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Reagan Mozer; Luke Miratrix; Jackie Eunjung Relyea; James S. Kim – Journal of Educational and Behavioral Statistics, 2024
In a randomized trial that collects text as an outcome, traditional approaches for assessing treatment impact require that each document first be manually coded for constructs of interest by human raters. An impact analysis can then be conducted to compare treatment and control groups, using the hand-coded scores as a measured outcome. This…
Descriptors: Scoring, Evaluation Methods, Writing Evaluation, Comparative Analysis
Teaching Mathematics Based on Integrating Reading Strategies and Working Memory in Elementary School
Farideh Hamidi; Shokoofeh Soleymani; Sara Dazy; Maryam Meshkat – Athens Journal of Education, 2024
This study strived to determine the effectiveness of integrative teaching of reading strategies and working memory on basic math and problem-solving skills. It is a quasi-experimental pretest-posttest study carried out on 50 second-graders from Chahashk Shandiz village in the academic year of 2020-2021 who were randomly selected by cluster…
Descriptors: Mathematics Instruction, Reading Strategies, Grade 2, Elementary School Students
Torkildsen, Janne von Koss; Bratlie, Siri Steffensen; Kristensen, Jarl Kleppe; Gustafsson, Jan-Eric; Lyster, Solveig-Alma Halaas; Snow, Catherine; Hulme, Charles; Mononen, Riikka-Maija; Naess, Kari-Anne B.; López-Pedersen, Anita; Wie, Ona Bø; Hagtvet, Bente – Journal of Educational Psychology, 2022
Morphemes, the smallest meaning-bearing units of language, recur in many words. Therefore, morphological knowledge can facilitate the comprehension of novel words. This study tested the effectiveness of a morphological training program on children's learning and retention of exposed words and morphologically related unexposed words compared with…
Descriptors: Morphemes, Morphology (Languages), Language Processing, Teaching Methods
Zhongdi Wu; Eric Larson; Makoto Sano; Doris Baker; Nathan Gage; Akihito Kamata – Grantee Submission, 2023
In this investigation we propose new machine learning methods for automated scoring models that predict the vocabulary acquisition in science and social studies of second grade English language learners, based upon free-form spoken responses. We evaluate performance on an existing dataset and use transfer learning from a large pre-trained language…
Descriptors: Prediction, Vocabulary Development, English (Second Language), Second Language Learning