Structuring and Regulating Collaborative Learning in Higher ...

Järvelä, S., Näykki, P., Laru, J., & Luokkanen., T. (2007). Structuring and Regulating Collaborative Learning in Higher Education with Wireless Networks and Mobile Tools. Educational Technology & Society, 10 (4), 71-79.

Structuring and Regulating Collaborative Learning in Higher Education with Wireless Networks and Mobile Tools Sanna Järvelä, Piia Näykki, Jari Laru and Tiina Luokkanen University of Oulu, Finland // [email protected] // Fax +358 8 553 3744 ABSTRACT In our recent research we have explored possibilities to scaffold collaborative learning in higher education with wireless networks and mobile tools. The pedagogical ideas are grounded on concepts of collaborative learning, including the socially shared origin of cognition, as well as self-regulated learning theory. This paper presents our three design experiments on mobile, handheld supported collaborative learning. All experiments are aimed at investigating novel ways to structure and regulate individual and collaborative learning with smartphones. In the first study a Mobile Lecture Interaction tool (M.L.I.) was used to facilitate higher education students’ self-regulated learning in university lectures. In the second study smartphones were used as regulation tools to scaffold collaboration by supporting externalization of knowledge representations in individual and collaborative levels. The third study demonstrates how face to face and social software integrated collaborative learning supported with smartphones can be used for facilitating socially shared collaboration and community building. In conclusion, it is stressed that there is a need to place students in various situations in which they can engage in effortful interactions in order to build a shared understanding. Wireless networks and mobile tools will provide multiple opportunities for bridging different contents and contexts as well as virtual and face to face learning interactions in higher education.

Keywords Collaborative learning, Higher education, Mobile tools, Self-regulated learning, Wireless networks

Introduction Recent developments in mobile technologies have contributed to the potential to support learners studying a variety of subjects (Scanlon, Jones & Waycott, 2005; Sharples, 2000) in elementary education (Zurita & Nussbaum, 2007) as well as in higher education (Baggetun & Wasson, 2006; Näykki & Järvelä, 2007; Milrad & Jackson, in press). Furthermore, there have also been efforts to improve the performance of knowledge workers in work-place settings (Brodt & Verburg, 2007). The integration of social software (web2.0) (Kolbitsch & Maurer, 2006; Cress & Kimmerle, 2007) and new mobile technologies (Kurti, Milrad & Spikol, 2007) has created interesting new possibilities for organizing novel learning and working situations. In higher education much effort has been made to find new ways to support individual student learning, but also to find ways for effective collaboration. Previous studies have explored how mobile technology can be used for offering an additional channel for the lecture interaction. The Classtalk project focused on giving lecturers the ability to pose questions to students (Dufresne, Gerace, Leonard, Mestre, & Wenk, 1996) while the eClass project provided facilities for structured capture and access of classroom lecture activities (Abowd, 1999). Ratto, Shapiro, Truong and Grisworld (2003) developed the ActiveClass application for encouraging lecture participation by using personal wireless devices. Furthermore, in order to support collaborative learning, new possibilities of mobile technologies have been explored. Interactive logbook (Chan, Corlet, Sharples, Ting & Westmanncott, 2005) provided the technology for knowledge sharing and multimedia notetaking, while many campus-wide laptop initiatives have provided students with access to social computing tools, such as instant messaging or chat (Gay, Stefanone, GraceMartin, Hembrooke, 2001). Overall, the general claim has been that when new technologies and software have been used in an educational setting, new learning opportunities have arisen. Thus far there have been plenty of case studies and design experiments where mobile technologies have been used for innovative pedagogical ideas and design studies. However, only a few studies give detailed arguments as to what are these new opportunities in terms of learning interaction and collaboration and what are the exact processes that mobile tools can scaffold. We claim that it is not only the learner being “mobile” that matters. A stronger argument for applying mobile tools for education is that of increasing students’ opportunities for interactions and sharing ideas and thus, increasing opportunities for an active mind in multiple contexts (Dillenbourg, Järvelä, & Fischer, in press). In this paper we describe our current research focusing on exploring possibilities to scaffold collaborative learning in higher education with wireless networks and mobile tools. The pedagogical ideas are grounded on collaborative learning, including the socially shared origin of ISSN 1436-4522 (online) and 1176-3647 (print). © International Forum of Educational Technology & Society (IFETS). The authors and the forum jointly retain the copyright of the articles. Permission to make digital or hard copies of part or all 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 the full citation on the first page. Copyrights for components of this work owned by others than IFETS must be honoured. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from the editors at [email protected].

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cognition as well as self-regulated learning theory. This is to say that special effort has been put on enhancing and scaffolding collaborative learning as cognitive, social, and motivated activity.

Structuring and regulating collaborative learning Earlier research on collaborative learning has pointed out that shared understanding is not easy to achieve (Häkkinen & Järvelä, 2006; Leinonen, Järvelä & Häkkinen, 2005), and that students face difficulties engaging in learning and achieving their learning goals in a variety of learning contexts, including technology supported learning environments (Volet & Järvelä, 2001). In order to favour the emergence of productive interactions and to improve the quality of learning, different pedagogical models and technology-based regulation tools have been developed to support collaboration between participants. One way to enhance the process of collaboration, as well as to integrate individual and group-level perspectives of learning, is to structure learners’ actions with the aid of scaffolding or scripted cooperation (Fischer, Kollar, Mandl, & Haake, 2007). One of the ideas in this field is to design scripts that can be defined as “a set of instructions prescribing how students should perform in groups, how they should interact and collaborate and how they should solve the problem” (Dillenbourg, 2002, p. 63), that can be modified according to what kind of interaction, learning or outcomes are expected to be achieved. In scripted collaboration participants are supposed to follow prescriptions and engage in learning tasks. In addition to scripting as a mechanism to structure collaboration, we suggest that structuring can be enriched with technology-based regulation tools, which offer an individual and a group of learners opportunities to self-regulate their collaborative learning processes. Self-regulated learning theory concerns how learners develop learning skills and use learning skills effectively (Boekaerts, Pintrich & Zeidner, 2000). Self-regulated learners take charge of their own learning by choosing and setting goals, using individual strategies in order to monitor, regulate and control the different aspects influencing the learning process and evaluating his or her actions. Eventually, they become less dependent on others and on the contextual features in a learning situation. Although research into self-regulation has traditionally focussed on the individual perspective, there is increasing interest in considering the mental activities that are part of self-regulated learning at the social level, with reference to concepts such as social regulation, coregulation and shared regulation (McCaslin, 2004). Järvelä, Volet & Järvenoja (2005) characterize self-regulated learning from three perspectives. Self-regulated learning focuses on an individual as a regulator of a behavior and refers to the process of becoming a strategic learner by regulating their cognition, motivation and behavior to optimize learning (Schunk & Zimmerman, 1994). Conceptualizing self-regulated learning as a co-regulation has been influenced by socio-cultural theory and it emphasizes gradual appropriation of sharing common problems and tasks through interpersonal interaction (Hadwin, Wosney & Pontin, 2005; McCaslin & Hickey, 2001). The third perspective looks at how the regulation process can be framed to shared cognition and recent research on collaborative learning, which is in essence the co-construction of shared understanding (Roschelle & Teasley, 1995). This is collective regulation, where groups develop shared awareness of goals, progress, and tasks toward co-constructed regulatory processes, thereby sharing regulation processes as collective processes. Self-regulated learning theory has been used in our studies as a theoretical framework to develop those learning activities that give potential to individual and collaborative learning so that it stimulates active minds and interactions on individual and social levels. There are not yet studies which use mobile technology for supporting self-regulated learning, but recently there have been specific efforts made by people working on self-regulated learning theory to find ways to design technology to assist in helping students develop better learning strategies and regulate their learning process (e.g. Winne et al., 2006). Previous studies have explored how visualization as a form of regulation tool can be used for supporting individuals’ understanding (Larkin & Simon, 1987) or awareness of each others ideas (Fisher, Bruun, Gräsel, & Mandl, 2002; Leinonen & Järvelä, 2006). Visualizing individuals’ understanding can create for a group of learners a shared reference point, which supports focusing on central issues, for example shared or non-shared knowledge in a group’s interaction (Pea, 1994). Opportunities have been also searched from computer-based regulation tools, which aim to promote cognitive regulation processes. Learning tools are to promote motivated learning from the point of view of the individual learner as well as in opening new learning opportunities for social and interactive learning (Azevedo, 2005). This developmental work can be used for compensating weak study and collaboration skills in different 72

interactive learning environments, and studying in different domains. Azevedo and his colleagues (Azevedo, Guthrie & Seibert, 2004) have investigated the effects of goal-setting conditions on the ability of learners to regulate their learning in hypermedia environment. Their research results show that students use various types of self-regulatory behavior in learning with hypermedia, such as planning, monitoring, strategy use, task difficulty and demands and interest statements, but that students differ in their ability to regulate their learning. Later studies have put effort into designing computer-based scaffolds for self-regulated learning (Azevedo & Hadwin, 2005). For example, in a study that focused on collaborative planning and monitoring of students working within an online scientific inquiry learning environment, Manlove, Lazonder and de Jong (2006) examined the effect of a tool designed to support planning and monitoring in a scientific inquiry into the fluid dynamics on students’ model quality. The results showed a significant correlation between planning and model quality, indicating an overall positive effect for the support tool.

Three studies of using wireless network and mobile tools in higher education In this paper our three design experiments on mobile, handheld supported collaborative learning are presented in order to demonstrate different pedagogical models and levels of scaffolds for socially-shared learning. Each experiment is aimed at investigating novel uses to structure and regulate collaborative learning with mobile tools.

Mobile lecture interaction tool for activating students’ participation to the lecture interaction The aim of this study was to explore how the Mobile Lecture Interaction tool (M.L.I.) can be used for regulating and supporting students’ thinking and participation in the lecture interaction. It was studied how higher education students used the M.L.I. tool during lectures and in what ways the students view the M.L.I. tool as a support for their learning. Participating in the study were 173 higher education students (114 male and 59 female). The data were collected as a part of the authentic lecture situations in nine lectures where five lectures were in economics studies, two lectures in technical studies and two lectures in educational psychology studies. The lecture interaction was supported with the M.L.I.-tool, which was developed for this experiment (©Costa, 2006). The basic idea of the M.L.I.-tool is as follows: using personal, mobile devices (smartphones), students can anonymously ask questions, answer polls, and give feedback during the lecture (See Table 1). The tool allows every student and the lecturer to see these lists of questions. Furthermore, students have a possibility to vote on presented questions. Voting raises questions ranking in the display, encouraging the lecturer to give those questions precedence. Table 1. The M.L.I Pedagogical Structure Description of activities in the Lecture Pedagogical idea Encourage students’ cognitive activity and self-regulation Send a question in the lecture, engage students to the learning in the lecture Send a comment Enhance reflection Enhance students’ metacognition and engage students’ Vote for a question or comment learning in the lecture The data were collected via a questionnaire (including likert-scale questions as well as open ended questions), group interviews, lecture observations and log files. The process-oriented data, in a form of observation and log files, were collected in order to explore how students use M.L.I. tools as a part of their lecture interaction, e.g. what kind of questions or comments students present. The questionnaire and the interview data were collected to explore how students reflect the use of the M.L.I. tool. The results show that the students used the M.L.I. tool mostly for voting. The students reported that with the M.L.I. tool they were more active in thinking of questions and evaluating the presented questions’ meaning for themselves than they normally are during the lectures. Furthermore, the use of the M.L.I. tool supported students’ feelings of belonging to a group. The students mentioned that the use of the M.L.I tool supported their engagement in the content of the lecture. Their concentration did not stray as much as it did in lectures. Awareness of other students’ questions offered new ideas for the students and therefore that was seen as valuable for their learning. 73

Mobile mind map tool for stimulating collaborative knowledge construction in groups The aim of this study was to investigate the process of collaborative knowledge construction when technology and self-generated pictorial knowledge representations are used for visualizing individual and group shared ideas (See Näykki & Järvelä, 2007). In particular, the aim was to find out how students contribute to the group’s co-regulation of collaborative knowledge construction and use each other’s ideas and cognitive tools as a provision for their jointly evolving cognitive systems. The participants of this study were teacher education students (N = 13, 5 male, 8 female) who were randomly assigned to work in groups. Their working was scaffolded with the Mobile Mind Map tool (© Scheible, 2005, see Figure 1.), and a problem-oriented pedagogical structure. Student activities were structured around different phases in which they brainstormed, explored real-life examples to visualize their thinking, and used pictures as knowledge representations to answer to the learning task. The Mobile Mind Map tool allowed students to take pictures with a smart phone and to add text annotations to the pictures. The annotated pictures were sent to the server and they were used to construct a mind map with the computer (See Table 2). Table 2. “The Mobile mind map” pedagogical structure Description of group activities 1. Mind mapping with paper and pen 2. Campus area exploration for evidence with mobile phones 3. Mind mapping with Mind Map Tool and pictures by the laptop computer 4. Reflection on the experience

Pedagogical idea Grounding

Outcome Mind map with paper & pen

Inquiring

Annotated pictures

Constructing

Mind map with pictures

Reflecting

Shared experiences

Figure 1. The Mind map tool The process-oriented data involved students’ videotaped face-to-face group activities (mind-mapping with paper and pen and mind-mapping with a Mobile Mind Map tool and pictorial knowledge representations) as well as stimulated 74

recall interviews (Ericsson & Simon, 1980). The data-driven qualitative content analysis revealed that pictures as self-generated knowledge representations were used for carrying individuals’ abstract meanings. Furthermore, students’ activity in processing each others ideas further, as well as a level of cognitively challenging activities, indicates that pictorial knowledge representations and technology tools scaffolded co-regulation of collaborative knowledge construction. However, students were of the opinion that pictorial knowledge representations are challenging and thorough negotiation is needed for grounding pictures on the content discussions.

Mobile “Edufeeds” for creating shared understanding among virtual learning communities The aim of this study was to explore how mobile technologies and social software (weblogs, wikis, RSS-aggregators and file-sharing services) can be used for scaffolding collaborative learning; sharing understanding and building virtual communities (See Näykki & Järvelä, 2007). The main assumption was that students’ interactions will be enriched when possibilities of social software are integrated in the learning situations, and thus, building virtual communities will be more fluent than in more traditional virtual learning environments. The participants of this study (N = 22, 5 male and 17 female) worked in groups of 4-5 students for a period of three months. Group work was structured to different phases, which were facilitated with social software (weblog, wikis and RSS-aggregators) as well as mobile phones and lap top computers (See Table 3). Visualizing ideas with pictorial knowledge representations was a tool for students to plan and monitor their individual level and group level learning processes. Table 3. Pedagogical structure Description of activities

Pedagogical idea

Outcome

Technological tool

Lecture (6 sessions)

Theoretical grounding

Theoretical concepts

-

Groups’ grounding

Shared concepts

-

Constructing knowledge representations Negotiating knowledge representations

Mobile phone, Weblog, RSS-aggregator

Face to face group working sessions (6 sessions) Individual working sessions (6 sessions) Group’s meaning making sessions (2 sessions) Virtual group working sessions (2 sessions)

Constructing, monitoring Elaborating Constructing, monitoring

Using knowledge representations

Weblog Wiki Weblog, Wiki RSS-aggregator

The students were introduced to the content of the course with six lectures and after the each lecture the students reflected on the content of the lectures in groups. The given task for each group was to first reflect on the content and to name five important themes in the lecture. After that the students were asked to choose one of the themes and to formulate their group’s working problem based on the theme with which they continued to work by finding real-life examples to represent their shared discussions. In practise, the group work was followed with a one-week phase of independent on-line work, where students were asked to use mobile phones to take pictures and/or video clips to represent their ideas of the learning content. While taking the pictures/videos students were also asked to answer the following questions: what is the name of this picture, what does this picture represent, and how is it related to the learning content, by typing a short description for the picture. The pictures and descriptions of the pictures were sent automatically to the each student’s own weblog. This same task continued after each lecture. Weblogs were used as personal journals, where students reflected their ideas further by writing journal entries around the respective pictures/videos. Furthermore, students were asked to follow each others’ contributions to their personal weblogs by using RSS-aggregators in their mobile phones. In the middle of the course, students had a “meaning-making session” where they reviewed all the group members’ weblogs to see the pictorial material everyone had collected. The students were asked to introduce the pictures by explaining what they represent and to negotiate and choose among 75

the pictorial knowledge representations those pictures that could represent the group’s shared understanding. This session was repeated twice, in the middle of the course and at the end of the course, and the session was followed by the virtual group working phase, where students continued to share their ideas with the chosen pictorial knowledge representations. The data were collected by using video-observation, questionnaire, stimulated recall interviews. In addition log files of the students’ activities, and students’ and groups’ products in weblogs and wikis were used as a data. The results showed that construction and sharing of knowledge representations scaffold students’ shared regulation of collaborative learning by activating their cognitive processes; explaining and elaborating their own understanding.

Conclusions In this paper three different studies were presented in order to illustrate how collaborative learning can be structured and regulated in higher education, with wireless networks and mobile tools. The pedagogical ideas derive from collaborative learning, including the socially shared origin of cognition as well as self-regulated learning theory. Each study shows that, with a novel use of technology, certain aspects of collaboration can be supported. The Mobile Lecture Interaction Tool (M.L.I) is an example of how individual self-regulation can be supported in university lectures. The results show that students’ cognitive activities, such as metacognition and reflection, were stimulated by focusing on questions about the content of the lecture. This kind of learning tool can be used for compensating weak study skills in different domains (Azevedo, Guthrie & Seibert, 2004) and especially in university lectures. Even though, the M.L.I. tool was credited as beneficial for lecture interaction, some students viewed that there were too many things to concentrate on at the same time. Students pointed out that listening to the lecturer, writing lecture notes and using the M.L.I. tool at the same time, were too much for them to handle. Therefore, aspects related to cognitive load (Kirschner, 2002) need to be recognized. To lower the cognitive load the M.L.I. tool could be developed further so that students and teacher could use questions and comments also after the lecture. Another possibility is structuring or scripting the lecture situation so that there are specific times for questions and comments, and therefore students would not feel that they are missing some important things while they are using the M.L.I. tool. The results of the Mobile Mind Map tool study imply that the tool can be used for enhancing co-regulation in terms of sharing and externalizing visual knowledge representations and developing them in interpersonal interactions. The students should be encouraged, when appropriate, to create, modify or co-design the learning environments in which they are working. Construction of external representations can be a successful learning strategy that not only helps students by externalizing and sharing their thoughts, but also provides a source of information for teachers about students’ current task understanding (Butler & Cartier, 2004). Students’ co-regulated learning can be supported by scaffolding externalization of their own thinking and by seeing what others are thinking and, when possible, to then continue their own and others’ flow of thinking. However, externalizing knowledge representations is cognitively challenging. In this study pictures were used as external knowledge representations and the study indicates that pictures can carry individuals’ co-created meanings in them but since those meanings are personal, ambiguous negotiation processes are highly valuable. The Edufeed study indicates that web 2.0 technologies can be designed to scaffold shared regulation processes within the groups. In the study the students constructed a variety of pictorial knowledge representations and shared their meaning collaboratively. However, the students thought that it was challenging to represent their own ideas with pictures and even more challenging to explain the representation to others. Nevertheless, the students who explained their pictures to others viewed that the elaboration of pictures was beneficial for their learning. The results showed that construction and sharing of knowledge representations activated students' self-regulated learning; explaining and elaborating their own understanding. Other studies from collaborative learning contexts have highlighted that in collaboration, individuals should share their understanding in discussion to converge their knowledge representations, which might lead to new shared knowledge representations (e.g. Dillenbourg & Traum, 2006; Fisher & Mandl, 2005; Rochelle, 1992). It is concluded that even though self-generated pictorial knowledge representations are often personal and ambiguous they may give an impetus for sharing and explaining individual knowledge representations to the socially shared level. 76

In conclusion, this paper stresses a need to place students in various situations in which they can engage in effortful interactions in order to create opportunities for active minds (Dillenbourg, Järvelä, & Fisher, in press). Wireless networks and mobile tools will provide multiple opportunities for bridging different contents and contexts, as well as virtual and face to face learning interactions in higher education. Since the learning environment in higher education is more open and less teacher-guided than at other educational levels there is a need to increase student opportunities for self-regulating their learning on an individual as well as socially shared level. Wireless networks and mobile tools will provide future potential for developing learning in higher education, which needs to be explored in detail.

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