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Sun-Joo Cho; Amanda Goodwin; Matthew Naveiras; Paul De Boeck – Grantee Submission, 2024
Explanatory item response models (EIRMs) have been applied to investigate the effects of person covariates, item covariates, and their interactions in the fields of reading education and psycholinguistics. In practice, it is often assumed that the relationships between the covariates and the logit transformation of item response probability are…
Descriptors: Item Response Theory, Test Items, Models, Maximum Likelihood Statistics
Sun-Joo Cho; Amanda Goodwin; Matthew Naveiras; Paul De Boeck – Journal of Educational Measurement, 2024
Explanatory item response models (EIRMs) have been applied to investigate the effects of person covariates, item covariates, and their interactions in the fields of reading education and psycholinguistics. In practice, it is often assumed that the relationships between the covariates and the logit transformation of item response probability are…
Descriptors: Item Response Theory, Test Items, Models, Maximum Likelihood Statistics
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
Sun-Joo Cho; Amanda Goodwin; Matthew Naveiras; Jorge Salas – Grantee Submission, 2024
Despite the growing interest in incorporating response time data into item response models, there has been a lack of research investigating how the effect of speed on the probability of a correct response varies across different groups (e.g., experimental conditions) for various items (i.e., differential response time item analysis). Furthermore,…
Descriptors: Item Response Theory, Reaction Time, Models, Accuracy
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
Yi Gui – ProQuest LLC, 2024
This study explores using transfer learning in machine learning for natural language processing (NLP) to create generic automated essay scoring (AES) models, providing instant online scoring for statewide writing assessments in K-12 education. The goal is to develop an instant online scorer that is generalizable to any prompt, addressing the…
Descriptors: Writing Tests, Natural Language Processing, Writing Evaluation, Scoring
Baysal, Esra; Sevinc, Serife – International Journal of Mathematical Education in Science and Technology, 2022
This study investigated the role of the bar model method, a significant aspect of the Singapore mathematics curriculum, in the remediation of seventh-grade students' errors on algebra word problems. To accomplish this purpose, we first assessed students' errors on a written test involving algebra problems and identified ten students based on the…
Descriptors: Grade 7, Word Problems (Mathematics), Mathematics Instruction, Error Patterns
Safadi, Rafi' – International Journal of Science Education, 2022
Troubleshooting activities require students to diagnose teacher-crafted erroneous examples by detecting and explaining the conceptual errors driving them. In a previous study, the author tested whether diagnosing erroneous examples and then scoring them using a rubric that contained the related worked examples, a step-by-step strategy to solve a…
Descriptors: Error Patterns, Scientific Concepts, Physics, Science Instruction
Rakes, Christopher R.; Ronau, Robert N. – International Journal of Research in Education and Science, 2019
The present study examined the ability of content domain (algebra, geometry, rational number, probability) to classify mathematics misconceptions. The study was conducted with 1,133 students in 53 algebra and geometry classes taught by 17 teachers from three high schools and one middle school across three school districts in a Midwestern state.…
Descriptors: Mathematics Instruction, Secondary School Teachers, Middle School Teachers, Misconceptions
An Application of a Random Mixture Nominal Item Response Model for Investigating Instruction Effects
Choi, Hye-Jeong; Cohen, Allan S.; Bottge, Brian A. – Grantee Submission, 2016
The purpose of this study was to apply a random item mixture nominal item response model (RIM-MixNRM) for investigating instruction effects. The host study design was a pre-test-and-post-test, school-based cluster randomized trial. A RIM-MixNRM was used to identify students' error patterns in mathematics at the pre-test and the post-test.…
Descriptors: Item Response Theory, Instructional Effectiveness, Test Items, Models
Jupri, Al; Drijvers, Paul – EURASIA Journal of Mathematics, Science & Technology Education, 2016
To investigate student difficulties in solving word problems in algebra, we carried out a teaching experiment involving 51 Indonesian students (12/13 year-old) who used a digital mathematics environment. The findings were backed up by an interview study, in which eighteen students (13/14 year-old) were involved. The perspective of mathematization,…
Descriptors: Foreign Countries, Grade 7, Algebra, Word Problems (Mathematics)
Tulis, Maria; Steuer, Gabriele; Dresel, Markus – Frontline Learning Research, 2016
Errors bear the potential to improve knowledge acquisition, provided that learners are able to deal with them in an adaptive and reflexive manner. However, learners experience a host of different--often impeding or maladaptive--emotional and motivational states in the face of academic errors. Research has made few attempts to develop a theory that…
Descriptors: Error Patterns, Metacognition, Learning Processes, Learning Motivation
Star, Jon R.; Foegen, Anne; Larson, Matthew R.; McCallum, William G.; Porath, Jane; Zbiek, Rose Mary; Caronongan, Pia; Furgeson, Joshua,; Keating, Betsy; Lyskawa, Julia – What Works Clearinghouse, 2015
Mastering algebra is important for future math and postsecondary success. Educators will find practical recommendations for how to improve algebra instruction in the What Works Clearinghouse (WWC) practice guide, "Teaching Strategies for Improving Algebra Knowledge in Middle and High School Students". The methods and examples included in…
Descriptors: Algebra, Mathematics Instruction, Secondary School Mathematics, Teaching Methods
Hershkovitz, Arnon; Baker, Ryan S. J. d.; Gobert, Janice; Wixon, Michael; Sao Pedro, Michael – Grantee Submission, 2013
In recent years, an increasing number of analyses in Learning Analytics and Educational Data Mining (EDM) have adopted a "Discovery with Models" approach, where an existing model is used as a key component in a new EDM/analytics analysis. This article presents a theoretical discussion on the emergence of discovery with models, its…
Descriptors: Learning Analytics, Models, Learning Processes, Case Studies
Retnowati, Endah, Ed.; Suprapto, Ed.; Jerusalem, Mohammad Adam, Ed.; Sugiyarto, Kristian, Ed.; Wagiran, Ed. – Routledge, Taylor & Francis Group, 2018
This proceedings volume of InCoTEPD 2018 covers many ideas for handling a wide variety of challenging issues in the field of education. The outstanding ideas dealing with these issues result in innovation of the system. There are many innovation strategies resulting from recent research that are discussed in this book. These strategies will become…
Descriptors: Educational Innovation, Knowledge Level, Skill Development, Vocational Education
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