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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
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
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
Horbach, Serge P. J. M.; Oude Maatman, Freek J. W.; Halffman, Willem; Hepkema, Wytske M. – Research Evaluation, 2022
Citing practices have long been at the heart of scientific reporting, playing both socially and epistemically important functions in science. While such practices have been relatively stable over time, recent attempts to develop automated citation recommendation tools have the potential to drastically impact citing practices. We claim that, even…
Descriptors: Citations (References), Citation Analysis, Automation, Reliability
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
Nuijten, Michèle B.; Polanin, Joshua R. – Research Synthesis Methods, 2020
We present the R package and web app "statcheck" to automatically detect statistical reporting inconsistencies in primary studies and meta-analyses. Previous research has shown a high prevalence of reported p-values that are inconsistent--meaning a re-calculated p-value, based on the reported test statistic and degrees of freedom, does…
Descriptors: Meta Analysis, Statistical Analysis, Reliability, Replication (Evaluation)
Doewes, Afrizal; Pechenizkiy, Mykola – International Educational Data Mining Society, 2021
Scoring essays is generally an exhausting and time-consuming task for teachers. Automated Essay Scoring (AES) facilitates the scoring process to be faster and more consistent. The most logical way to assess the performance of an automated scorer is by measuring the score agreement with the human raters. However, we provide empirical evidence that…
Descriptors: Man Machine Systems, Automation, Computer Assisted Testing, Scoring
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
Maio, Shannon; Dumas, Denis; Organisciak, Peter; Runco, Mark – Creativity Research Journal, 2020
In recognition of the capability of text-mining models to quantify aspects of language use, some creativity researchers have adopted text-mining models as a mechanism to objectively and efficiently score the Originality of open-ended responses to verbal divergent thinking tasks. With the increasing use of text-mining models in divergent thinking…
Descriptors: Creative Thinking, Scores, Reliability, Data Analysis
Tahani I. Aldosemani; Hussein Assalahi; Areej Lhothali; Maram Albsisi – International Journal of Computer-Assisted Language Learning and Teaching, 2023
This paper explores the literature on AWE feedback, particularly its perceived impact on enhancing EFL student writing proficiency. Prior research highlighted the contribution of AWE in fostering learner autonomy and alleviating teacher workloads, with a substantial focus on student engagement with AWE feedback. This review strives to illuminate…
Descriptors: Automation, Student Evaluation, Writing Evaluation, English (Second Language)
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
Aaron McVay – ProQuest LLC, 2021
As assessments move towards computerized testing and making continuous testing available the need for rapid assembly of forms is increasing. The objective of this study was to investigate variability in assembled forms through the lens of first- and second-order equity properties of equating, by examining three factors and their interactions. Two…
Descriptors: Automation, Computer Assisted Testing, Test Items, Reaction Time
Fox, Carly B.; Israelsen-Augenstein, Megan; Jones, Sharad; Gillam, Sandra Laing – Journal of Speech, Language, and Hearing Research, 2021
Purpose: This study examined the accuracy and potential clinical utility of two expedited transcription methods for narrative language samples elicited from school-age children (7;5-11;10 [years;months]) with developmental language disorder. Transcription methods included real-time transcription produced by speech-language pathologists (SLPs) and…
Descriptors: Transcripts (Written Records), Child Language, Narration, Language Impairments
Ullmann, Thomas Daniel – International Journal of Artificial Intelligence in Education, 2019
Reflective writing is an important educational practice to train reflective thinking. Currently, researchers must manually analyze these writings, limiting practice and research because the analysis is time and resource consuming. This study evaluates whether machine learning can be used to automate this manual analysis. The study investigates…
Descriptors: Reflection, Writing (Composition), Writing Evaluation, Automation
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