Career Bot for Career Prediction of Higher Secondary Students using Decision Tree

S. Selvakumar, A. Poongodi
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Abstract

Career guidance refers to a process that assists individuals, typically students in making informed decisions about their career paths. Career guidance can be delivered through various channels, including career counsellors, educational institutions, online platforms, and self-help resources. It plays a vital role in helping individuals make informed choices that align with their aspirations, values, and capabilities. Traditional career prediction models often lack transparency and fail to consider the diverse and dynamic factors that influence students' career choices. The existing systems may exhibit biases and limitations that hinder accurate and personalized career guidance. The project aims to tackle these problems by developing an Explainable ML (XML) model that provides transparent, personalized, and adaptable recommendations to higher secondary students. The proposed system incorporates Decision Tree algorithms within an Explainable ML framework to provide clear and comprehensible insights into the factors influencing career predictions. It takes into account a diverse set of input features, including academic performance, skills, interests, and extracurricular activities, to offer personalized career guidance to individual students. The project also addresses potential biases in the model to ensure fair and equitable career recommendations for students from varied backgrounds. By combining the power of Decision Tree algorithms with Explainable ML, the project aims to empower higher secondary students in making well-informed decisions about their future careers. The transparency provided by the Explainable ML model enhances user trust and understanding, fostering a more engaging and personalized career prediction system. The project's outcomes are expected to contribute significantly to the field of career guidance, providing a model that is not only accurate but also accessible and comprehensible for students navigating the critical phase of choosing their career paths.
利用决策树预测高中生职业生涯的职业生涯机器人
职业指导是指帮助个人(通常是学生)就其职业道路做出明智决定的过程。职业指导可以通过各种渠道进行,包括职业顾问、教育机构、在线平台和自助资源。职业指导在帮助个人做出符合自身愿望、价值观和能力的明智选择方面发挥着至关重要的作用。传统的职业预测模型往往缺乏透明度,未能考虑影响学生职业选择的各种动态因素。现有的系统可能存在偏差和局限性,从而阻碍了准确的个性化职业指导。本项目旨在通过开发一种可解释的 ML(XML)模型来解决这些问题,该模型可为高中学生提供透明、个性化和适应性强的建议。拟议的系统在可解释的 ML 框架内纳入了决策树算法,以便对影响职业预测的因素提供清晰易懂的见解。该系统考虑了各种输入特征,包括学习成绩、技能、兴趣和课外活动,为学生提供个性化的职业指导。该项目还解决了模型中可能存在的偏差,以确保为来自不同背景的学生提供公平公正的职业建议。通过将决策树算法与可解释的 ML 相结合,该项目旨在增强高中学生的能力,使他们能够对自己未来的职业做出明智的决定。可解释的 ML 模型提供的透明度增强了用户的信任和理解,促进了更具吸引力和个性化的职业预测系统。该项目的成果有望为职业指导领域做出重大贡献,为正在选择职业道路这一关键阶段的学生提供一个不仅准确,而且易于使用和理解的模型。
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