September 2009 Index
 
Home Page

Editor’s Note: This paper explains how project-based collaborative learning, supported by computers, can increase the intensity and productivity of learning experiences. It is especially valuable for learning high-level professional knowledge and skills.

 

Stimulating Collaborative Learning
by Doing Study Projects

Oleg Tilchin
Israel

Abstract

The goal of this paper is to provide a computer supported model of a specific project-based collaborative learning environment. The environment stimulates intensive collaborative knowledge construction by students during study projects due to maximization of the number of interactions inside collaborative groups and the presence of a special schedule for performance of project tasks. The Intelligent Tool provides computer support of the model. The tool dynamically forms project-based collaborative learning environment by means of dynamic co-ordination between building of the temporal sequence of groups of project tasks and assigning of collaborative group students for performance of the tasks. Such formation of the environment provides adaptation to dynamically changing project task characteristics and personal knowledge. The tool assists an instructor in evaluation of the outcomes of the collaboration among the students and in measuring course learning efficiency of each student. An opportunity for adaptive computer-mediated management of project-based collaborative learning emerges.

Keywords: project-based collaborative learning, stimulation of collaborative knowledge construction, dynamic formation and evaluation of the collaborative learning environment

1. Introduction

One constructive way to enhance learning is the Project-Based Learning (PBL) model (Thomas John W., 2000; Markham Tom, Jorn Larner, Jason Ravitz, 2003; Han S, Bhattacharya K., 2001).  This model organizes learning through involvement of students in a project activity. The results of the projects must be real products.

The PBL model produces a constructive basis for collaboration. Indeed, a common project has a purpose. Students engage in collaborative work on a project in order to achieve this purpose. In such work learners depend on each other. Furthermore, the project produces a real need for interactions between learners since it requires collective work.  Therefore, the PBL model must be integrated with the Collaborative Learning model (Roberts Tim S., 2005; Ornstein Allan, Lasley Thomas, 2003; Bransford, J. D., Brown, A. L. & Cocking, R. R. (Eds.), 2000).

Methodology of collaborative learning is based on

  • Constructivist theory(Maureen Tam, 2000); constructionism (Han S, Bhattacharya K., 2001) ; distributed constructionism (Resnick M., 1996); shared cognition theory (Hergenhahn B.R., Olson Matthew H., 2004)
  • The concepts of community of practice and community of purpose
    (
    Coakes  Elayne, Clarke Steve, 2006)
  • Problem based learning strategy
    (
    Schwartz Peter, Mennin Stewart,Webl Graham, 2001)
  • Effective strategies for collaborative learning
    (
    Ornstein Allan, Lasley Thomas, 2003)

A Project-Based Collaborative Learning (PBCL) model makes it possible for students to acquire high-level professional knowledge. It allows analysis, evaluation, and synthesis. According to the PBCL model, students learn to work collectively through cooperative group work. As a result, students can acquire collaborative skills. Collaborative skills enable students to effectively communicate, manage, and resolve disagreements.

There are many obstacles for instructors and for students to implement a PBCL model (Ellis Timothy J., Hafner William, 2008).  The main reason for obstacles is the high complexity of the model. Computer-supported collaborative design (Daradoumis T., Xhafa F., Marques J.M., 2002; Marion G. Ben-Jacob, David S. Levin, Talia K. Ben-Jacob, 2000) is chosen as the core learning activity since it combines all of the essential elements in a natural and effective way. Computer support tools for collaborative learning are being developed (Roberts Tim S., 2005; Stahl Gerry, 2006) to eliminate the obstacles.

The computer support tools for PBCL canbe divided into

  • Tools for technological support of PBCL (Roberts Tim S., 2004) 
  • Tools for forming and managing the PBCL environment (Laffey James, Tupper Thomas, Musser Dale, Wedman John, 1998; Orvis Kara L., Lassiter Andrea L. R., 2008).

Figure 1 shows interdependence of PBCL model with the tools of its computer support.

Fig.1. Interdependence of a Project-Based Collaborative Learning Model > with Computer Support Tools

The tools for technological support are wide-spread (Roberts Tim S., 2004; Fisher F., Bruhn J., Grasel C., Mandi H., 2002) while the tools for computer-mediated formation and management of PBCL are not sufficiently developed. Lack of such tools is the main reason for limited use of PBCL model in education.  Indeed, implementation of PBCL requires dynamic formation of the necessary learning environment. This is difficult work impractical to do by hand because of the high complexity of the model. Therefore, the PBCL model requires the Intelligent Tool in order to realize the dynamic formation of the learning environment.

2. Literature Review

Computer-supported formation of a collaborative learning environment is reviewed in this research. It should realize various requirements for building and organization for the functioning of collaborative learning groups (Graham C.R., Misanchuk M., 2003; Martin Wessner, Hans-Rüdiger Pfister, 2001; Michael Lawrence-Slater, 2006). The requirement for heterogeneous (complementary) or homogeneous (resembling) collaborative learning groups is one of the major requirements.

A new paradigm of learning theory, distributed constructionism is proposed by (Resnick, M., 1996). The four major principles that characterize distributed constructionism were formulated by (Chuen-Tsai Sun, Sunny S. J. Lin, 2001). They are: active learning, learning via simulation, interactive/inter-creative learning, and accumulative learning. They are called ASIA principles. Based on the principles, a method is proposed for formation of collaborative groups that support creative thinking.

An approach to integration of collaborative learning into the learning environment was proposed by (Martin Wessner, Hans-Rüdiger Pfister, 2001). An instructor specifies the collaboration activity (forms collaboration groups) for certain blocks of a web based course. The knowledge about the collaboration context is utilized in order to form appropriate learning groups.

The paper (Michael Lawrence-Slater, 2006) describes formation of the environment for learning an online course. The students formed online groups and successfully completed a collaborative project. In order to achieve this, students posted their interests, their academic majors, email addresses and other information. Such approach makes it easy to form collaborative groups based on an informational profile of each student. However, the difficulty of evaluating “ability to cooperate” is subjective and has to be performed by the students themselves.

Formation of groups in a CSCL environment, according to (Graham C.R., Misanchuk M., 2003) is provided by going through these stages: structuring of learning activities, creation of groups, and facilitation of group interactions. Facilitation of group interactions is accomplished by creation of a learning environment leading to group interactions (Dillenbourg P., 1999).

The work of (Orvis Kara L., Lassiter Andrea L.R., editors, 2008) takes a look at dynamic management of group organization. However, it does not examine organization of group functioning during the tasks of study project stimulating collaborative knowledge construction.

The work of (Ellis Timothy J., Hafner William, 2007) researches the impact of type of control structure on functioning of a collaborative group. The control structure determining the role of a student in a group may vary from an entirely democratic model to an autocratic model. However, an important aspect of functioning of a collaborative group directed to learning stimulation was not examined. This aspect assumes dynamic change of the role of a student in a group depending on his ability to perform project tasks. This ability must be determined as a result of comparison of his personal knowledge and task-relevant knowledge (knowledge necessary to perform a task).

The work of (Daradoumis T., Xhafa F., Marques J.M., 2002) assumes an approach to the creation of a PBCL environment facilitating interaction among students. However, formation of composition and structure of collaborative groups is left to students.

Authors link meeting learning objectives with going through stages of software project development. At that, students perform a dual role as project managers and project workers. Also, an influence of role dynamics on collaborative knowledge construction is not shown. The authors note the necessity for project scheduling. However, they do not suggest a mechanism for a group of students to build a temporal sequence of project tasks and organization of their performance.

The analysis of publications above shows that there is no computer-supported model of the PBCL environment stimulating collaborative knowledge construction by students during performance of study projects.

The model must be built by means of complex accounting for task-relevant knowledge, temporal, and structural project tasks parameters on one hand, and personal knowledge of students on the other.

The model has to provide dynamic co-ordination between formation of the temporal sequence of groups of project tasks and assigning of collaborative groups of students for performance of tasks.

Stimulation of collaborative knowledge construction must be achieved due to maximization of the number of collaborative interactions. Such maximization must be provided by means of creating situations of mutual supplementation of knowledge of students inside groups, and by the presence of a special schedule for performance of project tasks.

3.  Model of Project-Based Collaborative Learning Environment

The aim of this paper is to provide a computer supported model of a specific PBCL environment. The environment must stimulate knowledge construction by students doing study projects. Computer support of the model is realized by the Intelligent Tool.

PBCL environment includes collaborative groups of students and projects performed by the groups.

The collaborative group is characterized by size and composition. Each student has some professional personal knowledge before the start of the group project.

The project is a set of interdependent project tasks. Each task has the following characteristics: task-relevant knowledge; a task deadline; and time to perform a task.

Task-relevant knowledge of all project tasks represents project-relevant knowledge (knowledge necessary to perform a project).

The following conditions are observed in this paper:

  • all projects have the same project-relevant knowledge.
  • the project should be performed in allocated time period.
  • the project should be performed in one collaborative group.
  • interactions among students from different collaborative groups are allowed.

The model of the PBCL environment is created for stimulation of collaborative knowledge construction by students during performance of study projects.

It promotes effective study of a subject. The criterion of effective studying is minimal difference between project-relevant knowledge and personal knowledge of each student after the performance of a group project in a given time.

The model of the PBCL environment includes:

  • Temporal sequence of groups of project tasks built by means of complex accounting for task-relevant knowledge, temporal and structural project tasks parameters. The tasks in task groups have maximal diversity relative to task-relevant knowledge.
  • Collaborative groups of students for performance of the projects. Maximal mutual supplementation of knowledge of students inside a collaborative group working on a project is provided.
  • Order of assigning a student of the collaborative group to a task in a task group so that personal knowledge will differ as much as possible from task-relevant knowledge.
  • The schemes of possible knowledge construction through intra-group and inter-group interactions among the students.

The environment built according to the model stimulates collaborative knowledge construction. In fact, the original temporal sequence of groups of project tasks provides an opportunity for learning intensification and sets the work schedule of the project performance. Specific order of assigning a student of a collaborative group to a task in a task group maximizes the number of collaborative interactions inside groups. It allows making effective schemes of possible knowledge construction by students due to intra-group and inter-group interactions among the students.

The PBCL environment is formed dynamically by co-ordination between dynamic formation of the temporal sequence of groups of project tasks and dynamic assigning of collaborative group of students for performance of tasks.

Such formation of the PBCL environment provides adaptation to dynamically changing project task characteristics and personal knowledge.

Dynamic formation and evaluation of the PBCL environment is a complicated and difficult process.

Therefore, the Intelligent Tool must to be used to assist an instructor in dynamic formation and evaluation of the learning environment.

4.   The Intelligent Tool for Dynamic Formation and Evaluation
      of the PBCL Environment

The Intelligent Tool assists an instructor in the following activities:

  • Formation of the PBCL environment according to the proposed model. Such formation stimulates knowledge construction by students during collaborative performance of course projects.
  • Evaluation of outcomes of collaboration among students, and measurement of efficiency of studying a subject by each student.

The Intelligent Tool gains the following information from an instructor:

  • Knowledge necessary to complete each of the projects.
  • A time period allocated to perform each project, divided into intervals.
  • The quantity of projects to be performed.  
  • A set of interdependent project tasks.
  • The parameters for each project task: task-relevant knowledge; completion deadline of a task; time to perform a task.
  • The aggregate of students studying the subject.
  • The personal knowledge of students before performance of the projects and additional knowledge constructed by the students during the performance of the projects.
  • Limitations of collaboration (selection of students who cannot participate in performance of the same project due to parameters other than personal knowledge).

Based on the gathered information the Intelligent Tool performs the following procedures:

Procedure 1: Dynamic formation of the temporal sequence of the task groups

Maximal diversity of tasks relative to task-relevant knowledge should be provided for each task group of the temporal task sequence. In addition, a temporal and a structural coordination should take place during performance of tasks. 

Every task group of the project must be completed during the specified time interval. It sets time frames for performance of the project tasks. The algorithm (Tilchin O., 2005) is used to get the required temporal sequence of the task groups.

Procedure 2: Check the necessary condition for beginning of group projects.

The condition is that knowledge of all the students studying the subject should not be less than the project-relevant knowledge.

Procedure 3: Determine the size and composition of the collaborative groups

The size of a collaborative group is determined by taking into account the aggregate of the students studying the subject and the quantity of projects that have to be performed. Also, the quantity of students in a collaborative group should not be less than the quantity of unrelated tasks in a task group. This condition provides an opportunity for the simultaneous execution of group tasks.

Composition of a collaborative group for a project is determined by choosing students from the aggregate of students studying the subject according to a necessary condition: maximum mutual supplementation of knowledge of students inside a collaborative group. This condition provides an opportunity for interaction among the students of the collaborative group.

Limitations for collaboration are also taken into account during the formation of collaborative groups.

Procedure 4:  Assign students to perform tasks. Determine lack of personal knowledge

The tool assigns students in a collaborative learning group to perform tasks from task groups. This is done by comparing personal knowledge and task-relevant knowledge based on the following condition: knowledge of a student must differ as much as possible from the task-relevant knowledge. This process is done in turn for each task group of the project. It identifies lack of personal knowledge and initiates the maximal need of a student for knowledge necessary to complete the task. As a result, collaborative knowledge construction in a group is stimulated. Lack of personal knowledge is determined based on the order of assigning students by comparing student knowledge with task-relevant knowledge.

Procedure 5:  Determine the schemes of knowledge construction

The scheme represents the order of possible knowledge construction by collaborating students. The knowledge is constructed through intra-group and inter-group interactions among the students to compensate for the lack of personal knowledge necessary for successful performance of project tasks.

Procedure 6: Evaluation of quality of collaboration and effectiveness of studying a subject by each student

The Intelligent Tool evaluates quality of collaboration among students by comparing personal knowledge of each student before and after collaborative work on the project.

Evaluation of effectiveness of studying a subject by each student is done by comparing his final personal knowledge and project-relevant knowledge. 

The final knowledge of a student is determined by combining the personal knowledge before the group project with the additional knowledge constructed by a student during the performance of the group project.

As a result of its work, the Intelligent Tool generates output essential for formation and evaluation of the PBCL environment:

  • The temporal sequence of the task groups for each project   

  • The result of checking of the necessary condition for performance of projects

  • The size and composition of the collaborative groups for performance of the projects

  • The order in which students are assigned for project tasks

  • The schemes of possible knowledge construction by the students

  • Evaluations of quality of collaboration and effectiveness of studying a subject by the students

In the presence of changing project task characteristics and personal knowledge the Intelligent Tool forms the renewed temporal sequence of the task groups, the order of assigning students to perform their tasks, and the schemes of possible knowledge construction by the students.

5. Integration of the PBCL model with the Intelligent Tool

Realization of the proposed PBCL model integrated with the Intelligent Tool is represented by the following activities:

  1. Teaching of a subject by means of explanation through a sample project.

  2. Determination of sample project relevant knowledge.

  3. Performance of exercises by students within a sample project.

  4. 4.  Determination of personal knowledge of students based on the results of their exercises.

  5. The instructor offers students necessary additional exercises if the knowledge of all students studying the subject is less than the project-relevant knowledge.

  6. Introduction of limitations for collaboration (selection of students who cannot participate in performance of the same project due to parameters other than personal knowledge).

  7. Assignment of a separate project theme for each group (project-relevant knowledge of each project is equal to project-relevant knowledge in a sample project).

  8. Dynamic formation of the collaborative learning environment for various projects. In order to do that, an instructor uses the Intelligent Tool described above in part 4.

  9. Control of the project process. This action presupposes examination of success and timeliness of performance of project tasks by a group of students.

  10. Correction of learning environment.

  11. Presentation of projects.

  12. Evaluation of personal knowledge of students according to the results of collaborative project work. Evaluation of changes in personal knowledge of students is measured by comparing personal knowledge of students before and after collaborative project work. This action presupposes the use of the Intelligent Tool.

The order (scheme) of cooperation among an instructor, students, and the Intelligent Tool for dynamic formation and evaluation of PBCL environment according to the proposed model is presented in Figure 2.

 

Figure2. The order of cooperation among the instructor, students,
and the
Intelligent Tool

6. Conclusion

A computer–supported model of the collaborative learning environment stimulating knowledge construction by students during performance of study projects is presented.

The model contains:

  • Temporal sequence of groups of project tasks built by complex accounting for task- relevant knowledge, temporal and structural parameters of project tasks
  • Collaborative groups of students for performance of projects
  • The order of assigning a student of a collaborative group to a task in a task group
  • The schemes of possible knowledge construction through intra-group and inter-group interactions among the students.

Stimulation of the knowledge construction by students is provided by the following characteristics of the model: maximal diversity of the tasks in temporal task groups relative to task-relevant knowledge; maximal mutual supplementation of knowledge of students inside a collaborative group; assignment of students in the collaborative group to perform the tasks in a task group in such a way that personal knowledge differs as much as possible from task-relevant knowledge.

The collaborative learning environment forms dynamically according to the model by means of co-ordination between the dynamic formation of groups of project tasks and the dynamic assignment of a collaborative group of students to perform tasks.

Computer support of the model is realized by the Intelligent Tool. The Tool provides: formation of the PBCL environment; adaptation to dynamically changing temporal and structural project task characteristics and personal knowledge; measurement and evaluation of the results of PBCL. Realization of the proposed model integrated with the Intelligent Tool is presented.

Future research will be directed towards expansion of a set of parameters of the PBCL environment, expansion of abilities of the PBCL model, and expansion of the management capabilities of the proposed Intelligent Tool.

References

Chuen-Tsai, Sun, Sunny, S. J. Lin (2001). Learning Through Collaborative Design: A Learning Strategy on the Internet. In Proceedings of the 31st Annual Frontiers in Education Conference (FIE 2001), Reno, Nevada, USA, October 10-13.

Coakes, Elayne, Clarke, Steve (2006). Encyclopedia of Communities of Practice in Information and Knowledge Management, Idea Group Inc.

Daradoumis T., Xhafa F., Marques J.M.,(2002). A Methodological Framework for Project-Based Collaborative Learning in a Networked Environment.

Dillenbourg, P. (1999). Introduction: What do you mean by collaborative learning? Dillenbourg (ed.), Collaborative learning. Cognitive and computational approaches. Elsevier, Amsterdam.

Ellis, Timothy J., Hafner, William (2008). Building a Framework to Support Project-Based Collaborative Learning Experiences in an Asynchronous Learning Network. Interdisciplinary Journal of E-Learning and Learning Objects, Volume 4.

Ellis, Timothy J., Hafner, William (2007). Control Structure in Project-Based Asynchronous  Collaborative Learning. In Proceedings of the 40th Hawaii International Conference on System Sciences.

Fisher, F., Bruhn, J., Grasel, C., Mandi, H.(2002). Fostering Collaborative Knowledge Construction with Visualization Tools. Institute of Educational Psychology, University of Munich, Germany.

Graham., C.R., Misanchuk, M.(2003). Computer-mediated learning groups: Benefits and Challenges to using groupwork in Online Learning Environments, In T.S. Roberts, ed. Online Collaborative Learning: Theory and Practice, Hershey, PA: Information Science Publishing.

Han, S, Bhattacharya, K. (2001). Constructionism, Learning by Design and Project Based Learning. In Emerging perspectives on learning, teaching, and technology. Department of Educational Psychology and Instructional Technology, University of Georgia.

Hergenhahn, B.R., Olson Matthew, H.(2004). Introduction to the Theories of Learning  (7th edition).

Laffey, James, Tupper, Thomas, Musser, Dale, Wedman, John (1998). A Computer-Mediated Support System for Project-Based Learning. Journal Educational Technology Research and Development, Volume 46, Number 1.

Lawrence-Slater, Michael (2006). Facilitating the Self-Formation of Collaborative Groups, Online. In Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies, IEEE Computer Society, Washington, DC, USA.

Maureen, Tam (2000). Constructivism, Instructional Design, and Technology: Implications for Transforming Distance Learning. Journal of Educational Technology & Society 3(2).

Marion G., Ben-Jacob, David S., Levin, Talia K., Ben-Jacob (2000). The Learning Environment of the 21st Century. The IJET, vol.6, N3.

Markham, Tom, Larner, Jorn, Ravitz, Jason (2003). Project Based Learning. Handbook, second edition, Buck Institute for Education.

Ornstein, Allan, Lasley, Thomas (2003).Strategies for Effective Teaching, McGraw-Hill Humanities, 4 edition.

Orvis Kara, L., Lassiter Andrea, L.R., editors(2008). Computer-Supported Collaborative Learning; Best Practices and Principles for Instructors, Book News, Inc.

Resnick M., (1996). New Paradigms for Computing, New Paradigms for Thinking, in Constructionism in Practice: Designing, Thinking, and Learning in a Digital World, Eds. Kafai Y. & Resnick M., Lawrence Erlbaum Associates Inc.

Roberts Tim, S., editor (2004). Online Collaboration Learning: Theory and Practice, Idea Group Inc.

Roberts Tim, S., editor (2005). Computer – Supported Collaborative Learning in Higher Education, Idea Group Inc.

Schwartz, Peter, Mennin, Stewart, Webl, Graham, editors (2001). Problem Based Learning: Case Stadies, Experience and Practice, Kogan Page Limited.

Stahl, Gerry (2006). Group Cognition: Computer Support for Building Collaborative Knowledge (Acting with Technology), The MIT Press.

Thomas, John W. (2000).A review of research on project-based learning. Available at: http://www.autodesk.com/foundation.

Tilchin, Oleg (2005). Clustering Algorithm of Forming Dynamic Temporal Collaboration Groups. In  Proceeding of the International Conference on Computational Intelligence for Modelling, Control & Automation (CIMCA 2005) Jointly with International Conference on Intelligent Agents, Web Technologies & Internet Commerce(IAWTIC 2005), Vienna, Austria, November.

Wessner, Martin, Hans-Rüdiger, Pfister (2001). Group formation in computer-supported collaborative learning. In Proceedings of the International ACM SIGGROUP Conference on Supporting Group Work, ACM Press New York, NY, USA.

About the Author

Oleg Tilchin is professor and head of the Computer Science Department at Al-Qasemi-Academic College of Education, Israel. He received his Ph.D. in Engineering Cybernetics and Information Theory in 1978. He specializes in information systems, knowledge management systems and methods of combinatorial optimization.

His current research focuses on the development of methods and technological tools for organization and management of teaching and learning.

Email: otilchyn@yahoo.com

go top
September 2009 Index
Home Page