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What Is Self Grading In Data Mining

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Accepting or Rejecting Students’ Self-grading in their
Final Marks by using Data Mining

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Abstract—In this paper we propose a methodology based on data mining andself-evaluation in order to predict whether an instructor will or will not accept the students’ proposed marks in a course. This is an on-going work in which we have evaluated the usage of classification techniques and cost-sensitive corrections. We have carried out several experiments …show more content…

II. METHODOLOGY
The methodology that we have used in this study is as follows.During the course, students are evaluated by means of a multiple choice testing that is an effective assessment technique. Before the final exam date, all students are requested to self-grade. Students propose the mark/grade that they think they should get for the course. Then, the instructor accepts or declines the proposed mark of each student as the final mark for the course. This way, only students whose score was declined by the instructor will have to sit the final exam. Finally, we try to predict the instructor’s decision of accepting or declining the score proposed by students.
We have used two different (initial and new) data mining approaches (see Figure 1).

Figure 1. Approaches for predicting instructor’s decision.
The initial approach uses three numerical variables: the scoreobtained by students in the course’s activities, the proposed scores by students and the difference between these two previous scores.
Then, it applies traditional classification algorithms for predicting the instructor’s decision about whether to accept the proposed students’ scores (YES) or not (NO). The new approach uses the three previous variables as well as a self-evaluation questionnaire as another source of information. Then, it applies cost-sensitive classification [2] that is normally used for obtaining

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