Sustainable Higher Education Development through Technology Enhanced Learning

[EN] Higher education is incorporating Information and Communication Technology (ICT) at a fast rate for different purposes. Scientific papers include within the concept of Technology Enhanced Learning (TEL) the myriad applications of information and communication technology, e-resources, and pedagogical approaches to the development of education. TEL¿s specific application to higher education is especially relevant for countries under rapid development for providing quick and sustainable access to quality education (UN sustainable development goal 4). This paper presents the research results of an online pedagogical experience in collaborative academic research for analyzing good practice in TEL-supported higher education development. The results are obtained through a pilot implementation providing curated data on TEL competency¿s development of faculty skills and analysis of developing sustainable higher education degrees through TEL cooperation, for capacity building. Given the increased volume and complexity of the knowledge to be delivered, and the exponential growth of the need for skilled workers in emerging economies, online training is the most effective way of delivering a sustainable higher education. The results of the PETRA Erasmus+ capacity-building project provides evidence of a successful implementation of a TEL-supported methodology for collaborative faculty development focused on future online degrees built collaboratively and applied locally.This research was co-funded by the European Commission through the Erasmus+ KA2 project "Promoting Excellence in Teaching and Learning in Azerbaijani Universities (PETRA)" project number 573630-EPP-1-2016-1-ES-EPPKA2-CBHE-JP.Orozco-Messana, J.; Martínez-Rubio, J.; Gonzálvez-Pons, AM. (2020). Sustainable Higher Education Development through Technology Enhanced Learning. Sustainability. 12(9):1-13. https://doi.org/10.3390/su12093600S113129Abdullah, F., & Ward, R. (2016). Developing a General Extended Technology Acceptance Model for E-Learning (GETAMEL) by analysing commonly used external factors. Computers in Human Behavior, 56, 238-256. doi:10.1016/j.chb.2015.11.036Becker, H. J., & Ravitz, J. (1999). The Influence of Computer and Internet Use on Teachers’ Pedagogical Practices and Perceptions. Journal of Research on Computing in Education, 31(4), 356-384. doi:10.1080/08886504.1999.10782260Mumford, S., & Dikilitaş, K. (2020). Pre-service language teachers reflection development through online interaction in a hybrid learning course. Computers & Education, 144, 103706. doi:10.1016/j.compedu.2019.103706Lee, D., Watson, S. L., & Watson, W. R. (2020). The Relationships Between Self-Efficacy, Task Value, and Self-Regulated Learning Strategies in Massive Open Online Courses. The International Review of Research in Open and Distributed Learning, 21(1), 23-39. doi:10.19173/irrodl.v20i5.4389Passey, D. (2019). Technology‐enhanced learning: Rethinking the term, the concept and its theoretical background. British Journal of Educational Technology, 50(3), 972-986. doi:10.1111/bjet.12783Lai, Y.-C., & Peng, L.-H. (2019). Effective Teaching and Activities of Excellent Teachers for the Sustainable Development of Higher Design Education. Sustainability, 12(1), 28. doi:10.3390/su12010028Lee, S., Lee, H., & Kim, T. (2018). A Study on the Instructor Role in Dealing with Mixed Contents: How It Affects Learner Satisfaction and Retention in e-Learning. Sustainability, 10(3), 850. doi:10.3390/su10030850“Continuous Improvement in Teaching Strategies through Lean Principles”. Teaching & Learning Symposium, University of Southern Indiana http://hdl.handle.net/20.500.12419/455The DeLone and McLean Model of Information Systems Success: A Ten-Year Update. (2003). Journal of Management Information Systems, 19(4), 9-30. doi:10.1080/07421222.2003.11045748Goodman, J., Melkers, J., & Pallais, A. (2019). Can Online Delivery Increase Access to Education? Journal of Labor Economics, 37(1), 1-34. doi:10.1086/698895Alexander, J., Barcellona, M., McLachlan, S., & Sackley, C. (2019). Technology-enhanced learning in physiotherapy education: Student satisfaction and knowledge acquisition of entry-level students in the United Kingdom. Research in Learning Technology, 27(0). doi:10.25304/rlt.v27.2073How Can Adaptive Platforms Improve Student Learning Outcomes? A Case Study of Open Educational Resources and Adaptive Learning Platforms https://ssrn.com/abstract=3478134Sun, A., & Chen, X. (2016). Online Education and Its Effective Practice: A Research Review. Journal of Information Technology Education: Research, 15, 157-190. doi:10.28945/3502EU Commission https://ec.europa.eu/education/education-in-the-eu/digital-education-action-plan_enEssence Project https://husite.nl/essence/Orozco-Messana, J., de la Poza-Plaza, E., & Calabuig-Moreno, R. (2020). Experiences in Transdisciplinary Education for the Sustainable Development of the Built Environment, the ISAlab Workshop. Sustainability, 12(3), 1143. doi:10.3390/su12031143Kurilovas, E., & Kubilinskiene, S. (2020). Lithuanian case study on evaluating suitability, acceptance and use of IT tools by students – An example of applying Technology Enhanced Learning Research methods in Higher Education. Computers in Human Behavior, 107, 106274. doi:10.1016/j.chb.2020.10627

Partial Correctness of a Power Algorithm

This work continues a formal verification of algorithms written in terms of simple-named complex-valued nominative data [6],[8],[15],[11],[12],[13]. In this paper we present a formalization in the Mizar system [3],[1] of the partial correctness of the algorithm: i := val.1 j := val.2 b := val.3 n := val.4 s := val.5 while (i n) i := i + j s := s * b return s computing the natural n power of given complex number b, where variables i, b, n, s are located as values of a V-valued Function, loc, as: loc/.1 = i, loc/.3 = b, loc/.4 = n and loc/.5 = s, and the constant 1 is located in the location loc/.2 = j (set V represents simple names of considered nominative data [17]).The validity of the algorithm is presented in terms of semantic Floyd-Hoare triples over such data [9]. Proofs of the correctness are based on an inference system for an extended Floyd-Hoare logic [2],[4] with partial pre- and post-conditions [14],[16],[7],[5].Institute of Informatics, University of Białystok, PolandGrzegorz Bancerek, Czesław Byliński, Adam Grabowski, Artur Korniłowicz, Roman Matuszewski, Adam Naumowicz, and Karol Pąk. The role of the Mizar Mathematical Library for interactive proof development in Mizar. Journal of Automated Reasoning, 61(1):9–32, 2018. doi:10.1007/s10817-017-9440-6.R.W. Floyd. Assigning meanings to programs. Mathematical aspects of computer science, 19(19–32), 1967.Adam Grabowski, Artur Korniłowicz, and Adam Naumowicz. Four decades of Mizar. Journal of Automated Reasoning, 55(3):191–198, 2015. doi:10.1007/s10817-015-9345-1.C.A.R. Hoare. An axiomatic basis for computer programming. Commun. ACM, 12(10): 576–580, 1969.Ievgen Ivanov and Mykola Nikitchenko. On the sequence rule for the Floyd-Hoare logic with partial pre- and post-conditions. In Proceedings of the 14th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer. Volume II: Workshops, Kyiv, Ukraine, May 14–17, 2018, volume 2104 of CEUR Workshop Proceedings, pages 716–724, 2018.Ievgen Ivanov, Mykola Nikitchenko, Andrii Kryvolap, and Artur Korniłowicz. Simple-named complex-valued nominative data – definition and basic operations. Formalized Mathematics, 25(3):205–216, 2017. doi:10.1515/forma-2017-0020.Ievgen Ivanov, Artur Korniłowicz, and Mykola Nikitchenko. Implementation of the composition-nominative approach to program formalization in Mizar. The Computer Science Journal of Moldova, 26(1):59–76, 2018.Ievgen Ivanov, Artur Korniłowicz, and Mykola Nikitchenko. On an algorithmic algebra over simple-named complex-valued nominative data. Formalized Mathematics, 26(2):149–158, 2018. doi:10.2478/forma-2018-0012.Ievgen Ivanov, Artur Korniłowicz, and Mykola Nikitchenko. An inference system of an extension of Floyd-Hoare logic for partial predicates. Formalized Mathematics, 26(2): 159–164, 2018. doi:10.2478/forma-2018-0013.Ievgen Ivanov, Artur Korniłowicz, and Mykola Nikitchenko. Partial correctness of GCD algorithm. Formalized Mathematics, 26(2):165–173, 2018. doi:10.2478/forma-2018-0014.Ievgen Ivanov, Artur Korniłowicz, and Mykola Nikitchenko. On algebras of algorithms and specifications over uninterpreted data. Formalized Mathematics, 26(2):141–147, 2018. doi:10.2478/forma-2018-0011.Artur Kornilowicz, Andrii Kryvolap, Mykola Nikitchenko, and Ievgen Ivanov. Formalization of the algebra of nominative data in Mizar. In Maria Ganzha, Leszek A. Maciaszek, and Marcin Paprzycki, editors, Proceedings of the 2017 Federated Conference on Computer Science and Information Systems, FedCSIS 2017, Prague, Czech Republic, September 3–6, 2017., pages 237–244, 2017. ISBN 978-83-946253-7-5. doi:10.15439/2017F301.Artur Kornilowicz, Andrii Kryvolap, Mykola Nikitchenko, and Ievgen Ivanov. Formalization of the nominative algorithmic algebra in Mizar. In Leszek Borzemski, Jerzy Świątek, and Zofia Wilimowska, editors, Information Systems Architecture and Technology: Proceedings of 38th International Conference on Information Systems Architecture and Technology – ISAT 2017 – Part II, Szklarska Poręba, Poland, September 17–19, 2017, volume 656 of Advances in Intelligent Systems and Computing, pages 176–186. Springer, 2017. ISBN 978-3-319-67228-1. doi:10.1007/978-3-319-67229-8_16.Artur Korniłowicz, Andrii Kryvolap, Mykola Nikitchenko, and Ievgen Ivanov. An approach to formalization of an extension of Floyd-Hoare logic. In Vadim Ermolayev, Nick Bassiliades, Hans-Georg Fill, Vitaliy Yakovyna, Heinrich C. Mayr, Vyacheslav Kharchenko, Vladimir Peschanenko, Mariya Shyshkina, Mykola Nikitchenko, and Aleksander Spivakovsky, editors, Proceedings of the 13th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer, Kyiv, Ukraine, May 15–18, 2017, volume 1844 of CEUR Workshop Proceedings, pages 504–523. CEUR-WS.org, 2017.Artur Korniłowicz, Ievgen Ivanov, and Mykola Nikitchenko. Kleene algebra of partial predicates. Formalized Mathematics, 26(1):11–20, 2018. doi:10.2478/forma-2018-0002.Andrii Kryvolap, Mykola Nikitchenko, and Wolfgang Schreiner. Extending Floyd-Hoare logic for partial pre- and postconditions. In Vadim Ermolayev, Heinrich C. Mayr, Mykola Nikitchenko, Aleksander Spivakovsky, and Grygoriy Zholtkevych, editors, Information and Communication Technologies in Education, Research, and Industrial Applications: 9th International Conference, ICTERI 2013, Kherson, Ukraine, June 19–22, 2013, Revised Selected Papers, pages 355–378. Springer International Publishing, 2013. ISBN 978-3-319-03998-5. doi:10.1007/978-3-319-03998-5_18.Volodymyr G. Skobelev, Mykola Nikitchenko, and Ievgen Ivanov. On algebraic properties of nominative data and functions. In Vadim Ermolayev, Heinrich C. Mayr, Mykola Nikitchenko, Aleksander Spivakovsky, and Grygoriy Zholtkevych, editors, Information and Communication Technologies in Education, Research, and Industrial Applications – 10th International Conference, ICTERI 2014, Kherson, Ukraine, June 9–12, 2014, Revised Selected Papers, volume 469 of Communications in Computer and Information Science, pages 117–138. Springer, 2014. ISBN 978-3-319-13205-1. doi:10.1007/978-3-319-13206-8_6.27218919

Mediatisation in Twitter: an exploratory analysis of the 2015 Spanish general election

[EN] The mediatisation model in politics assumes that media conveys political messages between parties and citizenship, with the risk of promoting issues that frame the electoral content in terms of competition. These dynamics could distract from the debate of ideas and political policies. However, digital media like Twitter provide direct communication channels between parties, candidates and users. The present research explores Twitter content during an electoral campaign focused on the four issues proposed by Patterson (1980) to assess mediatisation: political, policy, campaign and personal (regarding the candidate). The goal of this research study is to evaluate the degree of mediatisation on Twitter using this typology. The research also evaluates the influence of the issue on retweet volume. The study¿s basis was a 15.8 million-tweet corpus obtained during the 2015 Spanish General Election pre-campaign and campaign. This dataset was analysed using an automatic classification system. The results highlighted a predominance of policy issues during both the pre- campaign and campaign, except for the two televised debates, during which campaign issues were the most prevalent. On the election night, users commented much more on political issues. Finally, the kind of issue most likely to be retweeted was policy issues.This research was supported by the Spanish Ministry of Economy and Competitiveness, with Grants CSO2013-43960-R (Los flujos de comunicación en los procesos de movilización política: medios, blogs y líderes de opinión) and CSO2016-77331-C2-1-R (Estrategias, agendas y discursos en las cibercampañas electorales: medios de comunicación y ciudadanos).Baviera, T.; Calvo, D.; Llorca-Abad, G. (2019). Mediatisation in Twitter: an exploratory analysis of the 2015 Spanish general election. Journal of International Communication. 25(2):275-300. https://doi.org/10.1080/13216597.2019.1634619S275300252Antonakaki, D., Spiliotopoulos, D., V. Samaras, C., Pratikakis, P., Ioannidis, S., & Fragopoulou, P. (2017). Social media analysis during political turbulence. PLOS ONE, 12(10), e0186836. doi:10.1371/journal.pone.0186836Barberá, P. (2015). Birds of the Same Feather Tweet Together: Bayesian Ideal Point Estimation Using Twitter Data. Political Analysis, 23(1), 76-91. doi:10.1093/pan/mpu011Bartholomé, G., Lecheler, S., & de Vreese, C. (2017). Towards A Typology of Conflict Frames. Journalism Studies, 19(12), 1689-1711. doi:10.1080/1461670x.2017.1299033Batrinca, B., & Treleaven, P. C. (2014). Social media analytics: a survey of techniques, tools and platforms. AI & SOCIETY, 30(1), 89-116. doi:10.1007/s00146-014-0549-4Baviera, T., Peris, À., & Cano-Orón, L. (2017). Political candidates in infotainment programmes and their emotional effects on Twitter: an analysis of the 2015 Spanish general elections pre-campaign season. Contemporary Social Science, 14(1), 144-156. doi:10.1080/21582041.2017.1367833BLUMLER, J. G., & KAVANAGH, D. (1999). The Third Age of Political Communication: Influences and Features. Political Communication, 16(3), 209-230. doi:10.1080/105846099198596Bor, S. E. (2013). Using Social Network Sites to Improve Communication Between Political Campaigns and Citizens in the 2012 Election. American Behavioral Scientist, 58(9), 1195-1213. doi:10.1177/0002764213490698Brants, K., & Neijens, P. (1998). The Infotainment of Politics. Political Communication, 15(2), 149-164. doi:10.1080/10584609809342363Burnap, P., Gibson, R., Sloan, L., Southern, R., & Williams, M. (2016). 140 characters to victory?: Using Twitter to predict the UK 2015 General Election. Electoral Studies, 41, 230-233. doi:10.1016/j.electstud.2015.11.017Campos-Domínguez, E. (2017). Twitter y la comunicación política. El Profesional de la Información, 26(5), 785. doi:10.3145/epi.2017.sep.01Campos-Domínguez, E., & Calvo, D. (2017). Electoral campaign on the Internet: Planning, impact and viralization on Twitter during the Spanish general election, 2015. Comunicación y Sociedad, 0(29), 93-116. doi:10.32870/cys.v0i29.6423Ceron, A., & Splendore, S. (2016). From contents to comments: Social TV and perceived pluralism in political talk shows. New Media & Society, 20(2), 659-675. doi:10.1177/1461444816668187Chadwick, A. (2013). The Hybrid Media System. doi:10.1093/acprof:oso/9780199759477.001.0001Conway, B. A., Kenski, K., & Wang, D. (2015). The Rise of Twitter in the Political Campaign: Searching for Intermedia Agenda-Setting Effects in the Presidential Primary. Journal of Computer-Mediated Communication, 20(4), 363-380. doi:10.1111/jcc4.12124Couldry, N., & Hepp, A. (2013). Conceptualizing Mediatization: Contexts, Traditions, Arguments. Communication Theory, 23(3), 191-202. doi:10.1111/comt.12019Dang-Xuan, L., Stieglitz, S., Wladarsch, J., & Neuberger, C. (2013). AN INVESTIGATION OF INFLUENTIALS AND THE ROLE OF SENTIMENT IN POLITICAL COMMUNICATION ON TWITTER DURING ELECTION PERIODS. Information, Communication & Society, 16(5), 795-825. doi:10.1080/1369118x.2013.783608D’heer, E., & Verdegem, P. (2014). Conversations about the elections on Twitter: Towards a structural understanding of Twitter’s relation with the political and the media field. European Journal of Communication, 29(6), 720-734. doi:10.1177/0267323114544866Díaz-Parra, I., & Jover-Báez, J. (2016). Social movements in crisis? From the 15-M movement to the electoral shift in Spain. International Journal of Sociology and Social Policy, 36(9/10), 680-694. doi:10.1108/ijssp-09-2015-0101DiGrazia, J., McKelvey, K., Bollen, J., & Rojas, F. (2013). More Tweets, More Votes: Social Media as a Quantitative Indicator of Political Behavior. PLoS ONE, 8(11), e79449. doi:10.1371/journal.pone.0079449Felt, M. (2016). Social media and the social sciences: How researchers employ Big Data analytics. Big Data & Society, 3(1), 205395171664582. doi:10.1177/2053951716645828Filer, T., & Fredheim, R. (2016). Popular with the Robots: Accusation and Automation in the Argentine Presidential Elections, 2015. International Journal of Politics, Culture, and Society, 30(3), 259-274. doi:10.1007/s10767-016-9233-7Freelon, D., & Karpf, D. (2014). Of big birds and bayonets: hybrid Twitter interactivity in the 2012 Presidential debates. Information, Communication & Society, 18(4), 390-406. doi:10.1080/1369118x.2014.952659Giglietto, F., & Selva, D. (2014). Second Screen and Participation: A Content Analysis on a Full Season Dataset of Tweets. Journal of Communication, 64(2), 260-277. doi:10.1111/jcom.12085Gil de Zúñiga, H., Garcia-Perdomo, V., & McGregor, S. C. (2015). What Is Second Screening? Exploring Motivations of Second Screen Use and Its Effect on Online Political Participation. Journal of Communication, 65(5), 793-815. doi:10.1111/jcom.12174Grover, P., Kar, A. K., Dwivedi, Y. K., & Janssen, M. (2019). Polarization and acculturation in US Election 2016 outcomes – Can twitter analytics predict changes in voting preferences. Technological Forecasting and Social Change, 145, 438-460. doi:10.1016/j.techfore.2018.09.009Jensen, K. B. (2013). Definitive and Sensitizing Conceptualizations of Mediatization. Communication Theory, 23(3), 203-222. doi:10.1111/comt.12014Jungherr, A. (2014). The Logic of Political Coverage on Twitter: Temporal Dynamics and Content. Journal of Communication, 64(2), 239-259. doi:10.1111/jcom.12087Kalsnes, B., Krumsvik, A. H., & Storsul, T. (2014). Social media as a political backchannel. Aslib Journal of Information Management, 66(3), 313-328. doi:10.1108/ajim-09-2013-0093Lee, K., Palsetia, D., Narayanan, R., Patwary, M. M. A., Agrawal, A., & Choudhary, A. (2011). Twitter Trending Topic Classification. 2011 IEEE 11th International Conference on Data Mining Workshops. doi:10.1109/icdmw.2011.171López García, G., Llorca Abad, G., Valera Ordaz, L., & Peris Blanes, A. (2018). Los debates electorales, ¿el último reducto frente la mediatización? Un estudio de caso de las elecciones generales españolas de 2015. Palabra Clave - Revista de Comunicación, 21(3), 772-797. doi:10.5294/pacla.2018.21.3.6López-Rico, C.-M., & Peris-Blanes, À. (2017). Agenda e imagen de los candidatos de las elecciones generales de 2015 en España en programas televisivos de infoentretenimiento. El Profesional de la Información, 26(4), 611. doi:10.3145/epi.2017.jul.05MAZZOLENI, G., & SCHULZ, W. (1999). «Mediatization» of Politics: A Challenge for Democracy? Political Communication, 16(3), 247-261. doi:10.1080/105846099198613Murthy, D. (2015). Twitter and elections: are tweets, predictive, reactive, or a form of buzz? Information, Communication & Society, 18(7), 816-831. doi:10.1080/1369118x.2015.1006659Russell Neuman, W., Guggenheim, L., Mo Jang, S., & Bae, S. Y. (2014). The Dynamics of Public Attention: Agenda-Setting Theory Meets Big Data. Journal of Communication, 64(2), 193-214. doi:10.1111/jcom.12088Orriols, L., & Cordero, G. (2016). The Breakdown of the Spanish Two-Party System: The Upsurge of Podemos and Ciudadanos in the 2015 General Election. South European Society and Politics, 21(4), 469-492. doi:10.1080/13608746.2016.1198454References to the IBEREVAL Workshop ProceedingsRill, S., Reinel, D., Scheidt, J., & Zicari, R. V. (2014). PoliTwi: Early detection of emerging political topics on twitter and the impact on concept-level sentiment analysis. Knowledge-Based Systems, 69, 24-33. doi:10.1016/j.knosys.2014.05.008Rogstad, I. (2016). Is Twitter just rehashing? Intermedia agenda setting between Twitter and mainstream media. Journal of Information Technology & Politics, 13(2), 142-158. doi:10.1080/19331681.2016.1160263Sampedro, V., & Lobera, J. (2014). The Spanish 15-M Movement: a consensual dissent? Journal of Spanish Cultural Studies, 15(1-2), 61-80. doi:10.1080/14636204.2014.938466Shah, D. V., Hanna, A., Bucy, E. P., Lassen, D. S., Van Thomme, J., Bialik, K., … Pevehouse, J. C. W. (2016). Dual Screening During Presidential Debates. American Behavioral Scientist, 60(14), 1816-1843. doi:10.1177/0002764216676245Shao, C., Ciampaglia, G. L., Varol, O., Yang, K.-C., Flammini, A., & Menczer, F. (2018). The spread of low-credibility content by social bots. Nature Communications, 9(1). doi:10.1038/s41467-018-06930-7Stella, M., Ferrara, E., & De Domenico, M. (2018). Bots increase exposure to negative and inflammatory content in online social systems. Proceedings of the National Academy of Sciences, 115(49), 12435-12440. doi:10.1073/pnas.1803470115Stier, S., Bleier, A., Lietz, H., & Strohmaier, M. (2018). Election Campaigning on Social Media: Politicians, Audiences, and the Mediation of Political Communication on Facebook and Twitter. Political Communication, 35(1), 50-74. doi:10.1080/10584609.2017.1334728Vaccari, C., Chadwick, A., & O’Loughlin, B. (2015). Dual Screening the Political: Media Events, Social Media, and Citizen Engagement. Journal of Communication, 65(6), 1041-1061. doi:10.1111/jcom.12187Vaccari, C., & Nielsen, R. K. (2013). What Drives Politicians’ Online Popularity? An Analysis of the 2010 U.S. Midterm Elections. Journal of Information Technology & Politics, 10(2), 208-222. doi:10.1080/19331681.2012.758072Vargo, C. J., Guo, L., McCombs, M., & Shaw, D. L. (2014). Network Issue Agendas on Twitter During the 2012 U.S. Presidential Election. Journal of Communication, 64(2), 296-316. doi:10.1111/jcom.12089Vergeer, M., & Franses, P. H. (2015). Live audience responses to live televised election debates: time series analysis of issue salience and party salience on audience behavior. Information, Communication & Society, 19(10), 1390-1410. doi:10.1080/1369118x.2015.1093526Xu, W. W., Sang, Y., Blasiola, S., & Park, H. W. (2014). Predicting Opinion Leaders in Twitter Activism Networks. American Behavioral Scientist, 58(10), 1278-1293. doi:10.1177/000276421452709

Semi-automatic assessment of unrestrained Java code: a Library, a DSL, and a workbench to assess exams and exercises

© ACM 2015. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in http://dx.doi.org/10.1145/2729094.2742615Automated marking of multiple-choice exams is of great interest in university courses with a large number of students. For this reason, it has been systematically implanted in almost all universities. Automatic assessment of source code is however less extended. There are several reasons for that. One reason is that almost all existing systems are based on output comparison with a gold standard. If the output is the expected, the code is correct. Otherwise, it is reported as wrong, even if there is only one typo in the code. Moreover, why it is wrong remains a mystery. In general, assessment tools treat the code as a black box, and they only assess the externally observable behavior. In this work we introduce a new code assessment method that also verifies properties of the code, thus allowing to mark the code even if it is only partially correct. We also report about the use of this system in a real university context, showing that the system automatically assesses around 50% of the work.This work has been partially supported by the EU (FEDER) and the Spanish Ministerio de Economíay Competitividad (Secretaría de Estado de Investigación, Desarrollo e Innovación) under grant TIN2013-44742-C4-1-R and by the Generalitat Valenciana under grant PROMETEOII2015/013. David Insa was partially supported by the Spanish Ministerio de Educación under FPU grant AP2010-4415.Insa Cabrera, D.; Silva, J. (2015). Semi-automatic assessment of unrestrained Java code: a Library, a DSL, and a workbench to assess exams and exercises. ACM. https://doi.org/10.1145/2729094.2742615SK. A Rahman and M. Jan Nordin. A review on the static analysis approach in the automated programming assessment systems. In National Conference on Programming 07, 2007.K. Ala-Mutka. A survey of automated assessment approaches for programming assignments. In Computer Science Education, volume 15, pages 83--102, 2005.C. Beierle, M. Kula, and M. Widera. Automatic analysis of programming assignments. In Proc. der 1. E-Learning Fachtagung Informatik (DeLFI '03), volume P-37, pages 144--153, 2003.J. Biggs and C. Tang. Teaching for Quality Learning at University : What the Student Does (3rd Edition). In Open University Press, 2007.P. Denny, A. Luxton-Reilly, E. Tempero, and J. Hendrickx. CodeWrite: Supporting student-driven practice of java. In Proceedings of the 42nd ACM technical symposium on Computer science education, pages 09--12, 2011.R. Hendriks. Automatic exam correction. 2012.P. Ihantola, T. Ahoniemi, V. Karavirta, and O. Seppala. Review of recent systems for automatic assessment of programming assignments. In Proceedings of the 10th Koli Calling International Conference on Computing Education Research, pages 86--93, 2010.H. Kitaya and U. Inoue. An online automated scoring system for Java programming assignments. In International Journal of Information and Education Technology, volume 6, pages 275--279, 2014.M.-J. Laakso, T. Salakoski, A. Korhonen, and L. Malmi. Automatic assessment of exercises for algorithms and data structures - a case study with TRAKLA2. In Proceedings of Kolin Kolistelut/Koli Calling - Fourth Finnish/Baltic Sea Conference on Computer Science Education, pages 28--36, 2004.Y. Liang, Q. Liu, J. Xu, and D. Wang. The recent development of automated programming assessment. In Computational Intelligence and Software Engineering, pages 1--5, 2009.K. A. Naudé, J. H. Greyling, and D. Vogts. Marking student programs using graph similarity. In Computers & Education, volume 54, pages 545--561, 2010.A. Pears, S. Seidman, C. Eney, P. Kinnunen, and L. Malmi. Constructing a core literature for computing education research. In SIGCSE Bulletin, volume 37, pages 152--161, 2005.F. Prados, I. Boada, J. Soler, and J. Poch. Automatic generation and correction of technical exercices. In International Conference on Engineering and Computer Education (ICECE 2005), 2005.M. Supic, K. Brkic, T. Hrkac, Z. Mihajlovic, and Z. Kalafatic. Automatic recognition of handwritten corrections for multiple-choice exam answer sheets. In Information and Communication Technology, Electronics and Microelectronics (MIPRO), pages 1136--1141, 2014.S. Tung, T. Lin, and Y. Lin. An exercise management system for teaching programming. In Journal of Software, 2013.T. Wang, X. Su, Y. Wang, and P. Ma. Semantic similarity-based grading of student programs. In Information and Software Technology, volume 49, pages 99--107, 2007

Factors Affecting Teacher Readiness for Online Learning (TROL) in Early Childhood Education: TISE and TPACK

This study aims to find empirical information about the effect of Technological Pedagogical Content Knowledge (TPACK), and Technology Integration Self Efficacy (TISE) on Teacher Readiness for Online Learning (TROL). This study uses a quantitative survey method with path analysis techniques. This study measures the readiness of kindergarten teachers in distance learning in Tanah Datar Regency, West Sumatra Province, Indonesia with a sampling technique using simple random sampling involving 105 teachers. Empirical findings reveal that; 1) there is a direct positive effect of Technology Integration Self Efficacy on Teacher Readiness for Online Learning; 2) there is a direct positive effect of PACK on Teacher Readiness for Online Learning; 3) there is a direct positive effect of Technology Integration Self Efficacy on TPACK. If want to improve teacher readiness for online learning, Technological Pedagogical Content Knowledge (TPACK) must be improved by paying attention to Technology Integration Self Efficacy (TISE). Keywords: TROL, TPACK, TISE, Early Childhood Education References: Abbitt, J. T. (2011). An Investigation of the Relationship between Self-Efficacy Beliefs about Technology Integration and Technological Pedagogical Content Knowledge (TPACK) among Preservice Teachers. Journal of Digital Learning in Teacher Education, 27(4), 134–143. Adedoyin, O. B., & Soykan, E. (2020). Covid-19 pandemic and online learning: The challenges and opportunities. Interactive Learning Environments, 1–13. https://doi.org/10.1080/10494820.2020.1813180 Adnan, M. (2020). Online learning amid the COVID-19 pandemic: Students perspectives. Journal of Pedagogical Sociology and Psychology, 1(2), 45–51. https://doi.org/10.33902/JPSP.2020261309 Alqurashi, E. (2016). Self-Efficacy in Online Learning Environments: A Literature Review. Contemporary Issues in Education Research (CIER), 9(1), 45–52. https://doi.org/10.19030/cier.v9i1.9549 Amir, H. (2016). Korelasi Pengaruh Faktor Efikasi Diri Dan Manajemen Diri Terhadap Motivasi Berprestasi Pada Mahasiswa Pendidikan Kimia Unversitas Bengkulu. Manajer Pendidikan, 10(4). Anderson, T. (2008). The theory and practice of online learning. Athabasca University Press. Anggraeni, N., Ridlo, S., & Setiati, N. (2018). The Relationship Between TISE and TPACK among Prospective Biology Teachers of UNNES. Journal of Biology Education, 7(3), 305–311. https://doi.org/10.15294/jbe.v7i3.26021 Ariani, D. N. (2015). Hubungan antara Technological Pedagogical Content Knowledge dengan Technology Integration Self Efficacy Guru Matematika di Sekolah Dasar. Muallimuna: Jurnal Madrasah Ibtidaiyah, 1(1), 79–91. Birisci, S., & Kul, E. (2019). Predictors of Technology Integration Self-Efficacy Beliefs of Preservice Teachers. Contemporary Educational Technology, 10(1). https://doi.org/10.30935/cet.512537 Bozkurt, A., Jung, I., Xiao, J., Vladimirschi, V., Schuwer, R., Egorov, G., Lambert, S. R., Al-freih, M., Pete, J., Olcott, D., Rodes, V., Aranciaga, I., Bali, M., Alvarez, A. V, Roberts, J., Pazurek, A., Raffaghelli, J. E., Panagiotou, N., Coëtlogon, P. De, … Paskevicius, M. (2020). UVicSPACE: Research & Learning Repository Navigating in a time of uncertainty and crisis. Asian Journal of Distance Education, 15(1), 1–126. Brinkley-Etzkorn, K. E. (2018). Learning to teach online: Measuring the influence of faculty development training on teaching effectiveness through a TPACK lens. The Internet and Higher Education, 38, 28–35. https://doi.org/10.1016/j.iheduc.2018.04.004 Butnaru, G. I., Niță, V., Anichiti, A., & Brînză, G. (2021). The effectiveness of online education during covid 19 pandemic—A comparative analysis between the perceptions of academic students and high school students from romania. 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Technological Pedagogical Content Knowledge (TPACK) in Action. Journal of Research on Technology in Education, 43(3), 211–229. https://doi.org/10.1080/15391523.2011.10782570 Hatlevik, I. K. R., & Hatlevik, O. E. (2018). Examining the relationship between teachers’ ICT self-efficacy for educational purposes, collegial collaboration, lack of facilitation and the use of ICT in teaching practice. Frontiers in Psychology, 9(JUN), 1–8. https://doi.org/10.3389/fpsyg.2018.00935 Hung, M. L. (2016). Teacher readiness for online learning: Scale development and teacher perceptions. Computers and Education, 94, 120–133. https://doi.org/10.1016/j.compedu.2015.11.012 Hung, M. L., Chou, C., Chen, C. H., & Own, Z. Y. (2010). Learner readiness for online learning: Scale development and student perceptions. Computers and Education, 55(3), 1080–1090. https://doi.org/10.1016/j.compedu.2010.05.004 Juanda, A., Shidiq, A. S., & Nasrudin, D. (2021). Teacher Learning Management: Investigating Biology Teachers’ TPACK to Conduct Learning During the Covid-19 Outbreak. Jurnal Pendidikan IPA Indonesia, 10(1), 48–59. https://doi.org/10.15294/jpii.v10i1.26499 Karatas, M. A.-K. (2020). COVID - 19 Pandemisinin Toplum Psikolojisine Etkileri ve Eğitime Yansımaları. Journal of Turkish Studies, Volume 15(Volume 15 Issue 4), 1–13. https://doi.org/10.7827/TurkishStudies.44336 Kaymak, Z. D., & Horzum, M. B. (2013). Relationship between online learning readiness and structure and interaction of online learning students. Kuram ve Uygulamada Egitim Bilimleri, 13(3), 1792–1797. https://doi.org/10.12738/estp.2013.3.1580 Keser, H., Karaoğlan Yılmaz, F. G., & Yılmaz, R. (2015). TPACK Competencies and Technology Integration Self-Efficacy Perceptions of Pre-Service Teachers. Elementary Education Online, 14(4), 1193–1207. https://doi.org/10.17051/io.2015.65067 Kim, J. (2020). Learning and Teaching Online During Covid-19: Experiences of Student Teachers in an Early Childhood Education Practicum. International Journal of Early Childhood, 52(2), 145–158. https://doi.org/10.1007/s13158-020-00272-6 Koehler, M. J., Mishra, P., & Cain, W. (2013). What is Technological Pedagogical Content Knowledge (TPACK)? Journal of Education, 193(3), 13–19. https://doi.org/10.1177/002205741319300303 Lee, Y., & Lee, J. (2014). Enhancing pre-service teachers’ self-efficacy beliefs for technology integration through lesson planning practice. Computers and Education, 73, 121–128. https://doi.org/10.1016/j.compedu.2014.01.001 Mallillin, L. L. D., Mendoza, L. C., Mallillin, J. B., Felix, R. C., & Lipayon, I. C. (2020). Implementation and Readiness of Online Learning Pedagogy: A Transition To Covid 19 Pandemic. European Journal of Open Education and E-Learning Studies, 5(2), 71–90. https://doi.org/10.46827/ejoe.v5i2.3321 Mishra, P. (2019). Considering Contextual Knowledge: The TPACK Diagram Gets an Upgrade. Journal of Digital Learning in Teacher Education, 35(2), 76–78. https://doi.org/10.1080/21532974.2019.1588611 Moorhouse, B. L. (2020). Adaptations to a face-to-face initial teacher education course ‘forced’ online due to the COVID-19 pandemic. Journal of Education for Teaching, 46(4), 609–611. https://doi.org/10.1080/02607476.2020.1755205 Mulyadi, D., Wijayatingsih, T. D., Budiastuti, R. E., Ifadah, M., & Aimah, S. (2020). Technological Pedagogical and Content Knowledge of ESP Teachers in Blended Learning Format. International Journal of Emerging Technologies in Learning (IJET), 15(06), 124. https://doi.org/10.3991/ijet.v15i06.11490 Murtaza, G., Mahmood, K., & Fatima, N. (2021). Readiness for Online Learning during COVID-19 pandemic: A survey of Pakistani LIS students The Journal of Academic Librarianship Readiness for Online Learning during COVID-19 pandemic: A survey of Pakistani LIS students. The Journal of Academic Librarianship, 47(3), 102346. https://doi.org/10.1016/j.acalib.2021.102346 Mustika, M., & Sapriya. (2019). Kesiapan Guru IPS dalam E-learning Berdasarkan: Survei melalui Pendekatan TPACK. 32–35. https://doi.org/10.1145/3306500.3306566 Niess, M. L. (2011). Investigating TPACK: Knowledge Growth in Teaching with Technology. Journal of Educational Computing Research, 44(3), 299–317. https://doi.org/10.2190/EC.44.3.c Oketch, & Otchieng, H. (2013). University of Nairobi, H. A. (2013). E-Learning Readiness Assessment Model in Kenyas’ Higher Education Institutions: A Case Study of University of Nairobi by: Oketch, Hada Achieng a Research Project Submitted in Partial Fulfillment of the Requirement of M. October. Pamuk, S., Ergun, M., Cakir, R., Yilmaz, H. B., & Ayas, C. (2015). Exploring relationships among TPACK components and development of the TPACK instrument. Education and Information Technologies, 20(2), 241–263. https://doi.org/10.1007/s10639-013-9278-4 Paraskeva, F., Bouta, H., & Papagianni, A. (2008). Individual characteristics and computer self-efficacy in secondary education teachers to integrate technology in educational practice. Computers and Education, 50(3), 1084–1091. https://doi.org/10.1016/j.compedu.2006.10.006 Putro, S. T., Widyastuti, M., & Hastuti, H. (2020). Problematika Pembelajaran di Era Pandemi COVID-19 Stud Kasus: Indonesia, Filipina, Nigeria, Ethiopia, Finlandia, dan Jerman. Geomedia Majalah Ilmiah Dan Informasi Kegeografian, 18(2), 50–64. Qudsiya, R., Widiyaningrum, P., & Setiati, N. (2018). The Relationship Between TISE and TPACK among Prospective Biology Teachers of UNNES. Journal of Biology Education, 7(3), 305–311. https://doi.org/10.15294/jbe.v7i3.26021 Reflianto, & Syamsuar. (2018). Pendidikan dan Tantangan Pembelajaran Berbasis Teknologi Informasi di Era Revolusi Industri 4.0. Jurnal Ilmiah Teknologi Pendidikan, 6(2), 1–13. Reski, A., & Sari, K. (2020). Analisis Kemampuan TPACK Guru Fisika Se-Distrik Merauke. Jurnla Kreatif Online, 8(1), 1–8. Ruggiero, D., & Mong, C. J. (2015). The teacher technology integration experience: Practice and reflection in the classroom. Journal of Information Technology Education, 14. Santika, V., Indriayu, M., & Sangka, K. B. (2021). Profil TPACK Guru Ekonomi di Indonesia sebagai Pendekatan Integrasi TIK selama Pembelajaran Jarak Jauh pada Masa Pandemi Covid-19. Duconomics Sci-Meet (Education & Economics Science Meet), 1, 356–369. https://doi.org/10.37010/duconomics.v1.5470 Semiz, K., & Ince, M. L. (2012). Pre-service physical education teachers’ technological pedagogical content knowledge, technology integration self-efficacy and instructional technology outcome expectations. Australasian Journal of Educational Technology, 28(7). https://doi.org/10.14742/ajet.800 Senthilkumar, Sivapragasam, & Senthamaraikannan. (2014). 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General Theory and Tools for Proving Algorithms in Nominative Data Systems

In this paper we introduce some new definitions for sequences of operations and extract general theorems about properties of iterative algorithms encoded in nominative data language [20] in the Mizar system [3], [1] in order to simplify the process of proving algorithms in the future. This paper continues verification of algorithms [10], [13], [12], [14] written in terms of simple-named complex-valued nominative data [6], [8], [18], [11], [15], [16]. The validity of the algorithm is presented in terms of semantic Floyd-Hoare triples over such data [9]. Proofs of the correctness are based on an inference system for an extended Floyd-Hoare logic [2], [4] with partial pre- and postconditions [17], [19], [7], [5].Institute of Informatics, University of Białystok, PolandGrzegorz Bancerek, Czesław Byliński, Adam Grabowski, Artur Korniłowicz, Roman Matuszewski, Adam Naumowicz, and Karol Pąk. The role of the Mizar Mathematical Library for interactive proof development in Mizar. Journal of Automated Reasoning, 61(1):9–32, 2018. doi:10.1007/s10817-017-9440-6.R.W. Floyd. Assigning meanings to programs. Mathematical Aspects of Computer Science, 19(19–32), 1967.Adam Grabowski, Artur Korniłowicz, and Adam Naumowicz. Four decades of Mizar. Journal of Automated Reasoning, 55(3):191–198, 2015. doi:10.1007/s10817-015-9345-1.C.A.R. Hoare. An axiomatic basis for computer programming. Commun. ACM, 12(10): 576–580, 1969.Ievgen Ivanov and Mykola Nikitchenko. On the sequence rule for the Floyd-Hoare logic with partial pre- and post-conditions. In Proceedings of the 14th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer. Volume II: Workshops, Kyiv, Ukraine, May 14–17, 2018, volume 2104 of CEUR Workshop Proceedings, pages 716–724, 2018.Ievgen Ivanov, Mykola Nikitchenko, Andrii Kryvolap, and Artur Korniłowicz. Simple-named complex-valued nominative data – definition and basic operations. Formalized Mathematics, 25(3):205–216, 2017. doi:10.1515/forma-2017-0020.Ievgen Ivanov, Artur Korniłowicz, and Mykola Nikitchenko. Implementation of the composition-nominative approach to program formalization in Mizar. The Computer Science Journal of Moldova, 26(1):59–76, 2018.Ievgen Ivanov, Artur Korniłowicz, and Mykola Nikitchenko. On an algorithmic algebra over simple-named complex-valued nominative data. Formalized Mathematics, 26(2):149–158, 2018. doi:10.2478/forma-2018-0012.Ievgen Ivanov, Artur Korniłowicz, and Mykola Nikitchenko. An inference system of an extension of Floyd-Hoare logic for partial predicates. Formalized Mathematics, 26(2): 159–164, 2018. doi:10.2478/forma-2018-0013.Ievgen Ivanov, Artur Korniłowicz, and Mykola Nikitchenko. Partial correctness of GCD algorithm. Formalized Mathematics, 26(2):165–173, 2018. doi:10.2478/forma-2018-0014.Ievgen Ivanov, Artur Korniłowicz, and Mykola Nikitchenko. On algebras of algorithms and specifications over uninterpreted data. Formalized Mathematics, 26(2):141–147, 2018. doi:10.2478/forma-2018-0011.Adrian Jaszczak. Partial correctness of a power algorithm. Formalized Mathematics, 27 (2):189–195, 2019. doi:10.2478/forma-2019-0018.Adrian Jaszczak and Artur Korniłowicz. Partial correctness of a factorial algorithm. Formalized Mathematics, 27(2):181–187, 2019. doi:10.2478/forma-2019-0017.Artur Korniłowicz. Partial correctness of a Fibonacci algorithm. Formalized Mathematics, 28(2):187–196, 2020. doi:10.2478/forma-2020-0016.Artur Korniłowicz, Andrii Kryvolap, Mykola Nikitchenko, and Ievgen Ivanov. Formalization of the algebra of nominative data in Mizar. In Maria Ganzha, Leszek A. Maciaszek, and Marcin Paprzycki, editors, Proceedings of the 2017 Federated Conference on Computer Science and Information Systems, FedCSIS 2017, Prague, Czech Republic, September 3–6, 2017., pages 237–244, 2017. ISBN 978-83-946253-7-5. doi:10.15439/2017F301.Artur Korniłowicz, Andrii Kryvolap, Mykola Nikitchenko, and Ievgen Ivanov. Formalization of the nominative algorithmic algebra in Mizar. In Leszek Borzemski, Jerzy Świątek, and Zofia Wilimowska, editors, Information Systems Architecture and Technology: Proceedings of 38th International Conference on Information Systems Architecture and Technology – ISAT 2017 – Part II, Szklarska Poręba, Poland, September 17–19, 2017, volume 656 of Advances in Intelligent Systems and Computing, pages 176–186. Springer, 2017. ISBN 978-3-319-67228-1. doi:10.1007/978-3-319-67229-8_16.Artur Korniłowicz, Andrii Kryvolap, Mykola Nikitchenko, and Ievgen Ivanov. An approach to formalization of an extension of Floyd-Hoare logic. In Vadim Ermolayev, Nick Bassiliades, Hans-Georg Fill, Vitaliy Yakovyna, Heinrich C. Mayr, Vyacheslav Kharchenko, Vladimir Peschanenko, Mariya Shyshkina, Mykola Nikitchenko, and Aleksander Spivakovsky, editors, Proceedings of the 13th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer, Kyiv, Ukraine, May 15–18, 2017, volume 1844 of CEUR Workshop Proceedings, pages 504–523. CEUR-WS.org, 2017.Artur Korniłowicz, Ievgen Ivanov, and Mykola Nikitchenko. Kleene algebra of partial predicates. Formalized Mathematics, 26(1):11–20, 2018. doi:10.2478/forma-2018-0002.Andrii Kryvolap, Mykola Nikitchenko, and Wolfgang Schreiner. Extending Floyd-Hoare logic for partial pre- and postconditions. In Vadim Ermolayev, Heinrich C. Mayr, Mykola Nikitchenko, Aleksander Spivakovsky, and Grygoriy Zholtkevych, editors, Information and Communication Technologies in Education, Research, and Industrial Applications: 9th International Conference, ICTERI 2013, Kherson, Ukraine, June 19–22, 2013, Revised Selected Papers, pages 355–378. Springer International Publishing, 2013. ISBN 978-3-319-03998-5. doi:10.1007/978-3-319-03998-5_18.Volodymyr G. Skobelev, Mykola Nikitchenko, and Ievgen Ivanov. On algebraic properties of nominative data and functions. In Vadim Ermolayev, Heinrich C. Mayr, Mykola Nikitchenko, Aleksander Spivakovsky, and Grygoriy Zholtkevych, editors, Information and Communication Technologies in Education, Research, and Industrial Applications – 10th International Conference, ICTERI 2014, Kherson, Ukraine, June 9–12, 2014, Revised Selected Papers, volume 469 of Communications in Computer and Information Science, pages 117–138. Springer, 2014. ISBN 978-3-319-13205-1. doi:10.1007/978-3-319-13206-8_6.28426927

Partial Correctness of a Fibonacci Algorithm

In this paper we introduce some notions to facilitate formulating and proving properties of iterative algorithms encoded in nominative data language [19] in the Mizar system [3], [1]. It is tested on verification of the partial correctness of an algorithm computing n-th Fibonacci number: i := 0 s := 0 b := 1 c := 0 while (i n)   c := s   s := b   b := c + s   i := i + 1 return s This paper continues verification of algorithms [10], [13], [12] written in terms of simple-named complex-valued nominative data [6], [8], [17], [11], [14], [15]. The validity of the algorithm is presented in terms of semantic Floyd-Hoare triples over such data [9]. Proofs of the correctness are based on an inference system for an extended Floyd-Hoare logic [2], [4] with partial pre- and post-conditions [16], [18], [7], [5].Institute of Informatics, University of Białystok, PolandGrzegorz Bancerek, Czesław Byliński, Adam Grabowski, Artur Korniłowicz, Roman Matuszewski, Adam Naumowicz, and Karol Pąk. The role of the Mizar Mathematical Library for interactive proof development in Mizar. Journal of Automated Reasoning, 61(1):9–32, 2018. doi:10.1007/s10817-017-9440-6.R.W. Floyd. Assigning meanings to programs. Mathematical aspects of computer science, 19(19–32), 1967.Adam Grabowski, Artur Korniłowicz, and Adam Naumowicz. Four decades of Mizar. Journal of Automated Reasoning, 55(3):191–198, 2015. doi:10.1007/s10817-015-9345-1.C.A.R. Hoare. An axiomatic basis for computer programming. Commun. ACM, 12(10): 576–580, 1969.Ievgen Ivanov and Mykola Nikitchenko. On the sequence rule for the Floyd-Hoare logic with partial pre- and post-conditions. In Proceedings of the 14th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer. Volume II: Workshops, Kyiv, Ukraine, May 14–17, 2018, volume 2104 of CEUR Workshop Proceedings, pages 716–724, 2018.Ievgen Ivanov, Mykola Nikitchenko, Andrii Kryvolap, and Artur Korniłowicz. Simple-named complex-valued nominative data – definition and basic operations. Formalized Mathematics, 25(3):205–216, 2017. doi:10.1515/forma-2017-0020.Ievgen Ivanov, Artur Korniłowicz, and Mykola Nikitchenko. Implementation of the composition-nominative approach to program formalization in Mizar. The Computer Science Journal of Moldova, 26(1):59–76, 2018.Ievgen Ivanov, Artur Korniłowicz, and Mykola Nikitchenko. On an algorithmic algebra over simple-named complex-valued nominative data. Formalized Mathematics, 26(2):149–158, 2018. doi:10.2478/forma-2018-0012.Ievgen Ivanov, Artur Korniłowicz, and Mykola Nikitchenko. An inference system of an extension of Floyd-Hoare logic for partial predicates. Formalized Mathematics, 26(2): 159–164, 2018. doi:10.2478/forma-2018-0013.Ievgen Ivanov, Artur Korniłowicz, and Mykola Nikitchenko. Partial correctness of GCD algorithm. Formalized Mathematics, 26(2):165–173, 2018. doi:10.2478/forma-2018-0014.Ievgen Ivanov, Artur Korniłowicz, and Mykola Nikitchenko. On algebras of algorithms and specifications over uninterpreted data. Formalized Mathematics, 26(2):141–147, 2018. doi:10.2478/forma-2018-0011.Adrian Jaszczak. Partial correctness of a power algorithm. Formalized Mathematics, 27 (2):189–195, 2019. doi:10.2478/forma-2019-0018.Adrian Jaszczak and Artur Korniłowicz. Partial correctness of a factorial algorithm. Formalized Mathematics, 27(2):181–187, 2019. doi:10.2478/forma-2019-0017.Artur Kornilowicz, Andrii Kryvolap, Mykola Nikitchenko, and Ievgen Ivanov. Formalization of the algebra of nominative data in Mizar. In Maria Ganzha, Leszek A. Maciaszek, and Marcin Paprzycki, editors, Proceedings of the 2017 Federated Conference on Computer Science and Information Systems, FedCSIS 2017, Prague, Czech Republic, September 3–6, 2017., pages 237–244, 2017. ISBN 978-83-946253-7-5. doi:10.15439/2017F301.Artur Kornilowicz, Andrii Kryvolap, Mykola Nikitchenko, and Ievgen Ivanov. Formalization of the nominative algorithmic algebra in Mizar. In Leszek Borzemski, Jerzy Świątek, and Zofia Wilimowska, editors, Information Systems Architecture and Technology: Proceedings of 38th International Conference on Information Systems Architecture and Technology – ISAT 2017 – Part II, Szklarska Poręba, Poland, September 17–19, 2017, volume 656 of Advances in Intelligent Systems and Computing, pages 176–186. Springer, 2017. ISBN 978-3-319-67228-1. doi:10.1007/978-3-319-67229-8_16.Artur Korniłowicz, Andrii Kryvolap, Mykola Nikitchenko, and Ievgen Ivanov. An approach to formalization of an extension of Floyd-Hoare logic. In Vadim Ermolayev, Nick Bassiliades, Hans-Georg Fill, Vitaliy Yakovyna, Heinrich C. Mayr, Vyacheslav Kharchenko, Vladimir Peschanenko, Mariya Shyshkina, Mykola Nikitchenko, and Aleksander Spivakovsky, editors, Proceedings of the 13th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer, Kyiv, Ukraine, May 15–18, 2017, volume 1844 of CEUR Workshop Proceedings, pages 504–523. CEUR-WS.org, 2017.Artur Korniłowicz, Ievgen Ivanov, and Mykola Nikitchenko. Kleene algebra of partial predicates. Formalized Mathematics, 26(1):11–20, 2018. doi:10.2478/forma-2018-0002.Andrii Kryvolap, Mykola Nikitchenko, and Wolfgang Schreiner. Extending Floyd-Hoare logic for partial pre- and postconditions. In Vadim Ermolayev, Heinrich C. Mayr, Mykola Nikitchenko, Aleksander Spivakovsky, and Grygoriy Zholtkevych, editors, Information and Communication Technologies in Education, Research, and Industrial Applications: 9th International Conference, ICTERI 2013, Kherson, Ukraine, June 19–22, 2013, Revised Selected Papers, pages 355–378. Springer International Publishing, 2013. ISBN 978-3-319-03998-5. doi:10.1007/978-3-319-03998-5_18.Volodymyr G. Skobelev, Mykola Nikitchenko, and Ievgen Ivanov. On algebraic properties of nominative data and functions. In Vadim Ermolayev, Heinrich C. Mayr, Mykola Nikitchenko, Aleksander Spivakovsky, and Grygoriy Zholtkevych, editors, Information and Communication Technologies in Education, Research, and Industrial Applications – 10th International Conference, ICTERI 2014, Kherson, Ukraine, June 9–12, 2014, Revised Selected Papers, volume 469 of Communications in Computer and Information Science, pages 117–138. Springer, 2014. ISBN 978-3-319-13205-1. doi:10.1007/978-3-319-13206-8_6.28218719