Mar 01, 2024
Master of Science in Information Systems
The Master of Science in Information Systems provides students with the technical skills and business acumen that are necessary for organizations to effectively manage and capitalize on their information assets. Broadly, the MSIS curriculum provides opportunities to develop knowledge and applied skills in the areas of information systems management, decision sciences and business analytics, all of which are highly valued by modern organizations. Students will be well prepared to meet the growing demand for analytics professionals who can work with and extract valuable insights from big data. Collectively, graduates from the program are able to perform a wide variety of job functions, including managing and capitalizing on new and existing technologies, aligning organizational strategies with technological strategies and using quantitative methods, data analysis and data visualization in order to inform and improve organizational decision-making.
Cal State Fullerton is the only university in Orange County accredited by the AACSB International at the undergraduate and graduate levels for both accounting and business administration.
Admission is competitive. Students must meet the CSU requirements for admission to a master’s degree program. Please consult the Graduate Admissions section in this catalog for complete information. In addition, applicants will be evaluated based on the following:
- Satisfactory grade point average (GPA) and a satisfactory score on the Graduate Management Admission Test (GMAT) or Graduate Record Exam (GRE). Preferential admission will be given to applicants who have an overall GMAT or GRE score in the 50th percentile or above, and who have a GPA of at least 3.0
- A bachelor’s degree with a major in business administration, equivalent to the degree as offered at CSUF. The degree must include calculus equivalent to passing MATH 135 with a “C” (2.0) or better. Students with a bachelor’s degree in a field other than business administration are eligible to apply. However such students will be required to complete additional courses or demonstrate proficiency as described under the Curriculum requirements below. Courses in the major that are more than seven years old must be evaluated/validated for currency
- For international students, a minimum score of 570 on the TOEFL exam or 88 on the internet based test (IBT) is required, or a minimum score of 7 on IELTS is required
- Recommendation from the ISDS Admission Committee based upon a review of the above requirements, the student’s “Statement of Purpose” and prior work experience. Additional coursework may be required of conditionally admitted students who holistically satisfy the criteria but are weak in one of the above areas
An overall 3.0 (B) GPA is required in study plan courses and all applicable coursework. Any study plan course with a grade lower than “C” (2.0) must be repeated with at a “C” (2.0) or better.
Business Foundation Courses
Students admitted with a bachelor’s degree in a field other than business administration will be required to complete the following foundation courses. The foundation course requirements can be waived if students have previously completed equivalent courses.
Required Courses (6 units)
At least 21 of the 30 units required for the Master of Science in Information Systems degree must be at the 500 level.
Capstone Course (3 units)
Students must complete the capstone course with a “B” (3.0) or better.
* Students must obtain department approval to enroll in these courses
Decision Sciences Concentration (12 units)
Decision science combines information technology, statistics, business knowledge and the rational analysis of alternatives to provide data-driven insights that can improve organizational decision-making for challenging business problems. The Decision Sciences concentration prepares students for careers requiring the ability to understand and use business intelligence systems, build and evaluate decision models, analyze and extract information from data using statistical techniques, efficiently work with large data sets, perform and evaluate simulations, and design, build and implement solutions to organizational data problems.