Please use this identifier to cite or link to this item: http://rps.chtei-knteu.cv.ua:8585/jspui/handle/123456789/2417
Title: Collaboration Based Simulation Model for Predicting Students’ Performance in Blended Learning
Other Titles: Моделювання в прогнозуванні успішності студентів в змішаному навчанні
Authors: Hu, Zhengbing
Su, Jun
Koroliuk, Yurii
Keywords: collaborative learning
interactive learning environments
simulations
teaching strategies
predicting of academic performance
Issue Date: Jul-2021
Publisher: Hu Z. COLLABORATION BASED SIMULATION MODEL FOR PREDICTING STUDENTS’ PERFORMANCE IN BLENDED LEARNING = МОДЕЛЮВАННЯ В ПРОГНОЗУВАННІ УСПІШНОСТІ СТУДЕНТІВ В ЗМІШАНОМУ НАВЧАННІ / Z. Hu, J. Su, Y. Koroliuk // ICCSEEA 2020 ; AISC. – №1247. – P. 1–15. – DOI: https://doi.org/10.1007/978-3-030-55506-1_58.
Citation: https://doi.org/10.1007/978-3-030-55506-1_58
Abstract: Due to the positive influence on students’ learning outcomes, the interests of studying effective knowledge management has been risen recently. Developing and implementing effective strategies ensures to promote learning outcomes. By reviewing and examining various influence factors, this research study has predicted the major factors that may influence of learning outcomes in blended learning environment. A series of simulation experiments and factor analyses have been conducted in order to investigate collaboration during group learning process. The simulation model for blended learning environment employed in this research has drawn on the characteristics of the Structural Equation Model (SEM) of the blended learning process of 128 students. Both randomness of those student learning behaviors and the reaction to information overload have been considered during simulation modeling. The simulation model enables for greatly increasing statistical samples of student learning behavior analysis. Besides, this research has studied the impact of multiple factors to blended learning mode, these factors include: the size of learning group, the group composition according to previous performance, teaching material amount, and the teacher influence. Experimental results predict that the factors mentioned above can enhance collaborative interaction among students during writing and reading activity. The research results of the optimization restriction factors for blended learning environment achieved in this study can be useful reference for a teacher who are facing the similar challenges. The results of this paper can also be used to reveal and eliminate the problem of inefficient collaboration and poor student performance in blended learning environment. The model proposed in this paper can be integrated with most of decision support systems of universities.
URI: http://rps.chtei-knteu.cv.ua:8585/jspui/handle/123456789/2417
Appears in Collections:06.39.41 Теорії менеджменту

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