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1 Economics Students Approaches to Learning in Different Assessment Regimes Economics Students Approaches to Learning in Different Assessment Regimes Tommy.

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Presentation on theme: "1 Economics Students Approaches to Learning in Different Assessment Regimes Economics Students Approaches to Learning in Different Assessment Regimes Tommy."— Presentation transcript:

1 1 Economics Students Approaches to Learning in Different Assessment Regimes Economics Students Approaches to Learning in Different Assessment Regimes Tommy Tang & Tim Robinson Queensland University of Technology, Australia Paper presented at the Third International Conference in Developments in Economics and Business Education, Cambridge, UK 1-2 Sept 2005.

2 2 Outline 1.Introduction Input-output approach and its limitations Biggs 3-P Model of Learning 2.The study 3.Findings & Discussions 4. Conclusion

3 3 Introduction Input-output Approach Q = f(X 1, X 2, X 3, … ) whereQ = Learning output (marks) X 1 = Aptitude X 2 = Age X 3 = Parental occupation … Limitations

4 4 Biggs 3-P Model of Learning Student characteristics Teaching context Learning approach Learning outcome Feedback PresageProcess Product (Biggs 1989, modified)

5 5 An econometric approach which assesses the impact of easily measurable independent variables on a single dependent variable may simply miss important responses to teaching change. (Shanahan et al., 1997) An econometric approach which assesses the impact of easily measurable independent variables on a single dependent variable may simply miss important responses to teaching change. (Shanahan et al., 1997)

6 6 Research Objective: Construct instruments to investigate students perceptions of assessment, and learning strategies for assessment Construction of Instrument: SPQ (Biggs), ASI (Entwistle & Ramsden), MSLQ (Pintrich et al), LAQ (Thomas) Focus groups Student surveys The Study

7 7 Subjects: Students in: Economics 1 Economics 2 Business cycles & economic growth Sample size Week 1: n = 1146 Week 2: n = 648

8 8 Findings & Discussions

9 9 Exploratory Factor Analysis (EFA) MCQ Essay Assignment Essay Exam (KMO=0.747) (KMO = 0.805) (KMO = 0.793) HighLow RW2_MCQ.709 CRIT_MCQ.603 DU2_MCQ.560 INTG_MCQ.528 RHI_MCQ.483 RW1_MCQ.461 FDBK_MCQ.387 RLOW_MCQ.333.311 MEM3_MCQ.792 MEM1_MCQ.685 MEM2_MCQ.570 MEM4_MCQ.231.306 DU1_MCQ.222 HighLow RW2_ASS.756 DU2_ASS.649 INTG_ASS.576 CRIT_ASS.568 RW1_ASS.543 FDBK_ASS.525 RHI_ASS.501 RLOW_ASS.379.341 MEM3_ASS.759 MEM1_ASS.641 MEM2_ASS.515 MEM4_ASS.261.357 DU1_ASS HighLow RW2_EX.657 DU2_EX.586 CRIT_EX.545 RW1_EX.513 INTG_EX.497 FDBK_EX.494 RHI_EX.417.322 MEM3_EX.711 MEM2_EX.706 MEM1_EX.587 RLOW_EX.288.548 MEM4_EX.236.347 DU1_EX Perceptions of Assessment

10 10 Confirmatory Factor Analysis (CFA) The final model MCQEssayExam 2 /df 2.1162.4242.458 CFI0.9630.9640.961 RMSEA0.0440.0470.048

11 11 Learning Strategies for Assessment UnderstandingReproducingIntegration Rote- memorising U6.529 R6.509 U3.496 U1.463 U2.400 U4.383 S10.518 S6.473 S11.456 S7.453 S8.406 U5.245.318 -.295 R2.726 R1.716 R5.623 R4.448 R3.239 S4.683 S3.594 S2.225.497 S1.434 KMO = 0.835 EFA

12 12 CFA ( 2 /df = 2.22, CFI = 0.949 and RMSEA = 0.034) The final model

13 13 CFA – 2 nd order factor model ( 2 /df = 2.610, CFI = 0.938, RMSEA = 0.038 )

14 14 Assessment type Level of intellectual skill NMean Std. dev. MCQ LOW5783.8980.7953 HIGH5653.0630.6495 Essay Exam LOW6133.7360.7932 HIGH6003.5910.5613 Essay Assignment LOW6412.6010.8137 HIGH6303.8960.6012 Perceptions of Assessment

15 15 Approaches Assessment type NMeanStd. Dev. Understanding MCQ5703.4690.6489 Essay Assignm6283.5130.6194 Essay Exam6043.6240.5937 Integrating MCQ5663.5630.7558 Essay Assignm6243.7210.7185 Essay Exam5983.7090.7257 Reproducing MCQ5703.6400.6921 Essay Assignm6303.2580.7144 Essay Exam6033.5420.7073 Rote- memorising MCQ5723.3180.7802 Essay Assignm6283.0710.8059 Essay Exam6033.2630.7742 Learning Approaches for Assessment

16 16 LOW_mcqLOW_exLOW_assHIGH_mcqHIGH_exHIGH_ass LOW_mcq 1 (578) LOW_ex.472** 1 (560)(613) LOW_ass.105*.178** 1 (576)(613)(641) HIGH_mcq -.063-.068.224**1 (563)(546)(562)(565) HIGH_ex.107*.050.089*.329** 1 (546)(599) (543)(600) HIGH_ass.151**.166**-.043.093*.499** 1 (564)(601)(628)(562)(599)(630) ** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed). Stability of Perceptions

17 17 ApproachAssessment Pre-course factors Conclusion Implication for Future Research (Stability)

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