Abstract
In the study the authors show how visualization and analysis of education data could be used in simulation and adjustment of education program curriculum for future evaluation of the formation levels the graduates competences as specified by educational standard. The authors suggest the scenario that demonstrate the possibility of automatic evaluation of graduate competences formation. This study is a viable teaching tool that can be used to simulation of the pedagogical activity scenario in order to eliminate all kinds of gaps in the training of the graduates and the evaluation of their professional competencies. The approach proposed in the study can be used to build a more result-oriented educational program by its redesigning to eliminate identified gaps in the consideration of important learning outcomes (the formation level of graduates’ professional competencies) and evaluate the educational program using an updated visual model of evaluation activity. The relevance of this work is also based on its contribution to expanding the capabilities of multidimensional analysis and visualization of the results in relation to solving professional educational tasks.
Keywords
Visualization of data analysis Big Data in education information visualization and data analysis graduate pro-fessional competencies qualification units qualification model of specialist competence based content of the educational program
References
- Adejo, O., & Connolly, T. (2017). Learning Analytics in Higher Education Development: A Roadmap. Journal of Education and Practice, 8(15), 156-163.
- Agasisti, T., & Bowers, A. J. (2017). Data Analytics and Decision-Making in Education: Towards the Educational Data Scientist as a Key Actor in Schools and Higher Education Institutions. Handbook of Contemporary Education Economics, 184-210. https://doi.org/10.7916/D8PR95T2
- Blazar,D.,&Kraft,M.A.(2017).Teacherandteachingeffectsonstudents’attitudesandbehaviors.Educational evaluation and policy analysis, 39(1), 146-170. https://doi.org/10.3102/0162373716670260
Abstract
References
- Adejo, O., & Connolly, T. (2017). Learning Analytics in Higher Education Development: A Roadmap. Journal of Education and Practice, 8(15), 156-163.
- Agasisti, T., & Bowers, A. J. (2017). Data Analytics and Decision-Making in Education: Towards the Educational Data Scientist as a Key Actor in Schools and Higher Education Institutions. Handbook of Contemporary Education Economics, 184-210. https://doi.org/10.7916/D8PR95T2
- Blazar,D.,&Kraft,M.A.(2017).Teacherandteachingeffectsonstudents’attitudesandbehaviors.Educational evaluation and policy analysis, 39(1), 146-170. https://doi.org/10.3102/0162373716670260
Details
| Primary Language | English |
|---|---|
| Journal Section | Articles |
| Authors | |
| Publication Date | October 1, 2021 |
| Submission Date | November 14, 2020 |
| Published in Issue | Year 2021 Volume: 22 Issue: 4 |