Bachelor
2023/2024
Digital Literacy
Type:
Compulsory course
Area of studies:
Business Informatics
Delivered by:
Department of Operations Management and Logistics
Where:
Graduate School of Business
When:
1 year, 3, 4 module
Mode of studies:
offline
Open to:
students of one campus
Language:
English
ECTS credits:
6
Contact hours:
38
Course Syllabus
Abstract
People encounter a lot of data at work and outside of work: for example, they look at predicted travel times and choose which mode of transportation to take, analyze prices of products they buy, plan dates for upcoming events, etc. Companies also operate with a lot of data: it can be financial (e.g., costs or revenue) and non-financial (e.g., level of service). This data can be discussed verbally or processed in mind but much more often it is visualized in some way and presented in a way that is easy for different people to work with. When is there a need to present data? For example in the preparation of reports, in presentations on a consulting project, at meetings to change the assortment of the company, when making decisions about inventory management, risk management, transportation, logistics, warehousing, etc. How correctly data is searched, processed, analyzed and visualized often determines a company's decision-making. Despite the evolving processes of digitalization, companies in all areas of business continue to use seemingly basic tools (such as Excel, Power Point and Word, Google Docs) for most data-related tasks (concerning both analysis and presentation) because of their relative simplicity and convenience. Even when using more advanced technologies for these tasks, employees need a basic understanding of why and how data work is needed. That's why this course will remain relevant throughout training and on the job, regardless of the position or area of business. The course is an adaptation of the university-wide Digital Literacy course; specifically for the Management and Digital Innovation program. This course focuses on an introduction to the basic principles of working with data. In particular, the course includes such topics as: preparation of data for processing and analysis, working with data, data aggregation, visualization using graphs and infographics, building a logical structure of the presentation for the most correct presentation of analysis results, computer literacy and security, basics of media communication, work with search engines, etc.
Learning Objectives
- The main goal of our course is to give students a holistic view of how to search for information and data; how to analyze different types of data and how to prepare competent presentation of the analysis results.
Expected Learning Outcomes
- ● Analyze the risks of leaks of sensitive information
- ● Apply basic Excel function knowledge: in particular, knows how to convert data from one type to another, works with combined formulas and functions (simple ones like SUM, dollar sign, useful functions like SUMMESLY and VPR), including formula stuffing, stretching formulas, tables, copying data from one sheet to another, switching cell reference styles, fixing cells in formulas
- ● Apply basic Word hotkeys
- ● Apply data filters in spreadsheets and pivot tables
- ● Apply Excel tools to create selected chart and graph types (including pie charts, bar charts, scatter charts)
- ● Apply file conversion from one format to another
- ● Apply primary data processing and analysis
- ● Apply the basic Power Point hotkeys
- ● Apply the Power Point tools to create a selected type of infographic/chart, and design a constructed chart
- ● Apply the principles of working with personal data
- ● Apply the rules of referencing to academic papers
- ● Apply the simplest statistical analysis methods for simple forecasts in MsExcel (e.g. trending. correlation analysis, etc.).
- ● Compare different types of data visualization and applies the selected type to the given task
- ● Compare formats for images and audio and applies the most appropriate one
- ● Create correct and appropriate emails for educational purposes
- ● Create formatting of different text components: knows how to create lists of different formats, align and change font, etc
- ● Create or knows how to insert pictures, diagrams, tables, hyperlinks in text
- ● Create relevant search queries for finding information on the Internet
- ● Create slides, and applies the following skills: copy, copy style, change background of slide, duplicate formatting, save and export slides in different formats
- ● Create spreadsheets and uses the search function to solve problems
- ● Create various visual elements such as tables, graphs, charts, etc.
- ● Describe the basic components of media literacy and online communication skills
- ● Describe the basic ways of structuring information on a slide
- ● Describe types of machine learning models and their essence, algorithm for assessing model quality
- ● Determine the version of the operating system installed on the computer
Course Contents
- Computer literacy
- Basics of documents formatting
- Internet and media literacy
- Academic literacy and the use of digital technology for research
- The basics of working with data in tables
- Basics of computer security and legal aspects of information technologies.
- Basics of presentation design and structure
- Working with data
Assessment Elements
- Activities in seminars and lectures, homeworksHanding in course assignments according to set criteria
- Final test for the online course
- Final project Theoretical part
- Final project Survey
- Final Project Defense (Exam)Handing in a project on a chosen topic, consisting of: 1) Title page; 2) Table of contents; 3) Introduction; 4) Theoretical part; 5) Practical part; 6) Conclusion; 7) List of references; 8) Appendices. What is to be submitted: Word with written part of the project, Excel file (with unprocessed data of survey, with processed data of survey, with data analysis and graphs and charts) no later than 12 days before the exam. The presentation of the project in 2 formats (.pptx and .pdf) should be submitted no later than 7 days before the examination. Presentation of the project in the examination session (presentation and answers to questions on the topic of the project and the course).
Interim Assessment
- 2023/2024 4th module0,8*MIN((0,3*Mark for Activities in seminars and lectures, homeworks + 0,3 * Mark for Final test for the online course + 0,05 * Mark for Final project Theoretical part + 0,05 * Mark for Final project Survey + 0,3 * Mark for Final Project Defence);8) Comments for the formula (paragraph 6 from ПОПАТКУС; https://www.hse.ru/docs/551872110.html): "69. The independent examination may have optional or mandatory prerequisite disciplines included in the curriculum of the educational programme. The degree of compulsory disciplines-requisites is defined in the programme of the independent examination or in other local normative acts describing the peculiarities of competence formation. The grade assigned on the basis of the results of interim certification on the discipline-requisites for the independent examination on the digital competence cannot be more than 8 points." It is possible to get a grade 9-10 for the discipline by re-crediting the grade for the independent examination. The re-credits are carried out automatically by the Data Culture team.
Bibliography
Recommended Core Bibliography
- Bailey, S. Academic Writing: A Handbook for International Students / Stephen Bailey. – 4th edition. – Oxon: Routledge; Taylor & Francis Group, 2015. – 305 p. – ISBN 978113877668022. - Текст: электронный // DB ProQuest Ebook Central (ebrary) [сайт]. – URL: https://ebookcentral.proquest.com/lib/hselibrary-ebooks/reader.action?docID=1811067&query=Bailey%252C%2BStephen
- Alpaydin, E. (2014). Introduction to Machine Learning (Vol. Third edition). Cambridge, MA: The MIT Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=836612
- Brian W. Kernighan. (2017). Understanding the Digital World : What You Need to Know About Computers, the Internet, Privacy, and Security. Princeton University Press.
- Freedman, J. J. (2013). Microsoft Word 2013 Plain & Simple. Microsoft Press.
- Held, B., Moriarty, B., & Richardson, T. (2019). Microsoft Excel Functions and Formulas (Vol. Fifth edition). Dulles, Virginia: Mercury Learning & Information. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=2051937
- Muir, N. (2013). Microsoft PowerPoint 2013 Plain & Simple. Microsoft Press.
- Vijayan, J. (2016). Google Now Combining Browsing Data With Personally Identifiable Info. EWeek, 1. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=bsu&AN=119088888
Recommended Additional Bibliography
- Ad A.M. Prins, Rodrigo Costas, Thed N. van Leeuwen, & Paul F. Wouters. (2016). Using Google Scholar in research evaluation of humanities and social science programs: A comparison with Web of Science data. Research Evaluation, (3), 264. https://doi.org/10.1093/reseval/rvv049
- Can Google Scholar and Mendeley help to assess the scholarly impacts of dissertations? (2019). Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.C32203D9
- Davenport, T. H. (2014). Big Data at Work : Dispelling the Myths, Uncovering the Opportunities: Vol. [Academic Subscription]. Harvard Business Review Press.
- Farney, T., McHale, N., & Library and Information Technology Association (U.S.). (2013). Maximizing Google Analytics : Six High-Impact Practices. ALA TechSource.
- Hales, J., & Aldrich, L. (2012). Powerpoint Tips & Tricks. [Boca Raton, Florida]: QuickStudy Reference Guides. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1534329
- I. Korotkina B., & И. Короткина Б. (2017). Academic Literacy and Methods of Global Scientific Communication ; Академическая грамотность и методы глобальной научной коммуникации. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.8C60FBE4
- Martín-Martín, A., Orduna-Malea, E., Thelwall, M., & López-Cózar, E. D. (2018). Google Scholar, Web of Science, and Scopus: a systematic comparison of citations in 252 subject categories. https://doi.org/10.1016/j.joi.2018.09.002