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…

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…

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…

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…

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…

Contemporary views on learning highlight that deep learning occurs not simply by accumulating knowledge, but by using and applying knowledge as one engages in disciplinary activity. Increasingly, those concerned with education policy and practice are shifting priorities toward supporting deeper learning by emphasizing the importance of students'…

Self-report inventories are commonly administered to measure social-emotional learning competencies related to college and career readiness. Inattentive responding can negatively impact the validity of interpreting individual results and the accuracy of construct validity evidence. This study applied nine methods of detecting insufficient effort…

We describe an approach to characterizing and diagnosing complex professional competencies (CPCs) for the field of Intrapreneurship, i.e. activities of an entrepreneurial nature engaged by employees within their existing organizations. Our approach draws upon prior conceptual, empirical, and analytical efforts by researchers in Germany. Results…

Although much research has been conducted on the psychometric properties of cognitive diagnostic models, they are only recently being used in operational settings to provide results to examinees and other stakeholders. Using this newer class of models in practice comes with a fresh challenge for diagnostic assessment developers: effectively…

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…

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…

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…

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:…

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…

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…