Abstract:

One of the most important aspects of learning is student engagement. Student engagement is integral to everything that happens in Educational institutions. Indeed, as educators, academics and teachers we construct our courses and develop teaching materials to maximise student engagement; taking into consideration novel approaches to delivering course materials that fully engages students as best we can. Long gone are the ideas that students are merely the consumers of knowledge, instead we now consider students to also be the producers of their own learning and development.

Much research has been done on improving student engagement though the notion of active learning, and Student as Producer (http://studentasproducer.lincoln.ac.uk/), interactive delivery of course materials and the use of interactive technologies in the classroom. All these initiatives help towards creating a much richer and vibrant learning environment for students to engage in. However, the physical properties of the learning environments in which students find themselves in for the majority of their learning are not usually considered. Whilst there are many different types of classrooms available in educational institutions, such as raked lecture rooms, seminar rooms, open plan, closed plan and all coming in many different shapes and sizes they are predominately seen as a static structure and taken as is.

The lecture / classroom environment itself can impact heavily on student engagement, learning and satisfaction. As such the research presented in this paper looks at monitoring and analysing the environmental conditions of the learning space and correlating this with the current satisfaction levels and moods of the students after the lecture. Several environmental monitoring devices have been constructed and are placed in the different lecture rooms at the University. These devices record the following environmental conditions throughout the duration of the lecture: Temperature, Humidity, Light Level, Sound, CO2 Level and Current Time. At the end of the lecture as students leave the lecture room there is a touch screen display for the students to record their current mood: Happy, Tired, Confused, Angry, Sleepy, Alert, Stressed, Inquisitive, etc. These are represented on the screen by smilies and the students can simply click the most representative one as they leave the room.

The environmental data and student responses are then compared across varying lecture rooms, cohorts of students and subjects in the hope that a correlation emerges between the environmental conditions and the student's engagement and mood. It is widely believed that a person's current emotional state influences how they learn. Sylwester (1994) draws together a lot of good research on the issue stating "We measure spelling accuracy, [but] not emotional well-being." Here he was referring to the metrics by which we measure learning, but how we discard the 'just as important' states of our brain and wellbeing which can drastically influence how and what we learn.

EMOSys is currently being rolled out in the School of Computer Science at the University of Lincoln, UK, where it is being tested by the students. It is funded by FED - Fund for Educational Development and is being designed, built and implemented by the very students it is designed to help.

References:
[1] Sylwester, R. (1994) "How Emotions Affect Learning". Reporting What Students Are Learning, Vol 52, Num 2.

Keywords:

Engagement, Environment, Computer Science, Moods, Emotions.