Using dual-mapping learning approach to visualize the connection between problem solving and knowledge

construction

Bian WU

CITE Research Symposium 2011  HKU

Contents

2

1 Introduction

2 Literature review

3 Learning approach design

4 Future work

1 Introduction1.1 Problem statement

1.2 Research goal

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• Cause of problem

The connection between problem solving solution and problem solver’s knowledge base is like a “black box”, for both tutors and learners.

• Obstacle for instruction

Mystery of this connection does little help to support learners in the development of professional expertise (Kinchin, 2008).

• Possible solution

Designing appropriate tools (techniques) to externalize problem solver’s mental activities (i.e. open the “black box”). (Hoffman & Lintern, 2006)

1.1 Problem statement

Kinchin, I. M., Cabot, L. B., & Hay, D. B. (2008). Using concept mapping to locate the tacit dimension of clinical expertise: towards a theoretical framework to support critical reflection on teaching. Learning in Health & Social Care, 7(2), 93-104. Hoffman, K., Hosokawa, M., Blake, R., Jr., Headrick, L., & Johnson, G. (2006). Problem-based learning outcomes: ten years of experience at the University of Missouri-Columbia School of Medicine. Acad Med, 81(7), 617-625.

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• General focus Study the development of professional expertise (e.g. clinical problem

solving competence) in terms of problem solving skill and personal knowledge construction from epistemological perspective.

• Aim of the study Propose a tentative learning approach in support of problem solving

and knowledge construction based on proper theories;

Implement this learning approach by designing an online learning environment

Assess learners behavior on the environment to prove the effectiveness of the approach

1.2 Research goal

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2 Literature Review

2.1 Problem solving & knowledge construction

– Term clarification

– Mutual relation

2.2 Previous studies on problem solving expertise development

– Instructional strategies to develop problem solving expertise

– Possible solutions to externalize mental models

– Dual mapping to visualize connections

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Term clarification of problem solving Investigate or analyze the cause or nature of a condition or problem

(Webster Dictionary, 1977)

Use of incoming information to guide subsequent data acquisition and tends to foster more speculation in judgment (Morgan and Engel, 1969)

Heavily knowledge-dependent that expertise in problem solving develops in line with the evolution of the domain knowledge base (Groves, 2008)

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2.1 Problem solving & knowledge construction(1)

Morgan and G.L. Engel (1969). The Clinical Approach to the Patient, W.B. Saunders, PhiladelphiaGroves, M. (2008). The diagnostic process in medical practice. New York: Nova Biomedical Books.

Term clarification of knowledge construction Through processes of accommodation and assimilation, individuals

construct new knowledge from their experiences (Piaget, 1950)

Knowledge construction includes assembling of knowledge, knowledge being sorted out, refined, or reorganized (Seel, 2003)

Knowledge construction during problem solving (not during instruction) (Phye, 2001)

Reconstruction of old knowledge base plus the dynamic construction of new knowledge based on old reconstructed knowledge base

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2.1 Problem solving & knowledge construction(2)

Piaget, J. (1950). The psychology of intelligence. London: Routledge & Kegan Paul.Phye, G. D. (2001). Problem-solving instruction and problem-solving transfer: The correspondence issue. Journal of Educational Psychology, 93(3), 571-578. Seel, N. M. (2003). Model-Centered Learning and Instruction. Technology, Instruction, Cognition and Learning, 1, 59-85.

Mutual relation From problem solving to knowledge construction

A model of successful learning: Adaptive experts are continually learning and updating their knowledge based on their experiences with novel problems and situational demands (Bransford et al., 1999; Schwatz et al., 2005).

From knowledge construction to problem solving Knowledge base reconstruction is a primary antecedent for the construction of a solution in a problem-solving context (Phye, 2001; Norman, 2005; Schmidt, 2006).

Externalize the connection between problem solving and knowledge construction is utmost important in learning (Grave et al., 1996; Kinchin et al., 2008)

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2.1 Problem solving & knowledge construction(3)

Instructional strategies to develop problem solving expertise Previous studies

Experience (Dewey, 1938); Practice with feedback (Gagné, 1985); Failure (Schank, 1989); Deliberate practice (Ericcson, 2008)

LimitationsKnowledge construction is often neglected (Norman, 2005)

Knowledge transfer is difficult(Patel, Yoskowitz, & Arocha, 2007)

Assessment focuses more on problem solving performance, but not on conceptual change (Spector, 2003)

Causes

Fails to consider problem solvers’ mental model (i.e. working memory, long-term memory, or the intricate relations between them) (Kirschner et al., 2006; Neville, 2009)

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2.2 Problem solving expertise development(1)

Possible solutions to externalize mental models Think aloud protocol (Ericsson, 1998)

Knowledge visualization (Spector, 2006)

Argument map to present problem solving solution (Fox, et al., 2007; Rittel & Webber, 1984; Kirschner et al., 2003)

Concept map to present domain knowledge base (Novak & Canas, 2006; Pinto & Zeitz, 1997)

2.2 Problem solving expertise development(2)

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Dual mapping to visualize connections

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Working memory

Long-term memory

Incoming information

Retrieve

Store

Knowledge construction

Problem solving

Argument mapping

Concept mapping

?

Knowledge base

Solution

Mental activity

Physical activity

2.2 Problem solving expertise development(3)

3 Learning approach design

3.1 Conceptual framework

3.2 Dual mapping learning process modelling

3.3 Prototype design

3.4 “ELICIT” principles to guide the design

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Interactions between three types of systems, i.e. internal conceptual systems;

representational systems and external systems (Seel, 2003)

3.1 Conceptual framework

Knowledge base evolution Cognitive process visualization

Information perception

Learning by doing

Learner model Learning context

Cognitive structure High-fidelity simulation cases (Learning Resources) WM LTM

Dual mapping tool

Problem Solving Knowledge

Construction

Knowledge Acquisition Concept Mapping

of Domain Knowledge

Knowledge Application

Argument Mapping of Problem Solving /Reasoning Process

Seel, N. M. (2003). Model-centered learning and instruction. Technology, Instruction, Cognition and Instruction, 1(1), 59-85. 14

EA

State1:Data collection

State4:Hypothesis evaluation

State3:Hypothesis generation

State5:Further investigation

Sub-state 4-4:Identify leading Hx

Sub-state 1-1:Chief complaint

Sub-state 1-2:Patient history/ current state

Sub-state 1-3:Physical exam

Sub-state 3-1:Hx generation

Sub-state 3-2:Reasoning

Sub-state 4-1:List of Differential Hx

Sub-state 4-2:Evaluate Confidence in Hx

Sub-state 4-5:Identify loose ends

Sub-state 4-3:Evidence appraise

Sub-state 5-1:Order test

Sub-state 5-3:Interpret test result

Sub-state 5-2:Select test result

State6:Conclusion

State2:Knowledge retrieval

Sub-state 2-1:Prototype extraction

Sub-state 2-2:Semantic activation

State7:Knowledge construction

Sub-state 7-1:Constructing new knowledge

Sub-state 7-2:Reorganizing knowledge

Information obtaining

Concept mapping

Argument mapping

3.2 Dual mapping learning process modelling

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3.3 Prototype design (1)Argument mapProblem solving context

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3.3 Prototype design (2)Argument map Concept map Previous argument map

(E)xplict goals Using dual-mapping(argument mapping & concept mapping) to improve problem solving performance and domain knowledge understanding

(L)earning activitiesInformation obtaining(action selection, action justification, information identification, ...); argument mapping; concept mapping

(I)nteresting informationIntegrating relevant information in the map will be useful

(C)lear connectionsDescribing connections through links, text, and iconsStructuring connections to make thinking process clear

(I)ntegrated overviewSimple map interface via pre-defined filtering, or highlighting techniqueBig picture to visualize the connections among the most relevant points

(T)rail as marked routeTracing learning pathway

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3.4 “ELICIT”principles to guide the design

Okada, A. (2010). Eliciting Thinking Skills with Inquiry Maps inn CLE. In P. L. Torres & R. d. C. V. Marriott (Eds.), Handbook of research on collaborative learning using concept mapping. Hershey, PA: Information Science Reference.

4 Future work4.1 Evaluation method

4.2 Further study

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RQ: What is the effect of the dual mapping learning tool on problem solving performance and problem solver’s domain knowledge? 30 medical students of year 2 or above

Randomly assigned into two groups

4 kidney cases, 1hr/case

case1 (pre-test), case2 & case3 (learning), case4 (post-test)

control group: text-based

experimental group: dual mapping tool

Assessment:

5 problem solving questions of the test case

5 questions of domain knowledge

2 domain experts as independent raters

4.1 Evaluation method

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How do students develop problem solving expertise as

they adopt dual-mapping learning approach to learn

problem solving?

How can students be effectively scaffolded when they

adopt the dual-mapping learning approach to learn

problem solving?

4.2 Further study

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Bransford, J. D., & Schwartz, D. L. (1999). Rethinking transfer: A simple proposal with

multiple implications. In A. Iran-Nejad & P. D. Pearson (Eds.), Review of Research in

Education. Washington DC: American Educational Research Association.

Ericsson, K. A. (2008). Deliberate Practice and Acquisition of Expert Performance: A

General Overview. Academic Emergency

Kirschner, P. A. (2003). Visualizing argumentation : software tools for collaborative and

educational sense-making. London: Springer.

Norman, G. R. (2005). Editorial - Beyond PBL. Advances in Health Sciences Education, 9,

257-260.

Novak, J. D., & Canas, A. J. (2006). The Theory Underlying Concept Maps and How to

Construct Them. Pensacola, FL: Institute for Human and Machine Cognition.

Patel, V. L., Yoskowitz, N. A., & Arocha, J. F. (2007). Towards effective evaluation and

reform in medical education: a cognitive and learning sciences perspective. Adv Health

Sci Educ.

Schmidt, H. J. (2006). Alternative approaches to concept mapping and implications for

medical education: Commentary on reliability, validity and future research directions.

Advances in Health Sciences Education, 11(1), 69-76.

Spector, J. M. (2006). A methodology for assessing learning in complex and ill-structured

task domains. Innovations in Education and Teaching International, 43(2), 109-120.

References

Comments and suggestions are welcome

BACK

Node observation

Node generation

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Structuring reasoning link

Simplifying concept node link

Connection across maps

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Hide justification

Hide evidence

Highlight nodes

Adjust weights of Hx

Support CBR

Logfile data of user records

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