Artificial intelligence (AI) glossary
This glossary compiles key terms used in recent POST research on artificial intelligence (AI).
This glossary compiles key terms used in recent POST research on artificial intelligence (AI).
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This research glossary accompanies POST's research evidence content and provides definitions for terms used there.
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What is validity, reliability, generalisability and applicability of research evidence? This section will focus on the way in which quality is assessed in quantitative and qualitative research.
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After data are collected, research studies can use various forms of analysis to draw conclusions from the information. This section goes over the different strategies for analysing data.
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A research study can collect quantitative data and/or qualitative data. This section goes over the different types of data researchers are able to collect, and the methods they employ to conduct their research.
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Secondary research refers to the analysis and synthesis of primary research. Secondary research can review primary research evidence- if you collect it together and explain what it says about an area.
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This section defines some of the study designs most commonly cited in POST’s work. Primary research refers to individual studies where researchers generate and analyse their own data. Secondary research refers to the synthesis and/or reanalysis of primary research data. We will start with primary research.
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There's a huge range of research evidence out there. Why is it different than other types of information? How is it collected and analysed? Here we have collected resources to help you understand and use research evidence more effectively.
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To ensure our research publications are comprehensive and balanced, we need insights from experts. Could that be you? Find out how to contribute to our research.