project outline | design | post-project
discourse study-blog | resources | lit review maps | profiles
enquiry research QNR | dysdefs QNR | dysdims QNR
thesis overview | literature | research design | data & analysis | discussion | conclusions
discourse study-blog | resources | lit review maps | profiles
enquiry research QNR | dysdefs QNR | dysdims QNR
thesis overview | literature | research design | data & analysis | discussion | conclusions
profiles
Creating data profiles
Visualization of data (Few, 2009) is a key process in this project. Assuming that the deployment of the main research QNR deployment collects the information that it is designed to, more than 100,000 bits of data will be generated, to sort, visualize and analyse.
As outlined elsewhere, the idea of creating construct profiles to more clearly 'see' the data has been an important part of the project design. The earlier 'Locus of Control Profiles' created in the pilot study (bottom) were an innovative visualization that was developed to convert list-based data into visually representative diagrams. At that time, no HTML-based process was known to the researcher that could create multi-axis radar plots, so these diagrams were all drawn 'by hand' using a graphics package. The outcome was startlingly effective and certainly worth the time and labour involved as the similarities and contrasts that emerged contributed substantially to understanding what the data meant. The complete MSc Disseration is available here.
With the advent of HTML5, functionality for creating web-browser-based graphics is developing well and it is now possible to generate multi-axis radar plots that can accept data in simple format to create engaging representations of the information locked up in that data. Far from being just pretty pictures, this level of visual representation of information will greatly aid the analysis and discussion processes of the project because it enables connections, patterns, trends, similarities and contrasts to be more easily identified.
Develoment work is progressing for creating the construct profiles for the data that this project's main research QNR will be generating, but it seems almost certain that 6-axis radar plots will be used to display the 6 constructs being explored. These will be combined with bullet charts to display Academic Behavioural Confidence and a newly-developed Dyslexia Index. Psuedo-respondent data has been used to create the two trial plots below so that the processes for generating these diagrams can be tested and assessed to decide whether the effort is worth it and to determine if this is a scalable for the whole project. Results so far are promising.
Respondent ID: 30113372 is a representation of a likely profile for a student with no indication of dyslexia whilst Respondent ID: 47218304 may be a typical representation of a student with moderate dyslexia.
Visualization of data (Few, 2009) is a key process in this project. Assuming that the deployment of the main research QNR deployment collects the information that it is designed to, more than 100,000 bits of data will be generated, to sort, visualize and analyse.
As outlined elsewhere, the idea of creating construct profiles to more clearly 'see' the data has been an important part of the project design. The earlier 'Locus of Control Profiles' created in the pilot study (bottom) were an innovative visualization that was developed to convert list-based data into visually representative diagrams. At that time, no HTML-based process was known to the researcher that could create multi-axis radar plots, so these diagrams were all drawn 'by hand' using a graphics package. The outcome was startlingly effective and certainly worth the time and labour involved as the similarities and contrasts that emerged contributed substantially to understanding what the data meant. The complete MSc Disseration is available here.
With the advent of HTML5, functionality for creating web-browser-based graphics is developing well and it is now possible to generate multi-axis radar plots that can accept data in simple format to create engaging representations of the information locked up in that data. Far from being just pretty pictures, this level of visual representation of information will greatly aid the analysis and discussion processes of the project because it enables connections, patterns, trends, similarities and contrasts to be more easily identified.
Develoment work is progressing for creating the construct profiles for the data that this project's main research QNR will be generating, but it seems almost certain that 6-axis radar plots will be used to display the 6 constructs being explored. These will be combined with bullet charts to display Academic Behavioural Confidence and a newly-developed Dyslexia Index. Psuedo-respondent data has been used to create the two trial plots below so that the processes for generating these diagrams can be tested and assessed to decide whether the effort is worth it and to determine if this is a scalable for the whole project. Results so far are promising.
Respondent ID: 30113372 is a representation of a likely profile for a student with no indication of dyslexia whilst Respondent ID: 47218304 may be a typical representation of a student with moderate dyslexia.
Pilot Study Locus of Control Profiles
Data collected from the e-Questionnaire deployed to the research group in the Pilot Study (Dykes, 2008), was coded and analysed using the software application SPSS so that associations between the 5 sub-constructs might be identified. However in order to visualize the results on a respondent-to-respondent basis this innovative 'radar plot' presentation was developed using each of the 5 sub-constructs as an axis to plot the 'scores' generated by each respondent's e-QNR result. In this way, both striking similarities and stark contrasts between profiles were observed which enabled the respondents' profiles to be sorted into distinct groups.
(Control the flow of profiles left-right, fast-slow using the mouse to rollover the left or right edges of the display window)
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