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001 1-4 Identify Filters

Page history last edited by Wilma Clark 13 years, 11 months ago

SELF-MANAGED LEARNING IN OUT-OF-SCHOOL CONTEXTS


[Study Home]  [Study Phase One]  [Study Phase Two]  [Study Phase Three]


[1.1] [1.2] [1.3] [1.4] [1.5] [1.6] [1.7]


 

1.4 Identify Filters

 

In this step, we draw on the same set of data generated by the initial focus of attention to identify elements which might limit or constrain a learner's access to the forms of assistance identified at (1.1) brainstorming and further categorised at (1.3) categorisation.

 

In step 1.3 for example, we suggested that those data depicted in data sample 1.3.1 represented not only potential resources to support the learner but also potential filters which might have implications for the ways in which the learner was able to access these potential resources. These included notions of access, utility, space (proximity, distance, overcrowding, etc.), rules of use/access, ambiance (light, dark, rainy), tactility of materials, learner motivation for interaction/engagement with their environment and available resources, seating arrangements, comfort and direction of movement and access, subtitling, signing for deaf visitors, use of visual/interactive displays and exhibits, etc.

 

These constraints and affordances are described as Filter Elements in the EoR Model and Design Framework. They may have positive and/or negative characteristics. For example, a limitation may produce a more focused selection of available technologies, e.g. where quality of image is important and lighting is low and the technology to be used has no flash facility. Filters might also be generated by rules of context. For example, in the Planetarium visitors are not permitted to take photographs (it would disturb other members of the audience and reduce their enjoyment of a show) or to make audio recordings (there would be a breach of copyright). In preliminary explorations of the learner's contexts, i.e. at the brainstorming and categorisation stage, it may not be easy to identify appropriate filters due to the complexity of available resources. If this is the case, then the focus of attention may be more narrowly focused from those already identified. For example, in this present case, we might select the knowledge category of "astronomy". In an ad hoc conversation between one of the learners and the researcher, the learner who instigated the trip demonstrated an interest in learning more about The Milky Way. Her interest was stimulated by two things: (1) a Planetarium show on The Night Sky; and (2) a documentary film in the exhibits area of the Planetarium section of the Royal Observatory.

 

We might then re-elaborate the ZAA framed at step 2 (specifying focus of attention) as follows:

 

Category Elements Data Filter Elements
Knowledge Astronomy The Milky Way, the Universe, Galaxies, Stars, Planets, Black Holes
Environment Planetarium, Planetarium Learning Workshops, Planetarium shop, Exhibits hall Location, time, accessibility, space and layout, money, availability, ambiance
Resources (People) Learners, learning mentors, peers, researcher, Planetarium show narrator, museum guides, Planetarium shop assistants, other museum staff, other learners/visitors Relationships, accessibility, time, location, existing knowledge, environment, confidence, opportunity, group/ community/public rules
Resources (Tools) Interactive exhibits, simulators, digital displays, digital information, video clips, video screens, voiceovers, touchscreen displays, audio commentaries, mobile phone, batteries, memory card, voice recorder, digital still image camera, digital video camera, combined still image/video camera, mp3 player, books, posters, models Connectivity, Planetarium rules, copyright, energy/power, storage capacity, learner skills and knowledge, availability, quality.

 

In this example, we have further sub-divided the Resources category element into People and Tools to facilitate identification of filters.

 

The example reflects a particular learner’s desire to learn more about the Milky Way. She has attended the Planetarium Show where she learned about the Milky Way as part of that particular scheduled show. However, she was not able to capture additional data about the show and had to rely on memory. This resource was filtered by time (show times, length of narrative/visuals about Milky Way) and rules (no audio recording or photography allowed). The EoR Model and Design framework can be used to ascertain other means of overcoming these filters (time, rules) and to highlight alternative opportunities for the learner to support her learning about the Milky Way. For example, sensors could be developed which ‘push’ information to learners’ mobile phones at various locations or the learner could opt to receive additional digital information about specific knowledge concepts, e.g. the Milky Way, via Bluetooth to their mobile phone. Or, facilities could be made available for learner's to dialogue with experts at the Planetarium both in situ or after they have returned home.

 

In the above example, it becomes clear that resources can also be filters, e.g. the Milky Way is both a resource (knowledge concept) and a filter (of the knowledge domain of astronomy), a learner’s mobile phone can be both a resource (to capture data) and a filter (of light in a darkened room), and the Planetarium show narrator is both a resource (narrating) and a filter (managing the environment).

 

We have looked at the category elements Knowledge, Environment and Resources and the filter elements which might impact on their availability to the learner. Up to this point, these have all been explicitly EXTERNAL elements. In the next step, we look at (1.5) resources and/or filters that the learner may bring to the situation, i.e. the learner's "internal" resources (cognitive, experiential, psychological, emotional, etc.).

 

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