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Peter Baldwin; Victoria Yaneva; Kai North; Le An Ha; Yiyun Zhou; Alex J. Mechaber; Brian E. Clauser – Journal of Educational Measurement, 2025
Recent developments in the use of large-language models have led to substantial improvements in the accuracy of content-based automated scoring of free-text responses. The reported accuracy levels suggest that automated systems could have widespread applicability in assessment. However, before they are used in operational testing, other aspects of…
Descriptors: Artificial Intelligence, Scoring, Computational Linguistics, Accuracy
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Elif Tuna Pusa; Serkan Dinçer – SAGE Open, 2025
This meta-synthesis study examines the use of digital assessment tools in education, focusing on their prevalence, benefits, limitations, and recommendations for effective integration into teaching processes. Based on 41 empirical studies published between December 2012 and January 2023, this study follows the thematic synthesis approach proposed.…
Descriptors: Student Evaluation, Portfolio Assessment, Electronic Publishing, Computer Assisted Testing
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Jinshui Wang; Shuguang Chen; Zhengyi Tang; Pengchen Lin; Yupeng Wang – Education and Information Technologies, 2025
Mastering SQL programming skills is fundamental in computer science education, and Online Judging Systems (OJS) play a critical role in automatically assessing SQL codes, improving the accuracy and efficiency of evaluations. However, these systems are vulnerable to manipulation by students who can submit "cheating codes" that pass the…
Descriptors: Programming, Computer Science Education, Cheating, Computer Assisted Testing
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Andy Nguyen; Anh Thi Duong; Diep Thi Bich Nguyen; Van Thi Thanh Lai; Belle Dang – Information and Learning Sciences, 2025
Purpose: The rapid advancement and widespread adoption of generative artificial intelligence (GenAI) in education have significantly impacted learning, teaching and assessment practices. This development has raised critical questions about necessary changes to learning design and traditional assessment methods for a society where GenAI becomes…
Descriptors: Artificial Intelligence, Instructional Design, Public Policy, Educational Policy
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Ishaya Gambo; Faith-Jane Abegunde; Omobola Gambo; Roseline Oluwaseun Ogundokun; Akinbowale Natheniel Babatunde; Cheng-Chi Lee – Education and Information Technologies, 2025
The current educational system relies heavily on manual grading, posing challenges such as delayed feedback and grading inaccuracies. Automated grading tools (AGTs) offer solutions but come with limitations. To address this, "GRAD-AI" is introduced, an advanced AGT that combines automation with teacher involvement for precise grading,…
Descriptors: Automation, Grading, Artificial Intelligence, Computer Assisted Testing
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Rajagopal Sankaranarayanan; Mohan Yang; Kyungbin Kwon – Journal of Computing in Higher Education, 2025
The purpose of this study is to explore the influence of the microlearning instructional approach in an online introductory database programming classroom. The ultimate goal of this study is to inform educators and instructional designers on the design and development of microlearning content that maximizes student learning. Grounded within the…
Descriptors: Teaching Methods, Introductory Courses, Databases, Programming
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Danielle Lottridge; Davis Dimalen; Gerald Weber – ACM Transactions on Computing Education, 2025
Automated assessment is well-established within computer science courses but largely absent from human--computer interaction courses. Automating the assessment of human--computer interaction (HCI) is challenging because the coursework tends not to be computational but rather highly creative, such as designing and implementing interactive…
Descriptors: Computer Science Education, Computer Assisted Testing, Automation, Man Machine Systems
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Selcuk Acar; Peter Organisciak; Denis Dumas – Journal of Creative Behavior, 2025
In this three-study investigation, we applied various approaches to score drawings created in response to both Form A and Form B of the Torrance Tests of Creative Thinking-Figural (broadly TTCT-F) as well as the Multi-Trial Creative Ideation task (MTCI). We focused on TTCT-F in Study 1, and utilizing a random forest classifier, we achieved 79% and…
Descriptors: Scoring, Computer Assisted Testing, Models, Correlation
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Harold Doran; Testsuhiro Yamada; Ted Diaz; Emre Gonulates; Vanessa Culver – Journal of Educational Measurement, 2025
Computer adaptive testing (CAT) is an increasingly common mode of test administration offering improved test security, better measurement precision, and the potential for shorter testing experiences. This article presents a new item selection algorithm based on a generalized objective function to support multiple types of testing conditions and…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Algorithms
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Amy Pallant; Christopher Lore; Hee-Sun Lee; Stephanie Seevers; Trudi Lord – Journal of Geoscience Education, 2025
This paper describes how plate tectonics and rock genesis, two topics that are typically addressed separately in secondary Earth science classes, can be taught together as an integrated system. We define the TecRocks Reasoning Framework, developed to support student reasoning about rock formation situated in the context of plate tectonics. We also…
Descriptors: Secondary School Science, Secondary School Students, Geology, Plate Tectonics
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Salvatore G. Garofalo; Stephen J. Farenga – Science & Education, 2025
The purpose of this study was to gauge the attitudes towards artificial intelligence (AI) use in the science classroom by science teachers at the start of generative AI chatbot popularity (March 2023). The lens of distributed cognition afforded an opportunity to gather thoughts, opinions, and perceptions from 24 secondary science educators as well…
Descriptors: Secondary School Teachers, Science Teachers, Teacher Attitudes, Artificial Intelligence
Project Tomorrow, 2025
In support of new local and state discussions about how to most effectively utilize technology in the classroom, Project Tomorrow, in collaboration with Spectrum Business®, is publishing a new series of reports that examine each of the three digital divides (the access, design and use divides) through the lens of the Speak Up Research findings.…
Descriptors: Technology Uses in Education, Access to Computers, Learning Processes, Educational Technology
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Alireza Maleki; Sedigheh Karimpour – Journal of Academic Ethics, 2026
The shift to online platforms has heightened concerns about academic misconduct, particularly contract cheating, where students outsource work to third parties. While research has examined perceptions of this issue, less attention has been given to concrete teacher-led strategies, especially within English as a Foreign Language (EFL) contexts.…
Descriptors: Language Teachers, Cheating, Computer Assisted Testing, English (Second Language)
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Suchart Homjan; Wanida Homjan – International Journal of Education and Literacy Studies, 2025
This research aimed to investigate and develop an online system for educational measurement and evaluation with a focus on authentic assessment. The research process consisted of four main stages: (1) analyzing the current state and carrying out qualitative interviews on authentic assessment, (2) developing an online measurement and evaluation…
Descriptors: Foreign Countries, Student Evaluation, Computer Uses in Education, Computer Assisted Testing
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Abdou L. J. Jammeh; Claude Karegeya; Savita Ladage – Education and Information Technologies, 2025
Clicker-integrated instruction is the current innovation in teaching and learning. Several studies used this technology to investigate learning processes, while others mainly used it to asses for learning, facilitation of group discussion and students' participation. All applications require creativity and analytical thinking and very much…
Descriptors: Chemistry, Science Instruction, Audience Response Systems, Computer Assisted Instruction
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