Empirical Study from Final Exams of Computer Science Courses Demystifying the Notion of 'an Average Software Engineer'
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32870
Empirical Study from Final Exams of Computer Science Courses Demystifying the Notion of 'an Average Software Engineer'

Authors: Alex Elentukh

Abstract:

The paper is based on data collected from final exams administered during five years teaching the graduate course in software engineering. The visualization instrument with four distinct personas has been used to improve effectiveness of each class. The study offers a plethora of clues toward students' behavioral preferences. Diversity among students (professional background, physical proximity) is too significant to assume a single face of a learner. This is particularly true for a body of on-line graduate students in computer science. Conclusions of the study (each learner is unique and each class is unique) are extrapolated to demystify the notion of an 'average software engineer'. An immediate direction for an educator is to assure a course applies to a wide audience of very different individuals. On another hand, a student should be clear about his/her abilities and preferences - to follow the most effective learning path.

Keywords: K.3.2 computer & information science education, learner profiling, adaptive learning, software engineering.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 575

References:


[1] Shirin Mojarad, Alfred Essa, Shahin Mojarad, Ryan S. Baker, “Data-Driven Learner Profiling Based on Clustering Student Behaviors: Learning Consistency, Pace and Effort”. https://link.springer.com/chapter/10.1007/978-3-319-91464-0_13
[2] James Reason, "Human Error", Cambridge University Press, 1990.
[3] Point Lookout, Chaco Canyon Consulting, February 2, 2022, Volume 22, Issue 4.
[4] Gilles Hilary and Charles Hsu. "Endogenous overconfidence in managerial forecasts." Journal of Accounting and Economics 51:3, (2011), 300-313. Retrieved 17 January 2022.
[5] Susanna Barrineau, “Students as Change Agents – Reorienting Higher Education Pedagogy for Wicked Times”, Uppsala University.
[6] Sallie Gordon, "Systematic Training Program Design", Prentice Hall, ISBN-13: 978-0131003897.
[7] Essaid El Bachari et al. "An Adaptive Learning Model Using Learner’s Preference", 2010, Cadi Ayyad University.
[8] Jose Manuel Marquez Vazquez, et. al. " Designing adaptive learning itineraries using features modeling and swarm intelligence". Springer-Verlag London Limited 2011.
[9] Alex Elentukh, Vijay Kanabar, "Improving Teaching and Learning Effectiveness of Computer Science Courses – Case Study ", CSECS 2019.
[10] Sally Fincher, Marian Petre, "Project-Based Learning Practices in Computer Science Education". December 1998.