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Title: Personal knowledge techniques
Author: Milton, Nicholas Ross
Awarding Body: University of Nottingham
Current Institution: University of Nottingham
Date of Award: 2003
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Work towards the development of a new computer-assisted methodology for psychological study and intervention is described. This is referred to as the Personal Knowledge Methodology since it focuses on the elicitation and presentation of personal knowledge. Personal knowledge includes the knowledge individuals have of their life history, their behaviours, their moods, their relationships, their ambitions, and so on. Principles and techniques used in Knowledge Engineering form the basis of the design of the Personal Knowledge Methodology. At the heart of the methodology is the use of a suite of knowledge acquisition and modelling techniques. These are referred to as Personal Knowledge Techniques. Based on a review of a wide-range of literature, eight techniques were selected to be assessed for their possible use as Personal Knowledge Techniques. These included interview-based techniques, repertory grid techniques and diagram-based techniques. Two in-depth studies took place involving 18 participants and a total of 100 knowledge acquisition sessions. The results revealed that each of the eight techniques showed promise at efficiently capturing and structuring aspects of an individual’s personal knowledge. In addition, the techniques showed potential for providing help in allowing reflection and revealing insights. In particular, a technique based on the construction and use of a state transition network was found to be the most highly rated by the participants. A content analysis of the knowledge acquired formed the basis of an ontology of personal knowledge that would underpin many uses of the Personal Knowledge Methodology. The empirical work and analysis led to a number of ideas for future developments of the methodology and uses for the Personal Knowledge Techniques.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: RC 321 Neuroscience. Biological psychiatry. Neuropsychiatry ; BF Psychology Psychology Artificial intelligence Humanities Social sciences