Tag: innovation

ALASI2018: Innovating for Impact Workshop

We’re pleased to announce this ALASI 2018 Workshop

Innovating Learning Analytics for Sustainable Impact

Simon Buckingham Shum, Cassandra Colvin, Shane Dawson,
Danny Liu, Pablo Munguia, Yi-Shan Tsai

THE CHALLENGE: INNOVATION + IMPACT

This workshop will explore the strategies that institutions are adopting to balance two key drivers  of learning analytics initiatives:

  1. Research & Innovation: the desire and need to conduct rigorous research (e.g. in order to develop learning analytics that are not available in current products to advance future-oriented teaching and learning strategies; to answer complex questions specific to the institution’s context; to build the university’s research profile)
  2. Sustainable Solutions: the need for robust, usable analytics infrastructure that is trusted by, and useful for, educators, students, the IT division, the data warehouse team, the academic development team, etc… (e.g. to ensure that tools work smoothly, and are easily learnt; to tackle immediate, pressing needs around data; to ensure that data is secure, and reliably captured ).

Typically, these two drivers pull in different directions. Innovative educational technologies typically fail to move beyond the “exploratory, exciting prototype” stage (Scanlon, et al. 2013). In their analysis of the state of the field in Australia, Colvin, et al. (2016) identified two clusters of universities: those who saw analytics as a more research-intensive vehicle for pedagogical innovation, and those seeking vendor solutions for pressing problems (such as student attrition). These conceptions implicate different stakeholders, with different success criteria.

However, are these tensions inevitable, or irreparable?Can the academic invention and rigour of good learning analytics research be harnessed to innovate solutions to strategic problems? Can R&D be accelerated and augmented so that it benefits more end users, more quickly, in sustainable and ethical ways  ? Although far from being solved, progress is being made on these questions (e.g. Buckingham Shum and McKay, 2018). We might also ask how do we advance research in institutions that are not encouraging it, seeing analytics ‘simply’ as a technical solution to be licensed from a vendor?

Please see the full workshop description (pdf), register for ALASI, and post your thoughts here to help seed the event…

 

Architecting Organisationally for Learning Analytics

I got to know Tim McKay in Vancouver at LAK17 (watch his outstanding keynote), and then at greater length when University of Michigan hosted LASI17. As I explained to him what we are doing at UTS with CIC, and learnt more about UM’s Office of Academic Innovation and in particular, the Digital Innovation Greenhouse, it became clear I had lots to learn from Tim and the UM model. So began a conversation which I’m very pleased has crystallised in this article, as we compare and contrast where we’ve got to on the road. We hope that it’s a conversation opener.

Buckingham Shum, S.J. and McKay, T.A. (2018), Architecting for Learning Analytics: Innovating for Sustainable Impact. EDUCAUSE Review, March/April 2018, pp. 25-37. Open Access: https://er.educause.edu/articles/2018/3/architecting-for-learning-analytics-innovating-for-sustainable-impact

Abstract: In light of the significant investments that some colleges and universities are making in their analytics infrastructures, how can an institution architect itself to tackle substantial, strategically important teaching and learning challenges? How can an institution innovate learning analytics for sustainable impact?

From the article:

“Our focus here is on organizational architectures that a college or university’s leadership can consider in order to advance innovative analytics for its own mission and context. We are seeking to open a dialogue on organizational architectures and processes as a way to address educational challenges that often require systemic thinking and change. Such challenges may be faced by many colleges and universities, opening up collaboration opportunities. Moreover, if the innovation-diffusion challenges facing one institution can be taken as a microcosm for the challenges facing the learning analytics field as a whole, organization-level insights may scale to consortia or more open networks.

Surveying the current landscape, we see three broad organizational models that are being used to deliver learning analytics. These three models are largely role-aligned: (1) the IT Service Center model (primarily professional services staff); (2) the Faculty Academics model (primarily faculty researchers); and (3) the hybrid Innovation Center model (a mix of professional services staff and faculty researchers).

To what extent can these three different organizational models deliver both production-grade services and innovation with sustainable impact? We will start by discussing the two “standard” models before moving on to the much less common third model.”

   

Serious Games: Jack Park wins “Breakthroughs to Cures”

Foresight Engine: Breakthroughs to Cures from Foresight Engine on Vimeo.

One of our team, Jack Park, just won Breakthroughs to Cures, a serious game run by the Institute for the Future, to explore the future of medical research. In the opening movie, the US President of 2020 sets the scene for an urgent medical crisis now facing the country, and invites input on how to transform the way in which research is conducted in order to find a cure as fast ass possible.

What makes this interesting is that the game is played by playing “cards” which correspond to conversational moves. With high production values, the game is powered by the Foresight Engine from the Institute for the Future:

“IFTF’s Foresight Engine drives engaged forecasting. It creates a fast flow of micro-forecasts from hundreds or thousands of participants in just a day or two. It’s all about focused insights and innovation—the discovery of social wisdom and outlier ideas.”

Clearly, this resonates closely with our interest in sensemaking in complexity, particularly given the conversational dimension which echoes our focus on scaffolding more reflective discourse through appropriate visual and computational affordances.

In his blog, Jack reflects on the strategy that he adopted in playing the game, and on the nature of the game more broadly. Jack is now exploring the development of gaming engines that intersect even more closely with our work on topic and argument mapping…