Abstract:

Success of a training program depends on how well the program allows students to enter the program in a smooth and easy way. The low percentage of retaining students to great extend depends on the way how the curriculum address difficulties students face when they start the study. Smooth introduction to the field of study and encouragement to accept and benefit of offered challenges, natural to every new endeavor, is essential in designing new curriculum. This is especially important in designing curriculum to train students in a new, immature area of education.

The paper is dedicated to share our experience in designing a Data Science Master Program with emphasis on potential students’ portfolio.

Designing the curriculum was done in three phases:
1. Defining the mission, objectives and scope of the program, according to market study of the needs of industry.
2. Empirical study of potential students’ competences acquired on their bachelor study and related to the objectives of the program as defined on the first stage.
3. Designing curriculum in a way to achieve program mission of training specific for Data Science competences.

The mission, objectives, and scope of the program were defined by obtaining feedback shared by ULSIT alumni, mostly graduated in Information Brokerage Bachelor and Master Programs. The objectives of these programs are to train professional in the information related fields. Students obtained competences serving as mediators between end users and information resources. This includes variety of skills from understanding and comprehends classical librarian issues, via expertise of using information technologies, especially to organize information resources within a social entity, toward analytical and presentational skills. Students are prepared to serve in support of consulting teams, as well as managers of information resources. This background allows alumni to obtain a broader view on the needs of variety of industries in the area currently marked as Data Science.

The target group of potential students in Data Science Master Program was defined as undergraduate students, studying information related fields. The natural target was ULSIT students in majors as Information Brokerage, Computer Science, Information Technologies. These three disciplines provide the needed diversity of background experience. A survey was designed to highlight analytical skills, identified as the key component of Data Science competences, and implemented in the Fall semester of 2018. About 200 students were approached, and 187 responded. Details of questionnaire, methodology of conducting the survey, and obtained results are presented.

Analysis of the profile of a typical candidate for study in the Data Science Master Program doesn’t show needs of adjusting the initial composition of courses to cover the content identified as essential for the program, but emphasize on pedagogical issues and on the way how to organize and submit specific topics, how to order them, and how to monitor students’ progress toward desired competences. Special attention is given on students’ outcome assessment, which includes both demonstration of theoretical knowledge with close to real life practical problem solving.

Keywords:

Curriculum model, Data Science, Competences, Analytical skills.