COLLAGE, a Collaborative Learning Design Editor Based on Patterns COLLAGE, a Collaborative Learning Design Editor Based on Patterns Davinia Hernández-Leo.

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Presentation transcript:

COLLAGE, a Collaborative Learning Design Editor Based on Patterns COLLAGE, a Collaborative Learning Design Editor Based on Patterns Davinia Hernández-Leo GSIC / EMIC Group University of Valladolid, Spain UNFOLD CoP meeting: Next generation activity-based eLearning Berlin, November

Contents  Introduction  Collaborative Learning Flow Patterns (CLFP)  Collage (COLaborative LeArning desiGn Editor)  Preliminary evaluation  Conclusions

Introduction (I) Design of CSCL ( Computer-Supported Collaborative Learning ) situations Productive interactions among participants Structuring CL, collaboration scripts Computational representations of collaborations scripts (CSCL scripts) interpretable by LMSs: - practitioners can influence in the behavior and functionality of a CSCL system (participatory design)

 How can teachers develop effective collaborative learning designs/ collaboration scripts according to the necessities of a particular learning situation? Introduction (II)

Introduction (III) Capturing the essence of broadly accepted scripts (best practices) - so that they can be easily reused in different situations (particularized according to their concrete necessities): Patterns for the design of (potentially effective) CSCL scripts

Introduction (IV) How can patterns for the design of CSCL scripts be made available? Computer-interpretable notations Templates integrated in authoring tools (so that patterns can particularized and combined) Formalisms (XML) are not familiar to educators: Representations and abstractions easy to understand CL complexity Selection of the patterns/templates Collaborative learning flow patterns IMS Learning Design

 Diverse approaches of LD editors: RELOAD, CopperAuthor, COSMOS: general purpose editors close to the specification (for LD experts) MOT+ Editor, ASK-LDT: graphical representations facilitates the authoring, but still LD knowledge is needed… Our approach: A high-level (distant from the specification, user- friendly) collaborative-learning specialized editor that allows teachers to create their own collaborative LD by starting from existing patterns: COLLAGE (COLaborative LeArning desiGn Editor) Introduction (V)

 Collection and formulation of Broadly accepted techniques repetitively used by CL practitioners (best practices) when structuring the flow of types of (collaborative) learning activities  as patterns: Collaborative Learning Flow Patterns (CLFPs) Solution to a recurrent problem: what flow of activities for promoting desired educational objectives Way of communicating CL expertise CL Flow Patterns (I)

Jigsaw CLFP (1) CL Flow Patterns (II) … SCRIPTED Collaborative Learning… This pattern gives the collaborative learning flow for a context in which several small groups are facing the study of a lot of information for the resolution of the same problem. *** The collaborative learning flow must enable the resolution of a complex problem/task that can be easily divided into sections or independent sub-problems (related “larger” patterns) CONTEXT PROBLEM

Jigsaw CLFP (2) CL Flow Patterns (III) (E.g.) To promote the feeling team members need each other to succeed (positive interdependence) High-risk: more appropriate for collaborative learning experienced individuals Each participant in a group (“Jigsaw Group”) studies a particular sub-problem. The participants of different groups that study the same problem meet in an “Expert Group” for exchanging ideas. These temporary groups become experts in the section of the problem given to them. At last, participants of each “Jigsaw group” meet to contribute with its “expertise” in order to solve the whole problem. SOLUTION (educational objectives) (complexity)

Jigsaw CLFP (3) CL Flow Patterns (IV) (diagram representing the solution) Individual or initial group Teacher Introductory individual (or initial group) activity Collaborative activity around the sub-problem Collaborative activity around the problem and solution proposal

Jigsaw CLFP (4) CL Flow Patterns (V) *** (E.g.) The expert-group phase can be structured according to Pyramid CLFP or Brainstorming CLFP Particularization into a script: (E.g.) Provide experts with a tool so that they can take notes during the expert group that provide support when the original group re-assembles… Instantiation of the Jigsaw CLFP-based script: (E.g.) Being the only expert in a sub-problem in the “Jigsaw Group” can be a demanding experience. This can be mitigated if two group members share the same section of the problem. (related patterns) (recommendations for particularization / customization, instantiation and execution)

Jigsaw CLFP (5) CL Flow Patterns (VI) Collaborative understanding of a paper where each subsection is assigned to each member of every “Jigsaw Group”… Aronson, E., & Thibodeau, R. (1992). The Jigsaw classroom: a cooperative strategy for an educational psychology course. In Lynch, J., Modgil, C. & Modgil, S. (Eds.), Cultural diversity and the schools, Washington: Palmer, Clarke, J. (1994). "Pieces of the puzzle: The jigsaw method" In Sharan, S. (Ed.), Handbook of cooperative learning methods, Greenwood Press. Johnson, D.W., & Johnson, R.T. (1999). Learning together and alone: cooperative, competitive and individualistic learning. (5th ed.) Needham Heights, MA: Allyn and Bacon. … (example) (references)

Pyramid CLFP (1) CL Flow Patterns (VII) … SCRIPTED Collaborative Learning… This pattern gives the collaborative learning flow for a context in which several participants face the collaborative resolution of the same problem *** The collaborative learning flow must enable the resolution of a complex problem/task, usually without a concrete solution, whose resolution implies the achievement of gradual consensus among all the participants (related “larger” patterns) CONTEXT PROBLEM

Pyramid CLFP (2) CL Flow Patterns (VIII) (E.g.) To promote the feeling team members need each other to succeed (positive interdependence) Medium-risk: some experience in collaborative learning is required Each participant studies the problem and proposes a solution. Groups (usually pairs) compare and discuss their proposals and, finally propose a new shared solution. These groups join in larger groups in order to generate new agreed proposals. At the end, all the participants must propose a final and agreed solution. SOLUTION (educational objectives) (complexity)

Pyramid CLFP (3) CL Flow Patterns (IX) (diagram representing the solution) Individual or initial groupTeacher PHASE N: Propose a final and agreed solution PHASE i: Compare, discuss and propose a shared solution PHASE 1: Individual (or initial group) study of the problem. Proposes a solution

Pyramid CLFP (4) CL Flow Patterns (X) *** (E.g.) Each level of the Pyramid (except level N) can be structured according to Jigsaw CLFP Particularization into a script: (E.g.) During particularization the number of the Pyramid levels should be determined (related patterns) (recommendations for particularization / customization, instantiation and execution)

Pyramid CLFP (5) CL Flow Patterns (XI) Agree on common conclusions about a paper Davis, W. A. (2002). A comparison of pyramids versus brainstorming in a problem based learning environment. In Focusing on the Student. Proceedings of the 11th Annual Teaching Learning Forum. Perth: Edith Cowan University. Gibbs, G. (1995) Teaching more students 3: Discussion with more students. The Oxford Centre for Staff Development, Headington, Oxford. Johnson, D.W., & Johnson, R.T. (1999). Learning together and alone: cooperative, competitive and individualistic learning. (5th ed.) Needham Heights, MA: Allyn and Bacon. … (example) (references)

 CLFPs can be collectively used forming CLFPs hierarchies in order to define more complex collaborative learning flows CLFPs can be combined (a phase of a CLFP is structured using another CLFP) Or concatenated (separated consecutive phases of a design are structured using different CLFPs) CL Flow Patterns (XII) +

(COLlaborative LeArning desiGn Editor) (Graphic-based high-level specialized authoring tool for collaborative learning. Integrated in Reload. IMS-LD level A compliant) Collage (I)

Collage (II) Selecting a CLFP a. Choose a CLFP depending on the objectives promoted, the type of problem or task the CLFP is more suited and the complexity… b. Read the “help” about the chosen CLFP: Understand the learning flow structure on which the LD will be based Authoring a CLFP-based LD IMS-LD formalized CLFPs Design process (1)

Collage (II) Selecting a CLFP (1) Learning objectives Type of problems / tasks Complexity (CL experience)

Collage (III) Selecting a CLFP (2) Overview Example

d. Specify the collaborative learning flow: The learning flow of the selected CLFP can be enriched replacing one or several of its phases with another CLFP. Depending on the CLFP some aspects should be decided e. Define the description activities, activity completion, the information about roles (including groups), group-size limits. Collage (IV) Selecting a CLFP Authoring a CLFP-based LD IMS-LD formalized CLFPs f. Create or select resources (content and tools) c. Determine the title, objectives and prerequisites of the LD d. Specify the collaborative learning flow: The learning flow of the selected CLFP can be enriched replacing one or several of its phases with another CLFP. Depending on the CLFP some aspects should be decided. e. Define the description activities, activity completion, the information about roles (including groups), group-size limits. g. Determine and configure the resources needed to support the activities h. Associate resources to activities i. Package the LD into a Unit of Learning Design process (2)

Collage (V) Authoring a CLFP-based LD (1)

 Trade off between generality and unrestricted design options vs. good reuse and particularization of CLFPs (and hierarchies) and an easy edition of collaborative LDs Intuitive graphical representation of CLFPs User do not need to know the existence and function of some (difficult to understand) IMS-LD elements Interoperability but it is not a viewer of any LD Selection of CLFPs (considering users not familiar with the jargon): supporting the analysis phase Reuse learning flow vs. reuse activity (LAMS): complementary Collage (VI)

Preliminary evaluation (I) Design a real CL experience  Faculty of Education, University of Valladolid, Spain  Course: “The use of ICT in Education”  Objective: deeper understanding of three topics  Blended scenario (F2F and distance activities, with and without computer-support)  40 students  Tools: (Synergeia) BSCL and MapTool  Method: Combination of Jigsaw and Pyramid CLFPs

Preliminary evaluation (II) Conditions of the evaluation study  The three teachers (familiar with CLFPs but not with LD, first time using Collage), 90 minutes, worksheet  Qualitative and quantitative approaches Direct observations, questionnaires, analysis of the generated UoLs  Categories of analysis: user profile, general use of the editor, example creation and suggestions

Preliminary evaluation (III) Some results Use of the editor  Intuitive adequate representations of CLFPs Arguments that support the user-friendliness Example creation  Successful (with minor problems)  CopperCore correctly validates the three UoLs  UoLs largely describes the example (but some description of activities not completed)

Preliminary evaluation (IV) Opinions  “It helps to think in terms of CL and its previous arrangements”  “It helps to structure a complex learning design and promotes time and resources planning”  “It enables the generation of contextualized learning processes according to the needs of each situation”

Preliminary evaluation (V) Further evaluation  Two other teachers (minor LD knowledge, familiar with CLFPs, first time using Collage)  Design experiences already performed “Administration of communication networks” Jigsaw CLFP combined with Brainstorming CLFP (expert phase of Jigsaw) and Pyramid CLFP (last phase of Jigsaw) “Advanced Telematic Systems” Jigsaw CLFP  Analogous evaluation method Minor usability problems (without worksheet) More flexibility needed

 Collage and further information about our authoring tool is available in User manual, worksheet and questionnaire Example: - brief description of the example - UoL - some snapshots of CopperCore running it

Conclusions (I)  CLFPs not only stored in a pattern repository but implemented in an authoring tool Communicating CL expertise, common conceptual ground, etc… Facilitating its reuse!  Collage : Easy edition of potentially effective LDs by reusing and customizing best practices in CL structuring (6 CLFPs at the moment but no limit on combinations…) More CLFPs…  Preliminary evaluations have been made but further evaluation is needed… (users not familiar with CLFPs, running UoLs in real settings)

Conclusions (II)  Exploring solutions to the lack of support of LD level B and C in Collage  Exploring alternative for creating LDs including CLFPs and other structures  Printed scripts or “lessons plans” (for checking, F2F…)  Management tool for the creation of groups and binding of individuals to groups according to the CLFP hierarchy structure of an LD

Conclusions (III)  e-Learning project: TELL (Towards Effective network supported coLLaborative learning activities) ( Identifying patterns using real case studies as a starting point Other types of patterns. Patterns that involves activities (e.g. discussion) or general aspects (e.g. awareness) How to incorporate these other types of patterns into authoring tools?  Structure of a pattern language for the design of CSCL scripts: connecting rules that relates the patterns

Davinia Hernández-Leo GSIC / EMIC Group University of Valladolid, Spain COLLAGE, a Collaborative Learning Design Editor Based on Patterns UNFOLD CoP Meeting Berlin, November

Summary of the example

Jigsaw, phase 1

Pyramid

Jigsaw, phase 3

Teacher