Skip to Main Content

Digital Literacy

This guide introduces the concept of digital literacy and relevant resources available at CityU and beyond.

Evaluating information sources

The internet provides us with a seamless access to information. While there are fewer barriers to access information, it is difficult to make sense of the huge amount of information we come across every day. The RADAR framework helps us evaluate information critically and choose quality information that fulfills our information needs, whether it is for academic use (e.g. course assignment) or general use in daily life.

While the following questions help you evaluate information sources, note that the answers to these questions are not absolute (either yes or no). It is important to look at a variety of sources so that you can get a balanced view and thorough understanding of a topic.

The RADAR Framework

Rationale - What is the rationale of creating the information?

  1. Is the information intended to inform, entertain, persuade or sell?
  2. Is the information fact, opinion or propaganda? 
  3. Does the information present a balanced view with alternative points of view?

Authority - What is the authority of the information source?

  1. What are the author’s credentials? Does the author have expertise in the topic?
  2. Is the author affiliated with an educational institution (e.g. a university) or a reputable organization?
  3. For online information (e.g. website) where the author is not known, consider the credibility of the company or organization that published the information. Check the “About us” page to find out more about the website.

Date - When was the information published?

  1. Is the recency of the information important to your topic? If so, when was the information last updated?
  2. Is the information obsolete? Note that in some disciplines, e.g. computer science, information can become obsolete quickly.

Accuracy - Is the information reliable, true and correct?

  1. Does it provide citations and references so you can check for accuracy?
  2. Is the information supported by evidence?
  3. Is the information written in a formal, academic language?
  4. Does the information look serious and professional?
  5. Are there any spelling, grammatical or typographical errors?

Relevance - How useful is the information in helping you understand the topic?

  1. Does it help you understand the topic or answer your research question?
  2. Is the information too general or too specific?
  3. Is the information too elementary or too advanced?

 

Content adapted from Mandalios, J. (2013). RADAR: An approach for helping students evaluate Internet sources. Journal of Information Science, 39(4), 470-478.

Verifying information

The internet does not only provide us with seamless access to information, it also connects us with one another. In particular, the social media (e.g. Facebook, Instagram, Twitter, etc.) connects us instantly to others with common interests, values and beliefs. In this networked media, we are both information consumers and information creators.

While everyone can publish information online, there is no guarantee of the truthfulness and accuracy of the information. Some information that we find online looks real but it may be fake. Therefore, it is important that we fact-check and verify these sources. 

Watch this video which explains how we are all connected in an interactive web of information. 

Tools for verifying

Fact-checking websites:

Tools for verifying images:

Working with data

The ability to work with data is essential for our studies and everyday life. Working with data includes, but not limit to, the practice of collecting, organizing, storing and protecting data.

To find Library resources on data science, please refer to the Data Science subject guide.

Big data emerged as a subject that has generated research interests and attracted public attention.

Big data refers to the "rapid acceleration in the expanding volume of high velocity, complex and diverse types of data".[1]

Big data is commonly described by the Three Vs - Volume, Variety, and Velocity.[2]

  • Volume – huge amount of data. The size or magnitude of data.
  • Variety – high level of variety. Various types of structured, semi-structured, and unstructured data.
  • Velocity – high speed of data being generated. An unprecedented rate of data creation.

Big data can be applied in various fields including industries, research and the public sector. Big data does not only drive the exponential growth of the internet economy, it also advances healthcare, improves education and optimizes business operations.

Big data analytics refers to the data being processed, analyzed and as a result, driving decision-making. One of the reasons of the broad application of big data is because it enables evidence-based decision-making.

The big data processes described the process of extracting insights from big data in 5 stages.[3]

Adapted from "Beyond the hype: Big data concepts, methods, and analytics," by A. Gandomi and M. Haider, 2015, International Journal of Information Management, 35(2), p.137-144 (http://doi.org/10.1016/j.ijinfomgt.2014.10.007). CC BY-NC-ND 3.0

 

The following are some techniques or tools of extracting insights from big data:[3]

  • Text analytics (text mining) – to extract information from texts
  • Audio analytics (speech analytics) – to extract information from audio clips
  • Video analytics (video content analysis ) – to extract information from videos
  • Social media analytics – to extract data from social media channels
  • Predictive analytics – to predict future outcomes based on historical and current data

Data visualization

Data visualization is "the visual representation and presentation of data to facilitate understanding".[4]

The purpose of visualizing data is to help people understand, analyze and compare data. It can appear as images, graphs, charts and other formats that show patterns, trends and relationships among data.

There are plenty of data visualization tools available. The following are some examples:

  • Canva - create infographics, graphs and charts
  • Google Data Studio - create interactive dashboards and reports
  • infogram - create infographics, reports and maps
  • Lucidchart - cloud-based application to create diagrams, dynamic graphics and more
  • Microsoft Power BI - software that focuses on business intelligence 
  • RAWGraphs - web application to visualize quantities, hierarchies, time series and more
  • Tableau - easy-to-use tool to create visualizations
  • ZOHOReports - create reports and dashboards for business 

 When choosing a tool, you may consider the following factors:

  • Technical requirements of the tool
  • Volume of data
  • Analysis needs
  • Price or cost

[1] TechAmerica Foundation. (2012). Demystifying big data: A practical guide to transforming the business of government. TechAmerica Foundation’s Federal Big Data Commission. https://bigdatawg.nist.gov/_uploadfiles/M0068_v1_3903747095.pdf

[2] Laney, D. (2001, February 6). 3-D data management: Controlling data volume, velocity and variety. META Group Inc. http://blogs.gartner.com/doug-laney/files/2012/01/ad949-3D-Data-Management-Controlling-Data-Volume-Velocity-and-Variety.pdf

[3] Gandomi, A. & Haider, Murtaza. (2015). Beyond the hype: Big data concepts, methods and analytics. International Journal of Information Management, 35(2), 137-144. https://doi.org/10.1016/j.ijinfomgt.2014.10.007

[4] Kirk, A.(2017). Module one: defining data visualisation [Video]. SAGE Research Methods Video: Data Science, Big Data Analytics, and Digital Methods. https://dx.doi.org/10.4135/9781526480835

© City University of Hong Kong | Copyright | Disclaimer