ERIC Number: EJ1185285
Record Type: Journal
Publication Date: 2018-Aug
Pages: 9
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1382-4996
EISSN: N/A
Multiple True-False Items: A Comparison of Scoring Algorithms
Lahner, Felicitas-Maria; Lörwald, Andrea Carolin; Bauer, Daniel; Nouns, Zineb Miriam; Krebs, René; Guttormsen, Sissel; Fischer, Martin R.; Huwendiek, Sören
Advances in Health Sciences Education, v23 n3 p455-463 Aug 2018
Multiple true-false (MTF) items are a widely used supplement to the commonly used single-best answer (Type A) multiple choice format. However, an optimal scoring algorithm for MTF items has not yet been established, as existing studies yielded conflicting results. Therefore, this study analyzes two questions: What is the optimal scoring algorithm for MTF items regarding reliability, difficulty index and item discrimination? How do the psychometric characteristics of different scoring algorithms compare to those of Type A questions used in the same exams? We used data from 37 medical exams conducted in 2015 (998 MTF and 2163 Type A items overall). Using repeated measures analyses of variance (rANOVA), we compared reliability, difficulty and item discrimination of different scoring algorithms for MTF with four answer options and Type A. Scoring algorithms for MTF were dichotomous scoring (DS) and two partial credit scoring algorithms, PS[subscript 50] where examinees receive half a point if more than half of true/false ratings were marked correctly and one point if all were marked correctly, and PS[subscript 1/n] where examinees receive a quarter of a point for every correct true/false rating. The two partial scoring algorithms showed significantly higher reliabilities (a[subscript PS1/n] = 0.75; a[subscript PS50] = 0.75; a[subscript DS] = 0.70, a[subscript A] = 0.72), which corresponds to fewer items needed for a reliability of 0.8 (n[subscript PS1/n] = 74; n[subscript PS50] = 75; n[subscript DS] = 103, n[subscript A] = 87), and higher discrimination indices (r[subscript PS1/n] = 0.33; r[subscript PS50] = 0.33; r[subscript DS] = 0.30; r[subscript A] = 0.28) than dichotomous scoring and Type A. Items scored with DS tend to be difficult (p[subscript DS] = 0.50), whereas items scored with PS[subscript 1/n] become easy (p[subscript PS1/n] = 0.82). PS[subscript 50] and Type A cover the whole range, from easy to difficult items (p[subscript PS50] = 0.66; p[subscript A] = 0.73). Partial credit scoring leads to better psychometric results than dichotomous scoring. PS[subscript 50] covers the range from easy to difficult items better than PS[subscript 1/n]. Therefore, for scoring MTF, we suggest using PS[subscript 50].
Descriptors: Scoring Formulas, Scoring Rubrics, Objective Tests, Multiple Choice Tests, Test Format, Test Bias, Test Reliability, Difficulty Level, Psychometrics, Medical Education, Item Analysis, Comparative Testing, Comparative Analysis
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A