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18
Декабрь

Digital Literacy

2021/2022
Учебный год
ENG
Обучение ведется на английском языке
5
Кредиты
Статус:
Курс обязательный
Когда читается:
1-й курс, 1, 2 модуль

Преподаватель


Крайникова Влада Александровна

Course Syllabus

Abstract

This course is an adaptation of the university-wide course"Digital Literacy" specifically for students of the bachelor program "International Business and Management" and "Economics" (in English). Practice-oriented course, the objectives of which are: the development of the ability to conduct research in the field of management, the acquisition of knowledge about modern information technologies used to conduct research, the acquisition of knowledge about working in MS Excel, MS Word, MS PowerPoint and the development of skills for searching and processing information.
Learning Objectives

Learning Objectives

  • To teach students the principles and methods of using digital tools in the field of economics and management.
Expected Learning Outcomes

Expected Learning Outcomes

  • Able to convert a file from one format to another
  • Can convert data from one type to another, enter formulas, drag out formulas, copy data from one source to another, switch styles of referring to cells, fix cells in formulas in MS Excel / Google.
  • Can create slides, copy, copy style, change slide background, duplicate formatting, save and export slides in different formats.
  • Can format various components of solid text: font, sheet alignment, indents, line spacing.
  • Can insert images, tables, hyperlinks, pagination, document / presentation content.
  • Can store, upload, find and download files on Google Drive, share a document with other users, comment on a document, and respond to comments from other users.
  • Choose a suitable format for image and sound files.
  • Distinguishes between shortcuts and symbolic links to files and directories.
  • Knows how to call the simplest actions such as "copy", "paste", "find", "cancel", etc., owns the functionality of "hot keys".
  • Knows how to carry out primary processing and analysis of data.
  • Knows how to create a numbered list, divide text into columns. Optimize work with text, create styles (for example, create headings).
  • Knows how to create collections of bibliographic descriptions and articles, add material to Zotero through a browser, explorer or manually, create bibliographic lists in a few clicks, work with Google Scholar and other bibliographic sources.
  • Knows how to find suitable informtaion and data in the Internet
  • Knows how to navigate and configure for productive work the interface of MS Office (Word, Excel, PowerPoint) and Google applications (Docs, Spreadsheets, etc.).
  • Knows how to protect their personal data from fraudsters and malicious software.
  • Knows how to recognize threats in the digital space.
  • Knows how to visualize data.
  • Knows how to work with tables and graphs.
  • Knows how to work with text and images.
  • Knows the concept of machine learning, the types of machine learning models and their essence, the algorithm for assessing the quality of the model.
  • Knows the features of data types and the principles of operation of modern technologies in the humanities.
  • Master skills of practical work with data and solving applied problems of data analysis and visualization.
Course Contents

Course Contents

  • Computer literacy
  • Internet and browsing
  • Computer security
  • Media literacy
  • Legal aspects of information technology
  • Basic text technologies. work with texts in MS Office Word and Google Docs
  • Working with tabular data in MS Excel and Google Spreadsheets
  • Preparation of presentations: tools and usage
  • Writing research papers
  • Basics of working with data. Machine learning
Assessment Elements

Assessment Elements

  • non-blocking Learning the online course
    The course "Digital Literacy" is held on the internal NRU HSE [URL: online.hse.ru]. Course is devoted to the key topics of digital litercay such as computer literacy, media literacy, security in the Internet and baisc approaches to data processing in text, media and tabular processors etc. The grade for the discipline is set in accordance with the assessment formula for all passed control elements.
  • non-blocking Test 1
    Cheating is strictly prohibited during the tests (using mobile devices, paper materials, cheat sheets, connecting to the Internet / local network, talking with other students, and viewing another screen or recordings). If the facts of cheating are revealed, the student is removed from the classroom ahead of schedule and receives 0 (zero) points for a specific test. If it is impossible to perform the test in person for a good reason (i.e. medical issues), by agreement, the test is carried out in a remote format using proctoring tools, the features of the procedure are described in the following document https://docs.google.com/document/d/1hq58cNWzb8uKROgwFOEpp9wnuQxIvCIZ/edit?usp=sharing&ouid=107885429336123860818&rtpof=true&sd=true
  • non-blocking Test 2
    Cheating is strictly prohibited during the tests (using mobile devices, paper materials, cheat sheets, connecting to the Internet / local network, talking with other students, and viewing another screen or recordings). If the facts of cheating are revealed, the student is removed from the classroom ahead of schedule and receives 0 (zero) points for a specific test. If it is impossible to perform the test in person for a good reason (i.e. medical issues), by agreement, the test is carried out in a remote format using proctoring tools, the features of the procedure are described in the following document https://docs.google.com/document/d/1hq58cNWzb8uKROgwFOEpp9wnuQxIvCIZ/edit?usp=sharing&ouid=107885429336123860818&rtpof=true&sd=true
  • non-blocking Test 3
    Cheating is strictly prohibited during the tests (using mobile devices, paper materials, cheat sheets, connecting to the Internet / local network, talking with other students, and viewing another screen or recordings). If the facts of cheating are revealed, the student is removed from the classroom ahead of schedule and receives 0 (zero) points for a specific test. If it is impossible to perform the test in person for a good reason (i.e. medical issues), by agreement, the test is carried out in a remote format using proctoring tools, the features of the procedure are described in the following document https://docs.google.com/document/d/1hq58cNWzb8uKROgwFOEpp9wnuQxIvCIZ/edit?usp=sharing&ouid=107885429336123860818&rtpof=true&sd=true
  • non-blocking Research Project
  • non-blocking Final Exam
    Cheating is strictly prohibited during the tests (using mobile devices, paper materials, cheat sheets, connecting to the Internet / local network, talking with other students, and viewing another screen or recordings). If the facts of cheating are revealed, the student is removed from the classroom ahead of schedule and receives 0 (zero) points for a specific test. If it is impossible to perform the test in person for a good reason (i.e. medical issues), by agreement, the test is carried out in a remote format using proctoring tools, the features of the procedure are described in the following document (note: fo the exam time is 80 min) https://docs.google.com/document/d/1hq58cNWzb8uKROgwFOEpp9wnuQxIvCIZ/edit?usp=sharing&ouid=107885429336123860818&rtpof=true&sd=true
Interim Assessment

Interim Assessment

  • 2021/2022 2nd module
    0.2 * Learning the online course + 0.15 * Test 2 + 0.15 * Test 3 + 0.05 * Research Project + 0.15 * Test 1 + 0.3 * Final Exam
Bibliography

Bibliography

Recommended Core Bibliography

  • 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.
  • Rockoff, L. (2013). Microsoft Excel 2013 for the Business Analyst. Cengage Learning PTR.

Recommended Additional Bibliography

  • Дюк, В., & Фомин, В. (2008). Интеллектуальный анализ данных в гуманитарных областях. Программные Продукты и Системы, (3). Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsclk&AN=edsclk.15549904
  • Дюк, В., Флегонтов, А., & Фомина, И. (2011). Применение технологий интеллектуального анализа данных в естественнонаучных, технических и гуманитарных областях. Известия Российского Государственного Педагогического Университета Им. А.И. Герцена, (138). Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsclk&AN=edsclk.2007827