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Sample Size and Item Parameter Estimation Precision When Utilizing the Masters' Partial Credit Model
Custer, Michael; Kim, Jongpil – Online Submission, 2023
This study utilizes an analysis of diminishing returns to examine the relationship between sample size and item parameter estimation precision when utilizing the Masters' Partial Credit Model for polytomous items. Item data from the standardization of the Batelle Developmental Inventory, 3rd Edition were used. Each item was scored with a…
Descriptors: Sample Size, Item Response Theory, Test Items, Computation
Herrmann-Abell, Cari F.; Hardcastle, Joseph; DeBoer, George E. – Grantee Submission, 2022
As implementation of the "Next Generation Science Standards" moves forward, there is a need for new assessments that can measure students' integrated three-dimensional science learning. The National Research Council has suggested that these assessments be multicomponent tasks that utilize a combination of item formats including…
Descriptors: Multiple Choice Tests, Conditioning, Test Items, Item Response Theory
Arthurs, Noah; Stenhaug, Ben; Karayev, Sergey; Piech, Chris – International Educational Data Mining Society, 2019
Understanding exam score distributions has implications for item response theory (IRT), grade curving, and downstream modeling tasks such as peer grading. Historically, grades have been assumed to be normally distributed, and to this day the normal is the ubiquitous choice for modeling exam scores. While this is a good assumption for tests…
Descriptors: Grades (Scholastic), Scores, Statistical Distributions, Models
Rachatasumrit, Napol; Koedinger, Kenneth R. – International Educational Data Mining Society, 2021
Student modeling is useful in educational research and technology development due to a capability to estimate latent student attributes. Widely used approaches, such as the Additive Factors Model (AFM), have shown satisfactory results, but they can only handle binary outcomes, which may yield potential information loss. In this work, we propose a…
Descriptors: Models, Student Characteristics, Feedback (Response), Error Correction
Zhou, Yuhao; Li, Xihua; Cao, Yunbo; Zhao, Xuemin; Ye, Qing; Lv, Jiancheng – International Educational Data Mining Society, 2021
In educational applications, "Knowledge Tracing" (KT) has been widely studied for decades as it is considered a fundamental task towards adaptive online learning. Among proposed KT methods, Deep Knowledge Tracing (DKT) and its variants are by far the most effective ones due to the high flexibility of the neural network. However, DKT…
Descriptors: Online Courses, Computer Assisted Instruction, Networks, Learning Analytics
Kovalkov, Anastasia; Paassen, Benjamin; Segal, Avi; Gal, Kobi; Pinkwart, Niels – International Educational Data Mining Society, 2021
Promoting creativity is considered an important goal of education, but creativity is notoriously hard to define and measure. In this paper, we make the journey from defining a formal creativity and applying the measure in a practical domain. The measure relies on core theoretical concepts in creativity theory, namely fluency, flexibility, and…
Descriptors: Creativity, Theory Practice Relationship, Evaluators, Specialists
Likourezos, Vicki; Kalyuga, Slava – Mathematics Education Research Group of Australasia, 2019
The variability effect occurs when learners' exposure to highly variable tasks results in better learning. It was hypothesised that learners who studied high variability worked examples would obtain higher post-test scores compared to learners who studied low variability examples, and learners who self-generated problem solutions for the same high…
Descriptors: Teaching Methods, Cognitive Ability, Pretests Posttests, Learning Theories
Guerrero, Tricia A.; Griffin, Thomas D.; Wiley, Jennifer – Grantee Submission, 2020
The Predict-Observe-Explain (POE) learning cycle improves understanding of the connection between empirical results and theoretical concepts when students engage in hands-on experimentation. This study explored whether training students to use a POE strategy when learning from social science texts that describe theories and experimental results…
Descriptors: Prediction, Observation, Reading Comprehension, Correlation
Sükür, Murat; Demircan, Fatma Esra – Novitas-ROYAL (Research on Youth and Language), 2020
This quasi-experimental research aims to investigate the effects of intensive and extensive recasts on learning the English simple present singular -s. In line with this purpose, firstly 56 beginner level learners were non-randomly assigned to three different groups: written intensive recast (n = 20), written extensive recast (n = 17), and control…
Descriptors: Comparative Analysis, English (Second Language), Second Language Learning, Second Language Instruction
Bramley, Tom – Cambridge Assessment, 2018
The aim of the research reported here was to get some idea of the accuracy of grade boundaries (cut-scores) obtained by applying the 'similar items method' described in Bramley & Wilson (2016). In this method experts identify items on the current version of a test that are sufficiently similar to items on previous versions for them to be…
Descriptors: Accuracy, Cutting Scores, Test Items, Item Analysis
Custer, Michael – Online Submission, 2015
This study examines the relationship between sample size and item parameter estimation precision when utilizing the one-parameter model. Item parameter estimates are examined relative to "true" values by evaluating the decline in root mean squared deviation (RMSD) and the number of outliers as sample size increases. This occurs across…
Descriptors: Sample Size, Item Response Theory, Computation, Accuracy
Hardcastle, Joseph; Herrmann-Abell, Cari F.; DeBoer, George E. – Grantee Submission, 2017
Can student performance on computer-based tests (CBT) and paper-and-pencil tests (PPT) be considered equivalent measures of student knowledge? States and school districts are grappling with this question, and although studies addressing this question are growing, additional research is needed. We report on the performance of students who took…
Descriptors: Academic Achievement, Computer Assisted Testing, Comparative Analysis, Student Evaluation
Ostrow, Korinn; Donnelly, Chistopher; Heffernan, Neil – International Educational Data Mining Society, 2015
As adaptive tutoring systems grow increasingly popular for the completion of classwork and homework, it is crucial to assess the manner in which students are scored within these platforms. The majority of systems, including ASSISTments, return the binary correctness of a student's first attempt at solving each problem. Yet for many teachers,…
Descriptors: Intelligent Tutoring Systems, Scoring, Testing, Credits
Cheung, Wai Ming; Huang, Yanli; Tsang, Hector W. H. – AERA Online Paper Repository, 2017
Hong Kong attained champion of the PIRLS 2011 that aroused keen interest in understanding the underlying reasons of a non-alphabetic language. The study aimed at unravelling various aspects of the student and home factors which contributed to remarkable Chinese reading performance. Totally 3,875 students from 132 primary schools completed the…
Descriptors: Chinese, Reading Achievement, Elementary School Students, Structural Equation Models
Haertel, Edward H. – Educational Testing Service, 2013
Policymakers and school administrators have embraced value-added models of teacher effectiveness as tools for educational improvement. Teacher value-added estimates may be viewed as complicated scores of a certain kind. This suggests using a test validation model to examine their reliability and validity. Validation begins with an interpretive…
Descriptors: Reliability, Validity, Inferences, Teacher Effectiveness