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Zhao, Ruibin; Zhuang, Yipeng; Zou, Di; Xie, Qin; Yu, Philip L. H. – Education and Information Technologies, 2023
Grading assignments is inherently subjective and time-consuming; automatic scoring tools can greatly reduce teacher workload and shorten the time needed for providing feedback to learners. The purpose of this paper is to propose a novel method for automatically scoring student responses to picture-cued writing tasks. As a popular paradigm for…
Descriptors: Artificial Intelligence, Automation, Scoring, Visual Aids
Jonathan K. Foster; Peter Youngs; Rachel van Aswegen; Samarth Singh; Ginger S. Watson; Scott T. Acton – Journal of Learning Analytics, 2024
Despite a tremendous increase in the use of video for conducting research in classrooms as well as preparing and evaluating teachers, there remain notable challenges to using classroom videos at scale, including time and financial costs. Recent advances in artificial intelligence could make the process of analyzing, scoring, and cataloguing videos…
Descriptors: Learning Analytics, Automation, Classification, Artificial Intelligence
Cathy Cavanaugh; Bryn Humphrey; Paige Pullen – International Journal on E-Learning, 2024
To address needs in one US state to provide a professional development micro-credential for tens of thousands of educators, we automated an assignment scoring workflow in an online course by developing and refining an AI model to scan submitted assignments and score them against a rubric. This article outlines the AI model development process and…
Descriptors: Artificial Intelligence, Automation, Scoring, Microcredentials
Mustafa Yildiz; Hasan Kagan Keskin; Saadin Oyucu; Douglas K. Hartman; Murat Temur; Mücahit Aydogmus – Reading & Writing Quarterly, 2025
This study examined whether an artificial intelligence-based automatic speech recognition system can accurately assess students' reading fluency and reading level. Participants were 120 fourth-grade students attending public schools in Türkiye. Students read a grade-level text out loud while their voice was recorded. Two experts and the artificial…
Descriptors: Artificial Intelligence, Reading Fluency, Human Factors Engineering, Grade 4
Paul Deane; Duanli Yan; Katherine Castellano; Yigal Attali; Michelle Lamar; Mo Zhang; Ian Blood; James V. Bruno; Chen Li; Wenju Cui; Chunyi Ruan; Colleen Appel; Kofi James; Rodolfo Long; Farah Qureshi – ETS Research Report Series, 2024
This paper presents a multidimensional model of variation in writing quality, register, and genre in student essays, trained and tested via confirmatory factor analysis of 1.37 million essay submissions to ETS' digital writing service, Criterion®. The model was also validated with several other corpora, which indicated that it provides a…
Descriptors: Writing (Composition), Essays, Models, Elementary School Students
Urrutia, Felipe; Araya, Roberto – Journal of Educational Computing Research, 2024
Written answers to open-ended questions can have a higher long-term effect on learning than multiple-choice questions. However, it is critical that teachers immediately review the answers, and ask to redo those that are incoherent. This can be a difficult task and can be time-consuming for teachers. A possible solution is to automate the detection…
Descriptors: Elementary School Students, Grade 4, Elementary School Mathematics, Mathematics Tests
Sperling, Katarina; Stenliden, Linnéa; Nissen, Jörgen; Heintz, Fredrik – European Journal of Education, 2022
Machine learning and other artificial intelligence (AI) technologies are predicted to play a transformative role in primary education, where these technologies for automation and personalization are now being introduced to classroom instruction. This article explores the rationales and practices by which machine learning and AI are emerging in…
Descriptors: Artificial Intelligence, Educational Technology, Technology Uses in Education, Mathematics Instruction
Mun, Jiyeong; Kim, Mijung; Kim, Sung-Won – Asia-Pacific Science Education, 2022
This study investigates what perspectives younger students considered and how they experienced the complexity of multiple perspectives about autonomous vehicle issues. Over the course of 6 weeks, 28 seventh-grade Korean students participated in role-play and group discussion to understand different perspectives on the issue. We qualitatively…
Descriptors: Foreign Countries, Grade 7, Automation, Motor Vehicles
K. Kavitha; V. P. Joshith – Journal of Pedagogical Research, 2024
Artificial intelligence (AI) technologies continue to revolutionize various sectors, including their incorporation into education, particularly in K-12 science education, which has become evidently significant. This paper presents a bibliometric analysis and systematic review that examines the incorporation of AI technologies in K-12 science…
Descriptors: Artificial Intelligence, Science Education, Elementary School Science, Secondary School Science
Abhijit Suresh – ProQuest LLC, 2022
Over the past decade, robust literature focused on teacher "talk moves" that promote student argumentation has emerged, especially in mathematics education. Teachers and students can use talk moves to construct conversations in which students share their thinking, actively consider the ideas of others, and engage in sustained reasoning.…
Descriptors: Automation, Feedback (Response), Teacher Effectiveness, Discourse Modes
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
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
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
Sao Pedro, Michael A.; Baker, Ryan S. J. d.; Gobert, Janice D.; Montalvo, Orlando; Nakama, Adam – Grantee Submission, 2013
We present work toward automatically assessing and estimating science inquiry skills as middle school students engage in inquiry within a physical science microworld. Towards accomplishing this goal, we generated machine-learned models that can detect when students test their articulated hypotheses, design controlled experiments, and engage in…
Descriptors: Artificial Intelligence, Inquiry, Middle School Students, Physical Sciences
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