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Radek Pelánek
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2020 – today
- 2024
- [j21]Radek Pelánek
:
Leveraging response times in learning environments: opportunities and challenges. User Model. User Adapt. Interact. 34(3): 729-752 (2024) - [j20]Radek Pelánek
Personalized recommendations for learning activities in online environments: a modular rule-based approach. User Model. User Adapt. Interact. 34(4): 1399-1430 (2024) - [c64]Anna Rechtácková
Catalog of Code Quality Defects in Introductory Programming. ITiCSE (1) 2024 - 2023
- [j19]Radek Pelánek
The Landscape of Computational Thinking Problems for Practice and Assessment. ACM Trans. Comput. Educ. 23(2): 22:1-22:29 (2023) - 2022
- [j18]Radek Pelánek
Adaptive, Intelligent, and Personalized: Navigating the Terminological Maze Behind Educational Technology. Int. J. Artif. Intell. Educ. 32(1): 151-173 (2022) - [j17]Radek Pelánek
Complexity and Difficulty of Items in Learning Systems. Int. J. Artif. Intell. Educ. 32(1): 196-232 (2022) - [j16]Radek Pelánek
Design and analysis of microworlds and puzzles for block-based programming. Comput. Sci. Educ. 32(1): 66-104 (2022) - [j15]Radek Pelánek
Improving Learning Environments: Avoiding Stupidity Perspective. IEEE Trans. Learn. Technol. 15(1): 64-77 (2022) - [c63]Tomás Effenberger, Radek Pelánek:
Code Quality Defects across Introductory Programming Topics. SIGCSE (1) 2022: 941-947 - 2021
- [j14]Radek Pelánek
Analyzing and Visualizing Learning Data: A System Designer's Perspective. J. Learn. Anal. 8(2): 93-104 (2021) - [c62]Tomás Effenberger, Radek Pelánek:
Interpretable Clustering of Students' Solutions in Introductory Programming. AIED (1) 2021: 101-112 - [c61]Jaroslav Cechák
Better Model, Worse Predictions: The Dangers in Student Model Comparisons. AIED (1) 2021: 500-511 - [c60]Jaroslav Cechák, Radek Pelánek:
Experimental Evaluation of Similarity Measures for Educational Items. EDM 2021 - [c59]Tomás Effenberger, Radek Pelánek:
Validity and Reliability of Student Models for Problem-Solving Activities. LAK 2021: 1-11 - 2020
- [j13]Radek Pelánek
Measuring Similarity of Educational Items: An Overview. IEEE Trans. Learn. Technol. 13(2): 354-366 (2020) - [j12]Radek Pelánek
A Classification Framework for Practice Exercises in Adaptive Learning Systems. IEEE Trans. Learn. Technol. 13(4): 734-747 (2020) - [j11]Radek Pelánek, Tomás Effenberger:
Beyond binary correctness: Classification of students' answers in learning systems. User Model. User Adapt. Interact. 30(5): 867-893 (2020) - [c58]Tomás Effenberger, Radek Pelánek:
Impact of Methodological Choices on the Evaluation of Student Models. AIED (1) 2020: 153-164 - [c57]Tomás Effenberger, Radek Pelánek, Jaroslav Cechák:
Exploration of the robustness and generalizability of the additive factors model. LAK 2020: 472-479 - [c56]Radek Pelánek:
Learning analytics challenges: trade-offs, methodology, scalability. LAK 2020: 554-558
2010 – 2019
- 2019
- [c55]Jaroslav Cechák, Radek Pelánek:
Item Ordering Biases in Educational Data. AIED (1) 2019: 48-58 - [c54]Tomás Effenberger, Radek Pelánek:
Measuring Students' Performance on Programming Tasks. L@S 2019: 26:1-26:4 - [c53]Tomás Effenberger, Jaroslav Cechák, Radek Pelánek:
Measuring Difficulty of Introductory Programming Tasks. L@S 2019: 28:1-28:4 - 2018
- [j10]Radek Pelánek
Analysis and design of mastery learning criteria. New Rev. Hypermedia Multim. 24(3): 133-159 (2018) - [j9]Radek Pelánek
The details matter: methodological nuances in the evaluation of student models. User Model. User Adapt. Interact. 28(3): 207-235 (2018) - [c52]Radek Pelánek:
Conceptual Issues in Mastery Criteria: Differentiating Uncertainty and Degrees of Knowledge. AIED (1) 2018: 450-461 - [c51]Tomás Effenberger, Radek Pelánek:
Towards making block-based programming activities adaptive. L@S 2018: 13:1-13:4 - [c50]Radek Pelánek:
Exploring the utility of response times and wrong answers for adaptive learning. L@S 2018: 18:1-18:4 - [c49]Radek Pelánek, Tomás Effenberger, Matej Vanek, Vojtech Sassmann, Dominik Gmiterko:
Measuring item similarity in introductory programming. L@S 2018: 19:1-19:4 - [i3]Radek Pelánek, Tomás Effenberger, Matej Vanek, Vojtech Sassmann, Dominik Gmiterko:
Measuring Item Similarity in Introductory Programming: Python and Robot Programming Case Studies. CoRR abs/1806.03240 (2018) - 2017
- [j8]Radek Pelánek
Elo-based learner modeling for the adaptive practice of facts. User Model. User Adapt. Interact. 27(1): 89-118 (2017) - [j7]Radek Pelánek
Bayesian knowledge tracing, logistic models, and beyond: an overview of learner modeling techniques. User Model. User Adapt. Interact. 27(3-5): 313-350 (2017) - [c48]Jirí Rihák, Radek Pelánek:
Measuring Similarity of Educational Items Using Data on Learners' Performance. EDM 2017 - [c47]Radek Pelánek, Jirí Rihák:
Experimental Analysis of Mastery Learning Criteria. UMAP 2017: 156-163 - [c46]Radek Pelánek
Measuring Predictive Performance of User Models: The Details Matter. UMAP (Adjunct Publication) 2017: 197-201 - [c45]Jan Papousek, Radek Pelánek
Should We Give Learners Control Over Item Difficulty? UMAP (Adjunct Publication) 2017: 299-303 - [c44]Jan Papousek, Radek Pelánek
Evaluation of Learners' Adjustment of Question Difficulty in Adaptive Practice of Facts. UMAP 2017: 379-380 - 2016
- [j6]Radek Pelánek
Applications of the Elo rating system in adaptive educational systems. Comput. Educ. 98: 169-179 (2016) - [j5]Jan Papousek, Radek Pelánek, Vít Stanislav:
Adaptive Geography Practice Data Set. J. Learn. Anal. 3(2): 317-321 (2016) - [c43]Radek Pelánek, Jirí Rihák:
Properties and Applications of Wrong Answers in Online Educational Systems. EDM 2016: 466-471 - [c42]Jan Papousek, Vít Stanislav, Radek Pelánek
Impact of Question Difficulty on Engagement and Learning. ITS 2016: 267-272 - [c41]Radek Pelánek
Impact of data collection on interpretation and evaluation of student models. LAK 2016: 40-47 - [c40]Jan Papousek, Vít Stanislav, Radek Pelánek
Evaluation of an adaptive practice system for learning geography facts. LAK 2016: 134-142 - 2015
- [j4]Radek Pelánek
Student Modeling Based on Problem Solving Times. Int. J. Artif. Intell. Educ. 25(4): 493-519 (2015) - [c39]Juraj Niznan, Jan Papousek, Radek Pelánek:
Exploring the Role of Small Differences in Predictive Accuracy using Simulated Data. AIED Workshops 2015 - [c38]Jan Papousek, Radek Pelánek
Impact of Adaptive Educational System Behaviour on Student Motivation. AIED 2015: 348-357 - [c37]Radek Pelánek:
Metrics for Evaluation of Student Models. EDM 2015: 19 - [c36]Juraj Niznan, Radek Pelánek, Jirí Rihák:
Student Models for Prior Knowledge Estimation. EDM 2015: 109-116 - [c35]Radek Pelánek:
Modeling Students' Memory for Application in Adaptive Educational Systems. EDM 2015: 480-483 - [c34]Radek Pelánek:
Modeling Student Learning: Binary or Continuous Skill? EDM 2015: 560-561 - [c33]Jan Papousek, Radek Pelánek, Jirí Rihák, Vít Stanislav:
An Analysis of Response Times in Adaptive Practice of Geography Facts. EDM 2015: 562-563 - 2014
- [c32]Jan Papousek, Radek Pelánek, Vít Stanislav:
Adaptive Practice of Facts in Domains with Varied Prior Knowledge. EDM 2014: 6-13 - [c31]Juraj Niznan, Radek Pelánek, Jirí Rihák:
Using Problem Solving Times and Expert Opinion to Detect Skills. EDM 2014: 433-434 - [c30]Radek Pelánek:
A Brief Overview of Metrics for Evaluation of Student Models. EDM (Workshops) 2014 - [c29]Radek Pelánek:
Application of Time Decay Functions and the Elo System in Student Modeling. EDM 2014: 21-27 - [c28]Juraj Niznan, Radek Pelánek
Mapping Problems to Skills Combining Expert Opinion and Student Data. MEMICS 2014: 113-124 - [i2]Radek Pelánek:
Difficulty Rating of Sudoku Puzzles: An Overview and Evaluation. CoRR abs/1403.7373 (2014) - 2013
- [c27]Petr Boros, Juraj Niznan, Radek Pelánek, Jirí Rihák:
Automatic Detection of Concepts from Problem Solving Times. AIED 2013: 595-598 - [c26]Radek Pelánek, Petr Jarusek, Matej Klusácek:
Modeling Students' Learning and Variability of Performance in Problem Solving. EDM 2013: 256-259 - 2012
- [c25]Petr Jarusek, Radek Pelánek
A web-based problem solving tool for introductory computer science. ITiCSE 2012: 371 - [c24]Petr Jarusek, Radek Pelánek
Analysis of a Simple Model of Problem Solving Times. ITS 2012: 379-388 - [c23]Petr Jarusek, Radek Pelánek
Modeling and Predicting Students Problem Solving Times. SOFSEM 2012: 637-648 - 2011
- [c22]Petr Jarusek, Radek Pelánek:
Problem Response Theory and its Application for Tutoring. EDM 2011: 371-372 - [c21]Petr Jarusek, Radek Pelánek:
What Determines Difficulty of Transport Puzzles? FLAIRS 2011 - [c20]Radek Pelánek:
Difficulty Rating of Sudoku Puzzles by a Computational Model. FLAIRS 2011 - 2010
- [c19]Petr Jarusek, Radek Pelánek
Difficulty Rating of Sokoban Puzzle. STAIRS 2010: 140-150
2000 – 2009
- 2009
- [c18]Radek Pelánek
EMMA: Explicit Model Checking Manager (Tool Presentation). SPIN 2009: 169-173 - 2008
- [j3]Radek Pelánek
Properties of state spaces and their applications. Int. J. Softw. Tools Technol. Transf. 10(5): 443-454 (2008) - [c17]Radek Pelánek
Fighting State Space Explosion: Review and Evaluation. FMICS 2008: 37-52 - [c16]Radek Pelánek
Complementarity of Error Detection Techniques. PDMC@ETAPS 2008: 51-65 - 2007
- [j2]Corina S. Pasareanu, Radek Pelánek
Predicate Abstraction with Under-Approximation Refinement. Log. Methods Comput. Sci. 3(1) (2007) - [c15]Radek Pelánek
Model Classifications and Automated Verification. FMICS 2007: 149-163 - [c14]Radek Pelánek:
BEEM: Benchmarks for Explicit Model Checkers. SPIN 2007: 263-267 - [i1]Corina S. Pasareanu, Radek Pelánek, Willem Visser:
Predicate Abstraction with Under-approximation Refinement. CoRR abs/cs/0701140 (2007) - 2006
- [j1]Gerd Behrmann, Patricia Bouyer, Kim Guldstrand Larsen, Radek Pelánek
Lower and upper bounds in zone-based abstractions of timed automata. Int. J. Softw. Tools Technol. Transf. 8(3): 204-215 (2006) - [c13]Willem Visser, Corina S. Pasareanu, Radek Pelánek:
Test input generation for java containers using state matching. ISSTA 2006: 37-48 - 2005
- [c12]Corina S. Pasareanu, Radek Pelánek, Willem Visser:
Concrete Model Checking with Abstract Matching and Refinement. CAV 2005: 52-66 - [c11]Radek Pelánek, Tomás Hanzl, Ivana Cerná, Lubos Brim:
Enhancing random walk state space exploration. FMICS 2005: 98-105 - [c10]Pavel Krcál, Radek Pelánek:
On Sampled Semantics of Timed Systems. FSTTCS 2005: 310-321 - [c9]Willem Visser, Corina S. Pasareanu, Radek Pelánek
Test input generation for red-black trees using abstraction. ASE 2005: 414-417 - [c8]Radek Pelánek, Jan Strejcek:
Deeper Connections Between LTL and Alternating Automata. CIAA 2005: 238-249 - 2004
- [c7]Radek Pelánek:
Typical Structural Properties of State Spaces. SPIN 2004: 5-22 - [c6]Gerd Behrmann, Patricia Bouyer, Kim Guldstrand Larsen, Radek Pelánek:
Lower and Upper Bounds in Zone Based Abstractions of Timed Automata. TACAS 2004: 312-326 - 2003
- [c5]Gerd Behrmann, Kim Guldstrand Larsen, Radek Pelánek:
To Store or Not to Store. CAV 2003: 433-445 - [c4]Ivana Cerná, Radek Pelánek:
Relating Hierarchy of Temporal Properties to Model Checking. MFCS 2003: 318-327 - [c3]Ivana Cerná, Radek Pelánek:
Distributed Explicit Fair Cycle Detection (Set Based Approach). SPIN 2003: 49-73 - 2001
- [c2]Lubos Brim, Ivana Cerná, Pavel Krcál, Radek Pelánek:
Distributed LTL Model Checking Based on Negative Cycle Detection. FSTTCS 2001: 96-107 - [c1]Lubos Brim, Ivana Cerná, Pavel Krcál, Radek Pelánek:
How to Employ Reverse Search in Distributed Single Source Shortest Paths. SOFSEM 2001: 191-200
Coauthor Index
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last updated on 2024-12-10 21:49 CET by the dblp team
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