CRITICAL THINKING AND DEEP LEARNING: USING NSSE WITH LOCAL SURVEY RESULTS Steve Graunke IUPUI...

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CRITICAL THINKING AND DEEP LEARNING: USING NSSE WITH LOCAL SURVEY RESULTS Steve Graunke IUPUI Information Management and Institutional Research Indiana University Higher Education and Student Affairs

Transcript of CRITICAL THINKING AND DEEP LEARNING: USING NSSE WITH LOCAL SURVEY RESULTS Steve Graunke IUPUI...

Critical Thinking and Deep Learning: Using NSSE with local survey results

Critical Thinking and Deep Learning:Using NSSE with local survey resultsSteve GraunkeIUPUI Information Management and Institutional ResearchIndiana University Higher Education and Student Affairs

GoalsBackground: What is Deep Learning?Background: What does this have to do with assessment?DIRECT AND INDIRECT ASSESSMENTBackground: Principles of Undergraduate LearningBackground: Critical ThinkingDefinition: The ability of students to analyze carefully and logically information and ideas from multiple perspectives.

Outcomes: This skill is demonstrated by the ability of students to analyze complex issues and make informed decisions; synthesize information in order to arrive at reasoned conclusions; evaluate the logic, validity, and relevance of data; solve challenging problems; and use knowledge and understanding to generate and explore new questions.

IUPUI Campus Bulletin: http://www.iupui.edu/~bulletin/iupui/2012-2014/undergraduate/principles.shtmlMethodology: IUPUI Continuing Student SurveyMethodology: NSSE DAL scales* Nelson Laird, T.F., Garver, A.K., Niskod-Dossett, A. S., & Banks, J.V. (2008)Methods: Participants105 studentsOther Independent VariablesResults: NSSE DAL scale AlphasOverall Deep Approaches to Learning Scale = 0.655Higher Order Learning subscale = 0.829Integrative Learning subscale = 0.631Reflective Learning subscale = 0.865Results: NSSE MeansVariableNMeanStd Error of Mean95% CL for MeanCT (Critical Thinking)1053.2190.0613.0983.340fem_flg (Female flag)1050.6000.0480.5050.694Sen_flg (Senior flag)1050.3620.0470.2690.455soft_flg (soft discipline flag)1050.6290.0470.5350.722DAL (Full Deep Approaches Scale)1052.7490.0512.6492.849HOL (Higher Order Learning) 1052.9760.0692.8393.114IL (Integrative Learning)1052.5790.0502.4802.678RL (Reflective Learning)1052.6920.0752.5432.841Results: Correlations with overall DAL scalefem_flgSen_flgsoft_flgDALCT (Critical Thinking)0.0190.1480.0610.402fem_flg (Female flag)---0.0730.3380.147Sen_flg (Senior flag)--

0.0870.151soft_flg (soft discipline flag)--

0.328DAL (Full Deep Approaches Scale)--

Results: Model Using full DAL scaleBStandard ErrortIntercept1.8700.3695.06*Female-0.010-0.0080.115-0.09Senior0.1200.0920.1310.92Soft discipline flag-0.104-0.0800.137-0.76Deep Approaches to Learning0.5010.4150.1413.56*F = 6.17Standard Error of Estimate = 0.582R squared = 0.175Results: Correlation with Individual DAL scalesfem_flgSen_flgsoft_flgHOLILRLCT (Critical Thinking)0.0190.1480.0610.1950.3880.372fem_flg (Female flag)---0.0730.3380.0820.1260.136Sen_flg (Senior flag)--

0.0870.1510.1700.052soft_flg (soft discipline flag)--

0.2030.2920.281HOL (Higher-order Learning)--

0.3250.427IL (Integrative learning)--

0.447RL (Reflective Learning)--Results: Correlation with Individual DAL scalesfem_flgSen_flgsoft_flgHOLILRLCT (Critical Thinking)0.0190.1480.0610.1950.3880.372fem_flg (Female flag)---0.0730.3380.0820.1260.136Sen_flg (Senior flag)--

0.0870.1510.1700.052soft_flg (soft discipline flag)--

0.2030.2920.281HOL (Higher-order Learning)--

0.3250.427IL (Integrative learning)--

0.447RL (Reflective Learning)--Results: Higher Order Learning and integrative LearningBStandard ErrortIntercept1.8700.4014.66*Female-0.007-0.0060.114-0.07Senior0.1030.0790.1360.76Soft discipline flag-0.088-0.0680.128-0.68Higher Order Learning0.0680.0770.0970.70Integrative Learning0.4530.3710.1243.67*F = 6.16Standard Error of Estimate = 0.588R squared = 0.166Results: Reflective Learning ModelBStandard ErrortIntercept2.3730.2399.95*Female-0.006-0.0050.122-0.05Senior0.1730.1330.1251.38Soft discipline flag-0.072-0.0560.138-0.52Reflective Learning0.3090.3820.0853.66*F = 6.12Standard Error of Estimate = 0.588R squared = 0.158FindingsLimitationsWhat does this mean?