Academic teaching-based research 2017 part 1

The recent 13th China Europe Symposium on Software Engineering Education (CEISEE) held in Athens, Greece 24-25th May 2017 provided the Computing Academic team an opportunity to present some their work in teaching computing. In the picture above going left to right Thomas Butler, Liz Coulter-Smith, Suraj Ajit, Scott Turner and Ryan Edwards.

Details of three of the six papers presented can be found below.

1.Changing minds: multitasking during lectures.
Coulter-Smith, L. (2017) 

Abstract: Multitasking students is a common topic amongst academics. Many studies focus on how students multitask while this study investigates why students multitask in formal lectures. A questionnaire was used to discover student perceptions around multitasking amongst computing students. The results indicate most students are adequately motivated to improve their multitasking behaviour if it influences their grades. Results show that most students claimed boredom as a significant reason for multitasking in class. This study suggests we inform students about the effects of multitasking as it relates to their academic achievement.

To find out more click here

2. The answers not on the screen
Hill, G.Turner, S. J. and Childs, K. (2017) 

Abstract: Reflection from two areas on the issues of getting students in Higher Education (HE) to become better problem-solvers earlier. Asks some questions about should HE increase the use of unplugged activities? If so, is there any evidence that it will help? What lessons can HE learn from what is happening in Primary Schools? What can schools learn from what is and has happened in HE teaching of programming and problem-solving?

To find out more click here.

3. Experience of using spreadsheets as a bridge in the understanding of AI techniques.
Turner, S. J. (2017) 

Abstract: Spreadsheets have and are being used as valuable tools in a variety of subjects including Engineering. Providing a tool for simulating and exploring models. In this paper, their role in allowing students to explore two AI approaches, basic neuron, and a simple genetic algorithm, is considered.

To find out more click here.

All views and opinions are the author's and do not necessarily reflected those of any organisation they are associated with. Twitter: @scottturneruon