Help Table

A system supports older adults in learning how to use smart devices

Project Brief

I joined Accessible Computing Technology Laboratory as a full time HCI researcher after I completed my master's degree at McGill in 2019, and I was advised by Prof. Karyn Moffatt and Dr. Carolyn Pang on the Help Table project. Our work was accepted at 2 leading HCI conferences - ASSETS19 and GI19

My contributions: 

  • Developed and iteratively evaluated high-fidelity interactive interface prototype to demonstrate research-driven design ideas using Axure RP.

  • Conducted online survey and interviews to understand user needs, and facilitated observations to gather user feedback and insights on the prototype design.

  • Created and refined user personas with different goals, needs, and preferences to help influence key features and design elements.

  • Led a design thinking workshop with a UX designer to generate new design ideas and drive change.

  • Computed descriptive statistics from survey data, analyzed audio recordings to extract design recommendations, and presented findings to diverse audiences at leading HCI conferences.

Research Questions: 

In terms of adopting and learning to use new technologies, how do older adults: perceive the experience, decide which ones to adopt, and approach learning?​ 

 

How can we design interactive technology to support the needs of older adults in learning to use smart devices for health information management?” 

Methods

1

2

3

4

Online Survey:

 

Participants completed a 15-min online questionnaire (n=42) mainly focused on their general experiences with using and learning to use personal wearables. Our survey was open for 10 weeks. 

Semi-structured Interviews:​

We also conducted in-person and phone interviews (n=27), which lasted between 45-60 min each. Completed over a 7-week period, the interviews were semi-structured and focused on participants’ experience with technologies, their motivations for adopting new technologies, and their personal health information management practices. 

Data Analysis & Main Findings:

​About 34 hours of audio recordings from our interviews were transcribed and analyzed, along with notes taken during each interview. We focus primarily on the qualitative results from our semi-structured interviews, bringing in descriptive statistics from the survey selectively to provide additional context. Help Table applies our survey and interview results as follows:

 

  • Help Table instructions are concise and use simpler language because participants in our survey and interviews preferred concise, step-by-step instructions and simple one-pagers over more detailed (and complicated) instructions. 

  • Help Table supports the top four preferred learning methods: internet (via an integrated Google Search), trial and error (through feedback), instruction manuals (through step-by-step and video instructions), and children (through video chat). 

  • Help Table shows instructions around the device to avoid attention splitting and make instructions more concise and clearer (more closely tied to device). 

 

  • Help Table videos are designed to be brief so that participants can follow along and remember steps easily

Design of Help Table:

From our findings, we developed Help Table, which leverages a 40” tabletop display to integrate support into one visual space, while also supporting older adults in learning how to use multiple devices that must be configured to work together (e.g., a smartwatch synched to a tablet).

​Over a six-month period we iteratively sketched, designed, and built the Help Table prototype, drawing from our findings from the online survey and semi-structured interviews. The key features include: 

  • A collaborative learning option through which older adults can receive remote support,

  • Support for the integrated learning of multiple smart devices, notably a smartwatch and tablet,

  • Support for a flexible range of learning approaches, including trial and error,

  • And integration of these supports into a single visual space via a 40” tabletop display. 

11.png

Sketch of Onboarding Process V.S. Sketch of Managing Personal Health Information

pictuer

Design of Help Table, including learning topics, remote video support, and interactive instructional information.

P1.png

P1: Collaborative (Child supports older adult)

p2.png

P2: Collaborative (Spouse supports older adult)

p3.png

P3: Individualized (Older adult learning alone)

5

Video Prototype Interviews & Design Workshop: 

 

Using a video prototype of our design, we revisited requirements with our interview participants. We also conducted a design thinking workshop with our lab members to seek more feedback on the current design. The goal was to test and help us iterate on the design of Help Table. 

6

New Design:

Based on the findings we collected from the video prototype interviews and design workshop, we redesigned the prototype as shown below.

ABOUT

I'm Collin. I am a UX Researcher at Kinaxis, a supply chain management software company based in Ottawa, Ontario. 

 

Previously, I was an Accessibility Researcher at McGill University's Accessible Computing Technology (ACT) lab, advised by Prof. Karyn Moffatt and Dr. Carolyn Pang. My research focused on designing an interactive tabletop display to support older adults in learning how to use smart devices. 

I hold a BA in Communications from University of Washington and an MS focused on Human Computer Interaction from McGill University. I am passionate about studying, designing, and building new technologies that can better accommodate a diversity of needs.

CONTACT

I am always looking for new and exciting opportunities. If you enjoyed looking through my work and would like to know more about me, please contact me!

Email: zhiqin.wang@mail.mcgill.ca

Phone: +1.613.700.5491

​2020 Collin Wang