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H Boulton

Biographic Data

ID6511063
NAMEH Boulton
GIVEN NAMESH
FAMILY NAMEBoulton
SIGNATUREBOULTON H
AFFILIATIONSNottingham Trent University
ORCID0000-0003-4671-0182
VERIFIEDYes
TOTAL WORKS3
TOTAL CITATIONS0
AUTHOR COUNT3
EDITOR COUNT0
FIRST PUBLICATION YEAR2016
LATEST PUBLICATION YEAR2020
H-INDEX0
  • Examining the potential impact of digital game making in curricula based teaching

    Open Access•Thomas Hughes-Roberts, Thomas Hughes‐Roberts et al.•ARTICLE•Computers & Education•2020

  • An evaluation of an adaptive learning system based on multimodal affect recognition for learners with intellectual disabilities

    Open Access•Penelope J Standen, David J Brown et al.•ARTICLE•British Journal of Educational…•2020

    Artificial intelligence tools for education (AIEd) have been used to automate the provision of learning support to mainstream learners. One of the most innovative approaches in this field is the use of data and machine learning for the detection of a student’s affective state, to move them out of negative states that inhibit learning, into positive states such as engagement. In spite of their obvious potential to provide the personalisation that …

  • Exploring the effectiveness of new technologies

    Open Access•H Boulton•ARTICLE•Teaching and Teacher Education•2016•References: 9

No prominent works on this page.

  • Exploring the effectiveness of new technologies

    Open Access•H Boulton•ARTICLE•Teaching and Teacher Education•2016•References: 9

  • Examining the potential impact of digital game making in curricula based teaching

    Open Access•Thomas Hughes-Roberts, Thomas Hughes‐Roberts et al.•ARTICLE•Computers & Education•2020

  • An evaluation of an adaptive learning system based on multimodal affect recognition for learners with intellectual disabilities

    Open Access•Penelope J Standen, David J Brown et al.•ARTICLE•British Journal of Educational…•2020

    Artificial intelligence tools for education (AIEd) have been used to automate the provision of learning support to mainstream learners. One of the most innovative approaches in this field is the use of data and machine learning for the detection of a student’s affective state, to move them out of negative states that inhibit learning, into positive states such as engagement. In spite of their obvious potential to provide the personalisation that …

Mathematics education (3 works) · Psychology (3 works) · Pedagogy (2 works) · Social Psychology (2 works) · Affect (linguistics) (1 works) · Affordance (1 works) · Artificial Intelligence (1 works) · Boredom (1 works) · Child Development and Digital Technology (1 works) · Collaborative learning (1 works)

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