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ORCIDJirí Rihák
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2010 – 2019
- 2018
[j2]Radek Pelánek
, Jirí Rihák:
Analysis and design of mastery learning criteria. New Rev. Hypermedia Multim. 24(3): 133-159 (2018)- 2017
- [j1]Radek Pelánek, Jan Papousek, Jirí Rihák, Vít Stanislav, Juraj Niznan:
Elo-based learner modeling for the adaptive practice of facts. User Model. User Adapt. Interact. 27(1): 89-118 (2017) - [c10]Jirí Rihák, Radek Pelánek:
Measuring Similarity of Educational Items Using Data on Learners' Performance. EDM 2017 - [c9]Radek Pelánek, Jirí Rihák:
Experimental Analysis of Mastery Learning Criteria. UMAP 2017: 156-163 - 2016
- [c8]Radek Pelánek, Jirí Rihák:
Properties and Applications of Wrong Answers in Online Educational Systems. EDM 2016: 466-471 - [c7]Radek Pelánek, Jirí Rihák, Jan Papousek:
Impact of data collection on interpretation and evaluation of student models. LAK 2016: 40-47 - 2015
- [c6]Juraj Niznan, Radek Pelánek, Jirí Rihák:
Student Models for Prior Knowledge Estimation. EDM 2015: 109-116 - [c5]Jan Papousek, Radek Pelánek, Jirí Rihák, Vít Stanislav:
An Analysis of Response Times in Adaptive Practice of Geography Facts. EDM 2015: 562-563 - [c4]Jirí Rihák:
Use of Time Information in Models behind Adaptive Practice System for Building Fluency in Mathematics. EDM 2015: 642-644 - 2014
- [c3]Juraj Niznan, Radek Pelánek, Jirí Rihák:
Using Problem Solving Times and Expert Opinion to Detect Skills. EDM 2014: 433-434 - [c2]Juraj Niznan, Radek Pelánek, Jirí Rihák:
Mapping Problems to Skills Combining Expert Opinion and Student Data. MEMICS 2014: 113-124 - 2013
- [c1]Petr Boros, Juraj Niznan, Radek Pelánek, Jirí Rihák:
Automatic Detection of Concepts from Problem Solving Times. AIED 2013: 595-598
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