MAKING SENSE OF TEXTS GATHERED WITH CLASSROOM RESPONSE TECHNOLOGY

Technology is used more and more in the educational settings, a trend that is fueled by the ever increasing ubiquity of mobile devices and access to internet. The classroom experience becomes interactive and engaging for the participants by making use of audience response technology. Response technology allows us to ask a question in the classroom and instantly get back the replies from the students.

In this paper we present our early experiences in crafting meaningful and useful interactive visualisations aimed to be included in the response technology enabled classroom.

When we use multiple choice questions, the aggregation and visualisation of the gathered responses can be done through simple charts which provide enough information for the teacher to allow her to give immediate feedback to the students. However, sometimes an important part of the classroom work involves text. This is especially relevant for language learning where there is a plethora of exercises that require free-text responses.

Visualising and aggregating text responses must facilitate teacher ability to give immediate feedback to the class, thus the responses received must be represented in a way that is manageable in a very short time. In designing our visualization we take into account the teacher task and her goal in that particular case. An exercise that calls for just a word would most likely require a different visualisation from another exercise that asks to make sentences from a limited set of words.

Moreover the visualisations should allow various interactions that render them a flexible discussion support with the students. The results could be displayed on the shared screen of a smart-board allowing the teacher to interact upon the visualisation and highlight elements or switch perspectives as needed.
The same set of responses can be represented in multiple ways. In our design and prototypes we strongly consider multi-modal representations.
The paper presents our proposed solutions for visualising and aggregating the text for several use cases.