Detailed learning objectives foster an effective and equitable learning environment by clarifying what instructors expect students to learn, rather than requiring students to use prior knowledge to infer these expectations. When questions are labeled with relevant learning goals, students understand which skills are tested by those questions.…

In this paper, we extracted content-based and structure-based features of text to predict human annotations for claims and nonclaims in argumentative essays. We compared Logistic Regression, Bernoulli Naive Bayes, Gaussian Naive Bayes, Linear Support Vector Classification, Random Forest, and Neural Networks to train classification models. Random…

Knowledge space theory (KST) is a mathematical framework for modeling and assessing student knowledge. While KST has successfully served as the foundation of several learning systems, recent advancements in machine learning provide an opportunity to improve on purely KST-based approaches to assessing student knowledge. As such, in this work we…

This research synthesizes studies that used a Digitalized Interactive Component (DIC) to assess K-12 student mathematics performance during Computer-based-Assessments (CBAs) in mathematics. A systematic search identified ten studies that categorized existing DICs according to the tools that provided language assistance to students and tools that…

The paper describes initial efforts on creating a system for the automatic assessment of Swedish second language (L2) learner essays from two points of view: holistic evaluation of the reached level according to the Common European Framework of Reference (CEFR), and the lexical analysis of texts for receptive and productive vocabulary per CEFR…

In online educational systems we can easily collect and analyze extensive data about student learning. Current practice, however, focuses only on some aspects of these data, particularly on correctness of students answers. When a student answers incorrectly, the submitted wrong answer can give us valuable information. We provide an overview of…

Item pools supporting computer-based tests are not always completely calibrated. Occasionally, only a small subset of the items in the pool may have actual calibrations, while the remainder of the items may only have classical item statistics, (e.g., "p"-values, point-biserial correlation coefficients, or biserial correlation…

A client of American College Testing, Inc. (ACT) decided to implement a computer-based testing program to replace their paper-pencil format for professional certification. This paper reports on the results of the developed test after 1 year's use, especially as the results relate to test security issues. ACT research shows that a variable length…

This study focused on the robustness of unidimensional item response theory (UIRT) models in computerized classification testing against violation of the unidimensionality assumption. The study addressed whether UIRT models remain acceptable under various testing conditions and dimensionality strengths. Monte Carlo simulation techniques were used…

The purpose of many certification or licensure tests is to identify candidates who possess some level of minimum competence to practice their profession. In general, this type of test is referred to as classification testing. When this type of test is administered with a computer, the test is a computerized classification test (CCT). This paper…

This paper proposes a new Information-Time index as the basis for item selection in computerized classification testing (CCT) and investigates how this new item selection algorithm can help improve test efficiency for item pools with mixed item types. It also investigates how practical constraints such as item exposure rate control, test…

This paper describes a study, now in progress, of new methods for representing the sampling variability of Mantel-Haenszel differential item functioning (DIF) results, based on the system for categorizing the severity of DIF that is now in place at the Educational Testing Service. The methods, which involve a Bayesian elaboration of procedures…

This paper addresses instrumentation design and an ongoing study of an online formative assessment instrument and its effects in pre-college (developmental/remedial) mathematics courses. The use of facet theory and instructional technologies are harmonized to construct and scale an online instrument designed to document student procedures while…

Two operational item pools were used to investigate the performance of stratum computerized adaptive tests (CATs) when items were assigned to strata based on empirical estimates of item difficulty or human judgments of item difficulty. Items from the first data set consisted of 54 5-option multiple choice items from a form of the ACT mathematics…

The potential for computer adaptive testing (CAT) has been well documented. In order to improve the efficiency of this process, it may be possible to utilize a neural network, or more specifically, a back propagation neural network. The paper asserts that in order to accomplish this end, it must be shown that grouping examinees by ability as…