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Hsu, Chia-Ling; Chen, Yi-Hsin; Wu, Yi-Jhen – Practical Assessment, Research & Evaluation, 2023
Correct specifications of hierarchical attribute structures in analyses using diagnostic classification models (DCMs) are pivotal because misspecifications can lead to biased parameter estimations and inaccurate classification profiles. This research is aimed to demonstrate DCM analyses with various hierarchical attribute structures via Bayesian…
Descriptors: Bayesian Statistics, Computation, International Assessment, Achievement Tests
Sami Baral; Eamon Worden; Wen-Chiang Lim; Zhuang Luo; Christopher Santorelli; Ashish Gurung; Neil Heffernan – Grantee Submission, 2024
The effectiveness of feedback in enhancing learning outcomes is well documented within Educational Data Mining (EDM). Various prior research have explored methodologies to enhance the effectiveness of feedback to students in various ways. Recent developments in Large Language Models (LLMs) have extended their utility in enhancing automated…
Descriptors: Automation, Scoring, Computer Assisted Testing, Natural Language Processing
Anh-Duc Hoang – International Education Journal: Comparative Perspectives, 2024
We conducted an experiment to determine the impact of short-term pressure on 1,228 Grade 8 students' outcomes when performing simple math exercises. We required all students to complete 100 simple math questions for 90 seconds. We analysed students' results and then divided them into three groups: (i) a control group who did nothing; (ii) a group…
Descriptors: Stress Variables, Academic Achievement, Outcomes of Education, Middle School Students
Hai Li; Wanli Xing; Chenglu Li; Wangda Zhu; Simon Woodhead – Journal of Learning Analytics, 2025
Knowledge tracing (KT) is a method to evaluate a student's knowledge state (KS) based on their historical problem-solving records by predicting the next answer's binary correctness. Although widely applied to closed-ended questions, it lacks a detailed option tracing (OT) method for assessing multiple-choice questions (MCQs). This paper introduces…
Descriptors: Mathematics Tests, Multiple Choice Tests, Computer Assisted Testing, Problem Solving
Gao, Xuliang; Ma, Wenchao; Wang, Daxun; Cai, Yan; Tu, Dongbo – Journal of Educational and Behavioral Statistics, 2021
This article proposes a class of cognitive diagnosis models (CDMs) for polytomously scored items with different link functions. Many existing polytomous CDMs can be considered as special cases of the proposed class of polytomous CDMs. Simulation studies were carried out to investigate the feasibility of the proposed CDMs and the performance of…
Descriptors: Cognitive Measurement, Models, Test Items, Scoring
Baral, Sami; Botelho, Anthony F.; Erickson, John A.; Benachamardi, Priyanka; Heffernan, Neil T. – International Educational Data Mining Society, 2021
Open-ended questions in mathematics are commonly used by teachers to monitor and assess students' deeper conceptual understanding of content. Student answers to these types of questions often exhibit a combination of language, drawn diagrams and tables, and mathematical formulas and expressions that supply teachers with insight into the processes…
Descriptors: Scoring, Automation, Mathematics Tests, Student Evaluation
Jahudin, Janet; Siew, Nyet Moi – Problems of Education in the 21st Century, 2023
Algebraic Thinking Skills (ATS) are one of the skills that students need to master in order to solve nonroutine problems. These skills are also necessary as a foundation for students preparing to enter university studies and fields of work that require logical and analytical thinking. However, Malaysian students' performance in solving algebraic…
Descriptors: Algebra, Thinking Skills, Mathematics Skills, Problem Solving
Qi Huang; Daniel M. Bolt; Weicong Lyu – Large-scale Assessments in Education, 2024
Large scale international assessments depend on invariance of measurement across countries. An important consideration when observing cross-national differential item functioning (DIF) is whether the DIF actually reflects a source of bias, or might instead be a methodological artifact reflecting item response theory (IRT) model misspecification.…
Descriptors: Test Items, Item Response Theory, Test Bias, Test Validity
Ji-Eun Lee; Amisha Jindal; Sanika Nitin Patki; Ashish Gurung; Reilly Norum; Erin Ottmar – Interactive Learning Environments, 2024
This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined 1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction and 2)…
Descriptors: Teaching Methods, Algorithms, Mathematics Tests, Computer Games
Charlotte Z. Mann; Jiaying Wang; Adam Sales; Johann A. Gagnon-Bartsch – Grantee Submission, 2024
The gold-standard for evaluating the effect of an educational intervention on student outcomes is running a randomized controlled trial (RCT). However, RCTs may often be small due to logistical considerations, and resulting treatment effect estimates may lack precision. Recent methods improve experimental precision by incorporating information…
Descriptors: Intervention, Outcomes of Education, Randomized Controlled Trials, Data Use
Ji-Eun Lee; Amisha Jindal; Sanika Nitin Patki; Ashish Gurung; Reilly Norum; Erin Ottmar – Grantee Submission, 2023
This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction; and…
Descriptors: Teaching Methods, Algorithms, Mathematics Tests, Computer Games
Ketterlin-Geller, Leanne R.; Perry, Lindsey; Adams, Elizabeth – Applied Measurement in Education, 2019
Despite the call for an argument-based approach to validity over 25 years ago, few examples exist in the published literature. One possible explanation for this outcome is that the complexity of the argument-based approach makes implementation difficult. To counter this claim, we propose that the Assessment Triangle can serve as the overarching…
Descriptors: Validity, Educational Assessment, Models, Screening Tests
Pham, Duy N.; Wells, Craig S.; Bauer, Malcolm I.; Wylie, E. Caroline; Monroe, Scott – Applied Measurement in Education, 2021
Assessments built on a theory of learning progressions are promising formative tools to support learning and teaching. The quality and usefulness of those assessments depend, in large part, on the validity of the theory-informed inferences about student learning made from the assessment results. In this study, we introduced an approach to address…
Descriptors: Formative Evaluation, Mathematics Instruction, Mathematics Achievement, Middle School Students
Ma, Wenchao; de la Torre, Jimmy – Journal of Educational and Behavioral Statistics, 2019
Solving a constructed-response item usually requires successfully performing a sequence of tasks. Each task could involve different attributes, and those required attributes may be "condensed" in various ways to produce the responses. The sequential generalized deterministic input noisy "and" gate model is a general cognitive…
Descriptors: Test Items, Cognitive Measurement, Models, Hypothesis Testing
Lin, Jing-Wen; Yu, Ruan-Ching – Asia Pacific Journal of Education, 2022
Modelling ability is one of the essential elements of the latest educational reforms, and Trends in International Mathematics and Science Study (TIMSS) is a curriculum-based assessment which allows educational systems worldwide to inspect the curricular influences. The aims of this study were to examine the role of modelling ability in the…
Descriptors: Grade 8, Educational Change, Cross Cultural Studies, Test Items