Book Review: Information Literacy beyond Library 2.0

A sequel to Information Literacy meets Library 2.0, Information Literacy beyond Library 2.0 is in my opinion, a must read for all information professionals. Exploring the shift of the information environment triggered by social and mobile channels, the contributors within this text explore the impact of technology trends on information as well as digital consumption and literacy, whilst sharing case studies to demonstrate trends and suggest theories. Questions are asked, new ways-of-working and theoretical frameworks are introduced, all in an effort to respond to the ‘new’ information literacy.

Key case studies include: Using games as treatments and creative triggers: a promising strategy for information literacy, written by Susan Boyle; and Informed cyberlearning: a case study, by Hilary Hughes.

 

Godwin, P and Parker, J. (2012). Information Literacy Beyond Library 2.0. London: Facet Publishing.

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Google it

In an age where ‘google’ has become synonymous with information searching online, I think it’s important for all Google Search users to understand what Google Search is, and how it operates. Formed in a Californian garage, Google is the very handsome love child of Larry Page and Sergey Brin. Both studying at Stanford University during the mid 90s, they were on a joint mission: “to organize the world’s information and make it universally accessible and useful.” (1)

Google Search, as we know it today is a Web search engine. If you are unfamiliar with this term, think of a Web search engine as a gateway to the World Wide Web. When you google something, you are searching Google’s index of the Web. A common misunderstanding is the assumption that when querying the Web using a Web search engine, you are searching the whole of the Web. This isn’t strictly true. Not only are you not searching the entire Web, you are not searching the Web at all. You are instead searching Google’s index of the web. The Web contains many pages, most of which would be incomprehensible without the help of the indexing of Web search engines. Google’s day job is to find and index information held on the Web, in order for users of Google Search to be able to access the information they want.

Google Search / I’m Feeling Lucky

When you hit search on your Google browser, your computer starts communicating with one (or more) of Google’s servers. These servers contain large databases of the Web’s content, and are accessed via Google’s query engine. The query engine retrieves potential information sources, and the Google algorithm (the recipe for which is top secret) gets to work determining the ranking of the potential information sources. Google Search will then feedback the results of your query, usually with multiple options. These results have been ranked in terms of reliability and trustworthiness by the Google Search algorithm.

The Birth of Search Engine Optimisation

Due to the ranking of pages within indexes, an entire cottage industry has grown up around Search Engine Optimisation (SEO). With many website owners relying on Web search engines to send users to their website, a pay-to-play operational cost has developed around the Web. In order for Google Search to operate efficiently, Google use a ranking algorithm in order to try and return what they interpret to be the best version of the information the user is looking for. In order to do this, Google Search ranks pages and sites, assigning a score to every page contained within the World Wide Web. The ranking of pages by Google is an intricate and ever changing process, which has led to the SEO industry flourishing. In an effort to improve rankings, Webmasters operating outside of Google will try and trick Web search engines – resulting in the ranking process being honed time and time again by the Web search engine owner (Google in this case) in order to filter out this spam.

As with most technology, Web search engines are evolving. Moving from the simplistic tagging of information, to a semantic understanding of the Web. No longer relying on what site owners tell them about their pages, Google are beginning to delve deeper into their knowledge base, aggregating semantic data by analysing the connections between information, as well as the information itself.

Enter centre stage right: Machine Learning.

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Sources: (1) https://www.google.com/intl/en/about/our-story/ http://www.bbc.co.uk/guides/z8yc2p3 https://www.google.com/search/howsearchworks

 

How to design a library that makes kids want to read

This TED talk is 12 minutes well spent. Michael Bierut discusses his input as Lead Graphic Designer on a New York library initiative, sponsored by charitable organisation, Robin Hood. Using energy, learning, art and graphics, Bierut’s work on this years-long ‘passion project’ supported school librarians in inspiring new generations of readers and thinkers.

Paper Review: The role of networking and social media tools during job search: an information behaviour perspective

Published in 2016, The role of networking and social media tools during job search: an information behaviour perspective, written by Prof. Hazel Hall, Prof. Robert Raeside and John Mowbray is an analysis of the available literature concerning networking behaviours of young jobseekers in both online and offline environments. Concentrating on three key themes: the use of social networks and informal information channels during job searches; networking behaviours in job search; and the use of social media tools, the paper offers an informative introduction, to a largely unexplored area.

Touching on the importance of ‘loosely-knit social circles’ that are generated using social networking sites, the paper recommends the need for further examination of young jobseekers’ engagement with social media tools supporting networks in online environments. During their interrogation of sixty-three papers from the extant literature published between 1973 and 2016, the researchers, sought to answer two questions:

  1. What are the key offline networking behaviours employed by young jobseekers during the job search process?
  2. How do social media tools support the networking behaviours of the young jobseekers during the job search process?

In answering these questions, the researchers propose Wilson’s (1997) general model of information behaviour as a suitable theoretical framework. Concluding that gaps exist within the literature, where further research is necessary to expound the process of networking during job search by young jobseekers.

 

Sources: Mowbray,J., Hall., Raeside, R. & Robertson, P. (in press). The role of networking and social media tools during job search: and information behaviour perspective. | Wilson, T.D. (1997). Information behaviour: an interdisciplinary perspective. Information Processing & Management, 33(4), 551-572.