Determining Relative Arithmetic Mean and Upper Bound in Sakarya University Relative Grading System Using Artificial Neural Network
Year: 2007
Type: article
Abstract: Evaluation process is done after measuring results are gathered in relative evaluation system and a criteria is determined. Grades taken from exam, homework, lab, application and such like by students are transmitted preoperation in order to derive success grade. This grade is called unconditional grade. When this point is acquired, firstly every activity grades (quiz, final, homework etc.) is multiply independently percentage value (%90, %20) and these is accumulated. After raw success grade is calculated, these are exchanged to relative points [1]. At this phase, a specific distribution related with trainer is performed to determine an appropriate relative grade distribution. At this paper, in order to define suitable distribution, grade data belonging to previous semester and year is trained by neural network and relative arithmetic mean and it is studied such that upper value determine.
Authors: Arslan, Halil, Canay, Özkan
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: bronze
OpenAlex ID: W4295206040