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Zifeng Liu; Wanli Xing; Xinyue Jiao; Chenglu Li; Wangda Zhu – Education and Information Technologies, 2025
The ability of large language models (LLMs) to generate code has raised concerns in computer science education, as students may use tools like ChatGPT for programming assignments. While much research has focused on higher education, especially for languages like Java and Python, little attention has been given to K-12 settings, particularly for…
Descriptors: High School Students, Coding, Artificial Intelligence, Electronic Learning
Sirinda Palahan – IEEE Transactions on Learning Technologies, 2025
The rise of online programming education has necessitated more effective personalized interactions, a gap that PythonPal aims to fill through its innovative learning system integrated with a chatbot. This research delves into PythonPal's potential to enhance the online learning experience, especially in contexts with high student-to-teacher ratios…
Descriptors: Programming, Computer Science Education, Artificial Intelligence, Computer Mediated Communication
Uto, Masaki; Nguyen, Duc-Thien; Ueno, Maomi – IEEE Transactions on Learning Technologies, 2020
With the wide spread large-scale e-learning environments such as MOOCs, peer assessment has been popularly used to measure the learner ability. When the number of learners increases, peer assessment is often conducted by dividing learners into multiple groups to reduce the learner's assessment workload. However, in such cases, the peer assessment…
Descriptors: Item Response Theory, Electronic Learning, Peer Evaluation, Accuracy
Kyrilov, Angelo – ProQuest LLC, 2017
Information technology is now ubiquitous in higher education institutions worldwide. More than 85% of American universities use e-learning systems to supplement traditional classroom activities. An obvious benefit of these online tools is their ability to automatically grade exercises submitted by students and provide immediate feedback. Most of…
Descriptors: Case Method (Teaching Technique), Educational Quality, Feedback (Response), Computer Assisted Testing
Maaliw, Renato R. III; Ballera, Melvin A. – International Association for Development of the Information Society, 2017
The usage of data mining has dramatically increased over the past few years and the education sector is leveraging this field in order to analyze and gain intuitive knowledge in terms of the vast accumulated data within its confines. The primary objective of this study is to compare the results of different classification techniques such as Naïve…
Descriptors: Classification, Cognitive Style, Electronic Learning, Decision Making
Barnes, Tiffany, Ed.; Desmarais, Michel, Ed.; Romero, Cristobal, Ed.; Ventura, Sebastian, Ed. – International Working Group on Educational Data Mining, 2009
The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…
Descriptors: Data Analysis, Educational Research, Conferences (Gatherings), Foreign Countries

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