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In order to improve the quality of their study programs, universities/faculties today are facing increasing demands to include employment skills into their curricula in order to maximize the potential of their students for a successful career. One of the key aspects in developing such skills is increasing students’ employability - a set of skills, understandings and personal attributes that make graduates more likely to gain employment and be successful in their chosen occupations, which benefits themselves, the workforce, the community and the economy. While there is a broad consensus amongst key stakeholders in the process (HEI, employers, students) on the importance of addressing employment skills within higher education, there are still open questions on how this can be achieved. While universities/faculties tend to put more emphasis on developing specific knowledge and skills within their field of education, a number of reports issued by employers urged them to make more explicit efforts to develop the “transferable” or “generic” skills needed in many types of high-level employment. In an ever increasing world of information, as one of the core components of these generic skills is developing information competencies – skill set needed for effective gathering, evaluating and communicating information in all its forms and contexts. This paper aims to explore how these information competencies are implemented at the Faculty of Humanities and Social Sciences, University of Zagreb by conducting research across its study programs on the masters’ level. Following that approach, this research will provide a snapshot of current situation and give recommendations on possible optimizations in including information competences into the curricula at the faculty level.

The conflict in focus  the relationship between the concept of secrecy, which the national security system is entitled to, and the request of the public, which is a norm of a democratic society  is only one of the elements appearing in a specific relationship between the system and the media. On the other hand, a part of their relationship can also be marked by a combination of dependence, manipulation, support and praise, which can lead to conflicts of other relevant categories from the group which are related to independence and the quality of information. A similar situation involving the relationship with the source is also conspicuous here  the relationship between the journalist and the source, the system and the source or, also according to the authors mentioned above, the possibility of fraudulent, including illegal, behaviour, in order to obtain the information inaccessible to the public.

This paper discusses the concept of data quality in the context of longitudinal research. By deconstructing quality assurance process and data collection strategies through a case study of the “Croatian Birth Cohort Study“, we try to define causes and sources of poor data quality in the context of longitudinal studies. Besides the problems discussed throughout the known literature (panel conditioning, sample attrition, recall bias, temporal and financial demands), we introduce singlesource problems, multi-source problems, security problems, design questionnaire problems and QA workflow problems as important aspects in the domain of the possible sources of errors. Additionaly, we propose models for eliminating the errors through prevention and detection in order to improve data quality.

Computational analysis of text is an increasingly important approach used by researchers in the field of digital humanities. A much-debated question is whether computational techniques such as text analysis, which is in fact a quantitative approach, is adequate for analysing literary texts, sinceliterature is considered as a type of artistic expression. In the paper we highlight the importance of the application of computational analysis with a study conducted on a corpus of selected Russian literary texts from the periods of Realism and Romanticism. Texts included in the romantic subcorpus are “Eugene Onegin” by Alexander Pushkin and “A Hero of Our Time” by Mikhail Lermontov. Texts that constitute the realist subcorpus are “Anna Karenina” by Leo Tolstoy and “Crime and Punishment” by Fyodor Dostoevsky. The analyzed texts are translations into the Croatian language. The paper presents current methods and approaches used in computational literature analysis. The focus of this research is the analysis of adjective usage in romantic and realist texts, due to the fact that these two literary periods are based on distinctive poetic principles. The texts were analyzed using the programming language “Python”. Part- of-speech tagging was accomplished with an online tagger for Croatian language. Considering that all texts are historical (because they originate in the 19th or early 20th century) difficulties with POS tagging are expected.Results of the research show more similarites in the usage of adjectives between the subcorpora then expected. The paper points out how quantitative methods “borrowed” from the field of natural language processing and statistics can be significant in drawing conclusions about literature and that numbers can be meaningful if interpreted competently.

Social media today are an inevitable part of everyday life ; networking of individuals and new ways of communication and interaction have emerged in the academic world. They are available 24 hours a day, 7 days a week across a range of devices and from different locations, thus depending only on the availability of the internet and the will of their users. By enabling the creation and sharing of information, ideas and interests through virtual communities and networks, whose purpose is to turn communication into interactive dialogue, they have influenced society, economics, politics, science and education. Students of today are generations who have started virtual life on social media since their early age, anddo not know the world where there are no computers, cell phones and social media. Social media is an example of technology students have widely adopted, but the digital gap between students and their educational institutions is evident. Numerous researche show that there is a need for integration of social media into the teaching process because students experience them as self-explanatory. There are many advantages and positive effects on the teaching process, but teachers are less likely to use them because they are more focused on their shortcomings and dangers. The use of technology can be influenced by numerous factors, and the current study is conducted with the aim of identifying the current status of teachers’ usage of social media in higher education and detection of factors which influence the usage of social media in higher education. The questionnaire is based on the Unified Theory of Acceptance and Use of Technology named UTAUT model as a theoretical framework, and data is collected on a sample of teachers at the Algebra University College in Zagreb and the University of Applied Sciences Baltazar Zaprešić. This research is the first research conducted among the higher education teachers in the Republic of Croatia, concerned not only with the social media usage for higher education purposes but also with factors that influence the willingness of higher education teachers to use social media for the higher education purposes.

The paper deals with the use of information and communication technology in the development of phonological awareness in children with hearing impairment. The research was conducted at the Polyclinic for the Rehabilitation of Listening and Speech (SUVAG). The Glaskalica app on a tablet device has been used to compare the phonological awareness test results that are obtained by using the paper-and-pencil method and through information and communication technology. There were 10 participants aged 6 to 8 years (four girls and six boys). The results show that ICT is interesting and motivating to children and has the potential to improve phonological awareness skills.

In this paper we present an approach to measuring the societal impact of scientific research. Our proposed methodology is based on the theory of productive interaction (Spaapen and van Drooge, 2011). The methodology was tested on the reports produced in the process of the expert evaluation of public higher education institutions (HEIs) at universities and public research institutes in Croatia. For the purpose of quantitative assessment, we have developed a conceptual framework and analyzed the narrative texts of reports based on recognising codified interactions. Finally, we discuss our results in the context of the research area of the Republic of Croatia in the fields of social sciences and biomedicine

This paper aims to detect the possibilities of automatic text transcription for the purpose of preparing a corpus for further natural language processing analysis. The corpus contains various Croatian folklore genres. The transcription goal is to have one character represent one phoneme and remove spaces between accentuated and non-accentuated words. This knowledge independent system is trained using supervised learning methods and applied to the rest of the corpus using classifiers such as the naïve Bayes, k-nearest neighbour, support vector machine and others. The results are compared to a human-annotated sample to determine accuracy.