5.08 Segment 2 Collaboration Assignment

Our analysis shows that the participating students were very busy regulating task performance. Especially planning the task and monitoring task progress were activities performed often by the students. This high level of regulatory behavior is not surprising given the complexity and size of the inquiry tasks used in the three studies. In all three studies, students worked on a complex inquiry task lasting for eight 50-minute lessons. To be able to complete this task, students needed to plan the task and monitor task progress carefully (Van der Meijden and Veenman 2005).

We also found that group members devoted large parts of the communication to social activities, of which a large part was reserved for reaching and maintaining shared understanding. This means that during the online collaboration, students were actively trying to shape the grounding process by tuning to the other group members, signaling agreement, or acknowledging understanding. Furthermore, social activities such as joking and comforting group members also occurred relatively frequently. This shows that the groups involved in the three studies paid considerable attention to creating a positive group climate and a sound social space (Kreijns et al. 2003). On the other hand, the high percentage of communication devoted to the grounding process also highlights the difficulties students sometimes face when communicating electronically (Walther 1992).

The other two main activities occurred less frequently. A relatively small part of the communication between group members was coded as exchange of task-related information or asking for task-related information. Moreover, an even smaller part of the communication was aimed at regulating the group process. This is surprising, because research has shown that task-related activities are important for group problem solving (Jehn and Shah 1997). Furthermore, several authors have speculated that regulation of the group process is also important for successful online collaboration (e.g., Manlove et al. 2006). Both activities did however not feature prominently in the collaborative process of the groups involved in this study.

Exploratory factor analysis of the coded data identified four broad categories of collaborative activities. These four categories are discussion of information, regulation of task-related activities, regulation of social activities, and social activities.

These four main categories were then used in a multiple regression analysis to predict group performance. Our analysis shows that discussing information did not predict group performance. This is surprising, because critical and exploratory discussions have been shown to be important for effective collaboration (Wegerif et al. 1999). This hypothesis is not confirmed by this study however.

We also found that regulation of task-related activities did not positively affect group performance. Again, the literature suggests that regulating the task is important for successful collaboration (De Jong et al. 2005), whereas this hypothesis cannot be confirmed by this study. Perhaps the large amount of task regulation displayed by the groups is an indication the inquiry tasks were too complex for them. During complex inquiry tasks, students’ working memory may be overloaded, thereby negatively affecting their performance (Kirschner et al. 2006). The large amount of task regulation found in the protocols may be a sign that this was the case for some of the groups in our study.

In the introduction of this article we stated that group members do not only need to regulate their task-related activities, but that the group process should be regulated as well. This hypothesis was confirmed by the significantly positive effect of regulation of social activities on group performance. This indicates that when group members pay attention to the planning, monitoring, and evaluation of the collaboration, they perform better on their task. This is in line with previous research on face-to-face collaboration (e.g., Yager et al. 1986).

This finding also sheds more light on findings from recent research from a cognitive load perspective. From such a perspective, the inter-individual coordination that is required for successful coordination, can be considered extraneous cognitive load (Kirschner et al. 2009). That is, coordinating and regulating the collaborative process places an additional burden on students which may overload their working memory resulting in less than optimal learning performance. In this respect, these coordinating and regulating activities are sometimes referred to as transaction costs (Ciborra and Olson 1988). On the other hand, it might be argued that collaboration also facilitates processes that are germane to learning and performance (i.e., processes that facilitate group members’ learning process such as giving detailed explanations or engaging in constructive argumentation). Furthermore, collaboration also allows students to pool their information resources, thereby decreasing the burden placed on their working memory. Whether collaboration will be effective and efficient therefore depends on the interplay between the benefits of collaboration (i.e., ability to pool resources and stimulating learning processes) and the costs of collaboration (i.e., transaction costs). This study shows that although regulation of social activities might be considered detrimental for learning and performance, this was not the case for the groups involved in our research. In contrast, when groups devoted more energy to regulating the collaboration, they performed better. It seems therefore that a minimum amount of regulation of social activities is a prerequisite for successful group performance.

Finally, a negative relationship between social activities and group performance was found. On the one hand this is surprising because a positive group climate is important for collaboration. In a positive climate for example, trust develops more quickly between group members. This trust in turn, helps group members to perform more effectively (Wilson et al. 2006). On the other hand, it might be hypothesized that group members can be too socially active during their collaboration. As illustrated by the collaboration episode shown in Table 7, social interaction may also distract from the goal of the collaboration: finishing the group product. This may explain the negative effect of social activities on group performance. Furthermore, in many studies the activities we consider to be social activities are considered to be off-task activities which are usually considered to be deleterious for learning and perfomance (Chiu 2004; Klein and Schnackenberg 2000).

In sum, this study yielded several unexpected results that warrant further discussion. Especially the lack of a significant relationship between information discussion and regulation of task-related activities on the one hand and group performance on the other hand, deserves further attention. In this study we did not, for example, investigate the role of the teacher. As described above, teachers could follow the progress of their groups and comment on this. Furthermore, teachers could also follow the discussions of their groups and post messages in their discussions. Teachers could have used this function to give task-related information or answer task-related questions. This may explain the relatively low frequencies we found for these collaborative activities and it may also (partly) explain why these activities did not predict group performance. Also, the teacher could also communicate with students about deadlines, strategies, and task progress and thus also affect how group members regulate the task. Clearly, the role of the teacher in CSCL environments could be investigated further (Casamayor et al. 2009).

It should also be noted that way we calculated group performance (i.e., expressing group performance as the proportion of the total amount of points earned divided by the total amount of points that could be earned), might have affected our results. This way, we assigned equal weight to all parts of the inquiry tasks. Another option would have been to assign weights to the different parts of the tasks, for example based on their complexity or the time students were expected to work on them. To facilitate interpretation of our results we did not chose for this latter option, but this may have caused unintended artifacts. That is, when a different algorithm to calculate group performance was used, other results might have been found.

Another limitation of this study lies within the fact that we did not consider how collaborative activities develop over time. It might be expected for example, that in the beginning of the collaboration students focus on social activities (e.g., to develop trust and group cohesion) and that later on they start engaging in task-related activities and start paying attention to regulation of task-related and social activities (Tuckman 1965). Clearly, an analysis that takes time into account might shed more light on how these processes develop. Furthermore, the structure and nature of the task may also have affected the results and the development of collaborative activities. During all three studies, students we are asked first to explore the environment and chat with their group members, and then the tasks required them to read and discuss information sources, before finally using these information sources to write a report or essay. This sequence of activities may also have affected students’ collaboration. For example, because studying information sources was a central activity only during the beginning of the task, this might explain why we only found low amounts of task-related activities and why we did not find an effect of task-related activities on group performance.

Because of the nature of this study, we are only able to show correlations (or absence of correlation) between collaboration and group performance, no cause-effect relationships. This leaves the question what comes first—collaboration or performance—unanswered. It might be the case that groups consisting of high ability students are aware of the effectiveness of regulating the collaboration, and thus choose to perform these activities consciously. Future research should also examine in more detail the relationship between collaboration and group performance taking into account the possible effects of group composition (i.e., group composition with respect to ability). Also, in this study, a negative effect of social activities on group performance was found. However, it might be the case that this relationship is different for groups of familiar students than for groups who have no shared history (Janssen et al. 2009). For example, in familiar groups the need for social interaction might be smaller, because these groups already have established group norms. On the other hand, these groups might be more inclined to engage in social interaction (Smolensky et al. 1990). Another aspect that could be investigated in this respect is group composition with respect to ability. Do groups composed of high-ability students engage in different collaborative activities than low-ability groups? And does this affect group performance differently for high- and low-ability groups? Clearly, there is a need to examine more closely how different factors, on the individual and group level, affect the relationship between the regulation of the collaboration process and group performance.

Тогда, при чтении сверху вниз, перед глазами магически возникало тайное послание. С течением времени этот метод преобразования текста был взят на вооружение многими другими и модифицирован, с тем чтобы его труднее было прочитать. Кульминация развития докомпьютерного шифрования пришлась на время Второй мировой войны. Нацисты сконструировали потрясающую шифровальную машину, которую назвали «Энигма».

Она была похожа на самую обычную старомодную пишущую машинку с медными взаимосвязанными роторами, вращавшимися сложным образом и превращавшими открытый текст в запутанный набор на первый взгляд бессмысленных групп знаков.


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