Abstract
In this paper we discuss the relevance of students' computer-based testing, as well as the currently existing approaches for the control of learning and training within the scope of blended learning. Construction of mixed diagnostic tests, representing a compromise between unconditional and conditional components, in order to develop students' knowledge monitoring in electrical engineering is proposed. The authors suggest a technique for optimal mixed diagnostic tests construction based on the expert knowledge of the subjects. Decision-making is carried out by means of fuzzy logic, threshold function and cognitive graphic tools. One of the useful outcomes of mixed diagnostic tests is the courses learning curve design for each individual student. The developed approach is applied for the "Power Electronics" discipline to construct students' learning trajectory and define their further ways of personal development in the field of electrical engineering.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 35th IASTED International Conference on Modelling, Identification and Control, MIC 2016 |
| Publisher | ACTA Press |
| Pages | 59-65 |
| Number of pages | 7 |
| Volume | 830 |
| ISBN (Electronic) | 9780889869790 |
| DOIs | |
| Publication status | Published - 1 Jan 2016 |
| Event | 35th IASTED International Conference on Modelling, Identification and Control, MIC 2016 - Innsbruck, Austria Duration: 15 Feb 2016 → 16 Feb 2016 |
Conference
| Conference | 35th IASTED International Conference on Modelling, Identification and Control, MIC 2016 |
|---|---|
| Country | Austria |
| City | Innsbruck |
| Period | 15.2.16 → 16.2.16 |
Fingerprint
Keywords
- Assessment
- Blended learning
- Cognitive graphic tool
- Fuzzy logic
- Learning and testing intelligent system
- Learning trajectory
- Mixed diagnostic tests
- Pattern recognition
- Quality control
- Simplex
ASJC Scopus subject areas
- Software
- Modelling and Simulation
- Computer Science Applications
Cite this
Design of individual learning trajectory based on mixed diagnostic tests and cognitive graphic tools. / Yankovskaya, Anna; Dementyev, Yury; Lyapunov, Danil; Yamshanov, Artem.
Proceedings of the 35th IASTED International Conference on Modelling, Identification and Control, MIC 2016. Vol. 830 ACTA Press, 2016. p. 59-65.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Design of individual learning trajectory based on mixed diagnostic tests and cognitive graphic tools
AU - Yankovskaya, Anna
AU - Dementyev, Yury
AU - Lyapunov, Danil
AU - Yamshanov, Artem
PY - 2016/1/1
Y1 - 2016/1/1
N2 - In this paper we discuss the relevance of students' computer-based testing, as well as the currently existing approaches for the control of learning and training within the scope of blended learning. Construction of mixed diagnostic tests, representing a compromise between unconditional and conditional components, in order to develop students' knowledge monitoring in electrical engineering is proposed. The authors suggest a technique for optimal mixed diagnostic tests construction based on the expert knowledge of the subjects. Decision-making is carried out by means of fuzzy logic, threshold function and cognitive graphic tools. One of the useful outcomes of mixed diagnostic tests is the courses learning curve design for each individual student. The developed approach is applied for the "Power Electronics" discipline to construct students' learning trajectory and define their further ways of personal development in the field of electrical engineering.
AB - In this paper we discuss the relevance of students' computer-based testing, as well as the currently existing approaches for the control of learning and training within the scope of blended learning. Construction of mixed diagnostic tests, representing a compromise between unconditional and conditional components, in order to develop students' knowledge monitoring in electrical engineering is proposed. The authors suggest a technique for optimal mixed diagnostic tests construction based on the expert knowledge of the subjects. Decision-making is carried out by means of fuzzy logic, threshold function and cognitive graphic tools. One of the useful outcomes of mixed diagnostic tests is the courses learning curve design for each individual student. The developed approach is applied for the "Power Electronics" discipline to construct students' learning trajectory and define their further ways of personal development in the field of electrical engineering.
KW - Assessment
KW - Blended learning
KW - Cognitive graphic tool
KW - Fuzzy logic
KW - Learning and testing intelligent system
KW - Learning trajectory
KW - Mixed diagnostic tests
KW - Pattern recognition
KW - Quality control
KW - Simplex
UR - http://www.scopus.com/inward/record.url?scp=85014828031&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85014828031&partnerID=8YFLogxK
U2 - 10.2316/P.2016.830-042
DO - 10.2316/P.2016.830-042
M3 - Conference contribution
VL - 830
SP - 59
EP - 65
BT - Proceedings of the 35th IASTED International Conference on Modelling, Identification and Control, MIC 2016
PB - ACTA Press
ER -