The New Master’s Standard: Opinion of the Academic Community

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The new unified standard provides a general framework for developing Master’s programmes and delegates the determination of specific professional skills, types of career activities and key learning outcomes to programmes themselves, as well as recommending particular courses to students. Which tracks did programmes select? What are the opportunities and risks under the new standard? How much do students demand individualization and a project component in their education? The HSE Look posed these and other questions to the Dean of the Faculty of Economic Sciences and Academic Supervisors of three programmes offered at HSE University.

Dr Sergey Pekarski, Dean of the HSE Faculty of Economic Sciences

The new Master’s standard is intuitively close to the Faculty of Economic Sciences since an understanding of the base in economics is still universal and not restricted in this sense by the standard. At the same time, the application of more variability in studies makes things a lot more flexible for us.

Three of our programmes have been included in the pilot project for the new standard. These include the Master of Business Analytics and Economic Analytics, which are new programmes, so it would be logical to start them in the new format; also, the Master’s in Economics and Economic Policy, which was drawn from two earlier programmes: Applied Economics and Economics: Research Programme.

These programmes were quite interrelated, with the difference being that the Applied Economics programme was meant to prepare students for working in business and government agencies, while the Economics: Research Programme was viewed as a preparatory programme for further doctoral studies.

Bearing in mind that the new standard foresees several tracks, we made the conscious decision to unify these two programmes into one and implement it within the framework of the new standard.

We can clearly see the major advantage in having several vectors of development within a single programme. Having three tracks ensures synergy between them, as in when students of a certain track may take courses from another. This is quite important for such a diverse, in terms of teachers’ and students’ interests, faculty such ours.

In addition, particularly owing to the number of international applicants, the Economics: Research Programme was offered for several years in English, while with Applied Economics, we attempted to build a line of courses, which could be pursued entirely in English. Under the new standard, we can do this with more flexibility, while offering tracks in Russian, English or both languages.

Paradoxically, the more options we offer students to develop their own trajectories, the more limitations begin to appear. On the one hand, we are ready to offer them a very wide range of courses, but the development of their own track is limited by the options in the timetable. Therefore, with the core seminars and the seminars with track supervisors, we hope to offer students several topic specializations.

It is important to note that the selection of courses within one particular track is directly linked to projects, which are selected by students themselves. Overall, the selection of a core seminar means that a learner accesses a “batch” of three to four courses.

Furthermore, project heads advise on the courses, which are necessary for carrying out a project. For instance, if a student selects a project that requires time series econometrics, they automatically will need to take a course in this subject, since they will be taught the necessary methods and instruments.

Thanks to this project-focused approach, we will help students build their own educational trajectories not erratically, but with a view to their future career development.

At our faculty, we offer around 150 projects, 30% of which are implemented jointly with potential employers. So, we are moving from the “just-in-case-learning” principle to students making informed choices for their professional development through the project-based-learning approach.

Students understand this approach, as we see significant competition with respect to certain projects. For instance, joint projects with the MICEX and the Bank of Russia are quite popular, since the majority of our Master’s students are interested in finance.

Students can also make proposals to take part in outside projects, which are not organized by our faculty. In such cases, if a project is in line with the objectives of the selected track under the programme, the initiative may get our support.

As such, our faculty offers all three tracks, and, although, 90% of our students are mostly interested in the general and applied tracks, some strong students are interested in the research pathway. Usually, they are Bachelor’s graduates, who are strong in mathematics and economics, who also might be considering a PhD overseas. It should be mentioned that the number of such students is increasing with every year.

Dr Inna Antipkina, Academic Co-supervisor of the Master’s Programme in Science of Learning and Assessment

In 2010, the Measurements in Psychology and Education programme was the first to offer instruction in psychometrics in the post-Soviet space. Prior to this, psychometrics as a field had not been developed in Russia owing to a ban first introduced in 1936.

Over a 10-year period, we have trained around 150 specialists in evaluation, who know how to design and implement contemporary testing, examinations and monitoring activities, perhaps some of the best of their kind in Russia. When the idea of updating the programme was first presented, we understood that neuroscience and its instruments – MRT, EEG, eye trackers, etc., - can be effectively combined with psychometric methods.

An increasingly fast-paced world means that people need to learn quickly; and to do this, it is necessary to understand the neurobiological foundations for study.

This type of approach allows us to create quality educational programmes and provide scientific evidence for accelerated studies. In turn, the ability to assess learning results lets us understand whether the learning approaches applied have helped to make programmes more efficient and whether they need further adjusting. With this in mind, we have developed the Science of Learning and Assessment programme.

We now have a broad outline of our three tracks and we plan to figure them out along the way. The programme is now being reconfigured in terms of its identity, as it earlier focused on research. Over the last three years, the question has been raised as to whether we want to allow project-based theses. However, the majority of the academic committee voted against this and only in the last year have they started supporting projects that might not have a specific scientific result, but rather a strong product.

We already have lined up with various EdTech companies. Another example of demand for the applied track is that every year, a portion of our graduates went into doctoral studies. But, this year everybody went into EdTech. Perhaps this is an effect of a decline in revenue because of the Covid-19 pandemic, but it is possible that the psychometrics fields have become more familiar for employers and, thus, in-demand. However, the general track, as the one foreseeing unrestricted decision-making with “no strings attached”, is still not entirely clear for us.

The new standard seems to cover all bases, although we still have some disagreements about how highly qualified specialists should graduate. The first year of the programme is adaptive – we provide instruction in what we believe an expert in education and pedagogy should know. Then, in the second year, students have a choice between two topical tracks – neuroscience with cognitive development and psychometrics; they are almost entirely free to choose from the many courses, including those taught in both or one of two languages. At the core seminar, we plan to discuss individual development strategies with our students. Now, we do not do this as much, since all of their tracks are more or less uniform.

The second concern is that we are losing those subjects that we consider important, while students are unlikely to vote for them “with their feet”. For instance, students are not fans of Experimental and Quasiexperimental Design in Education and Deep Psychometrics as they are considered difficult because of the statistical methods, albeit they are necessary for normal operations.

Our third worry is that group dynamics might change, as the framework is being loosened up: people from external programmes will come to us for some subjects, while some of our students might go over to other programmes. Still, on the other hand, this is a major opportunity to see the whole wide world and make ourselves visible. So, we have made all of our subjects accessible throughout all of HSE University, including Social and Emotional Development, Academic Analytics, and Staff Performance Reviews.

We have two requirements for student projects: relevance and tasks that ensure development. For instance, our students have already been involved in the organization of a pilot workshop at the Summer School (www.letnyayashkola.org) for three years: this is a major educational project, where we talk about development of qualitative tests and surveys for young specialists and new EdTech leaders.

Every student has the option of taking part in internships at the Institute of Education’s centres and laboratories.

This is not big money, but it gives them possibility to work on real research projects and develop networks of contacts. Projects “from clients” acquaint students with the corporate world during their studies, whereby they get to carry out orders under the guidance of their teachers. Moreover, these clients often become future employers. Our alumni work at YandexUchebnik, YandexPraktikum, Uchi.ru, SkyEng, Algoritmika and other EdTech firms.

Dr Valentina Kuskova, Academic Supervisor of Master’s Programme in Data and Network Analytics

The Master’s Programme in Applied Statistics with Network Analysis was originally designed by Professor Stanley Wasserman. At that time, he was the scientific supervisor of the International Laboratory for Applied Network Research - the programme’s “home.” He applied best practices from several major US research universities and envisioned different programme tracks, project-based education, and many other features that are now being implemented at HSE University. We started the programme with a new ethos in mind before the new guidelines were in place.

First and foremost, the programme is English-taught by world-renowned professors from major international universities. We have asked the experts in major fields of analysis, such as data mining, networks, machine learning, categorical data analysis, Bayesian methods, to join our faculty.

The programme is also unique as it has an applied focus. We teach applied analytics, and some of our graduates consider themselves data scientists. While I still think that the term data science belongs with computer science departments, it is our approach to focus on data and start with problem formulation, rather than teach theorems and methods. This makes our programme distinct from others.

It is the only programme in Russia (and one of the few worldwide) that has a systematic approach to teaching networks – one of the most exciting analytic areas.

• The general track is for those who do not want to specialize. It is the track in which students can select any courses they want from the large pool of electives to tailor their education to their specific needs.
• The research track is supervised by full-time senior researchers from our laboratory, and we call it the ‘PhD preparation track’.
• The business track was established in cooperation with our former graduates, now successful business professionals, who are working in the industry and are willing to bring most recent business practices into the classroom. We have joined forces with the HSE St. Petersburg’s Management and Analytics for Business programme, where students can pursue business-related courses. Students from the other programme can take our courses in return.

The project approach is integrated on every level. First, almost every course we teach (with exception of some basic math and probability courses) requires that students complete several projects. They often have to formulate problems that interest them, find their own data, and then solve problems using the methods taught in a particular course.

Second, projects are implemented at the track level. We have seminar courses that are required for the completion of each of the tracks, and students must submit either research projects or business projects to fulfil their seminar requirements.

Finally, projects are implemented at the programme level. First, we have a capstone course, called Statistical Consulting, where students work with real-life clients from either the academic community or the business world, helping them with real-life projects. Second, we have an analytic workshop, which is a major project run by students on a regular basis. It is a pro bono statistical consulting clinic, where clients can get help with any analytics-related questions.

As a result, students complete dozens of real-life projects before they ever set foot in the real corporate world, which they then join, well-prepared for any challenge.

All this experience has resulted in a new endeavour – opening an online mirror for the programme – Master of Data and Network Analytics on Coursera. We have taken our international-quality programme to the wider world and made it available to working professionals everywhere.