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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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Carragher, Natacha; Templin, Jonathan; Jones, Phillip; Shulruf, Boaz; Velan, Gary – Educational Measurement: Issues and Practice, 2019
In this ITEMS module, we provide a didactic overview of the specification, estimation, evaluation, and interpretation steps for diagnostic measurement/classification models (DCMs), which are a promising psychometric modeling approach. These models can provide detailed skill- or attribute-specific feedback to respondents along multiple latent…
Descriptors: Measurement, Classification, Models, Check Lists
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Kosh, Audra E.; Greene, Jeffrey A.; Murphy, P. Karen; Burdick, Hal; Firetto, Carla M.; Elmore, Jeff – Educational Measurement: Issues and Practice, 2018
We explored the feasibility of using automated scoring to assess upper-elementary students' reading ability through analysis of transcripts of students' small-group discussions about texts. Participants included 35 fourth-grade students across two classrooms that engaged in a literacy intervention called Quality Talk. During the course of one…
Descriptors: Computer Assisted Testing, Small Group Instruction, Group Discussion, Student Evaluation
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Bennett, Randy E. – Educational Measurement: Issues and Practice, 2018
This article is a written adaptation of the Presidential address I gave at the NCME annual conference in April 2018. The article describes my thoughts on the future of assessment. I discuss eleven likely characteristics of future tests and, for each characteristic, why I think it is important and what to watch with respect to it. Next, I outline…
Descriptors: Educational Assessment, Educational Trends, Tests, Trend Analysis
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Jerrim, John; Parker, Philip; Choi, Alvaro; Chmielewski, Anna Katyn; Sälzer, Christine; Shure, Nikki – Educational Measurement: Issues and Practice, 2018
The Programme for International Student Assessment (PISA) is an important international study of 15-olds' knowledge and skills. New results are released every 3 years, and have a substantial impact upon education policy. Yet, despite its influence, the methodology underpinning PISA has received significant criticism. Much of this criticism has…
Descriptors: Educational Assessment, Comparative Education, Achievement Tests, Foreign Countries
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Wind, Stefanie A. – Educational Measurement: Issues and Practice, 2018
In this digital ITEMS module, we introduce the framework of nonparametric item response theory (IRT), in particular Mokken scaling, which can be used to evaluate fundamental measurement properties with less strict assumptions than parametric IRT models. We walk through the key distinction between parametric and nonparametric models, introduce the…
Descriptors: Educational Assessment, Nonparametric Statistics, Item Response Theory, Scaling
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Rutkowski, David; Rutkowski, Leslie; Liaw, Yuan-Ling – Educational Measurement: Issues and Practice, 2018
Participation in international large-scale assessments has grown over time with the largest, the Programme for International Student Assessment (PISA), including more than 70 education systems that are economically and educationally diverse. To help accommodate for large achievement differences among participants, in 2009 PISA offered…
Descriptors: Educational Assessment, Foreign Countries, Achievement Tests, Secondary School Students
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Vijver, Fons J. R. – Educational Measurement: Issues and Practice, 2018
A conceptual framework of measurement bias in cross-cultural comparisons, distinguishing between construct, method, and item bias (differential item functioning), is used to describe a methodological framework addressing assessment of noncognitive variables in international large-scale studies. It is argued that the treatment of bias, coming from…
Descriptors: Educational Assessment, Achievement Tests, Foreign Countries, International Assessment
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