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Xuelin Liu; Hua Zhang; Yue Cheng – International Journal of Web-Based Learning and Teaching Technologies, 2024
In this article, a dialogue text feature extraction model based on big data and machine learning is constructed, which transforms the high-dimensional space of text features into the low-dimensional space that is easy to process, so that the best feature words can be selected to represent the document set. Tests show that in most cases, the…
Descriptors: Artificial Intelligence, Data, Text Structure, Classification
Hua-Xu Zhong; Jui-Hung Chang; Chin-Feng Lai; Pei-Wen Chen; Shang-Hsuan Ku; Shih-Yeh Chen – Education and Information Technologies, 2024
Artificial intelligence (AI) education is becoming an advanced learning trend in programming education. However, AI subjects can be difficult to understand because they require high programming skills and complex knowledge. This makes it challenging to determine how different departments of students are affected by them. This study draws on…
Descriptors: Undergraduate Students, Artificial Intelligence, Programming, STEM Education
Yu-Sheng Su; Shuwen Wang; Xiaohong Liu – Journal of Educational Computing Research, 2024
Pair programming (PP) can help improve students' computational thinking (CT), but the trajectory of CT skills and the differences between high-scoring and low-scoring students in PP are unknown and need further exploration. In this study, a total of 32 fifth graders worked on Scratch tasks in 16 pairs. The group discourse of three learning topics…
Descriptors: Epistemology, Network Analysis, Elementary School Students, Computation
Anna Keune – International Journal of Computer-Supported Collaborative Learning, 2024
A key commitment of computer-supported collaborative learning research is to study how people learn in collaborative settings to guide development of methods for capture and design for learning. Computer-supported collaborative learning research has a tradition of studying how the physical world plays a part in collaborative learning. Within the…
Descriptors: Design Crafts, Visual Arts, Algorithms, Cooperation
Shiyan Jiang; Joey Huang; Hollylynne S. Lee – Educational Technology Research and Development, 2024
Analyzing qualitative data from learning processes is considered "messy" and time consuming (Chi in J Learn Sci 6(3):271-315, 1997). It is often challenging to summarize and synthesize such data in a manner that conveys the richness and complexity of learning processes in a clear and concise manner. Moreover, qualitative data often…
Descriptors: Learning Processes, Data Analysis, Qualitative Research, Visual Aids
Danxia Xing; Yuan Zeng – Education and Information Technologies, 2025
Computational thinking skills as core skills for emerging citizens are receiving great attention from scholars and educators. Various measures have been taken to improve students' computational thinking skills. Among these measures, the smart classroom, as a technology-enhanced learning environment, plays an important role in cultivating students'…
Descriptors: Secondary School Students, Information Literacy, Digital Literacy, Information Technology
Yuan Hsiao; Lee Fiorio; Jonathan Wakefield; Emilio Zagheni – Sociological Methods & Research, 2024
Obtaining reliable and timely estimates of migration flows is critical for advancing the migration theory and guiding policy decisions, but it remains a challenge. Digital data provide granular information on time and space, but do not draw from representative samples of the population, leading to biased estimates. We propose a method for…
Descriptors: Migration, Migration Patterns, Data Collection, Data Analysis
Chander Diwaker; Neha Miglani – Journal of Computer Assisted Learning, 2025
Background: The ever-increasing computational demands call for optimal resource utilisation and system performance in the cloud environment. Organisations are increasingly migrating workloads to cloud platforms, mandating the need for efficient resource distribution. Load balancing, a critical cloud component, ensures equitable distribution of…
Descriptors: Internet, Information Storage, Educational Practices, Computation
Capturing Movement: A Tablet App, "Geometry Touch," for Recording Onscreen Finger-Based Gesture Data
Stoo Sepp; Sharon Tindall-Ford; Shirley Agostinho; Fred Paas – IEEE Transactions on Learning Technologies, 2024
This article presents a novel digital method of capturing finger-based gestures on touchscreen devices for the purpose of exploring tracing gestures in educational research. Given that tracing has been found to support cognition, learning, and problem solving in educational settings, data related to the performance of these gestures are…
Descriptors: Computer Oriented Programs, Tablet Computers, Data Collection, Problem Solving
Overton, Michael; Kleinschmit, Stephen – Teaching Public Administration, 2022
Public administration is struggling to contend with a substantial shift in practice fueled by the accelerating adoption of information technology. New skills, competencies and pedagogies are required by the field to help overcome the data-skills gap. As a means to address these deficiencies, we introduce the Data Science Literacy Framework, a…
Descriptors: Public Administration, Public Administration Education, Data, Information Literacy
Goswami, Sukalyan; Mukherjee, Kuntal – International Journal of Web-Based Learning and Teaching Technologies, 2020
Virtual resources team up to create a computational grid, which is used in computation-intensive problem solving. A majority of these problems require high performance resources to compute and generate results, making grid computation another type of high performance computing. The optimization in computational grids relates to resource…
Descriptors: Mathematics, Scheduling, Computation, Resources
Çakiroglu, Ünal; Kiliç, Servet – Interactive Learning Environments, 2023
Recent years have witnessed an increasing emphasis on integrating computational thinking into school curriculums. This study deals with suggesting a course model including data collection tools for evaluating teachers' pedagogical content knowledge in teaching computational thinking via teaching robot programming. Taking the advantages of virtual…
Descriptors: Teachers, Pedagogical Content Knowledge, Computation, Thinking Skills
Kassa, Ermias Abebe; Mekonnen, Enguday Ademe – Computer Science Education, 2022
Background and Context: Computational thinking (CT) is one of the 21st century skills required of graduates joining the workforce. Hence, countries have begun to incorporate CT into their curricula. Objective: There is, however, a dearth of research coming from Africa showing the extent of CT's integration in the science, technology, engineering,…
Descriptors: Computation, Thinking Skills, Secondary School Curriculum, Information Technology
Junfeng Man; Rongke Zeng; Xiangyang He; Hua Jiang – Knowledge Management & E-Learning, 2024
At present, the widespread use of online education platforms has attracted the attention of more and more people. The application of AI technology in online education platform makes multidimensional evaluation of students' ability become the trend of intelligent education in the future. Currently, most existing studies are based on traditional…
Descriptors: Cognitive Ability, Student Evaluation, Algorithms, Learning Processes
Mandanici, Marcella; Di Filippo, Roberto; Delle Monache, Stefano – Technology, Knowledge and Learning, 2021
This paper describes an educational experience realized in the form of extracurricular workshops involving music technology students of the "V. Gambara" music high school in Brescia (Italy). By means of a participatory prototyping experience, the project aimed at fostering the students awareness and understanding of technological means…
Descriptors: Extracurricular Activities, Workshops, Music Education, High School Students