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Multiple true–false items: a comparison of scoring algorithms

Overview of attention for article published in Advances in Health Sciences Education, November 2017
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Title
Multiple true–false items: a comparison of scoring algorithms
Published in
Advances in Health Sciences Education, November 2017
DOI 10.1007/s10459-017-9805-y
Pubmed ID
Authors

Felicitas-Maria Lahner, Andrea Carolin Lörwald, Daniel Bauer, Zineb Miriam Nouns, René Krebs, Sissel Guttormsen, Martin R. Fischer, Sören Huwendiek

Abstract

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, PS50 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 PS1/n where examinees receive a quarter of a point for every correct true/false rating. The two partial scoring algorithms showed significantly higher reliabilities (αPS1/n = 0.75; αPS50 = 0.75; αDS = 0.70, αA = 0.72), which corresponds to fewer items needed for a reliability of 0.8 (nPS1/n = 74; nPS50 = 75; nDS = 103, nA = 87), and higher discrimination indices (rPS1/n = 0.33; rPS50 = 0.33; rDS = 0.30; rA = 0.28) than dichotomous scoring and Type A. Items scored with DS tend to be difficult (pDS = 0.50), whereas items scored with PS1/n become easy (pPS1/n = 0.82). PS50 and Type A cover the whole range, from easy to difficult items (pPS50 = 0.66; pA = 0.73). Partial credit scoring leads to better psychometric results than dichotomous scoring. PS50 covers the range from easy to difficult items better than PS1/n. Therefore, for scoring MTF, we suggest using PS50.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 14%
Student > Doctoral Student 3 11%
Professor 2 7%
Researcher 2 7%
Professor > Associate Professor 2 7%
Other 6 21%
Unknown 9 32%
Readers by discipline Count As %
Social Sciences 5 18%
Nursing and Health Professions 3 11%
Medicine and Dentistry 3 11%
Psychology 2 7%
Computer Science 1 4%
Other 3 11%
Unknown 11 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 August 2018.
All research outputs
#14,372,208
of 23,016,919 outputs
Outputs from Advances in Health Sciences Education
#602
of 856 outputs
Outputs of similar age
#236,334
of 437,910 outputs
Outputs of similar age from Advances in Health Sciences Education
#8
of 9 outputs
Altmetric has tracked 23,016,919 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 856 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.8. This one is in the 25th percentile – i.e., 25% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 437,910 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one.