Why using robots to teach computer science can be successful theoretical reflection to andragogy and minimalism

Abstract

To help students understand subjects such as theoretical aspects of computation, algorithmic reasoning and intelligence of machines, a number of publications report experiments to teach these topics with the help of Lego Mindstorms robots. In the publications, the researchers report how they have created various ways to approach the issues either in Computer Science or in Artificial Intelligence. The reported results of the experiments are based on the learning outcomes, the feedback from the students, and the perceived informal observations (i.e. "feelings") of the instructors.But can anyone else benefit from the reportedly positive outcomes of the experiments? To give an answer to that question, this paper analyses the reported results through two support theories. The two theories chosen for this, andragogy and minimalism, are concerned with adult learning and how teaching adults should be approached. When reflecting the results of the four teaching experiments to the suggestions drawn from the theories, a more comprehensive answer to why the experiments have been successful can be given.The four teaching experiments analysed here were in many ways similar to each other. A connection to the chosen support theories was straightforward to make. Besides describing the artefacts of teaching with the robots, a deeper discussion on this teaching approach is provided. For an instructor, all these observations offer more concrete evidence about beneficial factors of teaching with robots.

Theoretical underpinnings of computing education research

“…Finally, networking of theories is used when the previous strategies are systematically applied by first comparing and contrasting and then integrating new perspectives giving a progressively deeper understanding of the phenomenon. Research using any of these strategies is currently scarce in CER, but examples can be found [15,28]. Of course this is not to diminish the value of papers that discuss the role of single theory in the CER context, such as those of Ben-Ari [1,2] A further finding of our analysis is that in nearly half of the papers we found no TMF.…”

PopBots: Designing an Artificial Intelligence Curriculum for Early Childhood Education

“…AI education goes beyond computational thinking, it explores how computers sense, think, act, learn, make decisions, create, perceive, and make sense of things. In higher education, students can take courses where they program and test algorithms and systems that cover the full range of AI concepts (Imberman 2003;Kumar, Kumar, and Russell 2006;Martin 2007;Klassner and McNally 2007;Koski, Kurhila, and Pasanen 2008;Talaga and Oh 2009;Burgsteiner, Kandlhofer, and Steinbauer 2016). AI courses in higher education emphasize the importance of students building their own projects.…”

“…AI courses in higher education emphasize the importance of students building their own projects. Instructors often use robots in these courses to help students concretize their understanding (Kumar 2004;Koski, Kurhila, and Pasanen 2008;Talaga and Oh 2009).…”

A Pair Programming Trial in the CS1 Lab

“…In recent years, a number of approaches has been tried to address the issues of both low CS1 enrollment and success rates. These include the use of more attractive interactive programming languages and IDEs (e.g., Alice, Greenfoot and Python), media computation [3], robotics [4], computer games [5] as well as pair programming. This paper reports a trial of the pair programming approach in the CS1 lab class over several semesters at CSU's School of Computer Science.…”