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Jiawei Xiong; George Engelhard; Allan S. Cohen – Measurement: Interdisciplinary Research and Perspectives, 2025
It is common to find mixed-format data results from the use of both multiple-choice (MC) and constructed-response (CR) questions on assessments. Dealing with these mixed response types involves understanding what the assessment is measuring, and the use of suitable measurement models to estimate latent abilities. Past research in educational…
Descriptors: Responses, Test Items, Test Format, Grade 8
Tamar Fuhrmann; Leah Rosenbaum; Aditi Wagh; Adelmo Eloy; Jacob Wolf; Paulo Blikstein; Michelle Wilkerson – Science Education, 2025
When learning about scientific phenomena, students are expected to "mechanistically" explain how underlying interactions produce the observable phenomenon and "conceptually" connect the observed phenomenon to canonical scientific knowledge. This paper investigates how the integration of the complementary processes of designing…
Descriptors: Mechanics (Physics), Thinking Skills, Scientific Concepts, Concept Formation
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
Cronenberg, Stephanie – Journal of Mixed Methods Research, 2020
Conceptual stances provide guidance to the mixed methods researcher as he or she makes decisions throughout the research process, including determining the dimensions of integration or levels at which mixing occurs. Only the dialectic conceptual stance specifically encourages mixing at the abstract paradigmatic level. This article outlines four…
Descriptors: Mixed Methods Research, Models, Philosophy, Data Analysis
Achilleas Mandrikas; Constantina Stefanidou; Constantine Skordoulis – Journal of STEM Education: Innovations and Research, 2024
A STEM education program entitled "Come rain or shine" implemented in a primary rural school in southern Greece as part of the "Diffusion of STEM (DI-STEM)" project and the results of its implementation are presented in this paper. The educational program deepened in weather education and intended to develop eight scientific…
Descriptors: Foreign Countries, STEM Education, Elementary Education, Program Implementation
Atsushi Miyaoka; Lauren Decker-Woodrow; Nancy Hartman; Barbara Booker; Erin Ottmar – Grantee Submission, 2023
More than ever in the past, researchers have access to broad, educationally relevant text data from sources such as literature databases (e.g., ERIC), an open-ended response from online courses/surveys, online discussion forums, digital essays, and social media. These advances in data availability can dramatically increase the possibilities for…
Descriptors: Coding, Models, Qualitative Research, Focus Groups
Poitras, Eric; Butcher, Kirsten R.; Orr, Matthew; Hudson, Michelle A.; Larson, Madlyn – Interactive Learning Environments, 2022
This study mined student interactions with visual representations as a means to automate assessment of learning in a complex, inquiry-based learning environment. Log trace data of 143 middle school students' interactions with an interactive map in Research Quest (an inquiry-based, online learning environment) were analyzed. Students used the…
Descriptors: Middle School Students, Electronic Learning, Maps, Science Instruction
Slater, Stefan; Baker, Ryan S.; Wang, Yeyu – International Educational Data Mining Society, 2020
Feature engineering, the construction of contextual and relevant features from system log data, is a crucial component of developing robust and interpretable models in educational data mining contexts. The practice of feature engineering depends on domain experts and system developers working in tandem in order to creatively identify actions and…
Descriptors: Data Analysis, Engineering, Classification, Models
Bosch, Nigel – Journal of Educational Data Mining, 2021
Automatic machine learning (AutoML) methods automate the time-consuming, feature-engineering process so that researchers produce accurate student models more quickly and easily. In this paper, we compare two AutoML feature engineering methods in the context of the National Assessment of Educational Progress (NAEP) data mining competition. The…
Descriptors: Accuracy, Learning Analytics, Models, National Competency Tests
Lee, Young Ri; Hong, Sehee – Journal of Experimental Education, 2019
The present study examines bias in parameter estimates and standard error in cross-classified random effect modeling (CCREM) caused by omitting the random interaction effects of the cross-classified factors, focusing on the effect of a sample size within cells and ratio of a small cell. A Monte Carlo simulation study was conducted to compare the…
Descriptors: Interaction, Models, Sample Size, Monte Carlo Methods
Michael Gilraine; Jeffrey Penney – Annenberg Institute for School Reform at Brown University, 2021
An administrative rule allowed students who failed an exam to retake it shortly after, triggering strong `teach to the test' incentives to raise these students' test scores for the retake. We develop a model that accounts for truncation and find that these students score 0.14 standard deviations higher on the retest. Using a regression…
Descriptors: Tests, Models, Scores, Test Coaching
Reed, Megan H.; Jenkins, Tom; Kenyon, Lisa – Science Teacher, 2019
Nitrogen- or phosphorus-based fertilizers, used in agriculture, can run off into nearby waterways during periods of heavy rain or high flow and cause harmful blooms (Paerl et al. 2016), low oxygen (Joyce 2000), and decreased biodiversity (Sebens 1994). Studies of the effects wetlands can have on water and habitat quality (Verhoeven and Meuleman…
Descriptors: Natural Resources, Biodiversity, Grade 9, Ecology
Kinnebrew, John S.; Segedy, James R.; Biswas, Gautam – IEEE Transactions on Learning Technologies, 2017
Research in computer-based learning environments has long recognized the vital role of adaptivity in promoting effective, individualized learning among students. Adaptive scaffolding capabilities are particularly important in open-ended learning environments, which provide students with opportunities for solving authentic and complex problems, and…
Descriptors: Computer Assisted Instruction, Problem Solving, Learning, Student Behavior
Aksoy, Esra; Narli, Serkan; Aksoy, Mehmet Akif – International Journal of Research in Education and Science, 2018
In the identification process, there may be gifted students who may be unnoticed or students who are misdiagnosed and are disappointed. In this context, this study is a step that may solve these two problems about the identification of mathematically gifted students with the help of data mining, which is data analysis methodology that has been…
Descriptors: Academically Gifted, Talent Identification, Data Collection, Mathematics Instruction