MEANINGFUL PATHWAYS FOR INCLUSIVE EDUCATION

H. Boulton1, D. Brown1, M. Taheri1, K. Van Isacker2, A. Burton1, N. Shopland1

1Nottingham Trent University (UNITED KINGDOM)
2PhoenixKM BVBA (BELGIUM)
This paper will present findings from the first phase of an Erasmus+ funded project which addresses at its very core inclusive education, thus affecting and supporting every teacher in the European countries that ratified the UNCRPD, 2008, as well as beyond Europe. Inclusive education is a major concern globally. This project aims to substantially contribute to the uptake and implementation of inclusive education by providing teachers and teacher educators with a toolset to support the assessment of each child as part of a holistic approach towards inclusive education. The countries involved in the project are Belgium, Bulgaria, Serbia, Turkey, and the United Kingdom.

The main task of this project is to provide teachers and teaching assistants with a mobile technology that will measure the engagement and attention of learners and provide information to the teacher on appropriate pedagogical adaptations to planned learning content. Thus, promoting differentiation, reducing teacher time in planning and preparation, improving both teacher and learner experience and supporting the learner in improved attention and engagement, leading to enhanced progression and a change in school’s practice.

The mobile technology will take multi-modal data of engagement and attention using a mobile tablet device on which the children play a game, drawing on Swanson’s [1] signal detection theory to create ‘games’ that test a learner’s attention inside their comfort zone. Their performance in the game (errors and reaction time) enable us to understand the multisensory data that are being collected whilst they play these games and allows us to understand the patterns using multisensory data: body posture, facial expression, gesture tracking, eye gaze, brain activity (EEG) and thermal data. Computer methods will be used to fuse the multisensory data, and to predict differing attention/engagement [2] to enable deep learning [3] and meaningful outcome [4]. The data will then be sent to a Cloud where an algorithm will use the data to identify appropriate pedagogy to support the learner which will be sent to the teacher via an App.

This paper will present findings from data collected from 74 Case Studies and 90 interviews with teachers from the countries involved. The one to one interviews were transcribed and translated into English, then analysed using Braun & Clarke’s [5] theory of thematic analysis of qualitative data. Codes were identified from the interviews patterns and relationships identified and organised into key themes. This data has formed a pedagogical framework which will be presented at the conference and will form the basis of the App. The planning for the mobile games and associated technology will also be shared.

References:
[1] L. Swanson, “Vigilance deficit in learning disabled children: a signal detection analysis,” J. Child Psychol. Psychiatry., vol. 22, no. 4, pp. 393–399, 1981.
[2] B. Carpenter “Engaging children with complex learning difficulties and disabilities in the Primary Classroom. 2011.
[3] D. H. Hargreaves, “A new shape for schooling?” 2006.
[4] B. Carpenter, “Disadvantaged, deprived and disabled, Special Children,” Special Children Magazine 193, pp. 42–45, Feb-2010.
[5] V. Braun, and V. Clarke, “Using thematic analysis in psychology”. Qualitative Research in Psychology, 3 (2), 77-101. 2006.