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Top1. Introduction
Education is the continuous process of learning or ongoing development in abilities, values, attitudes, behaviours and intelligence. Types of Education include instruction, reading, narrative, debate, and guided study. Education is mostly provided under the inspection of teachers, and also but learners may undergo self-learning. The process of education can be done in a formal or informal environment. The definition of education differs between philosophers. Figure 1 shows some description of Education by various philosophers.
The essential motive of any academic program is to provide students with the required knowledge and skillsets to transform onto a productive professional within a given stipulated period. Using Data Mining (DM) strategies to evaluate knowledge about students may help establish potential explanations for learning. Educational Data Mining (EDM) is a data mining technology field developed to address educational problems (Altrabsheh et al., 2013). This contains a large volume of contextual information which offers a better understanding of learners based on their methods of learning. This utilizes DM methods to analyze data from the academic environment and to address academic problems that stop from achieving the motive of the educational programme. As with other extraction methods using DM techniques, EDM derives relevant, interpretable, valuable and novel information from educational data (Algarni 2016). Educational data mining researchers view the following as their work goals (T. E. D. Mining 2012):
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Predicting the potential learning behaviour of students by developing models of students that include such specific details as the experience, motivation, meta- cognition, and attitudes of students
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The discovery or development of domain structures characterizing the learning material and optimal instructional sequences.
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Investigating the influences of different kinds of pedagogical aid that learning applications can offer.
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Advancing empirical information about learning and learners by developing computational models that include student simulations, the environment and the pedagogy of the program
Sentiment analysis, also termed as opinion mining, is an application of natural language processing, computational linguistics, and content interpretation that, by analyzing the viewpoint, recognizes and retrieves emotion polarity from the content. The polarity of opinion is typically either positive (confident and enthusiastic) or negative (confused, boisterous, and furious), but often used as neutral (Altrabsheh et al., 2014). Mostly the sentiment analysis is applied in e-commerce, to analyze the customer reviews. Only a few articles (Altrabsheh et al., 2013; Altrabsheh et al., 2014) apply sentiment analysis in the education domain. This paper reviews sentiment analysis in the field of education.
The study is organized in this survey paper as the following. Section 2 gives the different definition of education Section 3 describes various theories on learning. It is based on emotion and academic performance of the student. Section 4 explains the research on Education, which mainly includes academic performance, student behaviour and emotions. The application of Education under computer science is described in Section 4. In section 5 the sentiment analysis and research in education using sentiment analysis is explored, and finally, section 5 concludes this paper.
Top2. What Is Education?
Oxford definition of Education, Education is the process of acquiring or providing systematic instruction, especially at an academic environment like school, college or university. Education is the process of delivery of knowledge, skills and information to students by teachers.