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Zirou Lin; Hanbing Yan; Li Zhao – Journal of Computer Assisted Learning, 2024
Background: Peer assessment has played an important role in large-scale online learning, as it helps promote the effectiveness of learners' online learning. However, with the emergence of numerical grades and textual feedback generated by peers, it is necessary to detect the reliability of the large amount of peer assessment data, and then develop…
Descriptors: Peer Evaluation, Automation, Grading, Models
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Ngoc My Bui; Jessie S. Barrot – Education and Information Technologies, 2025
With the generative artificial intelligence (AI) tool's remarkable capabilities in understanding and generating meaningful content, intriguing questions have been raised about its potential as an automated essay scoring (AES) system. One such tool is ChatGPT, which is capable of scoring any written work based on predefined criteria. However,…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Automation
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Luke Strickland; Simon Farrell; Micah K. Wilson; Jack Hutchinson; Shayne Loft – Cognitive Research: Principles and Implications, 2024
In a range of settings, human operators make decisions with the assistance of automation, the reliability of which can vary depending upon context. Currently, the processes by which humans track the level of reliability of automation are unclear. In the current study, we test cognitive models of learning that could potentially explain how humans…
Descriptors: Automation, Reliability, Man Machine Systems, Learning Processes
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Monika Lohani; Joel M. Cooper; Amy S. McDonnell; Gus G. Erickson; Trent G. Simmons; Amanda E. Carriero; Kaedyn W. Crabtree; David L. Strayer – Cognitive Research: Principles and Implications, 2024
The reliability of cognitive demand measures in controlled laboratory settings is well-documented; however, limited research has directly established their stability under real-life and high-stakes conditions, such as operating automated technology on actual highways. Partially automated vehicles have advanced to become an everyday mode of…
Descriptors: Cognitive Processes, Difficulty Level, Automation, Psychophysiology
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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
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Héctor J. Pijeira-Díaz; Shashank Subramanya; Janneke van de Pol; Anique de Bruin – Journal of Computer Assisted Learning, 2024
Background: When learning causal relations, completing causal diagrams enhances students' comprehension judgements to some extent. To potentially boost this effect, advances in natural language processing (NLP) enable real-time formative feedback based on the automated assessment of students' diagrams, which can involve the correctness of both the…
Descriptors: Learning Analytics, Automation, Student Evaluation, Causal Models