http://www.researchonline.mq.edu.au/vital/access/services/Feed ${session.getAttribute("locale")} 5 http://www.researchonline.mq.edu.au/vital/access/manager/Repository/mq:18764 While technological improvements of the computer supported collaborative learning (CSCL) have been substantial, its nontask social aspect has not received proportional attention. This study investigates the notion of nontask sociability of CSCL, and identifies its relationship with the students' learning outcomes using the case of an Australian postgraduate programme. Learning outcome is defined as a multiple variable consisting of pedagogical affect, student's interest and perceived learning. Five items were identified for operationalising the nontask sociability. These are ‘finding help’, ‘sense of appealing’, ‘sense of boringness’, ‘sense of interactivity’ and ‘sense of frustration’. In addition, a strong relationship was revealed between nontask sociability and learning outcomes which implies that further attention needs to be given to the nontask aspect of the CSCL interactions. Theoretical and practical implications of the findings are then discussed. 2013-06-17T06:36:35.258Z ]]> http://www.researchonline.mq.edu.au/vital/access/manager/Repository/mq:22738 While computer supported collaborative learning (CSCL) environments offer a variety of benefits, learners’ isolation and lack of sense of community are emerging as key pitfalls for effectiveness of such environments and therefore, deserve more thoughts and explorations in future development efforts. The main objective of this study is therefore, to examine the relationship between sense of community and learning outcome in computer supported collaborative learning environments. Learning outcome has been defined as a multiple variable consisting of pedagogical affect, student interest, and perceived learning. This paper has firstly performed an exploratory factor analysis on a sample of post graduate students in an Australian postgraduate CSCL environment. The results revealed sense of cohesion and awareness of others are two underlying constructs of sense of community. Next, the findings of this paper have shown a strong relationship between sense of cohesion and awareness of others with learning outcome variables. The paper has then discussed practical and theoretical implications of the findings. 2013-06-17T06:20:44.782Z ]]> http://www.researchonline.mq.edu.au/vital/access/manager/Repository/mq:16067 The context of online learning has been transformed by the advent of Web 2.0. While universities have just recently started to use Web 2.0 applications, these applications already exist in the students’ personal and educational world. Yet it is still not clear in what ways universities may be able to incorporate Web 2.0 applications in learning and teaching practices. This paper gives an overview of Web 2.0 applications for universities and discusses new opportunities that Web 2.0 has brought for universities. Examples of how some universities have used these applications are then outlined and categorized. The paper also discusses some of the main issues with Web 2.0 applications and provides recommendations for resolving these issues. 2012-07-26T18:08:48.550Z ]]> http://www.researchonline.mq.edu.au/vital/access/manager/Repository/mq:17905 While there have been many studies on instructional and on-task side of computer supported collaborative learning (CSCL), social and non-task side of the CSCL has received less attention. This paper observes and studies the pattern of non-task social messaging over a period of time in online Seminar rooms -designed for learning activities- as well as Coffee shops- designed for informal conversations. The objective is to firstly uncover the pattern of social interactions in the online collaborative learning environment and, secondly to understand how the level of social interactions changes over time and what factors facilitate and lead such changes. Transcript Analysis Tool (TAT) has been used to code discussions of three online classes during a 10-week postgraduate summer course in an Australian university. Findings have indicated existence of a substantial amount of non-task interactions among students. Furthermore, the results have shown a larger amount of non-task interactions occurred at the beginning and end of the semester as well as during some special occasions. Students' willingness to share personal and work-related experiences with other classmates is amongst top factors leading such trend in social interactions in the environment. 2012-03-06T02:41:09.600Z ]]> http://www.researchonline.mq.edu.au/vital/access/manager/Repository/mq:15704 With the proliferation of the WWW, providing more intelligent Websites has become a major concern in human-website interactions. Giving more intelligence to e-commerce sites is popularly recognized as one of the effective strategies that increases customer satisfaction because such websites react intelligently and can give a personalized response to each customer. Although several researches have studied usability of websites, there is a lack of quantitative methods to categorize functionality of web pages. That is important issues, because different pages have different role and understanding their roles make it more effective to enhance ease of use and usability of the website. We emphasize the ambiguity of page categorization and propose a fuzzy approach to develop a model to categorize pages as ‘target’, ‘index’, ‘exit’ and ‘start’ page. 2011-10-28T10:45:32.317Z ]]> http://www.researchonline.mq.edu.au/vital/access/manager/Repository/mq:14910 While from a technological perspective Computer Supported Collaborative Learning (CSCL) systems have been improved considerably, previous studies have shown that the social aspect of the CSCL is often neglected or assumed to happen automatically by simply creating such virtual learning environments. By distinguishing between students’ non-task social interactions from on-task interactions, and through a content analysis, this paper demonstrates that non-task interactions do occur frequently in CSCL environments. Furthermore, by conducting a self-reported survey, the present study operationalizes non-task sociability of CSCL environments and determines factors that affect them. The findings from the survey revealed that the sense of cohesion and awareness about others significantly impact the non-task sociability of CSCL. Furthermore, the study demonstrates that the perception of self-representation and perception of compatibility affect the sense of cohesion and awareness about others and indirectly contribute to the perceived non-pedagogical sociability of the environment. The findings of this paper can be used in future research for investigating the relationship between the non-task sociability of CSCL and other CSCL factors. The study also provides the CSCL lecturers and facilitators with a conceptual model by which sociability can be explicitly addressed in their course planning and delivery processes. And finally, this study develops and validates an instrument that guides required changes in current CSCL systems to improve the non-task social functionality of the environment. 2011-09-22T04:51:05.470Z ]]> http://www.researchonline.mq.edu.au/vital/access/manager/Repository/mq:11322 Published online 15 January 2010. By the proliferation of online courses, the social dimension of computer supported collaborative learning (CSCL) is becoming more important than before. Research shows that communicative behavior adaptation to the computer medium is a critical issue in CSCL social relationship development. Two dominant theories in the CSCL field, social information processing theory and adaptive structuration theory, argue that individuals do not simply receive the technology passively but they adapt their behavior to increase benefits from the technology. This paper develops an instrument in order to operationalize the notion of individual’s communicative behavior adaptability in CSCL. Through an exploratory factor analysis performed on a small sample of post graduate students of an online degree in an Australian university, three factors have been unveiled: (1) individual perception of self-representation, (2) individual perception of compatibility, and (3) individual perception of the use of computer technology. Identification of these factors is expected to facilitate understanding of individuals’ social behaviors in CSCL environment, which in turn will guide the design of CSCL systems. In addition, the paper examines the relationships between the extracted factors and four environmental factors: learner’s characteristics, course characteristics, instructor characteristics, and technology characteristics. The results show that none of these characteristics strongly affect perception of self-representation or perception of the use of computer technology. On the other hand, a strong relationship was found between perception of compatibility and learner’s and course characteristics. The reliability as well as validity of the study is examined and findings are discussed. These findings will provide further insights into the design process of CSCL systems. 2011-09-08T01:40:06.799Z ]]> http://www.researchonline.mq.edu.au/vital/access/manager/Repository/mq:11021 With the proliferation of online and distance courses human factors and social dimensions of computer supported collaborative learning (CSCL) environments are becoming more important than before. Research shows that development of a sense of community among individuals in the CSCL environments improves learning outcomes in such environments. The objective of this study is to examine the underlying dimensions of sense of community. Through an exploratory factor analysis two constructs have emerged: Individual’s sense of cohesion and awareness of others. Identification of these factors facilitates a better understanding of sense of community in CSCL environments, which in turn will guide the design of CSCL environments. In addition, the present paper examines the relationships between the facilitating factors of CSCL and the extracted factors in order to assess changes in individuals’ behavior. These factors include learner’s characteristics, course characteristics, instructor characteristics, and technical characteristics. 2010-12-21T04:11:16.599Z ]]>