Effective use of data is vital for success in today’s business world. In education, Analytics (or Learning Analytics) is becoming a hot topic, promising to disrupt and transform education and learning. I have written an article to address some current trends and issues on analytics in education for TEL-Map, a European funded support action project, intended to help stakeholders develop roadmaps and work towards actually implementing desired future for TEL in Europe, in which CETIS has been involved. In this overview article, I did a short detour to the business world for some examples of analytics, then I looked at how education has approached the phenomenon, explored some practices, and raised some concerns about the downside of this trend. The full article is available at the TEL-Map project portal – Learning Frontiers.
At the “Emerging Reality: Making sense new models of learning organisation” workshop at the CETIS conference 2012, Bill Olivier from Institute of Educational Cybernetics at the University of Bolton presented a scenario of “ Open Higher Education” which was developed by a group of participants from the UK HE sector. Having been involved in the UK OER programme, looking at the trends and development around OERs and open education in HE, it was really interesting to see this scenario emerging as one of the outcomes of the meeting of a UK HE cluster through the modified Future Search Method adopted by the TEL-Map project.
During a meeting at Nottingham, prior to the CETIS conference, the TEL-Map UK HE cluster identified some 80 trends and drivers impacting on the future of TEL in UK higher education. The group rated them for Impact/Importance and consolidated the high impact, high uncertainty trends and drivers into two overarching but mutually independent axes: ‘Variety of universities’ and ‘Student demands’. This cross-impact analysis resulted in these two axes placed to develop four context scenarios, namely Oxbridge Model, Traditional University Model, De-Campus Model and Open-Ed Model.
The Open Higher Education scenario was identified from the bottom right quadrant of the scenario diagram above. In this scenario, emerging leaders include the OERu, P2Pu and Udacity. The common features of this scenario’s learning model include low cost content and peer learning support, with expert support when it is needed. Initially, students choose this form of HE because they don’t have to pay for the services provided by universities that they cannot benefit from, such as sports halls, students societies, classrooms and libraries, etc. This model expands as more and more people find online university courses affordable & practical and more students see its benefits, including those who would have attended traditional university.
Along with the Open Higher Education scenario, three other thought-provoking and interesting scenarios were presented and discussed, including, Christian Voigt’s “Technology Supported Learning Design”; Adam Cooper’s “The Network of Society of Scholars” and New Models of LearningideascaleTEL-Map project website
This wordle was generated from texts abstracted from mentions of key technologies in a collection of more than 20 articles and blogs on technology predictions for 2012, which I gathered through Google search recently. These predictions were produced mainly by individuals and organisations from the IT and business sectors.
First, I extracted the main topics from each article and blog as the basis for creating the wordle. Then I did a bit editing work in order to create a more accurate wordle presentation. For example, I added “-” between two or three words (e.g. cloud computing as cloud-computing) or “s” to words in the singular (e.g. tablet as tablets) and using a common name for same technology that has appeared in different forms (e.g. using cloud-computing instead of cloud service or cloud based technologies).
It probably comes as no surprise for most people to see which technologies appeared and their order in the wordle. However, there are several themes repeatedly mentioned in those articles and blogs. On the one hand these reflected the most popular technology trends in 2012 predictions and on the other hand they signal potentially important implications of these technological development in education, teaching and learning contexts. These themes are summarised:
1. Mobile and tablets are continuing to grow and BYOD (Bring Your Own Device) is increasing as more people use their own devices for work. Organisations will embrace that trend and proactively develop a stance and policies on BYOD to better manage, secure, maintain, and deploy mobile devices and applications within their organisations.
2. TV is being integrated with other devices to make it “mobile, local and social”, e.g. controlling your TV with smartphones, tablets and Microsoft’s Kinect. Internet TV and IP TV become embedded into the mainstream. Apple will launch Apple iTV to provide the next generation of television experiences.
3. Cloud computing continues to be the top IT investment priority for organizations; the scalability, flexibility and IT cost benefits of cloud computing become more apparent.
4. Big data and analytics are going mainstream. Businesses and government agencies alike are adopting big data and advanced analytics technologies to build innovative new services, improve service levels, and drive greater efficiency to provide better service for customers, open new markets and reduce costs.
5. A massively connected world: The Internet of things, Near Field Communications (NFC) and Context-aware computing are making a seamless link between data and various applications and services around us, e.g. remote health monitoring and diagnosis, mobile wallet, augmented reality (AR);
6. The next generation of social networks, e.g. Facebook, Google+ and Twitter, will continue to redefine how we interact with each other online. Advanced social networking technologies will be widely used in business to enhance collaboration between employees and improve efficiency and overall service levels in organisations.
7. Desktop 3D printing has caught the attention of the public. There will be cheaper and improved 3D printers, innovative user interfaces for model manipulation which make it possible for them to be used at home, schools and universities.
8. Others: image search and voice recognition goes mainstream; apps become an essential tool for businesses; HTML5 becomes important, etc …
This work intends to provide a quick update to the 2011 JISC Observatory’s “Technology Forecasting Literature Review”. Although we have covered most of the topics in the report, several technology trends appearing in the wordle might be worth further investigating, e.g. Big Data, 3D Printers, the next generation of TV, etc. For more detailed analysis of the technology predictions in 2012 and onwards from the IT and business sectors, please go to the google docs to see all the topics extracted from the articles and blogs and follow the links to the original websites. It is also worth noting that the NMC has just released its NMC 2012 Horizon HE Report, which identified mobile apps and tablet computing as technologies expected to enter HE mainstream in one year or less.
With the growth of the internet, mobile technologies, multimedia, social media and the ever increasing Internet of Things, the data we can mine effectively as well as the types of information we can process from that data are evolving rapidly. In a recent report, McKinsey Global Institute estimated that the amount of data increase globally is roughly 40%. The term “Big data” has emerged to describe “datasets whose size is beyond the ability of typical database software tools to capture, store, manage and analyse” (McKinsey, 2011). Big data represents data sets that can no longer be easily managed or analysed with traditional or common data management tools, methods and infrastructures. According to Gartner, the challenges of Big data come from three dimensions:
Volume: means the increase in data volumes within enterprise systems will cause a storage issue and a massive analysis issue.
Variety: means different types of information from various sources are available and need to be analysed, including databases, documents, e-mail, video, still images, audio, financial transactions, etc.
Velocity: means both how fast data is being produced and how fast the data must be processed to meet demand. This involves streams of data, structured record creation, and availability for access and delivery. (Gartner, 2011)
These characteristics bring new challenges to traditional Business Intelligence (BI) and analytics and require new approaches, new software tools, and new skill sets to manage and extract value from new, complex, unstructured and voluminous data sources.
Big Data has made its way onto the It is predictable that big data will provide new opportunities for data service providers, content/information publishers, and software companies to offer optimized services and platforms that help organizations make better business decisions. For example, Oracle has developed a comprehensive Big data strategy, which includes releasing Hadoop data-management software, a NoSQL database and R analytics. IBM has also unveiled InfoSphere BigInsights platform for big data analysis. Many governments, sectors and corporations have seen Big data as a key strategic business asset of the future development and have started to experiment with Big data technologies as a complementary or alternative form to traditional data management and analysis.for mainstream adoption in 2 to 5 years. According to Gartner, “By 2015, companies that have adopted big data and extreme information management will begin to outperform unprepared competitors by 20% in every available financial metric”.
How will HE institutions address the opportunities and challenges for Big data in education? According to MGI Big Data report, Education in the US is the tenth largest data sector, which stores and manages approximately 267 petabytes of information. However, compared to other sectors, Education faces higher hurdles because of the lack of a data-driven mind-set and available data. With an increased focus on such issues as data-informed accountability and transparency, emphasising student retentions and academic achievements, teacher performance and added value and productivity in education, big data will play an important role in guiding education reform, helping institutions to develop business strategies and assisting educators to improve teaching and learning. Predictably, while all sectors are facing the challenges of making effective use big data, several general development trends for big data in education can be detected for the future, for example:
- One of the key challenges for big data in education is to develop data informed mind–sets and to make sure that educational data are effectively managed and available for end users. It is clear that the use of Big data is different from traditional data mining, and it requires new approaches, new tools, and new skills to deliver the promise of BI and analytics. In order to optimise the use of big data, institutions will need not only to put the right talent and technology in place but must also structure their workflows and incentives to promote data informed decisions at all levels.
- One of the real opportunities for big data in education is to integrate information from multiple data sources. This means working with significantly greater data sets to store and mine all the unstructured and structured data to which institutions have access. These will include scientific research, library resources and administrative information, as well as data sets collected via LMS platforms and other sources to help institutions make smart decisions that lead to real success on e.g. development strategies and organisation management, student recruitment, international markets and intelligent curricula.
- A shift from data collecting to data connecting. The potential of big data and analytics in education is to connect the unstructured and structured data effectively to identify and leverage the real learning patterns that lead to student success. Mining unstructured and informal connections and information produced by students in this way, including blogs, social media networks, machine sensors and location-based data, will allow educators to uncover facts and patterns they weren’t able to recognise in the past.
- A new way to manage and use much larger sets of real-time student data. The real-time, contextual data could be used to provide real-time intelligence about learners and their collective/connected learning environments and contribute to open-ended and student-directed learning. For example, mobile analytics can be used to take advantage of the contextual data including tracking learner attention, behaviour management, truancy, teacher performance evaluation and school dashboards, etc.
Big data related technologies and applications:
- Cloud computing,
- Linked data
- Stream processing
- Google’s MapReduce and Google File System
- MapReduce & Hadoop
- InfoSphere &BigInsights
Big data: The next frontier for innovation, competition, and productivity. http://www.mckinsey.com/mgi/publications/big_data/pdfs/MGI_big_data_full_report.pdf
“Big data” prep: 5 things IT should do now. http://www.computerworld.com/s/article/9221055/_Big_data_prep_5_things_IT_should_do_now
Hype Cycle for Emerging Technologies, 2011, http://www.gartner.com/DisplayDocument?ref=seo&id=1754719,
Penetrating the Fog: Analytics in Learning and Education. http://www.educause.edu/EDUCAUSE+Review/EDUCAUSEReviewMagazineVolume46/PenetratingtheFogAnalyticsinLe/235017
HE institutions, from architecture and business to pedagogy and content delivery, have been designed for the classroom-based lecture model. However, rapid technological change now means that lecture capture technology is becoming widely available and lecturers can easily record their presentations so that students may view them anywhere, anytime. Millions of audios and videos of OERs have been produced by subject experts and are freely available at iTunes U for teachers and students to use and re-use in their teaching and learning. And students can search and find most of the information they need on Google, YouTube and social networks via their mobile phones or laptops. As a result of this ever-increasing student access to technology and online learning content, institutions and educators are being forced to rethink how student learning can be facilitated to make class time and activities as relevant and valuable as possible. A term “flipped classroom” has been articulated by some education practitioners, to describe a reversal of the traditional teaching method that gives students video lectures to watch in their own time at their own pace at home and then go to their classrooms for discussions, coaching and interaction with teachers and between peers. The idea of the “flipped classroom” has been brought to the public by the popularity of Khan Academy and its founder, Salman Khan’s TED Talk on reinventing education via using videos.
There is an ongoing debate on the concept of “flipped classroom” and its implications for education, in particular, most recently in the US school sector. A growing number of have been shared by advocators and practitioners but some confusion, critique, and hype also need to be addressed. As with any technology related educational practices, technology itself is only a tool that can be used to address some problems and challenges in education. In this case, the flipped approach offers a simple solution, for using technology in teaching and learning, that helps educators move from ‘sage on the stage’ to ‘side-by-side learners’ in the classroom. To many educators, however, the idea behind “flipped classrooms” may not be new and it could be interpreted and implemented in different ways in different learning contexts.
In general, it could be argued that technology has failed in its promise to transform education, especially, when PowerPoint and whiteboards have come to dominate classrooms, reinforcing the lectured–based class model. However, the “flipped classroom” may provide a new way to think about the role and relationship between technology, teacher and students. In essence it would allow the classroom to be used for interactive discussions and collaborative activities while using technology before, after and outside of the classroom. In this way, technology can be employed in radically different ways to support educators to explore new pedagogical approaches to meet individual student needs.
Eventually, the rapid and continuing developments in the areas of lecture capture technologies, OER, digital textbooks, search, social network tools and mobile devices will change students’ learning experience within and outside the classroom. The flipped approach provides a good example of how technology might be used to disrupt the existing education model and traditional education practice. However, to make real change for a better education system we need also to ‘flip thinking’ at all levels of education sector, from practice, method to process and business models, in order to take full advantage of these disruptive technologies in institutions .
In September, at the International Open Forum of e-Learning and Standardization in Shanghai, we organised a TEL-Map workshop to identify the main drivers in the use of technology in education, explore possible future scenarios of Technology Enhanced Learning and develop roadmaps to desired futures. The workshop provided a unique opportunity to engage people, both Chinese experts and experts participating in the 24th meeting of ISO/IEC JTC1 SC36 taking place at the same venue. Three main questions were used to prompt discussion and to enable the participants to pool their thinking and ideas about the current state and future vision of TEL, and how to achieve the desired future. These main questions were broken down into sub-questions as below:
1. What is the current state of Technology Enhanced Learning (TEL) in your country or region? (drivers)
- What are the most interesting developments in TEL you know of?
- What are the main drivers that are likely to impact on TEL in your country or region over the next few yea
- What would you identify as the significant lessons learned from the past in your country or region?
2. What is your vision for the future? (input to creating a shared desired future/s)
- What kind of innovation in learning technology would you consider to be desirable?
- What would you like to see people doing with technology to benefit education?
- What kind of culture and organisational structures do you think that educational institutions will need in order to deliver the desired future?
3. How do you see this vision being achieved? (roadmap)
- What would you see as priority actions which should be carried out soon?
- What are the main emerging developments you see supporting this?
- What are the main problems and obstacles that you see along the way?
Participants worked in groups with colleagues from their own country or region. Firstly, they were asked to write down their own answers to the questions on post-it notes and stick them on a flip-chart. They then shared each other’s views and add any new ideas emerging from the discussion onto the flip-chart. Finally, participants agreed the most important point for each question and moved it to the top of the flip-chart. The participants also had the opportunity to look at the outcomes from other groups.
Around 20 people attended the workshop, in two main groups – China and European/Asia/US. We had a lively discussion in both groups and all enjoyed the process of sharing their views and ideas with each other. The following are key observations and finding from the workshop:
- A wide range of different views emerged from different groups and individuals along with a few surprising ideas.
- Both groups considered mobile learning as the most interesting development in TEL.
- The Chinese participants agreed that national policy and commercial market were the main drivers of TEL while the other group considered technology to be the main driver, focussing on upcoming advanced mobile solutions enabling ubiquitous Learning Environments anywhere, anytime and in any context, and the even more advanced Brain Computer Interfaces, promising to make learning enjoyable and detecting cognitive dissonance.
- Not surprisingly, both groups agreed that interoperability and data exchange standards were the most important lessons learned from the past, which represented the concerns from the standards community well.
- Simple and easy to use tools for teaching and learning and universal and affordable access to education through technology were top concerns for desired technology innovations.
- Adopting an open approach, bridging formal and informal learning and connecting with various learning communities were top concerns for institutional culture and organisational change in order to deliver the desired future.
- Assessment and evaluation were the main problems and obstacles for TEL for the Chinese participants. Other concerns included ineffective investment mechanisms and inequality, lack of support from local governments; and the increasing digital divide between different regions and between the rich and the poor, which means that disadvantaged groups are unable to benefit from advanced technology.
A summary of perspectives on TEL in China from this workshop is available the www.sc36meeting.org site.