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Teaching Strategies in Software Engineering Towards Industry Interview Preparedness

EasyChair Preprint no. 4665

11 pagesDate: November 27, 2020


Software Engineering (SE) curriculum in undergraduate computer science (CS) education is designed to train students in the process of software and systems development. Traditionally, topics like software development methodologies, industry nomenclatures, and solution analysis are delivered through lectures and group projects. We propose a novel approach in teaching SE, which we call MACROVR: MAchine learning to select project team members; Cloud technologies required for project control, code versioning, and team communications; ROtational schedules in Agile/Scrum roles; an individual Video of the team project story board; and Rubrics for all presentations. Our teaching strategy with this approach utilizes the latest technologies currently found in industry and corresponds to commonly used interview areas related to soft skills in computing jobs. The goal of our study is to measure if using the MACROVR approach contributes to preparedness for a computing job interview. Most often, this class is taken towards the end of a four–year CS degree program while students are job hunting or seeking a summer internship in the computing industry. We use an anonymous, fifteen question survey instrument sent to volunteers that indicate they are seeking a computing job and have successfully completed the SE course. The sample is comprised of three sections of the SE course using the MACROVR approach (135 students) and four sections that did not use all of the approach's required components, which we call MACROVR–lite (184 students). We have two cohorts: MACROVR versus MACROVR–lite, and each are given the same survey questions. We analyze their Likert scale data responses using non–parametric methods. Our findings indicate the MACROVR approach better prepares students with skills and highly valued qualities for computing industry interviews.

Keyphrases: Agile, Computer Science Education, Educational Data Mining, Scrum, Software Engineering

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {William Gregory Johnson and Raj Sunderraman and Anu G. Bourgeois},
  title = {Teaching Strategies in Software Engineering Towards Industry Interview Preparedness},
  howpublished = {EasyChair Preprint no. 4665},

  year = {EasyChair, 2020}}
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