Credits and costs
Earn a Penn State Information Science Master's Degree — 100% online
The Master of Science in Information Science (MSIS), offered online through Penn State World Campus, presents a well-rounded and holistic computing and information technology (IT) curriculum. This online master's program can prepare you to face the numerous and varied challenges that IT professionals face every day, including analyzing data, developing state-of-the-art IT applications, and managing IT staff and projects.
The program is designed for mid-level information technology professionals who want to improve their skills, increase their knowledge, and move into a leadership or management position within the IT field. As a student in this program, you can gain a competitive advantage in your field and acquire greater insight into the role of IT by learning to:
- describe, model, and analyze information systems to support an organization's operations
- understand existing and emerging information system theories and principles to improve IT systems
- apply appropriate methodologies to design, develop, and maintain software and information systems
- implement and manage information systems and networks while protecting sensitive information assets
- lead people and projects, communicate effectively, and make informed decisions based on sound legal and ethical principles
Your Online Information Science Courses
The courses in this program emphasize data-driven IT and will help you acquire the knowledge and skills needed to meet evolving challenges of integration, security, and business continuity. To earn your degree, you will be required to complete a total of 33 credits. You can select core and elective courses to fit your interests and professional goals. Course subjects include:
- information system architecture
- big data and emerging information technologies
- cybersecurity and information protection
- enterprise solution design
- enterprise digital transformation
You must also successfully complete INSC 594, a 3-credit integrative research topics course, which includes a master's scholarly paper.
Why Pursue a Penn State Degree Online?
Penn State World Campus offers a flexible, online platform that allows you to pursue a world-class education while you continue to gain valuable work experience. You will receive the same education as a resident Penn State student, and your courses will be taught by the same graduate faculty who are active in research and experts in their fields.
Information for Military and Veterans
Are you a member of the military, a veteran, or a military spouse? Please visit our military website for additional information regarding financial aid, transfer credits, and application instructions.
As a student in this program, you will have the opportunity to master emerging theories and technologies in enterprise information systems. You'll also research and study solutions to transform enterprise systems to meet the needs of ever-changing business operations.
To graduate, you must successfully complete a total of 33 course credits at the 400-, 500-, or 800-level, including:
- at least 18 credits of required core courses
- at least 12 credits of approved electives
- three credits of INSC 594, an integrative research topics course, which includes a master's scholarly paper
Required Courses (18 credits)
Electives (select 12 credits)
Culminating Experience (3 credits)
Costs and Financial Aid
Graduate tuition is calculated based on the number of credits for which you register. Tuition is due shortly after each semester begins and rates are assessed every semester of enrollment.
|How many credits do you plan to take per semester?||Cost|
|11 or fewer||$1,007 per credit|
|12 or more||$12,082 per semester|
Financial Aid and Military Benefits
Some students may qualify for financial aid. Take the time to research financial aid, scholarships, and payment options as you prepare to apply. Military service members, veterans, and their spouses or dependents should explore these potential military education benefits and financial aid opportunities, as well.
How to Apply
Deadlines and Important Dates
Your degree application, including receipt of all transcripts, must be received by the following deadlines to be considered complete.
- Summer Deadline: Apply by April 15 to start May 15
- Fall Deadline: Apply by July 15 to start August 21
- Spring Deadline: Apply by November 15 to start January 8
Thank you for your interest in applying to this program. Contact an admissions counselor to discuss your educational goals, financial aid options, and application deadlines.
For admission to the Graduate School, you must hold either (1) a baccalaureate degree from a regionally accredited U.S. institution or (2) a tertiary (postsecondary) degree that is deemed comparable to a four-year bachelor's degree from a regionally accredited U.S. institution. This degree must be from an officially recognized degree-granting institution in the country in which it operates.
Students intending to earn the MSIS should hold a bachelor's degree in information systems, information science, or other quantitative, scientific, or business discipline. Those with experience in information technology will also be considered for admission to the program. Students should have earned at least a 3.00 junior/senior average (on a 4.00 scale) in their baccalaureate program.
Although not required, scores from the Graduate Record Examinations (GRE) or the Graduate Management Admissions Test (GMAT) will be considered by the admissions committee if submitted. If the admissions committee determines an area of weakness or insufficient baccalaureate preparation, the student may be required to take one pre-program requirement course (IST 140). The pre-program requirements do not count toward the 33-credit program total.
Applications are submitted electronically and include a nonrefundable application fee. You will need to upload the following items as part of your application:
What You Need
Official transcripts from each institution attended, regardless of the number of credits or semesters completed. Transcripts not in English must be accompanied by a certified translation. Penn State alumni do not need to request transcripts for credits earned at Penn State, but must list Penn State as part of your academic history. If you are admitted, you will be asked to send an additional official transcript. You will receive instructions at that time.
GPA and Test Scores — All applicants are expected to have earned a junior/senior grade-point average of 3.0 or higher.
GRE or GMAT scores are NOT required for admission but will be considered if provided.
English Proficiency — The language of instruction at Penn State is English. With some exceptions, international applicants must take and submit scores for the Test of English as a Foreign Language (TOEFL) or International English Language Testing System (IELTS). Minimum test scores and exceptions are found in the English Proficiency section on the Graduate School's "Requirements for Graduate Admission" page. Visit the TOEFL website for testing information. Penn State's institutional code is 2660.
Reference (1) — You will need to initiate the process through the online application by entering the name, email address, and mailing address of one (1) reference. Upon submission of your application, an email will be sent to your reference requesting they complete a brief online recommendation regarding your commitment to success in an online program. Please inform your reference that they must submit the form in order for your application to be complete.
Résumé — Upload your résumé to the online application.
Statement of Purpose — Provide a one-page written statement of intent, highlighting academic background, work experience, skills, strengths, academic interests, and professional goals.
You can begin your online application at any time. Your progress within the online application system will be saved as you go, allowing you to return at any point as you gather additional information and required materials.
Start Your Application
Begin the graduate school application
- Choose Enrollment Type: "Degree Admission"
- Choose "WORLD CAMPUS" as the campus
Checking Your Status
You can check the status of your application by using the same login information established for the online application form.
Given the scale of data and computing used in this program and the continuous advances in tools and platforms used in information science, students are urged to check individual course technical requirements vigilantly. At a minimum, students will need a PC or laptop that runs Windows 10 or higher with 8GB of RAM and 250GB of free space on the hard drive. Mac OS machines are not compatible for most courses in the program and are not recommended.
Complete this form to download a brochure and stay informed on upcoming events, application deadlines and requirements, and other important program information.
Ready to take the next step toward your Penn State master's degree?
Start or Advance Your Career
Start or Advance Your Career
You can use the knowledge gained from this program and the support of Penn State career resources to pursue careers in a variety of fields, depending on your goals.
To learn more about the Master of Science in Information Science, offered in partnership with the Penn State Great Valley School of Graduate Professional Studies, please contact:
For questions about the program:
Robin G. Qiu, PhD, Professor of Information Science
Email: [email protected]
For general questions about Penn State World Campus:
World Campus Admissions Counselors
Email: [email protected]
DegreeH.D.R., University of Lyon
DegreePh.D., Computer Science, National Institute of Applied Sciences (INSA-Lyon)
DegreeM.S., Mathematical Modeling and Scientific Software Engineering, Francophone University Agency
DegreeM.S., Computer Science, Lebanese University
DegreeB.S., Computer Science, Lebanese University
Dr. Youakim Badr, professor of data analytics, teaches courses in analytics programming, analytics systems design, data mining and predictive analytics. His research interests include smart service computing, IoT, information security, big data, machine learning, and built-in analytics. Dr. Badr is a professional member of IEEE, a lifetime member of ACM, and associate member of the ACM special interest group on knowledge discovery and data mining (SIGKDD).
Adrian S. Barb
DegreePh.D., Computer Science, University of Missouri
DegreeMBA, Finance and Management Information Systems, University of Missouri
DegreeB.S., Industrial Engineering, University of Bucharest
Dr. Adrian S. Barb, associate professor of information science, teaches databases, data mining, and big data courses. He has worked as a database programmer analyst as well as a web developer at University of Missouri. His research interests include data mining, knowledge discovery in databases, knowledge representation and exchange in content-based retrieval systems, semantic modeling and retrieval, conceptual change, ontology integration, and expert-in-the-loop knowledge generation and exchange.
Joanna F. DeFranco
DegreePh.D., Computer and Information Science, New Jersey Institute of Technology
DegreeM.S., Computer Engineering, Villanova University
DegreeB.S., Electrical Engineering and Math, Penn State
Dr. Joanna F. DeFranco is an assistant professor of software engineering. She has worked as an electronics engineer for the Navy and as a software engineer at Motorola. Her research interests include software engineering teams, effective teamwork, Internet of Things, and software-intensive critical systems.
Phillip A. Laplante
DegreePh.D., Computer Science, Stevens Institute of Technology
DegreeM.B.A., University of Colorado
DegreeM.Eng., Electrical Engineering, Stevens Institute of Technology
DegreeB.S., Systems Planning and Management, Stevens Institute of Technology
Dr. Phillip A. Laplante is a professor of software and systems engineering. He has an extensive list of publications and deep practical experience in requirements engineering, development, testing, and project management for a variety of complex systems, including safety critical and embedded ones. He is widely recognized for work in real-time systems, real-time imaging, and applications in the Internet of Things. He is also a pioneer in licensing of software engineers, having led the development and acceptance of the first licensure exam for software engineers in the United States.
DegreePh.D., Information and Technology, Penn State
DegreeM.S., Computer Science, University of Tulsa
DegreeM.Tech., Computer Science, Indian Statistical Institute
DegreeB.Eng., Mechanical Engineering, Jadavpur University
Dr. Partha Mukherjee, assistant professor of data analytics, teaches courses in analytics programming, data mining, predictive analytics, and analytics systems design. He is a member of ACM, ACEEE, AIS, AiR, and ASE, and has published papers in peer-reviewed IEEE, Elsevier, and ACM Journals and conferences. Dr. Mukherjee’s research interests include social computing, web analytics, data mining, e-commerce, and natural language processing with a focus on text simplification.
DegreePh.D., Software and Systems Engineering, University of Wales Swansea
DegreeM.Sc., Communications Systems, University of Wales Swansea
DegreeB.Eng., Electrical Engineering, University of Wales Swansea
Dr. Colin Neill is a professor of software engineering and systems engineering. He teaches many courses in software and systems engineering and project management. He is the author of more than 80 articles on the development and evolution of complex software and systems and their management and governance. Dr. Neill is a senior member of the IEEE and a member of INCOSE, and he serves as associate editor-in-chief of Innovations in Systems and Software Engineering.
Robin G. Qiu
DegreePh.D., Industrial Engineering, Penn State
DegreePh.D., (Minor), Computer Science, Penn State
DegreeM.S., Numerical Control, Beijing Institute of Technology, China
DegreeB.S., Mechanical Engineering, Beijing Institute of Technology, China
Dr. Robin G. Qiu is a professor of information science at Penn State. He teaches courses on data analytics, information science, software engineering, and cyber security. Dr. Qiu's research includes smart service systems, IoT, big data, data/business analytics, information systems and integration, supply chain and industrial systems, and analytics. He served as the editor-in-chief of INFORMS Service Science. He is an associate editor of IEEE Transactions on Systems, Man, and Cybernetics and IEEE Transactions on Industrial Informatics, and has more than 160 publications.
DegreePh.D., Computer and Information Sciences, CST, Temple University
DegreeM.Sc. and B.Sc., Electrical Engineering - Systems Control, University of Belgrade, Serbia
Dr. Dusan Ramljak, assistant teaching professor of information science, teaches courses on information science, data science, storage systems, and emerging technologies. He has been applying data science on storage systems in NSF IUCRC projects with HPE, Dell, Huawei, and other companies and has more than 20 years of system administration experience facilitating business and research in the U.S., Portugal, and Serbia. His research interests include solving challenging storage systems, provenance, and caching problems, and developing and integrating distributed and parallel data mining and statistical learning technology for an efficient knowledge discovery at large sequence and temporal databases.
Raghvinder S. Sangwan
DegreePh.D., Computer and Information Sciences, Temple University
DegreeM.S., Computer Science, West Chester University
DegreeB.S., Genetics and Plant Breeding, Haryana Agricultural University
Dr. Raghvinder S. Sangwan is a professor of software engineering. His teaching and research involve analysis, design, and development of software-intensive systems and their architecture, and automatic/semi-automatic approaches to assessment of their design and code complexity. He actively consults for Siemens Corporate Technology in Princeton, New Jersey, and holds a visiting scientist appointment at the Software Engineering Institute at Carnegie Mellon University in Pittsburgh, Pennsylvania. He is a senior member of the IEEE and ACM.
DegreePh.D., Information Technology, University of Nebraska at Omaha
DegreeM.S., Industrial Engineering and Management, Indian Institute of Technology, Kharagpur
DegreeB.S., Information Technology, Bharathidasan University
Dr. Satish Srinivasan is an associate professor of information science in the engineering division at Penn State Great Valley. He teaches courses related to database design, data mining, data collection and cleaning, design and implementation of predictive analytics system, network and web securities, and business process management. His research interests include social network analysis, data mining, machine learning, big data and predictive analytics, and bioinformatics.