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Measuring the effectiveness of pedagogical innovations using multiple baseline testing

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2013 ASEE Annual Conference & Exposition


Atlanta, Georgia

Publication Date

June 23, 2013

Start Date

June 23, 2013

End Date

June 26, 2013



Conference Session

Trends in Engineering Education

Tagged Division

Educational Research and Methods

Page Count


Page Numbers

23.891.1 - 23.891.15



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Paper Authors


Alex Albert University of Colorado

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Alex Albert is a PhD Candidate in the Construction Engineering and Management Program at the University of Colorado at Boulder. He has conducted research for the Construction Industry Institute and ELECTRI International, studying hazard recognition and response. Alex specializes in implementing experimental research methods in engineering education to perform hypothesis testing and draw causal inferences.

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Measuring the effectiveness of pedagogical innovations using multiple baseline testingABSTRACTA great deal of literature focuses on innovations that are designed to improve educationalperformance. Although some innovations are designed and implemented to address learning in avery specific domain, others influence student learning more generally as they are applicableregardless of specific content (e.g., mechanisms for delivering new content, new strategies forstudent-student interactions, and application of new technologies). Many instructors form thehypothesis that a particular innovation will enhance student learning and, consequently, theability to achieve desired learning objectives. Validly testing such a hypothesis can betroublesome when confounding factors exist in the student body’s learning environment such asscheduled breaks, social stressors, and activities occurring in other courses. Multiple baselinetesting is a promising strategy for statistically controlling the influence of confounding factorswhen innovations are implemented consistently across multiple courses. This strategy involvesmeasuring student performance, implementing the innovation at a randomly selected time, andcontinuing to measure student performance as the innovation is integrated within the course. Theimpact of the innovation treatment can be measured using time series regression models and F-tests. This paper presents the proper mechanics of multiple baseline testing, discusses therelatively small body of research on this method that exists outside the medical and biologicalfields, and provides clear recommendations for managing threats to validity in engineeringeducation research.

Albert, A. (2013, June), Measuring the effectiveness of pedagogical innovations using multiple baseline testing Paper presented at 2013 ASEE Annual Conference & Exposition, Atlanta, Georgia. 10.18260/1-2--22276

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