Gathering Insights from Teenagers' Hacking Experience with Authentic Cybersecurity Tools. - Valdemar Svábenský; Jan Vykopal (FIE, 2018)

Enhancing cybersecurity skills by creating serious games. - Valdemar Svábenský; Jan Vykopal; Milan Cermák; Martin Lastovicka (ITiCSE, 2018)

Challenges Arising from Prerequisite Testing in Cybersecurity Games. - Valdemar Svábenský; Jan Vykopal (SIGCSE, 2018)

Analyzing User Interactions with Cybersecurity Games. - Valdemar Svábenský (SIGCSE, 2019)

Towards Learning Analytics in Cybersecurity Capture the Flag Games. - Valdemar Svábenský; Jan Vykopal; Pavel Celeda (SIGCSE, 2019)

Reflective Diary for Professional Development of Novice Teachers. - Martin Ukrop; Valdemar Svábenský; Jan Nehyba (SIGCSE, 2019)

Visual Feedback for Players of Multi-Level Capture the Flag Games: Field Usability Study. - Radek Oslejsek; Vít Rusnák; Karolína Dockalová Burská; Valdemar Svábenský; Jan Vykopal (VizSEC, 2019)

How Does a Student-Centered Course on Communication and Professional Skills Impact Students in the Long Run? - Renate Motschnig; Michael Silber; Valdemar Svábenský (FIE, 2020)

Teaching Lab: Training Novice Computer Science Teachers. - Martin Ukrop; Valdemar Svábenský; Imrich Nagy (ITiCSE, 2020)

KYPO4INDUSTRY: A Testbed for Teaching Cybersecurity of Industrial Control Systems. - Pavel Celeda; Jan Vykopal; Valdemar Svábenský; Karel Slávicek (SIGCSE, 2020)

What Are Cybersecurity Education Papers About?: A Systematic Literature Review of SIGCSE and ITiCSE Conferences. - Valdemar Svábenský; Jan Vykopal; Pavel Celeda (SIGCSE, 2020)

Benefits and Pitfalls of Using Capture the Flag Games in University Courses. - Jan Vykopal; Valdemar Svábenský; Ee-Chien Chang (SIGCSE, 2020)

Reinforcing Cybersecurity Hands-on Training With Adaptive Learning. - Pavel Seda; Jan Vykopal; Valdemar Svábenský; Pavel Celeda (FIE, 2021)

Toolset for Collecting Shell Commands and Its Application in Hands-on Cybersecurity Training. - Valdemar Svábenský; Jan Vykopal; Daniel Tovarnák; Pavel Celeda (FIE, 2021)

Scalable Learning Environments for Teaching Cybersecurity Hands-on. - Jan Vykopal; Pavel Celeda; Pavel Seda; Valdemar Svábenský; Daniel Tovarnák (FIE, 2021)

Toward Guidelines for Designing Cybersecurity Serious Games. - Miriam Gáliková; Valdemar Svábenský; Jan Vykopal (SIGCSE, 2021)

The Stack: Unplugged Activities for Teaching Computer Science. - Valdemar Svábenský; Martin Ukrop (SIGCSE, 2021)

Cybersecurity knowledge and skills taught in capture the flag challenges. - Valdemar Svábenský; Pavel Celeda; Jan Vykopal; Silvia Brisáková (Comput. Secur., 2021)

Conceptual Model of Visual Analytics for Hands-on Cybersecurity Training. - Radek Oslejsek; Vít Rusnák; Karolína Dockalová Burská; Valdemar Svábenský; Jan Vykopal; Jakub Cegan (IEEE Trans. Vis. Comput. Graph., 2021)

Evaluating Two Approaches to Assessing Student Progress in Cybersecurity Exercises. - Valdemar Svábenský; Richard Weiss 001; Jack Cook; Jan Vykopal; Pavel Celeda; Jens Mache; Radoslav Chudovský; Ankur Chattopadhyay (SIGCSE (1), 2022)

Preventing Cheating in Hands-on Lab Assignments. - Jan Vykopal; Valdemar Svábenský; Pavel Seda; Pavel Celeda (SIGCSE (1), 2022)

Applications of educational data mining and learning analytics on data from cybersecurity training. - Valdemar Svábenský; Jan Vykopal; Pavel Celeda; Lydia Kraus (Educ. Inf. Technol., 2022)

Student assessment in cybersecurity training automated by pattern mining and clustering. - Valdemar Svábenský; Jan Vykopal; Pavel Celeda; Kristián Tkácik; Daniel Popovic (Educ. Inf. Technol., 2022)

Towards Generalizable Detection of Urgency of Discussion Forum Posts. - Valdemar Svábenský; Ryan Baker 001; Andrés Zambrano; Yishan Zou; Stefan Slater (EDM, 2023)

Want to Raise Cybersecurity Awareness? Start with Future IT Professionals. - Lydia Kraus; Valdemar Svábenský; Martin Horák; Vashek Matyás; Jan Vykopal; Pavel Celeda (ITiCSE (1), 2023)

Smart Environment for Adaptive Learning of Cybersecurity Skills. - Jan Vykopal; Pavel Seda; Valdemar Svábenský; Pavel Celeda (IEEE Trans. Learn. Technol., 2023)

Comparison of Large Language Models for Generating Contextually Relevant Questions. - Ivo Lodovico Molina; Valdemar Svábenský; Tsubasa Minematsu; Li Chen 032; Fumiya Okubo; Atsushi Shimada 001 (EC-TEL (2), 2024)

E2Vec: Feature Embedding with Temporal Information for Analyzing Student Actions in E-Book Systems. - Yuma Miyazaki; Valdemar Svábenský; Yuta Taniguchi; Fumiya Okubo; Tsubasa Minematsu; Atsushi Shimada 001 (EDM, 2024)

Evaluating Algorithmic Bias in Models for Predicting Academic Performance of Filipino Students. - Valdemar Svábenský; Mélina Verger; Maria Mercedes T. Rodrigo; Clarence James G. Monterozo; Ryan S. Baker 001; Miguel Zenon Nicanor Lerias Saavedra; Sébastien Lallé; Atsushi Shimada 001 (EDM, 2024)

Detecting Unsuccessful Students in Cybersecurity Exercises in Two Different Learning Environments. - Valdemar Svábenský; Kristián Tkácik; Aubrey Birdwell; Richard Weiss 001; Ryan Shaun Baker; Pavel Celeda; Jan Vykopal; Jens Mache; Ankur Chattopadhyay (FIE, 2024)

Comparison of Three Programming Error Measures for Explaining Variability in CS1 Grades. - Valdemar Svábenský; Maciej Pankiewicz; Jiayi Zhang 004; Elizabeth B. Cloude; Ryan Shaun Baker; Eric Fouh (ITiCSE (1), 2024)

From Paper to Platform: Evolution of a Novel Learning Environment for Tabletop Exercises. - Valdemar Svábenský; Jan Vykopal; Martin Horák; Martin Hofbauer; Pavel Celeda (ITiCSE (1), 2024)

Research and Practice of Delivering Tabletop Exercises. - Jan Vykopal; Pavel Celeda; Valdemar Svábenský; Martin Hofbauer; Martin Horák (ITiCSE (1), 2024)

Automated feedback for participants of hands-on cybersecurity training. - Valdemar Svábenský; Jan Vykopal; Pavel Celeda; Ján Dovjak (Educ. Inf. Technol., 2024)

Supplementary Materials: Evaluating the Impact of Data Augmentation on Predictive Model Performance. - Valdemar Svábenský; Conrad Borchers; Elizabeth B. Cloude; Atsushi Shimada 001 (Zenodo, 2024)

Supplementary Materials: Evaluating the Impact of Data Augmentation on Predictive Model Performance. - Valdemar Svábenský; Conrad Borchers; Elizabeth B. Cloude; Atsushi Shimada 001 (Zenodo, 2024)

Ranking-Based At-Risk Student Prediction Using Federated Learning and Differential Features. - Shunsuke Yoneda; Valdemar Svábenský; Gen Li; Daisuke Deguchi; Atsushi Shimada 001 (EDM, 2025)

Evaluating the Impact of Data Augmentation on Predictive Model Performance. - Valdemar Svábenský; Conrad Borchers; Elizabeth B. Cloude; Atsushi Shimada 001 (LAK, 2025)

Single-agent vs. Multi-agent LLM Strategies for Automated Student Reflection Assessment. - Gen Li; Li Chen 032; Cheng Tang 001; Valdemar Svábenský; Daisuke Deguchi; Takayoshi Yamashita; Atsushi Shimada 001 (PAKDD (5), 2025)

Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance. - Sukrit Leelaluk; Cheng Tang 001; Valdemar Svábenský; Atsushi Shimada 001 (SAC, 2025)

Cybersecurity Study Programs: What's in a Name? - Jan Vykopal; Valdemar Svábenský; Michael Tuscano Lopez II; Pavel Celeda (SIGCSE (1), 2025)

LECTOR: Summarizing E-book Reading Content for Personalized Student Support. - Erwin Daniel López Zapata; Cheng Tang 001; Valdemar Svábenský; Fumiya Okubo; Atsushi Shimada 001 (CoRR, 2025)

PALM: PAnoramic Learning Map Integrating Learning Analytics and Curriculum Map for Scalable Insights Across Courses. - Mahiro Ozaki; Li Chen 032; Shotaro Naganuma; Valdemar Svábenský; Fumiya Okubo; Atsushi Shimada 001 (CoRR, 2025)