A. Kangaiammal

Work place: Computer Applications, Govt. Arts College (Autonomous), Salem -7, Tamil Nadu, INDIA

E-mail: indurath2002@yahoo.co.in

Website:

Research Interests: Software Development Process, Data Mining, Data Structures and Algorithms

Biography

Dr. A. Kangaiammal received both B.Com. and MCA from Bharathidasan University, Trichy in 1993 and 1996, respectively. M.Phil. (Computer Science) from Manonmaniam Sundaranar University, Tirunelveli in 2001. Ph.D. in Computer Applications from the University of Madras in 2009 and M.E. Computer Science and Engineering from Salem Vinayaka Missions University in 2010. Her research interest includes Data Mining, Mobile Computing, Grid Computing, Web Mining, E-Learning, Content Development, Instructional Design and Curriculum Development. She is an Assistant Professor of Computer Applications in Government Arts College (Autonomous), Salem-7, Tamilnadu, India. She has put up more than 15 years of teaching and research experience. She has 2 national and 5 international publications. She has delivered special lectures at teachers‘ and students‘ FDPs, Conferences, Seminars and Workshops in the technical and pedagogical areas. She is a life member of ISTE and SETRAD. She is also a member in ACM.

Author Articles
Student Learning Ability Assessment using Rough Set and Data Mining Approaches

By A. Kangaiammal R. Silambannan C. Senthamarai M.V. Srinath

DOI: https://doi.org/10.5815/ijmecs.2013.05.01, Pub. Date: 8 May 2013

All learners are not able to learn anything and everything complete. Though the learning mode and medium are different in e-learning mode and in classroom learning, similar activities are required in both the modes for teachers to observe and assess the learner(s). Student performance varies considerably depending upon whether a task is presented as a multiple-choice question, an open-ended question, or a concrete performance task [3]. Due to the dominance of e-learning, there is a strong need for an assessment which would report the learning ability of a learner based on the learning skills under various stages. This paper focuses on assessment through multiple choice questions at the beginning and at the end of learning. The learning activities of the learner are tracked during the learning phase through a Continuous Assessment test to realize the understanding level of the learner. The scores recorded in the database is analyzed using a Rough Set Approach based Decision System. The effectiveness of teaching learning process indicates the learning ability of the learner, presented in a Graphical form. It is evident from the results that the entry behavior and the behavior while learning determine the actual learning. Students generate internal opinion as they monitor their engagement with learning activities and tasks and also assess progress towards goals. Those who are effective at self-regulation, however, produce better feedback or are able to use the self-opinion they generate to achieve their desired goals. The tool developed assists the teacher to be aware of the learning ability of learners before preparing the content and the presentation structure towards complete learning. In other words, the developed tool helps the learner to self-assess the learning ability and thereby identify and focus to gain the lacking skills.

[...] Read more.
Other Articles