LEARNING ANALYTICS FOR MODELLING STUDENT ENGAGEMENT IN E-LEARNING ENVIRONMENTS

2017 ◽  
Author(s):  
Maciej Pankiewicz
Keyword(s):  
Student Engagement ◽  
Learning Environments ◽  
Learning Analytics ◽  
E Learning

. Learning analytics technology in adaptive electronic learning environments.

2021 ◽  
Vol 92 (2) ◽  
pp. 144-153
Author(s):  
M.R. Attia ◽  
Keyword(s):  
Learning Styles ◽  
Learning Environments ◽  
Adaptive Learning ◽  
Learning Analytics ◽  
Rapid Identification ◽  
Electronic Learning ◽  
E Learning ◽  
Mental Abilities ◽  
The Difference ◽  
As If

Adaptive e-learning environments are based on diversifying the presentation of content according to the learning styles of each learner, where the content is presented as if it is directed to each student separately, and activities and tests are presented so that they are sensitive to the different styles of learners and suitable for their mental abilities. These environments depend in their design on intelligence, therefore, these environments can analyze the characteristics and capabilities of learners, each separately, and this is done through learning analytics technology that helps in the rapid identification of the patterns of learners and the development of their behavior within the environment. In this article, firstly we review what adaptive learning environments and its characteristics are; the difference between adaptable and adaptive environments; components of adaptive learning environments. Learning analytics technology is also highlighted; and its importance in adaptive e-learning environments.

Application of Deep Learning on Student Engagement in e-learning environments

2021 ◽  
Vol 93 ◽  
pp. 107277
Author(s):  
Prakhar Bhardwaj ◽  
P.K. Gupta ◽  
Harsh Panwar ◽  
Mohammad Khubeb Siddiqui ◽  
Ruben Morales-Menendez ◽  
...  
Keyword(s):  
Deep Learning ◽  
Student Engagement ◽  
Learning Environments ◽  
E Learning

scholarly journals Adaptive e-learning environment based on learning styles and its impact on development students' engagement

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Hassan A. El-Sabagh
Keyword(s):  
Student Engagement ◽  
Learning Environment ◽  
Learning Styles ◽  
Learning Environments ◽  
Control Group ◽  
Learning Approach ◽  
Quasi Experimental ◽  
E Learning ◽  
Research Experiment ◽  
The Impact

AbstractAdaptive e-learning is viewed as stimulation to support learning and improve student engagement, so designing appropriate adaptive e-learning environments contributes to personalizing instruction to reinforce learning outcomes. The purpose of this paper is to design an adaptive e-learning environment based on students' learning styles and study the impact of the adaptive e-learning environment on students’ engagement. This research attempts as well to outline and compare the proposed adaptive e-learning environment with a conventional e-learning approach. The paper is based on mixed research methods that were used to study the impact as follows: Development method is used in designing the adaptive e-learning environment, a quasi-experimental research design for conducting the research experiment. The student engagement scale is used to measure the following affective and behavioral factors of engagement (skills, participation/interaction, performance, emotional). The results revealed that the experimental group is statistically significantly higher than those in the control group. These experimental results imply the potential of an adaptive e-learning environment to engage students towards learning. Several practical recommendations forward from this paper: how to design a base for adaptive e-learning based on the learning styles and their implementation; how to increase the impact of adaptive e-learning in education; how to raise cost efficiency of education. The proposed adaptive e-learning approach and the results can help e-learning institutes in designing and developing more customized and adaptive e-learning environments to reinforce student engagement.

scholarly journals Exploring Factors, and Indicators for Measuring Students’ Sustainable Engagement in e-Learning

2019 ◽  
Vol 11 (4) ◽  
pp. 985 ◽  
Author(s):  
Jeongju Lee ◽  
Hae-Deok Song ◽  
Ah Hong
Keyword(s):  
Student Engagement ◽  
Learning Environments ◽  
Online Courses ◽  
Community Support ◽  
Dropping Out ◽  
Validity And Reliability ◽  
Confirmatory Factor Analyses ◽  
Cognitive Problem ◽  
E Learning ◽  
Online University Students

The topic of engagement has been attracting increasing amounts of attention in the field of e-learning. Research shows that multifarious benefits occur when students are engaged in their own learning, including increased motivation and achievement. Previous studies have proposed many scales for measuring student engagement. However, very few have been developed to measure engagement in e-learning environments. Thus, developing an instrument for measuring student engagement in e-learning environments is the purpose of this study. The participants of this study were 737 Korean online university students. Initial items were designed based on the literature. The instrument items were reduced from an initial 48 to 24 items after obtaining expert opinion and then validity and reliability analysis. Exploratory and confirmatory factor analyses were also conducted. Six factors, including psychological motivation, peer collaboration, cognitive problem solving, interaction with instructors, community support, and learning management emerged in the 24-item scale. This scale is expected to help instructors and curriculum designers to find conditions to improve student engagement in e-learning environments, and ultimately prevent students from dropping out of online courses.

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