Výpis publikací

PELÁNEK, Radek. Adaptive Learning is Hard: Challenges, Nuances, and Trade-offs in Modeling. International Journal of Artificial Intelligence in Education. NEW YORK: SPRINGER, 2024, 26 s. ISSN 1560-4292. Dostupné z: https://dx.doi.org/10.1007/s40593-024-00400-6.

PELÁNEK, Radek. Leveraging response times in learning environments: opportunities and challenges. User Modeling and User-Adapted Interaction. DORDRECHT: Springer Netherlands, 2024, 24 s. ISSN 0924-1868. Dostupné z: https://dx.doi.org/10.1007/s11257-023-09386-7.

PELÁNEK, Radek, Tomáš EFFENBERGER a Petr JARUŠEK. Personalized recommendations for learning activities in online environments: a modular rule-based approach. User Modeling and User-Adapted Interaction. DORDRECHT: Springer Netherlands, 2024, 32 s. ISSN 0924-1868. Dostupné z: https://dx.doi.org/10.1007/s11257-024-09396-z.

PELÁNEK, Radek a Tomáš EFFENBERGER. The Landscape of Computational Thinking Problems for Practice and Assessment. ACM TRANSACTIONS ON COMPUTING EDUCATION. UNITED STATES: ASSOC COMPUTING MACHINERY, 2023, roč. 23, č. 2, s. 1-29. ISSN 1946-6226. Dostupné z: https://dx.doi.org/10.1145/3578269.

PELÁNEK, Radek. Adaptive, Intelligent, and Personalized: Navigating the Terminological Maze Behind Educational Technology. International Journal of Artificial Intelligence in Education. 2022, roč. 32, č. 1, s. 151-173. ISSN 1560-4292. Dostupné z: https://dx.doi.org/10.1007/s40593-021-00251-5.

EFFENBERGER, Tomáš a Radek PELÁNEK. Code Quality Defects Across Introductory Programming Topics. Online. In Larry Merkle, Maureen Doyle. Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V. 1. New York, NY, USA: Association for Computing Machinery, 2022, s. 941-947. ISBN 978-1-4503-9070-5. Dostupné z: https://dx.doi.org/10.1145/3478431.3499415.

PELÁNEK, Radek, Tomáš EFFENBERGER a Jaroslav ČECHÁK. Complexity and Difficulty of Items in Learning Systems. International Journal of Artificial Intelligence in Education. 2022, roč. 32, č. 1, s. 196-232. ISSN 1560-4292. Dostupné z: https://dx.doi.org/10.1007/s40593-021-00252-4.

PELÁNEK, Radek a Tomáš EFFENBERGER. Design and analysis of microworlds and puzzles for block-based programming. Computer Science Education. Routledge, 2022, roč. 32, č. 1, s. 66-104. ISSN 0899-3408. Dostupné z: https://dx.doi.org/10.1080/08993408.2020.1832813.

PELÁNEK, Radek a Tomáš EFFENBERGER. Improving Learning Environments: Avoiding Stupidity Perspective. IEEE TRANSACTIONS ON LEARNING TECHNOLOGIES. UNITED STATES: IEEE COMPUTER SOC, 2022, roč. 15, č. 1, s. 64-77. ISSN 1939-1382. Dostupné z: https://dx.doi.org/10.1109/TLT.2022.3154936.

PELÁNEK, Radek, Tomáš EFFENBERGER a Adam KUKUČKA. Towards Design-Loop Adaptivity: Identifying Items for Revision. Journal of Educational Data Mining. International Educational Data Mining Society, 2022, roč. 14, č. 3, s. 1-25. ISSN 2157-2100. Dostupné z: https://dx.doi.org/10.5281/zenodo.7357331.

PELÁNEK, Radek. Analyzing and Visualizing Learning Data: A System Designer's Perspective. Journal of Learning Analytics. 2021, roč. 8, č. 2, s. 93-104. ISSN 1929-7750. Dostupné z: https://dx.doi.org/10.18608/jla.2021.7345.

ČECHÁK, Jaroslav a Radek PELÁNEK. Better Model, Worse Predictions: The Dangers in Student Model Comparisons. In Roll, Ido and McNamara, Danielle and Sosnovsky, Sergey and Luckin, Rose and Dimitrova, Vania. International Conference on Artificial Intelligence in Education. Cham: Springer, 2021, s. 500-511. ISBN 978-3-030-78291-7. Dostupné z: https://dx.doi.org/10.1007/978-3-030-78292-4_40.

ČECHÁK, Jaroslav a Radek PELÁNEK. Experimental Evaluation of Similarity Measures for Educational Items. Online. In I-Han Hsiao, Shaghayegh Sahebi, François Bouchet, Jill-Jênn Vie. Proceedings of the 14th International Conference on Educational Data Mining. Neuveden: Neuveden, 2021, s. 553-558. ISBN 978-1-7336736-2-4.

EFFENBERGER, Tomáš a Radek PELÁNEK. Interpretable Clustering of Students’ Solutions in Introductory Programming. Online. In Roll I., McNamara D., Sosnovsky S., Luckin R., Dimitrova V. Artificial Intelligence in Education. AIED 2021. Lecture Notes in Computer Science, vol 12748. Cham: Springer, 2021, s. 101-112. ISBN 978-3-030-78291-7. Dostupné z: https://dx.doi.org/10.1007/978-3-030-78292-4_9.

EFFENBERGER, Tomáš a Radek PELÁNEK. Validity and Reliability of Student Models for Problem-Solving Activities. Online. In Proceedings of the 11th International Conference on Learning Analytics and Knowledge. New York, NY, USA: Association for Computing Machinery, 2021, s. 1-11. ISBN 978-1-4503-8935-8. Dostupné z: https://dx.doi.org/10.1145/3448139.3448140.

EFFENBERGER, Tomáš a Radek PELÁNEK. Visualization of Student-Item Interaction Matrix. Online. In Muhittin Sahin, Dirk Ifenthaler. Visualizations and Dashboards for Learning Analytics. Cham: Springer, 2021, s. 439-456. Advances in Analytics for Learning and Teaching. ISBN 978-3-030-81221-8. Dostupné z: https://dx.doi.org/10.1007/978-3-030-81222-5_20.

PELÁNEK, Radek. A Classification Framework for Practice Exercises in Adaptive Learning Systems. IEEE Transactions on Learning Technologies. 2020, roč. 13, č. 4, s. 734-747. ISSN 1939-1382. Dostupné z: https://dx.doi.org/10.1109/TLT.2020.3027050.

PELÁNEK, Radek a Tomáš EFFENBERGER. Beyond binary correctness: Classification of students’ answers in learning systems. User Modeling and User-Adapted Interaction. Springer, 2020, roč. 30, č. 5, s. 867-893. ISSN 0924-1868. Dostupné z: https://dx.doi.org/10.1007/s11257-020-09265-5.

EFFENBERGER, Tomáš, Radek PELÁNEK a Jaroslav ČECHÁK. Exploration of the Robustness and Generalizability of the Additive Factors Model. Online. In Proceedings of the 10th International Conference on Learning Analytics and Knowledge. New York, NY, USA: Association for Computing Machinery, 2020, s. 472-479. ISBN 978-1-4503-7712-6. Dostupné z: https://dx.doi.org/10.1145/3375462.3375491.

EFFENBERGER, Tomáš a Radek PELÁNEK. Impact of Methodological Choices on the Evaluation of Student Models. Online. In Bittencourt I., Cukurova M., Muldner K., Luckin R., Millán E. Artificial Intelligence in Education. AIED 2020. Lecture Notes in Computer Science, vol 12163. Cham: Springer, 2020, s. 153-164. ISBN 978-3-030-52236-0. Dostupné z: https://dx.doi.org/10.1007/978-3-030-52237-7_13.

PELÁNEK, Radek. Learning analytics challenges: trade-offs, methodology, scalability. Online. In Christoph Rensing, Hendrik Drachsler. Proceedings of the Tenth International Conference on Learning Analytics & Knowledge. New York, NY, United States: Association for Computing Machinery, 2020, s. 554-558. ISBN 978-1-4503-7712-6. Dostupné z: https://dx.doi.org/10.1145/3375462.3375463.

PELÁNEK, Radek. Managing items and knowledge components: domain modeling in practice. Educational Technology Research and Development. 2020, roč. 68, č. 1, s. 529-550. ISSN 1042-1629. Dostupné z: https://dx.doi.org/10.1007/s11423-019-09716-w.

PELÁNEK, Radek. Measuring Similarity of Educational Items: An Overview. IEEE Transactions on Learning Technologies. 2020, roč. 13, č. 2, s. 354-366. ISSN 1939-1382. Dostupné z: https://dx.doi.org/10.1109/TLT.2019.2896086.

EFFENBERGER, Tomáš, Jaroslav ČECHÁK a Radek PELÁNEK. Difficulty and Complexity of Introductory Programming Problems. Online. In 3rd Educational Data Mining in Computer Science Education Workshop. 2019, 8 s.

ČECHÁK, Jaroslav a Radek PELÁNEK. Item Ordering Biases in Educational Data. Online. In Seiji Isotani, Eva Millán, Amy Ogan, Peter Hastings, Bruce McLaren, Rose Luckin. International Conference on Artificial Intelligence in Education. Cham: Springer, 2019, s. 48-58. ISBN 978-3-030-23203-0. Dostupné z: https://dx.doi.org/10.1007/978-3-030-23204-7_5.

EFFENBERGER, Tomáš, Jaroslav ČECHÁK a Radek PELÁNEK. Measuring Difficulty of Introductory Programming Tasks. Online. In Proceedings of the Sixth (2019) ACM Conference on Learning @ Scale (L@S '19). New York: ACM, 2019, s. „28:1“-„28:4“, 4 s. ISBN 978-1-4503-6804-9. Dostupné z: https://dx.doi.org/10.1145/3330430.3333641.

EFFENBERGER, Tomáš a Radek PELÁNEK. Measuring Students’ Performance on Programming Tasks. Online. In Proceedings of the Sixth (2019) ACM Conference on Learning @ Scale (L@S '19). New York: ACM, 2019, s. "26:1"-"26:4", 4 s. ISBN 978-1-4503-6804-9. Dostupné z: https://dx.doi.org/10.1145/3330430.3333639.

PELÁNEK, Radek a Jiří ŘIHÁK. Analysis and design of mastery learning criteria. New Review of Hypermedia and Multimedia. Taylor & Francis, 2018, roč. 24, č. 3, s. 133-159. ISSN 1361-4568. Dostupné z: https://dx.doi.org/10.1080/13614568.2018.1476596.

PELÁNEK, Radek. Conceptual Issues in Mastery Criteria: Differentiating Uncertainty and Degrees of Knowledge. Online. In Carolyn Penstein Rosé, Roberto Martínez Maldonado, Heinz Ulrich Hoppe, Rose Luckin, Manolis Mavrikis, Kaska Porayska-Pomsta, Bruce M. McLaren, Benedict du Boulay. Artificial Intelligence in Education. New York: Springer, 2018, s. 450-461. ISBN 978-3-319-93842-4. Dostupné z: https://dx.doi.org/10.1007/978-3-319-93843-1_33.

PELÁNEK, Radek. Exploring the Utility of Response Times and Wrong Answers for Adaptive Learning. Online. In Rose Luckin, Scott Klemmer, Kenneth R. Koedinger. Learning @ Scale. New York, NY, USA: ACM, 2018, s. "18:1"-"18:4", 4 s. ISBN 978-1-4503-5886-6. Dostupné z: https://dx.doi.org/10.1145/3231644.3231675.

PELÁNEK, Radek, Tomáš EFFENBERGER, Matěj VANĚK, Vojtěch SASSMANN a Dominik GMITERKO. Measuring Item Similarity in Introductory Programming. Online. In Rose Luckin, Scott Klemmer, Kenneth R. Koedinger. Proceedings of the Fifth Annual ACM Conference on Learning at Scale. New York, NY, USA: ACM, 2018, s. "19:1"-"19:4", 4 s. ISBN 978-1-4503-5886-6. Dostupné z: https://dx.doi.org/10.1145/3231644.3231676.

PELÁNEK, Radek. The details matter: methodological nuances in the evaluation of student models. User Modeling and User-Adapted Interaction. Springer, 2018, roč. 28, č. 3, s. 207-235. ISSN 0924-1868. Dostupné z: https://dx.doi.org/10.1007/s11257-018-9204-y.

EFFENBERGER, Tomáš a Radek PELÁNEK. Towards making block-based programming activities adaptive. Online. In Rose Luckin, Scott Klemmer, Kenneth R. Koedinger. Learning @ Scale. New York, NY, USA: ACM, 2018, s. "13:1"-"13:4", 4 s. ISBN 978-1-4503-5886-6. Dostupné z: https://dx.doi.org/10.1145/3231644.3231670.

PELÁNEK, Radek. Bayesian knowledge tracing, logistic models, and beyond: an overview of learner modeling techniques. User Modeling and User-Adapted Interaction. 2017, roč. 27, 3-5, s. 313-350. ISSN 0924-1868. Dostupné z: https://dx.doi.org/10.1007/s11257-017-9193-2.

PELÁNEK, Radek, Jan PAPOUŠEK, Jiří ŘIHÁK, Vít STANISLAV a Juraj NIŽNAN. Elo-based Learner Modeling for the Adaptive Practice of Facts. User Modeling and User-Adapted Interaction. Springer Netherlands, 2017, roč. 26, č. 1, s. 89-118. ISSN 0924-1868. Dostupné z: https://dx.doi.org/10.1007/s11257-016-9185-7.

PAPOUŠEK, Jan a Radek PELÁNEK. Evaluation of Learners' Adjustment of Question Difficulty in Adaptive Practice of Facts. Online. In Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization. New York: ACM, 2017, s. 379-380. ISBN 978-1-4503-4635-1. Dostupné z: https://dx.doi.org/10.1145/3079628.3079642.

PELÁNEK, Radek a Jiří ŘIHÁK. Experimental Analysis of Mastery Learning Criteria. Online. In Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization. New York, NY, USA: ACM, 2017, s. 156-163. ISBN 978-1-4503-4635-1. Dostupné z: https://dx.doi.org/10.1145/3079628.3079667.

PELÁNEK, Radek. Measuring predictive performance of user models: The details matter. Online. In Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization. USA: ACM, 2017, s. 197-201. ISBN 978-1-4503-5067-9. Dostupné z: https://dx.doi.org/10.1145/3099023.3099042.

ŘIHÁK, Jiří a Radek PELÁNEK. Measuring Similarity of Educational Items Using Data on Learners’ Performance. Online. In Proceedings of the 10th International Conference on Educational Data Mining. Wuhan, China.: International Educational Data Mining Society, 2017, s. 16-23.

PAPOUŠEK, Jan a Radek PELÁNEK. Should We Give Learners Control Over Item Difficulty?. Online. In Personalization Approaches in Learning Environments, Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization. New York: ACM, 2017, s. 299-303. ISBN 978-1-4503-5067-9. Dostupné z: https://dx.doi.org/10.1145/3099023.3099080.

PAPOUŠEK, Jan, Radek PELÁNEK a Vít STANISLAV. Adaptive Geography Practice Data Set. Journal of Learning Analytics. 2016, roč. 3, č. 2, s. 317-321. ISSN 1929-7750.

PELÁNEK, Radek. Applications of the Elo rating system in adaptive educational systems. COMPUTERS & EDUCATION. 2016, roč. 98, č. 1, s. 169-179. ISSN 0360-1315. Dostupné z: https://dx.doi.org/10.1016/j.compedu.2016.03.017.

PAPOUŠEK, Jan, Vít STANISLAV a Radek PELÁNEK. Evaluation of an Adaptive Practice System for Learning Geography Facts. Online. In Proceedings of the Sixth International Conference on Learning Analytics & Knowledge. Edinburgh, United Kingdom: ACM, 2016, s. 134-142. ISBN 978-1-4503-4190-5. Dostupné z: https://dx.doi.org/10.1145/2883851.2883884.

PAPOUŠEK, Jan, Vít STANISLAV a Radek PELÁNEK. Evaluation of the Impact of Question Difficulty on Engagement and Learning. Brno, 2016, 13 s.

ŘIHÁK, Jiří a Radek PELÁNEK. Choosing a Student Model for a Real World Application. Online. In Workshop Proceedings of 13th International Conference on Intelligent Tutoring Systems. Zagreb: Intelligent Tutoring Systems, 2016, s. 188-198.

PELÁNEK, Radek, Jiří ŘIHÁK a Jan PAPOUŠEK. Impact of Data Collection on Interpretation and Evaluation of Student Models. Online. In Proceedings of the Sixth International Conference on Learning Analytics & Knowledge. Edinburgh, United Kingdom: ACM, 2016, s. 40-47. ISBN 978-1-4503-4190-5. Dostupné z: https://dx.doi.org/10.1145/2883851.2883868.

PAPOUŠEK, Jan, Vít STANISLAV a Radek PELÁNEK. Impact of Question Difficulty on Engagement and Learning. Online. In Alessandro Micarelli, John Stamper, Kitty Panourgia. Intelligent Tutoring Systems: 13th International Conference. Zagreb, Croatia: Springer International Publishing, 2016, s. 267-272. ISBN 978-3-319-39582-1. Dostupné z: https://dx.doi.org/10.1007/978-3-319-39583-8_28.

PELÁNEK, Radek a Jiří ŘIHÁK. Properties and Applications of Wrong Answers in Online Educational Systems. Online. In Proceedings of the 9th International Conference on Educational Data Mining. Raleigh (USA, NC): International Educational Data Mining Society, 2016, s. 466-471.

ŘIHÁK, Jiří a Radek PELÁNEK. What is More Important for Student Modeling: Domain Structure or Response Times? In Intelligent Tutoring Systems : 13th International Conference, ITS 2016, Zagreb, Croatia, June 7-10, 2016. Proceedings. Zagreb: Springer International Publishing, 2016, s. 451-452. ISBN 978-3-319-39582-1. Dostupné z: https://dx.doi.org/10.1007/978-3-319-39583-8.

PAPOUŠEK, Jan, Radek PELÁNEK, Jiří ŘIHÁK a Vít STANISLAV. An Analysis of Response Times in Adaptive Practice of Geography Facts. Online. In Proceedings of the 8th International Conference on Educational Data Mining. Madrid: International Educational Data Mining Society, 2015, s. 562-563. ISBN 978-84-606-9425-0.

NIŽNAN, Juraj, Jan PAPOUŠEK a Radek PELÁNEK. Exploring the Role of Small Differences in Predictive Accuracy using Simulated Data. Online. In Second Workshop on Simulated Learners. Proceedings of the Workshops at the 17th International Conference on Artificial Intelligence in Education. Madrid: Sun SITE Central Europe, 2015, s. 21-30. ISSN 1613-0073.

PAPOUŠEK, Jan a Radek PELÁNEK. Impact of Adaptive Educational System Behaviour on Student Motivation. In Artificial Intelligence in Education. Madrid: Springer International Publishing, 2015, s. 348-357. ISBN 978-3-319-19772-2. Dostupné z: https://dx.doi.org/10.1007/978-3-319-19773-9_35.

PELÁNEK, Radek. Metrics for Evaluation of Student Models. Journal of Educational Data Mining. 2015, roč. 7, č. 3, s. 1-19. ISSN 2157-2100.

PELÁNEK, Radek. Modeling Students' Memory for Application in Adaptive Educational Systems. Online. In Proceedings of the 8th International Conference on Educational Data Mining. Madrid: International Educational Data Mining Society, 2015, s. 480-483. ISBN 978-84-606-9425-0.

PELÁNEK, Radek a Petr JARUŠEK. Student Modeling Based on Problem Solving Times. International Journal of Artificial Intelligence in Education. 2015, roč. 25, č. 4, s. 493-519. ISSN 1560-4292. Dostupné z: https://dx.doi.org/10.1007/s40593-015-0048-x.

ŘIHÁK, Jiří, Radek PELÁNEK a Juraj NIŽNAN. Student Models for Prior Knowledge Estimation. Online. In Proceedings of the 8th International Conference on Educational Data Mining. Madrid: International Educational Data Mining Society, 2015, s. 109-116. ISBN 978-84-606-9425-0.

PELÁNEK, Radek. A Brief Overview of Metrics for Evaluation of Student Models. Online. In Sergio Gutierrez-Santos, Olga C. Santos. Proceedings of the Workshops held at Educational Data Mining 2014. Velká Británie: RWTH Aachen University, 2014, s. 151-152. ISSN 1613-0073.

PELÁNEK, Radek, Jan PAPOUŠEK a Vít STANISLAV. Adaptive Practice of Facts in Domains with Varied Prior Knowledge. Online. In John Stamper, Zachary Pardos, Manolis Mavrikis, Bruce M. McLaren. Proceedings of the 7th International Conference on Educational Data Mining (EDM 2014). London, United Kingdom: International Educational Data Mining Society, 2014, s. 6-13. ISBN 978-0-9839525-4-1.

PELÁNEK, Radek. Application of Time Decay Functions and the Elo System in Student Modeling. Online. In John Stamper, Zachary Pardos, Manolis Mavrikis, Bruce M. McLaren. Proceedings of the 7th International Conference on Educational Data Mining (EDM 2014). 2014. vyd. London, United Kingdom: International Educational Data Mining Society, 2014, s. 21-27. ISBN 978-0-9839525-4-1.

NIŽNAN, Juraj, Radek PELÁNEK a Jiří ŘIHÁK. Mapping Problems to Skills Combining Expert Opinion and Student Data. In P. Hlineny et al. Proceedings of MEMICS'14. Německo: Springer, 2014, s. 113-124. ISBN 978-3-319-14895-3. Dostupné z: https://dx.doi.org/10.1007/978-3-319-14896-0_10.

NIŽNAN, Juraj, Radek PELÁNEK a Jiří ŘIHÁK. Using Problem Solving Times and Expert Opinion to Detect Skills. Online. In John Stamper, Zachary Pardos, Manolis Mavrikis, Bruce M. McLaren. Proceedings of the 7th International Conference on Educational Data Mining. London: International Educational Data Mining Society, 2014, s. 433-434. ISBN 978-0-9839525-4-1.

PELÁNEK, Radek, Petr BOROŠ, Juraj NIŽNAN a Jiří ŘIHÁK. Automatic Detection of Concepts from Problem Solving Times. In Lane, H.C.; Yacef, K.; Mostow, J.; Pavlik, P. Artificial Intelligence in Education. USA: Springer, 2013, s. 595-598. ISBN 978-3-642-39111-8. Dostupné z: https://dx.doi.org/10.1007/978-3-642-39112-5_67.

PELÁNEK, Radek, Petr JARUŠEK a Matěj KLUSÁČEK. Modeling Students' Learning and Variability of Performance in Problem Solving. Online. In D’Mello, S. K., Calvo, R. A., and Olney, A. Educational Data Mining. USA: International Educational Data Mining Society, 2013, s. 256-259. ISBN 978-0-9839525-2-7.

PELÁNEK, Radek a Petr JARUŠEK. A Web-Based Problem Solving Tool for Introductory Computer Science. In Proceedings of the 17th ACM annual conference on Innovation and technology in computer science education. New York. USA: ACM, 2012, s. 371-371. ISBN 978-1-4503-1246-2.

PELÁNEK, Radek a Petr JARUŠEK. Analysis of a simple model of problem solving times. In Springer. Proceeding ITS'12 Proceedings of the 11th international conference on Intelligent Tutoring Systems. Heidelberg: Springer Berlin / Heidelberg, 2012, s. 379-388. ISBN 978-3-642-30949-6. Dostupné z: https://dx.doi.org/10.1007/978-3-642-30950-2_49.

PELÁNEK, Radek a Petr JARUŠEK. Modeling and Predicting Students Problem Solving Times. In Proceedings of the 38th International Conference on Current Trends in Theory and Practice of Computer Science. Czech republic: Springer, 2012, s. 637-648. ISBN 978-3-642-27659-0. Dostupné z: https://dx.doi.org/10.1007/978-3-642-27660-6_52.

PELÁNEK, Radek. Modelování a simulace komplexních systémů. Jak lépe porozumět světu. 1. vyd. Brno: Masarykova univerzita, 2012, 236 s. e-book. ISBN 978-80-210-5807-1.

PELÁNEK, Radek. Programátorská cvičebnice: algoritmy v příkladech. Brno: Computer Press, 2012, 175 s. ISBN 978-80-251-3751-2.

PELÁNEK, Radek. Difficulty Rating of Sudoku Puzzles by a Computational Model. In Philip M. McCarthy, R. Charles Murray. Twenty-Fourth International Florida Artificial Intelligence Research Society Conference. USA: Association for the Advancement of Artificial Intelligence (AAAI), 2011, s. 434-439. ISBN 978-1-57735-501-4.

PELÁNEK, Radek. Modelování a simulace komplexních systémů. Jak lépe porozumět světu. 1. vyd. Brno: Masarykova univerzita, 2011, 236 s. mimo edice. ISBN 978-80-210-5318-2.

PELÁNEK, Radek a Petr JARUŠEK. Problem Response Theory and its Application for Tutoring. In Proceedings of the 4th International Conference on Educational Data Mining. Eindhoven: International Conference on Educational Data Mining 2011, 2011, s. 374-375. ISBN 978-90-386-2537-9.

JARUŠEK, Petr a Radek PELÁNEK. Problem Solving Tutor. 2011.

PELÁNEK, Radek a Petr JARUŠEK. What Determines Difficulty of Transport Puzzles? In Philip M. McCarthy, R. Charles Murray. Twenty-Fourth International Florida Artificial Intelligence Research Society Conference. USA: Association for the Advancement of Artificial Intelligence (AAAI), 2011, s. 428-433. ISBN 978-1-57735-501-4.

JARUŠEK, Petr a Radek PELÁNEK. Analýza obtížnosti logických úloh na základě modelů lidského chování. In Kognice a umělý život X. Neuveden: Slezská univerzita v Opavě, 2010, s. 171-176. ISBN 978-80-7248-589-5.

JARUŠEK, Petr a Radek PELÁNEK. Difficulty Rating of Sokoban Puzzle. In STAIRS 2010, Proceedings of the Fifth Starting AI Researchers' Symposium. Lisbon, Portugal: IOS Press BV, 2010, s. 140-146, 6 s. ISBN 978-1-60750-675-1.

PELÁNEK, Radek a Václav ROSECKÝ. EMMA: Explicit Model Checking Manager (Tool Presentation). In Model Checking Software. Německo: Springer, 2009, s. 169-173. ISBN 978-3-642-02651-5. Dostupné z: https://dx.doi.org/10.1007/978-3-642-02652-2_15.

PELÁNEK, Radek, Václav ROSECKÝ a Pavel MORAVEC. Complementarity of Error Detection Techniques. In Parallel and Distributed Methods in verifiCation (PDMC 2008). Nizozemsko: Elsevier, 2008, 14 s. ISSN 1571-0661.

ŠIMEČEK, Pavel a Radek PELÁNEK. Estimating State Space Parameters. In 7th International Workshop on Parallel and Distributed Methods in verifiCation. 2008.

PELÁNEK, Radek. Fighting State Space Explosion: Review and Evaluation. In Formal Methods for Industrial Critical Systems. Německo: Springer, 2008, 15 s. ISBN 3-642-03239-7.

PELÁNEK, Radek. Model Classifications and Automated Verification. In Formal Methods for Industrial Critical Systems. Německo: Springer, 2008, s. 149-163. ISBN 978-3-540-79706-7.

PELÁNEK, Radek. Properties of State Spaces and Their Applications. International Journal on Software Tools for Technology Transfer (STTT). Springer-Verlag GmbH, 2008, roč. 10, č. 5, s. 443-454. ISSN 1433-2779.

PELÁNEK, Radek. BEEM: Benchmarks for Explicit Model Checkers. In Model Checking Software. Německo: Springer, 2007, s. 263-267. ISBN 3-540-73369-8.

PELÁNEK, Radek, Corina PASAREANU a Willem VISSER. Predicate Abstraction with Under-Approximation Refinement. Logical Methods in Computer Science. Germany: Technical University of Braunschweig, 2007, roč. 3, č. 1, s. 1-22. ISSN 1860-5974.

PELÁNEK, Radek, Kim G. LARSEN, Gerd BEHRMANN a Patricia BOUYER. Lower and Upper Bounds in Zone-Based Abstractions of Timed Automata. International Journal on Software Tools for Technology Transfer (STTT). Springer-Verlag GmbH, 2006, roč. 8, č. 3, s. 204-215. ISSN 1433-2779.

PELÁNEK, Radek. Reduction and Abstraction Techniques for Model Checking. Brno: Masarykova univerzita, 2006, 160 s.

PELÁNEK, Radek, Corina PASAREANU a Willem VISSER. Test Input Generation for Java Containers using State Matching. In International Symposium on International Symposium on Software Testing and Analysis. USA: ACM, 2006, s. 37--48, 11 s. ISBN 1-59593-263-1.

PELÁNEK, Radek, Corina PASAREANU a Willem VISSER. Concrete Search with Abstract Matching and Refinement. In Computer Aided Verification. Edinburgh: Springer, 2005, s. 52-66. ISBN 3-540-27231-3.

PELÁNEK, Radek a Jan STREJČEK. Deeper Connections between LTL and Alternating Automata. In Implementation and Application of Automata. Berlin, Heidelberg: Springer-Verlag, 2005, s. 238-249. ISBN 978-3-540-31023-5.

PELÁNEK, Radek, Tomáš HANŽL, Ivana ČERNÁ a Luboš BRIM. Enhancing Random Walk State Space Exploration. In Formal Methods for Industrial Critical Systems. Lisbon: ACM SIGSOFT, 2005, s. 98-105. ISBN 1-59593-148-1.

PELÁNEK, Radek a Pavel KRČÁL. On Sampled Semantics of Timed Systems. In Foundations of Software Technology and Theoretical Computer Science. India: Springer, 2005, s. 310-321. ISBN 978-3-540-30495-1.

PELÁNEK, Radek, Corina PASAREANU a Willem VISSER. Test input generation for red-black trees using abstraction. In Automated Software Engineering. USA: ACM, 2005, s. 414-417.

PELÁNEK, Radek, Kim G. LARSEN, Gerd BEHRMANN a Patricia BOUYER. Lower and Upper Bounds in Zone Based Abstractions of Timed Automata. In Tools and Algorithms for Construction and Analysis of Systems (TACAS 2004). Barcelona (Španělsko): Springer-Verlag, 2004, s. 312-326. ISBN 3-540-21299-X.

PELÁNEK, Radek. Typical Structural Properties of State Spaces. In SPIN Workshop 2004. Barcelona (Španělsko): Springer-Verlag, 2004, s. 5-22, 15 s. ISBN 3-540-21314-7.

ČERNÁ, Ivana a Radek PELÁNEK. Distributed Explicit Fair Cycle Detection. In SPIN Workshop 2003. Portland (Oregon, USA): Springer-Verlag, 2003, s. 49-74, 25 s. ISBN 3-540-40117-2.

PELÁNEK, Radek. LTL Hierarchies and Model Checking. In Proceedings of the Eight ESSLLI Student Session. Wien: TU Wien, 2003, s. 245-254, 9 s.

ČERNÁ, Ivana a Radek PELÁNEK. Relating Hierarchy of Temporal Properties to Model Checking. In Mathematical Foundations of Computer Science (MFCS 2003). Bratislava (Slovensko): Springer-Verlag, 2003, s. 318-327. ISBN 3-540-40671-9.

BEHRMANN, Gerd, Kim G. LARSEN a Radek PELÁNEK. To Store or Not To Store. In Computer Aided Verification (CAV 2003). Boulder (Colorado, USA): Springer-Verlag, 2003, s. 433-445. ISBN 3-540-40524-0.

BRIM, Luboš, Ivana ČERNÁ, Pavel KRČÁL a Radek PELÁNEK. Distributed LTL Model-Checking Based on Negative Cycle Detection. In FST-TCS 2001. Bangalore, India: Springer, 2001, s. 96-110. LNCS 2245. ISBN 3-540-43002-4.

BRIM, Luboš, Ivana ČERNÁ, Pavel KRČÁL a Radek PELÁNEK. How to Employ Reverse Search in Distributed Single-Source Shortest Paths. How to Employ Reverse Search in Distributed Single-Source Shortest Paths. In SOFSEM 2001. Piestany: Springer, 2001, s. 191-200. LNCS 2234. ISBN 3-540-42912-3.