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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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Wallace N. Pinto Jr.; Jinnie Shin – Journal of Educational Measurement, 2025
In recent years, the application of explainability techniques to automated essay scoring and automated short-answer grading (ASAG) models, particularly those based on transformer architectures, has gained significant attention. However, the reliability and consistency of these techniques remain underexplored. This study systematically investigates…
Descriptors: Automation, Grading, Computer Assisted Testing, Scoring
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Rebecka Weegar; Peter Idestam-Almquist – International Journal of Artificial Intelligence in Education, 2024
Machine learning methods can be used to reduce the manual workload in exam grading, making it possible for teachers to spend more time on other tasks. However, when it comes to grading exams, fully eliminating manual work is not yet possible even with very accurate automated grading, as any grading mistakes could have significant consequences for…
Descriptors: Grading, Computer Assisted Testing, Introductory Courses, Computer Science Education
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Tri Sedya Febrianti; Siti Fatimah; Yuni Fitriyah; Hanifah Nurhayati – International Journal of Education in Mathematics, Science and Technology, 2024
Assessing students' understanding of circle-related material through subjective tests is effective, though grading these tests can be challenging and often requires technological support. ChatGPT has shown promise in providing reliable and objective evaluations. Many teachers in Indonesia, however, continue to face difficulties integrating…
Descriptors: Artificial Intelligence, Computer Assisted Testing, Scoring, Tests
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Uto, Masaki; Okano, Masashi – IEEE Transactions on Learning Technologies, 2021
In automated essay scoring (AES), scores are automatically assigned to essays as an alternative to grading by humans. Traditional AES typically relies on handcrafted features, whereas recent studies have proposed AES models based on deep neural networks to obviate the need for feature engineering. Those AES models generally require training on a…
Descriptors: Essays, Scoring, Writing Evaluation, Item Response Theory
Binglin Chen – ProQuest LLC, 2022
Assessment is a key component of education. Routine grading of students' work, however, is time consuming. Automating the grading process allows instructors to spend more of their time helping their students learn and engaging their students with more open-ended, creative activities. One way to automate grading is through computer-based…
Descriptors: College Students, STEM Education, Student Evaluation, Grading
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Zhang, Haoran; Litman, Diane – Grantee Submission, 2020
While automated essay scoring (AES) can reliably grade essays at scale, automated writing evaluation (AWE) additionally provides formative feedback to guide essay revision. However, a neural AES typically does not provide useful feature representations for supporting AWE. This paper presents a method for linking AWE and neural AES, by extracting…
Descriptors: Computer Assisted Testing, Scoring, Essay Tests, Writing Evaluation
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Chan, Kinnie Kin Yee; Bond, Trevor; Yan, Zi – Language Testing, 2023
We investigated the relationship between the scores assigned by an Automated Essay Scoring (AES) system, the Intelligent Essay Assessor (IEA), and grades allocated by trained, professional human raters to English essay writing by instigating two procedures novel to written-language assessment: the logistic transformation of AES raw scores into…
Descriptors: Computer Assisted Testing, Essays, Scoring, Scores
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Çinar, Ayse; Ince, Elif; Gezer, Murat; Yilmaz, Özgür – Education and Information Technologies, 2020
Worldwide, open-ended questions that require short answers have been used in many exams in fields of science, such as the International Student Assessment Program (PISA), the International Science and Maths Trends Research (TIMSS). However, multiple-choice questions are used for many exams at the national level in Turkey, especially high school…
Descriptors: Foreign Countries, Computer Assisted Testing, Artificial Intelligence, Grading
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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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Daniels, Paul – TESL-EJ, 2022
This paper compares the speaking scores generated by two online systems that are designed to automatically grade student speech and provide personalized speaking feedback in an EFL context. The first system, "Speech Assessment for Moodle" ("SAM"), is an open-source solution developed by the author that makes use of Google's…
Descriptors: Speech Communication, Auditory Perception, Computer Uses in Education, Computer Assisted Testing
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Santamaría Lancho, Miguel; Hernández, Mauro; Sánchez-Elvira Paniagua, Ángeles; Luzón Encabo, José María; de Jorge-Botana, Guillermo – Journal of Interactive Media in Education, 2018
Formative assessment and personalised feedback are commonly recognised as key factors both for improving students' performance and increasing their motivation and engagement (Gibbs and Simpson, 2005). Currently, in large and massive open online courses (MOOCs), technological solutions to give feedback are often limited to quizzes of different…
Descriptors: Online Courses, Formative Evaluation, Scoring, Feedback (Response)
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Çekiç, Ahmet; Bakla, Arif – International Online Journal of Education and Teaching, 2021
The Internet and the software stores for mobile devices come with a huge number of digital tools for any task, and those intended for digital formative assessment (DFA) have burgeoned exponentially in the last decade. These tools vary in terms of their functionality, pedagogical quality, cost, operating systems and so forth. Teachers and learners…
Descriptors: Formative Evaluation, Futures (of Society), Computer Assisted Testing, Guidance
Hadi-Tabassum, Samina – Phi Delta Kappan, 2014
Schools are scrambling to prepare students for the writing assessments aligned to the Common Core State Standards. In some states, writing has not been assessed for over a decade. Yet, with the use of computerized grading of the student's writing, many teachers are wondering how to best prepare students for the writing assessments that will…
Descriptors: Computer Assisted Testing, Writing Tests, Standardized Tests, Core Curriculum
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Newhouse, C. Paul – Technology, Pedagogy and Education, 2015
This paper reports on the outcomes of a three-year study investigating the use of digital technologies to increase the authenticity of high-stakes summative assessment in four Western Australian senior secondary courses. The study involved 82 teachers and 1015 students and a range of digital forms of assessment using computer-based exams, digital…
Descriptors: Educational Technology, High Stakes Tests, Summative Evaluation, Secondary School Students
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