Author
Listed:
- R. Niyazova
- A. Aktayeva
- A. Sharipbay
- A. Kubigenova
- B. Razakhova
Abstract
This article presents a project for developing interactive models of an educational resource for determining the semantic proximity between the ontology of knowledge extracted from a knowledge base based on a given question and the ontology generated from a student's answer in computer science. A general methodology for developing software has been proposed. This methodology will form the basis for the automated creation of smart textbooks on computer science in the Kazakh language using ontological models and thesauri. These educational resource models are suitable for any type of educational process (Blended Learning Technology (BLT), full-time, part-time). For example, the article describes an online smart textbook that will adapt to the student's individual learning path by providing personalized text, audio, and video materials, asking questions, and evaluating answers with an indication of percentage accuracy. A pedagogical experiment has been conducted to assess the students' performance. The online smart textbook will adapt to the student's learning style by providing personalized text, audio, and video materials. It will also ask questions and evaluate answers with an indication of percentage accuracy. In addition, completed assignments were analyzed to assess students' progress using static digital materials and standard computer testing systems for a dynamic, intelligent learning environment and knowledge assessment. The results show that the proposed methodology has great potential for increasing student engagement in studying the formalization and processing of the grammar of the Kazakh language using production rules and, based on them, developing a grammar processor, creating ontologies, thesauri, and knowledge bases on the content of “Computer Science”.
Suggested Citation
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aac:ijirss:v:8:y:2025:i:3:p:2413-2430:id:7020. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Natalie Jean (email available below). General contact details of provider: https://ijirss.com/index.php/ijirss/ .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.