M. A., & Salah, K. (2020). Cloud adoption for e-learning: Survey and future challenges. Education and Information Technologies, 25(2), 1417–1438.

Kharoufah, H., Murray, J., Baxter, G., & Wild, G. (2018). A review of human factors causations in commercial air transport accidents and incidents: From to 2000–2016. Progress in Aerospace Sciences, 99(November 2017), 1–13.

Khongpit, V., Sintanakul, K., & Nomphonkrang, T. (2018). The VARK Learning Style of the University Student in Computer Course. International Journal of Learning and Teaching, January 2018, 102–106.

KNKT. (2016). Data Investigasi Kecelakaan Penerbangan. Media Release KNKT, 2016(November), 1–17.

Koorsse, M., Cilliers, C. B., & Calitz, A. P. (2010). Motivation and learning preferences of information technology learners in South African secondary schools. ACM International Conference Proceeding Series, 144–152.

Lajis, A., Md Nasir, H., & Aziz, N. A. (2018). Proposed assessment framework based on bloom taxonomy cognitive competency: Introduction to programming. ACM International Conference Proceeding Series, 97–101.

Lepmets, M., Mernik, M., & de Brito, M. A. (2021). Quality of information and communication technology introduction. Software Quality Journal, 29(1), 195–196.

Lwande, C., Muchemi, L., & Oboko, R. (2019). Behaviour Prediction in a Learning Management System. 2019 IST-Africa Week Conference, IST-Africa 2019, May.

Mendonca, F. A. C., Keller, J., & Dillman, B. (2019). Competency-Based Education: A Framework for a More Efficient and Safer Aviation Industry. ISASI Publishing, 1–15.

Montalvo, P. (2018). Design and Evaluation of a 3D Map View using Augmented Reality in Flight Training Sim- ulators.

Muhayimana, T., Kwizera, L., & Nyirahabimana, M. R. (2022). Using Bloom's taxonomy to evaluate the cognitive levels of Primary Leaving English Exam questions in Rwandan schools. Curriculum Perspectives, 0123456789.

Onime, C., & Abiona, O. (2016). 3D Mobile Augmented Reality Interface for Laboratory Experiments. International Journal of Communications, Network and System Sciences, 09(04), 67–76.

Pantho, O., & Tiantong, M. (2015). Conceptual Framework of a Synthesized Adaptive e-Learning and e-Mentoring System Using VARK Learning Styles with Data Mining Methodology. International Journal of Computer Theory and Engineering, 7(4), 316–319.

Prakash, R., & Litoriya, R. (2022). Pedagogical Transformation of Bloom Taxonomy's LOTs into HOTs: An Investigation in Context with IT Education. Wireless Personal Communications, 122(1), 725–736.

Radosavljevic, S., Radosavljevic, V., & Grgurovic, B. (2020). The potential of implementing augmented reality into vocational higher education through mobile learning. Interactive Learning Environments, 28(4), 404–418.

Raviv, A., Cohen, S., & Aflalo, E. (2019). How Should Students Learn in the School Science Laboratory? The Benefits of Cooperative Learning. Research in Science Education, 49(2), 331–345.

Rios, H., González, E., Rodriguez, C., Siller, H. R., & Contero, M. (2013). A mobile solution to enhance training and execution of troubleshooting techniques of the engine air bleed system on boeing 737. Procedia Computer Science, 25, 161–170.

Rutledge, P., & Neal, M. (2012). Positive Engagement Evaluation Model for Interactive and Mobile Technologies. Proceedings of the International Conference on E-Learning, e-Business, Enterprise Information Systems, and e-Government, February, 1.

Safi, M., Chung, J., & Pradhan, P. (2019). Review of augmented reality in aerospace industry. Aircraft Engineering and Aerospace Technology, 91(9), 1187–1194.

Sasakura, M., & Yamasaki, S. (2007). A framework for adaptive e-learning systems in higher education with information visualization. Proceedings of the International Conference on Information Visualisation, 819–824.

Shi, Z., Pan, Q., & Xu, M. (2020). LSTM-Cubic A*-based auxiliary decision support system in air traffic management. Neurocomputing, 391, 167–176.

Singh, G., Mantri, A., Sharma, O., Dutta, R., & Kaur, R. (2019). Evaluating the impact of the augmented reality learning environment on electronics laboratory skills of engineering students. Computer Applications in Engineering Education, 27(6), 1361–1375.

Södervik, I., Katajavuori, N., Kapp, K., Laurén, P., Aejmelaeus, M., & Sivén, M. (2021). Fostering performance in hands-on laboratory work with the use of mobile augmented reality (Ar) glasses. Education Sciences, 11(12).

Teli, C., S, C., Daulatabad, V., & Kate, N. (2021). Assessment of learning style preferences in undergraduate medical students using VARK scale study. National Journal of Physiology, Pharmacy and Pharmacology, 0, 1.

Thees, M., Kapp, S., Strzys, M. P., Beil, F., Lukowicz, P., & Kuhn, J. (2020). Effects of augmented reality on learning and cognitive load in university physics laboratory courses. Computers in Human Behavior, 108, 106316.

Torres, T. (2003). A Cognitive Model To Analyse Physics and Chemistry Problem- Solving Skills : Mental Representations Implied in Solving Actions. 730–746.

Waheed, H., Hassan, S. U., Aljohani, N. R., Hardman, J., Alelyani, S., & Nawaz, R. (2020). Predicting academic performance of students from VLE big data using deep learning models. Computers in Human Behavior, 104.

Wiegman, D. (2003). Wiegmann, Shappell (2003) - A Human Error Approach to Aviation Accident Analysis. 161.

Wilson, L. O. (2016). Anderson and Krathwohl Bloom's Taxonomy Revised Understandifile:///C:/Users/Situmorang/Desktop/Calon/Sepsis/BAB 1/Kerangka Pemikiran/BLOOM LENGKAP.pdfng the New Version of Bloom's Taxonomy. The Second Principle, 1–8.

Wolf, T. (2010). Virtual Laboratory Environment. IEEE Transactions on Education, 53(2), 216–222.

Refbacks

  • There are currently no refbacks.