Developing and Running a Set of Competitive College/University Blended Courses

Alexander S. Belenky ()
Additional contact information
Alexander S. Belenky: The National Research University Higher School of Economics

A chapter in Data Analysis and Optimization, 2023, pp 23-45 from Springer

Abstract: Abstract A mathematical model underlying a decision support tool letting a college/university administration (a) find a financially optimal composition of teachers to design and run blended courses for its students using fragments of recorded lectures of distinguished professors from world-leading universities, and (b) be competitive in the education market of potential students by offering such designed blended courses, along with corresponding explanations and tutorials, in a new learning environment at affordable tuition fees, is proposed. This model, reflecting the college/university expenses associated with running each such blended course, lets its administration calculate (a) the maximal percentage of the students expected to succeed in studying each course from a set of these courses under a fixed budget, and (b) the minimal budget to secure desirable percentages of the students expected to succeed in studying particular blended courses from this set. The calculation can be done by formulating two Boolean programming problems on the basis of the proposed model and solving them using standard software packages.

Keywords: Blended learning; Integer programming problems; Mathematical models; Percentages of the students expected to succeed; Strategies of designing and running Blended courses - university competitiveness in the market of potential students (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-3-031-31654-8_2

Ordering information: This item can be ordered from
http://www.springer.com/9783031316548

DOI: 10.1007/978-3-031-31654-8_2

Access Statistics for this chapter

More chapters in Springer Optimization and Its Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().