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. 2021;33(3):668-683.
doi: 10.1007/s12528-021-09282-2. Epub 2021 Jun 18.

Personalized training model for organizing blended and lifelong distance learning courses and its effectiveness in Higher Education

Gulmira Bekmanova  1 , Yerkin Ongarbayev  1 , Baubek Somzhurek  1 , Nurlan Mukatayev  1
Affiliations

Personalized training model for organizing blended and lifelong distance learning courses and its effectiveness in Higher Education

Gulmira Bekmanova et al. J Comput High Educ. 2021.

Abstract

The main goal of this research is to improve the personification of learning in higher education. The proposed flexible model for organizing blended and distance learning in higher education involves the creation of an individual learning path through testing students before the start of training. Based on the learning outcomes, the student is credited to the learning path. The training path consists of mandatory and additional modules for training; additional modules can be skipped after successfully passing the test, without studying these modules. The paper examines the composition of intelligent learning systems: student model, learning model and interface model. A student model is described, which contains the level of their knowledge, skills and abilities, the ability to learn, the ability to complete tasks (whether they know how to use the information received or not), personal characteristics (type, orientation) and other factors. The student's model is described by a mathematical formula. Thus, being described using logical rules, which have formed the basis for the software implementation of mixed and distance learning rules for lifelong learning courses. There is an interface model presented in the paper, and the results of the course of the proposed flexible model for the organization of mixed and distance learning "Digital Skills of a Modern Teacher in the Context of Distance Learning", as well as the face-to-face course "Digital Learning for Everyone" before the start of the pandemic which is close in its content to the course under study. Based on the results of the analysis, we introduced criteria for the effectiveness of the training course, proposed the weighting coefficients for evaluating the training course, carried out the assessment and drew conclusions.

Keywords: Artificial intelligence; Blended learning; Digital literacy; E-learning; Intelligent systems; Ontological model; Personalized training.

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Figures

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The model of the learner
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Distribution by level of digital skills of university teachers
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Percentage of certified and non-certified trainees based on course results in the context of 24 individual trajectories
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The structure of course
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Fragment of the course
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Course novelty comparison
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Meeting expectation comparison
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References

    1. Aljawarneh SA. Reviewing and exploring innovative ubiquitous learning tools in higher education. Journal of Computing in Higher Education. 2020;32(1):57–73. doi: 10.1007/s12528-019-09207-0. - DOI
    1. Alshargabi B, Aljawarneh SA. Innovations in educational technology and e-learning social networking. Recent Patents on Computer Science. 2015;8(2):100–105. doi: 10.2174/221327590802150807151618. - DOI
    1. Barlybayev A, Kaderkeyeva Z, Bekmanova G, Sharipbay A, Omarbekova A, Altynbek S. Intelligent system for evaluating the level of formation of professional competencies of students. IEEE Access. 2020 doi: 10.1109/ACCESS.2020.2979277. - DOI
    1. Bekmanova, G., & Ongarbayev, Y. (2020). Flexible model for organizing blended and distance learning. Lecture notes in computer science (Vol. 12250). Cham: Springer. 10.1007/978-3-030-58802-1_21
    1. Bekmanova, G., Omarbekova, A., Kaderkeyeva, Z., & Sharipbay, A. (2020). A model of intelligent massive open online course development. In Lecture notes in computer science (Vol. 12250). Springer. 10.1007/978-3-030-58802-1_20

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