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Showing 1 to 15 of 34 results Save | Export
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Elizabeth L. Wetzler; Kenneth S. Cassidy; Margaret J. Jones; Chelsea R. Frazier; Nickalous A. Korbut; Chelsea M. Sims; Shari S. Bowen; Michael Wood – Teaching of Psychology, 2025
Background: Generative artificial intelligence (AI) represents a potentially powerful, time-saving tool for grading student essays. However, little is known about how AI-generated essay scores compare to human instructor scores. Objective: The purpose of this study was to compare the essay grading scores produced by AI with those of human…
Descriptors: Essays, Writing Evaluation, Scores, Evaluators
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Yubin Xu; Lin Liu; Jianwen Xiong; Guangtian Zhu – Journal of Baltic Science Education, 2025
As the development and application of large language models (LLMs) in physics education progress, the well-known AI-based chatbot ChatGPT4 has presented numerous opportunities for educational assessment. Investigating the potential of AI tools in practical educational assessment carries profound significance. This study explored the comparative…
Descriptors: Physics, Artificial Intelligence, Computer Software, Accuracy
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Fatih Yavuz; Özgür Çelik; Gamze Yavas Çelik – British Journal of Educational Technology, 2025
This study investigates the validity and reliability of generative large language models (LLMs), specifically ChatGPT and Google's Bard, in grading student essays in higher education based on an analytical grading rubric. A total of 15 experienced English as a foreign language (EFL) instructors and two LLMs were asked to evaluate three student…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Computational Linguistics
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Yishen Song; Qianta Zhu; Huaibo Wang; Qinhua Zheng – IEEE Transactions on Learning Technologies, 2024
Manually scoring and revising student essays has long been a time-consuming task for educators. With the rise of natural language processing techniques, automated essay scoring (AES) and automated essay revising (AER) have emerged to alleviate this burden. However, current AES and AER models require large amounts of training data and lack…
Descriptors: Scoring, Essays, Writing Evaluation, Computer Software
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Reagan Mozer; Luke Miratrix; Jackie Eunjung Relyea; James S. Kim – Journal of Educational and Behavioral Statistics, 2024
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, Evaluation Methods, Writing Evaluation, Comparative Analysis
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Shin, Jinnie; Gierl, Mark J. – Language Testing, 2021
Automated essay scoring (AES) has emerged as a secondary or as a sole marker for many high-stakes educational assessments, in native and non-native testing, owing to remarkable advances in feature engineering using natural language processing, machine learning, and deep-neural algorithms. The purpose of this study is to compare the effectiveness…
Descriptors: Scoring, Essays, Writing Evaluation, Computer Software
Walland, Emma – Research Matters, 2022
In this article, I report on examiners' views and experiences of using Pairwise Comparative Judgement (PCJ) and Rank Ordering (RO) as alternatives to traditional analytical marking for GCSE English Language essays. Fifteen GCSE English Language examiners took part in the study. After each had judged 100 pairs of essays using PCJ and eight packs of…
Descriptors: Essays, Grading, Writing Evaluation, Evaluators
Jiyeo Yun – English Teaching, 2023
Studies on automatic scoring systems in writing assessments have also evaluated the relationship between human and machine scores for the reliability of automated essay scoring systems. This study investigated the magnitudes of indices for inter-rater agreement and discrepancy, especially regarding human and machine scoring, in writing assessment.…
Descriptors: Meta Analysis, Interrater Reliability, Essays, Scoring
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Lian Li; Jiehui Hu; Yu Dai; Ping Zhou; Wanhong Zhang – Reading & Writing Quarterly, 2024
This paper proposes to use depth perception to represent raters' decision in holistic evaluation of ESL essays, as an alternative medium to conventional form of numerical scores. The researchers verified the new method's accuracy and inter/intra-rater reliability by inviting 24 ESL teachers to perform different representations when rating 60…
Descriptors: Essays, Holistic Approach, Writing Evaluation, Accuracy
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Ahmet Can Uyar; Dilek Büyükahiska – International Journal of Assessment Tools in Education, 2025
This study explores the effectiveness of using ChatGPT, an Artificial Intelligence (AI) language model, as an Automated Essay Scoring (AES) tool for grading English as a Foreign Language (EFL) learners' essays. The corpus consists of 50 essays representing various types including analysis, compare and contrast, descriptive, narrative, and opinion…
Descriptors: Artificial Intelligence, Computer Software, Technology Uses in Education, Teaching Methods
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Junifer Leal Bucol; Napattanissa Sangkawong – Innovations in Education and Teaching International, 2025
This research paper employs an exploratory framework to evaluate the potential of ChatGPT as an Automated Writing Evaluation (AWE) tool in teaching English as a Foreign Language (EFL) in Thailand. The main objective is to investigate how well ChatGPT can assess students' writing using prompts and pre-defined rubrics compared to human raters.…
Descriptors: Artificial Intelligence, Computer Software, Teaching Methods, English (Second Language)
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Uzun, Kutay – Contemporary Educational Technology, 2018
Managing crowded classes in terms of classroom assessment is a difficult task due to the amount of time which needs to be devoted to providing feedback to student products. In this respect, the present study aimed to develop an automated essay scoring environment as a potential means to overcome this problem. Secondarily, the study aimed to test…
Descriptors: Computer Assisted Testing, Essays, Scoring, English Literature
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Jeong, Heejeong – Language Testing in Asia, 2019
In writing assessment, finding a valid, reliable, and efficient scale is critical. Appropriate scales, increase rater reliability, and can also save time and money. This exploratory study compared the effects of a binary scale and an analytic scale across teacher raters and expert raters. The purpose of the study is to find out how different scale…
Descriptors: Writing Evaluation, English (Second Language), Second Language Learning, Second Language Instruction
Yun, Jiyeo – ProQuest LLC, 2017
Since researchers investigated automatic scoring systems in writing assessments, they have dealt with relationships between human and machine scoring, and then have suggested evaluation criteria for inter-rater agreement. The main purpose of my study is to investigate the magnitudes of and relationships among indices for inter-rater agreement used…
Descriptors: Interrater Reliability, Essays, Scoring, Evaluators
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Nagao, Akiko – English Language Teaching, 2020
This study applied a Systemic Functional Linguistics (SFL) model to explore how 27 first-year university students in two different English proficiency groups improved their lexicogrammatical choices and metafunctions for writing analytical exposition essays during a 15-week course. To explore how "the teaching learning cycle" influences…
Descriptors: Second Language Learning, Second Language Instruction, English (Second Language), Teaching Methods
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