Posts Tagged ‘social learning’

A Group-Based Mobile Application to Increase Adherence in Exercise and Nutrition Programs: A Factorial Design Feasibility Study

Novel methods of promoting self-monitoring and social support are needed to ensure long-term maintenance of behavior change. In this paper, we directly investigate the effects of group support in an exercise and nutrition program delivered by an mHealth application called Fittle.

Our first specific study aim was to explore whether social support improved adherence in wellness programs. Our second specific study aim was to assess whether media types (ePaper vs mobile) were associated with different levels of compliance and adherence to wellness programs. The third aim was to assess whether the use of an mHealth application led to positive changes to participants’ eating behavior, physical activity, and stress level, compared to traditional paper-based programs.

Conclusions: The team-based Fittle app is an acceptable and feasible wellness behavior change intervention and a full randomized controlled trial to investigate the efficacy of such an intervention is warranted.

A Group-Based Mobile Application to Increase Adherence in Exercise and Nutrition Programs: A Factorial Design Feasibility Study

by Honglu Du, Anusha Venkatakrishnan, Michael Youngblood, Ashwin Ram, Peter Pirolli

Journal of Medical Internet Research (JMIR) mHealth uHealth, 4(1), 2016.
mhealth.jmir.org/2016/1/e4/

From Dr Google, to Dr Facebook, and beyond…

I recently appeared on the ABC Health Report radio program.

Joel Werner: Do you ever go online to search for symptoms that you’re experiencing? I do it all the time, and it’s a trend that has picked up the nickname ‘Dr Google’. For Ashwin Ram, Dr Google is just one step on the path to future healthcare…

The Intelligent Web: Shaping Behavior at the Intersection of Health, Wealth, & Choice

The web is evolving from information (portals) to interaction (social/mobile). The next stage will be about influence: shaping attitudes and behaviors. To do this effectively requires a new kind of technology: user modeling. It also requires an innovation methodology that is fundamentally about people, not technology.

I discuss three big ideas in innovation for consumer engagement and behavior change, and illustrate using examples from healthcare, education, and financial services.

Invited keynote at Amplify: Business Innovation and Thought Leadership, June 2013, Australia.

SLIDES:

Health : Healthcare :: Learning : Education

With the advent of open education resources, social networking technologies and new pedagogies for online and blended learning, we are in the early stages of a significant disruption in current models of education. ‘Learning’ is beginning to peel away from ‘Education’ as a separate market, with its own set of opportunities and challenges for practitioners, technologists, and entrepreneurs. While ‘education’ is driven by schools, colleges, and governments, ‘learning’ focuses on empowering the individual to take charge of their learning.

Interestingly, a similar phenomenon is occurring in healthcare, fueled by the confluence of similar trends and technologies: open health resources, social networking technologies and new methodologies for consumer engagement. ‘Health’ is starting to emerge as a separate and disruptive market, with its own opportunities and challenges. While ‘healthcare’ is driven by providers, payers, and governments, ‘health’ focuses on empowering the consumer to take charge of their health and wellness. 

In this talk, I discuss recent trends in these two industries, explain why they are analogous, and discuss opportunities for user experience, big data, analytics and social capital research. I provide examples of social, mobile, and game technologies that are creating the disruption, and highlight key research challenges that are yet to be addressed.


Invited talk at UC Berkeley, iSchool “Thought Leaders in Data Science and Analytics”, April 11, 2012. 

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Transforming the Industry: Watson in Education

Watson, named after IBM founder Thomas J. Watson, was built by a team of IBM scientists with valuable help from research partners from Carnegie Mellon University, University of Texas, University of Southern California, University of Massachusetts, University of Trento (Italy), MIT, RPI, and the University of Albany. The team set out to accomplish a grand challenge—to build a computing system that rivals a human’s ability to answer questions posed in natural language with speed, accuracy and confidence. Watson passed its first test on Jeopardy! in February 2011, but the real test will be in applying the underlying systems, data management and analytics technology across different industries, especially in education.

Invited panel presentation at IBM Watson in Education: Transforming the Industry, IBM Almaden Research Center, November 16, 2011

Crowdsourcing: From Phenomenon to Business Model

Crowdsourcing is changing both the way we work, as well as the way Internet applications are designed and delivered. It’s no longer just the domain of technologists (who can now achieve breakthroughs together never before achievable); crowdsourcing is now ripe for enterprise professionals to understand and leverage the possibilities for their business goals.

From Wikipedia and YouTube, crowdsourcing has moved to a $5B “crowd worker” industry with applications proliferating for productivity, research, marketing, advertising, creative development, corporate workflow management, language translations, and much more — see a list of projects here.

I discuss social networks as a kind of crowdsourcing, with unique benefits and challenges.

Invited panel presentation at PARC Forum, Palo Alto, CA, November 10, 2011
 

View the panel discussion:

www.parc.com/event/1456/crowdsourcing-ceo-expert-panel.html

SoCS Computational Models and Techniques: A Case Study

I spoke today at the NSF Workshop on Social-Computational Systems (SoCS) on Mike Pazzani‘s Computational Models and Techniques panel with Tuomas Sandholm, Lise Getoor, and Tina Eliassi. We were asked to address the questions of what computation can teach us about socially intelligent systems, and what problems are encountered when applying existing technologies to such systems.

I focused on two key SoCS challenges : impedance mismatch, and research-at-scale. Let me explain.

What can computation teach us about SoCS? If we begin with technology, we’ll encounter the key challenge of “impedance mismatch” between people and technology. The technology, however good, may not address people’s needs. Instead, let’s reverse the question: What do socially intelligent systems teach us about computational technology?

Consider, as a case study, the problem of education: building a SoCS system to help students learn. Our first pass was a collaborative learning site with a state-of-the-art collaboration platform, a kind of “Google Docs meets WebEx meets Etherpad meets Skype on steroids”. While the site was useful, we learned that students didn’t use most of the features we had built. The issue was impedance mismatch: the technology did not address education problems from a student perspective.

What, then, are these problems? There are two: Access (scale) and engagement. To tackle the impedance mismatch, we need to design technology that provides the right affordances (in the Gibsonian sense) for student behaviors that address those problems.

We created a vision for Open Social Learning that blends, not Google Docs and WebEx, but Facebook and World of Warcraft. With funding from NSF, NIH, GRA, and Gates/Hewlett NextGenLC, and partnerships with MIT, Yale, NYU, and many others, we rethought the site from Education to SoCS to Learning Theories to Design Principles to Affordances to Architecture to User Experience (UX) to Mechanisms. (See slides and references below.) This process resulted in a fundamentally disruptive idea, one driven not by technology but by the SoCS it was to support.

Only then did it make sense to think about Computation: really real-time collaboration technologies for a highly interactive experience; intelligent recommender systems to help learners connect with relevant content and other learners; mining and analytics to assess learner outcomes; and reputation techniques to establish social capital.

The new OpenStudy.com is an Open Peer-to-Peer Social Learning Community, a place that matches learners studying the same things into live “massively multiplayer study sessions“. The problems of access (scale) and engagement are addressed through two mechanisms: A Luis von Ahn approach where the social community scales itself, and a kind of gamification in which everyone is on the same team.

Great idea—but how do we know it works? The education literature is full of great ideas that don’t work in practice. SoCS data research involves studying large-scale communities; the same applies to SoCS technology design. This is the research-at-scale challenge. Laboratory studies don’t prove much; the research fundamentally requires scale.

After 9 months, OpenStudy has grown into a vibrant community that both provides value to its users and serves as a “living lab” to study and validate the ideas. We’re continuing to research how new technologies can be combined to address the problem of education in a manner that is highly scalable yet interactive and engaging.

To understand what socially intelligent systems teach us about computation, then, requires a new methodology comprised of old ideas about design thinking brought into the new world of Social-Computational Systems at a massive scale.

READINGS

P Adams (2009). Designing for Social Interactions.

Terry Anderson (2007). Distance Learning: Social Software’s Killer App?

J Daniel (1996), cited in JS Brown (2007). Minds on Fire: Open Education, The Long Tail, and Learning 2.0.

RA DeMillo (2011). Abelard to Apple: The Fate of American Colleges and Universities in the Twenty-First Century.

R Friedrich, M Peterson, A Koster (2011). The Rise of Generation C.

Gates Foundation study: JM Bridgeland, JJ Dilulio Jr, KB Morrison (2006), The Silent Epidemic: Perspectives of High School Dropouts.

D Thomas & JS Brown (2011). A New Culture of Learning.

More readings at: Massively Multiplayer Online—Learning?

SLIDES

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