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Jonas Flodén – British Educational Research Journal, 2025
This study compares how the generative AI (GenAI) large language model (LLM) ChatGPT performs in grading university exams compared to human teachers. Aspects investigated include consistency, large discrepancies and length of answer. Implications for higher education, including the role of teachers and ethics, are also discussed. Three…
Descriptors: College Faculty, Artificial Intelligence, Comparative Testing, Scoring
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John R. Donoghue; Carol Eckerly – Applied Measurement in Education, 2024
Trend scoring constructed response items (i.e. rescoring Time A responses at Time B) gives rise to two-way data that follow a product multinomial distribution rather than the multinomial distribution that is usually assumed. Recent work has shown that the difference in sampling model can have profound negative effects on statistics usually used to…
Descriptors: Scoring, Error of Measurement, Reliability, Scoring Rubrics
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Swapna Haresh Teckwani; Amanda Huee-Ping Wong; Nathasha Vihangi Luke; Ivan Cherh Chiet Low – Advances in Physiology Education, 2024
The advent of artificial intelligence (AI), particularly large language models (LLMs) like ChatGPT and Gemini, has significantly impacted the educational landscape, offering unique opportunities for learning and assessment. In the realm of written assessment grading, traditionally viewed as a laborious and subjective process, this study sought to…
Descriptors: Accuracy, Reliability, Computational Linguistics, Standards
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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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Deborah Oluwadele; Yashik Singh; Timothy Adeliyi – Electronic Journal of e-Learning, 2024
Validation is needed for any newly developed model or framework because it requires several real-life applications. The investment made into e-learning in medical education is daunting, as is the expectation for a positive return on investment. The medical education domain requires data-wise implementation of e-learning as the debate continues…
Descriptors: Electronic Learning, Evaluation Methods, Medical Education, Sustainability
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Dadi Ramesh; Suresh Kumar Sanampudi – European Journal of Education, 2024
Automatic essay scoring (AES) is an essential educational application in natural language processing. This automated process will alleviate the burden by increasing the reliability and consistency of the assessment. With the advances in text embedding libraries and neural network models, AES systems achieved good results in terms of accuracy.…
Descriptors: Scoring, Essays, Writing Evaluation, Memory
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Conti, Gary J. – Journal of Education and Learning, 2023
The use of personality inventories has been limited because of their cost and the length. To overcome these limitations, this study created the Personality Identity Estimator (PIE), an easy-to-use inventory to estimate personality types that can be used at no cost. PIE is a categorical inventory containing 12 items with 3 items for each of the 4…
Descriptors: Personality Measures, Personality Traits, Validity, Reliability
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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
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Alyson Burnett; Katlyn Lee Milless; Michelle Bennett; Whitney Kozakowski; Sonia Alves; Christine Ross – Regional Educational Laboratory Mid-Atlantic, 2024
This study analyzed Pennsylvania School Climate Survey data from students and staff in the 2021/22 school year to assess the validity and reliability of the elementary school student version of the survey; approaches to scoring the survey in individual schools at all grade levels; and perceptions of school climate across student, staff, and school…
Descriptors: Educational Environment, Decision Making, Surveys, Validity
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Jordan M. Wheeler; Allan S. Cohen; Shiyu Wang – Journal of Educational and Behavioral Statistics, 2024
Topic models are mathematical and statistical models used to analyze textual data. The objective of topic models is to gain information about the latent semantic space of a set of related textual data. The semantic space of a set of textual data contains the relationship between documents and words and how they are used. Topic models are becoming…
Descriptors: Semantics, Educational Assessment, Evaluators, Reliability
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Davies, Ben; Alcock, Lara; Jones, Ian – Educational Studies in Mathematics, 2020
Proof is central to mathematics and has drawn substantial attention from the mathematics education community. Yet, valid and reliable measures of proof comprehension remain rare. In this article, we present a study investigating proof comprehension via students' summaries of a given proof. These summaries were evaluated by expert judges making…
Descriptors: Mathematical Logic, Mathematics Skills, Comprehension, Reliability
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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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Curran, Patrick J.; Georgeson, A. R.; Bauer, Daniel J.; Hussong, Andrea M. – International Journal of Behavioral Development, 2021
Conducting valid and reliable empirical research in the prevention sciences is an inherently difficult and challenging task. Chief among these is the need to obtain numerical scores of underlying theoretical constructs for use in subsequent analysis. This challenge is further exacerbated by the increasingly common need to consider multiple…
Descriptors: Psychometrics, Scoring, Prevention, Scores
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Rebecca Sickinger; Tineke Brunfaut; John Pill – Language Testing, 2025
Comparative Judgement (CJ) is an evaluation method, typically conducted online, whereby a rank order is constructed, and scores calculated, from judges' pairwise comparisons of performances. CJ has been researched in various educational contexts, though only rarely in English as a Foreign Language (EFL) writing settings, and is generally agreed to…
Descriptors: Writing Evaluation, English (Second Language), Second Language Learning, Second Language Instruction
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Romig, John Elwood; Olsen, Amanda A. – Reading & Writing Quarterly, 2021
Compared to other content areas, there is a dearth of research examining curriculum-based measurement of writing (CBM-W). This study conducted a conceptual replication examining the reliability, stability, and sensitivity to growth of slopes produced from CBM-W. Eighty-nine (N = 89) eighth-grade students responded to one CBM-W probe weekly for 11…
Descriptors: Curriculum Based Assessment, Writing Evaluation, Middle School Students, Grade 8
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