Veidlapa Nr. M-3 (8)
Study Course Description
Information Technologies
Course Code
LU_011
Target Audience
Information and Communication Science
ECTS
3.00
Study Type And Form
Full-Time
LQF
All Levels
RSU Unit
Course Supervisor
Lolita Vija Neimane
Structural Unit
Faculty of Health and Sport Sciences
Structure Unit Manager
Inga Millere
Study Course Implementer
Partner Organisation
Latvijas Universitāte
Partner Course Implementer
Māris Vītiņš
Partnership Liaison Person
Ida Jākobsone
About Study Course
Objective
-
Preliminary Knowledge
-
Learning Outcomes
Knowledge
1.1. Knows about digital tools for data collection and processing useful for professional activities and studies and the possibilities of their use. 2. Understands about the possibilities of using digital tools in professional communication and cooperation.
Skills
1.1. Collects information useful for professional activity and studies in electronic databases. 2. Uses digital tools in the development of documents (practice reports or final theses); for the preparation of presentations and their presentation necessary for professional activities and studies. 3. Performs statistical processing of data and graphical representation of the obtained results.
Competences
1.Chooses suitable digital tools and use them for professional activities and study tasks.
Assessment
Individual work
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Title
|
% from total grade
|
Grade
|
|---|---|---|
|
1.
Individual work |
-
|
-
|
|
Students' independent work is organized individually and / or in work groups, and it includes independent preparation for practical classes, intermediate and final examinations, performing the following tasks:
1. Working with databases, creating of annotations collection.
2. Development and presentation of an academic presentation.
3. Designing of practice report or final work.
4. Statistical data processing and relationship visualization. 5. Working with numerical data, use of data processing functions, their statistical processing and graphical representation
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||
Examination
|
Title
|
% from total grade
|
Grade
|
|---|---|---|
|
1.
Examination |
-
|
-
|
|
The final grade of the study course consists of interim assessment (independent assignments) and final examination grades. Students hand in their independent assignments by due dates mentioned in the syllabus of the study course. Students are permitted to take an exam only if all the interim assessment assignments are completed.
Interim assessment:
1. Work with databases, creating of annotations collection - 10%.
2. Development and presentation of an academic presentation - 10%.
3. Design of practice report or final work - 30%.
4. Statistical data processing and relationship visualization - 20%
Final assessment:
Examination - presentation of a task related to professional activity or studies, chosen by the student, which confirms the knowledge, skills and competencies acquired in the course - 30%.
Students have to do the practical work, independent work and pass an examination. In case of missed lecture students must do the practical works by themselves and their performance will be discussed with the lecturers during the consultation.
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Study Course Theme Plan
FULL-TIME
Part 1
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Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Other
|
2
|
Topics
|
IT competence and professional activity.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Other
|
2
|
Topics
|
Working with databases to collect useful information
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Other
|
2
|
Topics
|
Working with databases to collect useful information
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Other
|
2
|
Topics
|
Use of digital tools for preparation of final theses.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Other
|
2
|
Topics
|
Use of digital tools for preparation of final theses.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Other
|
2
|
Topics
|
Use of digital tools for preparation and presentation of presentations.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Other
|
2
|
Topics
|
Use of digital tools for preparation and presentation of presentations.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Other
|
2
|
Topics
|
Work with hardware and software useful for professional activities and studies.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Other
|
2
|
Topics
|
Work with hardware and software useful for professional activities and studies.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Other
|
2
|
Topics
|
Work with hardware and software useful for professional activities and studies.
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Other
|
2
|
Topics
|
Experimental measurement errors and their calculations.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Other
|
2
|
Topics
|
Experimental measurement errors and their calculations.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Other
|
2
|
Topics
|
Experimental measurement errors and their calculations.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Other
|
2
|
Topics
|
Processing of empirical research data and their visualization.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Other
|
2
|
Topics
|
Processing of empirical research data and their visualization.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Other
|
2
|
Topics
|
Processing of empirical research data and their visualization.
|
Total ECTS (Creditpoints):
3.00
Contact hours:
32 Academic Hours
Final Examination:
Exam
Bibliography
Required Reading
1.
Information design : research and practice / edited by Black. London; New York : Routledge, Taylor & Francis Group, 2017. xvi, 750 lpp
2.
Karnītis, E. Informācijas sabiedrība – Latvijas iespējas un uzdrošināšanās. Rīga : Pētergailis, 208 lpp.
3.
Logins, J. Informācijas tehnoloģija. E-studiju kurss LU Moodle vidē. Nodarbību materiāli. 2021.
Additional Reading
1.
Data science & big data analytics : discovering, analyzing, visualizing and presenting data / EMC Education Services. Indianapolis, IN : John Wiley and Sons, 2014. xviii, 410 lpp.
2.
Dorner, D. G. Information needs analysis: principles and practice in information organizations. London : Facet Publishing, 2015. xvii, 269 lpp.
3.
Pierson, L. Data science for dummies / by Lillian Pierson ; foreword by Jake Porway, Founder and Executive Director of DataKind. Hoboken, New Jersey : For Dummies, a Wiley Brand, [2015]. xvi, 384 lpp.
4.
Trochim, W. M. Research methods : the essential knowledge base. [2nd edition]. Boston, MA : Cengage Learning, ©2016. xxii, 422 lpp. Tiešsaistes resurss.
5.
Ware, C. Information visualization: perception for design / Colin Ware. Fourth edition. Philadelphia : Elsevier, Inc, 2020. xviii, 538 lpp.
Other Information Sources
1.
E-learning and Education (eleed) Journal. Pieejams tiešsaistē: http://eleed.campussource.de/
2.
The Electronic Journal of e-Learning. Pieejams tiešsaistē: http://www.ejel.org/main.html
3.
Top Tools for Learning. Pieejams tiešsaistē: https://www.toptools4learning.com/home/