Data, information, patterns and the creation of knowledge
Human understanding begins with encounters with data. Data consists of the symbols and signals that surround us in the world. Symbols include spoken and written language, numbers, diagrams, pictures and other representations. Signals include sensory readings of light, sound, smell, taste and touch. Researchers, journalists, scientists and teachers deliberately collect data, but we also encounter data constantly in everyday life. Observations about behaviour, measurements in experiments and examples in texts are all forms of data. On its own, however, data has no meaning. Data simply exists until someone begins to examine the data and look for relationships within the data.
Humans have a strong tendency to search for patterns in data. When enough observations accumulate, relationships begin to emerge and the data begins to form information. In the data–information–knowledge paradigm, information is the result of processing data by identifying patterns and relationships within the data. Meteorologists examine weather data and identify patterns that allow them to form information about changing weather systems. Scientists analyse experimental data and produce information about the phenomena they study. Journalists gather data and construct information about events and behaviour. In each case the data itself remains the same, but the recognition of patterns transforms the data into information.
As new data appears, the information we hold may change. A new piece of data may confirm the information we already have, or it may alter that information. Information therefore represents the best explanation available at a particular moment. It is an interpretation of the data rather than a final truth.
At this point another factor enters the process: beliefs. People rarely approach data and information with a completely neutral mind. Existing beliefs, values and expectations influence which patterns we notice and which information we accept. Psychologists refer to this tendency as confirmation bias. Information that confirms existing beliefs is readily accepted, while information that contradicts those beliefs often meets resistance or demands stronger proof. When beliefs harden into dogma they can obstruct inquiry by discouraging people from reconsidering the patterns they see in the data.
When information becomes integrated into a broader structure of understanding, it develops into knowledge. Knowledge forms a network in which information connects with experience, values and previous understanding. As information accumulates, knowledge grows and becomes part of a learner’s developing knowledge of the world. In this sense knowledge resides in the person who interprets the information and connects it with other knowledge already held.
In education an important distinction arises between transmitting information and creating knowledge. Information can be passed from teacher to student through explanations, textbooks or demonstrations. Knowledge, however, develops when learners actively examine data, recognise patterns in the data and transform the resulting information into knowledge for themselves. Through this process learners gradually construct their own knowledge rather than simply receiving information.
The progression from data to information and from information to knowledge therefore describes both a cognitive process and a pedagogical principle. Data provides the raw material that learners gather and examine. Information emerges when learners recognise and discover patterns and relationships in the data. Knowledge develops when learners integrate that information with their existing knowledge and use it to interpret new data.
As learners repeat this process they develop different kinds of knowledge. Declarative knowledge involves knowing about something: concepts, explanations and relationships. Procedural knowledge involves knowing how to do something: how to analyse a text, how to search for patterns in data, how to test an interpretation. With experience, learners also develop metacognitive knowledge, which is knowledge about their own learning strategies and about when particular procedures are useful. When learners repeatedly examine data, transform data into information and integrate that information into their understanding, these different forms of knowledge continue to develop together.
Humans have a strong tendency to search for patterns in data. When enough observations accumulate, relationships begin to emerge and the data begins to form information. In the data–information–knowledge paradigm, information is the result of processing data by identifying patterns and relationships within the data. Meteorologists examine weather data and identify patterns that allow them to form information about changing weather systems. Scientists analyse experimental data and produce information about the phenomena they study. Journalists gather data and construct information about events and behaviour. In each case the data itself remains the same, but the recognition of patterns transforms the data into information.
As new data appears, the information we hold may change. A new piece of data may confirm the information we already have, or it may alter that information. Information therefore represents the best explanation available at a particular moment. It is an interpretation of the data rather than a final truth.
At this point another factor enters the process: beliefs. People rarely approach data and information with a completely neutral mind. Existing beliefs, values and expectations influence which patterns we notice and which information we accept. Psychologists refer to this tendency as confirmation bias. Information that confirms existing beliefs is readily accepted, while information that contradicts those beliefs often meets resistance or demands stronger proof. When beliefs harden into dogma they can obstruct inquiry by discouraging people from reconsidering the patterns they see in the data.
When information becomes integrated into a broader structure of understanding, it develops into knowledge. Knowledge forms a network in which information connects with experience, values and previous understanding. As information accumulates, knowledge grows and becomes part of a learner’s developing knowledge of the world. In this sense knowledge resides in the person who interprets the information and connects it with other knowledge already held.
In education an important distinction arises between transmitting information and creating knowledge. Information can be passed from teacher to student through explanations, textbooks or demonstrations. Knowledge, however, develops when learners actively examine data, recognise patterns in the data and transform the resulting information into knowledge for themselves. Through this process learners gradually construct their own knowledge rather than simply receiving information.
The progression from data to information and from information to knowledge therefore describes both a cognitive process and a pedagogical principle. Data provides the raw material that learners gather and examine. Information emerges when learners recognise and discover patterns and relationships in the data. Knowledge develops when learners integrate that information with their existing knowledge and use it to interpret new data.
As learners repeat this process they develop different kinds of knowledge. Declarative knowledge involves knowing about something: concepts, explanations and relationships. Procedural knowledge involves knowing how to do something: how to analyse a text, how to search for patterns in data, how to test an interpretation. With experience, learners also develop metacognitive knowledge, which is knowledge about their own learning strategies and about when particular procedures are useful. When learners repeatedly examine data, transform data into information and integrate that information into their understanding, these different forms of knowledge continue to develop together.
