A Survey on Problem Formulations and (Meta)Heuristic-Based Solutions in Automated Assembly of Parallel Test Forms

Parallel test forms are ubiquitous in the educational, aptitude, achievement, and licensure testing. The problem of automated assembling of parallel test forms has been extensively explored for almost 40 years. Many different mathematical models of the problem formulations and a plenty of different solutions have emerged over the last two decades, indicating that the problem has matured. However, its investigation is still challenging, especially today, when the importance of distance learning and remote knowledge testing is rapidly growing. The diversity of proposed approaches originated notably from the variety of scientific fields involved such as psychometrics, applied mathematics, operations research, and artificial intelligence. Majority of solutions of the problem are (meta)heuristics-based, since they consider the problem as a combinatorial optimization problem which is NP-hard. In this paper, a comprehensive review of this research field, referring to related works since 1985, is conducted. Problem formulations and solutions of the problem are separately classified. Possible avenues of future research are pointed out.

The practice of licensure, the licensure of practice

Licensure tests play a critical role in any profession. Well-designed tests both delineate the core competencies that are required to enter a profession and provide evidence that candidates can safely practice in the profession. They also identify the professional knowledge and skill that differentiates any educated individual from the well-prepared professional. Geoffrey Phelps and Gary Sykes use a series of assessment tasks to illustrate how teacher licensure testing can be designed to focus more directly on assessing aspiring educators’ performance of the professional competencies that make up the day-to-day and moment-to-moment work of teaching.

Projection-Based Stopping Rules for Computerized Adaptive Testing in Licensure Testing

The confidence interval (CI) stopping rule is commonly used in licensure settings to make classification decisions with fewer items in computerized adaptive testing (CAT). However, it tends to be less efficient in the near-cut regions of the θ scale, as the CI often fails to be narrow enough for an early termination decision prior to reaching the maximum test length. To solve this problem, this study proposed the projection-based stopping rules that base the termination decisions on the algorithmically projected range of the final θ estimate at the hypothetical completion of the CAT. A simulation study and an empirical study were conducted to show the advantages of the projection-based rules over the CI rule, in which the projection-based rules reduced the test length without jeopardizing critical psychometric qualities of the test, such as the θ and classification precision. Operationally, these rules do not require additional regularization parameters, because the projection is simply a hypothetical extension of the current test within the existing CAT environment. Because these new rules are specifically designed to address the decreased efficiency in the near-cut regions as opposed to for the entire scale, the authors recommend using them in conjunction with the CI rule in practice.

“Slaying Ghosts in the Room”: Identity Contingencies, Teacher Licensure Testing Events, and African American Preservice Teachers

Background In 41 states, students must pass the “basic skills” portion of their licensure exam before they can be admitted into a teacher education program. Because African American test takers are roughly half as likely to pass basic skills exams on their first attempt compared to White test takers, this portion of the licensure exam is a key gatekeeper to the field and directly shapes the racial diversity of the profession. Researchers generally frame this problem in one of two opposing ways: (a) by locating the cause in skill and knowledge deficiencies of test takers or (b) by locating the cause in the cultural bias of standardized test instruments. This study looks beyond these two polarized views to conceptualize the licensure exam as a testing event that includes a nexus of cognitive and affective processes beyond the specific skills the test is designed to measure. Focus of Study The study examined the subjective and social psychological ways African American test takers experience teacher licensure testing events. This study was guided by the following research questions: (a) How do African American preservice teachers experience the licensure testing event? (b) How does race become a salient aspect of the testing event experience for African American preservice teachers? The study drew from the social psychological constructs of identity contingencies and situational cues to analyze students’ experiences in the testing event. Setting and Participants Participants in this study were 22 African American preservice teachers attending a predominantly and historically Black institution in the northeastern United States. Each of the participants took the paper format basic skills exam in either the spring 2009 or spring 2010 national administration. Research Design Drawing from culturally sensitive research practice, this study used a qualitative case study research design to explore test takers’ experiences in the testing event. Findings/Conclusions Findings illustrate how the licensure testing event can become a racialized experience for some participants through (a) interactions with test proctors and site administrators before and during examinations and (b) actions of other test takers that inadvertently signaled racial stereotypes about test preparation, intelligence, and character. Racialized experiences for participants were not based upon any specific test questions or content. Findings are discussed in light of previous research to suggest that these experiences have the capacity to produce a host of cognitive and affective states that undermine performance.