In classroom assessments, examinees can often answer test items multiple times, resulting in sequential multiple-attempt data. Sequential diagnostic classification models (DCMs) have been developed for such data. As student learning processes may be aligned with a hierarchy of measured traits, this study aimed to develop a sequential hierarchical…

Cognitive diagnosis models (CDMs) are the assessment tools that provide valuable formative feedback about skill mastery at both the individual and population level. Recent work has explored the performance of CDMs with small sample sizes but has focused solely on the estimates of individual profiles. The current research focuses on obtaining…

This study compared 2 units of analysis for assessing acquisition mastery during sight word instruction for 3 participants. The unit of analysis refers to the specific performances that criteria are applied to, either sets of stimuli or individual operants. In the Set Analysis condition, we applied the acquisition-performance criterion to the…

Instructors assess the acquisition of new skills by delivering blocks of trials containing multiple operants. Mastery is evaluated as percentage correct across all operants in the block. The purpose of the current study was to investigate this traditional mastery criterion arrangement compared to an analysis of mastery at the level of individual…

Procedural fidelity is defined as the extent to which the independent variable is implemented as prescribed. Research using computerized tasks has shown that fidelity errors involving consequences for behavior can hinder skill acquisition. However, studies examining the effects of these errors once skills have been mastered are lacking. Thus, this…

This article explores the limitations of traditional maximum performance tests in psychological assessments within educational settings, highlighting the need for efficiency assessments to better understand students' real-world capabilities. While maximum performance tests like IQ and achievement tests reveal peak abilities under optimal…

Self-efficacy, the beliefs learners hold about what they can do, develops largely from whether learners perceive and interpret their experiences as successful (i.e., perceived mastery). In mathematics, the relationship between perceived mastery and self-efficacy has been well established. Less is known about the factors that may influence…

We investigated the acquisition of Hindi split ergativity (zero or "-ne" marking) and Hindi differential object marking (DOM; zero or "-ko" marking) by L1 speakers of Dutch. Both grammatical phenomena are conditioned by multiple syntactic and semantic features. On a descriptive level, the study aims to examine when and how…

For students to advance beyond arithmetic, they must learn how to attend to the structure of math notation. This process can be challenging due to students' left-to-right computing tendencies. Brackets are used in mathematics to indicate precedence but can also be used as superfluous cues and perceptual grouping mechanisms in instructional…

We have investigated the temporal patterns of algebra (N = 606) and calculus (N = 507) introductory physics students practicing multiple basic physics topics several times throughout the semester using an online mastery homework application called science, technology, engineering, and mathematics (STEM) fluency aimed at improving basic physics…

Bayesian knowledge tracing model (BKT) is a typical student knowledge assessment method. It is widely used in intelligent tutoring systems. In the standard BKT model, all knowledge and skills are independent of each other. However, in the process of student learning, they have a very close relation. A student may understand knowledge B better when…

Cognitive diagnosis models (CDMs) typically assume skill attributes with discrete (often binary) levels of skill mastery, making the existence of skill continuity an anticipated form of model misspecification. In this article, misspecification due to skill continuity is argued to be of particular concern for several CDM applications due to the…

Considerable attention has been given to methods for knowledge estimation, a category of methods for automatic assessment of a student's degree of skill mastery or knowledge at a specific time. Knowledge estimation is frequently used to make decisions about when a student has reached mastery and is ready to advance to new material, but there has…

The purpose of this case study is to demonstrate how to utilize machine learning approaches to analyze student process data for validating and informing digital game-based assessments (DGBAs) with an evidence-centered game design (ECgD). The first analysis was conducted to examine whether students' mastery of the overall skill required by the game…

Cognitive diagnostic models (CDMs) are a family of psychometric models designed to provide categorical classifications for multiple latent attributes. CDMs provide more granular evidence than other psychometric models and have potential for guiding teaching and learning decisions in the classroom. However, CDMs have primarily been conducted using…