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Becker, Benjamin; Weirich, Sebastian; Goldhammer, Frank; Debeer, Dries – Journal of Educational Measurement, 2023
When designing or modifying a test, an important challenge is controlling its speededness. To achieve this, van der Linden (2011a, 2011b) proposed using a lognormal response time model, more specifically the two-parameter lognormal model, and automated test assembly (ATA) via mixed integer linear programming. However, this approach has a severe…
Descriptors: Test Construction, Automation, Models, Test Items
Yujia Liu; Emily K. Penner; Sabrina Solanki; Xuehan Zhou – Journal of Education Human Resources, 2025
Identifying high-quality educators at the point of hire can reduce future recruitment costs and minimize the impact of attrition on school organizations and student learning. One low-cost way to screen applicants and learn about their beliefs, values, and pedagogy is through their short-essay writing samples. However, there is limited research…
Descriptors: Teacher Selection, Screening Tests, Essays, Job Applicants
Vijayalakshmi B.; Radha G.; Veni Krishna Bharathi A. – Journal of Educational Technology, 2025
Libraries are increasingly adopting information and communication technologies to enhance their services. To ensure all libraries can benefit, regardless of budget, this study highlights gLabel, a freely available open-source tool for barcode label development. The purpose of this paper is to promote gLabel for low-budget libraries by exploring…
Descriptors: Academic Libraries, Library Services, Cost Effectiveness, Automation
Maja Hojer Bruun; Thea Engstrøm Vejlin – Discourse: Studies in the Cultural Politics of Education, 2025
How are educational values and pedagogical approaches inscribed into automated education technologies and their data visualizations? In this article we analyze the design process and technical and pedagogical debates of a team of researchers and developers working on an automated scoring tool for primary school students' early writing as part of…
Descriptors: Data Analysis, Visual Aids, Educational Technology, Automation
Rick Somers; Sam Cunningham; Sarah Dart; Sheona Thomson; Caslon Chua; Edmund Pickering – IEEE Transactions on Learning Technologies, 2024
Academic misconduct stemming from file-sharing websites is an increasingly prevalent challenge in tertiary education, including information technology and engineering disciplines. Current plagiarism detection methods (e.g., text matching) are largely ineffective for combatting misconduct in programming and mathematics-based assessments. For these…
Descriptors: Assignments, Automation, Identification, Technology Uses in Education
Jing Fang; Xiong Xiao; Xiuling He; Yangyang Li; Huanhuan Yuan; Xiaomin Jiao – Interactive Learning Environments, 2024
Knowledge maps are teaching tools that can promote deeply learning and avoid knowledge loss by helping students plan learning paths. Mining potential association rules of concepts from student exercise data was a common method to construct knowledge maps automatically. While manual conditions should be set to filter the association rules future to…
Descriptors: Concept Mapping, Multivariate Analysis, Associative Learning, Learning Strategies
Po-Chun Huang; Ying-Hong Chan; Ching-Yu Yang; Hung-Yuan Chen; Yao-Chung Fan – IEEE Transactions on Learning Technologies, 2024
Question generation (QG) task plays a crucial role in adaptive learning. While significant QG performance advancements are reported, the existing QG studies are still far from practical usage. One point that needs strengthening is to consider the generation of question group, which remains untouched. For forming a question group, intrafactors…
Descriptors: Automation, Test Items, Computer Assisted Testing, Test Construction
Verena Dornauer; Michael Netzer; Éva Kaczkó; Lisa-Maria Norz; Elske Ammenwerth – International Journal of Artificial Intelligence in Education, 2024
Cognitive presence is a core construct of the Community of Inquiry (CoI) framework. It is considered crucial for deep and meaningful online-based learning. CoI-based real-time dashboards visualizing students' cognitive presence may help instructors to monitor and support students' learning progress. Such real-time classifiers are often based on…
Descriptors: Electronic Learning, Discussion, Classification, Automation
Adrià Fenoy; Michal Bojanowski; Miranda J. Lubbers – Field Methods, 2024
To estimate the distribution of the number of acquaintances of the members of a society, the network scale-up method asks survey respondents about the number of people they know with features for which national statistics are available. While many features have been used for this purpose, first names have been suggested to produce particularly low…
Descriptors: Surveys, Population Groups, Automation, Population Distribution
Muhammad Fawad Akbar Khan; Max Ramsdell; Erik Falor; Hamid Karimi – International Educational Data Mining Society, 2024
This paper undertakes a thorough evaluation of ChatGPT's code generation capabilities, contrasting them with those of human programmers from both educational and software engineering standpoints. The emphasis is placed on elucidating its importance in these intertwined domains. To facilitate a robust analysis, we curated a novel dataset comprising…
Descriptors: Artificial Intelligence, Automation, Computer Science Education, Programming
Zhu, Xinhua; Wu, Han; Zhang, Lanfang – IEEE Transactions on Learning Technologies, 2022
Automatic short-answer grading (ASAG) is a key component of intelligent tutoring systems. Deep learning is an advanced method to deal with recognizing textual entailment tasks in an end-to-end manner. However, deep learning methods for ASAG still remain challenging mainly because of the following two major reasons: (1) high-precision scoring…
Descriptors: Intelligent Tutoring Systems, Grading, Automation, Models
Ercikan, Kadriye; McCaffrey, Daniel F. – Journal of Educational Measurement, 2022
Artificial-intelligence-based automated scoring is often an afterthought and is considered after assessments have been developed, resulting in nonoptimal possibility of implementing automated scoring solutions. In this article, we provide a review of Artificial intelligence (AI)-based methodologies for scoring in educational assessments. We then…
Descriptors: Artificial Intelligence, Automation, Scores, Educational Assessment
Yan Jiang; Lillie Ko-Wong; Ivan Valdovinos Gutierrez – Educational Researcher, 2025
In this essay, we explored the feasibility of utilizing artificial intelligence (AI) for qualitative data analysis in equity-focused research. Specifically, we compare thematic analyses of interview transcripts conducted by human coders with those performed by GPT-3 using a zero-shot chain-of-thought prompting strategy. Our results suggest that…
Descriptors: Artificial Intelligence, Feasibility Studies, Data Analysis, Interviews
Kangkang Li; Chengyang Qian; Xianmin Yang – Education and Information Technologies, 2025
In learnersourcing, automatic evaluation of student-generated content (SGC) is significant as it streamlines the evaluation process, provides timely feedback, and enhances the objectivity of grading, ultimately supporting more effective and efficient learning outcomes. However, the methods of aggregating students' evaluations of SGC face the…
Descriptors: Student Developed Materials, Educational Quality, Automation, Artificial Intelligence
Donnette Narine; Takashi Yamashita; Runcie C. W. Chidebe; Phyllis A. Cummins; Jenna W. Kramer; Rita Karam – New Horizons in Adult Education & Human Resource Development, 2025
Job automation can undermine economic security for workers in general, and older workers, in particular. In this respect, consistently updating one's knowledge and skills is essential for being competitive in a technology-driven labor market. Older workers with lower adult literacy skills experience difficulties with continuous education and…
Descriptors: Adult Literacy, Automation, Careers, Lifelong Learning

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