STRATEGIES FOR ENGAGING STUDENTS IN
Components of Technological Knowledge
Technological Modelling – Level 4 |
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Teacher Guidance Level 4 To support students to develop understanding of Technological Modelling at Level 4, teachers could:
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Indicators of Progression |
Teaching Strategy |
Explanation |
Explain why it is necessary to consider both what 'can' be done and what 'should' be done when making design decisions. |
Student investigation of what they consider an unfavorable outcome. |
Students investigate an existing technological outcome that they believe 'should not' have been made (weapons? nanotechnology? cell phones?), and present their justification as to why it 'shouldn't' have been created.
Class creates a bank of questions that need to/should be considered when developing a technological outcome, for example:
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Explain why different forms of functional modelling are needed to fully explore possibilities and different types of data. |
Weird or unsuccessful products that did not fully explore possibilities and different types of data. |
Explore weird or unsuccessful products that did not do enough functional modelling before production. This meant that all possibilities and issues were not fully explored before they were developed and implemented as technological outcomes (eg, McDonalds McDLT flop). |
Introduce and explore what CAD is and discuss what kind of data it provides as a functional model. |
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Discuss examples of prototyping to explain how evidence gathered provided justification for evaluating a technological outcome as fit for purpose or in need of refinement. |
Bad designs/prototypes. |
Students find examples of bad designs/prototypes and discuss their intended fitness for purpose (Bad designs site). Students to look at:
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Weird or unsuccessful products where the prototyping stage could have provided information about fitness for purpose. |
Weird or unsuccessful products where the prototyping stage could have provided info re fitness for purpose. This meant that they did not fully explore all possibilities and issues prior to them being developed and implemented as technological outcomes (eg, McDonalds McDLT flop). |
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