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Kamila Misiejuk; Sonsoles López-Pernas; Rogers Kaliisa; Mohammed Saqr – Journal of Learning Analytics, 2025
Generative artificial intelligence (GenAI) has opened new possibilities for designing learning analytics (LA) tools, gaining new insights about student learning processes and their environment, and supporting teachers in assessing and monitoring students. This systematic literature review maps the empirical research of 41 papers utilizing GenAI…
Descriptors: Literature Reviews, Artificial Intelligence, Learning Analytics, Data Collection
Stella Y. Kim; Sungyeun Kim – Educational Measurement: Issues and Practice, 2025
This study presents several multivariate Generalizability theory designs for analyzing automatic item-generated (AIG) based test forms. The study used real data to illustrate the analysis procedure and discuss practical considerations. We collected the data from two groups of students, each group receiving a different form generated by AIG. A…
Descriptors: Generalizability Theory, Automation, Test Items, Students
Meholick, Sarah; Honey, Rose; LaTurner, Jason – National Center for Education Statistics, 2023
Statewide longitudinal data systems (SLDSs) can enable researchers, policymakers, and practitioners to identify and understand important relationships and trends across the education-to-workforce continuum. A well-developed SLDS can increase state and territory governments' ability to establish more informed and equitable policies, enable agency…
Descriptors: Longitudinal Studies, State Programs, State Policy, Data Collection
Jae-Sang Han; Hyun-Joo Kim – Journal of Science Education and Technology, 2025
This study explores the potential to enhance the performance of convolutional neural networks (CNNs) for automated scoring of kinematic graph answers through data augmentation using Deep Convolutional Generative Adversarial Networks (DCGANs). By developing and fine-tuning a DCGAN model to generate high-quality graph images, we explored its…
Descriptors: Performance, Automation, Scoring, Models
Arantes, Janine Aldous; Vicars, Mark – Learning, Media and Technology, 2023
In the recent Australian 2021 census, the socio-technical construct of algorithmically driven decision-making processes made LGBTQI+ data as a category of diversity, inclusion and belonging an absent presence. In this paper, we position the notion of 'data justice' in relation to the entrenchment of inequalities and exclusion of LGBTQI+ lives and…
Descriptors: Foreign Countries, Homosexuality, LGBTQ People, Data
Holmes, Langdon; Crossley, Scott; Sikka, Harshvardhan; Morris, Wesley – Information and Learning Sciences, 2023
Purpose: This study aims to report on an automatic deidentification system for labeling and obfuscating personally identifiable information (PII) in student-generated text. Design/methodology/approach: The authors evaluate the performance of their deidentification system on two data sets of student-generated text. Each data set was human-annotated…
Descriptors: Open Source Technology, Automation, Identification, Confidentiality
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
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
Valdemar Švábenský; Jan Vykopal; Pavel Celeda; Ján Dovjak – Education and Information Technologies, 2024
Computer-supported learning technologies are essential for conducting hands-on cybersecurity training. These technologies create environments that emulate a realistic IT infrastructure for the training. Within the environment, training participants use various software tools to perform offensive or defensive actions. Usage of these tools generates…
Descriptors: Computer Security, Information Security, Training, Feedback (Response)
Halima Alnashiri; Mladen Rakovic; Sadia Nawaz; Xinyu Li; Joni Lamsa; Lyn Lim; Maria Bannert; Sanna Jarvela; Dragan Gasevic – Journal of Computer Assisted Learning, 2025
Background: Integrating information from multiple sources is a common yet challenging learning task for secondary school students. Many underuse metacognitive skills, such as monitoring and control, which are essential for promoting engagement and effective learning outcomes. Objective: This study aims to examine the relationship between…
Descriptors: Secondary School Students, Metacognition, Writing (Composition), English
Juliette Woodrow; Sanmi Koyejo; Chris Piech – International Educational Data Mining Society, 2025
High-quality feedback requires understanding of a student's work, insights into what concepts would help them improve, and language that matches the preferences of the specific teaching team. While Large Language Models (LLMs) can generate coherent feedback, adapting these responses to align with specific teacher preferences remains an open…
Descriptors: Feedback (Response), Artificial Intelligence, Teacher Attitudes, Preferences
Larry J. LeBlanc; Thomas A. Grossman; Michael R. Bartolacci – INFORMS Transactions on Education, 2024
The COVID-19 pandemic has forced the rapid adoption of remote teaching modalities including "hyflex" where students attend some class sessions in person and some online. Managing the hyflex course requires faculty to quickly generate several reports and to update these reports rapidly when the authorities adjust the rules, students…
Descriptors: Blended Learning, Scheduling, Spreadsheets, COVID-19
Calvera-Isabal, Miriam; Santos, Patricia; Hoppe, H. -Ulrich; Schulten, Cleo – Comunicar: Media Education Research Journal, 2023
There is an increasing interest and growing practice in Citizen Science (CS) that goes along with the usage of websites for communication as well as for capturing and processing data and materials. From an educational perspective, it is expected that by integrating information about CS in a formal educational setting, it will inspire teachers to…
Descriptors: Citizen Participation, Science and Society, Scientific and Technical Information, Web Sites
Mark Monnin; Lori L. Sussman – Journal of Cybersecurity Education, Research and Practice, 2024
Data transfer between isolated clusters is imperative for cybersecurity education, research, and testing. Such techniques facilitate hands-on cybersecurity learning in isolated clusters, allow cybersecurity students to practice with various hacking tools, and develop professional cybersecurity technical skills. Educators often use these remote…
Descriptors: Computer Science Education, Computer Security, Computer Software, Data
Zirou Lin; Hanbing Yan; Li Zhao – Journal of Computer Assisted Learning, 2024
Background: Peer assessment has played an important role in large-scale online learning, as it helps promote the effectiveness of learners' online learning. However, with the emergence of numerical grades and textual feedback generated by peers, it is necessary to detect the reliability of the large amount of peer assessment data, and then develop…
Descriptors: Peer Evaluation, Automation, Grading, Models

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