Publikationen:
2020
· | A. Askinadze: From Collecting, Integrating, and Visualizing Student Data to Predicting Student Dropout and Performance |
2019
· | A. Askinadze, S. Conrad: Predicting Student Dropout In Higher Education Based on Previous Exam Results Proceedings of the 12th International Conference on Educational Data Mining (EDM) | ||
· | A. Askinadze, M. Liebeck, S. Conrad: BoB: A Bag of eBook Click Behavior Based Grade Prediction Approach Companion Proceedings of the 9th International Conference on Learning Analytics & Knowledge (LAK’19) | ||
· | A. Askinadze, M. Liebeck, S. Conrad: Using Venn, Sankey, and UpSet Diagrams to Visualize Students’ Study Progress Based on Exam Combinations Companion Proceedings of the 9th International Conference on Learning Analytics & Knowledge (LAK’19) |
2018
· | A. Askinadze, M. Liebeck, S. Conrad: Predicting Student Test Performance based on Time Series Data of eBook Reader Behavior Using the Cluster-Distance Space Transformation 5th ICCE workshop on Learning Analytics (LA) & Joint Activity on predicting student performance | ||
· | A. Askinadze, S. Conrad: Development of an Educational Dashboard for the Integration of German State Universities’ Data Proceedings of the 11th International Conference on Educational Data Mining (EDM) | ||
· | A. Askinadze, S. Conrad: Respecting Data Privacy in Educational Data Mining: An Approach to the Transparent Handling of Student Data and Dealing with the Resulting Missing Value Problem 27th IEEE International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE-2018) |
2017
· | P. Hirmer, T. Waizenegger, G. Falazi, M. Abdo, Y. Volga, A. Askinadze, M. Liebeck, S. Conrad, T. Hildebrandt, C. Indiono, S. Rinderle-Ma, M. Grimmer, M. Kricke, E. Peukert: The First Data Science Challenge at BTW 2017 Datenbank-Spektrum | ||
· | A. Askinadze, S. Conrad: A Web Service Architecture for Tracking and Analyzing Data from Distributed E-Learning Environments 2017 IEEE 26th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE) | ||
· | A. Askinadze, S. Conrad: Application of the Dynamic Time Warping Distance for the Student Drop-out Prediction on Time Series Data Proceedings of the 10th International conference on Educational Data Mining (EDM) | ||
· | A. Askinadze: Fake war crime image detection by reverse image search Datenbanksysteme für Business, Technologie und Web (BTW 2017), Studierendenprogramm, 06.-10.03.2017 in Stuttgart |
2016
· | M. Liebeck, P. Modaresi, A. Askinadze, S. Conrad: Pisco: A Computational Approach to Predict Personality Types from Java Source Code Notebook Papers of FIRE 2016 | ||
· | A. Askinadze: Anwendung der Regressions-SVM zur Vorhersage studentischer Leistungen Proceedings of the 28th GI-Workshop Grundlagen von Datenbanken, Nörten Hardenberg, Germany, May 24-27, 2016. |
2015
· | A. Askinadze: Vergleich von Distanzen und Kernel für Klassifikatoren zur Optimierung der Annotation von Bildern Datenbanksysteme für Business, Technologie und Web (BTW 2015), Workshopband, 02.-03.03.2015 in Hamburg |