# Predicting Academic Performance Using an Efficient Model Based on Fusion of Classifiers
## 1 Introduction  
Educational data mining (EDM) is a growing area of research that is being used to explore educational data for different academic purposes. The main application of EDM is the prediction of students' academic performance [1, 2]. In data mining, the analysis and interpretation of student academic performance are regarded as suitable analysis, evaluation, and assessment tools [3]. In the present era of a knowledge economy, the students are the key element for the socio-economic growth of any country, so keeping their performance on track is essential. Data mining (DM) methods are applied to learn hidden knowledge and patterns which assist administrators and academicians in decision making regarding the delivery of instructions. DM techniques have applications in numerous areas including retail business, the health sector, marketing, banking, bioinformatics, counter-terrorism, and many others are also using it to enhance productivity and efficiency [4]. Education plays a vital role in the development of any nation. The education in Pakistan has improved in the past few years; it is further striving to enhance academic performance to produce a well-educated and competitive workforce to meet the requirements of the market [5]. The academic performance of high school students is a critical concern for parents, teachers, the education department, and the government. The performance of students at the secondary level is highly influenced by their demographic, schooling, social background, family background, and psychological factors [6]. Individuals vary from one another in terms of these factors, and hence their academic performance differs accordingly [5]. It is therefore important to predict students' academic performance, taking into account the aforementioned parameters. The performance of secondary level students in science subjects is expected to be high in order to provide quality entrants at a higher level of education, which is key to prosperity and the knowledge economy [7]. Therefore, the lower secondary level is very crucial for students aiming for science as a major subject, because it is a baseline for setting their academic goals. Ninth-grade students need to consider grades as imperative at the lower secondary level as they act as a stepping-stone in subsequent educational levels. Academic performance can be enhanced by identifying weak areas concerning academics and personal traits. To achieve this, the design of a prediction system is indispensable to estimation of students' academic progress at an early stage before they in board examination. Such prediction may be beneficial in multiple ways. For example, it can help in reinforcing students to improve their performance in their weak areas. Secondly, it may assist in the selection of subjects where students can perform better. Thirdly, it can be useful in deciding on career goals. Finally, it can assist in awarding accurate grades to students based on their previous performance in COVID-19-like situations where administering examinations is impossible. Therefore, a prediction system should be in place to predict the performance of ninth-grade students at an early stage of the academic year to keep them on track and enable them to perform better in board examinations. The basic objective is to minimize the dropout and failure ratios of students at the lower secondary level. Additionally, the selection of subjects in grade nine is considered important in students' academic growth and professional advancement. To support education in a traditional setting, numerous systems such as massive open online courses (MOOCS), intelligent tutoring systems (ITS) and web-based educational systems have been designed but there is a dearth of systems to predict students' academic progress [8]. As per our knowledge, in Pakistan, there is no prediction system available to measure students' progress at the lower secondary level.