Adaptive Data Analytics for Aged Care Workers using Personas

Primary supervisor

Anuradha Madugalla

Co-supervisors

Recently, Aged Care has been in the news with the release of Royal Commissions report in to Aged Care and COVID-19. Both these situations highlighted the need of a better understanding of the aged care workforce. This project focuses on understanding the aged care workforce and their diversity in order to present data analytics information effectively.  The project will use Personas to model diverse user needs, and will develop UIs that automatically/semi-automatically adapt to fit these Personas. The developed adaptive UIs will be used by our client company as the basis for their new data analytics product. 

Students will get the opportunity to work with an industry based client, develop the foundation for a real world product and experience in developing adaptive UIs for diverse users. 

     

     

    Student cohort

    Single Semester
    Double Semester

    Aim/outline

    Project Background

    • Aged care workforce consist of multiple roles eg: Nurses, Carers, Doctors, Admin Staff, Finances, C-Level Executives, Residents
    • Workforce has diverse users: multicultural, different education levels, different age levels, etc
    • Adaptable UIs would allow diverse users to reconfigure User Interfaces (UIs) to their needs/automatically adapt to fit the needs
    • Need to understand aged care workforce needs based on their diversity : context of use, frequency, what levels of access they need, languages, etc
    • How to design user-centred adaptive UIs for aged care workers by addressing these diverse needs?

     

    Motivation

    • Monash is working with a client company who is developing IT solutions for 200+ aged care facilities in AUS/NZ
    • Currently we are developing Machine Learning models to be implemented at these aged care centres via the IT company
    • Want to present the Data analytic information and ML models via adaptive UIs

     

    Main Research and Expected Outcomes

    • Consider range of diverse workforce characteristics e.g. age, gender, culture, language, socio-economic status, educational level, emotions, personality, cognitive style
    • Understand diverse features by conducting surveys/interview with aged care workforce
    • Model these via Personas or another modelling technique
    • Develop prototype/actual tool with more attention on Data Analytics UIs
    • Workout how to make UIs adaptive based on diverse user characteristics

    URLs/references

    Luy, C., Law, J., Ho, L., Matheson, R., Cai, T., Madugalla, A., Grundy, J.C., A Toolkit for Building Adaptive User Interfaces for Vision-impaired Users, 2021 IEEE Symposium on Visual Languages and Human-centric Computing (VLHCC2021), 10-13 October, St Louis, USA: https://raw.githubusercontent.com/nzjohng/publications/master/papers/vlhcc2021.pdf

    Jennifer McIntosh, Xiaojiao Du, Zexian Wu, Giahuy Truong, Quang Ly, Richard How, Sriram Viswanathan, Tanjila Kanij, "Evaluating Age Bias In E-commerce," 2021 IEEE/ACM 13th International Workshop on Cooperative and Human Aspects of Software Engineering (CHASE), 2021, pp. 31-40, doi: 10.1109/CHASE52884.2021.00012

    Shakshuki, E.M., Reid, M. and Sheltami, T.R., 2015. An adaptive user interface in healthcare. Procedia Computer Science, 56, pp.49-58

    Gonzalez de Heredia, A., Goodman-Deane, J., Waller, S., Clarkson, P.J., Justel, D., Iriarte, I. and Hernández, J., 2018. Personas for policy-making and healthcare design. In DS 92: Proceedings of the DESIGN 2018 15th International Design Conference (pp. 2645-2656)

    Woods, L., Cummings, E., Duff, J. and Walker, K., 2017, November. The development and use of personas in a user-centred mHealth design project. In Proceedings of the 29th Australian Conference on Computer-Human Interaction (pp. 560-565).

     

    Required knowledge

    • Interest in understanding diverse user characteristics
    • Experience in developing UIs/prototypes would be excellent
    • Interest in making UIs adaptive
    • Good communication in English to conduct user studies with aged care workforce including carers, nurses, C-Level executives etc.
    • Some knowledge in data visualisation/data science