Intelligent Decision Support System for guiding Students in Field Selection

Document Type : Research Paper

Abstract

The multiplicity of factors influencing success in field of study selection makes accurate decision-making in this regard challenging. Although counselors are available to assist students in this important process, they too are limited by human cognitive constraints (processing and storage capacities) and are unable to simultaneously and proportionately consider all factors affecting field selection. Therefore, there is a need for a system that can account for all aspects and factors in students’ academic guidance programs and reduce the decline in educational quality. Given researchers’ emphasis on the necessity of using intelligent systems in the academic guidance process and the capability of such systems to enhance the efficiency of guidance, this study designed a decision support system based on a comprehensive set of criteria influencing field selection to assist counselors and students. These criteria fall into three main categories: family-related factors, student-related individual factors, and educational and academic criteria. To this end, after collecting data from twelfth-grade students via a questionnaire, data analysis was conducted using RapidMiner software, and a decision tree was applied to extract the best rules for selecting each field of study. Additionally, the system can predict student performance based on various rules. To evaluate the accuracy and precision of the decision tree across all fields, the system achieved a correct prediction rate for 95% of test data, classifying it as highly efficient and accurate. This system can be utilized in schools to support counselors in providing guidance to students. Besides identifying the best choice for each student, the system also offers the capability to predict student performance in alternative fields.

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References

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History

  • Receive Date: 12 October 2023
  • Revise Date: 07 January 2024
  • Accept Date: 13 November 2023

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