Reducing the duration of Higher Education Study with Sequenced Course Recommendation using Categorical Subset Summation Algorithm
M. Premalatha1, V. Viswanathan2
1M. Premalatha, VIT, Chennai (Tamil Nadu), India.
2V. Viswanathan, VIT, Chennai (Tamil Nadu), India.
Manuscript received on 19 February 2019 | Revised Manuscript received on 10 March 2019 | Manuscript Published on 08 June 2019 | PP: 751-754 | Volume-7 Issue-5S4, February 2019 | Retrieval Number: E11550275S419/19©BEIESP
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Abstract: In recent years, gen-y student’s learning pace is expanded on account of which the students could complete the required courses before the duration of their degree program. Students enroll the courses in their very own successions and interests during the adaptable course enrolment process. Course arrangement proposal encourages the students to finish their degree program before the duration of the study. This paper proposes a course suggestion framework using categorical subset summation algorithm to decrease the higher education study duration. This model is evaluated by comparing the proposed method with the current course registration patterns followed at our university.
Keywords: Education Algorithm Sequenced Recommendation Program Process Framework.
Scope of the Article: Smart Learning and Innovative Education Systems