Research on Inquiry-Collaborative Learning of Tourism Economics Course Based on E-learning Environment

2009 ◽  
Author(s):  
Mu-chun Li ◽  
Bing Li
Keyword(s):  
Collaborative Learning ◽  
Learning Environment ◽  
E Learning

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.

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.

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

2011 ◽  
Vol 9 (2) ◽  
pp. 23-39 ◽  
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.

scholarly journals Enhancing the e-learning environment using wikis and blogs

2011 ◽  
Author(s):  
Susan Wikinson
Keyword(s):  
Higher Education ◽  
Collaborative Learning ◽  
Learning Environment ◽  
Teaching And Learning ◽  
Approaches To Learning ◽  
Widening Participation ◽  
Learning Tools ◽  
Short Account ◽  
Educational Benefits ◽  
E Learning

This paper provides a short account of the educational benefits of using wikis and blogs in teaching and learning in higher education.  It draws on constructivist principles to explain and support the use of collaborative learning tools in higher education, and explores the factors necessary to create a successful e-learning environment.  Support for use of such e-learning tools is placed in the context of recent shifts in pedagogical approaches to learning, the increase in demand for higher education, the widening participation agenda, and the technical revolution.  It intends to convey the importance of developing collaborative learning communities within higher education, whilst keeping focus on the pedagogical, rather than technological, reasons for change.

scholarly journals Increasing Geographic Literacy through the Development of Computer Supported Collaborative Learning

2020 ◽  
Vol 15 (07) ◽  
pp. 74
Author(s):  
Neni Wahyuningtyas ◽  
Idris Idris
Keyword(s):  
Collaborative Learning ◽  
Learning Environment ◽  
Research And Development ◽  
21St Century ◽  
Learning Process ◽  
Computer Supported Collaborative Learning ◽  
Efficiency And Effectiveness ◽  
E Learning ◽  
The Media ◽  
Geographic Literacy

This paper aims to develop computer supported collaborative learning to improve geographic literacy. This study used research and development with the ASSURE model. The results of this development are in the form of basic geography concept modules with 3 videos integrated into e-learning. The media and material validation show that the product developed was very good and worth testing. In addition, the results of media validation by taking into account indicators of attractiveness, efficiency and effectiveness, were declared very good and students were enthusiastic about learning to use this media. This product can be an alternative medium for the 21st century learning environment that applies e-learning in the learning process.

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.

Sign in / Sign up

Export Citation Format

Share Document