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Mead, Alan D.; Zhou, Chenxuan – Journal of Applied Testing Technology, 2022
This study fit a Naïve Bayesian classifier to the words of exam items to predict the Bloom's taxonomy level of the items. We addressed five research questions, showing that reasonably good prediction of Bloom's level was possible, but accuracy varies across levels. In our study, performance for Level 2 was poor (Level 2 items were misclassified…
Descriptors: Artificial Intelligence, Prediction, Taxonomy, Natural Language Processing
Abu-Ghazalah, Rashid M.; Dubins, David N.; Poon, Gregory M. K. – Applied Measurement in Education, 2023
Multiple choice results are inherently probabilistic outcomes, as correct responses reflect a combination of knowledge and guessing, while incorrect responses additionally reflect blunder, a confidently committed mistake. To objectively resolve knowledge from responses in an MC test structure, we evaluated probabilistic models that explicitly…
Descriptors: Guessing (Tests), Multiple Choice Tests, Probability, Models
Van Moere, Alistair; Hanlon, Sean – Language Testing, 2020
In language assessment and in educational measurement more broadly, there is a tendency to interpret scores from single-administration tests as accurate indicators of a latent trait (e.g., reading ability). Even in contexts where learners receive multiple formative assessments throughout the year, estimates of student ability are determined based…
Descriptors: Bayesian Statistics, Measurement, Accuracy, English (Second Language)
Ayanwale, Musa Adekunle; Isaac-Oloniyo, Flourish O.; Abayomi, Funmilayo R. – International Journal of Evaluation and Research in Education, 2020
This study investigated dimensionality of Binary Response Items through a non-parametric technique of Item Response Theory measurement framework. The study used causal comparative research type of nonexperimental design. The sample consisted of 5,076 public senior secondary school examinees (SSS3) between the age of 14-16 years from 45 schools,…
Descriptors: Test Items, Item Response Theory, Bayesian Statistics, Nonparametric Statistics
Puerta, Alejandro; Ramírez-Hassan, Andrés – Education Economics, 2022
We examine the effect of an integrity pilot campaign on undergraduates' behavior. As with many costly small-scale experiments and pilot programs, our statistical inference has to rely on small sample size. To tackle this issue, we perform a Bayesian retrospective power analysis. In our setup, a lecturer intentionally makes mistakes that favors…
Descriptors: Ethics, Integrity, Pilot Projects, Undergraduate Students
Brassil, Chad E.; Couch, Brian A. – International Journal of STEM Education, 2019
Background: Within undergraduate science courses, instructors often assess student thinking using closed-ended question formats, such as multiple-choice (MC) and multiple-true-false (MTF), where students provide answers with respect to predetermined response options. While MC and MTF questions both consist of a question stem followed by a series…
Descriptors: Multiple Choice Tests, Objective Tests, Student Evaluation, Thinking Skills
Winchell, Adam; Mozer, Michael; Lan, Andrew; Grimaldi, Phillip; Pashler, Harold – International Educational Data Mining Society, 2018
When engaging with a textbook, students are inclined to highlight key content. Although students believe that highlighting and subsequent review of the highlights will further their educational goals, the psychological literature provides no evidence of benefits. Nonetheless, a student's choice of text for highlighting may serve as a window into…
Descriptors: Textbooks, Biology, Documentation, Science Instruction
Ting, Mu Yu – EURASIA Journal of Mathematics, Science & Technology Education, 2017
Using the capabilities of expert knowledge structures, the researcher prepared test questions on the university calculus topic of "finding the area by integration." The quiz is divided into two types of multiple choice items (one out of four and one out of many). After the calculus course was taught and tested, the results revealed that…
Descriptors: Calculus, Mathematics Instruction, College Mathematics, Multiple Choice Tests
Mahmud, Jumailiyah; Sutikno, Muzayanah; Naga, Dali S. – Educational Research and Reviews, 2016
The aim of this study is to determine variance difference between maximum likelihood and expected A posteriori estimation methods viewed from number of test items of aptitude test. The variance presents an accuracy generated by both maximum likelihood and Bayes estimation methods. The test consists of three subtests, each with 40 multiple-choice…
Descriptors: Maximum Likelihood Statistics, Computation, Item Response Theory, Test Items
Trikalinos, Thomas A.; Hoaglin, David C.; Small, Kevin M.; Terrin, Norma; Schmid, Christopher H. – Research Synthesis Methods, 2014
Existing methods for meta-analysis of diagnostic test accuracy focus primarily on a single index test. We propose models for the joint meta-analysis of studies comparing multiple index tests on the same participants in paired designs. These models respect the grouping of data by studies, account for the within-study correlation between the tests'…
Descriptors: Meta Analysis, Diagnostic Tests, Accuracy, Comparative Analysis
Azevedo, Ana, Ed.; Azevedo, José, Ed. – IGI Global, 2019
E-assessments of students profoundly influence their motivation and play a key role in the educational process. Adapting assessment techniques to current technological advancements allows for effective pedagogical practices, learning processes, and student engagement. The "Handbook of Research on E-Assessment in Higher Education"…
Descriptors: Higher Education, Computer Assisted Testing, Multiple Choice Tests, Guides
Stiller, Jurik; Hartmann, Stefan; Mathesius, Sabrina; Straube, Philipp; Tiemann, Rüdiger; Nordmeier, Volkhard; Krüger, Dirk; Upmeier zu Belzen, Annette – Assessment & Evaluation in Higher Education, 2016
The aim of this study was to improve the criterion-related test score interpretation of a text-based assessment of scientific reasoning competencies in higher education by evaluating factors which systematically affect item difficulty. To provide evidence about the specific demands which test items of various difficulty make on pre-service…
Descriptors: Logical Thinking, Scientific Concepts, Difficulty Level, Test Items
Lee, Jihyun; Corter, James E. – Applied Psychological Measurement, 2011
Diagnosis of misconceptions or "bugs" in procedural skills is difficult because of their unstable nature. This study addresses this problem by proposing and evaluating a probability-based approach to the diagnosis of bugs in children's multicolumn subtraction performance using Bayesian networks. This approach assumes a causal network relating…
Descriptors: Misconceptions, Probability, Children, Subtraction
Peer reviewedBradlow, Eric T.; Wainer, Howard; Wang, Xiaohui – Psychometrika, 1999
Proposes a parametric approach that involves a modification of standard Item Response Theory models that explicitly accounts for the nesting of items within the same testlets and that can be applied to multiple-choice sections comprising a mixture of independent items and testlets. (Author/SLD)
Descriptors: Bayesian Statistics, Item Response Theory, Models, Multiple Choice Tests
Sinharay, Sandip; Johnson, Matthew S.; Williamson, David M. – Journal of Educational and Behavioral Statistics, 2003
Item families, which are groups of related items, are becoming increasingly popular in complex educational assessments. For example, in automatic item generation (AIG) systems, a test may consist of multiple items generated from each of a number of item models. Item calibration or scoring for such an assessment requires fitting models that can…
Descriptors: Test Items, Markov Processes, Educational Testing, Probability
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