Towards authentic undergraduate research experiences in software engineering and machine learning

Abstract

Authentic undergraduate research experiences have been shown to be very effective at sustaining students’ learning motivation and enhancing students’ theoretical knowledge and practical skills. However, there still exists some common challenges in undergraduate research. In this paper, we describe an approach that offers undergraduate students authentic and immersive research experience focusing on applied machine learning for software engineering and discuss our experiences with example undergraduate research projects and outcomes. A survey was designed to assess students’ overall experience of participating in authentic undergraduate research projects in machine learning for software engineering. Preliminary results from this survey are provided.