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Digital Literacy
Study Course Description
Course Description Statuss:Approved
Course Description Version:2.00
Study Course Accepted:20.05.2024 08:40:36
Study Course Information | |||||||||
Course Code: | VVDG_042 | LQF level: | All Levels | ||||||
Credit Points: | 2.00 | ECTS: | 3.00 | ||||||
Branch of Science: | Management; Business Management | Target Audience: | Communication Science; Public Health; Nursing Science; Management Science; Health Management; Political Science; Pharmacy; Information and Communication Science; Medical Technologies; Rehabilitation; Dentistry; Business Management; Medicine | ||||||
Study Course Supervisor | |||||||||
Course Supervisor: | Didzis Lauva | ||||||||
Study Course Implementer | |||||||||
Structural Unit: | Faculty of Social Sciences | ||||||||
The Head of Structural Unit: | |||||||||
Contacts: | Dzirciema street 16, Rīga, szfrsu[pnkts]lv | ||||||||
Study Course Planning | |||||||||
Full-Time - Semester No.1 | |||||||||
Lectures (count) | 0 | Lecture Length (academic hours) | 0 | Total Contact Hours of Lectures | 0 | ||||
Classes (count) | 0 | Class Length (academic hours) | 0 | Total Contact Hours of Classes | 0 | ||||
Total Contact Hours | 0 | ||||||||
Study course description | |||||||||
Preliminary Knowledge: | Not required. | ||||||||
Objective: | The purpose of the digital literacy course is to provide students with knowledge, skills and competences in the use of digital technologies. | ||||||||
Assessment | |||||||||
Unaided Work: | Learning of the "Digital Literacy" course takes place independently using the e-study activities "Lesson". Tasks are implemented in each lesson. These tasks include tasks dealing with digital information and data, analysis of graphs and charts, cyber security questions and other practice-oriented tasks. In order to evaluate the quality of the study course as a whole, the student must fill out the study course evaluation questionnaire on the Student Portal. | ||||||||
Assessment Criteria: | The evaluation of the "Digital Literacy" course is based on the participants' participation and performance in the activities published in e-studies. Each activity is evaluated with a certain number of points. | ||||||||
Final Examination (Full-Time): | Exam (Written) | ||||||||
Final Examination (Part-Time): | |||||||||
Learning Outcomes | |||||||||
Knowledge: | Participants of the "Digital Literacy" course will gain knowledge about the fundamentals of digital literacy and the history of its development. They will familiarize themselves with digital paradigms and their change, understand the nature and functionality of various digital platforms (latvija.lv, eveseliba.lv, datamed.lv), and also analyze the importance of digital infrastructure and resources. In addition, participants will learn information acquisition and research methods in the context of digital literacy, delving into data classification and pre-processing. The course will also include the understanding of the basic principles of Big Data and the skills to use Excel in data preparation, providing a full-fledged analysis of the prepared data. Finally, participants will gain knowledge about cyber security issues and how to effectively protect digital information. | ||||||||
Skills: | Upon completion of this course, participants will develop specific skills required for digital literacy. They will be able to successfully use different digital platforms and resources, for example, they will acquire skills in data research, information acquisition and analysis. Participants will develop skills in data classification and data preprocessing using Excel and other toolsets. They will also learn skills in working with various graphs and charts, as well as their correct interpretation and presentation. The course will also develop skills in big data processing. | ||||||||
Competencies: | By completing the "Digital Literacy" course, participants will develop broad competencies that are essential in the digital environment. They will acquire the skills to successfully manage digital information and data, being able to classify, organize and ensure high data quality prior to research analysis. In the area of big data analysis, participants will learn the skills to use tools such as Excel and identify trends characteristic of big data. Participants will also develop the ability to create and interpret various graphs and charts, effectively visualizing data and ensuring its proper presentation. Competence in the field of cyber security is also promoted during the course, providing participants with the skills to identify potential risks and take measures to mitigate them in the digital environment. In this context, participants will learn the ability to solve practical problems by applying the acquired knowledge and skills, and create creative solutions to challenges in the digital environment. Communication skills and collaboration abilities in the digital environment are developed, allowing participants to interact effectively, especially when working with data and information. Together, these competencies will form a strong foundation for participants' digital literacy and prepare them to function successfully in the digital environment. | ||||||||
Bibliography | |||||||||
No. | Reference | ||||||||
Required Reading | |||||||||
1 | A Guide to Microsoft Excel 2013 for Scientists and Engineers. by Bernard Liengme. Elsevier Science & Technology, 2015. | ||||||||
2 | Author(s): Janice Richardson, Dr. Elizabeth Milovidov, J.D., Martin Schmalzried. Internet literacy handbook. 2017 | ||||||||
3 | The Cyber Safety Handbook | ||||||||
Additional Reading | |||||||||
1 | The Data Journalism Handbook | ||||||||
2 | Excel Fundamentals - Manual | ||||||||
Other Information Sources | |||||||||
1 | Fundamentals of Data Visualization |