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Attali, Yigal – Educational Measurement: Issues and Practice, 2019
Rater training is an important part of developing and conducting large-scale constructed-response assessments. As part of this process, candidate raters have to pass a certification test to confirm that they are able to score consistently and accurately before they begin scoring operationally. Moreover, many assessment programs require raters to…
Descriptors: Evaluators, Certification, High Stakes Tests, Scoring
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Ames, Allison; Myers, Aaron – Educational Measurement: Issues and Practice, 2019
Drawing valid inferences from modern measurement models is contingent upon a good fit of the data to the model. Violations of model-data fit have numerous consequences, limiting the usefulness and applicability of the model. As Bayesian estimation is becoming more common, understanding the Bayesian approaches for evaluating model-data fit models…
Descriptors: Bayesian Statistics, Psychometrics, Models, Predictive Measurement
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West, Stephen G.; Hughes, Jan N.; Kim, Han Joe; Bauer, Shelby S. – Educational Measurement: Issues and Practice, 2019
The Motivation for Educational Attainment (MEA) questionnaire, developed to assess facets related to early adolescents' motivation to complete high school, has a bifactor structure with a large general factor and three smaller orthogonal specific factors (teacher expectations, peer aspirations, value of education). This prospective validity study…
Descriptors: Student Motivation, Educational Attainment, Questionnaires, Adolescent Attitudes
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Madison, Matthew J. – Educational Measurement: Issues and Practice, 2019
Recent advances have enabled diagnostic classification models (DCMs) to accommodate longitudinal data. These longitudinal DCMs were developed to study how examinees change, or transition, between different attribute mastery statuses over time. This study examines using longitudinal DCMs as an approach to assessing growth and serves three purposes:…
Descriptors: Longitudinal Studies, Item Response Theory, Psychometrics, Criterion Referenced Tests
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Zhang, Mo; Bennett, Randy E.; Deane, Paul; van Rijn, Peter W. – Educational Measurement: Issues and Practice, 2019
This study compared gender groups on the processes used in writing essays in an online assessment. Middle-school students from four grades responded to essays in two persuasive subgenres, argumentation and policy recommendation. Writing processes were inferred from four indicators extracted from students' keystroke logs. In comparison to males, on…
Descriptors: Gender Differences, Essays, Computer Assisted Testing, Persuasive Discourse
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Allen, Jeff; Mattern, Krista – Educational Measurement: Issues and Practice, 2019
We examined summary indices of high school performance (coursework, grades, and test scores) based on the graded response model (GRM). The indices varied by inclusion of ACT test scores and whether high school courses were constrained to have the same difficulty and discrimination across groups of schools. The indices were examined with respect to…
Descriptors: High School Students, Academic Achievement, Secondary School Curriculum, Difficulty Level
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Ma, Wenchao; de la Torre, Jimmy – Educational Measurement: Issues and Practice, 2019
In this ITEMS module, we introduce the generalized deterministic inputs, noisy "and" gate (G-DINA) model, which is a general framework for specifying, estimating, and evaluating a wide variety of cognitive diagnosis models. The module contains a nontechnical introduction to diagnostic measurement, an introductory overview of the G-DINA…
Descriptors: Models, Classification, Measurement, Identification
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Shewach, Oren R.; McNeal, Kyle D.; Kuncel, Nathan R.; Sackett, Paul R. – Educational Measurement: Issues and Practice, 2019
College students commonly have considerable course choice, and they can differ substantially in the proportion of their coursework taken at an advanced level. While advanced coursework is generally viewed as a desirable component of a student's education, research has rarely explored differences in student course-taking patterns as a measure of…
Descriptors: Advanced Courses, Course Selection (Students), Cognitive Ability, Grade Point Average
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Fidler, James R.; Risk, Nicole M. – Educational Measurement: Issues and Practice, 2019
Credentialing examination developers rely on task (job) analyses for establishing inventories of task and knowledge areas in which competency is required for safe and successful practice in target occupations. There are many ways in which task-related information may be gathered from practitioner ratings, each with its own advantage and…
Descriptors: Job Analysis, Scaling, Licensing Examinations (Professions), Test Construction
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Flake, Jessica Kay; Petway, Kevin Terrance, II – Educational Measurement: Issues and Practice, 2019
Numerous studies merely note divergence in students' and teachers' ratings of student noncognitive constructs. However, given the increased attention and use of these constructs in educational research and practice, an in-depth study focused on this issue was needed. Using a variety of quantitative methodologies, we thoroughly investigate…
Descriptors: Teachers, Students, Achievement Rating, Interrater Reliability
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Hansen, John; Sadler, Philip; Sonnert, Gerhard – Educational Measurement: Issues and Practice, 2019
The high school grade point average (GPA) is often adjusted to account for nominal indicators of course rigor, such as "honors" or "advanced placement." Adjusted GPAs--also known as weighted GPAs--are frequently used for computing students' rank in class and in the college admission process. Despite the high stakes attached to…
Descriptors: Grade Point Average, High School Students, Difficulty Level, Weighted Scores
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Meijer, Eline; Cleiren, Marc P. H. D.; Dusseldorp, Elise; Buurman, Vincent J. C.; Hogervorst, Roel M.; Heiser, Willem J. – Educational Measurement: Issues and Practice, 2019
Early prediction of academic performance is important for student support. The authors explored, in a multivariate approach, whether pre-entry data (e.g., high school study results, preparative activities, expectations, capabilities, motivation, and attitude) could predict university students' first-year academic performance. Preregistered…
Descriptors: Academic Achievement, College Freshmen, Prediction, Risk
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Moon, Jung Aa; Keehner, Madeleine; Katz, Irvin R. – Educational Measurement: Issues and Practice, 2019
The current study investigated how item formats and their inherent affordances influence test-takers' cognition under uncertainty. Adult participants solved content-equivalent math items in multiple-selection multiple-choice and four alternative grid formats. The results indicated that participants' affirmative response tendency (i.e., judge the…
Descriptors: Affordances, Test Items, Test Format, Test Wiseness
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Allen, Jeff; Mattern, Krista; Ndum, Edwin – Educational Measurement: Issues and Practice, 2019
We derived an index of high school academic rigor (HSAR) by optimizing the prediction of first-year college GPA (FYGPA) based on high school courses taken, grades, and indicators of advanced coursework. Using a large data set and nominal parameterization of high school course outcomes, the HSAR index capitalizes on differential contributions…
Descriptors: High Schools, Difficulty Level, Prediction, Grade Point Average
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Kosh, Audra E.; Simpson, Mary Ann; Bickel, Lisa; Kellogg, Mark; Sanford-Moore, Ellie – Educational Measurement: Issues and Practice, 2019
Automatic item generation (AIG)--a means of leveraging technology to create large quantities of items--requires a minimum number of items to offset the sizable upfront investment (i.e., model development and technology deployment) in order to achieve cost savings. In this cost-benefit analysis, we estimated the cost of each step of AIG and manual…
Descriptors: Cost Effectiveness, Automation, Test Items, Mathematics Tests
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