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Kole A. Norberg; Husni Almoubayyed; Logan De Ley; April Murphy; Kyle Weldon; Steve Ritter – International Journal of Artificial Intelligence in Education, 2025
Large language models (LLMs) offer an opportunity to make large-scale changes to educational content that would otherwise be too costly to implement. The work here highlights how LLMs (in particular GPT-4) can be prompted to revise educational math content ready for large scale deployment in real-world learning environments. We tested the ability…
Descriptors: Artificial Intelligence, Computer Software, Computational Linguistics, Educational Change
Kole A. Norberg; Husni Almoubayyed; Logan De Ley; April Murphy; Kyle Weldon; Steve Ritter – Grantee Submission, 2024
Large language models (LLMs) offer an opportunity to make large-scale changes to educational content that would otherwise be too costly to implement. The work here highlights how LLMs (in particular GPT-4) can be prompted to revise educational math content ready for large scale deployment in real-world learning environments. We tested the ability…
Descriptors: Artificial Intelligence, Computer Software, Computational Linguistics, Educational Change
Hatcher, Ryan C.; Breaux, Kristina C.; Liu, Xiaochen; Bray, Melissa A.; Ottone-Cross, Karen L.; Courville, Troy; Luria, Sarah R.; Langley, Susan Dulong – Journal of Psychoeducational Assessment, 2017
Children's oral language skills typically begin to develop sooner than their written language skills; however, the four language systems (listening, speaking, reading, and writing) then develop concurrently as integrated strands that influence one another. This research explored relationships between students' errors in language comprehension of…
Descriptors: Children, Error Patterns, Listening Comprehension, Reading Comprehension
Kogar, Esin Yilmaz; Kelecioglu, Hülya – Journal of Education and Learning, 2017
The purpose of this research is to first estimate the item and ability parameters and the standard error values related to those parameters obtained from Unidimensional Item Response Theory (UIRT), bifactor (BIF) and Testlet Response Theory models (TRT) in the tests including testlets, when the number of testlets, number of independent items, and…
Descriptors: Item Response Theory, Models, Mathematics Tests, Test Items
Mencias, Yaweh Lady E.; De Vera, Presley V. – Journal of English as an International Language, 2018
The study anchors on the Linguistic research tradition of Error Analysis (EA), focused on the grammatical errors, specifically on "verb tenses" manifested in the sentences of Japanese ESL learners. The entire respondent population was drawn from the pool of registered learners in 2017 at the Clark Institute of the Philippines Foundation,…
Descriptors: Error Analysis (Language), Verbs, Morphemes, English (Second Language)
Pearlman, Leslie – ProQuest LLC, 2011
This dissertation examines the patterns and types of mistakes students make on a large-scale mathematics assessment, and puts these patterns into perspective based on the textbook used and the specific content covered in a student's classroom. In order to investigate the nature of these patterns, I employ a method of analysis originally designed…
Descriptors: State Standards, Statistical Significance, Mathematics Education, Social Networks
Peer reviewedPutnam, Lillian R. – Perceptual and Motor Skills, 1981
The Minnesota Percepto-Diagnostic Test (MPDT) classifies remedial readers into three groups: primary, secondary, organic. This study of subjects aged 7-22 sought to determine if a significant negative relationship existed between (MPDT) scores and reading achievement and if error patterns differ significantly within and between the…
Descriptors: Adults, Correlation, Diagnostic Tests, Elementary Secondary Education

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