Conceptual design of the new generation adaptive learning management system

  • Authors

    • Aleksandrs Gorbunovs
    • Zanis Timsans
    • Bruno Zuga
    • Viktors Zagorskis
    2018-05-16
    https://doi.org/10.14419/ijet.v7i2.28.12894
  • Adaptive information system, Feedback, Learning analytics, Personalized learning.

  • Abstract

    Taking into account that each new day an amount of daily processed data grows exponentially, it is obvious that knowledge society needs flexible, effective and high performing tools to retrieve, learn and apply necessary information. Learning management systems become more and more intelligent and adaptive. Learning analytics instruments give course developers a possibility to assess and analyze learners’ activities and behavior patterns within e-learning environment, allowing to propose them personalized self-paced learning path and types of learning objects. This paper discusses challenges in development of adaptive learning management system and outlines its prospective models and properties.

     

     

  • References

    1. [1] UNESCO, World report: Towards knowledge societies. Paris: UNESCO Publishing, (2005), pp.1-220, available online: http://unesdoc.unesco.org/images/0014/001418/141843e.pdf, last visit: 01.02.2018.

      [2] Sivakumar S, Venkataraman S & Gombiro C, “A user-intelligent adaptive learning model for learning management system using data mining and artificial intelligenceâ€, International Journal for Innovative Research in Science and Technology, Vol.1, No.10, (2015), pp.78–81.

      [3] Bates AW (Tony), Teaching in a digital age: guidelines for designing teaching and learning, Ontario: Contact North, (2016), pp.1-509, available online: https://teachonline.ca/sites/default/files/pdfs/teaching-in-a-digital-age_2016.pdf, last visit: 14.02.2018.

      [4] Sclater N, Peasgood A & Mullan J, Learning analytics in higher education: a review of UK and international practice. Full report, UK, Bristol: Jisc, (April 2016), pp.1-40, available online: https://www.jisc.ac.uk/sites/default/files/learning-analytics-in-he-v3.pdf, last visit: 15.02.2018.

      [5] Schumacher C & Ifenthaler D, “Features students really expect from learning analyticsâ€, Proceedings of the 13th International Conference on Cognition and Exploratory Learning in Digital Age, (2016), pp.67-76.

      [6] Worsley M & Blikstein P, “Towards the development of multimodal action based assessmentâ€, Proceedings of the 3rd International Conference on Learning Analytics and Knowledge (LAK '13), Leuven, Belgium, April 08 - 13, 2013, New York: ACM, (2013), pp.94-101.

      [7] Shacklock X, From bricks to clicks - the potential of data and analytics in higher education. UK: Higher Education Commission, (January 26, 2016), pp.1-76. available online: http://www.policyconnect.org.uk/hec/sites/site_hec/files/report/419/fieldreportdownload/frombrickstoclicks-hecreportforweb.pdf, last visit: 30.01.2018.

      [8] Brusilovsky P, Methods and Techniques of Adaptive Hypermedia. In Brusilovsky P, Kobsa A & Vassileva J (Eds.), Adaptive Hypertext and Hypermedia. Dordrecht: Kluwer Academic Publishers, (1998), pp.1-43.

      [9] Leone S, Characterisation of a personal learning environment as a lifelong learning tool. New York: Springer-Verlag, (2013), pp.1-88, doi: 10.1007/978-1-4614-6274-3.

      [10] Graf S, Liu T & Kinshuk C, “Analysis of learners’ navigational behaviour and their learning styles in an online courseâ€, Journal of Computer Assisted Learning, Vol.26, No.2, (2010), pp.116-131, doi:10.1111/j.1365-2729.2009.00336.

      [11] Danielson R, “Learning styles, media preferences, and adaptive educationâ€, Proceedings of Workshop “Adaptive Systems and User Modeling on the World Wide Web†at the 6th International Conference on User Modeling, Chia Laguna, Sardinia, Italy, (1997), pp.31-35.

      [12] Gilbert JE & Han CY, “Arthur: adapting instruction to accommodate learning styleâ€, Proceedings of World Conference of the WWW and Internet, Honolulu, HI, (1999), pp.433-438.

      [13] Brusilovsky P, “Adaptive Hypermediaâ€, User Modeling and User-Adapted Interaction, Vol.11, No.1-2, (2001), pp.87-110.

      [14] Oppermann R, Introduction. Adaptive user support, Hillsdale, New Jersey: Lawrence Erlbaum Associates, (1994), pp.1-13.

      [15] Vagale V & Niedrite L, “Learner model’s utilization in the e-learning environmentsâ€, Local Proceedings and Materials of Doctoral Consortium of the Tenth International Baltic Conference on Databases and Information Systems, Vilnius, (July 8-11, 2012), pp.162-174.

      [16] Ragusa C, Hoffman M & Leonard J, “Unwrapping GIFT: a primer on developing with the generalized intelligent framework for tutoringâ€, Proceedings of the workshops, 16th International Conference on Artificial Intelligence in Education, Memphis, USA, Vol.7, (July 9-13, 201uy3), pp.10-19.

      [17] Sottilare R, “Challenges in authoring, instructional management, and evaluation methods for adaptive instructional systemsâ€, Conference “Technology, Instruction, Cognition & Learning Special Interest Groupâ€, Symposium on Intelligent Tutoring Systems, Big Data-Learning Analytics, and Automated Humanlike Tutoring: Similarities and Differences, San Antonio, (April 28, 2017), pp.1-6.

      [18] Gallagher PS, “The total learning architecture (TLA): learning across applicationsâ€, Abstracts of Human Systems Conference “Achieving the Third Offset: Maximizing Human-Machine Symbiosisâ€, Springfield, VA, USA, (March 7-8, 2017), pp.1-24.

      [19] Anohina-Naumeca A, “Determining the set of concept map based tasks for computerized knowledge self-assessmentâ€, Procedia - Social and Behavioral Sciences, Vol. 69, (2012), pp.143-152.

      [20] Panjaburee P, Hwang GJ, Triampo W & Shih BY, “A multi-expert approach for developing testing and diagnostic systems based on the concept-effect modelâ€, Computers & Education, Vol.55, No.2, (September 2010), pp.527-540.

      [21] Graudina V & Grundspenkis J, “Concept map generation from OWL ontologiesâ€, Proceedings of the 3rd International Conference on Concept Mapping, OU Vali Press, Estonia, (2008), pp.173-180.

      [22] Dzelzkaleja L, “Real-time color codes for assessing learning processâ€, Proceedings of the International Conference “Meaning in Translation: Illusion of Precisionâ€, May 11-13, 2016, Riga, Procedia - Social and Behavioral Sciences, Vol.231, (2016), pp.263-269, doi: 10.1016/j.sbspro.2016.09.101.

      [23] Dzelzkaleja L, “Real time color codes in a classroomâ€, Proceedings of the 9th International Conference on Computer Supported Education (CSEDU-2017), Porto, (April 21-23, 2017), pp.111-117, doi: 10.5220/0006357201600165.

      [24] Dzelzkaleja L & Timsans Z, “Colour codes method digitalization in edX e-learning platformâ€, Proceedings of the 10th International Conference on Computer Supported Education (CSEDU-2018), 2018, in press.

      [25] Kapenieks A, et al., “Piloting eBig3: a tripple-screen e-learning approachâ€, Proceedings of the 6th International Conference on Computer Supported Education (CSEDU 2014), Barcelona, Vol.1, (1-3 April, 2014), pp.325-329, doi:10.5220/0004848603250329.

      [26] Kapenieks A, et al., “User behavior in multi-screen eLearningâ€, Proceedings of the Int. Conf. on Communication, Management and Information Technology (ICCMIT 2015), Procedia - Computer Science, Vol.65, (2015), pp.761-767, doi: 10.1016/j.procs.2015.09.021.

      [27] Imrie P, “Virtual personal assistants - a different approach to supporting the end userâ€, Proceedings of the 3rd International Workshop on Socio-Technical Perspective in IS development, Essen, (June 13, 2017), pp.106-109.

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  • How to Cite

    Gorbunovs, A., Timsans, Z., Zuga, B., & Zagorskis, V. (2018). Conceptual design of the new generation adaptive learning management system. International Journal of Engineering & Technology, 7(2.28), 129-133. https://doi.org/10.14419/ijet.v7i2.28.12894

    Received date: 2018-05-16

    Accepted date: 2018-05-16

    Published date: 2018-05-16