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Yanyan Fu – Educational Measurement: Issues and Practice, 2024
The template-based automated item-generation (TAIG) approach that involves template creation, item generation, item selection, field-testing, and evaluation has more steps than the traditional item development method. Consequentially, there is more margin for error in this process, and any template errors can be cascaded to the generated items.…
Descriptors: Error Correction, Automation, Test Items, Test Construction
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Sandra McKeown; Zuhaib M. Mir – Research Synthesis Methods, 2024
Searching multiple resources to locate eligible studies for research syntheses can result in hundreds to thousands of duplicate references that should be removed before the screening process for efficiency. Research investigating the performance of automated methods for deduplicating references via reference managers and systematic review software…
Descriptors: Literature Reviews, Evaluation, Followup Studies, Automation
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Chaudhuri, Nandita Bhanja; Dhar, Debayan; Yammiyavar, Pradeep G. – International Journal of Technology and Design Education, 2022
Evaluating novelty in design education is subjective and generally depends on expert's referential metrics. Presently, practitioners in this field perform subjective evaluation of answers of prospective students, but many a time, humans are prone to errors when associated with repetitive tasks on large-scale. Therefore, this paper attempts to…
Descriptors: Novelty (Stimulus Dimension), Automation, Evaluation, Aptitude
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Fu, Yanyan; Choe, Edison M.; Lim, Hwanggyu; Choi, Jaehwa – Educational Measurement: Issues and Practice, 2022
This case study applied the "weak theory" of Automatic Item Generation (AIG) to generate isomorphic item instances (i.e., unique but psychometrically equivalent items) for a large-scale assessment. Three representative instances were selected from each item template (i.e., model) and pilot-tested. In addition, a new analytical framework,…
Descriptors: Test Items, Measurement, Psychometrics, Test Construction
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Fernandez-Gauna, Borja; Rojo, Naiara; Graña, Manuel – International Journal of Educational Technology in Higher Education, 2023
We describe an automated assessment process for team-coding assignments based on DevOps best practices. This system and methodology includes the definition of Team Performance Metrics measuring properties of the software developed by each team, and their correct use of DevOps techniques. It tracks the progress on each of metric by each group. The…
Descriptors: Computer Software, Programming, Coding, Teamwork
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Lemantara, Julianto; Hariadi, Bambang; Sunarto, M. J. Dewiyani; Amelia, Tan; Sagirani, Tri – IEEE Transactions on Learning Technologies, 2023
A quick and effective learning assessment is needed to evaluate the learning process. Many tools currently offer automatic assessment for subjective and objective questions; however, there is no such free tool that provides plagiarism detection among students for subjective questions in a learning management system (LMS). This article aims to…
Descriptors: Students, Cheating, Prediction, Essays
Zaki Zadeh Ghariehali, Mohammad – ProQuest LLC, 2023
Cognition is the mental process of acquiring knowledge and understanding through thought, experience and senses. Based on Embodied Cognition theory, physical activities are an important manifestation of cognitive functions. As a result, they can be employed to both assess and train cognitive skills. In order to assess various cognitive measures,…
Descriptors: Cognitive Processes, Physical Activities, Difficulty Level, Executive Function
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Jiang, Shiyan; Tang, Hengtao; Tatar, Cansu; Rosé, Carolyn P.; Chao, Jie – Learning, Media and Technology, 2023
It's critical to foster artificial intelligence (AI) literacy for high school students, the first generation to grow up surrounded by AI, to understand working mechanism of data-driven AI technologies and critically evaluate automated decisions from predictive models. While efforts have been made to engage youth in understanding AI through…
Descriptors: Artificial Intelligence, High School Students, Models, Classification
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Murat Polat; Ibrahim Hakan Karatas; Nurgün Varol – Leadership and Policy in Schools, 2025
The incorporation of artificial intelligence (AI) into educational management offers personalized learning, adaptive tutoring, and efficient resource management. However, ethical considerations such as fairness, transparency, accountability, and privacy are crucial. This paper reviews literature and conducts a bibliometric analysis on ethical AI…
Descriptors: Ethics, Artificial Intelligence, Technology Uses in Education, Leadership
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Xiaoming Xi – Language Assessment Quarterly, 2023
Following the burgeoning growth of artificial intelligence (AI) and machine learning (ML) applications in language assessment in recent years, the meteoric rise of ChatGPT and its sweeping applications in almost every sector have left us in awe, scrambling to catch up by developing theories and best practices. This special issue features studies…
Descriptors: Artificial Intelligence, Theory Practice Relationship, Language Tests, Man Machine Systems
Brown, Robert L. – ProQuest LLC, 2014
A problem in computer security is identification of attack signatures in network packets. An attack signature is a pattern of bits that characterizes a particular attack. Because there are many kinds of attacks, there are potentially many attack signatures. Furthermore, attackers may seek to avoid detection by altering the attack mechanism so that…
Descriptors: Computer Security, Identification, Automation, Programming
Taheriyan, Mohsen – ProQuest LLC, 2015
Information sources such as relational databases, spreadsheets, XML, JSON, and Web APIs contain a tremendous amount of structured data, however, they rarely provide a semantic model to describe their contents. Semantic models of data sources capture the intended meaning of data sources by mapping them to the concepts and relationships defined by a…
Descriptors: Semantics, Information Sources, Data, Models
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Dorça, Fabiano – International Journal of Artificial Intelligence in Education, 2015
Studies attest that learning is facilitated if teaching strategies are in accordance with students learning styles, making learning process more effective and considerably improving students performances. In this context, one major research point--and a challenge--is to efficiently discover students' learning styles. But, the test and validation…
Descriptors: Simulation, Students, Cognitive Style, Validity
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Romero, Lucila; North, Matthew; Gutiérrez, Milagros; Caliusco, Laura – Educational Technology & Society, 2015
The use of ontologies as tools to guide the generation, organization and personalization of e-learning content, including e-assessment, has drawn attention of the researchers because ontologies can represent the knowledge of a given domain and researchers use the ontology to reason about it. Although the use of these semantic technologies tends to…
Descriptors: Electronic Learning, Taxonomy, Networks, Evaluation
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Ogan, Amy; Walker, Erin; Baker, Ryan; Rodrigo, Ma. Mercedes T.; Soriano, Jose Carlo; Castro, Maynor Jimenez – International Journal of Artificial Intelligence in Education, 2015
In recent years, there has been increasing interest in automatically assessing help seeking, the process of referring to resources outside of oneself to accomplish a task or solve a problem. Research in the United States has shown that specific help-seeking behaviors led to better learning within intelligent tutoring systems. However, intelligent…
Descriptors: Help Seeking, Cultural Differences, Automation, Intelligent Tutoring Systems
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