Kapak Resmi

Data Mining and Computational Intelligence for E-learning and Education

This Reprint, Data Mining and Computational Intelligence for E-learning and Education, presents a collection of cutting-edge research focused on the application of artificial intelligence to educational contexts. The selected contributions explore how data mining and intelligent algorithms can be us...

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Kaydedildi:
Materyal Türü: Online
Dil:İngilizce
Baskı/Yayın Bilgisi: MDPI - Multidisciplinary Digital Publishing Institute 2025
Konular:
data mining tools
WEKA
J48 algorithm
KAPPA value
predict
confusion matrix
csv
school students
COVID-19
mental health
social support
picture fuzzy force field analysis (PF-FFA)
level based weight assessment (LBWA)
COVID
omicron
online learning
remote learning
online education
Twitter
dataset
tweets
social media
big data
dropout prediction
student attrition
machine learning
educational data mining
learning analytics
educational innovation
higher education
action recognition
cheating
computer vision
feature extraction
video surveillance
academic performance
machine learning in education
imbalanced classes
multi-class classification
learning management system
prediction
thematic analysis
Indonesia
physics education research
clustering
data mining
DBSCAN
K-Means
HDBSCAN
entrepreneurial intentions
measurement invariance
multigroup analysis
gender
Zimbabwe
federated learning
Learning Management System
Technology Acceptance Model
Cumulative Link Mixed Model
descriptive network analysis
student dropout
classification
data sampling
imbalanced datasets
digital literacy dataset
IC3 certification
improvement
RMUTT
thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries
Online Erişim:ONIX_20250812T110751_9783725840304_298
Etiketler: Etiketle
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Özet:This Reprint, Data Mining and Computational Intelligence for E-learning and Education, presents a collection of cutting-edge research focused on the application of artificial intelligence to educational contexts. The selected contributions explore how data mining and intelligent algorithms can be used to analyze learning behaviors, predict academic outcomes, personalize educational experiences, and optimize decision-making processes. Spanning both traditional and digital learning environments, the works featured here address real-world problems and demonstrate practical AI-based solutions, including the use of adaptive systems, chatbots, and predictive models. This Reprint also considers ethical concerns associated with the use of AI in education, offering a well-rounded view of the challenges and opportunities in this evolving field. This volume serves as a valuable reference for researchers, educators, and developers seeking to understand and harness the transformative power of computational intelligence in education.

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