Master of Education in Learning Analytics 

Campus Locations Boston, Online
Also available 100% Online Yes
Other Format(s)
Credits Required for Graduation 45
Entry Terms Fall Quarter, Winter Quarter, Spring Quarter, Summer Quarter
Meets International Visa Requirements No


Succeeding in today's learning landscape relies upon maximizing the vast amounts of data are currently being generated in education. A Master’s degree in Learning Analytics positions you to make effective decisions based on highly relevant “big data” that ultimately improve the learning environment.

As a graduate of one of the country’s only master’s programs in learning analytics, you are uniquely positioned to harness the power of educational data and help re-shape the future of education at all levels. 


  • Learn key analytics concepts and theories and relate them to education
  • Articulate and integrate learning analytics assumptions, theories, epistemologies, and debates
  • Align learning analytics processes to address the needs of educational institutions and answer questions posed by educational leaders
  • Implement educational data mining and predictive analytics techniques to improve educational outcomes for students and institutions
  • Effectively select, prepare, implement, interpret, and evaluate learning analytic models
  • Communicate data trends via data informative visualizations and dashboards to meet the needs of users throughout the educational system
  • Engage in project planning, communication, delivery, and reporting
  • Anticipate and contribute to the future direction of learning analytics

Get Started

  • Available fully online
  • No application fee
  • No GRE of GMAT required




Please note: Students who started this program prior to Fall 2017 should follow the curriculum reflected on their DegreeWorks audits via the self-service tab of their myNEU portal.  Please consult your advisor with any questions.

Required Courses (45 q.h.):

Complete the following two courses (9 q.h.):

EDU 6050 Education as an Advanced Field of Study (includes ePortfolio orientation) 5 q.h.
EDU 6051 Culture, Equality, Power and Influence 4 q.h. 

Complete the following eight courses (32 q.h.):

EDU 6182 Introduction to Educational Statistics  4 q.h. 
EDU 6340 Learning Analytics Concepts and Theories 4 q.h.
EDU 6341 Introduction to Data Mining in Education 4 q.h. 
EDU 6343  Predictive Modeling for Learning Analytics 4 q.h. 
EDU 6344  Data Visualization for Learning Analytics 4 q.h.  
EDU 6345 Text Mining For Learning Analytics 4 q.h.  
EDU 6324 Competencies, Assessment and Learning Analytics 4 q.h. 
EDU 6319  How People Learn   4 q.h. 


Complete the following course in your last term of study (4 q.h.):

EDU 6225 Capstone 4 q.h.

Required minimum credit hours: 45 q.h.

Admissions Requirements

Below are the official Admissions Requirements for this program.

  • Online application
  • Statement of purpose (500-1000 words): identifying your educational goals and expectations from the program; please be aware that the University's academic policy on plagiarism applies to applicant's statement of purpose
  • Professional resume: Current resume that displays job responsibilities, relevant experience, and education history
  • Two letters of recommendation: from individual(s) with either academic or professional knowledge of your capabilities, such as a faculty member, current employer, mentor, or colleague
  • Official undergraduate degree documentation
  • Proof of English language proficiency: ONLY for students for whom English is not their primary language: English language proficiency guidelines
  • Website Transcript Copy: To submit and complete your application you are able to upload your unofficial transcript directly to your online application. It can be uploaded in PDF format directly to the online application. Please ensure that the scanned documents are readable and include all courses, grades, (i.e. marks, scores, etc.) and credits completed to date. The scanned documents should also include information pertaining to the institution's grading scale. If accepted, you will additionally need to provide your official transcript. In order for a transcript to be "official," it must be in a sealed envelope from the transferring college or university.

For general admissions information and recommended admissions deadlines, Graduate Admissions.

All requirements must be received prior to review.


Estimated total tuition for this program is $24,840.00.

Tuition for individual courses is based on the number of quarter hours. Most courses are 3-6 quarter hours. See Graduate Tuition Rates for details.

Use our Tuition Calculator below to see if transfer credit or tuition reimbursement from your employer could reduce your total tuition.

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Please note: The estimated total tuition is based on tuition rates for Academic Year 2017-18 and does not include any fees or other expenses. Some courses and labs have tuition rates that may increase or decrease total tuition. Tuition and fees are subject to revision by the president and Board of Trustees at any time.

*A maximum of 9 quarter hours of graduate- or doctoral-level credit obtained at another institution may be awarded as Advanced Graduate Credit to the Doctor of Education program.

In Depth | Learning Outcomes

What can I gain from the Master's in Learning Analytics?

You practice mining different kinds of data. You analyze diverse types of numerical, textual, and semantic data; LMS data, course data, student assessment data, social media data, institutional data, enrollment and retention data, demographic data, and more.

You gain sought-after skills. You learn the technical aspects of analytics and big data in education including how to apply them in ways that can impact student learning, as well as institutional processes, workflows, cultures, and behaviors.

You learn in a vibrant and supportive virtual community. This includes geographically diverse students and seasoned online faculty.

You get hands-on experience. You use real educational data and state-of-the-art analytics software.

It’s rooted in the real-world practices. True to Northeastern’s experiential learning model, you connect learning with work experience. For your capstone project, you will connect with an educational organization to analyze real data and create solutions.

It’s specialized. Our focus on learning analytics allows you to fully explore how to apply analytics in educational settings to optimize learning and the learning environment.

You get a national perspective. Because the program is online, you have the opportunity to connect with fellow professionals across the nation, who exchange ways to solve common challenges and build professional networks.

You create an ePortfolio. You leverage the latest learning theory and research by creating an online portfolio that demonstrates your mastery of learning analytics. These work samples illustrate your distinct abilities. Learn more about ePortfolios.


What to expect

What is the student experience like?
  • Interdisciplinary
  • Extremely interactive, much like a classroom experience
  • Enthusiastic, congenial professional students
  • Communication through Skype, phone, video conferencing, email, Blackboard e-Education platform
  • Hands-on use of educational data mining and predictive analytics software
Who is a good fit for this program?

Our program is designed for professionals looking to assume leadership positions in learning analytics:

  • Institutional research, enrollment management and advancement professionals who want to develop and use predictive models for student recruitment, enrollment, completion, and fundraising, as well as institutional effectiveness
  • Professionals working on outcomes assessment and accreditation efforts in higher education and K-12 educational settings
  • K-12 and higher education leaders and administrators wishing to use analytics for better decision making
  • K-12 educators interested in developing a new skill set and/or moving from teaching into administration or consulting
  • Traditionally trained educational researchers seeking a new, cutting-edge skill set
  • Instructors and instructional designers who want to understand what’s working and what’s not in a course or program
  • Individuals working in the fields of educational publishing and software development
  • Professionals in nonprofits, governmental agencies, and corporations working in educational capacities


Program Student Learning Outcomes

  1. Specialized Knowledge 
    Elucidate the major theories, research methods, and approaches to inquiry and schools of practice in the field of study, articulate their sources, and illustrate both their applications and their relationships to allied fields of study.
  2. Broad and Integrative Knowledge 
    Design and execute an applied, investigative, or creative work that draws on the perspectives and methods of other fields of study and assess the resulting advantages and challenges of including these perspectives and methods.
  3. Applied and Collaborative Learning 
    Design and implement a project or performance that requires the application of advanced knowledge gained in the field of study to a practical challenge, articulate in writing or another medium the insights gained from this experience, and assess approaches, scholarly debates, or standards for professional performance applicable to the challenge.
  4. Civic and Global Learning 
    Assess and develop a position on a public policy question with significance in the field of study, taking into account both scholarship and published or electronically posted positions and narratives of relevant interest groups.
  5. Experiential Learning 
    Integrate education-specific best practices and tools into experiential learning opportunities offered in the program.

Careers & Faculty

Industry Information

Projected shortage of people with deep learning analytical skills by 2018: 140,000 to 190,000

Projected shortage of managers and analysts with the know-how to use the analysis of big data to make effective decisions by 2018: 1.5 million. Source: McKinsey Global Institute Report



Today’s educators are swimming in a sea of data. Despite its increasing relevance and strong promise, there is a significant shortage of professionals with sufficient expertise, as the current generation of educators is not equipped to meet its demands or take advantage of its benefits. The Master of Education in Learning Analytics degree opens up a world of opportunity. As a learning analytics expert, you will equipped with a unique blend of educational, analytical and professional capabilities that are in high demand.

Graduates are positioned for leadership roles in higher education (institutional research, information technology, and enrollment management), K-12 education (data divisions in district and state departments of education), educational technology companies and startups, educational think-tanks and other settings. 

Professional pathways include:
  • Chief Academic Officer
  • Director of Learning Analytics
  • Director of Institutional Research
  • Learning Analytics Specialist
  • Senior Institutional Research Analyst


You benefit from an interdisciplinary perspective that draws on the expertise of Northeastern faculty in domains pertinent to learning analytics, including K-12 education, higher education, learning and instructional design, and educational research and analytics.

Meet all of our Graduate Education Program faculty.



Who Will Your Classmates Be?

Your fellow students are career professionals who enroll having worked in institutions of higher learning, K-12 settings, not-for-profit or for-profit organizations, and other institutions that serve education around the world. Students are very diverse but share a passion to deepen their knowledge of educational theory and practice while learning to use data to improve education and outcomes for students and institutions.


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Next Term Starts
  • Summer Graduate
    Jul 10, 2017 (4-, 6-, and 8-week classes)
    Aug 7, 2017 (4-week classes)
  • Fall Undergraduate
    Sep 4, 2017 (7.5- and 15-week classes)
    Oct 25, 2017 (7.5-week classes)
  • Fall Graduate
    Sep 18, 2017 (6- and 12-week classes)
    Oct 30, 2017 (6-week classes)

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