Much ADO about Education and Technology

Maggie: What’s the buzz……tell me what’ happening
Vijay: Much ADO about education and technology

October-November is typically the season for academic technology gatherings. I was at the Educause annual conference and the Open Ed conference in Utah (a more recent phenomenon than the former long-standing mega-event but potent nevertheless). I had the opportunity to participate/present at two other events – the Pan IIT meet in NYC and more recently a meeting on Social Learning Spaces in Barcelona, organized by the Education Ministry,

Analytics, Data and Openness were the dominant themes that travelled across the conferences and dominated the discussions – indicative of what the educational enterprise and marketplace view as being the loci of influence, opportunity and concern.

The Data Dimension
“In God we trust; all others must bring data.” (statement widely attributed to the late Professor William Edwards Deming, scholar and management guru at large)

Well, in the world of education boat-loads of data are now being brought to us–through sensors, websites, learning management systems, personal response systems (clickers), tweets and through portfolios to name just some of the growing number of sources.

As Tony Hey, one of the leaders of the e-Science movement pointed out in his talk at Educause, data deluge is affecting all disciplines requiring new computational capabilities (tools, technologies, and platforms) and skills to capture, manipulate, visualize, integrate and manage (including preservation) large amounts of data. For instance, in order to be located and captured by search engines and data mining software tools, the increasing flood of data will need to be annotated with relevant metadata giving information as to provenance, content, conditions and so on in order to derive useful value. The data explosion has important implications for various aspects of educational practice not only across the sciences but also the humanities and the social sciences, which are also becoming data-intensive domains.

I believe the time is ripe for a discourse on the implications for teaching-learning in a world of data abundance/ubiquity (for example the shift to statistically and pattern based deductive approaches as different from induction).

The Analytics buzz is certainly on. One important dividend that derives directly from the data explosion is that of Analytics, specifically Learning Analytics.

Learning Analytics refers to the analysis of a wide range of data produced by and gathered on behalf of learners in order to assess academic progress, predict future performance, and spot potential issues. The section on Analytics in the Horizon Report 2011 from the New Media Consortium provides a useful overview of this topic.

The increased focus on accountability in education is certainly an important driver. But more importantly there is the opportunity to tailor materials and interventions based on student performance. Learning analytics can illuminate complex situations and help identify at-risk learners. Khan Academy provides some good examples through its fine-grained recording and display of student performance.

The growing attention to online learning has also fueled the interest in incorporating Analytic capabilities, including predictive modeling, in both learning management systems like Moodle, Sakai, Desire to Learn, Canvas etc., as well as other applications such as those for online collaboration, which are capturing a considerable amount of data. The challenge (and caution) is to be mindful of the difference between access metrics (frequency of posting, number of logins, page hits) and those that are indicative of learning performance. A new generation of tools such as those directed toward evaluating the qualitative attributes of discourse and discussions, such as the level of engagement and substantive contributions, can provide valuable insight into leaning activity and behaviors. With the ease of data collection and the increasing reliance to leverage it for performance assessment comes the risk of slipping into a very mechanistic and simplistic view of assessment and learning that glosses over the complexities of learning and cognition as well as the systemic considerations needed for educational success.

A macro perspective on Analytics suggests the use of data mining and statistical techniques based on large-scale data collection (including data that institutions have been gathering traditionally over the years) might provide valuable insight into what is actually happening in the learning process and suggest ways in which educators as well as institutions can make improvements. As an example, the Next Generation Learning Challenge (NGLC) is exploring the possibilities that can be achieved by modeling learning interactions based on large-scale data collection.

Openness outed! Any discussion of abundance and Analytics of course brings me to the other big influence that drew significant conference attention, namely Openness. Given my interest and work in this area over the past several years, it is understandable that I feel heartened (dare I say, relieved) by the amount of airtime (presentations, forums) devoted to discussing different dimensions of Openness (Access, OER,) in major conferences like Educause. What is noteworthy though is that the discourse is being directed to addressing issues and conditions for Openness to be a sustainable, transformative influence on education. For past pleas that this should happen you may want to see the recommendations presented in the Conclusions chapter of Opening Up Education. (My apologies for any tone of I told you so and the shameless self-promotion – entirely unintended).

There are many exciting developments in the world of open education resources beyond the fact that OER, including but not limited to Open Courseware, are becoming extensively available across the world. Of particular note is the Open Textbook movement that is gaining legs and helping address a significant obstacle for educational access.

Openness is being employed as a powerful driver for addressing large problems of educational access and quality. One example of this is the Kaleidoscope Project. The project involves seven community colleges collaborating to create courses using existing OERs, with each course being developed by at least two partner institutions (Full disclosure – I participate as an advisor on this project). The project so far has demonstrated a reduction of 98.7% in cost/course/student from $41.50 to $.75 per student, a one-term savings of $61,507. The focus however is not only on the cost-effectiveness outcome but also on improving the course design and learning results based on analysis of embedded assessments and deeper learning results

Overheard: Some of the key messages heard in regards to Openness in education at these gatherings:

• OER are a fundamental infrastructure for learning and teaching (formal, informal, online, blended) and should be supported as such by funders and policymakers in the education, research, and culture domains. (Malcolm Brown, JISC)
• Develop ecosystem to drive OER from the fringe to the center. This requires: OER to be directed toward significant outcome improvements and provide best in-class examples; infrastructure to reduce barriers to quality including data and interoperability standards; incentives to reduce regulatory barriers and to make performance matter. (Jim Shelton, U.S Dept. of Education)
• Direct the Open movement toward addressing significant challenges such as the College Completion Challenge, the Quality Challenge, the Funding Challenge (State budget cuts; higher ed tuition and fees have gone up twice that of healthcare) and the Demographic Challenge (Increasing diversity, Low academic readiness). (Josh Jarret, Gates Foundation).

These are solid recommendations and necessary conditions to reify my own belief that network enabled open education can be the central modality for delivering high quality educational opportunity at scale.

Of course, there were other important and heavily discussed topics at these events. Not surprisingly, Cloud services and Privacy are two important topics of great interest and consequence to the academic community, given a landscape increasingly characterized by abundance (content and community) as well as a tendency and need to share (Open).

Talking about Open and Cloud services reminds me that I would be remiss if I did not mention that the race to open the LMS marketplace is on even if openness is interpreted differently by the various systems. The latest entrant is Pearson with their announcement of Open Class, which is well integrated with Google’s Apps for education although it is not a shared product. Following on the heels of this, plans were announced to add a “Share” button that will let users make learning materials free and open online. They certainly enrich (even if confusingly) the marketplace of LMS offerings. My hope is that they do not further distract us from the important question which is NOT “What is the right LMS” but how do we build platforms that allow us to take advantage of a technology landscape that will include growing numbers of educational applications, platforms and content sources that do not simply co-exist, but integrate meaningfully in support of the complex and changing needs of diverse educational activities.

Finally, I am happy to note that educational inventiveness and entrepreneurship is alive and well and has even found mainstream acknowledgment – over 20 startups were presenting in the exhibit area at Educause! And what better evidence of innovativeness inspired by openness than CaPRéT (the Cut and Paste Reuse Tracking tool) that Justin Ball and Brandon (MIT) demoed at Open Ed. Stay tuned for more on this.

By Vijay Kumar, Senior Associate Dean of Undergraduate Education and Director, Office of Educational Innovation and Technology at MIT and member of QFI’s Program Advisory Group for Education Technology and Innovation