Classification Model of Prediction for Placement of Students

Data mining methodology can analyze relevant information results and produce different perspectives to understand more about the students' activities. When designing an educational environment, applying data mining techniques discovers useful information that can be used in formative evaluation to assist educators establish a pedagogical basis for taking important decisions. Mining in education environment is called Educational Data Mining. Educational Data Mining is concerned with developing new methods to discover knowledge from educational database and can used for decision making in educational system. In this study, we collected the student's data that have different information about their previous and current academics records and then apply different classification algorithm using Data Mining tools (WEKA) for analysis the student's academics performance for Training and placement. This study presents a proposed model based on classification approach to find an enhanced evaluation method for predicting the placement for students. This model can determine the relations between academic achievement of students and their placement in campus selection.

[1]  Lisa Gjedde,et al.  Research, Reflections and Innovations in Integrating ICT in Education Examining online learning processes based on log files analysis: A case , 2022 .

[2]  Saurabh Pal,et al.  Data Mining: A prediction for performance improvement using classification , 2012, ArXiv.

[3]  Zlatko J. Kovacic,et al.  Early Prediction of Student Success: Mining Students Enrolment Data , 2010 .

[4]  Zebun Nisa Khan.  Scholastic Achievement of Higher Secondary Students in Science Stream , 2005 .

[5]  Ian H. Witten,et al.  Data mining: practical machine learning tools and techniques, 3rd Edition , 1999 .

[6]  Petra Perner,et al.  Data Mining - Concepts and Techniques , 2002, Künstliche Intell..

[7]  Mark Bray,et al.  The Shadow Education System: Private Tutoring and Its Implications for Planners , 1999 .

[8]  Ian H. Witten,et al.  Data mining - practical machine learning tools and techniques, Second Edition , 2005, The Morgan Kaufmann series in data management systems.

[9]  Ian Witten,et al.  Data Mining , 2000 .

[10]  Syed Tahir Hijazi,et al.  Factors Affecting Students' Performance A Case Of Private Colleges , 2006 .

[11]  Jyoti Vashishtha,et al.  A Generalized Data mining Framework for Placement Chance Prediction Problems , 2011 .

[12]  Surjeet Kumar Yadav,et al.  Data Mining Applications: A comparative Study for Predicting Student's performance , 2012, ArXiv.

[13]  Surjeet Kumar Yadav,et al.  Mining Education Data to Predict Student's Retention: A comparative Study , 2012, ArXiv.

[14]  Qasem A. Al-Radaideh,et al.  Mining Student Data Using Decision Trees , 2006 .

[15]  Umesh Kumar Pandey,et al.  A Data Mining view on Class Room Teaching Language , 2011, ArXiv.

[16]  Ajay Kumar Pal.  Analysis and Mining of Educational Data for Predicting the Performance of Students , 2013 .

[17]  Alberto Maria Segre,et al.  Programs for Machine Learning , 1994 .

[18]  Xindong Wu,et al.  The Top Ten Algorithms in Data Mining , 2009 .

[19]  J. Ross Quinlan,et al.  C4.5: Programs for Machine Learning , 1992 .

[20]  Saurabh Pal,et al.  Mining Educational Data to Analyze Students' Performance , 2012, ArXiv.