research-article

Effect of media richness on user acceptance of blogs and podcasts

Authors:

Suku SinnappanAuthors Info & Claims

ITiCSE '10: Proceedings of the fifteenth annual conference on Innovation and technology in computer science education

Pages 137 - 141

https://doi.org/10.1145/1822090.1822130

Published: 26 June 2010 Publication History

Abstract

Effective communication has long been recognised as a key element in problem solving and decision making within and among organisations including educational institutions. With the advent of Web 2.0 technologies, the communication choices have also been expanded. Media Richness Theory (MRT) has long been used to examine the effect of traditional and new media on decision making. However, less is known about media richness of Web 2.0 technologies. This paper attempts to examine the media richness capabilities of two popular Web 2.0 technologies, blogs and podcasts, and its effect on user acceptance of these two technologies in Computer Science education. A theoretical model is presented using MRT and technology acceptance model (TAM). Students enrolled in Bachelor / Master of Computer Science programs participated in an online survey that helped in evaluating the proposed model. The study findings confirm the significant effect of media richness on user acceptance of blogs and podcasts but contradict MRT as rich medium (podcast) exerted weaker influence on user acceptance as compared to lean medium (blog).

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Cited By

Alhumaid KAlfaisal RAlnazzawi NAlfaisal AAlhumaidhi NAlamarin MSalloum S(2022)Predicting the Intention to Use Audi and Video Teaching Styles: An Empirical Study with PLS-SEM and Machine Learning ModelsThe 8th International Conference on Advanced Machine Learning and Technologies and Applications (AMLTA2022)10.1007/978-3-031-03918-8_23(250-264)Online publication date: 17-Apr-2022
https://doi.org/10.1007/978-3-031-03918-8_23
Sánchez-Prieto JMigueláñez SGarcía-Peñalvo F(2016)Enjoyment, resistance to change and mlearning acceptance among pre-service teachersProceedings of the Fourth International Conference on Technological Ecosystems for Enhancing Multiculturality10.1145/3012430.3012594(691-697)Online publication date: 2-Nov-2016
https://dl.acm.org/doi/10.1145/3012430.3012594
Hew TKadir S(2016)Predicting the acceptance of cloud-based virtual learning environmentTelematics and Informatics10.1016/j.tele.2016.01.00433:4(990-1013)Online publication date: 1-Nov-2016
https://dl.acm.org/doi/10.1016/j.tele.2016.01.004
Show More Cited By

Index Terms

Effect of media richness on user acceptance of blogs and podcasts
1. Computing methodologies
  1. Modeling and simulation
    1. Simulation theory
      1. Systems theory
2. Mathematics of computing
  1. Information theory

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cover image ACM Conferences

ITiCSE '10: Proceedings of the fifteenth annual conference on Innovation and technology in computer science education

June 2010

344 pages

ISBN:9781605588209

DOI:10.1145/1822090

General Chairs:
Reyyan Ayfer
Bilkent University, Turkey
,
John Impagliazzo
Qatar University, Qatar
,
Program Chair:
Cary Laxer
Rose-Hulman Institute of Technology, USA

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGCSE: ACM Special Interest Group on Computer Science Education

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Bilkent University: Bilkent University

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 June 2010

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SIGCSE

ITiCSE '10: Annual Conference on Innovation and Technology in Computer Science Education

June 26 - 30, 2010

Ankara, Bilkent, Turkey

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Overall Acceptance Rate 552 of 1,613 submissions, 34%

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Cited By

Alhumaid KAlfaisal RAlnazzawi NAlfaisal AAlhumaidhi NAlamarin MSalloum S(2022)Predicting the Intention to Use Audi and Video Teaching Styles: An Empirical Study with PLS-SEM and Machine Learning ModelsThe 8th International Conference on Advanced Machine Learning and Technologies and Applications (AMLTA2022)10.1007/978-3-031-03918-8_23(250-264)Online publication date: 17-Apr-2022
https://doi.org/10.1007/978-3-031-03918-8_23
Sánchez-Prieto JMigueláñez SGarcía-Peñalvo F(2016)Enjoyment, resistance to change and mlearning acceptance among pre-service teachersProceedings of the Fourth International Conference on Technological Ecosystems for Enhancing Multiculturality10.1145/3012430.3012594(691-697)Online publication date: 2-Nov-2016
https://dl.acm.org/doi/10.1145/3012430.3012594
Hew TKadir S(2016)Predicting the acceptance of cloud-based virtual learning environmentTelematics and Informatics10.1016/j.tele.2016.01.00433:4(990-1013)Online publication date: 1-Nov-2016
https://dl.acm.org/doi/10.1016/j.tele.2016.01.004
Hew TSyed Abdul Kadir S(2016)Behavioural intention in cloud-based VLEComputers in Human Behavior10.1016/j.chb.2016.05.07564:C(9-20)Online publication date: 1-Nov-2016
https://dl.acm.org/doi/10.1016/j.chb.2016.05.075

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