Attribute hierarchy, the underlying prerequisite relationship among attributes, plays an important role in applying cognitive diagnosis models (CDM) for designing efficient cognitive diagnostic assessments. However, there are limited statistical tools to directly estimate attribute hierarchy from response data. In this study, we proposed a…

Cognitive diagnostic assessment is known for its capacity to provide detailed feedback to test-takers, which can inform instruction and guide learning. Besides this core strength of the assessment approach, the measurement procedure also works as a construct validation method in itself. Previous studies do not call attention to this aspect of…

In signal detection rater models for constructed response (CR) scoring, it is assumed that raters discriminate equally well between different latent classes defined by the scoring rubric. An extended model that relaxes this assumption is introduced; the model recognizes that a rater may not discriminate equally well between some of the scoring…

Incremental intelligence plays an important role in self-regulating and enhancing writing performance among language learners. The present study aimed to investigate the relationship among variables of the incremental theory of intelligence, self-regulatory writing strategies, implicit theory of writing, and writing performance in EFL learners. To…

In language assessment, AI technology has been incorporated in task design, assessment delivery, automated scoring of performance-based tasks, score reporting, and provision of feedback. AI technology is also used for collecting and analyzing performance data in language assessment validation. Research has been conducted to investigate the…

In cognitive diagnostic assessment, multiple fine-grained attributes are measured simultaneously. Attribute hierarchies are considered important structural features of cognitive diagnostic models (CDMs) that provide useful information about the nature of attributes. Templin and Bradshaw first introduced a hierarchical diagnostic classification…

Assessments with a large amount of small, similar, or often repetitive tasks are being used in educational, neurocognitive, and psychological contexts. For example, respondents are asked to recognize numbers or letters from a large pool of those and the number of correct answers is a count variable. In 1960, George Rasch developed the Rasch…

The lack of comprehensive language proficiency assessment models recognizing the nonlinearity and dynamicity of individual differences, as well as the fundamental differences between paper- and computer-assisted language assessments (CALA) served as the rationale to conduct the present study. Drawing on dynamic systems theory, a Nonlinear Dynamic…

Based on theories on vocabulary knowledge, grammar knowledge, and reading comprehension subcomponents, ten attributes/subskills were defined for 50 items from relevant subtests of TEM4 (Band Four of Test for English Majors in China). Cognitive diagnosis was conducted on the TEM4 data of the randomly sampled 2285 examinees (roughly at the B2 level)…

While scholars have proposed different models of language assessment literacy (LAL), these models have mostly comprised prescribed sets of components based on principles of good practice. As such, these models remain theoretical in nature, and represent the perspectives of language assessment researchers rather than stakeholders themselves. The…

Diagnostic classification models (DCMs) have recently become very popular both for research purposes and for real testing endeavors for student assessment. A plethora of DCM models give researchers and practitioners a wide range of options for student diagnosis and classification. One intriguing option that some DCM models offer is the possibility…

In this paper we use historic score-reporting records and test-taker metadata to inform data-driven recommendations that support international students in their choice of undergraduate institutions for study in the United States. We investigate the use of Structural Topic Modeling (STM) as a context-aware, probabilistic recommendation method that…

In recent years, harmonic regression models have been applied to implement quality control for educational assessment data consisting of multiple administrations and displaying seasonality. As with other types of regression models, it is imperative that model adequacy checking and model fit be appropriately conducted. However, there has been no…

The C-test is a type of gap-filling test designed to efficiently measure second language proficiency. The typical C-test consists of several short paragraphs with the second half of every second word deleted. The words with deleted parts are considered as items nested within the corresponding paragraph. Given this testlet structure, it is commonly…

Promoting diversity, equity, and inclusion (DEI) has become a unifying cause within applied linguistics. Whether highlighting the experiences of linguistically diverse learners across the social class spectrum or advocating for the inclusion of marginalized populations in research, researchers within the subfields of applied linguistics have…