99. Learning Path Optimization by P-graph Algorithms for Curriculum Development in Higher Education
Invited abstract in session WF-4: P-graph Applications I., stream P-graph algorithms and applications.
Wednesday, 16:45 - 18:15Room: C105
Authors (first author is the speaker)
| 1. | Anikó Zseni
|
| Széchenyi István University | |
| 2. | Botond Bertok
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| Széchenyi István University | |
| 3. | András Horváth
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| Physics and Chemistry, Széchenyi István University | |
| 4. | Zsolt Kovács
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| Széchenyi István University |
Abstract
The rapidly changing environment and the expectations set by new generations necessitate frequent revision of the curriculum in higher education. Curriculum development focuses mainly on organizing learning activities to achieve desired outcomes of educational programs. As a result, the curriculum is a roadmap from previously available competencies to the achieved target competency levels, through a series of activities that support the path. Thus, a verifiable systematic method is needed for sustainable development. In the paper all the above aspects are to be addressed by the Process Network Synthesis.
Process Network Synthesis or PNS aims at achieving all the specified desired targets by a combination of potential activities while utilizing a selection of the available resources. The P-graph framework was introduced for PNS by Friedler et al. in the early 90’s. The framework involves mathematical formulation, graphical representation, and a set of combinatorial algorithms for generating the best, N-best, or all the feasible process networks for a PNS problem.
Desired competences at the end of the educational program are modeled as process targets; initially available competences, credits as resources; and each courses as a potential activity. Personal preferences and learning strategies leading to different learning paths are generated by P-graph algorithms. The results help the validation of alternative curriculum development plans.
Keywords
- Optimization for learning and data analysis
- Data driven optimization
- Optimization in industry, business and finance
Status: accepted
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