1 University of Library Studies and Information Technologies (BULGARIA)
2 American Univercity in Bulgaria (BULGARIA)
About this paper:
Appears in: EDULEARN19 Proceedings
Publication year: 2019
Pages: 4389-4394
ISBN: 978-84-09-12031-4
ISSN: 2340-1117
doi: 10.21125/edulearn.2019.1106
Conference name: 11th International Conference on Education and New Learning Technologies
Dates: 1-3 July, 2019
Location: Palma, Spain
Recent evolution of information technologies (IT), computing power and Internet have resulted in a tremendous growth of the amount of data generated by humans and machines. Big Data paradigm revolutionized entire IT landscape and changed human culture and behavior. Nowadays we have many new technologies, methods and tools to manage and process efficiently the large data volumes available. As a result of the information age, Data Science has emerged as a new inter and multidisciplinary area of knowledge. The Data Scientist is “a unicorn” who has to face the complex Big Data challenges, responsible for uncovering patterns and insights hidden in huge volumes of heterogeneous data to drive decision-making.

A Data Scientist is a professional possessing analytic skills, abilities in bringing disparate areas together in a novel creative way, asking the right questions, and driven by solving problems, and being curious, and creative. In our previous studies, we identified analytical thinking and analytical skills as the core competences of data analysts and researchers. This study addresses Data Science and the Data Scientist’s skills from point of view of designing curriculum for developing competences for successful career in the area of Data Science.

In this paper we share results of a research conducted to assess the entry competences of students, potential candidates for a Data Science Master Program. The survey emphasizes abilities rather knowledge, stressing on analytical, critical thinking of current students in IT-related bachelor degree programs.

The constructed questionnaire is based on known tests to assess analytical thinking, critical thinking, problem solving attitude, etc. adopted to the objectives of designing Data Science curriculum. It represents logical problems in three different formats: math questions, text assignment and figures pattern recognition. The questionnaire also includes self-assessment of analytical thinking skills and dispositions.

The survey was done in the Fall 2018. About 200 students on their senior year were approached by an on-line questionnaire. Students were originally classified according to their majors as possessing “technical” and “non-technical” background. We have used standard statistical methods and analysis using the SPSS. Our analysis reveals the level of analytical, creative and critical thinking of the respondents. It justified, in general terms, one of the assumptions that both categories of potential students are capable to study in the Data Science Master program and to become successful Data Scientist.
Data Science, Data Scientist, Data Science skills, analytical skills.