Research support-oriented MATLAB learning: tackling difficult concepts and promoting personalised learning
DOI:
https://doi.org/10.29311/ndtps.v0i12.2402Keywords:
Programming, MATLAB, Research supportAbstract
This study investigated the acquisition of MATLAB programming skills by postgraduate students, and whether this learning was improved by research support-oriented teaching. Questionnaire surveys were given to academic staff asking about what they considered the most important knowledge and skills in programming to be. Questionnaire surveys were also given to students asking about what programming concepts they found the most difficult and confusing to understand. The intersection between what knowledge and skills in programming the researchers deemed the most important, and what areas in programming students had most difficulty with, was carefully addressed in subsequent teaching in a module teaching the essentials of programming to postgraduate students. Student learning performance, as measured by examination marks on the module, before and after the intersection concepts were emphasised was compared. The student learning performance improvement, together with interviews to students about their perceptions about programming, suggests that teaching oriented to research support is effective at increasing student understanding of programming in MATLAB.
Keywords: Programming; MATLAB; Research support
References
Azemi, A., Bodek, M. & Chinn, G. (2013). Teaching an Introductory Programming Course Using Hybrid E-learning Approach. In: Frontiers in Education Conference. IEEE, pp. 1911-1913. DOI: 10.1109/FIE.2013.6685168.
Cohen, M.X. (2017). MATLAB for Brain and Cognitive Scientists. Cambridge, MA: MIT Press.
Gresty, K., Heffernan, T., Pan, W. & Edwards-Jones, A. (2015). Minimising risks in research-informed teaching. Higher Education Review, 48(1), pp. 40-67.
Hay, D.B., Weller, S. & Ashton, K. (2015). Researcher-led teaching: embodiment of academic practice. Higher Education Review, 48(1), pp. 25-39.
Misirlisoy, E. (2017). Programming Behavioral Experiments with MATLAB and Psychtoolbox: 9 Simple Steps for Students and Researchers. New York: Routledge.
Nyamapfene, A. & Lynch, S. (2016). Systematic Integration of MATLAB into Undergraduate Mathematics Teaching: Preliminary Lessons from Two UK Institutions. In: IEEE Global Engineering Education Conference (EDUCON). IEEE, pp. 1145-1148. DOI: 10.1109/EDUCON.2016.7474699.
Robins, A., Rountree, J. & Rountree, N. (2003). Learning and Teaching Programming: A Review and Discussion. Computer Science Education, 13(2), pp. 137-172. DOI: 10.1076/csed.13.2.137.14200.
Rosenbaum, D.A., Vaughan, J. & Wyble, B. (2015). MATLAB for Behavioral Scientists. 2nd ed. New York: Routledge.
Smith, J., Flowers, P. & Larkin, M. (2009). Interpretative Phenomenological Analysis: Theory, Method and Research. London: SAGE.
