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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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Paula Cristina R. Azevedo; Christine B. Valadez – Impacting Education: Journal on Transforming Professional Practice, 2025
Artificial Intelligence (AI) has seen a significant rise in public use since the release of ChatGPT in November of 2022. Higher education institutions (HEI) have struggled to negotiate how best to manage AI technologies within their academic communities, acknowledging both positive and negative impacts of AI on education. Focused primarily on…
Descriptors: Higher Education, Artificial Intelligence, Technology Uses in Education, Educational Policy
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David Eubanks; Scott A. Moore – Assessment Update, 2025
Assessment and institutional research offices have too much data and too little time. Standard reporting often crowds out opportunities for innovative research. Fortunately, advancements in data science now offer a clear solution. It is equal parts technique and philosophy. The first and easiest step is to modernize data work. This column…
Descriptors: Higher Education, Educational Assessment, Data Science, Research Methodology
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Élisabeth Bélanger; Lorie-Marlène Brault Foisy; Steve Masson – International Journal of Research & Method in Education, 2025
The main objective of this methodological article is to discuss the contribution of response times as a tool in education research. The use of response times in research is largely a legacy of the work carried out in cognitive psychology, which has made it possible to describe the cognitive processes involved in information processing. In…
Descriptors: Educational Research, Reaction Time, Cognitive Processes, Research Methodology
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Umar Alkafaween; Ibrahim Albluwi; Paul Denny – Journal of Computer Assisted Learning, 2025
Background: Automatically graded programming assignments provide instant feedback to students and significantly reduce manual grading time for instructors. However, creating comprehensive suites of test cases for programming problems within automatic graders can be time-consuming and complex. The effort needed to define test suites may deter some…
Descriptors: Automation, Grading, Introductory Courses, Programming
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Marlene Steinbach; Johanna Fleckenstein; Livia Kuklick; Jennifer Meyer – Journal of Computer Assisted Learning, 2025
Background: Providing students with information on their current performance could help them improve by stimulating their reflection, but negative feedback that saliently mirrors task-related failure can harm motivation. In the context of automated scoring based on artificial intelligence, we explored how feedback on written texts might be…
Descriptors: Student Motivation, Academic Achievement, Low Achievement, Feedback (Response)
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Yucheng Chu; Peng He; Hang Li; Haoyu Han; Kaiqi Yang; Yu Xue; Tingting Li; Yasemin Copur-Gencturk; Joseph Krajcik; Jiliang Tang – International Educational Data Mining Society, 2025
Short answer assessment is a vital component of science education, allowing evaluation of students' complex three-dimensional understanding. Large language models (LLMs) that possess human-like ability in linguistic tasks are increasingly popular in assisting human graders to reduce their workload. However, LLMs' limitations in domain knowledge…
Descriptors: Artificial Intelligence, Science Education, Technology Uses in Education, Natural Language Processing
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Tatiana M. Lebedintseva; Andrey V. Nikitin; Anna M. Vasilieva; Olga Yu Dmitrieva; Valery A. Filippov – Education in the Asia-Pacific Region: Issues, Concerns and Prospects, 2025
The emergence of artificial intelligence and neural networks creates a significant potential for automating an increasing number of business processes of large, small, and medium-sized businesses in various sectors of the economy. The financial sector, education, medicine, retail trade, and transport are the most promising from the point of view…
Descriptors: Artificial Intelligence, Technology Uses in Education, Labor Market, Automation
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Somayeh Fathali; Fatemeh Mohajeri – Technology in Language Teaching & Learning, 2025
The International English Language Testing System (IELTS) is a high-stakes exam where Writing Task 2 significantly influences the overall scores, requiring reliable evaluation. While trained human raters perform this task, concerns about subjectivity and inconsistency have led to growing interest in artificial intelligence (AI)-based assessment…
Descriptors: English (Second Language), Language Tests, Second Language Learning, Artificial Intelligence
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