Modelling Mobile Interactions: Exploring in-Context interaction to improve interface design (Advert reference: RDF20/EE/CIS/POINTON)

Considerable HCI work involves capturing user behaviour when interacting with devices to understand this interaction, permitting identification of usability problems and improvements in interface design. The ever-increasing use of mobile devices in various situational contexts away from a desk presents a range of novel challenges and possibilities for interface improvements. However, there is a lack of work evaluating interaction in such contexts to inform and shape interface development.

The recent increase in use of mobile devices in preference to more frequently studied (and thus better understood) desktop machines, presents a range of challenges for these evaluations, especially in situations where we need to move with the device. Put simply: we use mobile devices in situations that we cannot use desktops and laptops and these everyday situations (i.e. walking) can often present distractions, dividing our attention as we interact. Research suggests that these situations increase cognitive load and, therefore, may have an impact on performance, increasing the possibility of interaction errors as we hold and alter our grip to complete common tasks.

This project investigates user interaction within everyday situations (i.e., walking whilst using a mobile phone, interacting with a Smartwatch or other wearable devices) with an aim of understanding interaction behaviour. An investigation into mobile interaction behaviour will feed into the design of controlled and natural user studies. Using multiple videos recordings (i.e., mobile screen recordings, head camera and a wide angled camera), capturing behaviour we will develop tools to model and assess in context behaviour. Based upon the recordings we intend to design interfaces that adapt to walking (using phone accelerometers), investigating whether a UI can respond to situational changes (e.g. in walking speed) to improve user experience and reduce interaction errors.

This project is supervised by Dr Matthew Pointon. The second supervisor will be Dr Alison Pickard.

Eligibility and How to Apply:

Please note eligibility requirement:
• Academic excellence of the proposed student i.e. 2:1 (or equivalent GPA from non-UK universities [preference for 1st class honours]); or a Masters (preference for Merit or above); or APEL evidence of substantial practitioner achievement.
• Appropriate IELTS score, if required.
• Applicants cannot apply for this funding if currently engaged in Doctoral study at Northumbria or elsewhere.

For further details of how to apply, entry requirements and the application form, see
https://www.northumbria.ac.uk/research/postgraduate-research-degrees/how-to-apply/

Please note: Applications that do not include a research proposal of approximately 1,000 words (not a copy of the advert), or that do not include the advert reference (e.g. RDF20/EE/CIS/POINTON) will not be considered.

Deadline for applications: Friday 24 January 2020

Start Date: 1 October 2020

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