DIGITAL LIBRARY
MOBILE DEVELOPMENTS TO SUPPORT LEARNERS IN MAINSTREAM EDUCATION
1 Nottingham Trent University (UNITED KINGDOM)
2 PheonisKM (BELGIUM)
About this paper:
Appears in: EDULEARN19 Proceedings
Publication year: 2019
Pages: 3921-3927
ISBN: 978-84-09-12031-4
ISSN: 2340-1117
doi: 10.21125/edulearn.2019.1006
Conference name: 11th International Conference on Education and New Learning Technologies
Dates: 1-3 July, 2019
Location: Palma, Spain
Abstract:
This paper will present findings from the second 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. The project supports teachers and teacher educators who have learners with special educational needs in mainstream classrooms, facilitating inclusive education. The countries involved in the project are Belgium, Bulgaria, Serbia, Turkey, and the United Kingdom.

To date the project has analysed 74 case studies and 90 interviews with teacher educators across the countries involved to develop a pedagogical framework. This has informed the development of a mobile technology that will measure the engagement levels of learners and provide useful information to the teachers for appropriate pedagogical adaptations to planned learning content. This will promote differentiation, reduce teacher time in planning and preparation, and improve teacher and learner experience, thus leading to enhanced progression and a change in school’s practice.

The mobile technology, now in beta testing stage, collects and analyses the multimodal data of engagement via five specially developed computer games to test a learner’s engagement level inside their comfort zone. The project draws on Swanson’s standardization of signal detection theory in a continuous performance test [1][2]. The learner’s performance in the game (errors and reaction time) provides objective criteria for labelling multimodal sensory data (body posture, facial expression and eye gaze). Machine learning methods are utilized to create a model of engagement from the fused multimodal sensory data features. The learner’s engagement levels are presented to the teacher as a method to choose best practices and teaching methods that sustain learner engagement - which encourages deep learning [3] and meaningful outcomes [4].

This paper will present findings from data collected from the beta testing phase, explain the process which has been developed, share the mobile games and associated application, and provide examples of use in schools across the partner countries. There will be opportunity for delegates to use the toolkit.

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, Oct. 1981.
[2] H. L. Swanson, “A developmental study of vigilance in learning-disabled and nondisabled children,” J. Abnorm. Child Psychol., vol. 11, no. 3, pp. 415–29, Sep. 1983.
[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.
Keywords:
Innovative use of technologies, primary school, secondary school, pedagogical innovation.