margaret green 2008

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Session B - H6-09

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Developing Functional Feedback:A Case Study

Margaret GreenUniSA

Asking for feedback

We listened to:

what the students said they wanted

what they didn’t like

how they thought the course could

be improved

We acted on it

• Feedback– Tutor feedback within 24 hrs– Structured feedback form

• consistency• Easily identifiable criterion

– Peer feedback

Theories of education

Cooper et al. (2001)Systematic review

Evidence supporting IPPOnly 30/141 studies rigorous enough

73% those did not reflect on theory

Does this infer educational strategy inadequate?

Theories of education:

No evidence

Feedback sheetGrade Hypotheses Questions Learning goals:

before tutor intervention

Group dynamics

HD Excellent hypotheses with excellent reasoning formed under all relevant headings. Excellent use of current knowledge base

Excellent range, very well ordered and phrased. Able to modify planned questions depending on the answers received.

Very specific, well described. All LG identified and excellently applied to “client” and hypotheses.

Excellent contribution from all members, taking into account different roles in a group. No help with group dynamics required

Comments:

D Very good hypotheses with very good reasoning formed under most relevant categories. Very good use of current knowledge base

Very good range, ordered and phrased. Able to modify some planned questions depending on the answers received.

Mostly specific, well described and appropriate to the problem. Most LG identified and very well applied to “client” and hypotheses.

Very good contribution from all members, taking into account different roles in a group. Little help with group dynamics required

Comments:

24 hours

Peer feedback

3= major contribution 2= some contribution1= minor contribution 0= no contribution -1= a hindrance to the group

Josh’s rating 15/15= 1 80% 80%

Jess’s rating 12/10 = 1.2 80% 96%

Jem’s rating 9/10 = 0.9 80% 72%

Jenny’s rating 5/10 = 0.5 80% 40%

ConclusionHigh learning payoff

Highly efficient Not highly efficient

Low learning payoff

25

Race 2005, p. 117

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