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A Web Application for Learning Support Vector Machine Algorithms in Computer Engineering

Year: 2025

Type: article

Abstract: In this paper, we present a web application designed for learning and visualizing Support Vector Machine (SVM) algorithms, which are key components in the fields of machine learning and data processing. The application was developed as an interactive tool that allows students and researchers to experiment with SVM models, providing insight into their structure and functionality. By using modern web technologies, the application offers a user environment that is accessible, intuitive, and adaptable for learning and research. In addition to implementing a web tool for learning the SVM algorithm, this study proposes a method for its application in teaching and analyzes the impact of applying the new interactive method on final learning outcomes. To assess the effectiveness of this tool, an experiment was conducted consisting of three phases: pre-testing, training, and post-testing. To evaluate students’ experiences with the applied alternative learning method using the auxiliary tool and their perception of the software system’s effectiveness, the standardized System Usability Scale (SUS) was used.

Source: International Journal of Cognitive Research in Science Engineering and Education

DOI: 10.23947/2334-8496-2025-13-1-175-190

Authors: Nenad Jovanović, Stefan Jovanović, Srećko Stamenković, Dražen Marinković, Negovan Stamenković

Institutions: University of Priština - Kosovska Mitrovica, University of Nis, Toplica Academy of Applied Studies, University of Belgrade, University of Prishtina

Language: English

Topic: Experimental Learning in Engineering

Subfield: Media Technology

Field: Engineering

Domain: Physical Sciences

SDG: Quality education

Open Access status: diamond

OpenAlex ID: W4409908735

FWCI:

Cites: 33

Cited by:

Related to: 10