Technological Problem Solving Seminar
- 1. Secondary School Technological Problem Solving: An Investigation of Factors Associated with Levels of Success. Dr David Morrison-Love (@dmorrisonlove) BTechEd (hons) PhD Click for: Profile LinkedIn ResearchGate 18th September 2013
- 2. Overview 1. Defining Technological Problem Solving 2. Developing a Conceptual Framework 3. Design of the Study & Cohort Identification 4. Analytical Methods: Observation & Artefact Development 5. Analytical Methods: Verbal Data 6. Findings & Conclusions 7. Questions & Discussion
- 3. PART 1 PHILOSOPHY, CONCPETUAL FRAMEWORK & STUDY DESIGN
- 4. Defining Technological Problem Solving 1. Context of Activity: Problem Solving ‘In’ vs. ‘Through’ Technology 2. Type of Problem & Resultant ‘Solving’: Ill-defined vs. well-defined (Explicit vs. Implicit) 3. Form of Solution (and intended use): Conceptual vs. Tangible Result
- 5. Defining Technological Problem Solving Within the context of secondary school technology classrooms, Technological Problem Solving: 1. Involves solving problems within the intellectual domain of technology. 2. Involves a broad range of problem types and associated solver strategies. 3. Results in a shift from conceptual ideation to tangible analogue (developed for use by others). 4. Does not deny other forms of problem solving taking place within technology classrooms.
- 6. Developing a Conceptual Framework Four modes of problem solving identified from literature: 1. Well-Defined 2. Ill-defined 3. Discrete Proactive Troubleshooting 4. Emergent/Reactive Troubleshooting
- 7. Developing a Conceptual Framework Around 20 intellectual processes identified (e.g. Williams, Halfin). • Include computing, measuring, visualising, predicting, modelling and so forth. • Stem from analysis of expert technologists; validated for classroom context (Hill & Wicklen).
- 8. Developing a Conceptual Framework Detailed review of literature allowed an original ‘Epistemic Model of Technological Problem Solving’ to be developed. Model is transformative in nature and shown on hand-out 1. It accounts for types of knowledge brought to bear and the development of ‘technological knowledge through application’.
- 9. Research Question “In terms of intellectual processes and knowledge, what are the differences in the modi operandi between groups of pupils that produced more and less successful technological solutions to a well-defined problem?”
- 10. Design of the Study Study design addressed the following key areas: 1. Epistemic Stance of Study (Interpretive/P. Positivist). 2. Appropriately targeted participant schools (broad demographic spread). 3. Design of Problem Solving Task 4. Multiple data gathering instruments (mixed method - composite representation of reality). 5. Execution of Data Gathering
- 11. Design of the Study – Sample Identification • 1 school identified from within 3 socio-demographic groups (low, average and high poverty). • Schools placement validated through multiple demographic measures (SADI, Cartsairs Scores, School Meal Subsidy). • Demographic profile compiled for each school (example profile in hand-out 2). • S2 Pupils chosen as (relative to a given class) they all share the same curricular exposure and not made subject choices. 13 groups in total.
- 12. Design of the Study – Design of Problem Solving Task • Well-defined Mode (detailed start state) • Topic: Structures (Cantilevers) - (Principle shown in hand-out 3). • Design and construct one half of a cantilever bridge using materials provided, and taking account of the stated restrictions, to exhibit high rigidity and low deflection. • Competitive Task Environment • 2 full periods to complete solutions prior to testing.
- 13. Design of the Study – Design of Problem Solving Task
- 14. Design of the Study – Design of Problem Solving Task
- 15. Design of the Study – Data Gathering Instruments * Observation in same mode throughout - Temporal Acclimatisation
- 16. Design of the Study – Data Gathering Instruments * Observation in same mode throughout - Temporal Acclimatisation
- 17. Design of the Study – Data Gathering (Hand-out 4) • Pupils in groups of 4 (as far as possible). • Single Gender Groups. • Observation rotates between groups. • Audio recording throughout. • All groups photographed at 4 min intervals.
- 18. PART 1 PHILOSOPHY, CONCPETUAL FRAMEWORK & STUDY DESIGN ANY QUESTIONS?
- 20. Selected Analytical Areas Area 1: Analysis of Photographs of Solution Development (Bespoke Procedure) Area 2: Identification of ‘Best’ and ‘Poorest’ groups (Modified Delphi) Area 3: Analysis of Verbal Data (Ranked Inductive Analysis)
- 21. Analysis of Photographs of Solution Addition or removal of materials (a development), is coded against each zone it is physically connected with.
- 22. Analysis of Photographs of Solution (Example 1) 1. Individual development in Zone D 2. Individual development in Zone A
- 23. Analysis of Photographs of Solution (Example 2) Individual development in Zone A & B
- 24. Analysis of Photographs of Solution (Example 3) Individual development in Zones A(4), C(2) & D(1). Not coded for Zone B(3) as it is not physically joined to the solution.
- 25. Analysis of Photographs of Solution (Example 4) All developments were also coded for the level of functional advantage (‘offering’ or ‘little to no’) Good Functional Advantage
- 26. Analysis of Photographs of Solution (Example 4) All developments were also coded for the level of functional advantage (‘offering’ or ‘little to no’) Poor Functional Advantage
- 27. Analysis of Photographs of Solution 0 5 10 15 20 25 30 35 40 1 2 3 4 5 6 7 8 9 E 10 11 12 13 14 15 16 17 18 E LevelofDevelopment Sample Number Physical Development of Solution Group 5 Group 7
- 28. Analysis of Photographs of Solution
- 29. Identification of ‘Best’ & ‘Poorest Groups’ • There were 13 groups in total; the study sought a best cohort or 4 and poorest cohort of 4. • There was no single correct solution. • Nature of the models meant that quantifiable physical testing was not reliable (or possible). • The criteria for physical testing were relative to a given class (was 1st place in Class A better or worse than 1st place in Class B?) • Researcher had already observed groups creating solutions – risk that choices fit preconceptions?
- 30. Identification of ‘Best’ & ‘Poorest Groups’ • Modified Delphi with 8 experts over two rounds. • Teachers with specific knowledge of structures, not from participating schools who underwent training. • Successfully ranked the 13 solutions • Face validity analysis. • Combined with physical testing data in WC Matrix. • Top 4 = Best Task Performance; Bottom 4 = Poorest Task Performance. • Researcher removed from decision making process.
- 31. Analysis of Verbal Data Group 5 Rank 1 (Best) Group 7 Rank 1 (Poorest) Dyad 1 Group 6 Rank 2 (Best) Group 13 Rank 2 (Poorest) Dyad 2 Group 12 Rank 3 (Best) Group 4 Rank 3 (Poorest) Dyad 3 Group 8 Rank 4 (Best) Group 2 Rank 4 (Poorest) Dyad 4 Most Contrasting Least Contrasting Stage 2 Analysis Stage 3 Analysis • Immersion Approach – initial themes/areas of contrast. • Two most contrasting cases. • Notional coding from C.F. • Iterative refinement of coding (7/8 rnds).
- 32. Analysis of Verbal Data • Nvivo – Direct Coding of Waveforms • Not searchable (as with transcribed text) • Group rather than individual as unit of study. • Apx. 2 Hrs/group.
- 33. PART 2 ANALYTICAL METHODS ANY QUESTIONS?
- 34. PART 3 FINDINGS & RESULTS
- 35. Emerging Frameworks Analysis of most contrasting cases gave rise to 3 frameworks that described where differences lay. • Knowledge Differences • Process Differences (inc. Declarative & Analytical Ref) • Social & Extrinsic Differences Frameworks were applied to remaining dyads to determine the extent to which this was reflected.
- 36. Emerging Frameworks (Hand Out 5) Knowledge Differences Attainment in Structures Unit Verbalised Knowledge During Activity The Solution as Manifest Knowledge Tenison & Compression Triangualtion Turning Moments Task Concpets & Principles Good Planning Results of Poor Planning Process Differences Global Process Management of Problem Solving Process Process Engagement Pattern of Solution Development Phases of Activity Fragmented Vision Poor Involvement Roles & Tasks Group Involvement Increasing Efficiency Planning Task Reflection Declarative Reflection Analytical Reflection Social & Extrinsic Differences Group Tension Competitive Dynamic Study Effects Positive Effects Neutral Effects Negative Effects Researcher Recorder
- 37. Concepts of Declarative & Analytical Reflection Declarative Reflection That which is close to the observable. A statement about something already done that does not reveal reasoning (e.g. “That’s good”, “That doesn’t move”). Analytical Reflection A statement about something already done that does reveal reasoning (e.g. “Aye, that would be better ‘cause that is stronger than a bit of thread…”)
- 38. Overall Findings by Cohort Overall, it was found that higher performing groups: 1. Engaged in more task-related discussion (>21.5%) 2. Verbalise more objective knowledge correctly with fewer deficits evident in the final artefact. 3. Demonstrate a higher level of tacit-procedural knowledge (dexterity/fine motor manipulation).
- 39. Overall Findings by Cohort
- 40. Overall Findings by Cohort
- 41. Overall Findings by Cohort Overall, it was found that higher performing groups: 4. Spent longer in the conceptual phase of problem solving, prior to commencing construction (18% longer + all had starting point established). 5. Utilise more positive managerial traits and fewer negative managerial traits (+ve 252/155; -ve 25/77). 6. Engage in more reflection and, specifically, more analytical reflection (38% longer gen; 57.5% more AR)
- 42. Overall Findings by Cohort Overall, it was found that higher performing groups: 7. Exhibit considerably lower levels of tension between group members (Hand Out 6). 91% time difference between high/low cohorts. 8. Are significantly more affected by the competitive task dynamic (>2x as many negative instances). 9. Are not as affected by influences from the study itself (65% less duration of instances).
- 43. ANY QUESTIONS