Filtrování publikací

    2019

    1. ŠAFRÁNEK, David; Matej TROJÁK; Vojtěch BRŮŽA; Tomáš VEJPUSTEK; Jan PAPOUŠEK; Martin DEMKO; Samuel PASTVA; Aleš PEJZNOCH a Luboš BRIM. Barbaric Robustness Monitoring Revisited for STL* in Parasim. In Bortolussi L., Sanguinetti G. Computational Methods in Systems Biology (CMSB 2019). LNBI 11773. Neuveden: Springer, 2019, s. 356-359. ISBN 978-3-030-31303-6. Dostupné z: https://dx.doi.org/10.1007/978-3-030-31304-3_26.

    2017

    1. PAPOUŠKOVÁ, Tereza a Jan PAPOUŠEK. Advokáti před Ústavním soudem: zaručuje jejich zkušenost úspěch? Jurisprudence. Wolters Kluwer a.s., 2017, roč. 26, č. 2, s. 12-24. ISSN 1802-3843.
    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.
    3. 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.
    4. 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.
    5. PAPOUŠKOVÁ, Tereza a Jan PAPOUŠEK. Ústavní soudci v kvantitativní perspektivě. Časopis pro právní vědu a praxi. Brno: Masarykova univerzita, 2017, roč. 25, č. 1, s. 73-92. ISSN 1210-9126.

    2016

    1. 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.
    2. 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.
    3. PAPOUŠEK, Jan; Vít STANISLAV a Radek PELÁNEK. Evaluation of the Impact of Question Difficulty on Engagement and Learning. Brno, 2016, 13 s.
    4. 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.
    5. 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.

    2015

    1. 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.
    2. 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.
    3. 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.

    2014

    1. 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.
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