which enable everybody to participate, and structuring the discussion as a ... In: Proceedings of the ED-MEDIA'99 â World Conference on Educational ... We call cooperative learning methods in a distributed setting learning protocols.
In: Proceedings of the ED-MEDIA'99 – World Conference on Educational Multimedia, Hypermedia & Telecommunications, pp. 471-476, Seattle, Washington, June 19-24, 1999.
Using Learning Protocols to Structure Computer-Supported Cooperative Learning Martin Wessner, Hans-Rüdiger Pfister & Yongwu Miao GMD - German National Research Center for Information Technology Integrated Publication and Information Systems Institute (IPSI) Dolivostr. 15, D-64293 Darmstadt, Germany, E-Mail: {wessner, pfister, miao}@darmstadt.gmd.de
Abstract: A common problem of CSCL (Computer-Supported Cooperative Learning) is addressed: How can we coordinate goal-directed, effective interaction in a group of learners? We introduce the concept of learning protocols which originates in script theory. We then discuss which dimensions of cooperative learning can be supported by learning protocols and propose how learning protocols can be integrated in a CSCL environment.
1. Introduction Consider the following two examples: • A trainer asks his/her students a question. After some seconds without response he thinks that nobody understood or could answer the question and re-phrases his question. Increasing the time between the question and the intervention by a few seconds has several positive quantitative and qualitative effects on students’ answers [Rowe 1974]. • A group of learners is discussing a concept introduced in a presentation. The most eloquent and extrovert students dominate the discussion. Ideas and arguments of others remain unheard. Providing a set of rules which enable everybody to participate, and structuring the discussion as a cooperative process can guide the interaction in discussions and improve the learning process [Hall & Mancini 1997]. These examples indicate that learning can be improved by defining certain constraints and by structuring the learning process. Our work deals with the question: How can such constraints, rules, or process structuring methods be realized in a computer-supported cooperative learning environment? We call this kind of integrated learning support „learning protocols“. We see several developments which lead to the need for learning protocols. During the last decades learning is regarded more and more important due to the increasing amount of knowledge available worldwide, the increasing complexity of knowledge, and the increasing speed of these changes. This raises demands to establish a new learning culture: (1) Learning has to be a life-long process, we have to better support adult learners whose learning processes differ in many ways from those in schools or universities. (2) Individual learning methods are not sufficient for mastering the complexity of knowledge, we have to provide methods and support for groups of learners to cooperatively acquire knowledge and transfer it to daily practise. (3) In order to address changes in work organization as well as in society in general, learning cannot be limited to scheduled activities in a common classroom. Learning has to be flexible over various dimensions such as time and space. Therefore we need learning environments which support different learning scenarios, e.g. asynchronous learning or learning by geographically distributed learning teams. Our focus is on distributed cooperative settings, in which learning teams of adults want to learn in a flexible way. Focussing on co-located and synchronous settings, a number of field studies have indicated that students can learn effectively in pairs and in small groups, if they are supported by appropriate learning methods [Slavin 1995]. Cooperative learning can improve several cognitive and social aspects of the learning process [Mancini et al. 1998]. In a distributed cooperative setting, learning teams need means to communicate and to coordinate their learning activities. Given an infrastructure with networked computers, communication and cooperation environments which address these needs, e.g. by providing various communication channels and shared data repositories, are available (e.g., Microsoft NetMeeting). Can cooperative learning also be used
in a distributed cooperative setting in order to achieve similiar positive results as in a traditional setting? Can we transfer the cooperative learning methods? These topics are tackled by a field of research called computer-supported cooperative learning (CSCL) [Koschmann 1996]. Some positive experiences have been made using computers to support cooperative learning in traditional settings. For example, in the CSILE system a certain cooperative learning method is modelled, and learners are guided through the process by specific rules [Scardamalia & Bereiter 1996]. In [Hron et al. 1997] a system was successfully tested that controlled the dialog in cooperative dyads with a specific communication interface. There are some additional constraints in a distributed cooperative setting: The quantity and quality of transmitted information is different because many non-verbal signals are not transmitted. E.g., chat and e-mail deal with written communication and provide only limited support for non-verbal communication by using emoticons or attaching sound or image files to a message. Audio/video conferences provide audio-visual information in a lower quantity and quality than face-to-face settings. A major problem is that some cues are missing which structure cooperative learning in the co-located, synchronous setting. As a result, e.g. simple turn taking mechanisms in discussions fail in such settings. We see two ways to address this issue: • Integrate nonverbal signals in a CSCL environment by integrating additional communication channels, e.g. sensors detecting whether the learner is currently present in front of the computer or cameras analyzing facial expressions. • A second way is to develop cooperative learning methods or adapt existing ones to the distributed cooperative setting, and thereby taking into account the constraints of this setting such as changed number and quality of communication channels or less ambient information flow. The first solution leads to systems which track and check user activities with various kinds of sensors. That can be in the way of virtual reality as immersive 3-dimensional virtual worlds or by enhancing the intelligence of rooms and furniture in the real world. The advantage of these approaches is to represent reality and thereby providing a familiar environment with well-known or easy-to-learn means of communication and cooperation. But this advantage holds only as long as the system more or less clings to reproducing reality; additional support provided by the system has to be learned by the users. Our approach, however, is related to the second solution. We call cooperative learning methods in a distributed setting learning protocols. The remainder of this paper is organized as follows: In the next section the concept of learning protocols is described in more detail. Section three elaborates on the various ways in which learning protocols can help teams of learners to improve their learning process and results. The integration of learning protocols in a CSCL environment is presented in the fourth section. We close with a description of our next steps.
2. Learning Protocols as Implemented Scripts In cooperative learning we distinguish two kinds of supporting methods [Hron et al. 1997, Mancini et al. 1998]: • Global methods which structure the cooperation on a general level, e.g. by providing support for group organization, monitoring constraints such as a maximum floor holding time. • Structured or scripted cooperative learning methods which provide protocols for cooperative learning by structuring the dialog and actions of the learners. Learning protocols perceived as scripted cooperative learning methods are theoretically based on psychological script theory. In cognitive and social psychology, generalised knowledge about a routine sequence of related events and activities is commonly called a script [Schank 1982], [Schank & Abelson 1977]. A script is a knowledge structure that, once activated, yields information on what events to expect and how to act in a specific type of situation. For example, the well known restaurant script describes the sequence of actions when having a meal in a restaurant (e.g., ordering, eating, paying), and it specifies what to expect from others, e.g., from the waiter, depending on one's own actions. A script can be seen as a type of schema, which, in addition to a prototypical chain of actions, contains slots to specify the temporary circumstances, and default
values to guide expectations and inferences if no further information is available. Hence, scripts not only control many stereotyped encounters of daily life, they also reduce cognitive effort by providing guidelines that decrease the need to think about one's actions in well known situations. Scripts can be triggered by aspects of the situation (situation-controlled script; e.g. initiating a vote in a controversial discussion) or by a specific role (role-controlled script; e.g. a trainer is expected to answer a question and to determine the learning process). To act according to a script one has to know the script itself and one's part in that script. The activation of a script is considered to be mostly automatic. Cooperative learning methods can be perceived as externalized scripts attached to learning situations or roles in a learning team. In natural face-to-face situations, the actions of persons applying the same script are aligned by a lot of explicit and implicit cues (e.g., non-verbal cues such as pauses or changes in posture indicate turn-taking in a discussion script). In computer-mediated learning environments, however, these cues are largely missing, and the coordinated enactment of a script can be seriously endangered. Especially, cooperating learners may not use the same script at all, or may be uncertain about which script the others apply, or may define their roles in the script differently, or may loose orientation where the group currently is in the script. These difficulties in CSCL environments suggest that one should not rely on an automatic script enactment, but that one should provide scripts as implemented procedures that can be executed on demand. Learning protocols, as defined here, are just a set of useful scripts for learning, externalized as executable methods, with roles, events, and actions made explicit.
3. How Learning Protocols Can Structure Cooperative Learning 3.1 Explaining: An Example of a Learning Protocol Imagine that in a pairwise learning situation person A needs an explanation about some problem. Hence, he asks for explanation from person B, who tries to provide the explanation. In natural face-to-face situations, all interactions during the explanation process are usually carried out without much friction, since many verbal and non-verbal cues guide the dialog. However, in a distributed computer mediated situation, person A might want to activate an "explanation protocol", which then controls the communication process. The explanation protocol is very simple, basically controlling the right to speak and indicating which type of communication is currently being performed (if, e.g., a question is asked, or if an explanation is delivered). The protocol will, for example, strictly switch between explainer and explainee. The explainee will respond to an explanation either by asking for more information, or by deciding that he is satisfied with the explanation, which will terminate the protocol. The explainer will either deliver a further explanation, or he will declare himself unable to provide the explanation, which will also terminate the protocol. Learning protocols can be represented as a kind of state-transition-diagram; Figure 1 gives an example. The following sections show that this very simple learning protocol can be enhanced by integrating control over other ressources such as learning artifacts and shared workspaces.
start explainee: ask question
explainee: ask question
explaining
responding
explainer: query understanding
explainer: cannot explain
explainee: satisfied
exit
Figure 1: State-transition-diagram of an explanation protocol 3.2 Levels of Learning Protocols Learning protocols are useful on different levels of the cooperative learning process: • On the most basic level, they guide elementary communication processes among learners, e.g., discussions (be it by audio or chat), presentations, or dyadic dialog. • On the next level, protocols support group activities which need some coordination control, e.g., common navigation through hypermedia documents or preparation of agendas and time schedules. • The third level refers to protocols which are designed to support cooperation, e.g. jointly editing, domain specific role plays or simulations. On each level protocols range from more generic collaboration protocols, such as a discussion protocol, to very learning specific protocols, such as giving an explanation in a certain domain. In principle, the list of potential candidates of cooperative learning processes that could be translated into learning protocols is almost infinite. Special techniques such as "Jigsaw II" [Slavin 1995], or different cooperation modes such as symmetrical (e.g., a discussion among students) and asymmetrical (e.g. a presentation) modes, depending on role and group structure, could be devised. We think of learning protocols as a set of potential support tools from which learners and trainers may select what they consider to be useful. At any time, participants may choose from a menu a specific protocol, which is then activated. When finished, the group is free to select any other protocol, or to proceed without systematic support. Hence, the overall learning process is not itself controlled by a protocol, but can be augmented at any time when support seems appropriate.
3.3 Components of a Learning Protocol Irrespective of the level of a protocol, a protocol consists of a set of components, which can be derived from script theory. First, a protocol has a name; the name signifies the situation type to which the protocol can be applied. For example, a (cooperative) explanation protocol applies to situations in which an explanation is needed by some person and can be delivered by some other person. Unlike in natural situations, learning protocols are selected solely by name, i.e., a person subsumes the situation under the category referred to by the protocol's name, and intentionally activates the protocol.
Secondly, a protocol consists of a set of states and transitions. In each state the users can perform actions such as communicate or manipulate artifacts. A transition to another state is triggered by an action or a specific condition, e.g., the time-out of the preceeding state. Of course, various iterations and conditional branchings may occur. The interface of the learning protocol has to take care that different types of actions are appropriately perceived and classified. Thirdly, a protocol includes different roles pertaining to the persons involved in the enactment of the protocol. A learning process commonly consists of one or more students, and one or more trainers or teachers. Other roles specific to learning are tutors, experts, and moderators. Each participant of a running learning protocol needs to obtain a definite and unique role, and needs to know which roles other participants have. The role one has is either arbitrarily defined by oneself, or is derived from the overall group structure. Roles should also be indicated on the computer screen, i.e., everybody should be informed about his and the others' roles by some sort of visual indicator, in order to prevent role confusion. Finally, a protocol may contain various types of artifacts, i.e., text documents, graphical objects, test forms, etc. In many simple communication protocols, however, the definition of special artifacts is unnecessary, or only optional. For example, in the course of an explanation, the explainer and the explainee may use a shared whiteboard to outline some ideas, but this is not essential for the explanation process.
3.4 The Construction of Shared Knowledge A special problem in cooperative learning is to gain a common understanding of the shared knowledge of the group. Efficient communication requires that each participant knows, at least approximately, what the other participants know. Without this common background, it would require a lot of time and effort to achieve effective cooperation. In cooperative learning, due to the continuous acquisition of new knowledge of each participant, the shared knowledge is ever changing. This makes it even more important to provide systematic support to construct and represent the common knowledge of the learning group in some way. We propose that learners externalize their knowledge in the form of a diagram with nodes and links: nodes denote specific concepts (from the domain to be learned), and links denote specific relations among concepts, such as "is-example-of", or "is-subtopic-of". Without going into detail (see [Pfister et al. 1999]), it seems clear that this diagram of shared knowledge needs to be modified or updated regularly and systematically. A special type of learning protocol is needed to support the maintenance of the shared knowledge, providing protocols for expanding, for reducing, for restructuring the knowledge corpus, and for establishing consensus among learners on when and how to introduce changes to the knowledge.
4. Implementation In the CLear (computer-supported cooperative learning) project at GMD-IPSI, we develop computer-supported cooperative learning environments and cooperative learning methods for such systems. In a first step we designed the VITAL (=virtual teaching and learning) prototype using the COAST [Schuckmann et al. 1996] framework for building groupware. As described in section 2, we distinguish two kinds of supporting methods for cooperative learning: global methods and scripted cooperative learning methods. In VITAL we focussed mainly on supporting global methods. The prototype offers global group organization methods and a limited cooperation support, e.g. by providing a structured communication board and different cooperation modes. Evaluations of VITAL in university settings showed that the system is well accepted but offers only limited support for structuring the cooperative learning process [Beck-Wilson in press]. Therefore we extended the approach and integrated learning protocols [Pfister et al. 1998]. Our approach can be briefly characterized by (1) providing a virtual learning world consisting of different types of virtual rooms, in which learners can communicate and cooperate synchronously and asynchronously, (2) supplying each virtual learning room with a shared hypermedia workspace, (3) using hypermedia to represent the learning material, and (4) using hypermedia to define learning protocols and visualize their execution. For implementing learning protocols in a CSCL environment we use several techniques:
• •
Some global methods can rely on access rights, rules and conditions, or mechanisms for conflict resolution. Therefore, we need functionality for defining and checking these methods. Scripted cooperative learning methods are modelled using collaboration protocols similar to state transition diagrams (see Figure 1). Each state is defined by specific functionalities and rights of the involved participants, i.e., a set of behavior rules, which define which role is allowed to perform which operation on which resource. The learning protocols are implemented using the modelling method of SCOPE, a system which allows the definition, execution, modification and monitoring of general collaboration protocols [Miao & Haake 1998].
The implementation provides guided interactions between the system and the users. Depending on the kind of learning protocol and his/her role a user may initiate a protocol, e.g., by simply pushing a button. If all preconditions are met, the roles in the protocol are matched with the actual team members. During the execution of the protocol, the user interface provides information, such as the current state and possible actions in this state of the protocol. Special templates, e.g. for requests, explanations, and responses can be provided, and control is passed depending upon team members’ actions. An advanced prototype, called CROCODILE (=creative open cooperative distributed learning environment), is currently being implemented based on the experiences made with VITAL and SCOPE.
5. Next Steps We want to investigate whether learning protocols really inherit the advantages of their predecessors: cooperative learning methods and scripts. In addition to structuring the cooperative learning process we also expect them to serve as a means for meta-learning, i.e. learning to learn cooperatively. Field studies will show whether users can create (internal!) scripts by multiple usage of learning protocols and thereby transfer their behaviour to other collaborative situations. We still have a lot of open issues which require further research, two important ones being the usability of learning protocols in medium/large groups and in asynchronous settings. • Group size Most research on scripted cooperative learning (with and without using computers) deals with dyads [Mancini et al. 1998], [Hron et al. 1997] or relatively low structured scripts, which structures the learning process in coarse steps [Hall & Mancini 1997]. Only limited knowledge is available on which methods are suited for which group size. This has to be evaluated by performing extensive testing with user groups of various size. • Asynchronous learning A problem for learning teams at the workplace is the need to learn asynchronously, e.g. at times dictated by business requirements. Asynchronous cooperation is also very important or in many cases the only possible solution for dispersed learning teams spread over different time zones. Many of the traditional cooperative learning methods assume synchronous settings and have to be adapted for asynchronous usage. Further information about the CLear project and the learning environments VITAL and CROCODILE is available at our website http://www.darmstadt.gmd.de/concert . 6. References Beck-Wilson, J., Pfister, H.-R., Schuckmann, C., & Wessner, M. (in press). The CLear approach: Designing distributed computer supported cooperative learning environments. In A. Eurelings (Ed.) Integrating information & communication technology in higher education. Amsterdam: Kluwer. Hall, R. H., Mancini, B. M. (1997). „Real life“ scripted collaborative discussion within the context of a general psychology class. Cooperative Learning and College Training, 8 (1), 9-10. Hron, A., Hesse, F. W., Reinhard, P., and Picard, E. (1997). Strukturierte Kooperation beim computerunterstützten kollaborativen Lernen [Structured cooperation in computer-supported collaborative learning]. Unterrichtswissenschaft, 1/97, 56-69. Koschmann, T. (Ed.): CSCL: Theory and practice of an emerging paradigm. Mahwah, NJ: Erlbaum.
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Acknowledgements We want to thank Christian Schuckmann and his team for implementing the VITAL prototype and all our colleagues at the CONCERT department at GMD-IPSI for very helpful discussions.
