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Showing 1 to 15 of 25 results Save | Export
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Duo Liu; Lei Wang; Terry Tin-Yau Wong; R. Malatesha Joshi – Journal of Research in Reading, 2024
Background: Rapid automatised naming (RAN) has been found to predict children's reading and arithmetic abilities. However, the underlying mechanisms for its involvement in the two abilities are not clear. This study examines how RAN shared variances with domain-general and domain-specific abilities in predicting reading and arithmetic in Chinese…
Descriptors: Grade 3, Elementary School Students, Foreign Countries, Automation
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Figen Durkaya – Shanlax International Journal of Education, 2023
The present study has been developed in order to inquire the cognitive awareness of the 2nd grade-level students of the Science Teaching program on "sensors", which has an important place in the development of the robotic and automation systems. In the study, the method of case study, which is one of the qualitative research motifs, was…
Descriptors: Preservice Teachers, Science Teachers, Grade 2, Teacher Education Programs
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Wilson, Joshua; Myers, Matthew C.; Potter, Andrew – Assessment in Education: Principles, Policy & Practice, 2022
We investigated the promise of a novel approach to formative writing assessment at scale that involved an automated writing evaluation (AWE) system called MI Write. Specifically, we investigated elementary teachers' perceptions and implementation of MI Write and changes in students' writing performance in three genres from Fall to Spring…
Descriptors: Writing Evaluation, Formative Evaluation, Automation, Elementary School Teachers
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Charles Hulme; Joshua McGrane; Mihaela Duta; Gillian West; Denise Cripps; Abhishek Dasgupta; Sarah Hearne; Rachel Gardner; Margaret Snowling – Language, Speech, and Hearing Services in Schools, 2024
Purpose: Oral language skills provide a critical foundation for formal education and especially for the development of children's literacy (reading and spelling) skills. It is therefore important for teachers to be able to assess children's language skills, especially if they are concerned about their learning. We report the development and…
Descriptors: Automation, Language Tests, Standardized Tests, Test Construction
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Chen, Dandan; Hebert, Michael; Wilson, Joshua – American Educational Research Journal, 2022
We used multivariate generalizability theory to examine the reliability of hand-scoring and automated essay scoring (AES) and to identify how these scoring methods could be used in conjunction to optimize writing assessment. Students (n = 113) included subsamples of struggling writers and non-struggling writers in Grades 3-5 drawn from a larger…
Descriptors: Reliability, Scoring, Essays, Automation
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De Angelis, Marta; Miranda, Sergio – Research on Education and Media, 2023
This paper aims to illustrate an automated system developed to give formative and personalized feedback to teachers in training. It is an expert system (Paviotti, Rossi & Zarka, 2012) that uses concrete examples, cases and scenarios to guide the engaged learners (Leake, 1996). In this regard, this system is able to create questionnaires,…
Descriptors: Inservice Teacher Education, Elementary School Teachers, Secondary School Teachers, Early Childhood Teachers
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Nese, Joseph F. T.; Kamata, Akihito – School Psychology, 2021
Curriculum-based measurement of oral reading fluency (CBM-R) is widely used across the United States as a strong indicator of comprehension and overall reading achievement, but has several limitations including errors in administration and large standard errors of measurement. The purpose of this study is to compare scoring methods and passage…
Descriptors: Curriculum Based Assessment, Oral Reading, Reading Fluency, Reading Tests
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Christopher Dignam; Candace M. Smith; Amy L. Kelly – Journal of Education in Science, Environment and Health, 2025
The evolution of artificial intelligence (AI) and robotics in education has transitioned from automation toward emotionally responsive learning systems through artificial emotional intelligence (AEI). While AI-driven robotics has enhanced instructional automation, AEI introduces an affective dimension by recognizing and responding to human…
Descriptors: Robotics, Artificial Intelligence, Teaching Methods, Computer Software
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Renu Balyan; Tracy Arner; Tong Li; Ellen Orcutt; Reese Butterfuss; Panayiota Kendeou; Danielle McNamara – Grantee Submission, 2022
Speech technology (automated speech recognition -- ASR and text-to-speech) offers great promise in the field of automated literacy and reading tutors for children. Students in third and fourth grades struggle with generating longer strings of text on a QWERTY keyboard because they still "hunt and peck" for AQ1 the letters and symbols…
Descriptors: Assistive Technology, Technology Integration, Intelligent Tutoring Systems, Automation
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Rezat, Sebastian – ZDM: Mathematics Education, 2021
One of the most prevalent features of digital mathematics textbooks, compared to traditional ones, is the provision of automated feedback on students' solutions. Since feedback is regarded as an important factor that influences learning, this is often seen as an affordance of digital mathematics textbooks. While there is a large body of mainly…
Descriptors: Automation, Feedback (Response), Electronic Publishing, Textbooks
Mozer, Reagan; Miratrixy, Luke; Relyea, Jackie Eunjung; Kim, James S. – Annenberg Institute for School Reform at Brown University, 2021
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, Automation, Data Analysis, Natural Language Processing
Wilson, Joshua; Rodrigues, Jessica – Grantee Submission, 2020
The present study leveraged advances in automated essay scoring (AES) technology to explore a proof of concept for a writing screener using the "Project Essay Grade" (PEG) program. First, the study investigated the extent to which an AES-scored multi-prompt writing screener accurately classified students as at risk of failing a Common…
Descriptors: Writing Tests, Screening Tests, Classification, Accuracy
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Younes-Aziz Bachiri; Hicham Mouncif; Belaid Bouikhalene; Radoine Hamzaoui – Turkish Online Journal of Distance Education, 2024
This study examined the integration of artificial intelligence-powered speech recognition technology within early reading assessments in Morocco's Teaching at the Right Level (TaRL) program. The purpose was to evaluate the effectiveness of an automated speech recognition tool compared to traditional paper-based assessments in improving reading…
Descriptors: Foreign Countries, Artificial Intelligence, Speech Communication, Identification
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L. Hannah; E. E. Jang; M. Shah; V. Gupta – Language Assessment Quarterly, 2023
Machines have a long-demonstrated ability to find statistical relationships between qualities of texts and surface-level linguistic indicators of writing. More recently, unlocked by artificial intelligence, the potential of using machines to identify content-related writing trait criteria has been uncovered. This development is significant,…
Descriptors: Validity, Automation, Scoring, Writing Assignments
Sano, Makoto; Baker, Doris Luft; Collazo, Marlen; Le, Nancy; Kamata, Akihito – Grantee Submission, 2020
Purpose: Explore how different automated scoring (AS) models score reliably the expressive language and vocabulary knowledge in depth of young second grade Latino English learners. Design/methodology/approach: Analyze a total of 13,471 English utterances from 217 Latino English learners with random forest, end-to-end memory networks, long…
Descriptors: English Language Learners, Hispanic American Students, Elementary School Students, Grade 2
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