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Showing 1 to 15 of 16 results Save | Export
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Jian Zhao; Elaine Chapman; Peyman G. P. Sabet – Education Research and Perspectives, 2024
The launch of ChatGPT and the rapid proliferation of generative AI (GenAI) have brought transformative changes to education, particularly in the field of assessment. This has prompted a fundamental rethinking of traditional assessment practices, presenting both opportunities and challenges in evaluating student learning. While numerous studies…
Descriptors: Literature Reviews, Artificial Intelligence, Evaluation Methods, Student Evaluation
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Putnikovic, Marko; Jovanovic, Jelena – IEEE Transactions on Learning Technologies, 2023
Automatic grading of short answers is an important task in computer-assisted assessment (CAA). Recently, embeddings, as semantic-rich textual representations, have been increasingly used to represent short answers and predict the grade. Despite the recent trend of applying embeddings in automatic short answer grading (ASAG), there are no…
Descriptors: Automation, Computer Assisted Testing, Grading, Natural Language Processing
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Daniel Lupiya Mpolomoka – Pedagogical Research, 2025
Overview: This systematic review explores the utilization of artificial intelligence (AI) for assessment, grading, and feedback in higher education. The review aims to establish how AI technologies enhance efficiency, scalability, and personalized learning experiences in educational settings, while addressing associated challenges that arise due…
Descriptors: Artificial Intelligence, Higher Education, Evaluation Methods, Literature Reviews
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Dongkwang Shin; Jang Ho Lee – ELT Journal, 2024
Although automated item generation has gained a considerable amount of attention in a variety of fields, it is still a relatively new technology in ELT contexts. Therefore, the present article aims to provide an accessible introduction to this powerful resource for language teachers based on a review of the available research. Particularly, it…
Descriptors: Language Tests, Artificial Intelligence, Test Items, Automation
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Nigam, Aditya; Pasricha, Rhitvik; Singh, Tarishi; Churi, Prathamesh – Education and Information Technologies, 2021
There have been giant leaps in the field of education in the past 1-2 years. Schools and colleges are transitioning online to provide more resources to their students. The COVID-19 pandemic has provided students more opportunities to learn and improve themselves at their own pace. Online proctoring services (part of assessment) are also on the…
Descriptors: Supervision, Artificial Intelligence, Computer Assisted Testing, Educational Research
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Zhai, Xiaoming; Shi, Lehong; Nehm, Ross H. – Journal of Science Education and Technology, 2021
Machine learning (ML) has been increasingly employed in science assessment to facilitate automatic scoring efforts, although with varying degrees of success (i.e., magnitudes of machine-human score agreements [MHAs]). Little work has empirically examined the factors that impact MHA disparities in this growing field, thus constraining the…
Descriptors: Meta Analysis, Man Machine Systems, Artificial Intelligence, Computer Assisted Testing
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Surahman, Ence; Wang, Tzu-Hua – Journal of Computer Assisted Learning, 2022
Background: Academic dishonesty (AD) and trustworthy assessment (TA) are fundamental issues in the context of an online assessment. However, little systematic work currently exists on how researchers have explored AD and TA issues in online assessment practice. Objectives: Hence, this research aimed at investigating the latest findings regarding…
Descriptors: Ethics, Trust (Psychology), Computer Assisted Testing, Educational Technology
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Angxuan Chen; Yuyue Zhang; Jiyou Jia; Min Liang; Yingying Cha; Cher Ping Lim – Journal of Computer Assisted Learning, 2025
Background: Language assessment plays a pivotal role in language education, serving as a bridge between students' understanding and educators' instructional approaches. Recently, advancements in Artificial Intelligence (AI) technologies have introduced transformative possibilities for automating and personalising language assessments. Objectives:…
Descriptors: Artificial Intelligence, Technology Uses in Education, Computer Assisted Testing, Language Tests
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Zhai, Xiaoming; Yin, Yue; Pellegrino, James W.; Haudek, Kevin C.; Shi, Lehong – Studies in Science Education, 2020
Machine learning (ML) is an emergent computerised technology that relies on algorithms built by 'learning' from training data rather than 'instruction', which holds great potential to revolutionise science assessment. This study systematically reviewed 49 articles regarding ML-based science assessment through a triangle framework with technical,…
Descriptors: Science Education, Computer Assisted Testing, Science Tests, Scoring
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Nejdet Karadag – Journal of Educational Technology and Online Learning, 2023
The purpose of this study is to examine the impact of artificial intelligence (AI) on online assessment in the context of opportunities and threats based on the literature. To this end, 19 articles related to the AI tool ChatGPT and online assessment were analysed through rapid literature review. In the content analysis, the themes of "AI's…
Descriptors: Artificial Intelligence, Computer Assisted Testing, Natural Language Processing, Grading
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Mazhar Bal; Emre Öztürk – British Educational Research Journal, 2025
The purpose of this study is to examine the relationship between technology-supported writing instruction at the K-12 level and deep learning approaches and to understand the trends in this field. In the study, 12 articles selected from Web of Science, Scopus, ERIC and EBSCO databases were systematically analysed. The findings reveal that the…
Descriptors: Learning Processes, Writing Processes, Writing Skills, Writing Instruction
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Rukthin Laoha; Wichittra Chomthong; Weerapa Pongpanich – Higher Education Studies, 2025
The integration of Artificial Intelligence (AI) into English as a Foreign Language (EFL) education has transformed teaching practices, necessitating a re-evaluation of teacher competencies in the digital age. This systematic review examines the intersection of AI technologies and EFL teachers' competencies, exploring how AI tools influence…
Descriptors: Artificial Intelligence, Technology Uses in Education, Second Language Instruction, English (Second Language)
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Jones, Daniel Marc; Cheng, Liying; Tweedie, M. Gregory – Canadian Journal of Learning and Technology, 2022
This article reviews recent literature (2011-present) on the automated scoring (AS) of writing and speaking. Its purpose is to first survey the current research on automated scoring of language, then highlight how automated scoring impacts the present and future of assessment, teaching, and learning. The article begins by outlining the general…
Descriptors: Automation, Computer Assisted Testing, Scoring, Writing (Composition)
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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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Bejar, Isaac I. – Journal of Educational Measurement, 1984
Approaches proposed for educational diagnostic assessment are reviewed and identified as deficit assessment and error analysis. The development of diagnostic instruments may require a reexamination of existing psychometric models and development of alternative ones. The psychometric and content demands of diagnostic assessment all but require test…
Descriptors: Artificial Intelligence, Computer Assisted Testing, Criterion Referenced Tests, Diagnostic Tests
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