Seeking Empirical Validity in an Assurance of Learning System

Business schools have established measurement tools to support their assurance of learning (AoL) systems and to assess student achievement of learning objectives. However, business schools have not required their tools to be empirically validated, thus ensuring that they measure what they are intended to measure. The authors propose confirmatory factor analysis (CFA) be utilized by business schools to evaluate AoL measurement systems. They illustrate a CFA model used to evaluate the measurement tools at their college. The authors’ approach is in its initial steps, currently evaluating individual measurement tools, but the authors are working toward developing a system that can evaluate the entire AoL measurement system.

[1]  Susan D. Sampson,et al.  Assurance of Learning and Outcomes Assessment: a Case Study of Assessment of a Marketing Curriculum , 2008 .

[2]  Peter M. Bentler,et al.  Estimates and tests in structural equation modeling. , 1995 .

[3]  P. Bentler,et al.  Comparative fit indexes in structural models. , 1990, Psychological bulletin.

[4]  E. Romero,et al.  AACSB Accreditation: Addressing Faculty Concerns , 2008 .

[5]  Dennis Zocco A Recursive Process Model for Aacsb Assurance of Learning , 2011 .

[6]  Nathan Garrett,et al.  Assessment of Business Programs: A Review of Two Models , 2012 .

[7]  Assurance of Learning (AoL) Methods Just Have to Be Good Enough , 2007 .

[8]  Gail Corbitt,et al.  Program Assessment: Getting to a Practical How-To Model , 2009 .

[9]  An assurance of learning success model: toward closing the feedback loop , 2008 .

[10]  Kathryn A. Martell,et al.  Assessing Student Learning: Are Business Schools Making the Grade? , 2007 .

[11]  P. B. Hess,et al.  A Research-based Approach to Continuous Improvement in Business Education , 2007 .

[12]  Dana Schwieger,et al.  Integrating Soft Skills Assessment through University, College, and Programmatic Efforts at an AACSB Accredited Institution , 2008, J. Inf. Syst. Educ..

[13]  Bradley J. Sleeper,et al.  Self-Efficacy Toward Service, Civic Participation and the Business Student: Scale Development and Validation , 2004 .

[14]  R. P. McDonald,et al.  Goodness-of-fit indexes in confirmatory factor analysis : The effect of sample size , 1988 .

[15]  P. Bentler,et al.  Significance Tests and Goodness of Fit in the Analysis of Covariance Structures , 1980 .

[16]  J. H. Steiger Structural Model Evaluation and Modification: An Interval Estimation Approach. , 1990, Multivariate behavioral research.

[17]  P. Bentler,et al.  Cutoff criteria for fit indexes in covariance structure analysis : Conventional criteria versus new alternatives , 1999 .

[18]  Rex B. Kline,et al.  Principles and Practice of Structural Equation Modeling , 1998 .

[19]  Thomas L. Keon,et al.  Summary of Assessment in Higher Education and the Management of Student-Learning Data , 2008 .

[20]  Sieh-Hwa Lin,et al.  Book Review: Kline, R. B. (2005). Principles and Practice of Structural Equation Modeling (2nd ed.). New York: Guilford. 366 pp., $40.50 paperback, ISBN 978-1-57230-690-5 , 2010 .

[21]  C. Fornell,et al.  Evaluating structural equation models with unobservable variables and measurement error. , 1981 .

[22]  Alan B. Czyzewski,et al.  Ethical Reasoning Instruction in Undergraduate Cost Accounting: A Non-Intrusive Approach , 2012 .

[23]  R. Sitgreaves Psychometric theory (2nd ed.). , 1979 .

[24]  Tapabrata Maiti,et al.  Principles and Practice of Structural Equation Modeling (2nd ed.) , 2006 .

[25]  A. Bedeian Even if the Tower Is “Ivory,” It Isn't “White:” Understanding the Consequences of Faculty Cynicism. , 2007 .

[26]  B. Pesta,et al.  The Assurance of Learning Tool as Predictor and Criterion in Business School Admissions Decisions: New Use for an Old Standard? , 2011 .

[27]  Jeffrey S. Harper,et al.  Assurance of Learning in the MIS Program. , 2009 .

[28]  J. Nunnally Psychometric Theory (2nd ed), New York: McGraw-Hill. , 1978 .