This course is part of the programme:
Bachelor's programme in Engineering and Management (First Level)
Objectives and competences
The main objective of the course is present the basic web technology concepts that are required for developing web applications. The key technology components are descriptive languages, server-side program elements and client-side program elements.
Fluent in English or Slovene language, basic knowledge in computer and information science
Content (Syllabus outline)
- The goal and purpose of the course
- Course materials and method of work
- Required and additional literature
- Study guide
2. Basic definitions
- Internet and web
- Communication systems and networks
- Computer networking principles
- Client-server architecture
- Web pages and web applications
3. Web technologies
- Internet environment
- Web servers
- Web browsers
- DOM document object model
- Internet protocols HTTP and HTTPS
- Web services
- Sessions and cookies
4. Languages for web techologies
- HTML and XML
- JSON data format
5. Advanced web technologies
- Web databases
- MVC (Model-View-Controller) architecture
- CMS systems (Content Management Systems)
6. Web page design
- Principles of web page design
- Web page design tools
- Internet security
Intended learning outcomes
Kumar, A., Web technologies, CRC press, 2019
Gupta, R., Internet & Web Technologies, Engineering Handbook, 2019
Kohli , S., Web Technologies, PPB Publications, 2015
Seminar with oral presentation and discussion, Written exam 40/60
Prof. Suzana Loshkovska, Ph.D. received the bachelor and master degrees in computer science and automation from the Faculty of Electrical Engineering, Skopje, in 1988 and 1992, respectively, and the Ph.D. from the Technical University of Wien, Wien, Austria in 1995. She is a full professor of Computer Science and the head of the Department of Software Engineering at the Faculty of Computer Science Engineering, “Ss. Cyril and Methodius” University in Skopje. Her research interests include programming, visualization, human-computer interaction, virtual reality, medical imaging, and technologically enhanced learning. Suzana Loshkovska has over 25 years of experience in teaching, supervising and guidance of undergraduate and graduate students in the fields of programming, medical informatics, content-based image retrieval, visualization and human-computer interaction. Also, she has over 10 years of experience in developing and ensuring quality assurance of study programs for higher education institutions. She entered the Open Education for a Better World program as a mentor from the very beginning, and acts as a mentor in international teams.
 Ademi, N. and Loshkovska, S., (2020) Clustering Learners in a Learning Management System to Provide Adaptivity, ICT Innovations 2020, web-proceedings (https://proceedings.ictinnovations.org/2020/paper/529/clustering-learners-in-a-learning-management-system-to-provide-adaptivity), pp. 82-95
 Ademi, N., Loshkovska, S., (2020) Weekly Analysis of Moodle Log Data in RStudio for Future Use in Prediction, 17th International Conference on Informatics and Information Technologies – CIIT 2020, 8-May-2020, Mavrovo, North Macedonia.
 Ademi, N., Loshkovska, S., Chorbev, I., (2019) Reinforcing motivation and engagement by behavioral design in learning systems, International Open & Distance Learning Conference, IODL 2019, 14-16 November 2019, Eskisehir, Turkey, p. 237-244.
 Ademi N., Loshkovska S., Kalajdziski S. (2019) Prediction of Student Success Through Analysis of Moodle Logs: Case Study. In: Gievska S., Madjarov G. (eds) ICT Innovations 2019. Big Data Processing and Mining. ICT Innovations 2019. Communications in Computer and Information Science, vol 1110. Springer, Cham
 Trojacanec, Katarina, Ivan Kitanovski, Ivica Dimitrovski, and Suzana Loshkovska (2017). “Longitudinal Brain MRI Retrieval for Alzheimer’s Disease Using Different Temporal Information.” IEEE Access. VOLUME 6, 2018, pp. 9703-9712, DOI: 10.1109/ACCESS.2017.2773359 (IF: 3.244)
 Trojacanec, Katarina, Slobodan Kalajdziski, Ivan Kitanovski, Ivica Dimitrovski, Suzana Loshkovska, and Alzheimer’s Disease Neuroimaging Initiative (2017). “Image Retrieval for Alzheimer’s Disease Based on Brain Atrophy Pattern.” In International Conference on ICT Innovations, pp. 165-175. Springer, Cham, 2017.
 Dimitrovski, I., Kocev, D ., Loskovska, S., Dzeroski S., (2016) Improving bag-of-visual-words image retrieval with predictive clustering trees. Inf. Sci. 329: 851-865
 Kitanovski, I., Strezoski, Gj., Dimitrovski, I., Madjarov Gj., Loskovska, S. (2016), “Multimodal medical image retrieval system.” Multimedia Tools and Applications: 1-24 (IF: 1.36)
 Dimitrovski, I., Kocev, D., Kitanovski I., Loskovska. S., Džeroski, S. “Improved medical image modality classification using a combination of visual and textual features.” Computerized Medical Imaging and Graphics 39 (2015): 14-26. (IF:1.21)
 Trojacanec, K., Kitanovski, I., Dimitrovski, I., & Loshkovska, S. (2016). Medical Image Retrieval for Alzheimer’s Disease Using Data from Multiple Time Points. In ICT Innovations 2015 (pp. 215-224). Springer International Publishing.
 Trojacanec, K., Kitanovski, I., Dimitrovski, I., Loshkovska, S., & Alzheimer’s Disease Neuroimaging Initiative. (2015). Medical Image Retrieval for Alzheimer’s Disease Using Structural MRI Measures. In Biomedical Engineering Systems and Technologies (pp. 126-141). Springer International Publishing.
 Trojacanec K., Kitanovski I., Dimitrovski I. & Loshkovska S. (2015). Content Based Retrieval of MRI Based on Brain Structure Changes in Alzheimer’s Disease. In Proceedings of the International Conference on Bioimaging (BIOSTEC 2015), ISBN 978-989-758-072-7, pages 13-22. DOI: 10.5220/0005182200130022.
 Dimitrovski, I., Kocev, D., Loskovska, S., Dzˇeroski, S. (2014) “Fast and efficient visual codebook construction for multi-label annotation using predictive clustering trees”, Pattern Recognition Letters 38, 38–45 (IF:1.062)
 Trojacanec, K., Kitanovski, I., Dimitrovski, I., & Loshkovska, S. (2015). New Representation of Information Extracted from MRI Volumes Applied to Alzheimer’s Disease. In ICT Innovations 2014 (pp. 249-258). Springer International Publishing.
 Trojacanec, Katarina, Ivan Kitanovski, Ivica Dimitrovski, and Suzana Loshkovska. (2014) “3D Content Based Medical Image Retrieval: Basic Concepts and Challenges”. In Proceedings of the 11th International Conference for Informatics and Information Technology, Bitola (Macedonia).
 Kitanovski, Ivan, Ivica Dimitrovski, Gjorgji Madjarov, and Suzana Loskovska. (2014) “Medical Image Retrieval Using Multimodal Data.” In Discovery Science, pp. 144-155. Springer International Publishing
 Trojacanec, Katarina, Ivan Kitanovski, Ivica Dimitrovski, and Suzana Loshkovska (2014). “Content Based Image Retrieval in the Context of Alzheimer’s Disease”. In Proceedings of the 9th Annual South East European Doctoral Student Conference, DSC 2014, Thessaloniki (Greece).
Project title: Applying Semantic Technologies for dynamic adaptivity of health information systems in Montenegro and Macedonia
Financed by: Ministry of Education (bilateral project)
Role in the project (PI or participant): PI
Project title: MAESTRA: Learning from Massive, Incompletely Annotated, and Structured Data
Financed by: FP7 Project
Role in the project (PI or participant): participant
Project title: Future education and training in computing: how to support learning at anytime anywhere (FETCH)
Financed by: FP7 Project
Role in the project (PI or participant): PI
Project title: Tools and techniques for improvement and support of learning introductory programming
Financed by: FINKI, UKIM
Role in the project (PI or participant):participant
User Interface Design Patterns
Client Side Internet programming
Human Computer Interaction
Design of User-Computer Interaction
Software Design Patterns
Software Testing and Usability
Software Quality Management
Technologies for Open Education
University course code: 1GI030
Year of study: 2
- Lectures: 30 hours
- Exercises: 18 hours
- Seminar: 12 hours
- Individual work: 65 hours
Course type: mandatory
Learning and teaching methods:
the subject content will be divided into logical units. lectures with be given with active students' involvement (explanation, discussion, questions and answers, case studies). individual and group research will be carried out by the seminar assignments.