A systematic analysis of difficulty level of the question paper using student’s marks: a case study

Lourdusamy, Ravi; Magendiran, Poovizhi

doi:10.1007/s41870-020-00599-2

Cited by 2 publications

(1 citation statement)

References 11 publications

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“…However, when an instructor makes a new question, it is useful for them to have an idea of the question's DL. The common method to obtain a valid and reliable DL is by collecting sufficient student performance data and report an Item Difficulty Level [10], [11] and a Discrimination Index [10]. Automated methods such as the accumulative test by Sokolova et al [12], the Question Classifier Engine by Narayanan et al [13], or the algorithm based on a Monte-Carlo approach by Sud et al [14] require actual student performance as input data.…”

Section: Background and Theoretical Frameworkmentioning

confidence: 99%

Comparing Expert Predictions to Student Performance on Challenging Conceptual Questions: Towards an Adaptive Learning Module for Materials Science

Nigon,

Simionescu,

Ekstedt

et al.

2022 ASEE Annual Conference &Amp; Exposition Proceedings

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Thomas Ekstedt is a software developer in the School of Chemical, Biological and Environmental Engineering at Oregon State University. He is involved in the development of technology-based educational systems, particularly in the areas of concept-based instruction, adaptive learning, and interactive simulation of physical phenomena. Julie TuckerDr. Tucker earned her B.S. in Nuclear Engineering from the University of Missouri -Rolla. She attended graduate school at the University of Wisconsin -Madison as a Naval Nuclear Propulsion Fellow, where she received her M.S. and Ph.D. in Nuclear Engineering with a minor in Materials Science in 2008. After graduation, Dr. Tucker spent five years as a Principal Scientist at Knolls Atomic Power Laboratory in Schenectady, NY studying the thermal stability of structural alloys for nuclear power systems. She joined the School of Mechanical, Industrial, and Manufacturing Engineering at Oregon State University as an Assistant Professor in 2013 and was promoted to Associate Professor in 2019. In 2019 she was awarded the Dean's Professorship and was also appointed as the Materials Science Interdisciplinary Graduate Program Director. Dr. Tucker has an active research group focused on degradation of materials in extreme environments and alloy development. Her research efforts leverage both modeling and experimental approaches to gain fundamental understanding of materials performance. Milo KoretskyMilo Koretsky (he/him/his) is the McDonnell Family Bridge Professor holding a joint appointment in Chemical and Biological Engineering and Education at Tufts University. He received his BS and MS degrees from UC San Diego and his PhD from UC Berkeley, all in chemical engineering. He is interested in integrating technology into effective educational practices and in promoting the use of higher-level cognitive and social skills in engineering problem solving.

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Section: Background and Theoretical Frameworkmentioning

confidence: 99%