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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
Christopher D. Wilson; Kevin C. Haudek; Jonathan F. Osborne; Zoë E. Buck Bracey; Tina Cheuk; Brian M. Donovan; Molly A. M. Stuhlsatz; Marisol M. Santiago; Xiaoming Zhai – Journal of Research in Science Teaching, 2024
Argumentation is fundamental to science education, both as a prominent feature of scientific reasoning and as an effective mode of learning--a perspective reflected in contemporary frameworks and standards. The successful implementation of argumentation in school science, however, requires a paradigm shift in science assessment from the…
Descriptors: Middle School Students, Competence, Science Process Skills, Persuasive Discourse
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
Boorse, Jaclin; Van Norman, Ethan R. – Psychology in the Schools, 2021
Prior research on the Measures of Academic Progress (MAP), a computer-adaptive test distributed by the Northwest Evaluation Association, has primarily focused on the Reading MAP for screening/benchmarking in elementary grades. The purpose of this study was to explore the functional form of growth and the extent to which student variability in…
Descriptors: Achievement Tests, Mathematics Tests, Adaptive Testing, Computer Assisted Testing
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
Ethan R. Van Norman; Emily R. Forcht – Journal of Education for Students Placed at Risk, 2024
This study evaluated the forecasting accuracy of trend estimation methods applied to time-series data from computer adaptive tests (CATs). Data were collected roughly once a month over the course of a school year. We evaluated the forecasting accuracy of two regression-based growth estimation methods (ordinary least squares and Theil-Sen). The…
Descriptors: Data Collection, Predictive Measurement, Predictive Validity, Predictor Variables
Mark Wilson; Kathleen Scalise; Perman Gochyyev – Educational Psychology, 2019
In this article, we describe a software system for assessment development in online learning environments in contexts where there are robust links to cognitive modelling including domain and student modelling. BEAR Assessment System Software (BASS) establishes both a theoretical basis for the domain modelling logic, and offers tools for delivery,…
Descriptors: Computer Software, Electronic Learning, Test Construction, Intelligent Tutoring Systems
Levin, Nathan A. – Journal of Educational Data Mining, 2021
The Big Data for Education Spoke of the NSF Northeast Big Data Innovation Hub and ETS co-sponsored an educational data mining competition in which contestants were asked to predict efficient time use on the NAEP 8th grade mathematics computer-based assessment, based on the log file of a student's actions on a prior portion of the assessment. In…
Descriptors: Learning Analytics, Data Collection, Competition, Prediction
Matayoshi, Jeffrey; Uzun, Hasan; Cosyn, Eric – International Educational Data Mining Society, 2022
Knowledge space theory (KST) is a mathematical framework for modeling and assessing student knowledge. While KST has successfully served as the foundation of several learning systems, recent advancements in machine learning provide an opportunity to improve on purely KST-based approaches to assessing student knowledge. As such, in this work we…
Descriptors: Knowledge Level, Mathematical Models, Learning Experience, Comparative Analysis
Schiffl, Iris – Universal Journal of Educational Research, 2016
Science standards have been a topic in educational research in Austria for about ten years now. Starting in 2005, competency structure models have been developed for junior and senior classes of different school types. After evaluating these models, prototypic tasks were created to point out the meaning of the models to teachers. At the moment,…
Descriptors: Science Education, Standards, Foreign Countries, Models
Kupiainen, Sirkku; Vainikainen, Mari-Pauliina; Marjanen, Jukka; Hautamäki, Jarkko – Journal of Educational Psychology, 2014
The role of time on task (TOT) for students' attainment in a low-stakes assessment of cross-curricular skills was examined using the log data collected in the computer-based assessment (CBA). Two structural equation models were compared: Model 1, in which students' test scores were explained by grade point average (GPA) together with mastery and…
Descriptors: Computer Assisted Testing, Time on Task, Grade Point Average, Scores
Ramírez-Montoya, María-Soledad, Ed. – IGI Global, 2017
Educational strategies have evolved over the years, due to research breakthroughs and the application of technology. By using the latest learning innovations, curriculum and instructional design can be enhanced and strengthened. The "Handbook of Research on Driving STEM Learning with Educational Technologies" is an authoritative…
Descriptors: Guides, STEM Education, Educational Technology, Foreign Countries
Evanini, Keelan; Heilman, Michael; Wang, Xinhao; Blanchard, Daniel – ETS Research Report Series, 2015
This report describes the initial automated scoring results that were obtained using the constructed responses from the Writing and Speaking sections of the pilot forms of the "TOEFL Junior"® Comprehensive test administered in late 2011. For all of the items except one (the edit item in the Writing section), existing automated scoring…
Descriptors: Computer Assisted Testing, Automation, Language Tests, Second Language Learning
Lin, Chen-Yu; Wang, Tzu-Hua – EURASIA Journal of Mathematics, Science & Technology Education, 2017
This research explored how different models of Web-based dynamic assessment in remedial teaching improved junior high school student learning achievement and their misconceptions about the topic of "Weather and Climate." This research adopted a quasi-experimental design. A total of 58 7th graders participated in this research.…
Descriptors: Program Implementation, Computer Assisted Testing, Student Evaluation, Evaluation Methods
Gobert, Janice D.; Sao Pedro, Michael A.; Baker, Ryan S. J. D.; Toto, Ermal; Montalvo, Orlando – Journal of Educational Data Mining, 2012
We present "Science Assistments," an interactive environment, which assesses students' inquiry skills as they engage in inquiry using science microworlds. We frame our variables, tasks, assessments, and methods of analyzing data in terms of "evidence-centered design." Specifically, we focus on the "student model," the…
Descriptors: Data Analysis, Inquiry, Science Process Skills, Student Evaluation
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