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Wang, Ling Ling; Jian, Sun Xiao; Liu, Yan Lou; Xin, Tao – Applied Measurement in Education, 2023
Cognitive diagnostic assessment based on Bayesian networks (BN) is developed in this paper to evaluate student understanding of the physical concept of buoyancy. we propose a three-order granular-hierarchy BN model which accounts for both fine-grained attributes and high-level proficiencies. Conditional independence in the BN structure is tested…
Descriptors: Bayesian Statistics, Networks, Cognitive Measurement, Diagnostic Tests
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Ma, Hua; Huang, Zhuoxuan; Tang, Wensheng; Zhu, Haibin; Zhang, Hongyu; Li, Jingze – IEEE Transactions on Learning Technologies, 2023
To provide intelligent learning guidance for students in e-learning systems, it is necessary to accurately predict their performance in future exams by analyzing score data in past exams. However, existing research has not addressed the uncertain and dynamic features of students' cognitive status, whereas these features are essential for improving…
Descriptors: Prediction, Student Evaluation, Performance, Tests
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Xu, Tianshu; Wu, Xiaopeng; Sun, Siyu; Kong, Qiping – Psychology in the Schools, 2023
Considering the importance of mathematics in modern society, it is crucial to understand the cognitive processes involved in the acquisition of complex mathematical competency. As a new generation of evaluation theory, cognitive diagnosis has its unique advantages in personalized evaluation. Based on the mathematical cognitive framework of Trends…
Descriptors: Cognitive Processes, Mathematics Skills, Competence, Grade 4
D. Betsy McCoach; Anthony J. Gambino; Scott J. Peters; Daniel Long; Del Siegle – Annenberg Institute for School Reform at Brown University, 2023
Teacher rating scales (TRS) are often used to make service eligibility decisions for exceptional learners. Although TRS are regularly used to identify student exceptionalism either as part of an informal nomination process or through behavioral rating scales, there is little research documenting the between-teacher variance in teacher ratings or…
Descriptors: Rating Scales, Student Evaluation, Academically Gifted, Ability Identification
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Wang, Fei; Huang, Zhenya; Liu, Qi; Chen, Enhong; Yin, Yu; Ma, Jianhui; Wang, Shijin – IEEE Transactions on Learning Technologies, 2023
To provide personalized support on educational platforms, it is crucial to model the evolution of students' knowledge states. Knowledge tracing is one of the most popular technologies for this purpose, and deep learning-based methods have achieved state-of-the-art performance. Compared to classical models, such as Bayesian knowledge tracing, which…
Descriptors: Cognitive Measurement, Diagnostic Tests, Models, Prediction
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Provasnik, Stephen – Large-scale Assessments in Education, 2021
This paper presents the concepts and observations in the author's keynote address at the May 2019 "Opportunity versus Challenge: Exploring Usage of Log-File and Process Data in International Large-Scale Assessments" conference in Dublin, Ireland. This paper recaps briefly some key points that emerged at the December 2018 ETS symposium on…
Descriptors: Data Collection, Cognitive Processes, Ethics, Student Evaluation
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Youn Seon Lim; Catherine Bangeranye – International Journal of Testing, 2024
Feedback is a powerful instructional tool for motivating learning. But effective feedback, requires that instructors have accurate information about their students' current knowledge status and their learning progress. In modern educational measurement, two major theoretical perspectives on student ability and proficiency can be distinguished.…
Descriptors: Cognitive Measurement, Diagnostic Tests, Item Response Theory, Case Studies
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Mukasheva, Manargul; Omirzakova, Aisara – World Journal on Educational Technology: Current Issues, 2021
The study was carried out from 2018 to 2020 with the challenge - how to assess the level of computational thinking. The research design is mixed since the disclosure of mutual influence of the components of the chain 'learning programming -- computational thinking -- evaluating computational thinking' requires the use of both qualitative and…
Descriptors: Computation, Thinking Skills, Student Evaluation, Cognitive Measurement
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Chuang Wang; Dawson Hancock; Jin-Jy Shieh; Jeremy Hachen – Educational Research and Development Journal, 2023
The purpose of this study is to investigate the use of both formative and summative assessment in Taiwan and the United States. The focus is on the comparisons between undergraduate and graduate students and between U.S. and Taiwanese students in their attitudes toward the use of assessment in higher education. Responses from 349 undergraduate and…
Descriptors: Foreign Countries, Undergraduate Students, Graduate Students, Student Attitudes
Paulman, Briana E.; Johnson, Wendi L.; Roberts, Heather; Shierk, Angela – Communique, 2022
This article demonstrates the importance of school psychologists' understanding of which type of cognitive or developmental measure is most appropriate when working with young children with cerebral palsy (CP). Cognitive profiles vary greatly within this population and motor impairments also need to be taken into consideration. School…
Descriptors: School Psychologists, Cerebral Palsy, Student Characteristics, Student Needs
Li, Tingxuan – ProQuest LLC, 2019
In order to achieve broadening participation in computer science and other careers related to computing, middle school classrooms should provide students opportunities (tasks) to think like a computer scientist. Researchers in computing education promote the idea that programming skill should not be a pre-requisite for students to display…
Descriptors: Cognitive Measurement, Computation, Thinking Skills, Computer Science
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Meng, Lingling; Zhang, Mingxin; Zhang, Wanxue; Chu, Yu – Interactive Learning Environments, 2021
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…
Descriptors: Bayesian Statistics, Intelligent Tutoring Systems, Student Evaluation, Knowledge Level
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Bandyopadhyay, Subir; Szostek, Jana – Journal of Education for Business, 2019
Critical thinking is a skill that potential employers expect all graduates to possess. Hence, most business management programs consider critical thinking as an important student learning goal. Unfortunately, there is ambiguity about how to best assess critical thinking, both as a skill and a learning outcome. The authors empirically demonstrate…
Descriptors: Critical Thinking, Business Administration Education, College Students, Student Evaluation
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Sabatini, John; O'Reilly, Tenaha; Wang, Zuowei; Dreier, Kelsey – Grantee Submission, 2018
This book is a testament to the increasing role and importance of multiple source use in everyday and academic literacy activities in the 21st century. How should we introduce the topic of multiple sources here? For most readers, we need not, because this chapter is not their first literacy stop in the volume, so the topic has been adequately…
Descriptors: Vignettes, Information Sources, Reading Comprehension, Reading Tests
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Evran, Derya – International Journal of Modern Education Studies, 2019
Detection of students' ability levels is one of the common aims in educational studies. Cognitive Diagnosis Modeling approach has been used recently for the purpose of ability level detection by defined Q-matrices. To evaluate students' strengths and weaknesses, determine their mastery skills, and design instructions and interventions in learning…
Descriptors: Cognitive Measurement, Models, Foreign Countries, Achievement Tests
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