scholarly journals User acceptance in a computer-supported collaborative learning (CSCL) environment with social network awareness (SNA) support

2019 ◽  
Vol 35 (1) ◽  
Author(s):  
Jian-Wei Lin ◽  
Hao-Chiang Koong Lin
Keyword(s):  
Social Network ◽  
Collaborative Learning ◽  
Social Influence ◽  
Explanatory Power ◽  
User Acceptance ◽  
Learning System ◽  
Extended Model ◽  
Computer Supported Collaborative Learning ◽  
Network Awareness ◽  
E Learning

Although many e-learning studies have applied the unified theory of acceptance and usage of technology (UTAUT) to investigate user acceptance, their findings have been inconsistent. One of reasons is that the user acceptance model of an e-learning system can be determined by the new information technologies (or mechanisms) the e-learning system utilises. Computer-supported collaborative learning (CSCL) with social network awareness (SNA) mechanisms has been widely adopted because it can enhance online collaborative learning effectiveness. Since new SNA mechanisms are expected to have a huge impact on user acceptance in CSCL environments, this study extends UTAUT to investigate user acceptance of an SNA CSCL environment. This study empirically evaluated the extended model by surveying 186 undergraduates, who had completed a 5-week electric commerce course in an SNA CSCL environment. The findings indicated that the SNA mechanism substantially strengthened the effect of social influence on behavioural intention to use the SNA CSCL system. Compared with other CSCL studies, the predictive power of social influence in this study was higher, while that of other determinants (i.e., performance expectancy and effort expectancy) in this study were lower. The extended model demonstrated higher explanatory power compared to models used in other CSCL studies.

scholarly journals Intelligent Edutab Box: Supporting Real-Time Face-to-Face Collaborative Learning

2021 ◽  
Vol 25 (2) ◽  
pp. 258-269
Author(s):  
Yuto Omae ◽  
Kazutaka Mizukoshi ◽  
Tatsuro Furuya ◽  
Takayuki Oshima ◽  
Norihisa Sakakibara ◽  
...  
Keyword(s):  
Collaborative Learning ◽  
Real Time ◽  
Information And Communications Technology ◽  
Learning System ◽  
Computer Supported Collaborative Learning ◽  
Learning Groups ◽  
Educational Benefits ◽  
Face To Face ◽  
E Learning ◽  
Learning Analysis

Educational benefits of collaborative learning have been demonstrated in several studies and various systems have been developed to date. Numerous efforts have been made to enhance these benefits by supporting collaborative learning with information and communications technology. These efforts have primarily involved support for constructing collaborative learning groups, for collaborative learning in e-learning environments, and for collaborative learning analysis. This study aims to develop a computer-supported collaborative learning system that supports instructors in real time to facilitate collaborative learning in a face-to-face environment with multiple learners at the same time to provide enhanced support. Both the learner and instructor have one tablet terminal and conduct collaborative learning in a single classroom. Herein, the learner can use the tablet to save an educational log and freely browse the educational log of another learner. By referencing the educational logs, learners can learn through face-to-face communication. Additionally, the instructor can determine (1) who is viewing whose educational log and to what extent and (2) which learner is struggling to achieve targets. Herein, an overview of the proposed system is provided and the results obtained using the proposed system are reported to evaluate its effectiveness.

scholarly journals Profile reliability to improve recommendation in social-learning context

2018 ◽  
Vol 44 (2) ◽  
pp. 433-454 ◽  
Author(s):  
Corinne Amel Zayani ◽  
Leila Ghorbel ◽  
Ikram Amous ◽  
Manel Mezghanni ◽  
André Péninou ◽  
...  
Keyword(s):  
Social Network ◽  
Social Learning ◽  
Learning System ◽  
Learning Context ◽  
Content Type ◽  
Semantic Relationships ◽  
The Hierarchical Structure ◽  
E Learning ◽  
Many Sources

Purpose Generally, the user requires customized information reflecting his/her current needs and interests that are stored in his/her profile. There are many sources which may provide beneficial information to enrich the user’s interests such as his/her social network for recommendation purposes. The proposed approach rests basically on predicting the reliability of the users’ profiles which may contain conflictual interests. The paper aims to discuss this issue. Design/methodology/approach This approach handles conflicts by detecting the reliability of neighbors’ profiles of a user. The authors consider that these profiles are dependent on one another as they may contain interests that are enriched from non-reliable profiles. The dependency relationship is determined between profiles, each of which contains interests that are structured based on k-means algorithm. This structure takes into consideration not only the evolutionary aspect of interests but also their semantic relationships. Findings The proposed approach was validated in a social-learning context as evaluations were conducted on learners who are members of Moodle e-learning system and Delicious social network. The quality of the created interest structure is assessed. Then, the result of the profile reliability is evaluated. The obtained results are satisfactory. These results could promote recommendation systems as the selection of interests that are considered of enrichment depends on the reliability of the profiles where they are stored. Research limitations/implications Some specific limitations are recorded. As the quality of the created interest structure would evolve in order to improve the profile reliability result. In addition, as Delicious is used as a main data source for the learner’s interest enrichment, it was necessary to obtain interests from other sources, such as e-recruitement systems. Originality/value This research is among the pioneer papers to combine the semantic as well as the hierarchical structure of interests and conflict resolution based on a profile reliability approach.

Perceptions in Computer-Supported Collaborative Learning

2011 ◽  
pp. 182-199
Author(s):  
Yingqin Zhong ◽  
John Lim
Keyword(s):  
Collaborative Learning ◽  
Cultural Diversity ◽  
Negative Relationship ◽  
Learning Technology ◽  
Computer Supported Collaborative Learning ◽  
Research Attention ◽  
Homogeneous Groups ◽  
E Learning ◽  
And Performance

Computer-supported collaborative learning (CSCL) has received increasing research attention owing to advances in e-learning technology and paradigmatic shifts in the educational arena. Owing to the growing diversity in student population in terms of nationality, the role of cultural diversity becomes greatly pronounced, and must be addressed. In this study, a laboratory experiment with a 2×2×2 factorial design was conducted, to investigate the interaction effects of perceived cultural diversity, group size, and leadership, on learners’ performance and satisfaction with process. Contrary to an expected negative relationship between perceived cultural diversity and performance, a positive relationship emerged as a result of leadership. Leadership lowered learners’ satisfaction with the process in perceived homogeneous groups (as compared to perceived heterogeneous groups) and smaller groups (as compared to larger groups).

The Study of User Acceptance Toward E-Learning System in Higher Education

2017 ◽  
Vol 7 (2) ◽  
pp. 466
Author(s):  
Dana Indra Sensuse ◽  
Darmawan Baginda Napitupulu
Keyword(s):  
Higher Education ◽  
Technology Acceptance ◽  
Evaluation Model ◽  
User Acceptance ◽  
Positive Influence ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Learning System ◽  
Perceived Ease Of Use ◽  
E Learning

<p>E-learning is a model of delivering learning content electronically with the help of computers and multimedia. ABC University has implemented the e-learning system for two (2) years in order to improve the quality of teaching and learning process. This study aims to determine the level of user acceptance, especially from the perspective of students. In other words, this study also wants to evaluate the implementation of e-learning systems in higher education as well as identifying any factors that encourage students to use e-learning system especially in ABC University. The research method used was survey with the approach of TAM (Technology Acceptance Model) as the technology acceptance evaluation model consisting of two main factors: perceived ease of use and perceived usefulness. The results showed perceived usefulness significantly positive influence on user acceptance, while perceived ease of use did not significantly influence on user acceptance. The perceived ease of use also significantly positive influence perceived usefulness. The variance of user acceptance could be explained by two factors about 50.5%. </p>

scholarly journals Implementing M-Learning System for Learning Mathematics Through Computer Games and Applying Neural Networks for Content Similarity Analysis of an Integrated Social Network

2021 ◽  
Vol 15 (13) ◽  
pp. 145
Author(s):  
Petar Juric ◽  
Marija Brkic Bakaric ◽  
Maja Matetic
Keyword(s):  
Neural Networks ◽  
Social Network ◽  
Computer Games ◽  
Primary Schools ◽  
Learning System ◽  
Learning Mathematics ◽  
Educational Computer ◽  
E Learning ◽  
Content Similarity ◽  
Educational Computer Games

In order to make e-learning systems more readily available for use, the majority of new systems are being developed in a form suitable for mobile learning, i.e. m-learning. The paper puts focus on the parts of the implementation of an e-learning system which is not restricted to desktop platforms, but works equally well on smartphones and tablets in the form of m-learning. The implemented system uses educational computer games for learning Mathematics in primary schools and has an integrated social network, which is used for communication and publishing of the content related to the game. Besides analysing the platforms used for accessing the system (desktop/mobile), since students are given a choice, the paper also questions how to interpret messages when they contain concepts in student jargon or generally unknown to teachers, and shows that these messages can be interpreted by applying neural networks.

Bridging the Gap between LMS and Social Network Learning Analytics in Online Learning

2016 ◽  
Vol 9 (4) ◽  
pp. 1-15 ◽  
Author(s):  
Ángel Hernández-García ◽  
Miguel Ángel Conde-González
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Collaborative Learning ◽  
Learning Analytics ◽  
Real Data ◽  
General Purpose ◽  
Computer Supported Collaborative Learning ◽  
Message Boards ◽  
Social Graphs

Despite the great potential of social network analysis (SNA) methods and visualizations for learning analytics in computer-supported collaborative learning (CSCL), these approaches have not been fully explored due to two important barriers: the scarcity and limited functionality of built-in tools in Learning Management Systems (LMS), and the difficulty to import educational data from formal virtual learning environments into social network analysis programs. This study aims to cover that gap by introducing GraphFES, an application and web service for extraction of interaction data from Moodle message boards and generation of the corresponding social graphs for later analysis using Gephi, a general purpose SNA software. In addition, this paper briefly illustrates the potential of the combination of the three systems (Moodle, GraphFES and Gephi) for social learning analytics using real data from a computer-supported collaborative learning course with strong focus on teamwork and intensive use of forums.

Successful Implementation of a Computer-Supported Collaborative Learning System in Teaching E-Commerce

2013 ◽  
Vol 9 (4) ◽  
pp. 1-20
Author(s):  
E. W. T. Ngai ◽  
S. S. Lam ◽  
J. K. L. Poon
Keyword(s):  
Collaborative Learning ◽  
Teaching And Learning ◽  
Learning By Doing ◽  
Project Based Learning ◽  
Learning System ◽  
Future Research ◽  
Successful Implementation ◽  
Computer Supported Collaborative Learning ◽  
Business Context ◽  
Game Environment

This paper describes the successful application of a computer-supported collaborative learning system in teaching e-commerce. The authors created a teaching and learning environment for 39 local secondary schools to introduce e-commerce using a computer-supported collaborative learning system. This system is designed to equip students with additional knowledge and skills in e-commerce. In this paper, the authors focus on the practical implications of the project-based learning approach on the teaching and learning of introductory e-commerce in the business context. Results indicate that students are interested in the proposed approach, particularly in learning by doing. In conclusion, the authors describe in this paper the successful development of a project-based teamwork game environment for the teaching and learning of e-commerce in schools. This environment can enrich learning and the pedagogical use of development tools in the academe. Finally, the paper puts forward two propositions that can guide hypothesis generation in future research.

Collaborative Activities Management System Model (CAMS) for Web-based Virtual Classrooms

2017 ◽  
Vol 2 (2) ◽  
pp. 1-14
Author(s):  
Ibam E. Onwuka ◽  
Agbonifo O. Catherine ◽  
Adewale O. Sunday
Keyword(s):  
Collaborative Learning ◽  
Learning Environment ◽  
Management System ◽  
Learning Systems ◽  
Learning System ◽  
System Model ◽  
Online Collaborative Learning ◽  
Individual Participant ◽  
E Learning ◽  
Collaborative Activities

Online collaborative learning systems have emerged as one of the most valuable aspects of e-learning systems. E-learning products that lack features for online collaboration among participants are deemed to be incomplete or sub-standard. Collaboration modules within an e-learning system consist of assets for group communication and work “spaces” and facilities. Activities within the collaborative framework of an e-learning system advances collaborative social interaction and the social construction of knowledge. Participants in an e-learning environment get involved in many activities which if not well coordinated could hamper collaboration instead of enhancing it. Therefore, the need to create measurable tools (models) that can coordinate these collaborative activities and provide up-to-date information or status of individual participant and group participants in collaborative activities within an e-learning environment has become inevitable. This work seeks to presents the design of activities management system model for online collaborative learning systems. The model contains some mathematical models for determining the level of involvements of a participant or groups in online classes (class attendance), discussions, project and polls. Their levels of participation are assigned weights and their aggregate value interpreted to give up-to-date status of their involvement in collaborative activities. The model is developed using WAMP tools.

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