Problem Formulation and Resolution in Online Problem-based Learning

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Presentation to the CADE conference, Montreal, May 2006 with Rick Kenny

Transcript of Problem Formulation and Resolution in Online Problem-based Learning

Problem Formulation & Resolution in Online Problem-based LearningRick Kenny, Athabasca UniversityMark Bullen, British Columbia Institute of Technology

Introduction

• E-learning pedagogies must be defensible

• E-learning pedagogies are evolving• E-learning instructional design must be guided by research and theory

• Examination of problem-based learning in an online course

Authentic PBL Characteristics

• Problem-based• Problem-solving• Student – centred• Self-directed learning• Reflection

Effectiveness of PBL

• Meta-analyses examining use of PBL in Medical Education

• Conventional curricula outperformed PBL on measures of basic science

• PBL students scored higher on clinical examinations

• PBL most positive effects when constructs assessed at level of understanding principles that link concepts.

Methodology

Research Questions– What evidence is there that PBL fosters problem-solving behaviours and skills in undergraduate Agricultural Sciences students?

– What is the nature of the problem-solving process which students apply when engaged in PBL activities?

Methodology

Research Setting– Undergraduate Agroecology course– Fully online, WebCT

Participants– 11 students– Two PBL groups

Methodology

Methodology

Context

• PBL work took place in asynchronous discussion forums

• Instructor participated by monitoring, guiding, clarifying

Analysis

• Content analysis based on Murphy’s OAD instrument (2004, 2005)

• Based on Jonassen’s (1997) conceptual framework

• Two main categories– Problem formulation– Problem resolution

Methodology – Modified InstrumentProblem formulation Indicator

Defining PBL Space Agreeing with problem as presented in OAD

Specifying ways that the problem manifests itself

Redefining problem within problem space

Minimizing and/or denying problem

Identifying extent of problem

Identifying causes of problem

Articulating a problem outside problem space

Building knowledge Identifying unknowns in knowledge

Seeking information to resolve lack of knowledge

Clarifying (meaning, importance, accuracy of) information

Accessing and reporting on sources of information

Identifying value of information

Reflecting on one’s thinking

Methodology – Modified Instrument

Problem resolution

Indicator

Identifying solutions

Proposing solutions

Hypothesizing about solutions

Evaluating solutions

Agreeing with solutions proposed by others

Weighing and comparing alternative solutions

Critiquing solutions

Rejecting/eliminating solutions judged unworkable

Reaching conclusions

Coming to agreement about solutions

Acting on solutions

Planning to take action to resolve the problem

Results - Pass 1

Code Coder 2 Coder 1 Count % Count %

F 372 71.0 345 65.8 R 124 23.7 171 32.6

Other 28 5.3 8 1.5

Results - Pass 2

Process Coder 1 Coder 3

Cases % Cases %

Problem Formulation

Defining problem space

11 2.9 44 11.7

Building knowledge 218 57.8 191 50.7

Problem Resolution

Identifying solutions

54 14.3 37 9.8

Evaluating solutions

52 13.8 39 10.3

Reaching conclusions

16 4.2 0 0

Acting on solutions

0 0 0 0

Other 26 6.9 66 17.5

Results

• Only coded two levels: category, process

• Cohen’s kappa used for inter-coder agreement (Cohen, 1960)

• Categories– Case 2, Group 1: 0.449– Case 2, Group 2: 0.593

• Processes– Case 2, Group 1: 0.344

Issues

• The PFR process and PBL• Unit of analysis• Representing the PFR process in a PBL context

• Training

Contact Information

Rick KennyAssociate ProfessorCentre for Distance EducationAthabasca Universityrickk@athabascau.ca

Mark BullenAssociate DeanLearning & Teaching CentreBC Institute of TechnologyMark_bullen@bcit.ca