Sunday, 22 December 2013


Have a safe and happy holiday, and all the best for 2014!
Big Education Analytics

Friday, 2 November 2012

Thought Leaders and Events in Learning Analytics


A key conference in Learning Analytics is the international Learning Analytics and Knowledge (“LAK 2013”) Conference:
Disclosure: Blog Author may be part of a submission of papers to this conference
LAK 2013 is a mechanism for combining the expansion of technologies in supporting learning, with large volumes of data from the learning process. Learning Analytics research combines several domains of study to ensure that interventions and organizational systems meet the needs of all stakeholders.


The Society for Learning Analytics Research (SoLAR) is an international group that oversees this conference, and a range of other activities in Learning Analytics.
Disclosure: Employer of Blog Author has an affiliation with SoLAR.

Friday, 26 October 2012

Big Data and Learning Analytics Resources


A definition of big data in terms of size and/or complexity:
"Big Data” is a term used to describe data sets so large and/or complex that they become awkward to work with using traditional database management tools. An example is the use of Learning Analytics techniques to find trends in comments on a course in a Learning Management System (LMS) in conjunction with comments in Social Media.
A useful reference:
Franks, B 2012, Taming the Big Data Tidal Wave: Finding Opportunities in Huge Data Streams with Advanced Analytics, Wiley
This book has some good sections on analytics practices and teams, and isn't just about Big Data. It also has sections on Enterprise Analytical Datasets (ADS), creating secure data, Model and Score Management, statistical tools, and Analytic Sandbox types.
Learning Analytics is an area set to grow rapidly:
Acknowledgement: New Media Consortium
A definition of Learning Analytics:
Learning analytics is the measurement, control, collection, and analysis of data about learners, educators, and their environments. Initiatives based on an understanding of these elements and how they interact can lead to superior outcomes.
The following text provides a thorough coverage of most Analytics, Predictive Modeling, and Data Science techniques:
Ratner, B 2011, Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data", CRC Press
Interesting chapters include Principal Components Analysis (PCA), Smoothing, Segmentation with Chi-squared Automatic Interaction Detection (CHAID), look-alike profiles, data treatments, and the principles of genetic modeling.
Science Fiction becomes reality:
Most enterprises don’t have the amazing power of Watson yet, but capability can be built across time.
Acknowledgement: Network World
“Any sufficiently advanced technology is indistinguishable from magic.”, Arthur C. Clarke

Monday, 15 October 2012

Building Analytical Capability


A focus on Students and Tutors drives the need for Analytics, and an entrepreneurial approach to initiatives.

Information Governance, Reporting, and Business Intelligence, underpin development in Analytics. A useful reference is the following data and information visualization classic:
Stephen, F 2012, Show Me the Numbers: Designing Tables and Graphs to Enlighten, Analytics Press.

The following text provides useful material on technical architecture, data modeling, and the implementation and application of scoring models. Secure Data Systems for Analytics and Predictive Modeling can drive recommendations and value for learning and teaching initiatives:
Haertzen, D 2012, The Analytical Puzzle: Profitable Data Warehouse, Business Intelligence and Analytics, Technics Publications.

The interactions and data from digital environments are also necessary for Analytics in the online space, and require appropriate measurement and interpretation. The following guide includes data integration, online metrics, campaign tracking, and benchmarking:
Clifton, B 2012, Advanced Web Metrics with Google Analytics, Sybex.
This Case Study combines these elements to drive initiatives in an Education context to boost student performance and add commercial value:
Disclosure: Blog Author, Employer, Supplier, and Implementation Partner, are referenced in the Case Study. This is also a current Top 5 candidate for this Award:

Photo Source: Wikipedia

Friday, 12 October 2012

Educating and Learning in Online Environments

The Science of Education (Pedagogy)

The application of Analytics in the Education context requires a sound understanding of teaching, learning, and environments. The following references are particularly useful in the Online space:

Harasim, L 2011, Learning Theory and Online Technologies, Routledge, New York.
This text covers Behaviorist, Cognitivist, Constructivist, and Online Collaborative Learning (OCL).

Crawley, A 2012, Supporting Online Students: A Practical Guide to Implementing, and Evaluating Services, Jossey-Bass.
Provides detailed descriptions of a range of student support initiatives. Includes rating systems for services, useful frameworks, and the measurement of online student engagement and persistence.

Thursday, 11 October 2012

The Transformation of Education and Big Analytics

In a session at the ‘Current/Future State of Higher Education, An Open Online Course’ 
Jeff Selingo (Vice President of ‘The Chronicle of Higher Education’) 
identified five general factors that are likely to disrupt Education including: 

1) skilled jobs, 
2) diversity, 
3) cost, 
4) lifelong learning, and 
5) learning outcomes.

Data, Technology, and Pedagogy enable Big Analytics to create value and generate positive outcomes from this transformation. A journey we can take together.

Tuesday, 9 October 2012


The Future of Analytics in Education

We are in an Education revolution ...

driven by progress in data, technology, and pedagogy.

What is Big Education Analytics?

The culmination of:

Business Intelligence, Business Analytics, Digital Analytics, Learning Analytics, Big Data, & Data Science; 

in the Education context.

So take part, contribute, analyze, review, challenge, and explore - 

we all have something valuable to teach and learn:

“Tell me and I forget, teach me and I may remember, involve me and I learn.”
Benjamin Franklin.

Blog Author: G. Edlund