Major structural shifts in offline and online learning delivery will lead to integrated systems that enable adaptive and holistic higher-education learning environments. Digital footprints will pave way for schools and, eventually, employers to discover learners' competencies and interests and match it to their own offerings and talent needs.

1. It’s Time for Learning to
Go Back to School:
Next-Generation Approaches
Enrich the Student Experience
Major structural shifts in offline and online learning
delivery will lead to integrated systems that enable
adaptive and holistic higher-education learning
environments that harness the capabilities of social,
mobile, analytics and cloud — the SMAC Stack. ‘Digital
footprints’ point the way for schools and, eventually,
employers to discover learners’ competencies and interests
and match them with their own offerings and talent needs.

2. 2 KEEP CHALLENGING March 20152 KEEP CHALLENGING March 2015
Executive Summary
How students want to learn — and institutions need to teach — is
undergoing a total digital transformation. Today’s higher education
students demand more flexible, personalized models of learning that
offer a higher return on investment and preparation for employment
in the 21st century workplace. All stakeholders in the educational value
chain stand to benefit from this overhaul; the more data that is collected
and analyzed, the better synergy that can be created among students,
educational institutions, areas of study, approaches to learning and
employment opportunities.
The catalyst for the transformation is generational. Millennial students
and their younger counterparts expect learning options that utilize the
advanced technologies that they, as digital natives, use every day, as
well as learning experiences that are tailored to their particular needs
and objectives. Toward that end, institutions are employing social,
mobile, analytics and cloud technologies (a.k.a., the SMAC StackTM
) to
develop the insights that lead to personalized and engaging learning
experiences.
The transformation toward personalized and adaptive learning
experiences will be achieved by collecting and applying analytics to the
data surrounding students and other entities in the learning lifecycle.
These digital footprints (what we call a Code HaloTM
) are generated by
the online behaviors of and existing data about individuals, institutions,
learning processes and devices. The meaning that can be derived in
this data is a ripe source for understanding and even predicting student
needs and optimally matching students with schools, learning models
and employers.
Code Halo thinking1
will enrich every aspect of the learning lifecycle,
from admissions to coursework to job placement and lifelong education.

3. IT’S TIME FOR LEARNING TO GO BACK TO SCHOOL: NEXT-GENERATION APPROACHES ENRICH THE STUDENT EXPERIENCE 3IT’S TIME FOR LEARNING TO GO BACK TO SCHOOL: NEXT-GENERATION APPROACHES ENRICH THE STUDENT EXPERIENCE 3

4. Forces Driving the Transformation of Learning
Traditional educational models are at a crossroads. With less than half of full-time students at
public four-year colleges and universities in the U.S. graduating within four years,2
the higher
education learning landscape is in need of serious modernization, if not a full transformation.
Public spending on education is lower than it has been historically,3
as is parental satisfaction
with cost, graduation rates and return on investment.4
With high unemployment levels among
recent college grads,5
the perceived ROI for a traditional college education is under intense
scrutiny. The value of higher education will remain an open question for the foreseeable future
unless all stakeholders recognize that change is needed today. All roads to the future of work in
the U.S. — and the developed world — pass through the education sector.
Indeed, the signposts of change are already visible, with new-breed educational providers
entering the market with affordable and innovative learning solutions. For example, massive
open online courses (MOOCs)6
address a growing customer segment looking for an enriched,
cost-effective approach to learning. Of course, this is not just about earning a degree or certifi-
cation but also about obtaining verifiable skills that lead to employment and higher pay.
Evidence is also growing that adaptive learning models that are personalized to student needs
are key to optimizing student performance. In one study, students who completed a course that
matched their learning style spent significantly less time in the course and achieved, on average,
the same grades as students who took a course that was mismatched with their learning styles
or included all available learning content.7
Even for traditional players, interacting with students today requires utilizing and managing
more channels of interaction than ever before. The result of all these changes: Higher education
business models — tuition and net revenue models, marketing, enrollment strategy, content dis-
tribution and engagement of alumni networks — are evolving drastically. Not only is technology
altering core business processes, but the ways in which individuals use technology to learn are
shifting, as well. Figure 1 (next page) illustrates the new higher education learning ecosystem.
Higher education is being disrupted by the intersection of several forces:
• The new student mindset. Millennial students want learning opportunities delivered via a
wide range of channels — especially online — and they want more input into their own learning
processes.
• Leveraging the SMAC Stack. Institutions are implementing SMAC technologies to deliver a
learning experience that employs familiar technologies that students use in their everyday
life. They are also using the SMAC Stack to capture, track and analyze Code Halos to obtain
insight into the student’s needs, preferences and desires (see sidebar, page 6).
• The advancement of adaptive learning. Adaptive learning is personalized to the student’s
abilities, interests, preferences and learning style.
• The emergence of new learning delivery models. This includes blended models (which mix
online and classroom instruction) and flipped models (in which classroom lectures can be ac-
cessed virtually, such as as through videos or online).
4 KEEP CHALLENGING March 2015
Not only is technology altering core business
processes, but the ways in which individuals use
technology to learn are shifting, as well.

5. IT’S TIME FOR LEARNING TO GO BACK TO SCHOOL: NEXT-GENERATION APPROACHES ENRICH THE STUDENT EXPERIENCE 5
The Future of Learning
Source: Adapted from an infographic by KnowledgeWorks, http://blogs.kqed.org/mindshift/2013/07/what-the-
future-of-learning-might-look-like/.
Figure 1
Communities will take
ownership of learning
in new ways, blending
with other activities.
Social innovation
will help address
resource constraints
& other challenges.
Diverse forms of
credentials will
reflect the many
ways in which
people learn.
The workplace will
evolve so rapidly
that continuous
career readiness will
be the norm.
Learners will create
individualized learning
playlists, reflecting
goals, interests.
Schools will adapt
themselves to
new forms — self
organized.
Radical
personalization
will become the
new norm.
Educators’ jobs
will diversify as
learning agents.
A variety of digital
networks, platforms
& content resources
will boost learning.
Inception of rich
data into learning
tools will enable
learning transformation.
New-Age
Learning
Ecosystem

6. 6 KEEP CHALLENGING March 2015
Reinventing the Student Experience
Growing volumes of information are available across the digital landscape and learning lifecycle,
including:
• Public information from social platforms, such as personal interests and hobbies (including
musical tastes and trips taken). Social data imbues the learner with color and dimension,
which drives new insights.
• Data obtained through student interactions with online coursework, including from
learning management systems (LMS). This includes data such as last log-in and time spent
on content; course progress and time spent on course modules; intra-student communica-
tions; and scores/teacher feedback. Such data can track student performance and whether
intervention is needed.
• Information from third-party and government sources, including educational statistics
(such as educational spending, institutional policies and rank, majors, infrastructure, campus
life, etc.).
Institutions of higher learning can use this data to gain insight into student preferences and
learning styles (see Figure 2, next page). By tracking, capturing and building upon the infor-
mation gathered at every stage of the student lifecycle, educational institutions can create a
“student persona,” which they can then use to provide tailored services that benefit the student
at various stages of his or her educational and professional life (see Figure 3, page 8).
Quick Take
Code Halo Elements
Organizations need several foundational elements to create
and distill meaning from Code Halos, and then use those
insights to develop next-generation approaches to learning:
• Data: The raw material, the fuel, of Code Halos is data. Big
or small, structured or unstructured, all sorts of data can
provide insights into learning behavior.
• Amplifiers: Any device or platform that helps to create,
manage and share Code Halos is an amplifier. With the
proliferation of the Internet of Things (IoT), any wearable
device (Google Glass, a smartwatch) or mobile phone pro-
vides an opportunity to amplify the learning experience.8
• Application interfaces: The application interface is the
presentation layer for user engagement (such as a Web
browser, specific application, mobile app or any wearable
device). For example, Netflix interacts with its customers
via its Web site and mobile app to present new content
releases. Institutions and software providers will be able
to differentiate themselves not just on the basis of course
content but also on the design and learning experience.
For example, Khan Academy offers personalized learning
dashboards similar to the personalized pages on Netflix
and Amazon to guide learners and provide relevant con-
tent based on their learning path.9
• Algorithms: The interfaces are powered by algorithms
that personalize the learner’s digital experience. Used
along with teacher and mentor engagement, algorithm-
based predictions can provide customized learning experi-
ences based on the learner’s needs and desires.
Note: Material in this sidebar was adapted from
“Code Halos: How the Digital Lives of People, Things,
and Organizations Are Changing the Rules of Business,”
by Malcolm Frank, Paul Roehrig and Ben Pring.

7. The Code Halo Effect in Higher Education
Figure 2
Retail
Libraries and
Online Learning
Blogs
Travel
Information
Personal
• 18 years old, in first year
of college, pursuing an
undergrad degree. Major
undecided.
• Listens to Busted, McFly,
JLo, Xtina tracks.
• Likes to travel and blog her
experiences.
Educational
• Completed Grade 9 and 10
with AP in Mathematics
and English.
• Completed high school with
3.6 GPA; SAT 1680.
• Scholarship awarded.
Code Halo Analytics — Insights Generated
• Learning style through LMS history, library track history, assessment scores,
queries posted, scholarships applied for, financial aid, demographic data.
• Understanding of social patterns through blogs, discussion forums, tweets,
posts, online book purchases.
• Entertainment patterns (interest around probability and trigonometry through
online movies, games interacted with).
• Increased learner engagement through gamification patterns.
LMS
• Last logged-in and time spent
on content
• Course progress and time spent
on course modules
• Intra-student communications
• Teacher scores/feedback
• Enrollment status
SIS
• Student data/demographics
• Grades and transcripts
• Behavior records
• Scheduling/attendance
• Health and medical records
• Special education needs
• Fees records/calculation
• Student lifecycle details
CRM
• Personalized marketing
content
• Billing information
• Behavior records
• Events attended by
prospective students
• Packages and other
pricing options
Social and
Behavioral

8. 8 KEEP CHALLENGING March 2015
A New Role for Learning Management Systems
Even with the vast changes occurring in education, the LMS will remain central to educational
institutions. In their current state, however, LMSs are used more as a tool for administrative
efficiency, with teachers primarily using them to distribute course content, broadcast announce-
ments, initiate discussions and send e-mail. The interactive learning component of the LMS does
not customize the learning experience or promote the student’s everyday communication, pro-
ductivity and collaborative abilities.
For students, these systems provide minimal adaption to learning styles, are constrained by insti-
tutional boundaries and don’t make use of insights from the student’s social activities or other
third-party data sources to construct the student persona.
When LMSs interact with Code Halos, however, the learner’s experience can be enriched, from
selecting the right college, to choosing a major, to identifying a mentor during school, to finding
a job after graduation. In addition, next-generation LMSs will include an adaptive learning
component that tailors learning objects to the individual learner.
Turning Code Halo Insights into Better Learning Experiences
Figure 3
K-12 Student
Higher Ed
Prospect
Core Enrollment
Learning
Experience
Graduation/
Deregistration
Professional/
Alumni
Student Life
K-12 Experience Points
Student engagement: Engagement
increases as courses adapt to
student strengths.
Teacher empowerment: Teachers
can configure courses, identify gaps
and provide differentiated instruc-
tion.
College and career readiness:
Students can be measured on
college and career readiness
based on Common Core and other
standards.
Higher Ed Experience
Points
College match: Students can be
mapped to schools based on skills
and college or university offerings.
College/peers acquaintances:
Students can get to know peers at a
more personal level.
Program/course help: Students can
get help deciding which courses will be
most useful.
Student learning environment:
A learner profile can be developed for
personalizing learning and career help.
Student risk/intervention: Measures
can be taken to increase retention and
degree completion rates.
Professional
Experience Points
Job analysis: Students/
employees can align skills with
current job role.
Career pathways: Individuals
can manage career progress,
evaluate alternate career
approaches, identify what is
needed to supplement current
skill sets.
Industry relationships: Profes-
sionals can use their network as
a career catalyst
Virtuous communication with
alma mater: Alumni can mentor/
guide aspiring students to get
a head start in pursuing their
career paths.

9. IT’S TIME FOR LEARNING TO GO BACK TO SCHOOL: NEXT-GENERATION APPROACHES ENRICH THE STUDENT EXPERIENCE 9
Adaptive Learning and LMS
According to the Felder-Silverman learning style model (FSLSM), learners fall into three
basic categories: active/reflective, sensing/intuitive and sequential/global.11
Under this model,
courses can be broken down into elements such as exercises, examples, content objects and
self-assessment.
The three different learning styles require content to be presented in different orders. For
example, an active learner would prefer to learn by trying things and completing exercises and
self-assessments at the beginning of the course module, followed by accessing content objects,
with very few examples given. A reflective learner, on the other hand, prefers to learn by con-
templating the material, so she would prefer content objects at the beginning of the course, with
less focus on exercises. Figure 4 (next page) illustrates how learning style should inform the
individual’s unique learning path and type of content delivered.
Yet another dimension of learning style is content preference: audio, video or text, which can be
deduced through a standard questionnaire. Based on these student inferences, institutions can
design custom courses that suit individual needs.
In order to align with an adaptive learning style, future LMSs will need to be built on a Web
Services framework from the ground up to ensure tight integration with many of the Web 2.0
tools that students already use. Also, adherence to emerging standards such as the IMS LTI
framework will be critical to enabling data and app interoperability. The integration of these
features will encourage students to remain within the purview of the LMS for the majority
of their learning activities, enabling institutions to capture, measure and infer some of their
strengths, weaknesses and preferences.
Quick Take
Privacy and Ethics Issues Surrounding Code Halos
Code Halos provide an immense opportunity to add value
to all stakeholders involved in the educational value chain.
But because they involve the collection and use of student
data, they also raise privacy concerns as to what code can
and should be shared to advance the learning process — and
how it should be protected to prevent misuse, identity theft
or worse.
Institutions and individuals alike must ensure the privacy of
student information; those that don’t will lose trust with their
student body. Openness and transparency are paramount.
Learners must be able to know what data is being captured
about them, how it is being used and which hands it’s passing
through. They also need the flexibility to either delete their
Code Halos or opt out of their data being mined. President
Obama recently proposed the Student Data Privacy Act,
which would prohibit technology companies from profiting
from information collected in schools as teachers adopt
tablets, online services and Internet-connected software.10
Trust is the currency of the Code Halo generation. We
recommend taking the following steps to ensure learner
privacy protection:
• Give your Code Halo a “delete” button.
• Act with transparency: “Show me you know me.”
• Demonstrate value: What does the learner receive in
exchange for sharing his data?
• Calibrate your approach for the global stage as necessary.
• Hard-code organizational self-control.
(For more, see our book, “Code Halos: How the Digital Lives
of People, Things, and Organizations are Changing the Rules
of Business,” by Malcolm Frank, Paul Roehrig and Ben Pring.

10. 10 KEEP CHALLENGING March 2015
Text
Traditional LMMSMSMSMSM
TThhee NNeeww DDyynnaammiicc LLeeaarrnniinngg SSttaacckk
Inputs to the LMS
Analyzing
Unique Learning Paths– Based on Each Persona
Video
Audio
■ Course creation/
configuration
■ Online assessments
■ Reporting features
■ Chat support
■ Progress monitoring
■ Notificationsons
■■■ es//g ststylylylyleeses//nIndividuaIndividual learndividual learnual learnlearnvidual learnIndividual learnIndividualIndiv nnnining sty
prefereepreference npreference not incorporrporatedpreference nott ininncococorpprprepreferenpr fpreference noteference nonce nottence nott atedtedtedtedot in
■■■ id unguideiNon mNon-modulaNon-modular anmodular andnd unguiular and unguin-modular and unNon-modular aNon mod a andd unguidlar and unguidiideded
approaapproach tapproach too courseach too coursecourserseto courseroach to courseapproach to couapproachapp
creation/coon/coon/coon/ccreatioon/configureation/n/configurationfigurationti nurationonfigurationtion/configuration
■ Incomp ture ofplete picturplete picture offfete picture ofplete pictureplete pip e picture ofte piccture off
learnerr engar engagement,mentngagement,r engagementr engage
progress aneess and quss and qualityitytalitynd qualityss and quality
of course contentof cours nttntnttttt
■ Decipher the behavioral
traits (active/sensing…)tr
■ entify contentIde
eferencespprere
Sample Course
(Course breakdown)
■ Learning content
■ Examples
■ Exercises
■ Self-assessment
■
Traits/Preferences
■ Active/reflective
■ Sensing/intuitive
■ Sequential/global
■ Audio/video/text
preferences
Global
■ Self-assessment
■ Exercises
■ Learning material
■ Examples
Intuitive
■ Self-assessment
■ Exercises
■ Learning material
■ Examples
SeequentSSequenquenSequeSequSeSequenSequenenenttiiaallen
■■■ erialgLearniniLearninLearninLearn ngngggg mmaatateereriaial
■■■ ExampleExamplelxampleExampleExamp eeesss
■ Self-assessmentSelf-assessmSelf-asss
■ Exercises
Audio Active
■ Exercises
■ Self-assessments
■ Learning material
■ Examples
Video
Video
GapsGapGapGaGapGapapGapGapppps
■ Social persona
(collaboration scores, etc.)
■ Engagement patterns
■ Mastery levels for
different subject matter
Colliding Code Halos
Everyone in the learning value chain — educators, institutions, students and employers hungry
for credentialed talent — can benefit from the insights gleaned from Code Halos. For instance:
• Student Code Halos: Students’ Code Halos can reveal insights based on their social media in-
teractions, reading lists, interests, study habits, collaboration preferences, learning aptitudes,
scholarships applied for/obtained, degrees and credentials earned, and the stage of their edu-
cation or career path. These patterns can illuminate insights about the best subject area for
the student, his motivations for learning and even her potential career path.
• Educator Code Halos. Code Halos can dramatically transform the role of professors and men-
tors in the learning process. Code Halo-based experiences can help students and professors
connect with each other based on learning needs, the professor’s expertise, the pace of learn-
ing and necessary interventions wherever and whenever needed. The flexibility to reach men-
tors and teachers at any stage of the learning process increases student trust. Additionally,
professors can enrich the learning experience by providing real-time feedback and necessary
interventions during challenging moments in the learning journey.
• Educational Product Code Halos. The insights generated from the information surrounding
learners, teachers and institutions are enabling smart system and course design, as well. Soft-
ware manufacturers and institutions can use these insights to bring continuous innovations to
course curricula, course design and the user experience.
Different Strokes for Different Folks
Figure 4

11. IT’S TIME FOR LEARNING TO GO BACK TO SCHOOL: NEXT-GENERATION APPROACHES ENRICH THE STUDENT EXPERIENCE 11
Interaction leads to a
college match offering
— a solution concept
for suggesting
potential college
options based on
student persona.
1
2
3
4
Interaction leads to a
career match offering,
which helps employers
find the right
candidate for their
organization.
■ University ranking.
■ Specializations offered.
■ Teacher/professor research
contribution publications.
■ Student profiles, performances, activities.
■ Alumni course/career path and success.
■ Application data, student preferences.
■ Social feedback, profile of the university.
■ Areas of strength, collaboration,
contribution.
■ Social behavioral traits, likes,
dislikes, preferences, interests,
contribution.
■ Student academic
extracurriculars — historic
current.
■ Aspirational universities,
degrees, courses.
■ Interests, improvement areas.
■ Application data, student
preferences.
■ Ranking (i.e., Fortune 500, Forbes).
■ Awards (i.e., best companies to work for,
top employers, popular employee perks).
■ Job openings (i.e., LinkedIn, TheLadders.,
Monster.com, Glassdoor).
■ Company stock performance(i.e., stock price,
dividends, splits, quarterly and full-year earnings).
■ News, events social sentiment (i.e.,Twitter,
Facebook, news channels.
■ Company profile (i.e., diversity, demographics,
social causes, sustainability initiatives).
■ Academic qualification and areas
of interest
■ Research and collaboration with peers
■ PoV insights: Contribution to
content editorial teams on learning
pedagogies for educational publishers
■ Online discussion on topics and
enabling focus group discussions
■ Social behavioral traits
■ Mentoring junior teachers
Interaction leads to a
career match offering,
which helps educators
find the right institution
for themselves based
on their aspirations. Educator Code Halo
Interaction leads to
an industry connect
offering, a solution for
improving research
collaboration based
on industry needs.
Employer Code Halo
Student Code HaloInstitution Code Halo
Code
Halos
Interplay
• Institutions’ Code Halos. Schools’ Code Halos could include alumni networks, reputation in-
formation, location, graduation rates, vocational alignment and the quality/depth/breadth of
the curriculum. For employers, Code Halo attributes such as location and volume/quality of
demand are also applicable.
Institutions are already leveraging Code Halos to add value to their students’ learning journeys.
For example, the Signals project at Purdue University utilizes the data collected from student
information systems, LMSs and the grade book for a specific course to track students’ perfor-
mance and identify at-risk students in real time.12
The interplay of the stakeholders’ Code Halos will define the next generation of learning. For
instance, something akin to Match.com from the world of online dating may best exemplify
the power of the convergence of student, institution, educator and employer Code Halos (see
Figure 5). When student Code Halos intersect with institutional Code Halos, for example, it can
reveal best matches of students with schools. Educator Code Halos intersecting with employer
Code Halos can pinpoint opportunities for collaboration. Student Code Halos connecting with
employer Code Halos can show fruitful matches, just as when educator Code Halos intersect with
institutional Code Halos.
Code Halo Thinking at Work
Figure 5

12. 12 KEEP CHALLENGING March 2015
For example, if a student is 70% likely to pursue a career in applied mathematics, this insight can
be matched with colleges that offer a strong math program, leading math professors, personal-
ized course plans and connection to outside resources, such as academic groups of interest and
industry experts. Or, assume that a student earns a degree in anthropology from a prestigious
university. Based on her Code Halo, she presents strong traits indicating a fit with a particular
company’s organizational theory and culture. This type of “code-meets-code” matching is poten-
tially more powerful than traditional hiring and recruiting models.
A few institutions have begun leveraging the power of Code Halos, especially in their admissions
function. Information including social media messages, campus-visit logs and student records
are all input into the admissions software to predict the likelihood of students accepting an offer
of admission.
Stanford University, through its Facebook/mobile app, uses an “enrollment intelligence” algorithm
to predict students who are more likely to enroll by analyzing their social and behavioral data
patterns.13
Denver University predicts interest in enrollment by analyzing the student’s online and
social media behaviors, such as number of friends or conversations the student participates in.14
Code Halos can also help institutions focus their communication and create deeper, more
engaging relationships with prospective students. This process begins before the learner ever
attends a university, as well as after graduation, from admissions to employment.
Looking Ahead
As new technologies raise expectations across nearly every aspect of our lives, the learning
ecosystem needs a radical overhaul, powered by SMAC Stack technologies. But what will success
look like? Increased four-year graduation rates and higher pay for graduates? What about lifelong
learning? How best to prepare young minds for the future workplace they will enter? What
behaviors, creativity and emotional intelligence skills will be required for success? What will work
look like in the next few years? All these questions need to be addressed in the way we confront,
challenge and change our current learning ecosystems. If these issues are addressed thought-
fully, that change can occur without causing chaos to the education system as we know it.
Code Halos provide the lens through which to imagine aligning students, educators, institutions
of higher learning and potential employers. Improving the student experience and increasing
their value in the future is essential to ensuring that these efforts are a success.
To take the first steps, institutions should:
• Revisit their student lifecycle to identify specific touchpoints where they can leverage Code
Halos to transform the student experience.
• Identify programs and courses that can be redesigned for adaptive learning.
• Identify one or more hypotheses that can be put to the test with analytics tools; obtain insights
that can drive student recruitment, retention and persistence.
At a time when many are questioning the value of “business as usual” for higher education,
there has never been a better moment to rethink the art of the possible. It’s time to go back to
school and re-think, reset and unlock the immense potential of the learning paradigm for the
success and prosperity of our society, nation and the world.

13. IT’S TIME FOR LEARNING TO GO BACK TO SCHOOL: NEXT-GENERATION APPROACHES ENRICH THE STUDENT EXPERIENCE 13
Footnotes
1 For more on Code Halos and innovation, read the book, Code Halos: How the Digital Lives of
People, Things, and Organizations Are Changing the Rules of Business, by Malcolm Frank, Paul
Roehrig and Ben Pring, John Wiley Sons, April 2014,
www.wiley.com/WileyCDA/WileyTitle/productCd-1118862074.html.
2 Lynn O’Shaugnessy, “Why Your Child Won’t Graduate from College On Time,” Moneywatch,
Dec. 3, 2014, http://www.cbsnews.com/news/why-your-child-wont-graduate-from-college-in-
4-years/.
3 U.S. Government Spending, http://www.usgovernmentspending.com/us_education_
spending_20.html.
4 “2014 Retention/Completion Summary Tables,” ACT.org,
http://www.act.org/research/policymakers/pdf/14retain_trends.pdf.
5 Jordan Weissmann, “How Bad Is the Job Market for the Class of 2014,” Slate.com, May 8, 2014,
http://www.slate.com/blogs/moneybox/2014/05/08/unemployment_and_the_class_of_2014_
how_bad_is_the_job_market_for_new_college.html.
6 A massive open online course (MOOC) is a model for delivering learning content online to any
person who wants to take a course, with no limit on attendance. For more information, see
http://www.educause.edu/library/massive-open-online-course-mooc.
7 Sabine Graf and Kinshuk, “Providing Adaptive Courses in Learning Management Systems with
Respect to Learning Styles,” Vienna University of Technology and Athabasca University,
http://sgraf.athabascau.ca/publications/graf_kinshuk_eLearn2007.pdf.
8 Jeanne Meister, “The Wearable Era Is Here,” Forbes, June 16, 2014, http://www.forbes.com/sites/
jeannemeister/2014/06/16/the-wearable-era-is-here-implications-for-the-future-workplace/.
9 “How Khan Academy Is Using Design to Pave the Way for the Future of Education,” GigaOM,
Feb. 25, 2014, http://gigaom.com/2014/02/25/how-khan-academy-is-using-design-to-pave-the-
way-for-the-future-of-education/.
10 Michael D. Shear and Natasha Singer, “Obama to Call for Laws Covering Data Hacking and
Student Privacy,” The New York Times, Jan. 11, 2015, http://www.nytimes.com/2015/01/12/us/
politics/obama-to-call-for-laws-covering-data-hacking-and-student-privacy.html?_r=1.
11 “The Felder-Silverman Learning and Teaching Styles Model,” International Centre for
Educators’ Learning Styles, http://www.icels-educators-for-learning.ca/index.php?option=com_
contentview=articleid=47.
12 Li Yuan, “Will Analytics Transform Education?” Learning Frontiers,
http://blogs.cetis.ac.uk/cetisli/2012/11/02/will-analytics-transform-education/.
13 Eric Hoover, “Facebook Meets Predictive Analytics,” The Chronicle of Higher Education, Nov. 6,
2012, http://chronicle.com/blogs/headcount/facebook-meets-predictive-analytics/32770.
14 “Looking Beyond the Campus Visit,” Uversity, http://www.uversity.com/blog/what-you-should-
know-about-behavioral-enrollment-data/.
Note: Code Halo™ and SMAC Stack™ are pending trademarks of Cognizant Technology Solutions.
All company names, trade names, trademarks, trade dress, designs/logos, copyrights, images and
products referenced in this white paper are the property of their respective owners. No company
referenced in this white paper sponsored this white paper or the contents thereof.

14. 14 KEEP CHALLENGING March 2015
About the Authors
Venkat Srinivasan is Cognizant’s Education Practice Lead. He has over 20 years
of experience in business strategy, innovation and operations in the education
industry. Venkat’s areas of interest and research include higher education, online
learning, student retention analytics and emerging technology disruptions for
schools and universities. He earned an M.B.A. in global business from Georgia Tech.
Venkat can be reached at Venkatraman.Srinivasan2@cognizant.com.
Robert Hoyle Brown is an Associate Vice-President in Cognizant’s Center for the
Future of Work, and drives strategy and market outreach for the Business Process
Services Practice. He is also a regular contributor to futureofwork.com, “Signals
from the Future of Work.” Prior to joining Cognizant, he was Managing Vice-Presi-
dent of the Business and Applications Services team at Gartner, and as a research
analyst, he was a recognized subject matter expert in BPO, cloud services/ BPaaS
and HR services. He also held roles at Hewlett-Packard and G2 Research, a boutique
outsourcing research firm in Silicon Valley. He holds a bachelor of arts degree
from the University of California at Berkeley and, prior to his graduation, attended
the London School of Economics as a Hansard Scholar. He can be reached at
Robert.H.Brown@cognizant.com | LinkedIn: http://www. linkedin.com/pub/robert-
brown/1/855/a47.
Meenu Sharma is an Associate Director with Cognizant’s Center for the Future of
Work (CFoW). With over 14 years of experience, Meenu currently works with CFoW
leadershiptoadvanceitsstrategicresearchagenda.Priortothisrole,sheledstrategy
and successful implementation of enterprise 2.0 and knowledge management for
organizations across multiple industries. Her interest areas include SMAC tech-
nologies, consumerization of IT and the Future of Work. Meenu earned her Ph.D.
in knowledge management from Punjabi University, India. She can be reached at
Meenu.Sharma@cognizant.com.
Joydeep Sinha is the Consulting Lead for Cognizant’s Education Practice. He
has seven years of professional experience and is responsible for developing the
company’s consulting capabilities in the education domain across sectors such as
higher education, assessment, training and digital publishing. Joydeep has also
worked with leading education publishers and new media organizations across
various geographies, including the U.S., UK, Singapore, China and the Middle East.
Joydeep received his M.B.A. from the SP Jain School of Global Management. He
can be reached at Joydeep.Sinha@cognizant.com.
Sumit Prakash is a Consultant in Cognizant’s Education Practice. He has more
than four years of professional experience encompassing education publishing,
LMSs, assessments and assessment bodies, education standards and the mobile
applications domain. Sumit received his M.B.A. degree from the Indian Institute of
Management, Indore. He can be reached at Sumit.Prakash3@cognizant.com.

15. World Headquarters
500 Frank W. Burr Blvd.
Teaneck, NJ 07666 USA
Phone: +1 201 801 0233
Fax: +1 201 801 0243
Toll Free: +1 888 937 3277
inquiry@cognizant.com
European Headquarters
1 Kingdom Street
Paddington Central
London W2 6BD
Phone: +44 (0) 207 297 7600
Fax: +44 (0) 207 121 0102
infouk@cognizant.com
India Operations Headquarters
#5/535, Old Mahabalipuram Road
Okkiyam Pettai, Thoraipakkam
Chennai, 600 096 India
Phone: +91 (0) 44 4209 6000
Fax: +91 (0) 44 4209 6060
inquiryindia@cognizant.com
© Copyright 2015, Cognizant. All rights reserved. No part of this document may be reproduced, stored in a retrieval system, transmitted in any form or by any means,
electronic, mechanical, photocopying, recording, or otherwise, without the express written permission from Cognizant. The information contained herein is subject to
change without notice. All other trademarks mentioned herein are the property of their respective owners.
About Cognizant
Cognizant (NASDAQ: CTSH) is a leading provider of in-
formation technology, consulting, and business process
outsourcing services, dedicated to helping the world’s
leading companies build stronger businesses. Headquar-
tered in Teaneck, New Jersey (U.S.), Cognizant combines
a passion for client satisfaction, technology innovation,
deep industry and business process expertise, and a
global, collaborative workforce that embodies the future
of work. With over 75 development and delivery centers
worldwide and approximately 211,500 employees as of
December 31, 2014, Cognizant is a member of the NAS-
DAQ-100, the SP 500, the Forbes Global 2000, and the
Fortune 500 and is ranked among the top performing and
fastest growing companies in the world. Visit us online at
www.cognizant.com or follow us on Twitter: Cognizant.