863 research outputs found
Balancing independence and safety: the challenge of supporting older people with dementia and sight loss
Special Issue on participatory research with older people with a mental health condition and/or dementia: tensions and challenges
Attitudes and support needs of Black Caribbean, south Asian and White British carers of people with dementia in the UK
An interpretative phenomenological analysis of the experience of receiving a diagnosis of bi-polar disorder
“Physically it was fine, I’d eat what normal people do. But it’s never like this in my head”: A qualitative diary study of daily experiences of life in recovery from an eating disorder
Qualitative diary methods in mental health research:A scoping review and recommendations for research and re-porting
A qualitative study of informal caregiver perceptions of the benefits of an early dementia diagnosis
Therapist self-disclosure in positive psychotherapy for psychosis
© 2020, British Psychological Society. All rights reserved. Setting boundaries is common in therapist self-disclosure. This qualitative study examined attitudes and experiences of therapists towards self-disclosure during a positive psychotherapy for psychosis research trial. Participants reported therapeutic benefits but discussed challenges with retaining personal privacy while ensuring their authenticity
How Teachers Conceptualise Shared Control With an AI Co-Orchestration Tool: A Multiyear Teacher-Centred Design Process
Artificial intelligence (AI) can enhance teachers\u27 capabilities by sharing control over different parts of learning activities. This is especially true for complex learning activities, such as dynamic learning transitions where students move between individual and collaborative learning in un-planned ways, as the need arises. Yet, few initiatives have emerged considering how shared responsibility between teachers and AI can support learning and how teachers\u27 voices might be included to inform design decisions. The goal of our article is twofold. First, we describe a secondary analysis of our co-design process comprising six design methods to understand how teachers conceptualise sharing control with an AI co-orchestration tool, called Pair-Up. We worked with 76 middle school math teachers, each taking part in one to three methods, to create a co-orchestration tool that supports dynamic combinations of individual and collaborative learning using two AI-based tutoring systems. We leveraged qualitative content analysis to examine teachers\u27 views about sharing control with Pair-Up, and we describe high-level insights about the human-AI interaction, including control, trust, responsibility, efficiency, and accuracy. Secondly, we use our results as an example showcasing how human-centred learning analytics can be applied to the design of human-AI technologies and share reflections for human-AI technology designers regarding the methods that might be fruitful to elicit teacher feedback and ideas. Our findings illustrate the design of a novel co-orchestration tool to facilitate the transitions between individual and collaborative learning and highlight considerations and reflections for designers of similar systems
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