Abstract
This ‘industry’ paper reports on the combined effort of researchers and industrial designers and developers to ground the automatic quality assurance of online maths human-to-human tutoring on best practices. We focus on the first step towards this goal. Our aim is to understand the largely under-researched field of online tutoring, to identify success factors in this context and to model best practice in online teaching. We report our research into best practice in online maths teaching and describe and discuss our design and evaluation iterations towards annotation software that can mark up human-to-human online teaching interactions with successful teaching interaction signifiers.
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Cukurova, M., Mavrikis, M., Luckin, R., Clark, J., Crawford, C. (2017). Interaction Analysis in Online Maths Human Tutoring: The Case of Third Space Learning. In: André, E., Baker, R., Hu, X., Rodrigo, M., du Boulay, B. (eds) Artificial Intelligence in Education. AIED 2017. Lecture Notes in Computer Science(), vol 10331. Springer, Cham. https://doi.org/10.1007/978-3-319-61425-0_80
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DOI: https://doi.org/10.1007/978-3-319-61425-0_80
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