On June 26, the Academic Council approved the concept of developing students’ digital competencies. The project authors – Olga Podolskaya, Director of the Continuing Education Centre at the Faculty of Computer Science, and Evgeny Sokolov, Academic Supervisor of the programme in Applied Mathematics and Information Science – spoke about the concept and the subjects that will required for students to develop these competencies.
– How did the Concept appear? How does it differ from the existing Data Culture project?
– The Data Culture project started in 2017 and focuses on data analysis skills. But we came to understand that students also need to develop a competency called ‘digital literacy.’ And about a year later, we decided that this should also be extended with algorithmic thinking and programming. This is how Python courses appeared in all HSE University programmes.
The new concept virtually describes this whole experience. As the undergraduate educational standards have been implemented, all undergraduate students are now required to master three competencies: digital literacy, algorithmic thinking and programming, and methods of data analysis and artificial intelligence.
– Why would philosophers or philologists need these skills, for example?
– Digital literacy is the ability to exist in the world of information technology, starting from very basic things, such as choosing the characteristics for your new computer or preventing your data from being stolen online. For many students, this information turned out to be new and helpful.
Digital literacy also means the ability to work with spreadsheets, to formalize academic citations, to perform basic analysis, as well as to understand the basics of statistics and modelling. These skills will be useful for both future work and for studies at HSE University (for example, carrying out research and writing essays).
Programming is also an important skill, including for philologists. Today, there are a lot of international projects for digitalization of ancient manuscripts. If a philologist is able to write a simple script to get the necessary data, they will do things faster. They might have some routine tasks, such as finding certain characters or words in a text. These can easily be solved by Python. This is a simple and powerful language for applied tasks.
– What levels of digital competencies will be offered by different programmes?
– Students are supposed to master digital literacy at the same level, but the programmes don’t need to include every course if they believe that the students already have certain skills. They can also give students the option of taking the courses online.
In terms of programming and data analysis, each programme sets the minimum level of competencies. For example, students of journalism and culture have the elementary level, those in economics and political science take the basic level, and students from the Faculty of Computer Science take the advanced level courses.
The elementary level means the ability to write a simple code, several dozen lines in length; analysis of spreadsheet data at the level of descriptive statistics and simple visualization; and solving routine tasks of text analysis.
The basic level includes the application of simple algorithms and data structures; writing a complicated code; application of statistical methods for interpreting data and extracting knowledge from it.
The advanced level involves writing an effective program code, knowing the methods of machine learning and the ability to apply them to solve tasks related to big data analysis.
– How will the new concept be implemented in curricula?
– Each programme determines the set of compulsory subjects in accordance with the required level of digital competencies, as well as additional minors, electives, online resources (MOOCs), research and project seminars and HSE+ elements that help students to improve their level.
It’s important to note that students in various programmes may reach the same high level through different trajectories. For example, a MIEM student may choose to minor in Intellectual Data Analysis, while a political science student may choose a course in political decision analysis or machine learning for political science offered by their programme. In terms of data analysis method, they learn to do the same thing, but the minor provides a more general view, while the political programme track provides an experience of solving tasks necessary for the future profession.
In addition, the education is project-based. After completing the programme’s required coursework, students usually conduct a small data research project. For example, our philology students have analysed the texts of popular songs, while economics students have studied cases of banking fraud.
– How will the students’ digital competencies be assessed?
– As with compulsory English language exams, digital competencies will be assessed by level tests.
A digital literacy pass/fail test will be offered after the first year of studies. A test in programming and data analysis will take place after completion of the courses that provide the necessary level of competencies.
Students who take elective courses in these areas may take exams at a more advanced level. If they pass the tests, they earn a certificate that will make a good addition to their portfolio.
– Is there a plan to develop teachers’ digital skills??
– This is also an important part of the Development Programme. If a student learns Python and then comes to an academic supervisor and talks to them about scripts, which they don’t know, that won’t be good. That’s why we are working with the Continuing Education Centre to offer a course in Python for researchers. In the new academic year, we will repeat it and launch new courses in machine learning and other digital competencies that are aimed for teachers and academic supervisors in particular.
Interview by Yulia Giatsintova