| 000 | 03899nla2a2200529 4500 | ||
|---|---|---|---|
| 001 | 656140 | ||
| 005 | 20231030041415.0 | ||
| 035 | _a(RuTPU)RU\TPU\network\22543 | ||
| 090 | _a656140 | ||
| 100 | _a20171026a2017 k y0engy50 ba | ||
| 101 | 0 | _aeng | |
| 105 | _ay z 100zy | ||
| 135 | _adrcn ---uucaa | ||
| 181 | 0 | _ai | |
| 182 | 0 | _ab | |
| 200 | 1 |
_aLearning Outcomes Evaluation Based on Mixed Diagnostic Tests and Cognitive Graphic Tools _fA. E. Yankovskaya [et al.] |
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| 203 |
_aText _celectronic |
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| 225 | 1 | _aEngineering Education | |
| 300 | _aTitle screen | ||
| 320 | _a[References: 19 tit.] | ||
| 330 | _aIn this paper, we discuss the relevance of students’ learning outcomes evaluation using computer-based testing. The learning process is based on mixed diagnostic tests. For the purpose of evaluation, we use the threshold, fuzzy logic and cognitive graphic tools. The construction of mixed diagnostic tests, representing a compromise between unconditional and conditional components, in order to develop students’ knowledge evaluation is proposed for a number of disciplines. We suggest a technique for optimal mixed diagnostic tests construction based on the expert knowledge of the subjects for effective learning. The developed approach is used for a number of both the humanities and technical disciplines. One of useful outcomes of mixed diagnostic tests application is the learning trajectory design for each individual. We construct students’ learning trajectory using the intelligent learning and testing system and suggest defining their inherent approach to the learning process within the problem area. | ||
| 333 | _aРежим доступа: по договору с организацией-держателем ресурса | ||
| 461 | _tAdvances in Intelligent Systems and Computing | ||
| 463 | 0 |
_0(RuTPU)RU\TPU\network\22542 _tVol. 677 : Linguistic and Cultural Studies: Traditions and Innovations, (LKTI 2017) _oXVIIth International Conference, October 11-13, 2017, Tomsk, Russia _o[proceedings] _fNational Research Tomsk Polytechnic University (TPU) ; eds. A. Yu. Filchenko ; Zh. S. Anikina _v[P. 81-90] _d2017 |
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| 610 | 1 | _aэлектронный ресурс | |
| 610 | 1 | _aтруды учёных ТПУ | |
| 610 | 1 | _aтестирование | |
| 610 | 1 | _aссылки | |
| 610 | 1 | _aраспознавание | |
| 610 | 1 | _aдиагностика | |
| 610 | 1 | _aлогика | |
| 610 | 1 | _alearning and testing intelligent system | |
| 610 | 1 | _apattern recognition | |
| 610 | 1 | _amixed diagnostic tests | |
| 610 | 1 | _athreshold logic | |
| 610 | 1 | _afuzzy logic | |
| 610 | 1 | _an-simplex | |
| 610 | 1 | _acognitivegraphic tool | |
| 610 | 1 | _alearning trajectory | |
| 701 | 1 |
_aYankovskaya _bA. E. _cspecialist in the field of electrical engineering _cProfessor of Tomsk Polytechnic University, doctor of technical Sciences _f1939- _gAnna Efimovna _2stltpush _3(RuTPU)RU\TPU\pers\36250 |
|
| 701 | 1 |
_aDementiev _bYu. N. _cspecialist in the field of electrical engineering _cHead of the Department of Tomsk Polytechnic University, candidate of technical sciences _f1953- _gYuriy Nikolaevich _2stltpush _3(RuTPU)RU\TPU\pers\34134 |
|
| 701 | 1 |
_aLyapunov _bD. Yu. _cspecialist in the field of electrical engineering _cAssociate Professor of Tomsk Polytechnic University, candidate of technical sciences _f1982- _gDanil Yurievich _2stltpush _3(RuTPU)RU\TPU\pers\34175 |
|
| 701 | 1 |
_aYamshanov _bA. _gArtem |
|
| 712 | 0 | 2 |
_aНациональный исследовательский Томский политехнический университет (ТПУ) _bЭнергетический институт (ЭНИН) _bКафедра электропривода и электрооборудования (ЭПЭО) _h178 _2stltpush _3(RuTPU)RU\TPU\col\18674 |
| 801 | 2 |
_aRU _b63413507 _c20171107 _gRCR |
|
| 856 | 4 | _uhttps://doi.org/10.1007/978-3-319-67843-6_11 | |
| 942 | _cCF | ||