It is now recognised that the original dichotomy of Digital Natives (referring mainly the younger generation) versus Digital Immigrants (referring to older users), as postulated by M. Prenski back in 2001 (1) as a way to classify digital capabilities including the use of Social Media is now seen as too stereotypical as it fails to account for unique personal and professional preferences and experiences of the normal user.
In order to reflect the more transient nature of technology competencies Donna Lanclos and David White (2) propose a model described as (Digital) Visitors versus (Digital) Residents thus adding more subtlety to the level of human engagement with different types of technologies.
Based on this concept many graphical representation of such V&R maps (3) have been created with the aim of aligning particular (learning) technologies within a particular institutional context; for examples see https://www.flickr.com/photos/jiscinfonet/sets/72157641903755433/
Recently a further adaptation has been put forward by James Clay (4) by mapping various learning tools and technologies across two dimensions, with one axis for mode of delivery (broadcasting versus engaging/interactive) and the second axis for informal versus formal teaching.
Fig. 1: A sketch of such an array is shown opposite illustrating the more traditional modes of teaching and learning (taken from reference 4).
In order to create such diagrams in a digital format a MS Excel Macro called Perceptual Maps for Marketing has been used to input and visualise such type of data.
The positional co-ordinates are entered in an Excel spreadsheet using a 2d table format encompassing up to 25 different variables (in this case learning tools); the data is visualised as bubbles and updated in real-time.
The static image can then be grabbed from Excel and embedded into a document for publication, as shown below (fig. 2).
Fig. 2 . A screenshot of an early brainstorming session using the default colour scheme.
In order to enhance these infographics further a ‘third’ dimension may be overlaid by manually colour-coding the bubbles according to certain desired parameters.
Figures 3-5 exemplify how this may be achieved based on different parameters.
Fig. 3. Mapping in the ‘third’ dimension using the parameter Mode of learning
Fig. 4: Mapping in the ‘third’ dimension using the parameter Target learner
Fig. 5: Mapping in the ‘third’ dimension using the parameter Institutional service provision
Whilst it needs to be recognised that the data entered is derived from an individual perspective it is nevertheless noteworthy that certain trends can be detected as exemplified in figures 3 and 5 where a colour pattern appears across the four sectors, with clustering of related items observed in the bottom left and top right sectors.
This exercise would lend itself for an activity as part of a staff development session whereby relevant aspects may be considered, debated and then disseminated.
It may provide a useful guide on how to effectively embed relevant technologies within the curriculum of study to enhance the student learning experience.
1. M. Prenksy (2001) http://www.marcprensky.com/writing/Prensky%20-%20Digital%20Natives,%20Digital%20Immigrants%20-%20Part1.pdf (last accessed: 9 Feb. 2016)
2. D. White (2013) http://daveowhite.com/vandr/ (last accessed: 9 Feb. 2016)
3. V&R Mapping: http://daveowhite.com/vandr/vr-mapping/ (last accessed: 9 Feb. 2016)
4. J. Clay (2015) http://elearningstuff.net/2016/01/14/mapping-the-learning-and-teaching/ (last accessed: 9 Feb. 2016)
5. Perceptual Maps for Marketing: http://www.perceptualmaps.com/
Acknowledgements: I am grateful to R. Payne for pointing out the usefulness of Perceptional Maps for this exercise