SubjectsSubjects(version: 945)
Course, academic year 2023/2024
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Fundamentals of Informatics and Methodology of Scientific Research - PKIN011C
Title: Fundamentals of Informatics and Methodology of Scientific Research
Guaranteed by: Department of Social Sciences Foundation in Kinanthropology (51-300000)
Faculty: Faculty of Physical Education and Sport
Actual: from 2023
Semester: summer
Points: 0
E-Credits: 1
Examination process: summer s.:
Hours per week, examination: summer s.:0/2, C [HT]
Extent per academic year: 28 [hours]
Capacity: unknown / 24 (24)
Min. number of students: unlimited
4EU+: no
Virtual mobility / capacity: no
Key competences:  
State of the course: taught
Language: English
Teaching methods: full-time
Teaching methods: full-time
Level:  
Note: course can be enrolled in outside the study plan
enabled for web enrollment
priority enrollment if the course is part of the study plan
Guarantor: PhDr. Šárka Vokounová, Ph.D.
Teacher(s): prof. Dr. Ing. Tomáš Navrátil, Ph.D.
PhDr. Šárka Vokounová, Ph.D.
Interchangeability : PLSM038C
In complex incompatibility with: PFYZ219C
Annotation -
Last update: PhDr. Šárka Vokounová, Ph.D. (09.09.2023)
The content of the subject is the current trends of work in the environment of information and communication technologies in the field. Methods of searching and obtaining professional information, their processing, presentation and the possibilities of their publication, sharing and transmission. Basic methods of electronic data collection and their processing. Information and communication systems of Charles University. Artificial Intelligence.
Aim of the course -
Last update: PhDr. Šárka Vokounová, Ph.D. (09.09.2023)

The aim of the subject is to familiarize students with current information systems at the University of Warsaw and trends in work in the field of information and communication technologies. Students will acquire practical skills to search for and obtain professional information, process it, present it, and will navigate the possibilities of its publication, sharing and transmission. Students will be introduced to some artificial intelligence tools.

After completing the course, the student will be competent to:

  • Find your way around UK information systems, connect to Eduroam, use your M365 account.
  • Find your way around UK information sources, search in the UKAŽ search engine, be able to search for an article in licensed scientific databases.
  • Find your way around UK e-learning tools. Be able to use LMS Moodle, be able to search for videos on stream servers, be able to use Zoom, or other current tools.
  • Back up your data effectively, use clouds, orient yourself in the tools offered by Cesnet.
  • Be able to master MS Word so that the skills are sufficient for processing a bachelor's thesis. Be able to create content, format text, divide a document into sections, number pages.
  • Be able to create a correct bibliographic citation according to the selected standard. Be able to cite sources in the text, be able to create a list of used literature.
  • Orientation in publication and citation ethics. Know the functionality of Turnitin. Orientate yourself in artificial intelligence tools.
  • Process data in MS Excel, create descriptive statistics. Present the results of your work in MS Powerpoint.
  • Orient yourself to the meaning and functionality of the data box and electronic signature.
Course completion requirements
Last update: PhDr. Šárka Vokounová, Ph.D. (09.09.2023)

Participation on seminaries (cca 80%), conclusion test

Literature -
Last update: PhDr. Šárka Vokounová, Ph.D. (09.09.2023)

Literature:

GEMERT-PIJNEN, Lisette van, Saskia M. KELDERS, Kip HANNEKE a Robbert SANDERMAN. EHealth research, theory and development: a multi-disciplinary approach. Oxford: Routledge, 2018. ISBN 978-1-138-23043-9.
SCHMULLER, Joseph. Statistical analysis with Excel for dummies. 3rd ed. Hoboken, NJ: Wiley, 2013. ISBN 978-1-118-46431-1.
WILLIAMS, Anthony S. Big data: Data analytics for beginners / Analyzing data with Power BI / Deep learning with Keras / Convolutional neural networks in Python. North Charleston, SC: CreateSpace, 2017. ISBN 9781974435562.


Syllabus -
Last update: PhDr. Šárka Vokounová, Ph.D. (09.09.2023)

Exercises:

1. Introduction to information science, information systems at UK, Eduroam

2. Electronic information sources, multidisciplinary databases

3. Application for e-learning, Moodle in the UK environment

4. Operating systems, anti-virus software, data sharing and transfer options, data protection

5. Text editors

6. Creation of the Bible citations according to ISO 690

7. Publication and citation ethics

8. Spreadsheet processors

9. Basics of scientific work

10. Basics of statistical data analysis

11. Presentation software and hardware, interactive whiteboards

12. Artificial intelligence

13. Google tools

14. Data box, electronic signature

Learning resources
Last update: PhDr. Pavlína Vostatková, Ph.D. (15.02.2021)

Study materials will be distributed through Adobe Connect, Moodle and email.

Link on courses (MS TEAMS):

https://teams.microsoft.com/l/message/19:adb6d54ddfe7422eaa0abbdb2c39c988@thread.tacv2/1613315132387?tenantId=e09276da-f934-4086-bf08-8816a20414a2&groupId=5211a030-69b4-470f-ac94-2a3315291f73&parentMessageId=1613315132387&teamName=PKIN011C-2020%2F21&channelName=General&createdTime=1613315132387

 
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