Analyzing and Predicting Learner Sentiment Toward Specialty Schools Using Machine Learning Techniques

Introduction

Specialty schools differ from regular schools in that they provide more in-depth coverage of the disciplines in which they concentrate (Prieto et al., 2019). Secondary schools with expanded coverage of particular topics that make up the school's specialty are known as specialized schools (Walls & Kemper, 2018). They should not be confused with vocational schools, which aim to provide skills for a specific career. Learning should be promoted early and regularly, and specialized technical or vocational skills are important to labor market success, according to international consensus (Akhter et al., 2021; World Bank Group, 2011). Specialized schools were established in England to enhance choice and encourage diversity, and they are a popular choice for parents due to their specialist status (West & Noden, 2000). Indeed, specialty schools now account for 88 percent of state-funded secondary schools in England (DfES, 2005; Prieto et al., 2019).

Students' self-expression in activities that are relevant to them is facilitated by the diversified approach to the creation of the contingent of specialist schools (Lazarev, 1992). The area of specialty schools give education in the labor process, as well as in the interaction between students and scientists that is developed via academics and extracurricular activities, as well as during periods of individual and group initiatives. Many nations have begun educational reforms in recent decades with the goal of increasing educational access, promoting equity, and boosting educational efficiency and effectiveness. The World Bank's “Learning for All” Education Sector 2020 Strategy was created with the objective of “ensuring that all children not only attend school, but also learn” (World Bank Group, 2011). One of the objectives is to foster educational equity, ensuring that all students, not only the most advantaged, gain the information and skills necessary for success in life (Prieto et al., 2019; Akhter et al., 2021).

Educational psychology, as an area of study and a focus of psychological research, is a relatively new phenomenon that is expanding and being actively contested across the world due to its potential contributions to the educational environment (Ferreira et al., 2016). The field of psychology dealing with the scientific study of human learning is known as educational psychology. Individual variations in intellect, cognitive development, emotions, motivation, self-regulation, and self-concept, as well as their function in learning, may all be understood via the study of learning processes from both cognitive and behavioral perspectives. Most educational psychologists regard their field as a scientific study concerned with understanding and improving how people learn a wide range of talents via formal classroom instruction (Snowman, 1997; Jones et al., 2019). Physiological arousal, psychological evaluation, and subjective experiences combine to create our emotional states. The components of emotion are all of these things put together. By analyzing user sentiment the emotional psychology of learners can be deduced from the supplied reviews (Geng et al., 2020). Which analysis is a form of text mining that extracts certain emotional expressions from text in order to predict the human mind, especially a person's emotional condition (Geng et al., 2020; Pang & Lee, 2008).

Due to various stakeholders in education and data availability, present research on sentiment analysis techniques in educational contexts is significantly lagging behind in comparison to other sectors (e.g., business, social networks). Sentiment analysis is becoming increasingly popular as a subfield of natural language processing. In the context of teaching assessment, sentiment analysis may assist educators in quickly discovering students' real sentiments about a course and accurately and timely adjusting the teaching plan to improve the quality of education and teaching (Zhai et al., 2020). The appraisal theory may be used to describe the psychology underlying users' sentiments.