Topic 1 Introduction to search strategies for digital resources and importance in the learning process

Searching on the internet is easy today but an unplanned and unreflected search will often result in a chaotic mass that is difficult to navigate in. The educator first need to handle his or her own search strategy and then how to search for digital resources. A search strategy combines the key concepts of your search question in order to retrieve accurate results.

Your search strategy will account for all:

  • possible search terms
  • keywords and phrases
  • truncated and wildcard variations of search terms
  • subject headings


To develop a search strategy you will need to:

  • define and write down your research question – what is it that you are going to search?
  • identify, and keep a record of key words, terms and phrases
  • identify keyword synonyms
  • determine a timeframe from your search, if needed
  • consider what type of material you will include and why
  • identify where you will search for the information

A short introduction to create a search strategy

Write down some of your very first search experiences. Google became the biggest search engine. Even if you started your very first search on Google, write down some words about the experience.

You can also include what made it difficult and confusing

The way we search and access digital resources changed when search engines started helping humans!

look into how search engines work:

How does a search engine work

The biggest most used search engine is Google (surprise?)

When you search on Google the engine will use search algorithms – for example:

  • Meaning of your query
  • Relevance of webpages
  • Quality of content
  • Usability of webpages
  • Context and settings

Meaning of your query

Google build language models to try to decipher what strings of words they should look up in the index.

The language models take into considerations:

  • interpreting spelling mistakes
  • synonym system
  • specific search or a broad query
  • freshness algorithms

Relevance of webpages

Beyond simple keyword matching, Google use aggregated and anonymized interaction data to assess whether search results are relevant to queries. They transform that data into signals that help the machine-learned systems better estimate relevance.

These relevance signals help search algorithms assess whether a webpage contains an answer to your search query, rather than just repeating the same question.

Quality of content

Search algorithms aim to prioritize the most reliable sources available. To do this, systems are designed to identify signals that can help determine which pages demonstrate expertise, authoritativeness, and trustworthiness on a given topic.

Google’s search engines look for sites that many users seem to value for similar queries.

Usability of webpages


When ranking results, Google search engines also whether webpages are easy to use. When they identify persistent user pain points, they develop algorithms to promote more usable pages over less usable ones, all other things being equal.

Context and settings

Information such as your location, past search history and search settings all tailor your results to what is most useful and relevant for you in that moment.

Google use your country and location to deliver content relevant for your area.

The business model for Google is that they can sell targeted advertisings that fit your presumed preferences

To see or change the information Google on you, you can look at 

How does a search engine work

What happens when you do a Google search?

How Google Search Works (5:15 min)

Full length movie Google search (58:10 min)

In this very first topic in module 2 ”Introduction to search strategies for digital resources and importance in the learning process” we have into traditional search and search strategies. Here the user the way a search is performed.

After the traditional search introduction, we went through a modern search – done by search engines. The way a search engine works introduced.