Manual composition of tasks and exams is a challenging and time-consuming task. Especially when exams are taken remotely without the personal monitoring by examiners, most exams can easily lose their integrity with the use of previously done exercises or student communication. This research introduces an approach that incorporates the principles…

Currently, Indonesia has 122 State Universities (PTN) under the Ministry of Education and Culture and other ministries. Improving the quality of the selection process for new student admissions at PTN is critical for Indonesia's human resources development. Then in 2019, there was a transformation with the implementation of the exam becoming a…

In low-stakes assessment settings, students' performance is not only influenced by students' ability level but also their test-taking engagement. In computerized adaptive tests (CATs), disengaged responses (e.g., rapid guesses) that fail to reflect students' true ability levels may lead to the selection of less informative items and thereby…

The use of computerized adaptive testing algorithms for ranking items (e.g., college preferences, career choices) involves two major challenges: unacceptably high computation times (selecting from a large item pool with many dimensions) and biased results (enhanced preferences or intensified examinee responses because of repeated statements across…

The purpose of this research is to create a personalized system called CARIA that suggests career recommendations based on students' competencies and the required skills in each career. The focus of this study is on digital technology and digital media careers. The personalized career recommender system uses a novel similarity measure called…

Over the past few years, several states have begun to explore or pilot different through-year assessments to serve as replacements to the traditional end-of-year summative assessments that are currently the predominant source of information used by states to meet federal accountability requirements. While there are several different assessment…

For item selection in cognitive diagnostic computerized adaptive testing (CD-CAT), ideally, a single item selection index should be created to simultaneously regulate precision, exposure status, and attribute balancing. For this purpose, in this study, we first proposed an attribute-balanced item selection criterion, namely, the standardized…

The goal in personalized assessment is to best fit the needs of each individual test taker, given the assessment purposes. Design-In-Real-Time (DIRTy) assessment reflects the progressive evolution in testing from a single test, to an adaptive test, to an adaptive assessment "system." In this paper, we lay the foundation for DIRTy…

The goal in personalized assessment is to best fit the needs of each individual test taker, given the assessment purposes. Design-in-Real-Time (DIRTy) assessment reflects the progressive evolution in testing from a single test, to an adaptive test, to an adaptive assessment "system." In this article, we lay the foundation for DIRTy…

Administration of high-stakes language proficiency tests has been disrupted in many parts of the world as a result of the 2019 novel coronavirus pandemic. Institutions that rely on test scores have been forced to adapt, and in many cases this means using scores from a different test, or a new online version of an existing test, that can be taken…

Diagnostic classification models (DCMs) can provide multidimensional diagnostic feedback about students' mastery levels of knowledge components or attributes. One advantage of using DCMs is the ability to accurately and reliably classify students into mastery levels with a relatively small number of items per attribute. Combining DCMs with…

The development of cognitive diagnostic-computerized adaptive testing (CD-CAT) has provided a new perspective for gaining information about examinees' mastery on a set of cognitive attributes. This study proposes a new item selection method within the framework of dual-objective CD-CAT that simultaneously addresses examinees' attribute mastery…

Item exposure control is, relative to adaptive testing, a nascent concept that has emerged only in the last two to three decades on an academic basis as a practical issue in high-stakes computerized adaptive tests. This study aims to implement a new strategy in item exposure control by incorporating the standard error of the ability estimate into…

Purpose: This study aims to reveal effects of content balancing and item selection method on ability estimation in computerized adaptive tests by comparing Fisher's maximum information (FMI) and likelihood weighted information (LWI) methods. Research Methods: Four groups of examinees (250, 500, 750, 1000) and a bank of 500 items with 10 different…

Studies examining feedback in educational settings have largely focused on feedback that is received, rather than chosen, by students. This study investigates whether adult participants learn more from choosing rather than receiving feedback from virtual characters in a digital poster design task. We employed a yoked study design and two versions…