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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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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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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
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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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Beaty, Roger E.; Johnson, Dan R.; Zeitlen, Daniel C.; Forthmann, Boris – Creativity Research Journal, 2022
Semantic distance is increasingly used for automated scoring of originality on divergent thinking tasks, such as the Alternate Uses Task (AUT). Despite some psychometric support for semantic distance -- including positive correlations with human creativity ratings -- additional work is needed to optimize its reliability and validity, including…
Descriptors: Semantics, Scoring, Creative Thinking, Creativity
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Dalton, Sarah Grace; Stark, Brielle C.; Fromm, Davida; Apple, Kristen; MacWhinney, Brian; Rensch, Amanda; Rowedder, Madyson – Journal of Speech, Language, and Hearing Research, 2022
Purpose: The aim of this study was to advance the use of structured, monologic discourse analysis by validating an automated scoring procedure for core lexicon (CoreLex) using transcripts. Method: Forty-nine transcripts from persons with aphasia and 48 transcripts from persons with no brain injury were retrieved from the AphasiaBank database. Five…
Descriptors: Validity, Discourse Analysis, Databases, Scoring
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Wind, Stefanie A.; Wolfe, Edward W.; Engelhard, George, Jr.; Foltz, Peter; Rosenstein, Mark – International Journal of Testing, 2018
Automated essay scoring engines (AESEs) are becoming increasingly popular as an efficient method for performance assessments in writing, including many language assessments that are used worldwide. Before they can be used operationally, AESEs must be "trained" using machine-learning techniques that incorporate human ratings. However, the…
Descriptors: Computer Assisted Testing, Essay Tests, Writing Evaluation, Scoring
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Sari, Elif; Han, Turgay – Reading Matrix: An International Online Journal, 2021
Providing both effective feedback applications and reliable assessment practices are two central issues in ESL/EFL writing instruction contexts. Giving individual feedback is very difficult in crowded classes as it requires a great amount of time and effort for instructors. Moreover, instructors likely employ inconsistent assessment procedures,…
Descriptors: Automation, Writing Evaluation, Artificial Intelligence, Natural Language Processing
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Sieke, Scott A.; McIntosh, Betsy B.; Steele, Matthew M.; Knight, Jennifer K. – CBE - Life Sciences Education, 2019
Understanding student ideas in large-enrollment biology courses can be challenging, because easy-to-administer multiple-choice questions frequently do not fully capture the diversity of student ideas. As part of the Automated Analysis of Constructed Responses (AACR) project, we designed a question prompting students to describe the possible…
Descriptors: Genetics, Scientific Concepts, Biology, Science Instruction
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Yarnell, Jordy B.; Pfeiffer, Steven I. – Journal of Psychoeducational Assessment, 2015
The present study examined the psychometric equivalence of administering a computer-based version of the Gifted Rating Scale (GRS) compared with the traditional paper-and-pencil GRS-School Form (GRS-S). The GRS-S is a teacher-completed rating scale used in gifted assessment. The GRS-Electronic Form provides an alternative method of administering…
Descriptors: Gifted, Psychometrics, Rating Scales, Computer Assisted Testing
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Liu, Sha; Kunnan, Antony John – CALICO Journal, 2016
This study investigated the application of "WriteToLearn" on Chinese undergraduate English majors' essays in terms of its scoring ability and the accuracy of its error feedback. Participants were 163 second-year English majors from a university located in Sichuan province who wrote 326 essays from two writing prompts. Each paper was…
Descriptors: Foreign Countries, Undergraduate Students, English (Second Language), Second Language Learning
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Irwin, Brian; Hepplestone, Stuart – Assessment & Evaluation in Higher Education, 2012
There have been calls in the literature for changes to assessment practices in higher education, to increase flexibility and give learners more control over the assessment process. This article explores the possibilities of allowing student choice in the format used to present their work, as a starting point for changing assessment, based on…
Descriptors: Student Evaluation, College Students, Selection, Computer Assisted Testing
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Harik, Polina; Baldwin, Peter; Clauser, Brian – Applied Psychological Measurement, 2013
Growing reliance on complex constructed response items has generated considerable interest in automated scoring solutions. Many of these solutions are described in the literature; however, relatively few studies have been published that "compare" automated scoring strategies. Here, comparisons are made among five strategies for…
Descriptors: Computer Assisted Testing, Automation, Scoring, Comparative Analysis
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Darling-Hammond, Linda – Learning Policy Institute, 2017
After passage of the Every Student Succeeds Act (ESSA) in 2015, states assumed greater responsibility for designing their own accountability and assessment systems. ESSA requires states to measure "higher order thinking skills and understanding" and encourages the use of open-ended performance assessments, which are essential for…
Descriptors: Performance Based Assessment, Accountability, Portfolios (Background Materials), Task Analysis
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Attali, Yigal; Sinharay, Sandip – ETS Research Report Series, 2015
The "e-rater"® automated essay scoring system is used operationally in the scoring of the argument and issue tasks that form the Analytical Writing measure of the "GRE"® General Test. For each of these tasks, this study explored the value added of reporting 4 trait scores for each of these 2 tasks over the total e-rater score.…
Descriptors: Scores, Computer Assisted Testing, Computer Software, Grammar
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