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Evan E. Maicus – ProQuest LLC, 2021
As Computer Science course enrollments have increased over recent years, instructors have turned to automated grading systems to help relieve the burden of processing student assignments. However, the available autograding solutions have generally lacked support for traditionally difficult-to-grade advanced topics courses. In this thesis, I…
Descriptors: Computer Assisted Testing, Automation, Grading, Advanced Courses
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Mike Richards; Kevin Waugh; Mark A Slaymaker; Marian Petre; John Woodthorpe; Daniel Gooch – ACM Transactions on Computing Education, 2024
Cheating has been a long-standing issue in university assessments. However, the release of ChatGPT and other free-to-use generative AI tools has provided a new and distinct method for cheating. Students can run many assessment questions through the tool and generate a superficially compelling answer, which may or may not be accurate. We ran a…
Descriptors: Computer Science Education, Artificial Intelligence, Cheating, Student Evaluation
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Hsiao-Wen Hsu – International Journal of Technology in Education, 2024
The implementation of computer-assisted pronunciation training (CAPT) has been proven to be successful in improving learners' pronunciation abilities. Automatic speech recognition (ASR) software was used to provide mediated support to 103 pre-intermediate level students (62 males and 41 females). After experiencing a two-semester of CAPT…
Descriptors: Automation, Assistive Technology, Pronunciation, English Language Learners
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Charles Hulme; Joshua McGrane; Mihaela Duta; Gillian West; Denise Cripps; Abhishek Dasgupta; Sarah Hearne; Rachel Gardner; Margaret Snowling – Language, Speech, and Hearing Services in Schools, 2024
Purpose: Oral language skills provide a critical foundation for formal education and especially for the development of children's literacy (reading and spelling) skills. It is therefore important for teachers to be able to assess children's language skills, especially if they are concerned about their learning. We report the development and…
Descriptors: Automation, Language Tests, Standardized Tests, Test Construction
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K. Kavitha; V. P. Joshith – Journal of Pedagogical Research, 2024
Artificial intelligence (AI) technologies continue to revolutionize various sectors, including their incorporation into education, particularly in K-12 science education, which has become evidently significant. This paper presents a bibliometric analysis and systematic review that examines the incorporation of AI technologies in K-12 science…
Descriptors: Artificial Intelligence, Science Education, Elementary School Science, Secondary School Science
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Xizhe Wang; Yihua Zhong; Changqin Huang; Xiaodi Huang – IEEE Transactions on Learning Technologies, 2024
Reading comprehension is a widely adopted method for learning English, involving reading articles and answering related questions. However, the reading comprehension training typically focuses on the skill level required for a standardized learning stage, without considering the impact of individual differences in linguistic competence. This…
Descriptors: Reading Comprehension, Artificial Intelligence, Computer Software, Synchronous Communication
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Cunningham, Samuel; Laundon, Melinda; Cathcart, Abby; Bashar, Md Abul; Nayak, Richi – Assessment & Evaluation in Higher Education, 2023
Student evaluation of teaching (SET) surveys are the most widely used tool for collecting higher education student feedback to inform academic quality improvement, promotion and recruitment processes. Malicious and abusive student comments in SET surveys have the potential to harm the wellbeing and career prospects of academics. Despite much…
Descriptors: Student Evaluation of Teacher Performance, Written Language, Antisocial Behavior, Language Usage
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Ayfer Sayin; Sabiha Bozdag; Mark J. Gierl – International Journal of Assessment Tools in Education, 2023
The purpose of this study is to generate non-verbal items for a visual reasoning test using templated-based automatic item generation (AIG). The fundamental research method involved following the three stages of template-based AIG. An item from the 2016 4th-grade entrance exam of the Science and Art Center (known as BILSEM) was chosen as the…
Descriptors: Test Items, Test Format, Nonverbal Tests, Visual Measures
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Hooman Saeli; Payam Rahmati; Svetlana Koltovskaia – Journal of Response to Writing, 2023
The study explored six ESL university students' behavioral, cognitive, and affective engagement with e-rater feedback on local issues and examined any changes in students' engagement over two weeks. We explored behavioral engagement through the analysis of screencasts of students' e-rater usage and writing assignments. We measured cognitive and…
Descriptors: Learner Engagement, Error Correction, Feedback (Response), Writing Evaluation
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Ullmann, Thomas Daniel – International Journal of Artificial Intelligence in Education, 2019
Reflective writing is an important educational practice to train reflective thinking. Currently, researchers must manually analyze these writings, limiting practice and research because the analysis is time and resource consuming. This study evaluates whether machine learning can be used to automate this manual analysis. The study investigates…
Descriptors: Reflection, Writing (Composition), Writing Evaluation, Automation
Canzonetta, Jordan Nicole – ProQuest LLC, 2019
This dissertation focuses on the dynamics between teachers and machines at the intersections of design, teaching labor, and pedagogy when automation is deployed in writing classrooms. The sites of analysis are Eli Review and Turnitin, two technologies that represent different design approaches that center around "informating" or…
Descriptors: Writing Instruction, Computer Uses in Education, Automation, Writing Teachers
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Shin, Jinnie; Gierl, Mark J. – International Journal of Testing, 2022
Over the last five years, tremendous strides have been made in advancing the AIG methodology required to produce items in diverse content areas. However, the one content area where enormous problems remain unsolved is language arts, generally, and reading comprehension, more specifically. While reading comprehension test items can be created using…
Descriptors: Reading Comprehension, Test Construction, Test Items, Natural Language Processing
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Jiang, Lianjiang; Yu, Shulin – Computer Assisted Language Learning, 2022
While automated feedback is becoming readily accessible to student writers, how students employ resources and strategies to use such feedback remains largely unexplored. Informed by activity theory and the construct of appropriation, this study conceptualizes students' use of automated feedback as social appropriation mediated by resources and…
Descriptors: Automation, Feedback (Response), Second Language Learning, Writing Instruction
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Link, Stephanie; Mehrzad, Mohaddeseh; Rahimi, Mohammad – Computer Assisted Language Learning, 2022
Recent years have witnessed an increasing interest in the use of automated writing evaluation (AWE) in second language writing classrooms. This increase is partially due to the belief that AWE can assist teachers by allowing them to devote more feedback to higher-level (HL) writing skills, such as content and organization, while the technology…
Descriptors: Automation, Writing Evaluation, Feedback (Response), Revision (Written Composition)
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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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