"An Analysis on the Research Trends on Online Learning Engagement Using CiteSpace"

2021 ◽  
Vol 65 (3) ◽  
pp. 1-20
Author(s):  
Chen Yuanyuan ◽  
Kim Gina
Keyword(s):  
Online Learning ◽  
Research Trends ◽  
Learning Engagement

Teacher Presence

2018 ◽  
pp. 7922-7934
Author(s):  
Caroline M. Crawford
Keyword(s):  
Online Learning ◽  
Instructional Design ◽  
Learning Environment ◽  
Learning Environments ◽  
Mobile Learning ◽  
Support System ◽  
Distributed Learning ◽  
Learning Engagement ◽  
Teacher Presence ◽  
Instructional Facilitator

Teacher presence refers to the fully engaged instructional facilitator within a learning environment. Within this specific discussion of teacher presence, the focus is upon distributed learning environments that includes not only online learning environments but also mobile learning engagement efforts. Teacher presence engages not merely an instructional design and evaluative assessment effort, but integrally engages the learners within the instructional environment through discourse, reflective practices and supporting the motivational needs of the learner. Further, teacher presence directly impacts the motivational and cognitive support needs of learners, through instructionally appropriate actions of the instructor as a facilitative guide, as a self-regulatory maven, within a cognitive load support system, as well as mentor-focused instructional efforts.

Investigating English teachers' online learning engagement: A case study during COVID-19 pandemic

2021 ◽  
pp. 49-54
Author(s):  
Pratiwi Amelia ◽  
Dwi Rukmini ◽  
Januarius Mujiyanto ◽  
Dwi Anggani Linggar Bharati
Keyword(s):  
Online Learning ◽  
English Teachers ◽  
Learning Engagement

scholarly journals Online engagement and performance on formative assessments mediate the relationship between attendance and course performance

2022 ◽  
Vol 19 (1) ◽  
Author(s):  
Chang Lu ◽  
Maria Cutumisu
Keyword(s):  
Online Learning ◽  
Academic Success ◽  
Formative Assessment ◽  
Academic Outcomes ◽  
Formative Assessments ◽  
Learning Engagement ◽  
Class Attendance ◽  
And Performance ◽  
The Impact ◽  
The Relationship

AbstractIn traditional school-based learning, attendance was regarded as a proxy for engagement and key indicator for performance. However, few studies have explored the effect of in-class attendance in technology-enhanced courses that are increasingly provided by secondary institutions. This study collected n = 367 undergraduate students’ log files from Moodle and applied learning analytics methods to measure their lecture attendance, online learning activities, and performance on online formative assessments. A baseline and an alternative structural equation models were used to investigate whether online learning engagement and formative assessment mediated the relationship between lecture attendance and course academic outcomes. Results show that lecture attendance does not have a direct effect on academic outcomes, but it promotes performance by leveraging online learning engagement and formative assessment performance. Findings contribute to understanding the impact of in-class attendance on course academic performance and the interplay of in-class and online-learning engagement factors in the context of technology-enhanced courses. This study recommends using a variety of educational technologies to pave multiple pathways to academic success.

Data-driven Online Learning Engagement Detection via Facial Expression and Mouse Behavior Recognition Technology

2019 ◽  
Vol 58 (1) ◽  
pp. 63-86 ◽  
Author(s):  
Zhaoli Zhang ◽  
Zhenhua Li ◽  
Hai Liu ◽  
Taihe Cao ◽  
Sannyuya Liu
Keyword(s):  
Online Learning ◽  
Facial Expression ◽  
Fundamental Problem ◽  
Recognition Rate ◽  
Detection Algorithm ◽  
Expression Recognition ◽  
Learning Engagement ◽  
Movement Data ◽  
Efficient Detection ◽  
Mouse Movement

Online learning engagement detection is a fundamental problem in educational information technology. Efficient detection of students’ learning situations can provide information to teachers to help them identify students having trouble in real time. To improve the accuracy of learning engagement detection, we have collected two aspects of students’ behavior data: face data (using adaptive weighted Local Gray Code Patterns for facial expression recognition) and mouse interaction. In this article, we propose a novel learning engagement detection algorithm based on the collected data (students’ behavior), which come from the cameras and the mouse in the online learning environment. The cameras were utilized to capture students’ face images, while the mouse movement data were captured simultaneously. In the process of image data labeling, we built two datasets for classifier training and testing. One took the mouse movement data as a reference, while the other did not. We performed experiments on two datasets using several methods and found that the classifier trained by the former dataset had a better performance, and its recognition rate is higher than that of the latter one (94.60% vs. 91.51%).

scholarly journals Secondary School Language Teachers’ Online Learning Engagement during the Covid-19 Pandemic in Indonesia

10.28945/4626 ◽  
2020 ◽  
Vol 19 ◽  
pp. 803-832
Author(s):  
Anita - Lie ◽  
Siti Mina Tamah ◽  
Imelda - Gozali ◽  
Katarina Retno Triwidayati ◽  
Tresiana Sari Diah Utami ◽  
...  
Keyword(s):  
Online Learning ◽  
Technology Integration ◽  
Digital Divide ◽  
Content Knowledge ◽  
Technological Knowledge ◽  
Language Teachers ◽  
Equal Opportunities ◽  
Learning Engagement ◽  
Impacting Factors ◽  
The Government

Aim/Purpose: The purpose of this study was to explore language teachers’ online engagement during the Covid-19 pandemic in Indonesia. Four questions guided the inquiry in this study: 1) To what extent did teachers engage in online learning during the Covid-19 pandemic? 2) What challenges did teachers encounter while engaging in online learning during the Covid-19 crisis? 3) How has the suspension of face-to-face classroom meetings changed teachers’ practices? and 4) What were their hopes for the future of education in their respective regions?v Background: The sudden learn-from-home mode enacted since 24 March 2020 due to the Covid-19 pandemic has forced all schools to shift into online learning with no or little preparation in terms of internet access, teacher capacity, and student-parent readiness. All in all, the pandemic disruption has shed light on the widening digital divide that has serious implications for the human capital development in Indonesia Methodology: This case study involved 18 teachers from four regions in Indonesia. Data were collected through an online survey, weekly reflections, and interviews with the teachers. A group interview with five students for each of the 18 teachers was used as triangulation. To probe more deeply into a representative sample for a variety of attributes, the researchers then focused on four teachers for a more in-depth analysis. Contribution: Knowledge of the impacting factors on online learning engagement can aid in resolving the issues and providing equal opportunities for all students. This study highlighted that teachers in remote regions would need a more top-down intervention from education authorities and offered two recommendations to the government to overcome the widening digital divide as amplified by the current school suspension. This study presents interesting results pertaining to online learning engagement during the Covid-19 pandemic in Indonesia. Insights gained in this study would contribute to the perspective on the challenges and dilemmas faced by educators and students elsewhere while engaging in online learning. Findings: This study found an interplay of five related factors of online learning processes against five levels of engagement. Those five factors are learners, teachers’ prior exposure to online learning, technological knowledge, pedagogical knowledge, and the support system. Teachers in this study were still struggling to enhance the quality of online learning engagement. Nevertheless, given the rising awareness of the inadequacy of their online learning delivery and a renewed sense of commitment, these teachers had high hopes that they would be able to enhance their competence and improve their professional practices. Recommendations for Practitioners: This study found most teacher participants have, within a short period, enhanced their technological knowledge (TK) regardless of their prior exposure to technology. Teachers can be encouraged to integrate their technological knowledge with pedagogical and content knowledge to develop their technological pedagogical content knowledge (TPACK) by participating in the government program for teacher professional development. Recommendation for Researchers: This study involves only language teachers; therefore, future researchers are invited to involve non-language teachers so that more conclusive findings can be obtained. Impact on Society: Knowledge of the impacting factors on online learning engagement can aid in resolving the issues and providing equal opportunities for all students. More importantly, the lessons learned should enlighten educators that technology integration into sound pedagogy would transform current practices into quality learning. Future Research: Issues related to technology integration in education can still be unearthed especially because the budding insights of online learning will steadily be developing in post-pandemic realm, particularly in Indonesia.

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