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22 DECEMBER 2013

Global Technology Outlook 2013: Personalised Education

"An industry at the brink of transformation: The education industry is at the brink of an IT–enabled transformation. This transformation is driven by a demand for quality education that outstrips supply especially in the growth markets, misalignment between education and employment needs, and impatience with inefficiencies of education systems. For example, the government of Brazil is already funding students to go abroad because of a shortage of education infrastructure and quality educators. If growth continues to follow the existing trajectory, India will need about 800 more traditional universities than current levels today of about 350 universities.

Today, the most talked about application of technology to address these gaps is the advent of Massive Open Online Courses, or MOOC, which are growing rapidly. Several startups have emerged including Udacity, Khan Academy and Coursera, with millions of students enrolled across hundreåds of countries. Large amounts of new data are being created, which thus far is untapped for its potential.

What is Personalized Education: Education today is mainly delivered on a one size fits all basis. This is a key cause of the poor quality and inefficiencies associated with the industry. Educational institutions can learn from healthcare by drawing the parallels of doctors to educators, patients to learners, medicine/treatment to courses/learning, and payers to education loan providers. From a technology point of view, the use of electronic health data to form patient records, derive evidence, and provide patient–centric personalized healthcare can be extended to education, with the formulation of digital student records helping to inform and provide personalized learning pathways based on the capabilities of the learner and the desired outcomes.

Implications for the industry: The education industry is ripe for innovation, as new business models are instantiated on the emerging new sources of data, in particular the longitudinal learning data (tracking student information over multiple years in multiple schools). Predictive and prescriptive analytics will be applied to improve outcomes and efficiency. Clustering learners into groups, assigning new learners to existing clusters, identifying when a learner is deviating from a particular path are some possible outcomes. Prescriptive analytics would identify personalized learning pathways, track progress, and provide feedback to ultimately improve timely graduations and employability. Combined with industry demand data, supply estimates could be provided and targeted courses created with intakes tweaked to meet estimated demand. What will it take to succeed?: Ultimately there are many stakeholders who will be involved in improving education. This includes academic institutions, state education departments, students, learning management systems (LMS) and MOOC providers, government social service agencies and corporations. In order to achieve their often–shared goals, particularly to improve graduation and employment rates, they'll need to come together to create an open platform for sharing this data and insights from the analytics."

(William LaFontaine, 2013, IBM Research)



2013 • Alabama State Education • analyticsBrazilCourseradata integration • demand for quality education • Desire2Learn • digital student records • e-learningeducationeducation and employment • education industry • education shortage • electronic health data • healthcareIBM • IBM Global Technology Outlook (GTO) • IBM Research • IndiaKhan Academy • learning management systems • LMSlongitudinal learning dataMassive Open Online CoursesMOOCsone-size-fits-all solution • outcomes and efficiency • patient records • patient-centric • personalised educationpersonalised healthcarepersonalised learning • personalised learning pathways • predictive analytics • prescriptive analytics • Qatar Supreme Education • study abroadUdacity


Simon Perkins

Opening up UCAS Data

"The 'Big Idea' behind my entry to the TSO competition was a simple one–make UCAS course data (course code, title and institution) available as data. By opening up the data we make it possible for third parties to construct services and applications based around complete data skeleton of all the courses offered for undergraduate entry through clearing in a particular year across UK higher education.

The data acts as scaffolding that can be used to develop consumer facing applications across HE (e.g. improved course choice applications) as well as support internal 'vertical' activities within HEIs that may also be transferable across HEIs.

Primary value is generated from taking the course code scaffolding and annotating it with related data. Access to this dataset may be sold on in a B2B context via data platform services. Consumer facing applications with their own revenue streams may also be built on top of the data platform.

This idea makes data available that can potentially disrupt the currently discovery model for course choice and selection (but in its current form, not in university application or enrolment), in Higher Education in the UK."

(Tony Hirst, 2011)



annotationapplicationsB2B • consumer facing applications • course choice • course choice applications • course code • course data • course selection • course title • coursesdatadata integration • data platform • data platform services • dataset • discovery model • enterpriseentrepreneurship • entry through clearing • HEHEIhigher educationinformation in contextinnovationintegrationJISCmash-uporganisations • revenue streams • services • third parties • TSO • TSO OpenUP Competition • UCASUKundergraduateuniversity applications processuniversity enrolmentvisualisation


Simon Perkins
18 FEBRUARY 2011

Semantic Web: integration through abstraction and standardisation

"The Semantic Web is about two things. It is about common formats for integration and combination of data drawn from diverse sources, where on the original Web mainly concentrated on the interchange of documents. It is also about language for recording how the data relates to real world objects. That allows a person, or a machine, to start off in one database, and then move through an unending set of databases which are connected not by wires but by being about the same thing."



abstractionAPIbusiness rulescomputer sciencecontextconvergencedatadata accessdata contextdata integrationdata interchange • description resources • documentsenabling technologiesformatHTMLHTML5informationinformation retrievalintegrationinteroperabilitymachinesmetadataontologyorderingprotocol • R2RML • RDFreal world objects • Resource Description Framework • rule systemschemasemantic websolutionspecificationstandardisationstructurestructured datatechnologyunificationusabilityW3Cweb • XHTML5 • XML


Simon Perkins

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