ISSN: 2226-6348
Open access
Artificial intelligence (AI) technologies have attracted the curiosity of academics and practitioners in recent years. However, few researchers have investigated the advantages of applying AI into the education industry. Artificial intelligence (AI) creates new possibilities and opportunities in educational processes with the development of computing and information processing techniques which can provide important insights to administrators and decision makers at the institutional level. Artificial Intelligence in Education (AIEd) in this paper base on three paradigms, AI-directed- learner-as-recipient, AI supported- learner-as-collaborator, and AI-empowered- learner-as-leader addressing the educational and learning. The study proposes the role of AIEd, intelligent tutor, intelligent tutee and intelligent learning tool to improve student’s performance for logistics and supply chain course in Peninsula College Central Malaysia. As a result, the development trend of AIEd empower learners and tutors to personalize learning and teaching through application of AI systems to improve student’s practical skills, cognitive skills, critical thinking skill and analytics skills and achieve greater student’s performances. Future researcher could investigate the impact of robotics and automation application in the physical classroom to improve the quality of education, application of AI in other institutes and also investigate the impacts of the AI-supported learning designs on and the performances and experience of the students with different personal characteristics, such as varying levels of learning motivation or self-efficacy.
An den Broeck, E., Zarouali, B., & Poels, K. (2019). Chatbot advertising effectiveness: When does the message get through? Computers in Human Behavior, 98, 150–157.
Arraza-Mendiluze, E., Garay-Vitoria, N., Soraluze, I., Martín, J., Muguerza, J., & Ruiz-Vazquez, T. (2016). Using a real bare machine in a project-based learning environment for teaching computer structure: an analysis of the implementation following the action research model. J. Educ. Resour. Comput., 16(3), 117.
Baker, T., Smith, L., & Annisa. (2019).Edu-AI-education rebooted? Exploring the future of artificial intelligence in school and colleges
Chen, X., Xie, H., & Hwang, G. J. (2020). A multi-perspective study on artificial intelligence in education: Grants, conferences, journals, software tools, institutions, and researchers. Computers & Education: Artificial Intelligence, 1,
Chen, S. H., Jakeman, A. J., & Norton, J. P. (2008). Artificial Intelligence techniques: An introduction to their use for modelling environmental systems. Mathematics and Computers in Simulation, 78, 379–400
Cretchley, J., Rooney, D., & Gallois, C. (2010). Mapping a 40-year history with Leximancer: themes and concepts in the journal of cross-cultural psychology. J. Cross Cult. Psychol., 41(3),
Cretchley, J., Rooney, D., & Gallois, C. (2010). Mapping a 40-year history with Leximancer: themes and concepts in the journal of cross-cultural psychology. J. Cross Cult. Psychol., 41(3), 318e328.
Dahman, M. R., & Dag, H. (2019). Machine learning model to predict an adult learner ’s decision to continue ESOL course. Educ. Inf. Technol., 24(4), 2429e2452.
Dubey, R., Gunasekaran, A., Childe, S. J., Bryde, D. J., Giannakis, M., Foropon, C., … Hazen, B. T. (2020). Big data analytics and artificial intelligence pathway to operational performance under the effects of entrepreneurial orientation and environmental dynamism: A study of manufacturing organisations. International Journal of Production Economics, 226
Edirisingha, P., Nie, M., Pluciennik, M., & Young, R. (2009). Socialisation at a distance in a 3-D multi-user virtual environment. Br. J. Educ. Technol., 40,
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Boston, MA: Center for Curriculum Redesign.
Hwang, G. J., Xie, H., Wah, B. W., & Gasevic, D. (2020). Vision, challenges, roles and research issues of Artificial Intelligence in Education. Computers & Education: Artificial Intelligence, 1,
Indulska, M., Hovorka, D., & Recker, J. (2011). Quantitative approached to content analysis: identifying conceptual drift across publication outlets. Eur. J. Inf. Syst., 21(2), 49e69.35 Ma, Adesope, Nesbit, & Liu, 2014;
Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons, 61, 577–586
Krishna, P. K. V., Kumar, M., & Sri, A. P. S. G. (2018). Student information system and performance retrieval through dashboard. Int. J. Eng. Technol., 7,
Kaplan, A., & Haenlein, M. (2020). Rulers of the world, unite! The challenges and opportunities of artificial intelligent
Kearney, V., Chan, J. W., Valdes, G., Solberg, T. D., & Yom, S. S. (2018). The application of artificial intelligence in the IMRT planning process for head and neck cancer. Oral Oncology, 87, 111–116.
Lai, A.-F., Chen, C.-H., & Lee, G.-Y. (2019). An augmented reality-based learning approach to enhancing students’ science reading performances from the perspective of the cognitive load theory. Br. J. Educ. Technol.,50.
Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. London: Pearson Education.
Mayr, A., Weigelt, M., Masuch, M., Meiners, M., Hüttel, F., & Franke, J. (2018). Application Scenarios of Artificial Intelligence in Electric Drives Production. Procedia Manufacturing, 24, 40–47
Min, H. (2010). Artificial intelligence in supply chain management: Theory and applications. Int. J. Logist. Res. Appl., 13, 13–39
Nix, I., & Wyllie, A. (2011). Exploring design features to enhance computer-based assessment: learners’views on using a confidence-indicator tool and computer-based feedback. Br. J. Educ. Technol., 42(1), 101e112.
Pinkwart, N. (2016). Another 25 years of AIED? Challenges and opportunities for intelligent educational technologies of the future. International Journal of Artificial Intelligence in Education, 26(2), 771–783.
Rienties, B., & Toetenel, L. (2016). The impact of learning design on student behaviour, satisfaction and performance: a cross-institutional comparison across 151 modules. Comput. Hum. Behav., 60, 333e341
Russell, S., & Norvig, P. (2018). Artificial Intelligence: a Modern Approach (global edition). Harlow, United Kingdom: Pearson Education Limited.
Russell, S., & Norvig, P. (2018). Artificial Intelligence: a Modern Approach (global edition). Harlow, United Kingdom: Pearson Education Limited.
Saka, M. P., Dogan, E., & Aydogdu, I. (2013). Analysis of Swarm Intelligence-Based Algorithms for Constrained Optimization. In X.-. S. Yang, Z. Cui, R. Xiao, A. H. Gandomi, & M. Karamanoglu (Eds.), Swarm Intelligence and Bio-Inspired Computation, 2 pp. 25–48)
Sanders, D., & Gegov, A. (2013). AI tools for use in assembly automation and some examples of recent applications. Assem. Autom., 33, 184–19441.Sung, Y.-T., Liao, C.-N., Chang, T.-H., Chen, C.-L., & Chang, K.-E. (2016). The effect of online summary assessment and feedback system on the summary writing on 6th graders: the LSA-based technique. Comput. Educ., 95, 118.
Shakya, S., Chin, C. M., & Owusu, G. (2010). An AI-based system for pricing diverse products and services. Knowledge-Based Systems, 23, 357–362.
Tsang, Y. P., Choy, K. L., Wu, C. H., Ho, G. T. S., Lam, C. H. Y., & Koo, P. S. (2018). An internet of things (IoT)-based risk monitoring system for managing cold supply chain risks. Industrial Management & Data Systems., 118, 1432–1462.
Wang, W., & Siau, K. (2019). Artificial intelligence, machine learning, automation, robotics, future of work and future of humanity: a review and research agenda. J. Database Manag., 30(1), 6179.
Weismayer, C., & Pezenka, I. (2017). Identifying emerging research fields: a longitudinal latent semantic keyword analysis. Scientometrics, 113(3)
Wei, M. M., & Zhang, F. (2018). Recent research developments of strategic consumer behavior in operations management. Computers & Operations Research, 93, 166–176.
Yang, J. C., Chen, C. H., & Jeng, M. C. (2010). Integrating video-capture virtual reality technology into a physically interactive learning environment for English learning. Comput. Educ., 55(3),
Zhang, X., Chan, F. T. S., Adamatzky, A., Mahadevan, S., Yang, H., Zhang, Z., & Deng, Y. (2017). An intelligent physarum solver for supply chain network design under profit maximization and oligopolistic competition. International Journal of Production Research, 55, 244–263
Zawacki-Richter, O., & Naidu, S. (2016). Mapping research trends from 35 years of publications in distance education. Dist. Educ., 37(3)
In-Text Citation: (Kaur, 2021)
To Cite this Article: Kaur, K. (2021). Role of Artificial Intelligence in Education: Peninsula College Central Malaysia. International Journal of Academic Research in Progressive Education and Development, 10(2), 1006–1016.
Copyright: © 2021 The Author(s)
Published by HRMARS (www.hrmars.com)
This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at: http://creativecommons.org/licences/by/4.0/legalcode