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Online teaching in universities during the Covid-19 epidemic: A study of the situation, effectiveness and countermeasures

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TLDR
The number of learning sessions designed by teachers, teaching methods, problems encountered in conducting online teaching, class interactions are all significantly related to teaching effectiveness and support attitude.
Abstract
This paper studies the online teaching practices carried out in universities during the Covid-19 epidemic. This study, through interviews, questionnaires, and model construction, finds: 1) the number of learning sessions designed by teachers, teaching methods, problems encountered in conducting online teaching, class interactions are all significantly related to teaching effectiveness and support attitude; 2) as to the students, the gender, number of class platforms adopted, number of courses participation, difficulties encountered in online learning and preferred learning styles are all significantly related to course quality, learning effectiveness and support attitude.

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The Selection of Learning Platforms to Support Learning Using Fuzzy Multiple Attribute Decision Making

TL;DR: This study will analyze how to choose the right learning platform for an educational institution using SAW (Simple Additive Weighting)-based Fuzzy Multiple Attribute Decision Making (FMADM) method.

Implementation of Contextual Learning Model Efforts to Improve the Quality of Online Learning of Professional English Students

TL;DR: In this paper , the authors used the contextual teaching and learning (CTL) model for online learning of professional English courses and found that the level of student participation in cycle two was known to increase the active participation rate of students by 41.94%.
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A Combination of Context Input Process Product and Kirkpatrick Evaluation Model to Determine the Effectiveness of E-Training for Principals during COVID-19 Pandemic

TL;DR: In this article , the authors evaluated the effectiveness of e-training in context, input, process, response, study, behavior, and outcome to determine the effectiveness and make recommendations for training.
Journal ArticleDOI

Artificial intelligence-based group decision making to improve knowledge transfer: the case of distance learning in higher education

TL;DR: In this paper , a method based on multicriteria classification and a dominance-based rough set approach (DRSA) is proposed to support teachers in decision making, which is composed of two phases: phase I builds collective decision rules from teachers' preferences, and phase II classifies students into two decision classes: "atrisk students" and "leader students".
References
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Journal Article

A Conceptual Model for Understanding Self-Directed Learning in Online Environments.

TL;DR: The purpose of this paper is to introduce a research-based framework for understanding SDL in online learning contexts, focusing primarily on process and personal attributes in face-to-face settings.
Journal ArticleDOI

Incorporating student population differences for effective online education: A content-based review and integrative model

TL;DR: This study applied a content-based method for collecting and evaluating recently published studies relating to populations of students engaged in formal online programs and courses and identified key descriptors and processes that prove essential for defining online student populations and understanding their differences.
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