Learning outcomes

The programme of Master of Digital Text Analysis builds on the competences the students acquired in their prior training (i.e. Bachelor’s programme in Humanities). In this master programme the students acquire the following core competences:

1. They are able to formulate a scientific question clearly and accurately as a starting point for their own research.
2. They are familiar with the most important theories and models in digital text analysis, in particular in computer linguistics, digital literature and artificial intelligence, and they are able to easily use the basic concepts of this domain.
3. They can reflect independently on texts and they have insight in the diversity of (digital) forms of communication.
4. They are able to gather, select and process professional scientific literature and data.
5. They have acquired the linguistic and communicative skills to report adequately on their research and to efficiently participate in discussions about their subject area. They subscribe to the principles of transparant science (Open Science) and are prepared to show great openness with regard to sharing code, insights and data.
6. They are aware of the current ethical and legal debates in the domain of text analyis and have insight in how to handle textual data responsibly and respectfully. They subscribe to the openness of research (Open Science) and understand how, in light of this, scientific data need to be cured sustainably.
7. They have the necessary background knowledge to correctly assess the possibilities ànd the impossibilities of computational methods in the cultural domain.
8. They have the necessary background knowledge to situate their research in their own subject area, they have developed considerable powers of analysis and interpretation enabling them to judge the originality and relevance of their research and to critically evaluate its social relevance. They can also actively but critically follow the new developments in the domains of research and in the relevant scientific and cultural context.

The above-mentioned core competences are developed further into 15 competences representing a whole of knowledge, skills and attitudes.

1. The Master is familiar with the current and contemporary methodological approaches in digital text analysis and is able to apply these autonomously (including the more computer-technical aspects).

2. The Master is familiar with the most important primary literature in their research area (books and articles on digital text analysis).

3. The Master is familiar with the most important questions and future challenges within their subject area, in particular these in the area of automatic comprehension.

4. The Master is familiar with the most important theories in the subject area, current ones as well as less current ones, and is able to easily use the basic concepts in their research area. The Master can develop a personal point of view about the areas studied.

5. The Master has a basic insight in the structure and functioning of the language in which the master thesis is written and is able to reflect on the structure and the use of language.

6. The Master has acquired linguistic and communication skills to formulate a scientific question as clearly and accurately as possible as a starting point for their own research.

7. The Master can place their own domain of research in relation to other scientific disciplines and actively look for relations with these disciplines.

8. The Master has the necessary knowledge about the literature and publications in their subject area (magazines, websites and other digital media).

9. The Master has developed considerable powers of analysis and interpretation and can convincingly translate quantitative results into relevant qualitative insights.

10. The Master has a critical attitude towards the scientific quality and social relevance of their own research.

11. The Master is able to actively but critically follow the developments in the domains of research and in the relevant scientific and cultural context. The Master sees that digital text analysis is a rapidly evolving subject area in which autonomous continuous training is required to remain relevant as a professional in a rapidly changing context.

12. The Master is able to independently gather and select professional scientific literature, and also to gather, select and process data in function of research (primary literature, documents, corpora, questionnaires, etc. depending on the research area).

13. The Master has acquired linguistic and communication skills to write argumentative texts and to effectively participate in discussions about his/her subject area while defending their position convincingly.

14. The Master has a critical orientation in the broad cultural, political and social context.

15. The Master has acquired linguistic, technical and communication skills to report, both orally and in writing, including electronic reporting.