A student collaborative social network was established based on computer-supported collaborative learning (CSCL) platform of EU-SUPPORT network. The EU-SUPPORT network is a sub network under the Norwegian Environmental Education Network that focuses on schools to promote the quality of education for sustainable development. Participants were two hundred of secondary school students from Malaysia and Thailand. Students taking part in this project collaboratively worked on assigned online activities with the theme 'Climate Change' via web-based instructions. The development of the social network was monitored and social interaction amongst participants was examined using social network analysis (SNA) and content analysis (CA). Self-reported survey questionnaires were administered prior and after the activities in order to investigate sustainability behaviors, self-regulated learning behaviors and learners' attitudes towards learning platform. The results indicated that the established student network was considered active with rather dense network. The discussion forum produced in the network was proven to be sustained with high average length of discussion thread. The questionnaire statistical analysis revealed that collaborative learning activities significantly increased self-regulated learning behaviors and sustainability behaviors of students participating in this social network while students showed positive attitudes towards learning environment.
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The development of advanced information and communication technologies (ICT) has led to new computer application in education such as e-mail, chat room, video conference and discussion forum. These technologies become potentially useful tools to enhance effective learning environment for students while the benefits of ICT in moderating positive effects on students' learning have also been regularly reported (Fletcher-Flinn & Gravatt, 1995).
In addition, a new concept of learning is recognized by researchers and theorists that learning is not only cognitive but also a social cultural and interpersonal constructive process (Salomon & Perkins, 1998). Hence, instructional strategies such as collaborative learning are increasingly used in educational setting in order to create interaction among students for such learning environment. In collaborative learning environment, students work together in groups, exchange ideas and share experiences in order to achieve group solutions to complex problems and, hence build up knowledge. Positive effects of collaborative learning have been well documented by researchers that it enhances students' cognitive performance and stimulates students to engage in knowledge construction (Johnson & Johnson, 1999; Slavin, 1996; Stahl, 2004).
A combination of ICT application and collaborative learning results in a new field of educational design; computer-supported collaborative learning (CSCL) which deals with issues concerning collaboration, learning processes, and the use of computer-mediated communication (CMC). The primary aim of CSCL is to provide an environment that supports collaboration between students and enhance learning processes (Kreijns, Kirschner, & Jochems, 2003), CSC usually offers tools that facilitate sharing of information and ideas, and the distribution of expertise among group members (Lipponen, Rahikainen, Lallimo, & Hakkarainen, 2003). When students collaborate in a CSCL environment, they use computer-mediated communication- CMC to communicate with group members in form of synchronous; a chat facility and video conferencing, or asynchronous; a discussion forum and e-mail.
Research in CSCL has gained considerable attention in recent years while implementing of CSCL in educational setting has been increasingly paid attention to. Research findings indicate that CSCL environments offer a medium for classroom discussion that possibly facilitates participation and social interaction among students, hence providing more effective interaction and participation than in the traditional classroom setting (Lipponen et al., 2003). Several studies have reported the benefits of CSCL in facilitating task oriented and reflective activity (Chohen & Scardamalia, 1998), complex reasoning and argumentation (Hoadley & Limn. 2000), critical thinking (Yukawa, 2006) and authentic proof activity (Ã-ner, 2008).
However, effective CSCL learning environment requires particular online learning behaviors for successful outcomes. In general, online learning environment needs more learner control and self direction as the situation represents higher level of intellectual development (Bell, 2007). In addition, providing learners with control of their own learning, it is recommended that self-regulated behaviors are essentially required (Young, 1996).
This study reports results of the investigation into CSCL setting under EU-SUPPORT network and its effect on self-regulated learning behaviors, sustainability behaviors and attitudes of students participating in the network activities. Both qualitative and quantitative techniques are used in this study. Nature of the social network is revealed by using social network analysis (SNA) and content analysis (CA) whereas learning behaviors and students' attitudes are examined through self-reported survey questionnaires.
Background of the study
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With a fast pace in several dimensions of unpredictable global issues, Decade of Education for Sustainable Development (2005-2014 DESD) scheme was proposed by the United Nation in order to create more sustainable world. The major thrusts of the agenda emphasize the role of quality education as the key solution for the sustainable future by developing public awareness about sustainability and addressing sustainable development (UNCED, 1992). Furthermore, it is recommended that along with addressing towards sustainability, rethinking beyond current practices in the community should be taken into account if sustainable future is to be achieved (UNESCO, 2005). Therefore, learning process in social network is not just about knowledge but also a suitable opportunity to nurture values and attitudes about sustainability in young learners so that they possibly develop awareness and sense of concern towards sustainable development alongside with the subject content in an effective learning environment.
EU-SUPPORT social network
EU-SUPPORT social network is a sub network under Norwegian Environmental Education Network and initially established for students to collaboratively work on network activities involving environmental issues. The ultimate goal of EU-SUPPORT aligns with ESD scheme with the aim to enhance the quality of education for sustainable development by connecting schools and research institutes as well as communities through web-based learning network (Partnership and Participation for Sustainable Tomorrow, 2008). EU-SUPPORT network focuses mainly on schools to provide enriched collaborative learning environment for students and inculcate value inherent as well as awareness towards sustainability among these young learners through well-designed activities with the theme of the 'Climate Change'.
According to socio-cultural learning approach, human activities are seen as socially mediated and learning is a matter of participation in a process of knowledge construction (Vygotsky, 1978). Lave and Wenger (1991) also claimed that learning is a process that takes place in a participation framework while knowledge is socially co-constructed through the network interaction, and distributed among learners interacting in the social network.
Participation learning metaphor is a process of participating in various and shared learning activities when learner becomes a member of a certain community (Sfrad, 1998). It is suggested that constructivist theory fits well with this learning process in online setting support with computer technologies and the internet (Thorsen, 2003). The philosophy behind constructivism is that students learn by building their own knowledge through group activities. Constructivist approach is learner-centered pedagogy which includes social construction of knowledge and context of learning collaborative activities (Weller, 2002). In addition, social constructivism is based on the key assumption that learning is the collaborative framework with meaning negotiated from various perspectives (Smith & Ragan, 1999).
Social interaction and self-regulated learning
Interaction plays a critical role in learning effectiveness of any online learning environment (Hannafin, Hill & Land, 1997). It involves an event that takes place between students and the environment in order to move them towards achieving their goals (Wagner, 1994). The social interaction among computer- supported collaborative learners can explain how learners acquire knowledge together with skills through the process by which they work together on the learning task (Wegerif, 2006). In a CSCL setting, a crucial prerequisite is the willingness of the network members to share their knowledge and information (Kimmerle &Cress, 2008) so that social interaction can possibly be initiated.
However, in order to get engaged in network activities for effective learning in CSCL situation, it is important that students are intuitively able to control their own paces of learning. Unlike traditional learning, CSCL is considered a highly learner-centered and self regulated learning environment where learners must take responsibility for what and how to learn due to the nature of online setting (Lee, 2002). High demand of self regulated learning is required in online learning environment (Mayer & Mereno, 2002) and learners are obligated to independently manage their own learning in accordance with their goals. In order to cope with this demand, learners basically develop self regulatory skills by applying meta-cognitive strategies to monitor and regulate the learning process (Pintrich, 2004). Self regulatory skills appear to derive from learning environment factors and has been found to be influential on students' success in computer mediated communication (Barnard, Paton & Lan, 2008).
Computer-Support collaborative learning- CSCL
CSCL aims to provide students with an environment that supports and enhances collaboration, in order to facilitate their learning processes (Kreijns et al., 2003). Empirical studies have demonstrated the effects of CSCL on students' learning while the perceived potential of CSCL has been supported (Lou, Abrami, & Apollonia, 2001; Cavanaugh, 2001). CSCL environment includes multiple collaborative models of learning based on socio-constructivist perspectives to assist the construction of knowledge acquisition through interaction of learners with the support of software tools (Salovaara & Järvelä, 2003). CSCL can also be combined with activities that engage learners in participating and interacting with others. This learning approach not only helps learners in their own learning process, but also helps the group in the collaborative process.
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The possibilities for CSCL in supporting learning interaction were established by Linn, Bell, & Hsi, (1998). Similarly, Cohen and Scardamalia (1998) reported findings that demonstrated how CSCL enhanced social knowledge construction and created a more solid basis for reflective activity compared to face-to-face interaction with an indication of the positive influence on student motivation. In addition, studies conducted by Rahikainen, Järvelä and Salovaara (2000) also show how CSCL can restructure the motivational interpretations of non-task-oriented students and contribute to their task engagement.
Research on learning has demonstrated the usefulness of collaboration for improving student's problem-solving skills. When learning in a collaborative setting, students are encouraged to work together, share ideas and their reasoning, ask questions, explain and justify their opinions, elaborate and reflect upon their knowledge (Soller 2001). All of these activities increase students' responsibility for their own learning and open up new ways of solving or examining problems. These benefits, however, are only achieved by active and well-functioning learning teams (Oshima, Oshima & Murayama et al., 2006).
Measuring CSCL learning process
It is claimed that while CSCL has gained an intensive interest in research and design of learning environments, the effective process of collaboration is worth recognized (Strijbos, Kirschner, & Martens, 2004). Research on collaborative learning supported by the use of technology increasingly focuses on understanding collaborative process rather than the learning outcomes (Rumel & Spada, 2004). However, empirical research has shown that there is no guarantee that the networked collaboration leads to successful learning (Järvelä & Häkkinen, 2002). Despite the popularity of forums and networks, teachers have come to the realization that putting students together does not mean they will engage in collaborative inquiry and deep discourse (Kreijns et al., 2003). Therefore, it is crucial that learning process occurs during collaboration is monitored and investigated so that the effectiveness of learning can be possibly promoted. Apparently, as it is claimed that no single method is sufficient to unravel all aspects of a collaborative process (Rumel & Spada, 2004), different methodological approaches have been adopted for analyzing collaborative processes in technology-support learning setting.
The application of CSCL approach to authentic learning scenarios demands particular techniques to analyze and assess the learning processes. It is argued that traditional method usually focuses on examining characteristic of the individual rather than assessing participatory processes in learning. Therefore, it is recommended that completely new methods are needed in order to assess the role of participatory processes in learning (Palonen & Hakkarainen, 2000). Although there is an active line of research in computer-assist communication, there is a lack of tools to support teachers in the regulation and assessment of students' collaborative activities (Dimitracopoulou, 2005).
A mixed evaluation method with the combination of different sources of data and analysis approach is recommended in CSCL (Martínez et al. 2003). This approach involves opportunistic selection of qualitative and quantitative data collecting and analysis techniques in order to achieve the desired evaluation goals. The mixed method seems to be the solution in order to face the demands posed by CSCL to the evaluation of participatory aspects of learning. However, it is important to adapt the data collection and analysis techniques to the variety of evaluation contexts that can be encountered in CSCL (Marti'nez et al., 2006). This analysis technique has been implemented to investigate pattern of participation and interaction in CSCL learning platform by researchers in previous studies (e.g. Palonen & Hakkarainen, 2000; Lipponen, Rahikainen, Lallimo & Hakkarainen, 2003; Sing & Khine, 2006).
Social Network Analysis
Social network analysis (SNA) is an appropriate discipline for the study different forms of interaction as it focuses on the study of the interrelationships among individuals (Scott, 2000). Recently, it is found that social network analysis has been successfully applied in examining CSCL environments (Reyes & Tchounikine, 2005). The analysis generally provides the insight information of how the learning community organize themselves in the social network to achieve the certain goals (Haythornthwaite, 1996). A study carried out by Sing and Kine (2006) claimed that the technique revealed useful details regarding the organization of the network. Along the same line, it is claimed that SNA provides information about pattern and structure of interaction that would have been difficult to obtain by other means (Palonen & Hakkarainen, 2000). In addition, using SNA in the combination with qualitative content analysis appeared to be appropriate for studying the participation and interaction processes that take place in the CSCL environment. SNA generally brought out interesting interaction and participation structure that could be further analyzed with qualitative content analysis (Lipponen et al., 2003)
Despite the different content analysis schemes that reflect the diversity in theoretical base such as the information about validity and reliability and the choice for the unit of analysis, an important step in content analysis is the development of categories and indicators that researchers can use to analyze the transcripts (Wever, Schellens,Valcke, & Keer, 2006). Compared with other methods, content analysis is widely used to analyze and assess the collaborative process with assistance of tools in CSCL.
Gunawardena et al. (1997) purposed a content analysis model based on a constructivist paradigm designed to detect evidence of knowledge construction in online forum. Their interaction analysis model (IAM) was developed in an attempt to further understand and describe the processes of negotiating meaning and knowledge co-construction in a collaborative online discussion environment. The transcripts of a online debate was used to develop a model that posits five phases in which learners must move through as knowledge is being constructed; 1) sharing, comparing of information, 2) discovery of dissonance, 3) negotiation of meaning and co-construction of knowledge, 4) testing and modification of proposed synthesis and 5) agreement/ application of newly constructed meaning.
The participants and setting
Two hundred students from secondary schools in Thailand and Malaysia took part as distributed learners in this network through collaborative web-based project along with other network members from schools around the globe. The main activity of the project was the International Campaign of CO2 on the way to school. The resources and instructions of project activities were available on the website of co2connect and communication among participants was facilitated through web-based instruction under EU-SUPPORT network system. While students are engaged in learning activities, the development of social network is monitored through participation and interaction among participants. Data stored in log files of the server database system was later retrieved to use for data analysis.
Procedure and task
Schools participating in the project were required to sign up for membership of the network on the website: http:///www.co2nnect.org which was established under EU-SUPPORT program. Students taking part in the co2connect campaign were allowed to login and enter information of how they travelled to school and the distance on co2connect website. The amount of CO2 was automatically computed and available for students to view. Data from all locations of schools that had taken part in this project was pooled, shared compared along with collaborative activities regarding the obtained information. Discussion forum for climate ideas was initially established to exchange ideas among participants for possible solutions, based on local context.
During the co2connect campaign, students were encouraged to carry out other related project activities concerning reducing the amount of CO2 both in classes and between schools. The outcomes of project activities were uploaded to share for constructive comments. Basically, climate ideas posted in discussion forum represented of groups' ideas. The campaign lasted for two weeks then related activities were continually carried on for another four weeks. Prior to the beginning of the campaign students were asked to complete self regulated learning behavior questionnaires and sustainability behavior questionnaires. These questionnaires were also distributed along with students' attitude questionnaires by the end of network co2connect campaign activities.
Measure and data analysis
Interaction occurs during the communication phase was examined in order to explain nature of the network. Pattern of the participation in the social network was represented in terms of the amount of discussion and frequency of participation. In order to examine if the discussion was sustained, quality of discussion is determined by the average length of discussion thread. Communication messages were categorized into groups and the average discussion thread was calculated. Data collected from log files was used to quantitatively support the social network analysis of network density.
Three self-reported survey questionnaires; self-regulatory learning questionnaires, sustainability questionnaires and students' attitudes questionnaires with 5-points Likert scale were used to examine learning behaviors and students' attitudes. Self-regulated learning questionnaires consisted of 23 items in six dimensions, adapted from previous study of Barnard et al. (2008) with internal consistency reliability of Cronbach Î± 0.90. Sustainability behavior questionnaires were 10 items, adapted from Cuthill's (1998) study with Cronbach Î± of 0.80. Students' attitude questionnaires consisted of 23 items in four dimensions adapted from the studies of Tseng, Chiang, & Hsu, (2008), Liaw et al. (2007) and Barnard et al. (2007) with Cronbach Î± 0.93. Pretest and posttest results from self-regulated learning, sustainability behavior questionnaires and the posttest of students' attitude questionnaires were quantitatively analyzed using SPSS version 16 software.
Data obtained from server database; the number of notes posted, out degree of each participant including number of words were used as indicators to examine the extent of participation. There were 79 schools considered active participants in this social network and the total number of notes posted was 217 notes in six weeks. The number of average notes per week was 39.17 notes. Total number of words found in the discussion forum was 10,644 words and average number of words per note is 49.05. On average each participant posted 2.75 notes whereas the highest number of posting by a participant was 17 notes. Average percentage of out degree contributed in discussion forum by each participant was 1.30.
Quality of discussion
The quality of discussion was examined by the average length of discussion thread to gain more information regarding the depth of discussion. The average length of thread implies number of responses according to every posted note. The higher number average length of thread indicates the more responses to the posted note, hence the discussion is likely to be sustained (Lipponen et al., 2003). Messages from posting were categorized in to 9 clusters. The category of coding was not predetermined and the unit of analysis for coding used in this study was a posted message. The average length of thread was calculated from the total number of notes divided by the total number of cluster (Sing &Khine, 2006). The mean note cluster size in this study was 24.11.
The results from paired sample t-test of SPSS analysis show that posttest mean score of self- regulated learning behaviors is significantly higher than pretest mean score t(199)=17.40, p<0.05 with the mean score of pretest and posttest of 3.35 (SD=0.51) and 3.74 (SD=0.42) respectively (Table 1). The mean scores in six dimensions of self regulated learning behaviors are shown in Table 2. Further t-test analysis for each dimension was carried out to ensure the difference. It is found that there is a statistically significant increase of mean scores in all dimensions; Goal setting t(199)=15.27, p<0.05, Environmental structuring t(199)=12.92, p<0.05, Task strategies t(199)=16.22, p<0.05, Time management t(199)=12.65, p<0.05, Help seeking t(199)=13.69, p<0.05 and Self evaluation t(199)=12.34, p<0.05.
Similarly, the results from SPSS paired-sample t-test analysis indicate that posttest mean score of sustainability behaviors is significantly higher than pretest t(199)=5.29, p<0.05. The mean score of sustainability behaviors on pretest and posttest is 3.09 (SD=0.66) and 3.36 (SD=0.51) respectively (Table 3).
The results of students' attitudes survey in four dimensions are shown in Table 4. Over all mean score of students' attitudes from both studied group, Thailand and Malaysia are 3.60 (SD=0.45) and 3.54 (SD=0.21) respectively. The results from independent sample t-test analysis shows that there is no statistically difference between mean score of students' attitude between the two groups t(198)=0.86, p>0.05. Independent sample t-test analysis of the four dimensions also shows that there is no significant difference in the mean score of students' attitudes in Learning platform t(198)=0.17, p>0.05, Communication and collaboration t(198)=0.13, p>0.05 and Learning environment t(198)=0.73, p>0.05. However, there is a significant difference in Interaction t(198)=1.98, p<0.05.
Interaction among participants in this social network can be explained through the obtained results of network density. A study conducted by Lipponen et al. (2003) considered that the density of 0.39 of 12 participants as high whereas another study with a group of 28 students yielded in the density of 0.28 (Palonen & Hakkarainen, 2000). It is suggested that network density tends to be higher in the smaller network as participants are easier to be connected (Lipponen et al., 2003). Provided that EU-SUPPORT is large network, the density of 0.31 is considered to be rather high. Consequently, interaction in this student collaborative social network under EU-SUPPORT appears to be active. Although the suitable density of the network for effective collaboration has not been clearly established, the higher range of density is preferred as it indicates more connections between participants in the network and hence encouraging collaborative learning process.
The interaction between students in the network is a result from participation that is contributed to discussion forum. Participation in this network is likely to be even as each participant posted at least one message. Average notes created per week of 39.17 is rather high compared to the study of Sing and Khine (2006) that indicates the average number of notes produced per week is 25.6. They considered that participation rate is relatively high. Low participation rate less than one note to a note per week has previously been reported (Schellen & Valcke, 2005; Guzdial & Turns, 2000). Despite the low average percentage of out degree from each participant, this network can be seen as active participation. However, to indicate central participant in the network is beyond the scope of this study.
Quality of discussion was examined by the length of discussion thread in order to ensure that the discussion was sustained. The mean of discussion thread in this study is 24.11, which means there were around 24 responses to a posted note. The number is rather high compared to the study of Sing and Khine (2006) that is 3.47 of notes per cluster. However, Guzdial & Turns (2000) reported a maximum of 56.3 notes with the discussion anchored around examination and homework. It is possible that the length of discussion thread is partially related to particular tasks or activities provided in the network that motivate students to communicate more regarding their interest. The activities in this network are purposive with well designed features for a particular group of learning with focused area of discussion. As a result, the discussion forum of this social network is apparently sustained.
Results of learning behaviors imply that collaborative learning environment in this social network supported by computer network system has positive influence on self-regulated learning and sustainability behaviors of students participating in network activities. SRL is initially developed as interaction of personal, behavioral and environmental factors (Zimmerman & Schunk, 2001) and usually occurs when students are motivated to strategically engaged in learning activities within environments that foster self-regulation (Patrick & Middleton, 2002). Learning process in this social network is, therefore assumed to provide enriched environment for students to reinforce self-regulatory skills while engaging in the collaborative learning activities. As SRL is associated with academic achievement (Barnard et al., 2008), it is possible to claim that students who have reflectively developed SRL skills are likely to be more successful in learning. However, further researches are required to investigate into this aspect.
Unlike SRL, sustainability behaviors are basically rooted in values and attitudes and later transfer into action (Mio et al., 2003). This study shows that learning activities with local and global context such as 'Climate change' resulted in creating awareness about environmental problem among these participants. However, a study on the survey conducted in first year students indicated that although students were concerned about environmental issues, their concern did not always transfer into action (Cuthills, 1998). Sustainability behaviors should, therefore be initiated at early stage of education i.e. in schools with effective learning setting. Moreover, developing and transferring of these preferable behaviors into actual habits deserve attention for further studies so that it is possible that sustainability behaviors in learners are substantially determined.
Apparently, students from studied groups perceive CSCL learning platform in the social network similarly with positive effect though not in all dimensions. Over all mean score of students' attitudes web-based problem based learning platform in a study conducted by Tseng et al. (2008) is 3.89. Generally students' attitudes obtained from students participating in learning activities in this study, is considered satisfying. There is an evidence indicates that students' attitudes toward online course is associated with self-regulated learning (Barnards et al., 2007). In addition, a study of Karoly (1993) demonstrates that students who are highly self-regulated tend to engage in their learning more, perform better, compared to those who are less self-regulated and hence have positive attitudes.
Another reason that possibly leads to positive effect students' attitudes in this study is due to the features of friendly human-computer interface and well-established network system with actively updated information. These features of the webpage are in accordance with TAM-Technology Accepted Model and hence cause perceive of usefulness among users (Davis, Bagozzi & Warsaw, 1089). Besides, the activities that are practically realistic and related to current issue i.e. global warming also result in encouraging students to actively participate and collaborate in the network.
In summary, the investigation into student social network under EU-SUPPORT provides initial information about nature of the network and its effect on learning behaviors and students' attitudes in some extent. Although the learning process in this network is apparently group collaboration as a whole, the effectiveness of collaborative process resulted from enriched learning environment is apparently observed in an individual through learning behaviors and attitudes. Further studies are essential to reveal more about the effect of social interaction in other aspects in order that the effectiveness of learning process in CSCL environment is possibly established.