Ph.D. Computational and Data Sciences

This is the Educational Effectiveness Evaluation Plan for this program. See department website for additional information about this program

Learning Outcomes

  • Graduates will develop quantitative reasoning skills which will enable them to: A. Solve problems by utilizing extrapolation, approximation, precision, accuracy, rational estimation and statistical validity. B. Interpret data. C. Create quantitative models to describe natural phenomena.
  • Graduates will be able to apply the principles of computational science to scientific problems. Students will develop critical thinking, end to end problem-solving, and data analysis skills. With these skills, they will be able to: A. Collect, process and analyze data B. Prioritize different potential solutions to a problem C. Use advanced mathematics and computing to solve scientific problems.
  • Graduates will be able to apply advanced principles of applied mathematics to scientific problems. A. Students will be able to evaluate the accuracy of approximations. B. Students will be able to interpret the results of calculations.
  • Graduates will be able to apply advanced principles of computer technology and computer science to scientific problems. A. Students will be skilled in the use of advanced high performance computer architectures including clusters and supercomputers. Students will be capable of creating programs to manipulate and analyze data on high performance computer systems. B. Students will construct solutions to scientific problems using advanced parallel algorithms and data structures. C. Students will analyze the performance of algorithms.
  • Graduates will be able to create new scientific knowledge. The overall quality of student learning in the degree is dependent on the students’ abilities to integrate the individual learning outcomes to generate new scientific knowledge. This will be measured by A. The number of articles published by students in peer reviewed journals. B. The success of students in securing post-doctoral appointments and positions in research facilities and in industry.

Course requirements for the degree

» University Catalog

Curricular Map

The curricular map shows how each required course contributes to the program's learning outcomes.

» Curricular Map (PDF)

Annual Learning Outcomes Assessment Report(s)

In a process called assessment, the faculty of each degree program measure student attainment of program learning outcomes goals on an annual basis. The assessment processes used by this program can be found in the link (PDF) below:

» Learning Outcomes Assessment Process (PDF)

Assessment Rubric

In assessing learning outcomes, program faculty often develop rubrics which establish criteria and expectations showing how outcomes are evaluated. The assessment processes used by this program can be found in the link (PDF) below:

» Learning Outcomes Assessment Rubric (PDF)

Program Review

Program review represents Chapman's commitment to excellence in academic programs through periodic review of educational effectiveness. Every 5 to 7 years, program faculty members prepare a self-study report, which is reviewed by external, expert reviewers, numerous Chapman faculty governance councils and committees, and the Office of the Provost. Program review provides an opportunity for each program to reflect on its educational effectiveness as well as its contribution to the university's mission and strategic plan. The results of program review guide institutional planning, budgeting and decision-making.