A Model for Improving Online Collaborative Learning through Machine Learning

2015 ◽  
pp. 204-219 ◽  
Author(s):  
E. Muuro Maina ◽  
Peter W. Wagacha ◽  
Robert O. Oboko
Keyword(s):  
Machine Learning ◽  
Online Learning ◽  
Collaborative Learning ◽  
Learning Environment ◽  
Online Learning Environment ◽  
Online Collaborative Learning ◽  
Collaborative Software ◽  
Online Tools ◽  
E Learning ◽  
Collaborative Learning Environment

Online collaborative learning provides new opportunities for student collaboration in an online learning environment and at the same time spawns new challenges for teachers supporting group work. With the current Course Management Systems (CMS) such as Moodle, technology has provided online tools that include discussions forums, chat rooms, e-mails, newsgroups, workshops, etc. These tools provide a collaborative learning environment. To include constructivist learning in an online learning environment is a good collaborative strategy that is necessary since it engages learners in learning activities through interaction with their peers and teacher. A good collaborative strategy in an e-learning environment must primarily ensure that the expected interaction occurs in line with the learning mechanism being employed. This cannot merely be met by offering a set of collaborative software tools alone. It also requires the instructors' support. As the number of students studying online continues to increase, there is need to develop models that can improve online collaborative learning with minimal involvement of the instructor because the instructor might not be able to cope with increased number of students. To address this need, this chapter discusses a novel model for improving online collaborative learning that uses Machine Learning (ML) techniques.

A Multi-Agent Question-Answering System for E-Learning and Collaborative Learning Environment

2014 ◽  
pp. 134-149
Author(s):  
Tannaz Alinaghi ◽  
Ardeshir Bahreininejad
Keyword(s):  
Collaborative Learning ◽  
Learning Environment ◽  
Question Answering ◽  
Question Answering System ◽  
Course Materials ◽  
Life Styles ◽  
History Of ◽  
E Learning ◽  
Multi Agent ◽  
Collaborative Learning Environment

The increasing advances of new Internet technologies in all application domains have changed life styles and interactions. E-learning and collaborative learning environment systems are originated through such changes and aim at providing facilities for people in different times and geographical locations to cooperate, collaborate, learn and work together by using various educational services. One of the most important requirements of learners in online and virtual environments is the ability to ask questions and receive appropriate answers. The nature of such environments and the lack of physical existence of teachers make such issues critical and challenging problems. This paper presents a multi-agent system for building a question-answering system in learning management systems and collaborative learning environments. In the proposed system, after validating the content of questions, all available resources including course materials, frequently asked questions and responses from other learners will be gathered and finally using a recommender system, the most appropriate answer(s) with respect to several criteria such as learner’s knowledge, research background, history of previous questions, and the candidate answers relevant to the question will be suggested. A simplified version of the system has been implemented and integrated to a well known open source collaborative learning environment system in order to simulate and evaluate the applicability and appropriateness of the proposed system. The result shows that the proposed question-answering system may be used efficiently and expanded to accommodate further advanced capabilities.

Social Software and E-Learning

2007 ◽  
pp. 228-247
Author(s):  
Jon Dron
Keyword(s):  
Online Learning ◽  
Learning Environment ◽  
Web 2.0 ◽  
Learning Environments ◽  
Social Software ◽  
Learning Trajectory ◽  
Online Learning Environment ◽  
Networked Learning ◽  
E Learning

This book offers an exploration of the ways that a learning trajectory is determined, and, in particular, how an online learning environment can affect that trajectory. It provides suggestions about how, primarily through technologies that underlie what is vulgarly known as “Web 2.0,” networked learning environments should be constructed to give control to learners if they need it, as they need it, and when they need it.

scholarly journals EXPLORING COLLABORATIVE ONLINE LEARNING

2019 ◽  
Vol 5 (1) ◽  
Author(s):  
David D. Curtis ◽  
Michael J. Lawson
Keyword(s):  
Online Learning ◽  
Collaborative Learning ◽  
Learning Environment ◽  
Work Groups ◽  
Online Learning Environment ◽  
Substantial Evidence ◽  
Face To Face

An investigation was carried out to determine the extent to which evidence of collaborative learning could be identified in students’ textual interactions in an online learning environment. The literature on collaborative learning has identified a range of behaviors that characterize successful collaborative learning in face-to-face situations. Evidence of these behaviors was sought in the messages that were posted by students as they interacted in online work groups. Analysis of students’ contributions reveals that there is substantial evidence of collaboration, but that there are differences between conventional face-to-face instances of collaborative learning and what occurs in an asynchronous, networked environment.

scholarly journals Development, validation and use of the Online Learning Environment Survey

2005 ◽  
Vol 21 (1) ◽  
Author(s):  
Sue Trinidad ◽  
Jill Aldridge ◽  
Barry Fraser
Keyword(s):  
Online Learning ◽  
Hong Kong ◽  
Learning Environment ◽  
Learning Environments ◽  
Quantitative Data ◽  
Reliability And Validity ◽  
Female Students ◽  
Online Learning Environment ◽  
Male And Female ◽  
E Learning

<span>This article reports the development, validation and use of a survey for assessing students' perceptions of their e-learning environments. The Online Learning Environment Survey (OLES) was administered to 325 students, 131 in Australia and 194 in Hong Kong. The data were analysed to examine 1) the reliability and validity of the survey, 2) differences between the perceptions of a) students' actual and preferred environment, b) students and their teacher and c) male and female students and 3) whether associations exist between students' perceptions of their e-learning environment and their enjoyment of e-learning. In addition to quantitative data, unstructured interviews were used to provide a more in depth understanding of the e-learning environments created. These data provide valuable feedback to educators working in e-learning environments to help teachers to evaluate the effectiveness of the environment and to make adjustments and improvements as required.</span>

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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