Prakash Hegade
*,
Nirmala Patil
,
Indira Bidari
- School of Computer Science and Engineering, KLE Technological University, Hubli-31, India
Abstract
Along with core courses, an education program is usually designed with discretionary elective courses for professional advancement. It is naturally inherent that most electives' course contents need periodic apprise to persevere to the state-of-art. The pace at which industries adapt to new technologies is considerably rapid as compared to the teaching and learning that happens at the university. However, an elective design needs an equal role and support to be played by the industry and the institute. This paper proposes the design principles for an elective course, which envelopes from curriculum structure to evaluation methodologies. The principles are outlined to cover the design aspects, selection methodologies for the content and course materials, syllabus division to units, course learning outcomes, teaching pedagogy, industry principles, evaluation methodologies, and course learning attainment. Each principle is presented with an objective and deliberation. The intended principles were applied to the design and delivery of an elective � Semantic Web. The course, which was offered with an industry-institute collaboration, was opted by 125 students in the sixth semester. The paper further presents each of the principles as applied and delivered for the semantic web course. The course attainment with respect to course learning outcomes, student elective opt ratio, and the feedback obtained stand in favor of the proposed model. The principles can be applied to design the elective for enhanced learning experiences and make students industry-ready, which is one of the major objectives for introducing the electives.
References
- Altunbay, M. (2018), The Effects of Elective Courses on the Personal Development of Prospective Teachers. Universal Journal of Educational Research. 6. 2094-2100. 10.13189/ujer.2018.061006.
- Adak MF, Yumusak N and Taskin H. (2016), An elective course suggestion system developed in computer engineering department using fuzzy logic. In 2016 International Conference on Industrial Informatics and Computer Systems (CIICS) 6 Mar 13, pp. 1-5, IEEE.
- Amin, H., Rahman, A.R.A. and Ramayah, T. (2009), What makes undergraduate students enroll into an elective course?. International Journal of Islamic and Middle Eastern Finance and Management. 2. 289-304.
- Bhumichitr, K., Channarukul, S., Saejiem, N. Jiamthapthaksin, R. and Nongpong, K. (2017), Recommender Systems for university elective course recommendation. In 2017 14th International Joint Conference on Computer Science and Software Engineering (JCSSE), pp. 1-5, IEEE.
- Darby, J.A. (2006), The effects of the elective or required status of courses on student evaluations. Journal of Vocational Education and Training, 58(1), pp.19-29.
- Ding, H. T. and Christina, K. C. L. (2012), Understanding students' choice of electives and its implications, Studies in Higher Education, 37:3, 309-325, DOI: 10.1080/03075079.2010.512383.
- Esteban, A., Zafra, A. and Romero, C. (2020), Helping university students to choose elective courses by using a hybrid multi-criteria recommendation system with genetic optimization. Knowledge-Based Systems, 194, p.105385.
- Evyapan, N., Korkut, F. and Hasdo?an, G. (2005), Implications of collaboration with industry for educational strategies in industrial design: the graduation project course. METU, Faculty of Architecture Press, Ankara, pp.137-159.
- Ferrer-Caja, E. and Weiss, M.R. (2002), Cross-validation of a model of intrinsic motivation with students enrolled in high school elective courses, The Journal of Experimental Education, 71(1), pp.41-65.
- Higbee, J.L., Dwinell, P.L. and Thomas, P.V. (2002), Beyond University 101: Elective courses to enhance retention. Journal of College Student Retention: Research, Theory & Practice, 3(4), pp.311-318.
- Jackson, H., Tarhini, K., Zapalska, A. and Zelmanowitz, S. (2010), Strategies to infuse global perspectives and industrial collaboration in engineering education. In 2010 IEEE Frontiers in Education Conference (FIE) pp. S1J-1, IEEE.
- Jie, Q.I.N. (2005), research on the Development of the Elective Courses in Higher Education [J], Journal of Beijing University of Physical Education, 6.
- M�ller, T. and Rudov�, H. (2016), Real-life curriculumbased timetabling with elective courses and course sections. Annals of Operations Research, 239(1), pp.153 170.
- Patil, U., Iyer, N., Budihal, S., Ramesh, T., Heera, W. and Rohit, K. (2020), Industry Institute Collaborative Domain specific Theme Based Projects. Procedia Computer Science, 172, pp.181-186.
- Patterson, B.J., Garza, O.W., Witry, M.J., Chang, E.H., Letendre, D.E. and Trewet, C.B. (2013), A leadership elective course developed and taught by graduate students. American journal of pharmaceutical education, 77(10).
- Ray, S. and Sharma, A. (2011), A collaborative filtering based approach for recommending elective courses. In International Conference on Information Intelligence, Systems, Technology and Management, pp. 330-339, Springer, Berlin, Heidelberg.
- Susan, S. and Bhutani, A. (2018), Data Mining with Association Rules for Scheduling Open Elective Courses Using Optimization Algorithms. In International Conference on Intelligent Systems Design and Applications, pp. 770-778, Springer, Cham.
- Tener, R.K. (1996), Industry-university partnerships for construction engineering education. Journal of Professional Issues in Engineering Education and Practice, 122(4), pp.156-162.
- Ulusoy, Y.�., Da?, F., Fidan, D., Sahran�, �., Inan, B. and G�ll�, D. (2012), Students opinions about elective courses in changing education: The example of Kocaeli University Faculty of Education. Journal of Educational and Instructional Studies in the World, 2(4), pp.135-142.
- Versypt, A.N.F. (2019), November. Building Computational Skills for Mathematical Modeling in Science and Engineering through an Interdisciplinary Elective Course. In 2019 AIChE Annual Meeting. AIChE.
