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Collaborative teaching and learning, construction of knowledge, cognition and metacognition

Three state-of-the-art literature reviews written by Hannelore Platteeuw, Emilie Bekaert and Evelien Van Hulle (UGent)

Hannelore Platteeuw

on 26 August 2010

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Transcript of Collaborative teaching and learning, construction of knowledge, cognition and metacognition

State-of-the-art literature reviews
on collaborative teaching and learning models,
construction of knowledge and
cognition and metacognition. Content of the presentation:

1. Teaching and learning models
2. Construction of knowledge
3. Cognition and metacognition
4. Links between the three types of models 1. Teaching and learning models Constructivism
Inquiry learning and inquiry teaching Problem-based learning

1. Clear out vague terms and concepts to the other group members.
2. Define the problem(s). What needs to be discussed?
3. Analyze the problem(s). Make a brief inventory of everybody's first solutions and
explanations, e.g. by brainstorming.
4. Cluster ideas systematically. Try to give explanations based on what you already know.
5. Formulate learning goals by determining what you do not know, on what points you do not
agree and by formulating questions. Based on those questions, you can start your research.
6. Self study. Search for information outside the group in books, articles, magazines, videos, the
7. Report and integrate the new information into the group. Structure the newly found
information and adapt this new knowledge to the problem. Effective learning process

National training laboratories (Maine) 4. ICT-based environments

5. Scripting and structuring

e.g. Role taking:
starter, summarizer, moderator, theoretician, source researcher

e.g. Jigsaw:
1. Students are divided into groups (5 or 6 persons/group), and in each group there are students from different genders, ethnicities, races and abilities.
2. In each group, there is one leader, namely the most mature student.
3. The learning material is divided into segments, one for each person of the group.
4. Each student is told to learn one part of the material.
5. The students have enough time to read their material two or more times. They don't really have to learn it by heart.
6. The students from the different groups who have read the same segments, are put together in an expert group. They discuss the material and practise for a presentation in their home group.
7. The students go back to the main group.
8. Each student presents her segment to the group and the others ask questions.
9. The teacher walks around and observes the different group processes. The group leader can handle difficulties, if needed with help from the teacher.
10. At the end of the lesson the teacher gives a quiz on the learning materials. The students realize that the session was not just a game, but a real lesson.

e.g. Six Thinking Hats, Grid script, ArgueGraph,... 6. Teacher support 2. Construction of knowledge Framework + models that derive from that framework: Henri
1.Participative dimension
2.Social dimension
3.Interactive dimension
4.Cognitive dimension
5.Metacognitive dimension.
Gunawardena, Lowe, and Anderson:

=> present a tool to examine the social construction of knowledge in computer conferencing
They outlined five phases of knowledge construction:
1. Sharing and comparing of information
2. The discovery and exploration of dissonance or inconsistency among ideas
3. the negotiation of meaning and co-construction of knowledge
4. Testing and modification
5. final statements of agreement and/or the application of newly constructed meanings (van der Meijden, 2005).

Main advantages:
•Its focus on the overall pattern of knowledge construction
•Its appropriateness for use in constructivist and collaborative, student centered learning contexts.
•Its straightforwardness and simplicity of use.
•Its adaptability to different evaluation purposes

Models of knowledge Construction that focus on online environments: Schellens & Valcke
investigated whether asynchronous discussion groups can enhance knowledge construction. They used several models described before. Although I think this is a good model that can be of great use, I believe it would be a little bit too complicated to use for this project.
This model was inspired by Henri and examines how university students construct knowledge during CSCL interactions and the level of information processing involved. They distinguish five stages of understanding:
1. Pre structural phase: activities are off-task
2. unistructural phase: activities are focused on only one aspect of a task
3. multistructural phase: several aspects of a task are mastered but not connected with each other
4. relational stage: several aspects of the task are acquired and connected with each other
5. extended abstract stage: students reflect on ideas and integrate new knowledge into existing structures

Pena-Shaff & Nicholls
were also inspired by Henri. They analyzed student participation, interaction and knowledge construction in a synchronous computer bulletin-board system. They present a Knowledge Construction Category System and Indicators.
Weinberger & Fisher
Propose this model in order to measure the influence of scripts on specific processes of argumentative knowledge construction. They present a framework to be able to analyze multiple dimensions of knowledge construction in CSCL, namely
(1) the participation dimension
(2) the epistemic dimension
(3) the argument dimension
(4) the dimension of social models of co-construction.
This model of collaborative knowledge-building incorporates insights from various theories of understanding and learning to be able to provide a useful conceptual framework for the design of CSCL software, specifically collaborative knowledge-building environments. He defines a sequence of typical phases of social knowledge-building. Although this could be a useful model I think it would be difficult to implement this in the current project.
‘Cress & Kimmerle’ & ‘Yap & Chia’
These models are interesting and can provide inspiration however it would be difficult to implement these.
Taxonomies of knowledge construction: Biggs & Collis
Developed the solo taxonomy (Structure of Observed Learning Outcomes). It describes student’s understanding through five different stages:
1 Pre-structural: here students are simply acquiring bits of unconnected information, which have no organization and make no sense.
2 Unistructural: simple and obvious connections are made, but their significance is not grasped.
3 Multistructural: a number of connections may be made, but the meta-connections between them are missed, as is their significance for the whole.
4 Relational level: the student is now able to appreciate the significance of the parts in relation to the whole.
5 At the extended abstract level, the student is making connections not only within the given subject area, but also beyond it, able to generalize and transfer the principles and ideas underlying the specific instance

Bloom (revised)
In the revision active verbs are given and two categories were changed as to their hierarchical position: evaluation and creating (Krathwohl, 2002) (Valcke, 2009).
This implies that it is now applicable to analyze learning outcomes as well as the cognitive process used by students to finish a task.
1. Knowledge: arrange, define, duplicate, label, list, memorize, name, order, recognize, relate, recall, repeat, reproduce state.
2. Comprehension: classify, describe, discuss, explain, express, identify, indicate, locate, recognize, report, restate, review, select, translate,
3. Application: apply, choose, demonstrate, dramatize, employ, illustrate, interpret, operate, practice, schedule, sketch, solve, use, write.
4. Analysis: analyze, appraise, calculate, categorize, compare, contrast, criticize, differentiate, discriminate, distinguish, examine, experiment, question, test.
5. Synthesis: arrange, assemble, collect, compose, construct, create, design, develop, formulate, manage, organize, plan, prepare, propose, set up, write
6. Evaluation: appraise, argue, assess, attach, choose compare, defend estimate, judge, predict, rate, core, select, support, value, evaluate
3. Cognition and metacognition 4. Links between the three types of models Definitions: Metacognition

Flavell (1977): thinking about the own thinking, a sort of meta-thinking
Flavell (1979): processes used to regulate and monitor memory and cognition
Flavell (1979): knowledge and cognition about cognitive phenomena
Flavell (1985): cognition about cognition
Schraw & Dennison (1994): the ability to reflect upon, understand, and control one’s learning
Valcke (2005): a type of ‘executive control processes’ who observe the knowledge-processing on a quite conscious manner
Veenman (2006): higher-order cognition about cognition
Distinctions in metacognition (e.g.):

- Nelson (1996); Veenman et al. (2006); Shamir, Mevarech & Gida (2009):
-‘object’-level of cognition: level on which cognitive activity takes place
-‘metacognitive’ level(: with meta: about): governs the object-level

Relationship between these two levels: a reciprocal flow between monitoring and control
Monitoring: information about the state of the object-level is conveyed to the meta-level
Control : instructions from the meta-level are transmitted to the object-level

- Veenman et al. (2006); Desoete (2010)
Most common distinction:
metacognitive skills (steering and regulating of the own thinking and learning processes) metacognitive knowledge (being aware of the own cognitive competences)
--> Takes time and effort

+ Metacognitive beliefs (visions on intelligence and learning) Cognition versus metacognition

1) Veenman et al. (2006): higher-order agent overlooking and governing the cognitive system, while simultaneously being part of it.

2) Nelson (1999): metacognition is a particular kind of cognition
--> Occurs when one aspect of cognition is monitoring or controlling another aspect of cognition

3) Hamers en Overtoom (1997a): schedule of cognition and metacognition in mathematics
Models of metacognition 1) Flavell
a)Metacognitive knowledge
b)Metacognitive experiences
c)Goals (or tasks), and
d)Actions (or strategies)
2) Brown (1987): determinants for the present state of affairs about metacognition:
a) Research with regard to introspection, the verbal reporting about the own cognitive activity (with its possibilities and impossibilities)
b) Research with regard to ‘executive control’, full attention goes to tasks of planning and the resolvement of problems
c) Self-regulation (also mentioned in review 1)
d) “Regulation-trough-the-other”, from the inter-individual context to the intra-individual context
3a) Flavell 3b) Brown e.g. Valcke (2005) distinguishes between the moments of the measurement of metacognition:
-Before a concrete cognitive activity Prospective measurement E.g. questionnaires
-During a concrete cognitive activitiy Concurrent measurement E.g. observation, hypothetical problems, peer tutoring, …
-After a concrete cognitive activitiy Retrospective measurement E.g. questionnaires

Hadwin et al. (2007): log-file-data to construct profiles of self-regulated learning activity in four ways:
a.frequency of studying events,
b.patterns of studying activity,
c.timing and sequencing of events, and
d.content analyses of students’ notes and summaries.

-gStudy: a cross-platform software tool for researching learning
-‘trace data’: log data that are precise time-stamped records of everything a student does in gStudy So, what research are we finally searching for?
- multi-method research e.g. Whitebread et al. (2009): C.Ind.Coding Scheme

-Video taping
-Log-file registration
-CRS: classroom response system Computer-mediated communication (CMC): Asynchronuous (e.g. email, forum) Vs. Synchronuous (e.g. chat)
Face-to-face communication (F2F)

Computer-supported collaborative learning (CSCL) environments
e.g. Web-based inquiry science environment (WISE)
e.g. Science Created by You (SCY)

Veerman & Veldhuis-Diermanse
They developed a categorising model of knowledge construction based on social constructivist principles. It consist out of two major categories: task related and non-task related discussions: Hong & Lee
=> wanted to document the different types of knowledge construction during asynchronous conferencing and evaluate the quality of that knowledge construction in a blended learning environment for a postgraduate course at a Malaysian tertiary institution
They modified Veerman and Veldhuis-Diermanse’s model by adding different categories
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