Buch, Englisch, 599 Seiten, Format (B × H): 155 mm x 235 mm
22nd EAI International Conference, CSECS 2026, Boston, MA, USA, November 3–5, 2026, Proceedings
Buch, Englisch, 599 Seiten, Format (B × H): 155 mm x 235 mm
ISBN: 978-3-032-42319-1
Verlag: Springer
This book constitutes the refereed proceedings of the 22nd EAI International Conference on Computer Science and Education in Computer Science, CSECS 2026, held in Boston, USA, during November 3–5, 2026.
The 28 full papers and 8 short papers included in this book were carefully reviewed and selected from 121 submissions.They are organized into the following topical sections: Artificial Intelligence in Education in Computer Science; Data analytics in Education in Computer Science; Quality of Learning Process in Education in Computer Science; Optimization Solutions in Computer Science Theory; ML Implementation in Financial Sector; Security and Ethics in AI Implementations; Optimization of the Algorithms in Edge-to-Fog-to-Cloud Continuum; Computing Systems and AI Implementation in Well Being and Medicine.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Software Engineering
- Sozialwissenschaften Pädagogik Lehrerausbildung, Unterricht & Didaktik E-Learning, Bildungstechnologie
- Mathematik | Informatik EDV | Informatik Technische Informatik Netzwerk-Hardware
- Mathematik | Informatik EDV | Informatik Angewandte Informatik Computeranwendungen in Geistes- und Sozialwissenschaften
Weitere Infos & Material
.- Artificial Intelligence in Education in Computer Science.
.- Exploring Students’ Employment Expectations, AI Concerns and the Role of Universities.
.- Orchestrated Agent Architecture for AI-Assisted Discussion Evaluation.
.- Orchestrating Semester Readiness within a Large LMS Ecosystem A Process-Driven Operational Platform for a
Small Academic Technology Team.
.- Digitalisation of educational centre: case study.
.- Data analytics in Education in Computer Science.
.- Centralized Classroom Data Repository for Learning Analytics in Software Engineering Education.
.- When Incorrect Feedback Goes Undetected: Evidence from Taxonomy-Based Learning in Software Engineering.
.- Development and Application of the EDUFlow BI Platform in the Context of Contemporary Practices of Educational
Analytics.
.- Subjective Preference Judgments in a Hands-On Machine Learning Activity: An Exploratory Study of Packaging Design
Evaluations among University Students.
.- Quality of Learning Process in Education in Computer Science.
.- The Efficiency Paradox: The Algorithmic Bypass in Higher Education.
.- Career Compass- A Multi-Agent Systems for Skill-Aware Career Advising.
.- TerrierTA: An Open, Multi-Agent Framework for Course-Grounded Assessment, Tutoring, and Content Generation.
.- Comparative Analysis of Student Performance and Discussion Participation in Online Learning Environments.
.- Optimization Solutions in Computer Science Theory.
.- Representative Subsample as a LP Problem.
.- Ontology Design Approach Based on Model-Driven Architecture Principles.
.- Evolution of a Software Engineering Project Course: From Traditional Development to AI-Integrated Practice.
.- A study of the software engineering process’s complexity and its relationship with software quality.
.- Autonomous UWB Infrastructure Mapping via Accumulative Ring Intersection.
.- Cognitive Value Assessment of UML Sequence Diagrams: A Miller-Based Model with AI-Driven Experimental
Validation.
.- ML Implementation in Financial Sector.
.- Data Leakage in Financial Machine Learning: A Taxonomy,Empirical Quantification, and Remediation Framework Using
Cryptocurrency Markets.
.- Adaptive Computational Scaling in Sparse Mixture-of Experts via Entropy-Gated Thinking Budgets.
.- AI and Machine Learning in Financial Fraud Detection:Defending Financial Systems in the Age of Adversarial AI.
.- Security and Ethics in AI Implementations.
.- WikiFlow: Predicting Wikipedia Editor Dropout at Scale Using Distributed Machine Learning on Google Cloud.
.- Is Artificial Intelligence (AI) Technology Anti-Human? Ethics of the Relationship Between Machines and Humans.
.- Intelligent System for Early Risk Assessment.
.- Optimization of the Algorithms in Edge-to-Fog-to-Cloud Continuum.
.- Minimum Spanning Tree Algorithms on Large Scale Random Networks.
.- Unsupervised Vibration Fault Detection Using Cepstrum Based Feature Extraction and Mahalanobis Analysis.
.- Data-Driven Predictive Maintenance via Adaptive Hilbert Huang Feature Extraction and XGBoost Classification.
.- Performance Analyses of the Linux Dispatcher.
.- Audio Augmented Reality for Celestial Objects through Music-theoretic and Spatial Sonification.
.- Computing Systems and AI Implementation in Well Being and Medicine.
.- CareVault: Design and Implementation of a Secure Information Management Prototype for Family Caregiving.
.- Sublexical Emotional Valence Recognition: A Biphone Based Experimental Framework.
.- Evaluating Predictive Models for Drug–Drug Interaction.
.- Genetic Testing Utilization Among Ovarian Cancer Patients.
.- Machine Learning Classification of Documented Asthma Status in Pediatric Outpatients: Internal Validation,
Calibration, and Interpretation with SHAP and LIME.
.- MA-CD-KT: Calibration-Centric Multi-Agent Knowledge Tracing with LLM-Guided Semantic Arbitration and
Cognitive Diagnosis.
.- Assessment of Foundation Vision-Language Models on Dental Radiograph Interpretation.
