Fair and Equitable Measurement of Student Learning in MOOCs: An Introduction to Item Response Theory, Scale Linking, and Score Equating

J. Patrick Meyer and Shi Zhu   |   

Massive open online courses (MOOCs) are playing an increasingly important role in higher education around the world, but despite their popularity, the measurement of student learning in these courses is hampered by cheating and other problems that lead to unfair evaluation of student learning. In this paper, we describe a framework for maintaining test security and preventing one form of cheating in online assessments. We also introduce readers to item response theory, scale linking, and score equating to demonstrate the way these methods can produce fair and equitable test scores. Patrick Meyer is an Assistant Professor in the Curry School of Education at the University of Virginia. He is the inventor of jMetrik, an open source psychometric software program. Shi Zhu is a doctoral student in the Research, Statistics, and Evaluation program in the Curry School of Education. He holds a Ph.D. in History from Nanjing University in China.

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