USING EDUCATIONAL DATA MINING IN ASSESSMENT OF STUDENT ACHIEVEMENT

Abstract

Education is the deliberate enculturation process in general. The concept of deliberation here emphasizes a program that does not leave expectations to coincidences and thus excludes unwanted situations. No matter how accurately and effectively this program is organized, quality control is still carried out at the end of the process with assessment and evaluation processes. The assessment and evaluation processes in education provide feedback in terms of the effectiveness of both the student and the program. This would also lead to an effective reorganization of the process. One of the problems faced during the transition from product or outcome based student assessment approaches to process-based alternative assessment approaches is the difficulty in evaluating the student data collected by more than one alternative assessment instruments. Using all the data about the student in determining the academic achievement of students affects the success of process assessment approach positively. Educational Data Mining is the computer aided search of the relations and rules that enable us to make predictions about the present and the future through the use of the massive amount of data concerning the educational process obtained from various sources. With this process, patterns, similarities and correlations that are in a large data warehouse can be determined and interpreted by using any of pattern recognition methods. Through enabling holistic evaluation of data obtained by process evaluation oriented assessment instruments such as portfolio, rubrics, self and peer assessment, performance assessment etc. it will be possible to obtain the relations concerning not only students’ academic achievement but also students, teachers, schools and courses. Keywords: Assessment, alternative assessment, data mining, educational data mining