Think critically about information and search results to make informed, balanced decisions.
Evaluate critically refers to the ability to ask questions about information sources, including AI generated outputs, to assess their strengths and weaknesses and make balanced judgements about them. This enables learners to evaluate their search results, which may require them to return to planning and searching, and to choose the most appropriate information sources for a need.
Teaching this skill? Read on to see the learning objectives associated with each level or click here to skip straight to our teaching case studies.
Finding glossary terms? Select highlighted terms to view a definition or find relevant resources.
Select the boxes below to view the learning objectives for each level.
Learning objectives
Understand that sources of information have different intended audiences, and the need to engage with Scholarly sources material aimed at an academic readership.
Ask and answer questions to evaluate the quality of an information source (e.g. Who wrote it? When? Why?)
Understand that some sources of information are more suitable than others for the purposes of a research task. Judge the relevance of different kinds of information for a task.
Identify AI-generated content when encountered and understand that AI may provide false information.
Understand the importance of checking facts presented in AI responses or other sources.
Understand that bias exists in sources and that sources vary in credibility. Identify a source’s author/creator and evaluate their credibility based on information available about them.
Review search results, discard items with irrelevant titles or Abstracts, and use simple quality checks to identify reliable and relevant information for the task.
Understand that evaluating sources might lead to re-examining the scope or focus of a search.
Resources and activities
View these example models to find questions you can ask about a source to evaluate it critically: CRAAP test, PROMPT or RADAR.
Pick an information source to evaluate. This could be a book, article or website for example. Now choose one of the following models: CRAAP test, PROMPT or RADAR. Use the model to ask questions about the source.
Learning objectives
Apply comprehensive quality criteria to critically evaluate information, tools and data from any source (considering Authority, bias, etc.) to focus on the most appropriate source for the context.
Demonstrate the ability to check the facts and evaluate any citations or references that are presented in a source, including AI responses.
Demonstrate understanding of potential search engine and AI algorithm bias. Understand that the way these tools work can impact the results (or information) returned and the order they are returned in.
Demonstrate the ability to scrutinise any data, methodologies and conclusions presented in the literature and consider the possibility of bias.
Apply relevant criteria to filter large quantities of information related to the research question.
Adopt a more sophisticated approach to evaluating search results and focus on the most relevant information within documents (by skim-reading article Abstracts, for example).
Distinguish between good and bad search results. Develop a basic understanding of article or journal-level Research metrics and use this to inform the evaluation of search results.
Identify ways of modifying a search strategy to improve future results or adjust the scope as required.
Run a search in Library Search and examine the search results. Look at how many results you get and how relevant they are to your topic - how effective was this search? Would adding filters or adjusting your search terms improve future results?
Learning objectives
Critically appraise any source (including academic, non-scholarly and professional sources and Grey literature) using comprehensive quality criteria.
Critically appraise the reliability and validity of own work and the work of others.
Confidently check the facts and evaluate citations and references in any source, including responses from AI assistants.
Demonstrate the ability to scrutinise any data, methodologies and conclusions presented in the literature and consider the possibility of bias and bad practice.
Demonstrate awareness of potential systemic and computational bias in search engine and AI algorithms and consider ways to mitigate this through search strategies.
Can make quick judgements about the relevance and quality of search results to filter large quantities of information according to the scope of the research question.
Understand and responsibly deploy Research metrics to evaluate search results. Understand the limits of research metrics and why they are limited.
Adapt search strategies to improve future results or adjust the scope as required.
Find three articles on the same topic and compare their citation counts or journal metrics. Which one do the metrics suggest is strongest? Can you identify any limitations to these metrics? You might consider article age, niche research area or other factors.
Teaching staff
The skills of critically evaluating information are most effectively nurtured when developed within the context of a student’s discipline and assessed work – by showing students examples that are relevant to their context and demonstrating what kinds of resources can be relied upon in the student’s disciplinary. The case studies below provide examples of where these skills, and library instruction, have been integrated into modular teaching and departmental skills provision.
The Research and Academic Services division can work with you to identify the searching skills most relevant to your students, design activities using subject-specific examples and resources, and embed teaching within your module or programme.
In Sociology first year students undertake an Academic Skills module SO131. The Library runs one lecture on the module, which focuses on understanding different types of academic source, searching for sources and evaluating sources. In the evaluating sources section, students first consider what criteria they might use to evaluate sources. They are then introduced to the CRAAP test model and use this to examine a set of search results.
Evaluation is often included as an implicit skill in undergraduate or PGT dissertation and independent project modules, alongside elements relating to searching for literature. We would be very happy to develop new, focused case studies, particularly relating to AI use, for PGT or dissertation skills sessions.
The Library runs an interdisciplinary workshopLink opens in a new window on investigating research metrics. Attendees explore finding citation metrics, altmetricsand journal impact factors; use of the Scopus, Web of Science and Dimensions databases; limitations and responsible use of research metrics,and they consider use of artificial intelligence in measuring research. This could be developed into a bespoke workshop for specific disciplines and cohorts.
Similarly, the team runs a workshop called Critical AI Use for Researchers, which explores how one might evaluate an AI tool (as opposed to an academic search engine) and how to go about evaluating an AI output. We would be happy to develop this into a bespoke workshop as part of your department's graduate skills provision.
Contact us
We are developing the teaching provision (and case studies) arising from this framework on an ongoing basis. Please get in touch if you have any feedback, or would like to propose a session as part of your programme: contact us.
