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Rubén Buitrago; Jesús Salinas; Oscar Boude – Knowledge Management & E-Learning, 2024
Design patterns for learning are about articulating, testing and sharing the principles of problem solving in the educational context. In this way, multiple patterns are developed to solve common problems, described in various pattern language formats. Therefore, this work is about characterizing and establishing functional relationships between…
Descriptors: Delphi Technique, Programming Languages, Programming, Computer Software
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Amanda Konet; Ian Thomas; Gerald Gartlehner; Leila Kahwati; Rainer Hilscher; Shannon Kugley; Karen Crotty; Meera Viswanathan; Robert Chew – Research Synthesis Methods, 2024
Accurate data extraction is a key component of evidence synthesis and critical to valid results. The advent of publicly available large language models (LLMs) has generated interest in these tools for evidence synthesis and created uncertainty about the choice of LLM. We compare the performance of two widely available LLMs (Claude 2 and GPT-4) for…
Descriptors: Data Collection, Artificial Intelligence, Computer Software, Computer System Design
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Sarah Narvaiz; Qinyun Lin; Joshua M. Rosenberg; Kenneth A. Frank; Spiro J. Maroulis; Wei Wang; Ran Xu – Grantee Submission, 2024
Sensitivity analysis, a statistical method crucial for validating inferences across disciplines, quantifies the conditions that could alter conclusions (Razavi et al., 2021). One line of work is rooted in linear models and foregrounds the sensitivity of inferences to the strength of omitted variables (Cinelli & Hazlett, 2019; Frank, 2000). A…
Descriptors: Statistical Analysis, Computer Software, Robustness (Statistics), Statistical Inference
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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
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Haering, Marlo; Bano, Muneera; Zowghi, Didar; Kearney, Matthew; Maalej, Walid – IEEE Transactions on Learning Technologies, 2021
With the vast number of apps and the complexity of their features, it is becoming challenging for teachers to select a suitable learning app for their courses. Several evaluation frameworks have been proposed in the literature to assist teachers with this selection. The iPAC framework is a well-established mobile learning framework highlighting…
Descriptors: Automation, Courseware, Computer Software Evaluation, Computer Software Selection
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Xiaoheng Yan; Gila Hanna – International Journal of Mathematical Education in Science and Technology, 2025
As new technological developments continue to change the educational landscape, it is not an exception in the area of proof and proving. This classroom note introduces the use of one of the trending proofs assistants -- the Lean theorem prover. We first provide a technical account of Lean, then exemplify Lean proofs in propositional logic, number…
Descriptors: Mathematics Instruction, Undergraduate Students, Mathematical Logic, Validity
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Catherine Mick; Don Lee; Leah Sandall; Katherine Frels; Yufeng Ge – Natural Sciences Education, 2025
Traditional phenotyping methods are labor-intensive, time-consuming, and often destructive measurements that describe plant traits. Technology allows the advancement of sensor-based phenotype data to be collected digitally. This area of work is called high-throughput phenotyping (HTP). HTP is rapid, non-destructive, and non-invasive. The effective…
Descriptors: Plants (Botany), Genetics, Open Educational Resources, Technology Integration
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Simon M. Ceh; Mathias Benedek – Journal of Creative Behavior, 2025
Creative behaviors are increasingly impacted by digital technologies, but little is known about the way digital technologies support everyday creativity and what factors predict their creative use. We investigated to what extent individual differences in person-specific (creativity, personality) and platform-specific (e.g., perceived creativity…
Descriptors: Creativity, Behavior, Social Media, Personality Traits
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Hanxiang Du; Gaoxia Zhu; Wanli Xing; Charles Xie – Journal of Science Education and Technology, 2025
Engineering design that requires mathematical analysis, scientific understanding, and technology is critical for preparing students for solving engineering problems. In simulated design environments, students are expected to learn about science and engineering through their design. However, there is a lack of understanding concerning linking…
Descriptors: Engineering, Design, Scientific Concepts, Problem Solving
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Yin Kiong Hoh – American Biology Teacher, 2025
Artificial intelligence (AI) encompasses the science and engineering behind creating intelligent machines capable of tasks that typically rely on human intelligence, such as learning, reasoning, decision-making, and problem-solving. By analyzing vast amounts of data, identifying patterns, and making predictions that were once impossible, AI has…
Descriptors: Artificial Intelligence, Biological Sciences, Computer Software, Algorithms
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Claire Ahn; Alexandra Minuk – Journal of Adolescent & Adult Literacy, 2025
In secondary English classrooms, poetry is often a text that is least liked because it is viewed as being "inaccessible," reserved for the elite, and/or too abstract. Part of the reason for this also lies in the traditional, colonial structures of introducing poetry such as relying on canonical texts and close reading analysis. Yet,…
Descriptors: Poetry, Multimedia Materials, Creative Writing, Teaching Methods
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Stefanie Panke – Journal of Teacher Education, 2025
The autoethnographic study investigates the transformative impact of generative AI on educational research, instructional design, and teaching practices over a 5-month period (May-October 2024). By integrating AI tools into every phase of the research process, the study examines AI's role as both a research partner and a subject of inquiry. Field…
Descriptors: Ethnography, Artificial Intelligence, Computer Software, Instructional Design
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Ken Frank; Guan Saw; Qinyun Lin; Ran Xu; Joshua Rosenberg; Spiro Maroulis; Bret Staudt Willet – Grantee Submission, 2025
This is a practical guide for applying the Impact Threshold for a Confounding Variable and the Robustness of Inference to Replacement using the konfound packages in Stata and R as well as the R-shiny app. It includes motivation worked examples, and tutorials.
Descriptors: Robustness (Statistics), Statistical Inference, Programming Languages, Computer Software
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Luka Doric; Nikola Luburic; Jelena Slivka; Simona Prokic; Anica Ðukic – ACM Transactions on Computing Education, 2025
Teamwork is crucial in software engineering. However, recent literature concludes that software engineering graduates have underdeveloped teamwork skills. Instructors wishing to develop teamwork skills are faced with many teamwork models and a lack of empirical studies that examine their utility in higher education. We conducted an exploratory…
Descriptors: Teamwork, Cooperative Learning, Computer Software, Undergraduate Students
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Rachel F. Adler; Devorah Kletenik – Education and Information Technologies, 2025
Although digital accessibility topics are increasingly gaining inclusion in university computing classrooms, many instructors still encounter difficulties in engaging students with this subject. The Universal Design for Learning (UDL) framework, a pedagogical approach that emphasizes multiple means of engagement, offers a promising strategy to…
Descriptors: Access to Education, Learning Processes, Preferences, Educational Games
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