Introduction
A educational quantity of data is stored within a system for providing education. This data may pertain to students, graduates of the institution, teachers, non-teaching staff, resources, or any number of other categories. Mining educational data allows for the discovery of patterns in the data, which may then be used for decision-making (Edin Osmanbegovic, 2012).
The patterns that are derived from student data can provide the answers to many questions that can be asked about educational data mining. These questions include: That are the students who are likely to fail in the future?
How active and engaged are the students in this activity?
Who among the students is most likely to withdraw from a class?
How likely is it that a student will be promoted to the class after that?
Which classes ought a department to provide in order to entice a greater number of students?
How many new students should be admitted to the department at the beginning of each semester?
The results of educational data mining may be put to use by a variety of stakeholders within the educational system, including administrators, teachers, students, and even school security personnel. Students can utilize them to determine the necessary activities, resources, and learning assignments to enhance their own learning. The teachers may use them to gain more objective feedback, to separate the stronger students from the weaker students, and to coach and assist the weaker students, who are also referred to as students at risk, in order for them to be successful. In the event of a crisis, the security agents can utilize the information gleaned via educational data mining to identify and locate individual students. The results of educational data mining may also be utilized by the institution to determine the errors that are most frequently committed and to arrange the information found on the school's website in a manner that is both effective and efficient.
The first form of educational system is the traditional one.
A. The older, more conventional educational education:
The students and the teachers engage in face-to-face interaction throughout the entirety of the traditional educational model. Records of students, which may contain information like as attendance and grades, may be recorded manually or digitally, depending on the preference of the teacher. One way to measure this information is by looking at the performance of the students.
E-learning is another name for the web-based learning system, which is also referred to as B. web-based learning system. It is becoming the most expedient strategy towards education, and it has gotten more popular as a result of the fact that students may learn from any location and at any time without being constrained by any kind of schedule. Logs are used in the web-based education system, which allows for the automatic collection of a variety of data pertaining to the students.
The work that was done on this project offers a model that can predict the academic performance of students who are educated in the conventional manner. Because lowering the percentage of students who receive failing grades is the primary objective of this work on the project, the next development will assist us in better comprehending the significance of this model. Since weaker students are also accepted into the institutions, the results of the institutions are deteriorating when it comes to achieving high grades; consequently, if we know in advance which students are likely to fail, the institutions or the teachers can take the necessary steps towards improving the results. This will contribute to an improvement in the overall quality of the graduates that are generated each year from these educational institutions (Kabra and Bichkar, 2011).
Since one of the objectives of tertiary institutions is to make a contribution to the enhancement of the quality and level of higher education, the achievement of success in the production of human capital has been an ongoing topic of investigation. As a result, the prediction of students' performance is very significant to these higher education institutions. This is due to the fact that the objective of any teaching process is to satisfy the educational requirements of students and to increase students' overall academic achievement. In this respect, significant information and data are collected on a consistent basis, and then thereafter, they are utilized in the process of making predictions regarding the academic performance of students (Edin Osmanbegovic, 2012).
Because students' academic performance is dependent on a variety of factors including personal, socio-economic, psychological, and other environmental variables, it is a difficult undertaking to measure and forecast the academic performance of students. The prediction of a student's performance, on the other hand, is a very important endeavor because it assists both students and teachers in minimizing poor academic performances and producing students who are better educated and more enlightened in order to make the society in which they live a better place. A student who is struggling academically can be recognized and assisted with the aid of performance prediction. This is accomplished by taking into account all of the factors that have an impact on the student and offering solutions to combat these factors in order to facilitate better academic performance (Brijesh Kumar Bhardwaj and Saurabh Pal, 2011).
1.2. Statement of the Problem
It is certain that failure rates among students will continue to be a major issue for educational institutions of higher learning so long as proper steps are not taken to address the issue. However, by doing research into the socio-economic, psychological, and environmental aspects that contribute to student failure, significant strides may be achieved toward reducing the severity of the problem.
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