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Lecture 2 - Data Driven Personalisation
Page last edited by Per Bækgaard (pgba) 08/09-2019
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08:00-08:45 | Feedback and Lecture in 306#035 |
08:45-11:00 | Group work in 324#030, 040 and 060 |
11:00-12:00 | 3*20 min presentations/feedback on group work in 324#030, 040 and 060 |
Upload one PDF per group outlining how you would use collected (user) data and input to improve your "hearable" system. This should minimally be in the form of extending your system to allow validating/comparing designs or behaviour and learning about your users, but even better by making your system adapt to individual preferences learned from user behaviour. Do this by 1) sketching goals, activities and tasks in a user story map as hypotheses that can be validated 2) and as a prototype app described by a working link to a functional Marvell/POP app wireframe/prototype.
Hand in by Thursday September 13 at 19:00 to the peergrade.io course page and subsequently individually review the projects you have been assigned on peergrade before Friday September 14 at 23:00.
NOTE: Remember to update and include also 3) your lean business canvas for the app in the PDF.
NOTE2: If easier that way, you may also include an additional slide that details how you're e.g. planning to do your data collection (A/B tests, learning from data, ...)
Jeff Patton: "User story mapping" Chapter 1 (free sample chapter 1)
Johansen et al: Rethinking Hearing Aid Fitting by Learning From Behavioral Patterns