Calculation of Knowledge Levels in the Rush Model (Methods, Examples)

Michael Lutsenko and Dzhemil Seytmanbitov ()
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Michael Lutsenko: Emperor Alexander I Petersburg State Transport University
Dzhemil Seytmanbitov: Emperor Alexander I Petersburg State Transport University

A chapter in Digital Technologies in Teaching and Learning Strategies, 2022, pp 29-38 from Springer

Abstract: Abstract An integral part of the learning process is the knowledge control procedure. The results of this procedure are used to assess the level of knowledge acquired and to make important administrative decisions, as well as to decide on changes in teaching methods and forms of knowledge control. Recently, with the development of distance learning systems, pedagogical testing as a knowledge control tool has become widespread. In this paper we consider a method for assessing knowledge levels, which allows you to significantly expand the set of their possible values. A probabilistic interpretation of the difference of possible values of knowledge levels is shown. The calculation of knowledge levels is carried out by solving a non-linear uncertain system with a large number of equations and variables by available means. The mathematical apparatus was tested on the Unified State Exam in Mathematics, held in St. Petersburg. Difficulties of tasks and levels of knowledge in the logits are calculated. The distribution of the input stream of test takers by level of knowledge is given. The found values of latent parameters (proposed parameter calculation methodology) can be used: for modelling the testing procedure, predicting the learnability of test takers, calculating the accuracy and reliability of the decisions made.

Keywords: Testing; Rush model; Level of knowledge; Level of difficulty (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnichp:978-3-031-05175-3_3

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DOI: 10.1007/978-3-031-05175-3_3

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