Visual Communication Technologies and Their Applications in Education

The aim of this course is to empower students how to effectively use visual communication in learning process. Based on an understanding of concepts and through practical exercises, they will develop skills that will help them to improve their creativity and efficiency as lecturers.

Students will gain the following competencies:

• understanding the concepts of visual communication and its advantages and disadvantages in the educational environment,

• the ability to use visual communication technologies in designing effective ways to achieve learning objectives.

Students should have basic knowledge of open education concepts and instructional design as presented in the first semester first year cours-es Basics of Open Education and Open Educa-tion Design. They should be able to use computer-supported tools for content generation and design, as well as communication and collaboration tools. Additionally, they should be prepared to work in interdisciplinary teams.

This course introduces basic principles of using visual communication. By completing numerous short exercises students will develop skills for efficient use of visual communication in educa-tion.

This course explores the following topics in more detail:

• The Physiology and Psychology of Vision
• Graphics Design And Layout
• Analogy-Metaphor-Symbolism-Iconography
• Semiotics
• Visual Technology and Tools
• Using Open Source Digital Media, Free-ware, and Shareware to Enhance Learning
• Using Visual Communication to Engage, Collaborate, and Demonstrate
• Storyboarding: Tell Your Tale
• Photography Editing Tools and Instructional Design Strategy
• Video Editing Tools and Instructional Design Strategy
• Visual Communication in the Age of Social Media, Virtual Reality
• Visualization Techniques

After completing this course, students will:

• Understand the concepts and theories of visual persuasion, photography, graphic design, cultural and ethical issues, visualization of ideas;

• Be able to distinguish between different visual media and to select appropriate visual media to deliver content to the students;

• Be able to select and use different tools for visual communication;

• Produce simple visual education material using appropriate technologies.

• Smith, K., Moriarty, S., Barbatsis, G., Kenne, K. (2005) Handbook of Visual Communication: Theory, Methods, and Media (Routledge Communication Series). Lawrence Erlbaum Associates, Inc. E-version
• Golombisky, K., Hagen, R. (2016). White Space Is Not Your Enemy: A Beginner's Guide to Com-municating Visually Through Graphic, Web and Multimedia Design (3rd ed.). Boca Raton: Taylor & Francis. E-version
• Osgood, R., & Hinshaw, M. (2014). Visual storytelling: Videography and post production in the digital age (2nd ed.). Boston, MA: Wadsworth Cengage Learning.

• Interim presentations • Final written exam

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.

Selected bibliography:

1. Dimitrovski, Ivica & Spasev, Vlatko & Loskovska, Suzana & Kitanovski, Ivan. (2024). U-Net Ensemble for Enhanced Semantic Segmentation in Remote Sensing Imagery. Remote Sensing. 16. 2077. 10.3390/rs16122077.
2. Trojachanec, D., Kitanovski, D., Dimitrovski, I., Loshkovska, S., (2023). A Multi-Modality Approach to Medical Case Retrieval for Alzheimer's Disease. In 16th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, Proceedings. ISBN 978-989-758-631-6, ISSN 2184-4305, (pp. 554-561). DOI: 10.5220/0011939800003414.
3. Dineva, K.T., Kitanovski, I., Dimitrovski, I., Loshkovska, S. and Alzheimer’s Disease Neuroimaging Initiative (2022). Combining Static and Dynamic Features to Improve Longitudinal Image Retrieval for Alzheimer’s Disease. In ICT Innovations 2022. Reshaping the Future Towards a New Normal: 14th International Conference, ICT Innovations 2022, Skopje, Macedonia, September 29–October 1, 2022, Proceedings (pp. 107-120). Cham: Springer Nature Switzerland.
4. Loshkovska, S. (2022) Virtual and Augmented Reality in Education, International Conference on New Approaches (ICNAE’22)/2022, pp. 86-90
5. Trojachanec, D., Kitanovski, D., Dimitrovski, I., Loshkovska, S., (2022). Missing Data in Longitudinal Image Retrieval for Alzheimer’s Disease. In 19th International Conference for Informatics and Information Technology, Proceedings (pp.69-74). 2022.
6. 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
7. 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.
8. Ademi, N., Loshkovska, S., Chorbev, I., (2020) User Modeling Approaches in Adaptive Learning Systems, International Journal of Technical and Natural Sciences, Skopje, North Macedonia, 2020, Vol.1(2), [Available at: http://ijtns.ibu.edu.mk/wp-content/uploads/2021/01/IBU-IJTNS_Vol-1_Issue-2.pdf]
9. Ademi N., Loshkovska S. (2019) Exploratory Analysis of Student Activities and Success Based on Moodle Log Data, CiiT - 16th International Conference on Informatics and Information Technologies, Mavrovo, Macedonia, May 10-12, 2019.
10. 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
11. Ademi, N., Loshkovska, S. (2019). Early Detection of Dropouts in E-Learning Systems. Academic Perspective Procedia, 2 (3), 1008-1015. DOI: 10.33793/acperpro.02.03.112
12. Ademi, N., Loshkovska, S., (2019) User Data In Adaptive Learning Systems, Turkish Studies Information Technologies and Applied Sciences, Volume 14 Issue 4, 2019, p. 507-518.
13. 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.