scholarly journals Watch Party Lectures: Synchronous Delivery of Asynchronous Material

2021 ◽  
Author(s):  
Carolina Ellen Kuepper-Tetzel ◽  
Emily Nordmann
Keyword(s):  
Learning Environment ◽  
Virtual Learning ◽  
Virtual Learning Environment ◽  
Teaching Approaches ◽  
Crucial Element ◽  
The Future ◽  
Screen Sharing ◽  
Synchronous Time

Watch party lectures combine asynchronous and synchronous teaching approaches: lecturers record short videos of the directly instructed content, for one-hour lectures, lecturers aim to record 2-3 short videos for a maximum of 40-45 minutes. These pre-recorded videos are uploaded on the virtual learning environment (VLE). However, the crucial element of watch party lectures is the scheduled, synchronous time during which these pre-recordings are watched together via screen sharing. Watch party lectures allow for meaningful interactions between lecturer and students while watching the videos. Students use the chat box to ask questions and the lecturer addresses them immediately, e.g., by providing links to additional resources. Watch party lectures were welcomed by students and lecturers alike and we strongly recommend integrating both asynchronous and synchronous elements in the future, regardless of the modality or format of teaching delivery.

Proposal of an instrument to evaluate interaction spaces in a VLE

2019 ◽  
pp. 1-13
Author(s):  
Rubí Estela Morales-Salas ◽  
Daniel Montes-Ponce
Keyword(s):  
Learning Environment ◽  
Design Space ◽  
Collaborative Work ◽  
Virtual Learning ◽  
Interaction Space ◽  
Learning Objects ◽  
Traditional Education ◽  
Virtual Learning Environment ◽  
Discussion Forums ◽  
Exhibition Space

A virtual learning environment is conceived as an interaction space that ease the realization of mediated activities by technology, in this case the internet; besides using multimedia materials, learning objects, social networks, among others; which have changed imminently the traditional education. In this article an instrument is proposed in a checklist format, to evaluate any platform that has interaction spaces such as a Virtual Learning Environment, in this case responding to four spaces or general indicators: information Space, Mediation / Interaction Space, Instructional Design Space and Exhibition Space. Criteria are used according to the interactions and activities carried out by the consultant and virtual student. These, in turn, come up from the analysis and interaction of the advisers achieved in the discussion forums and portfolio activities through collaborative work. It was situated as a qualitative research, with a descriptive nature since it is not limited to data collection only, but also it refers and analyzes the interaction of the advisers achieved in the discussion forums and portfolio activities through the collaborative work of the workshop course "Virtual Learning Environments" developed in a virtual learning environment.

scholarly journals Self-Regulation using Moodle Virtual Learning Environment (VLE) in Solar System Practice

2021 ◽  
Vol 1779 (1) ◽  
pp. 012072
Author(s):  
BR Rosyadi ◽  
Khoirun Nisa ◽  
Irfan Afandi ◽  
Fathor Rozi ◽  
Ahmad Fawaid ◽  
...  
Keyword(s):  
Solar System ◽  
Learning Environment ◽  
Self Regulation ◽  
Virtual Learning ◽  
Virtual Learning Environment

scholarly journals Using Virtual Learning Environment Data for the Development of Institutional Educational Policies

2021 ◽  
Vol 11 (15) ◽  
pp. 6811
Author(s):  
Emanuel Marques Queiroga ◽  
Carolina Rodríguez Enríquez ◽  
Cristian Cechinel ◽  
Alén Perez Casas ◽  
Virgínia Rodés Paragarino ◽  
...  
Keyword(s):  
Learning Environment ◽  
Predictive Models ◽  
Data Science ◽  
Educational Data Mining ◽  
Virtual Learning ◽  
Academic Community ◽  
Virtual Learning Environment ◽  
Educational Policies ◽  
Interdisciplinary Exchange ◽  
Computational Resources

This paper describes the application of Data Science and Educational Data Mining techniques to data from 4529 students, seeking to identify behavior patterns and generate early predictive models at the Universidad de la República del Uruguay. The paper describes the use of data from different sources (a Virtual Learning Environment, survey, and academic system) to generate predictive models and discover the most impactful variables linked to student success. The combination of different data sources demonstrated a high predictive power, achieving prediction rates with outstanding discrimination at the fourth week of a course. The analysis showed that students with more interactions inside the Virtual Learning Environment tended to have more success in their disciplines. The results also revealed some relevant attributes that influenced the students’ success, such as the number of subjects the student was enrolled in, the students’ mother’s education, and the students’ neighborhood. From the results emerged some institutional policies, such as the allocation of computational resources for the Virtual Learning Environment infrastructure and its widespread use, the development of tools for following the trajectory of students, and the detection of students at-risk of failure. The construction of an interdisciplinary exchange bridge between sociology, education, and data science is also a significant contribution to the academic community that may help in constructing university educational policies.

scholarly journals Medical Student Engagement in a Virtual Learning Environment Positively Correlates with Course Performance and Satisfaction in Psychiatry

2021 ◽  
Author(s):  
Larrilyn L. Grant ◽  
Michael J. Opperman ◽  
Brennan Schiller ◽  
Jonathan Chastain ◽  
Jennelle Durnett Richardson ◽  
...  
Keyword(s):  
Medical Student ◽  
Student Engagement ◽  
Learning Environment ◽  
Virtual Learning ◽  
Virtual Learning Environment ◽  
Course Performance

Adaptive virtual learning environment

2012 ◽  
Author(s):  
Sandra Dutra Piovesan ◽  
Erico Marcelo Hoff do Amaral ◽  
Catiane Priscila Barbosa Arenhardt ◽  
Roseclea Duarte Medina
Keyword(s):  
Learning Environment ◽  
Virtual Learning ◽  
Virtual Learning Environment
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