C# or Java? analysis of student preferences
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(2) 102 Łukasz RadliĔski, Jakub Swacha C# or Java? – analysis of student preferences. focus on the technical aspects of these languages but rather on how students perceive them during the actual educational process. The aim of this paper is to answer the following research question: which programming language, C# or Java, is preferred for learning by students of the subject field ‘computer science and econometrics?’ Apart from answering this general question, partial aims are to determine preferences of various groups of students, depending on the mode of their studies and their level of general programming skills. We have performed a questionnaire survey among students at the University of Szczecin. Next, we have analyzed the answers provided to individual questions. To address the main and additional research aims, we have used the Analytic Hierarchy Process (AHP) method that enables aggregating responses and expressing the overall preference quantitatively. The main motivation for this analysis is to use its outcome in preparation of the program of studies for the entire subject field ‘computer science and econometrics’ and similar fields that involve courses in computer programming and software engineering. Achieved results may help to tailor programs of studies to student needs and expectations. They may also partially help in designing the individual courses in terms of the general approach, teaching methods and tools, and the way of monitoring and assessing students’ progress throughout the semester. This paper is organized as follows: Section II provides the details on the research approach followed in this study. Section III provides an overview of the environment where the study was performed, including the respondents who participated in the questionnaire survey and the details on the courses on programming in C# and Java. Section IV provides and discusses the results of the study – first, the answers to the individual questions, then the aggregated results for groups of students, and finally the overall preference aggregating all responses. Section V considers the threats to the validity of the results. Section VI draws conclusions and discusses possibilities of the future work in this area. 2. Research approach Analysis of student preferences for programming languages involves analyzing several factors that contribute to the overall selection. Therefore, it is a problem within a discipline of multicriteria decision analysis (MCDA). There are various methods for solving MCDA problems: – AHP – Analytic Hierarchy Process [19], – ANP – Analytic Network Process [18], – ELECTRE – ELimination and Choice Expressing REality [16], – Goal Programming [4], – MAUT – Multi-Attribute Utility Theory [9], – PROMETHEE – Preference Ranking Organization Method for Enrichment of Evaluations [3], – SIR – Superiority and Inferiority Ranking method [24], – SMART – Simple Multiattribute Ranking Technique [10], – UTA – UTilitès Additives [2]. In this study, we decided to use AHP – it is a well-established method, easy to use, not too intensive computationally, and provides results in a clear way. It has been used in various similar.
(3) 103. Studies & Proceedings of Polish Association for Knowledge Management No. 58, 2012. problems [11], most notably in a similar research on determining student preferences between C# and Python [21]. The research procedure for this study involved the following main steps: 1. Preparing a list of questions to be included in the questionnaire survey and to be used as criteria in the AHP models. 2. Creating a decision hierarchy for the AHP models. 3. Defining the importance of criteria. In AHP models, they are typically defined numerically by pair-wise comparisons, by manually setting a weight to each criterion – either in a way that the weights do or do not add up to 1. For simplicity (to avoid inconsistencies) and to enable an easy extension of the questionnaire, we expressed the weights on a 1–10 scale, with ‘1’ indicating the lowest and ‘10’ the highest importance. The course leader set the values of these weights, listed in Table 1, based on his experience and vision for the courses, and also based on previous similar work [21]. 4. Performing a survey where students provided their preferences with respect to alternative programming languages separately for each question/criterion. 5. Analysis of the frequencies of responses provided for individual questions. (See Section IV. A.). 6. Preparing the data for the AHP models – regrouping values for the ‘level of general Table 1.Weights for selection criteria Criterion. Weight. Simpler at the first contact. 9. Easier to learn. 9. More reasonable and intuitive syntax. 7. Faster to develop programs. 5. Easier to develop desktop applications. 5. Easier to develop web applications. 7. Easier to find defects. 7. Shorter source code. 3. Clearer source code. 8. More comfortable programming environment. 5. Easier to install and use at home. 3. Easier to find documentation. 5. Higher value for future professional career. 10. programming skills’ (detailed explanation in Section III.A.), transforming the responses to the scale 1/9-9 required by AHP..
(4) 104 Łukasz RadliĔski, Jakub Swacha C# or Java? – analysis of student preferences. 7. Aggregating data from the survey. We have calculated the geometric means for each criterion to be entered into the AHP models. Aczél and Saaty [1] demonstrated that the geometric mean is the only mean which preserves the reciprocal property in the combined pair-wise comparison matrix, and thus is the most common approach in defining priorities [13], [21]. Because we used several AHP models (for analyses of by group and overall results), we needed to calculate the different geometric means for each model. 8. Calculating the AHP models. 9. Analyzing the results from AHP models, including the decision scores for each alternatives and contributions of criteria to these decision scores. 3. Overview of the Environment for the Study A. Respondents We performed a questionnaire survey among students in ‘computer science and econometrics’ at the University of Szczecin. We addressed the survey to third-year students of the ‘Internet engineering’ specialization. This selection limited the number of respondents. However, in this study the focus was on opinions of those students who attended both courses – on C# and Java – in the same semester. This was important to obtain valid results – i.e. students provide answers at the end of both courses when they may still remember their experiences from the process of learning both languages. In total, 44 students participated in the survey. Table 2 illustrates the number of students in different groups – depending on the mode of study (full- or part-time) and the level of general programming skills that students had before the start of courses on C# and Java. We introduced such categorizations to analyze if they have any impact on student preferences. Table 2. Number of respondents by their mode of studies and level of general programming skills Level of programming skills. Full-time. Part-time. Total. Beginner. 16. 13. 29. Semi-advanced. 9. 5. 14. Advanced. 0. 1. 1. Total. 25. 19. 44. Because there was only one student who declared his ‘advanced’ level of programming skills, we decided to analyze student responses in two groups, depending on the level of skills: beginners and non-beginners, i.e. ‘semi-advanced’ and ‘advanced’ together in the second group. To investigate students’ background, we asked them to provide the level of programming skills in the two analyzed languages: C# and Java. Fig. 2 illustrates the obtained results. Approximately 48% of students declared that they had some skills in C# while only about 11% had skills in Java. This difference was caused by the fact that some students attended another course in an earlier semester (object-oriented programming) that covered the introduction to C#..
(5) 105. Studies & Proceedings of Polish Association for Knowledge Management No. 58, 2012. Table 3. Differences between courses taught Factor. C#. Java. Number of teaching hours for full-time students (lectures/labs). 15/30. 30/45. Number of teaching hours for part-time students (lectures/labs). 9/18. 18/27. Course ends with. credit. credit and exam. Number of teachers for labs. EƵŵďĞƌŽĨƐƚƵĚĞŶƚƐ. IDE used. . 1. 3. MS Visual Studio 2010. Netbeans 6.9.1. . #$ %". . . . . . ! " . . Figure 1 Levels of skills of respondents before the courses B. Courses Taught on C# and Java Both the course on C# and on Java are focused on teaching some practical skills, most importantly developing desktop and web-based applications. The contents of both courses include some background on object-oriented programming. However, this is basically a reminder from earlier courses on programming basics and object-oriented programming. Since the students study at the Faculty of Economics and Management, they are focused on the functional perspective, i.e. on developing applications that are suitable, useful, and easy to use, rather than on very technical aspects such as performance, security, or reliability. Thus, these courses focus not only on learning programming in a specific language but also on learning using various supporting technologies/libraries: for the C# course – within .NET Framework; for the Java course – within JSE and JEE platforms. As mentioned earlier, selecting courses on C# and Java for this analysis was caused by the fact that both of these courses were taught in the same semester and exactly the same students were enrolled to both courses. Furthermore, the same leader manages and gives lectures to both courses. Table 3 summarizes the differences between both courses. These differences are in the number of teaching hours (yet different for full- and part-time students), in the formal way of crediting the course, the number of teachers, and the integrated development environment (IDE) used. For C#, the course leader was the only instructor for labs. For Java, one other instructor took the lab classes on full-time studies, and yet another one on a part-time studies. Students were able.
(6) 106 Łukasz RadliĔski, Jakub Swacha C# or Java? – analysis of student preferences. to select an IDE to develop their projects. For the lab classes, we selected Microsoft Visual Studio 2010 and Netbeans 6.9.1. The main criteria for selection were: free for students and lecturers, visual development – at least for desktop applications, and ease of installation (no need for further packages, tools, etc.). While the selection of the tool for the C# course was rather obvious, for Java it was more difficult. After analyzing different tools and published comparisons between them [8], we selected Netbeans as it appeared to be the most user-friendly among the free and popular IDEs for Java. 4. Results A. Analysis of Responses Figure 2 illustrates the histograms of responses provided by students to each question in the survey. In nearly all questions, the majority of students expressed their preference for C# rather than Java. The significant dominance of C# can be observed for the following factors (numeric values indicate the number of votes for C#/Java, respectively): – simpler from the first contact – 35/5, – easier to learn – 30/7, – more reasonable and intuitive syntax – 32/8, – faster to develop programs – 34/2, – faster to develop desktop applications – 36/3, – faster to develop web applications – 27/7, – easier to find defects – 30/4, – shorter source code – 33/1, – clearer source code – 30/8, – more comfortable programming environment – 35/6. Most of the aforementioned items directly reflect the students’ perception of the respective programming language. Only the last of these factors, a ‘more comfortable programming environment’, does not exactly rate the programming language itself. However, since it is a direct point of contact between a programmer and the developed code, its features may significantly affect the way a programmer perceives the whole language. For the ‘easier to find documentation’ factor, there was a clear preference to C#, but its advantage over Java was not as dominant as for other factors. The course leader and lab instructors provided students with some learning materials such as slides for lectures, course notes and exercises, as well as addresses of recommended websites with further information. For C# students, they also gained access to the teaching materials for various courses within the Microsoft IT Academy program. In terms of the ability to install and use a particular language at home, the students on average did not point out a clear winner. In fact, the answer ‘both similarly’ was provided the most often. Still, some students pointed a clear preference of C# or Java in this matter. We suspect that they probably faced some configuration problems during installation or use, but we have not investigated this in detail..
(7) 107. Studies & Proceedings of Polish Association for Knowledge Management No. 58, 2012. Java was preferred over C# only for a single factor, but the most important one – ‘higher value for future professional career’. Still, its advantage over C# was very narrow and an answer ‘both similarly’ was the most often selected answer. ĂƐŝĞƌƚŽůĞĂƌŶ. . . . . . . . ! & '#$. . '. . ! & '%". EƵŵďĞƌŽĨƐƚƵĚĞŶƚƐ. EƵŵďĞƌŽĨƐƚƵĚĞŶƚƐ. ^ŝŵƉůĞƌĂƚƚŚĞĨŝƌƐƚĐŽŶƚĂĐƚ . . . . . ! & '#$. '. . . ! & '%". EƵŵďĞƌŽĨƐƚƵĚĞŶƚƐ. EƵŵďĞƌŽĨƐƚƵĚĞŶƚƐ. ). ! & '#$. . . . ! & '#$. . '. . . ! & '%". EƵŵďĞƌŽĨƐƚƵĚĞŶƚƐ. EƵŵďĞƌŽĨƐƚƵĚĞŶƚƐ. . . . . ! & '#$. '. . . ! & '%". EƵŵďĞƌŽĨƐƚƵĚĞŶƚƐ. EƵŵďĞƌŽĨƐƚƵĚĞŶƚƐ. . *. (. . ! & '#$. '. . ! & '#$. . '. . . ! & '%". . . . (. . ( . . . ! & '#$. '. . . ! & '%". . . . . . ! & '#$. '. . . ! & '%". ůĞĂƌĞƌƐŽƵƌĐĞĐŽĚĞ. . . . ! & '%". EƵŵďĞƌŽĨƐƚƵĚĞŶƚƐ. EƵŵďĞƌŽĨƐƚƵĚĞŶƚƐ –. . *. . ^ŚŽƌƚĞƌƐŽƵƌĐĞĐŽĚĞ . ! & '%". ĂƐŝĞƌƚŽĨŝŶĚĚĞĨĞĐƚƐ. (. . . . ĂƐŝĞƌƚŽĚĞǀĞůŽƉǁĞďĂƉƉůŝĐĂƚŝŽŶƐ . . DŽƌĞĐŽŵĨŽƌƚĂďůĞƉƌŽŐƌĂŵŵŝŶŐĞŶǀŝƌŽŶŵĞŶƚ. (. . . '. . ĂƐŝĞƌƚŽĚĞǀĞůŽƉĚĞƐŬƚŽƉĂƉƉůŝĐĂƚŝŽŶƐ . ). &ĂƐƚĞƌƚŽĚĞǀĞůŽƉƉƌŽŐƌĂŵƐ. . . . DŽƌĞƌĞĂƐŽŶĂďůĞĂŶĚŝŶƚƵŝƚŝǀĞƐLJŶƚĂdž . (. . . ). . ). ). (. ) . ! & '#$. '. . . ! & '%".
(8) 108 Łukasz RadliĔski, Jakub Swacha C# or Java? – analysis of student preferences. ĂƐŝĞƌƚŽĨŝŶĚĚŽĐƵŵĞŶƚĂƚŝŽŶ. . . ) . ( . . . . ! & '#$. '. ! & '%". EƵŵďĞƌŽĨƐƚƵĚĞŶƚƐ. EƵŵďĞƌŽĨƐƚƵĚĞŶƚƐ. ĂƐŝĞƌƚŽŝŶƐƚĂůůĂŶĚƵƐĞĂƚŚŽŵĞ . . . ). ). . ) . . . . ! & '#$. '. ! & '%". EƵŵďĞƌŽĨƐƚƵĚĞŶƚƐ. ,ŝŐŚĞƌǀĂůƵĞĨŽƌĨƵƚƵƌĞƉƌŽĨĞƐƐŝŽŶĂů ĐĂƌĞĞƌ . . . ( . . . . . ! & '#$. '. ! & '%". Figure 2 Histograms of student responses B. By Group Results We have aggregated the responses provided by students and analyzed them in three groupings of students, depending on: 1. mode of studies – full-time or part-time, 2. level of general programming skills – beginner or non-beginner, 3. mode of studies and level of general programming skills – full-time beginner, full-time non-beginner, part-time beginner, or part-time non-beginner. Figure 3 illustrates decision scores for C# and Java obtained from AHP for all of these groups. The higher value of the score for one alternative indicates the overall preference of respondents to this alternative rather than the second one. For all analyzed groups, there was a clear overall dominance of preferences for C# rather than Java. For the first grouping, depending on the mode of studies, part-time students more strongly prefer C# over Java than full-time students. This may be due to the fact that part-time students have less time to acquire the necessary knowledge and skills than full-time students, and they see that with such limited time it is easier for them to learn C# rather than Java. For the second grouping, depending on the level of general programming skills, there was also a clear dominance of C# over Java. However, the difference in the scores between beginners and non-beginners was very narrow..
(9) 109. Studies & Proceedings of Polish Association for Knowledge Management No. 58, 2012. .- . , - . 0 /- . +). , - , - - . +*. +( + +(. +)) +) #$ %". +*( +. .- .- - . +(). +* + +. +(( +** +)). + + + +( +* +. Figure 3 Results by group from the AHP model For the third grouping, depending on both the mode of studies and the level of general programming skills, part-time beginner students provided the highest difference between the scores – 0.808 for C# and 0.193 for Java. Full-time beginner students provided the smallest difference between the scores – 0.586 for C# and 0.414 for Java. Results for this grouping revealed that the relationship between the level of general programming skills and preferences for languages is not straightforward. In the subgroup of full-time students, those who are nonbeginners prefer C# over Java more strongly than those who are beginners. However, in the subgroup of part-time students, those who are beginners prefer C# over Java more strongly than non-beginners. Still, the differences in preferences between beginners and non-beginners are not that great. C. Overall Results Figure 4 illustrates results from the AHP model aggregated for the entire survey. The decision scores are: 0.727 for C# and 0.273 for Java. Since the score for C# is approximately 2.7 times higher than the score for Java, these results confirm the overall dominance of C# in student preferences. In addition to the overall decision score, this figure shows the contribution of each criterion to the score. The higher bar for a criterion indicates the larger contribution. For the C# score, the following criteria have the highest contribution (all at the same level): – simpler at the first contact, – faster to develop programs, – faster to develop desktop applications, – shorter source code, – clearer source code, – more comfortable programming environment..
(10) 110 Łukasz RadliĔski, Jakub Swacha C# or Java? – analysis of student preferences. The lowest contribution for C# contains two factors: ‘easier to install and use at home’ and ‘higher value for future professional career’. For Java, the order of the level of contribution is reversed – i.e. criteria with the lowest contribution to the C# score have the highest contribution to the Java score, and criteria with the highest contribution to the C# score have the lowest contribution to the Java score. +*.
(11) & . +)). 1 . +). ! " ' 2. +(. . ! " 1 !! . + 1 ! . +. 1 &!! & . +).
(12) !. + # !. & " . +. 1 ! . +. 1 &!! 3 " && & . . #$. %". Figure 4 Overall results from AHP model with contributions by each criterion 5. Threats to Validity We have identified the following threats to the validity of the obtained results. First, the number of respondents is relatively small. Although we asked all our students to complete the questionnaire, about 15% of students attending both courses did not participate in the survey. So far, we have been mostly interested in opinions from our students as they have already been familiar with our educational environment. In the future, we plan to extend the analysis by involving students from other universities. Although there were some important similarities between courses for C# and Java, there were also some differences between them. We have highlighted them in Table 3. The course leader, based on earlier similar research [21], selected the questions for the survey. It is possible that, from the students’ point of view, there were other important differences between C# and Java not included in the questionnaire. The weights for criteria in the AHP model have been arbitrarily set by the course leader, according to his vision for both courses. Although setting other weights would obtain different results, the general dominance in answers to nearly all questions would not be broken. We could not analyze student preferences depending on the gender of students because only three female students participated in the survey. Thus, the results would not be representative if we performed such an analysis..
(13) 111. Studies & Proceedings of Polish Association for Knowledge Management No. 58, 2012. 6. Conclusion Based on the results of our study that was aimed at investigating student preferences to learning C# or Java, we can draw the following main conclusions: 1. Students very strongly prefer to learn C# rather than Java. 2. Part-time students more strongly prefer learning C# over Java than full-time students. 3. The impact of prior level of general programming skills of students on preferences for C#/Java does not seem to be significant. 4. Although the vast majority of students strongly prefer learning C#, there were some, but very few, students who actually prefer learning Java. 5. In none of analyzed groups of students was Java preferred over C#. 6. The only criterion where, on average, students gave a preference to Java was a ‘higher value for future professional career’. Yet, the difference in ratings between C# and Java in this aspect was very narrow. In the future, we plan to extend the survey by also analyzing the preferences of students from other universities. Additionally, we plan to include programming languages other than C# and Java. We also plan to analyze how student preferences change over time by performing surveys at the beginning and end of the courses and then comparing the results.. Bibliography [1] [2] [3] [4] [5] [6] [7]. [8]. [9]. Aczél, J., Saaty, T., Procedures for synthesizing ratio judgements, Journal of Mathematical Psychology, 27, 1 (1983) 93–102. Beuthe, M., Scannella, G., Comparative analysis of UTA multicriteria methods, European Journal of Operational Research, 130, 2 (2001) 246–262. Brans, J., Vincke, P., A preference ranking organisation method: The PROMETHEE method for MCDM, Management Science, 31, 6 (1985) 647–656. Charnes, A., Cooper, W.W., Ferguson, R., Optimal estimation of executive compensation by linear programming, Management Science, 1, 1955, 138–151. Comparison of C Sharp and Java, http://en.wikipedia.org/wiki/Comparison_of_C _Sharp_and_Java, 2011 (accessed on 25 June 2011). Computerworld Development Survey gives nod to C#, ComputerWorld, March 2005, http://www.computerworld.com/s/article/100542 (accessed on 25 June 2011). Conwey, D. Ranking the popularity of programming languages, 2010, http://www.dataists.com/2010/12/ranking-the-popularity-of-programming-langauges/ (accessed on 25 June 2011). Dagdeviren, H., Juric, R., Ogunleye, O., Tesanovic, I., Analysis of integrated development environments for J2EE applications. In Proceedings of the 11th IASTED International Conference on Software Engineering and Applications (SEA '07), Jeffrey E. Smith (Ed.). ACTA Press, Anaheim, CA, USA, 2007, 349–354. Dyer, J., Fishburn, P., Steuer, R., Wallenius, J., Zionts, S., Multiple Criteria Decision Making, Multiattribute Utility Theory: The Next Ten Years, “Management Science”, 38, 5 (1992) 645–654..
(14) 112 Łukasz RadliĔski, Jakub Swacha C# or Java? – analysis of student preferences. [10]. [11] [12] [13]. [14] [15]. [16]. [17]. [18] [19] [20]. [21] [22] [23] [24]. Edwards, W., Barron, F., SMARTS and SMARTER: Improved simple methods for multiattribute utility measurement, Organizational Behavior and Human Decision Processes, 60 (1994) 306–325. Jadhav, A., Sonar, R., Evaluating and selecting software packages: A review, Information and Software Technology, 51, 3 (2009) 555–563. Java vs. C#. Code for Code Comparison, 2008, http://www.javacamp.org/javavscsharp/ (accessed on 25 June 2011). Melón, M., Beltran, P., Cruz, M., An AHP-based evaluation procedure for Innovative Educational Projects: A face-to-face vs. computer-mediated case study, Omega – The International Journal of Management Science, 36 (2008) 754–765. Most Popular Programming Languages, 2007, http://www.devtopics.com/most-popularprogramming-languages/ (accessed on 25 June 2011). Obarasanjo, D., A Comparison of Microsoft’s C# Programming Language to SUN Microsystems’ Java Programming Language, 2007, http://www.25hoursaday.com/CsharpVsJava.html (accessed on 25 June 2011). Roy, B., "Classement et choix en présence de points de vue multiples (la méthode ELECTRE)". La Revue d'Informatique et de Recherche Opérationelle (RIRO), (8) 1968, 57–75. Rothberg, D., 10 Programming Languages You Should Learn Right Now, eWeek.com, 2006, http://www.eweek.com/c/a/IT-Management/10-Programming-Languages-YouShould-Learn-Right-Now/ (accessed on 25 June 2011). Saaty, T., Decision Making with Dependence and Feedback: The Analytic Network Process. Pittsburgh, Pennsylvania: RWS Publications, 1996. Saaty, T., The Analytic Hierarchy Process, McGraw-Hill, New York, 1980. Swacha, J., New concepts for teaching computer programming to future Information Technology engineers, [in:] Perspective Technologies and Methods in MEMS Design, Lviv Polytechnic National University, Lviv (2010), 188–191. Swacha, J., Muszy%ska, K., Python and C#: A Comparative Analysis from Students’ Perspective, Annales UMCS, 2011 (submitted). The C# Programming Language for Java Developers, Microsoft Developer Library, http://msdn.microsoft.com/en-us/library/ms228602.aspx (accessed on 25 June 2011) TIOBE Programming Community Index for June 2011, TIOBE Software, 2011, http://www.tiobe.com/index.php/content/paperinfo/tpci/ (accessed on 25 June 2011). Xu, X., The SIR method: A superiority and inferiority ranking method for multiple criteria decision making, European Journal of Operational Research, Volume 131, Issue 3, 16 June 2001, 587–602..
(15) 113. Studies & Proceedings of Polish Association for Knowledge Management No. 58, 2012. C# CZY JAVA? – ANALIZA PREFERENCJI STUDENTÓW Streszczenie Celem niniejszej pracy jest analiza preferencji studentów dotyczących uczenia siĊ jednego z dwóch jĊzyków programowania: C# i Javy. WĞród studentów kierunku ”informatyka i ekonometria” na Uniwersytecie SzczeciĔskim przeprowadzone zostało badanie ankietowe. Wszyscy studenci uczyli siĊ zarówno C# i Javy w tym samym semestrze i z tą samą osobą prowadzącą oba przedmioty. Przeanalizowane zostały odpowiedzi na kaĪde z trzynastu pytaĔ. NastĊpnie odpowiedzi zostały zagregowane z uĪyciem metody Analytic Hierarchy Process (AHP) w celu iloĞciowego wyraĪenia preferencji studentów. Wyniki wykazują bardzo silną dominacjĊ preferencji studentów odnoĞnie uczenia siĊ C# (73%) w przeciwieĔstwie do Javy (27%). Co wiĊcej, jedyną przewagĊ Javy stanowi, zdaniem respondentów, jej wyĪsza wartoĞü w przyszłej karierze zawodowej. Najsilniejsze preferencje wzglĊdem C# przejawiali studenci studiów zaocznych okreĞlający siebie jako początkujących, a najsłabsze preferencje wzglĊdem C# – studenci studiów dziennych, równieĪ początkujący. Słowa kluczowe: C#, Java, studenci, uczenie si, programowanie, preferencje, AHP Łukasz Radli%ski Jakub Swacha Institute of Information Technology in Management University of Szczecin, Poland e-mail: lukrad@uoo.univ.szczecin.pl jakubs@uoo.univ.szczecin.pl.
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