Social learning networks: Efficiency optimization for MOOC forums

This study aims to produce a product in the form of a Social Learning Networks (SLN) based learning design using the Microsoft Teams platform that can be used by students who are taking Animation courses at the Jakarta State University Technology Study Program. This research was conducted by following the ADDIE development model procedure, which consisted of 5 stages, namely (1) Analysis: conducting a needs analysis, students and materials, (2) Design: designing a learning design, (3) Development: developing a learning design, (4) ) Implementation: conducting trials on experts and users, (5) Evaluation: evaluating the results of product development based on the trials that have been done. Based on the trial results of the experts, the overall average value was 3.36 which means very good. While the results of the one to one and small group trials obtained an overall average of 3.55 which means very good. The results of this development research indicate that the learning design developed can be used to facilitate students in the learning process, especially online learning.

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Investigating the educational value of social learning networks: a quantitative analysis

Interactive Technology and Smart Education ◽

10.1108/itse-09-2016-0034 ◽

2016 ◽

Vol 13 (4) ◽

pp. 305-322 ◽

Cited By ~ 5

Author(s):

Georgios Dafoulas ◽

Azam Shokri

Keyword(s):

Social Learning ◽

Social Engagement ◽

Technology Enhanced Learning ◽

Learning Networks ◽

Educational Value ◽

Content Type ◽

Learning Network ◽

Moderation Model ◽

The Impact ◽

Enhanced Learning

Purpose The emergence of Education 2.0 enabled technology-enhanced learning, necessitating new pedagogical approaches, while e-learning has evolved into an instrumental pedagogy of collaboration through affordances of social media. Social learning networks and ubiquitous learning enabled individual and group learning through social engagement and social distribution of knowledge. Nevertheless, these developments have not been supported with extensive studies focusing on quantifying the impact of technology-enhanced learning on students’ progress and achievement. The purpose of this paper is to investigate how a quantitative overview of Facebook’s influence on students’ progress can be incorporated in a proposed e-moderation model of teaching and learning. Design/methodology/approach The approach is based on extending Salmon’s (2003) e-moderation model, which provides an emphasis on the theoretical perspectives that support socially situated learning environments of social networks such as Facebook. The findings revealed that students’ grades were positively influenced by the complementary use of Facebook on their courses of study. Findings The use of a social learning network also triggered a significant increase in student participation in learning activities delivered over Facebook. Research limitations/implications The main research limitations were due to the fact that a single social network was chosen for conducting the experiments. Furthermore, the investigation was narrowed down to a selected range of sessions offered to college and university students as part of their course. Originality/value The paper’s contribution is twofold, as it offers an original set of guidelines for conducting social learning network experiments and provides valuable quantifiable findings on the educational value of such networks.

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A system to filter unsolicited texts from social learning networks

2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT) ◽

10.1109/icccnt.2013.6726687 ◽

2013 ◽

Author(s):

Sunil Yadav ◽

S. Das ◽

D. Rudrapal

Keyword(s):

Social Learning ◽

Learning Networks

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Online Learning Communities in the COVID-19 Pandemic: Social Learning Network Analysis of Twitter During the Shutdown

International Journal of Learning Analytics and Artificial Intelligence for Education (iJAI) ◽

10.3991/ijai.v2i1.15427 ◽

2020 ◽

Vol 2 (1) ◽

pp. 85 ◽

Cited By ~ 1

Author(s):

David John Lemay ◽

Tenzin Doleck

Keyword(s):

Online Learning ◽

Social Learning ◽

Network Analysis ◽

Learning Communities ◽

Learning Networks ◽

Online Learning Communities ◽

Learning Network ◽

Media Technologies ◽

Conventional Teaching ◽

The Social

This paper presents a social learning network analysis of Twitter during the 2020 global shutdown due to the COVID-19 pandemic. Research concerning online learning environments is focused on the reproduction of conventional teaching arrangements, whereas social media technologies afford new channels for the dissemination of information and sharing of knowledge and expertise. We examine Twitter feed around the hashtags #onlinelearning and #onlineteaching during the global shutdown to examine the spontaneous development of online learning communities. We find relatively small and ephemeral communities on the two topics. Most users make spontaneous contributions to the discussion but do not maintain a presence in the Twitter discourse. Optimizing the social learning network, we find many potential efficiencies to be gained through more proactive efforts to connect knowledge seekers and knowledge disseminators. Considerations and prospects for supporting online informal social learning networks are discussed.

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