Fundamentals of Food Science II

Total Hours in Course81

Number of hours for lectures10

Number of hours for seminars and practical classes22

Independent study hours49

Date of course confirmation19.02.2014

Responsible UnitInstitute of Food

Course developer

Pārtikas institūts

Mārtiņš Šabovics

Dr. sc. ing.

Prior knowledge

PārZ1011, Fundamentals of Food Science I

Course abstract

The aim of the study course is to help students acquire the fundamentals of conducting research – from gathering and analysing information to visual and content formatting and presentation. During the course, students will gain practical experience in using various applications (MS Word, MS Excel, PREZI, Mentimeter, etc.) as well as working with scientific sources and large documents (such as research papers, scientific articles, and databases). Additionally, students will acquire basic knowledge of mathematical and statistical data processing in food science and production, as well as the effective use of presentation tools.

Learning outcomes and their assessment

Knowledge:
Students will acquire theoretical and practical knowledge in conducting research projects, organizing, formatting, and presenting information, with a particular focus on food production, quality management, and innovation.
Assessment: Test, analysis of theoretical tasks, discussions on research project development.
Skills:
Students will be able to develop and format research projects according to academic requirements, organize data, accurately represent, interpret, and present results using various methods and applications.
Assessment: Practical tasks involving software applications (MS Word, Excel, PREZI, etc.), data processing, and presentation tasks.
Competence:
Students will be able to select and apply the most appropriate data visualization and formatting techniques, use mathematical, statistical, and graphical analysis methods, and integrate them into academic and research work.
Assessment: Individual research work, data analysis and presentation tasks, final presentation.

Course Content(Calendar)

1. Lecture: Course Structure, Competencies, and Assessment Criteria – Fundamentals of research paper development, guidelines for structuring chapters, and content requirements. Formatting academic research papers according to the methodological guidelines of LBTU, LPTF, and PI (2 hours). Independent Work: Development of a course paper following the methodological guidelines (30 hours).
2. Lecture: Using Microsoft Word for Research Paper Formatting – Features and functions for technical formatting, managing large documents, structuring textual content, paragraph indents, spacing, numbering, bullet points, alignment, creating and applying document styles, and generating an automatic table of contents (2 hours). Practical Work: Preparing a title page and creating various forms/applications (2 hours).
3. Lecture: Creating and Using Electronic Links – Applying bookmarks, citation management, creating an index, sorting data in columns, tables, and flowcharts, organizing information using tab stops, applying the "Caption" heading style, and generating an automatic list of tables and figures (2 hours).
4. Lecture: Database Creation and Formatting, Calculations in MS Excel – Mathematical functions and their applications, sorting and filtering data, pivot tables, graphical data representation, statistical methods in food science, and statistical processing of research and study data (2 hours). Practical Work: Creating a multi-level list and tables in MS Word (2 hours). Independent Work: Application of tabulation markers (3 hours).
5. Lecture: Fundamentals and Requirements for Preparing a Presentation – Data presentation tools, PowerPoint and online presentation tools, infographic creation (1 hours). Artificial intelligence tools as an aid to study (1 hours).
6. Practical Work: Creating flowcharts (1 hour). First Assessment: Technical document formatting, managing large documents, and organizing information (1 hour).
7. Practical Work: Percentage calculations, using the IF function (2 hours).
8. Practical Work: Using complex functions (2 hours).
9. Practical Work: Creating intermediate results in databases (2 hours).
10. Practical Work: Creating tables and charts (2 hours). Independent Work: Entering data in tables and creating charts (6 hours).
11. Practical Work: Statistical data processing (2 hours).
12. Practical Work: Statistical data processing (1 hour). Second Assessment: Data processing, calculations, statistics, and graphical representation (1 hour).
13. Practical Work: Presentation creation and tool application (2 hours).
14. Practical Work: Application of various artificial intelligence tools to support study-related processes (2 hours). Independent Work: Creating a course paper presentation (10 hours).

Part-Time Distance Learning: All topics listed for full-time studies are covered; however, the number of contact hours is reduced to half of the specified hours.

Requirements for awarding credit points

The study course requires the completion of 11 practical works and two written tests. Additionally, a course paper must be developed and defended through a presentation. The course concludes with a pass/fail assessment (credit). The final evaluation consists of: Practical and independent work (70% of the total grade). Tests (30% of the total grade). To pass the course, students must achieve at least 60% of the total score from all assessed tasks.

Description of the organization and tasks of students’ independent work

During the semester, students are required to develop a course paper following the methodological guidelines. Additionally, they must create a presentation for the independent paper and deliver it. Independent work must be completed throughout the semester and submitted by the end of the semester. Students will also take two written assessments (tests) during the semester.

Criteria for Evaluating Learning Outcomes

The independent work evaluation consists of: Written paper quality assessment (based on methodological guidelines and compliance with all requirements) and presentation development – 70% of the final grade. Tests, including all practical assignments (which serve as preparatory material for the tests) – 30% of the final grade.

Compulsory reading

1. Noformēšanas vadlīnijas. Pārtikas tehnoloģijas fakultātes studentu referātu, prakses atskaišu, kursa projektu/darbu, diplomprojektu, bakalaura un maģistra darbu izstrādei, Jelgava, 2020. (https://www.lptf.lbtu.lv/sites/lptf/files/2025-02/ noformesanas%20noteikumi_2025.pdf)
2. Metodiskie norādījumi. Akadēmiskās studiju programmas «Pārtikas kvalitāte un inovācijas» studentiem bakalaura darba izstrādei. Jelgava, 2025 (https://www.lptf.lbtu.lv/sites/lptf/files/2025-02/metodiskie_bakalauram%20_2025.pdf).
3. Klieders J., Datorzinības. Microsoft Office 2013/2016: mācību līdzeklis., Rīga: Juridiskā koledža, 2018., 295 lpp.
4. Jānis Augucēvičs J., Word Microsoft Office 2013., Rīga: Biznesa augstskola Turība, 2015., 83 lpp.
5. Duffy J., Cram C., Illustrated course guide: Microsoft Word 2013 intermediate., Stamford, CT: Cengage Learning, 2014., 280 p.
6. Bluttman K. ,Excel formulas & functions for dummies. Indianapolis, IN: John Wiley & Sons, 2019., 383 p.
7. Corti L., Van den Eynden V., Libby Bishop & Matthew Woollard, Managing and sharing research data: a guide to good practice., Los Angeles : SAGE, 2014, 222 p.
8. Matthews M., Carole Matthews C., How to Do Everything: Microsoft Office Online. McGraw-Hill Education; 1 edition, 2015., 244 p.
9. Pripp A. H., Statistics in food science and nutrition. New York: Springer, 2013., 66 p.

10. Bower J.A., Statistical Methods for Food Science: introductory procedures for the food practioner. Queen Margaret University, Edinburg, UK: 2013, 318 p.

Periodicals and other sources

1. Scientific peer-reviewed papers' database, SCIENCEDIRECT. [tiešaiste] [Skatīts: 03.01.2025.]. Peejams: http://www.sciencedirect.com/

2. Scientific peer-reviewed papers' database, SCOPUS. [tiešaiste] [Skatīts 03.01.2025.]. Peejams: http://www.scopus.com/

Notes

Compulsory study course in the academic bachelor's study programm “Food Quality and Innovations”.

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