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UK Department for Education, 2024
Over the last year, interest in and use of generative artificial intelligence (GenAI) has rapidly increased. Although GenAI is not new, recent advances in the underlying technology and greater accessibility mean that the public can now use it more easily. This poses opportunities and challenges for the education sector. The Digital Strategy…
Descriptors: Artificial Intelligence, Technology Uses in Education, Automation, Information Technology
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Gilbert Dizon; John M. Gayed – Cogent Education, 2024
The use of automated writing evaluation (AWE) in second language (L2) writing contexts has increased dramatically, as evidenced by the large body of research published on the topic over the past decade. Considering this, several systematic reviews on AWE have been published. Nevertheless, none of these review studies has exclusively focused on the…
Descriptors: Literature Reviews, Meta Analysis, Second Language Learning, Writing Evaluation
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Vanda Santos; Joana Teles; Pedro Quaresma – International Journal for Technology in Mathematics Education, 2024
Using a Dynamic Geometry System (DGS) students can engage in a dynamic learning process that allows them to experiment, create strategies, make conjectures, argue, and deduce mathematical properties. A DGS enables the introduction of proofs, by providing visual aids. The proof of the conjectures made emerges as the next step towards formalising…
Descriptors: Grade 7, Mathematics Education, Geometry, Validity
Davis, Van L. – WICHE Cooperative for Educational Technologies (WCET), 2023
This resource is a quick primer on AI, with examples of what the different programs can generate based on user prompts, challenges and opportunities, discussion of implications and our recommendations for higher education institutions.
Descriptors: Artificial Intelligence, Higher Education, Automation, Writing (Composition)
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Sunilkumar, Dolly; Kelly, Steve W.; Stevenage, Sarah V.; Rankine, Dillon; Robertson, David J. – Applied Cognitive Psychology, 2023
In several applied contexts (e.g., earwitness testimony), the accurate recognition of unfamiliar voices can be a critical part of the person identification process. However, recognising unfamiliar voices is prone to error. While such errors could be reduced by testing the proficiency of listeners, the established tests of unfamiliar voice matching…
Descriptors: Identification, Audio Equipment, Computer Software, Automation
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Thompson, Greg; Gulson, Kalervo N.; Swist, Teresa; Witzenberger, Kevin – Learning, Media and Technology, 2023
The use of automated decision-making systems is increasing in education. While the potential impacts of ADM are becoming widely known amongst experts, the perspectives of those impacted by ADM remain peripheral. To broaden expertise and participation, this paper proposes that ADM needs to be considered as a sociotechnical controversy, as part of a…
Descriptors: Automation, Decision Making, Educational Technology, Democracy
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Okubo, Fumiya; Shiino, Tetsuya; Minematsu, Tsubasa; Taniguchi, Yuta; Shimada, Atsushi – IEEE Transactions on Learning Technologies, 2023
In this study, we propose an integrated system to support learners' reviews. In the proposed system, the review dashboard is used to recommend review contents that are adaptive to the individual learner's level of understanding and to present other information that is useful for review. The pages of the digital learning materials that are…
Descriptors: Learning Management Systems, Student Evaluation, Automation, Artificial Intelligence
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Wang, Hei-Chia; Maslim, Martinus; Kan, Chia-Hao – Education and Information Technologies, 2023
Distance learning frees the learning process from spatial constraints. Each mode of distance learning, including synchronous and asynchronous learning, has disadvantages. In synchronous learning, students have network bandwidth and noise concerns, but in asynchronous learning, they have fewer opportunities for engagement, such as asking questions.…
Descriptors: Automation, Artificial Intelligence, Computer Assisted Testing, Asynchronous Communication
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Singh, Anil; Bhadauria, Vikram S.; Mangalaraj, George – Journal of Information Systems Education, 2023
Large parts of the enterprise resource planning (ERP) processes are automated. One example is the item values in the sales order process. To execute a sales order, the ERP system applies a specific "find" strategy on a wide variety of data sources such as customer master, material master, and customer price-specific data tables, and…
Descriptors: Teaching Methods, Business Administration Education, Entrepreneurship, Planning
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Uto, Masaki; Aomi, Itsuki; Tsutsumi, Emiko; Ueno, Maomi – IEEE Transactions on Learning Technologies, 2023
In automated essay scoring (AES), essays are automatically graded without human raters. Many AES models based on various manually designed features or various architectures of deep neural networks (DNNs) have been proposed over the past few decades. Each AES model has unique advantages and characteristics. Therefore, rather than using a single-AES…
Descriptors: Prediction, Scores, Computer Assisted Testing, Scoring
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Zaki, Nazar; Turaev, Sherzod; Shuaib, Khaled; Krishnan, Anusuya; Mohamed, Elfadil – Education and Information Technologies, 2023
Quality control and assurance plays a fundamental role within higher education contexts. One means by which quality control can be performed is by mapping the course learning outcomes (CLOs) to the program learning outcomes (PLO). This paper describes a system by which this mapping process can be automated and validated. The proposed AI-based…
Descriptors: Program Evaluation, Outcomes of Education, Natural Language Processing, Higher Education
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Wang, Qi; Rose, Carolyn P.; Ma, Ning; Jiang, Shiyan; Bao, Haogang; Li, Yanyan – IEEE Transactions on Learning Technologies, 2022
Forums are essential components facilitating interactions in online courses. However, in large-scale courses, many posts generated, which results in learners' difficulties. First, the posts are poorly organized and some deviate from the topic, making it difficult for learners' knowledge acquisition. Second, learners cannot receive timely feedback…
Descriptors: Design, Automation, Feedback (Response), Scaffolding (Teaching Technique)
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Muller, Ashley Elizabeth; Ames, Heather Melanie R.; Jardim, Patricia Sofia Jacobsen; Rose, Christopher James – Research Synthesis Methods, 2022
Systematic reviews are resource-intensive. The machine learning tools being developed mostly focus on the study identification process, but tools to assist in analysis and categorization are also needed. One possibility is to use unsupervised automatic text clustering, in which each study is automatically assigned to one or more meaningful…
Descriptors: Artificial Intelligence, Man Machine Systems, Automation, Literature Reviews
Frisby, Joshua C. – ProQuest LLC, 2022
Higher education institutions adopt conversational agents, or chatbots, to perform and automate certain business functions. While chatbots exist to support Enrollment Services, Financial Aid, and other departments within an institution, Institutional Research lacks options. Institutional Research supports higher education institutions by providing…
Descriptors: Institutional Research, Artificial Intelligence, Higher Education, State Universities
Deane, Paul – Educational Testing Service, 2022
Writing is a critical 21st century skill. Today's knowledge economy places a premium upon collaboration and written communication, which means that the skilled writer enters the job market at a significant advantage (Aschliman, 2016; Brandt, 2005). And yet students typically enter the job market with weak writing skills. Only 27% of 12th-grade…
Descriptors: Writing Evaluation, Writing Instruction, Instructional Improvement, Automation
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