Abstract
Learner Management Systems (LMSs) are widely deployed across the industry as they provide a cost-saving approach that can support flexible learning opportunities. Despite their benefits, LMSs fail to cater for individual learning behavior and needs and support individualised prediction and progression. Learning Analytics (LAs) support these gaps by correlating existing learner data to provide meaningful predictive and prescriptive analysis. The industry and research community have already recognised the necessity of LAs to support modern learning needs. But a little effort has been directed towards the integration of LA into LMSs. This paper presents a novel automated Intelligence Learner Management System (iLMS) that integrates learner management and learning analytics into a single platform. The presented iLMS considers Machine Learning techniques to support learning analytics including descriptive, predictive and perspective analytics.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Bezovski, Z., Poorani, S.: The evolution of e-learning and new trends. In: Information and Knowledge Management, vol. 6, no. 3, pp. 50–57. IISTE (2016)
LMS Market by Component (Solution and Services), Delivery Mode (Distance Learning, Instructor-Led Training and Blended Learning), Deployment Type, User Type (Academic and Corporate), and Region - Global Forecast to 2025. https://www.marketsandmarkets.com/PressReleases/learning-management-systems.asp
Kumar, K., Vivekanandan, V.: Advancing learning through smart learning analytics: a review of case studies. Asian Assoc. Open Univ. J. (2018)
Herodotou, C., Rienties, B., Boroowa, A., Zdrahal, Z., Hlosta, M.: Large-scale implementation of predictive learning analytics in higher education: the teachers’ role and perspective. Educ. Tech. Res. Dev. 67(5), 1273–1306 (2019)
Viberg, O., Hatakka, M., Bälter, O., Mavroudi, A.: The current landscape of learning analytics in higher education. Comput. Hum. Behav. 89, 98–110 (2018)
Papamitsiou, Z., Economides, A.: Learning analytics and educational data mining in practice: a systematic literature review of empirical evidence. Educ. Technol. Soc. 17(4), 49–64 (2014)
Rosé, C.P., McLaughlin, E.A., Liu, R., Koedinger, K.R.: Explanatory learner models: why machine learning (alone) is not the answer. Br. J. Edu. Technol. 50(6), 2943–2958 (2019)
Carmen, C., Davis, B., Wagner, E.D.: The Evolution of LMS: From Management to Learning. The eLearning Guild, Santa Rosa (2009)
Siemens, G., Long, P.: Penetrating the fog: analytics in learning and education. EDUCAUSE Rev. 46(5), 30 (2011)
Andriotis, N.: Will Artificial Intelligence Bring Real Smarts To Elearning?. https://www.efrontlearning.com/blog/2017/06/artificial-intelligence-elearning.html. Accessed 17 May 2020
Islam, S., Mahmud, H.: Integration of learning analytics into learner management system using machine learning. In: 2020 the 2nd International Conference on Modern Educational Technology ICMET. ACM (2020)
Islam, S., Mahmud, H.: An intelligence learner management system using learning analytics and machine learning. In: 12th International Conference on Education Technology and Computers, ICETC 2020. ACM (2020)
Wong, B.T.M.: Learning analytics in higher education: an analysis of case studies. Asian Assoc. Open Univ. J. 12, 21–40 (2017)
Avella, J.T., Kebritchi, M., Nunn, S.G., Kanai, T.: Learning analytics methods, benefits, and challenges in higher education: a systematic literature review. Online Learn. 20, 13–29 (2016)
Chen, L., Chen, P., Lin, Z.: Artificial intelligence in education: a review. IEEE Access 8, 75264–75278 (2020)
Busch, J., Hanna, P., O’Neill, I., McGowan, A., Collins M.: Can machine learning on learner analytics produce a predictive model on student performance?. In: Innovative and Creative Education and Technology International Conference (ICETIC) (2017)
Akçapınar, G., Altun, A., Aşkar, P.: Using learning analytics to develop early warning system for at-risk students. Int. J. Educ. Technol. High. Educ. 16, 1–20 (2019)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 IFIP International Federation for Information Processing
About this paper
Cite this paper
Islam, S., Mouratidis, H., Mahmud, H. (2021). An Automated Tool to Support an Intelligence Learner Management System Using Learning Analytics and Machine Learning. In: Maglogiannis, I., Macintyre, J., Iliadis, L. (eds) Artificial Intelligence Applications and Innovations. AIAI 2021. IFIP Advances in Information and Communication Technology, vol 627. Springer, Cham. https://doi.org/10.1007/978-3-030-79150-6_39
Download citation
DOI: https://doi.org/10.1007/978-3-030-79150-6_39
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-79149-0
Online ISBN: 978-3-030-79150-6
eBook Packages: Computer ScienceComputer Science (R0)
