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Showing 1 to 15 of 16 results Save | Export
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Guher Gorgun; Okan Bulut – Education and Information Technologies, 2024
In light of the widespread adoption of technology-enhanced learning and assessment platforms, there is a growing demand for innovative, high-quality, and diverse assessment questions. Automatic Question Generation (AQG) has emerged as a valuable solution, enabling educators and assessment developers to efficiently produce a large volume of test…
Descriptors: Computer Assisted Testing, Test Construction, Test Items, Automation
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Bin Tan; Hao-Yue Jin; Maria Cutumisu – Computer Science Education, 2024
Background and Context: Computational thinking (CT) has been increasingly added to K-12 curricula, prompting teachers to grade more and more CT artifacts. This has led to a rise in automated CT assessment tools. Objective: This study examines the scope and characteristics of publications that use machine learning (ML) approaches to assess…
Descriptors: Computation, Thinking Skills, Artificial Intelligence, Student Evaluation
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Hossein Kermani; Alireza Bayat Makou; Amirali Tafreshi; Amir Mohamad Ghodsi; Ali Atashzar; Ali Nojoumi – International Journal of Social Research Methodology, 2024
Despite the increasing adaption of automated text analysis in communication studies, its strengths and weaknesses in framing analysis are so far unknown. Fewer efforts have been made to automatic detection of networked frames. Drawing on the recent developments in this field, we harness a comparative exploration, using Latent Dirichlet Allocation…
Descriptors: COVID-19, Pandemics, Automation, Foreign Countries
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Lishan Zhang; Linyu Deng; Sixv Zhang; Ling Chen – IEEE Transactions on Learning Technologies, 2024
With the popularity of online one-to-one tutoring, there are emerging concerns about the quality and effectiveness of this kind of tutoring. Although there are some evaluation methods available, they are heavily relied on manual coding by experts, which is too costly. Therefore, using machine learning to predict instruction quality automatically…
Descriptors: Automation, Classification, Artificial Intelligence, Tutoring
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Soomaiya Hamid; Narmeen Zakaria Bawany – Interactive Learning Environments, 2024
E-learning is the process of sharing knowledge out of the traditional classrooms through different online tools using internet. The availability and use of these tools are not easy for every student. Many institutions gather e-learning feedback to know the problems of students to improve their systems. In e-learning systems, typically a high…
Descriptors: Feedback (Response), Electronic Learning, Automation, Classification
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Ricardo Conejo Muñoz; Beatriz Barros Blanco; José del Campo-Ávila; José L. Triviño Rodriguez – IEEE Transactions on Learning Technologies, 2024
Automatic question generation and the assessment of procedural knowledge is still a challenging research topic. This article focuses on the case of it, the techniques of parsing grammars for compiler construction. There are two well-known techniques for parsing: top-down parsing with LL(1) and bottom-up with LR(1). Learning these techniques and…
Descriptors: Automation, Questioning Techniques, Knowledge Level, Language
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Hunkoog Jho; Minsu Ha – Journal of Baltic Science Education, 2024
This study aimed at examining the performance of generative artificial intelligence to extract argumentation elements from text. Thus, the researchers developed a web-based framework to provide automated assessment and feedback relying on a large language model, ChatGPT. The results produced by ChatGPT were compared to human experts across…
Descriptors: Feedback (Response), Artificial Intelligence, Persuasive Discourse, Models
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Cathy Cavanaugh; Bryn Humphrey; Paige Pullen – International Journal on E-Learning, 2024
To address needs in one US state to provide a professional development micro-credential for tens of thousands of educators, we automated an assignment scoring workflow in an online course by developing and refining an AI model to scan submitted assignments and score them against a rubric. This article outlines the AI model development process and…
Descriptors: Artificial Intelligence, Automation, Scoring, Microcredentials
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Jiseung Yoo; Jisun Park; Minsu Ha; Chelcea Mae Lagmay Darang – SAGE Open, 2024
In the context of formative assessment in classrooms, the incorporation of automated evaluation (AE) systems and teachers' interactions with them hold significant importance. This study aimed to investigate the cognitive processes of pre-service teachers as they engaged with an AE system. We developed an unsupervised learning-based AE system, the…
Descriptors: Preservice Teachers, Cognitive Processes, Automation, Supervision
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Seyedahmad Rahimi; Justice T. Walker; Lin Lin-Lipsmeyer; Jinnie Shin – Creativity Research Journal, 2024
Digital sandbox games such as "Minecraft" can be used to assess and support creativity. Doing so, however, requires an understanding of what is deemed creative in this game context. One approach is to understand how Minecrafters describe creativity in their communities, and how much those descriptions overlap with the established…
Descriptors: Creativity, Video Games, Computer Games, Evaluation Methods
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Shinta Estri Wahyuningrum; Gilles van Luijtelaar; Augustina Sulastri; Marc P. H. Hendriks; Ridwan Sanjaya; Tom Heskes – SAGE Open, 2024
Visual Reproduction is a condition to measure Visual Spatial Memory as one of the cognitive domains commonly used to measure visuo-spatial memory. Geometric figures serve as stimulus material, and probands have to reproduce the figures from memory through a hand drawing. The scoring of the drawing has subjective elements. This study aims to…
Descriptors: Automation, Scores, Geometry, Visual Aids
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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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Alice Barana; Marina Marchisio Conte – Journal on Mathematics Education, 2024
Ensuring equity in education is a goal for sustainable development. Among the factors that hinder equity, socioeconomic status (SES) has the highest impact on learning Mathematics. This paper addresses the issue of equity at the secondary school level by proposing an approach based on adopting automatic formative assessment (AFA). Carefully…
Descriptors: Equal Education, Sustainable Development, Socioeconomic Status, Mathematics Achievement
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Traci C. Eshelman – Turkish Online Journal of Educational Technology - TOJET, 2024
The purpose of this multiple intrinsic case study was to describe how Northeastern United States middle school teachers and students engaged with a new automated writing evaluation tool used to score and provide feedback on extended essay assignments to improve teaching and learning writing. Richard Elmore's (1993) instructional core framework is…
Descriptors: High School Teachers, Learner Engagement, Automation, Writing Evaluation
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Younes-Aziz Bachiri; Hicham Mouncif; Belaid Bouikhalene; Radoine Hamzaoui – Turkish Online Journal of Distance Education, 2024
This study examined the integration of artificial intelligence-powered speech recognition technology within early reading assessments in Morocco's Teaching at the Right Level (TaRL) program. The purpose was to evaluate the effectiveness of an automated speech recognition tool compared to traditional paper-based assessments in improving reading…
Descriptors: Foreign Countries, Artificial Intelligence, Speech Communication, Identification
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