Open AccessEvaluation of the Information-based Teaching Design Abilities of Educators in Blended Teaching
Author(s) -
Ya Wang
Publication year - 2022
Publication title -
international journal of emerging technologies in learning/international journal: emerging technologies in learning
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.454
H-Index - 24
eISSN - 1868-8799
pISSN - 1863-0383
DOI - 10.3991/ijet.v17i05.29849
Subject(s) - computer science , set (abstract data type) , curriculum , process (computing) , online and offline , teaching method , sample (material) , information technology , fuzzy logic , mathematics education , multimedia , artificial intelligence , psychology , pedagogy , chemistry , chromatography , operating system , programming language
Information-based teaching is a process where the information technologies are actively integrated with the curriculum system, teaching objectives and teaching content. In order to improve the information-based teaching design abilities of teachers, it is of practical significance to study the criteria and methods for evaluating their information-based teaching design abilities under the online and offline blended teaching model. Based on the visualized measurement results of the keyword co-occurrence network, this paper constructed an evaluation indicator system for the information-based teaching design abilities of teachers under the online and offline blended teaching model, and gave the detailed steps of fuzzy comprehensive evaluation. In order to identify the improvements in the information-based teaching design abilities of teachers, it established a neural network prediction model for the information-based teaching design ability set of teachers based on the given evaluation indicator sample time series. At last, the scientificity of the proposed evaluation indicator system was verified through a test, with the prediction results of the model given.