How do learning affordances define niches?

May 22, 2008

A work in progress for the affordance paper.


An affordance term is used for signifying the intermediate constructs that emerge dynamically in the activities what people perform with certain objectives while using the environment as a mediator for these activities. Affordances indicate the certain dimension of the environment that learners actualize as the mediator of specific activities. Affordances also constrain the certain range of possible activities that would be considered in this environment. Therefore affordance definitions usually contain activity verbs, actors and object properties from the environment. The two components – the emerging activity objectives, and the certain aspects in the environment as the mediators of actions simultaneously influence, which affordances will be actualized.

One of the hypotheses is that the emergence of affordances may at some cases be triggered more by the environement side, and at other cases more by the activity planning side.

At an environment side the environment is the niche that forms through the uncoordinated action of many individuals. At action side, each individual performs coordinated actions and influences the niche. These both sides of the ecosystem are interrelated, the individual ‘particle’ level state creates feedback to the environment that in large scale causes the emergence of another ‘whole’ state of the niche. The whole state serves as the activity system, constraining the actions for each individual.

The learner’s choice of affordances at their activity- and landscape descriptions enables to investigate how some social media tools are perceived and actualized as learning mediators more at particle level, while others are perceived as obtaining the learning affordances at the whole activity system level.

The questions in interest were:
1. Which are the learning affordances that learners evoke when using certain social media tools?
2. Do learners perceive the overlapping learning affordances when using different social media tools?
3. Does the description type (activity description or learning landscape description) actualize different sets of learning affordances?
4. Do learners evoke different learning affordances with individual and collaborative learning activity and learning landscape descriptions?


For the data analysis the visual and narrative, data collected from the master level students participating at the course ‘Self-directed learning with web 2.0 tools‘, was used. The students composed personal learning environments from web 2.0 tools and described these, composing learning landscape schemes. They also draw activity patterns to describe activities at their personal learning landscapes. Several of the landscape and activity pattern descriptions were composed for collaborative groups. Each figure was accompanied by narrative descriptions mentioning several learning affordances in relation with the tools the student(s) used for activities and for constructing distributed learning landscapes.

The analysis of 63 activity- and learning landscape descriptions was conducted. From the figures and from the narratives the learning affordances were collected and categorised. The categorization scheme separated each affordance according to its belonging to: a) activity scheme or learning landscape scheme, and b) individual or collaborative learning activity. The relationship of the learning affordance with the tool(s) was categorised using binary system. The main tool categories were: blog, wiki, chat tools (MSN, Skype, Gabbly), email, search engines, RSS aggregator, social bookmarking tools, forums, co-writing tools (eg. zoho or google documents), co-drawing tools (eg. Vyew, Gliffy), and social repositories Flickr and Youtube. These were selected because these tools were mostly in use by the students during the course and they also appeared at their schemes frequently.

Analytically, ANOVA , Cross tabulation and Chi square anlaysis were used as primary methods to show if there was a difference in the distribution of learning affordances in different settings: wholistic and collaborative emergence level, and particular and individual emergence level.

These data reflect specifically the learning affordance perception of the students of the course (beginner users of web 2.0 tools), and cannot be broadened to the perception of learning affordances of the active web 2.0 users in various settings.

The learning affordances were categorized into specific types representing similar affordances: assembling, managing, creating, reading, presenting, changing and adding, collaborating and communicating, sharing, exchanging, searching, filtering and mashing, collecting, storing, tagging, reflecting and argumenting, monitoring, giving tasks and supporting, asking and giving-getting feedback, and evaluating. These types were taken from the main verbs the students tended to use in their learning affordances.

Factor analysis was used to indicate how certain learning affordance categories are related with certain tools. Cross tabulation shows the overlap of some tools on the basis of learning affordances.

The frequency of learning affordance categories was found for each tool both in case of activity and landscape descriptions. Each learning affordance eg. searching was considered as a variable defining the niche. Niches have been defined as the environmental gradients with certain ecological amplitude, where the ecological optimum marks the gradient peaks where the organisms are most abundant. In all activity/landscape descriptions the optimum for certain learning affordance category was calculated dividing the frequency of this affordance per certain tool to the total frequency of certain learning affordance category for all tools.


Factor analysis related certain tool types with certain learning affordance categories.

Factor analysis indicated that learners relate certain affordances with certain tools. 13 factors, describing 60 % of the system, were identified:

1. searching with search engine
2. collecting and sharing in social repositories (flickr, youtube)
3. collaborating, communicating and exchanging with email and chat
4. collecting, tagging and storing with social bookmarking tool
5. finding, filtering and mashing and monitoring with aggregator
6. collaborating and communicating with collaborative publishing tools (wiki, zoho and google documents, View and forums)
7. presenting, reflecting and monitoring with co-drawing tools (Vyew, Gliffy)
8. giving tasks, asking and supporting with blog
9. changing, adding, collaborating and communicating and sharing with co-drawing tools (View, Gliffy)
10. creating, assembling and reflecting with co-drawing tools (View, Gliffy)
11. managing, collecting and monitoring with blog
12. assembling and evaluating with blog
13. reading and reflecting with forum and blog

Learners perceived that several tools have overlapping affordances and can be used simultaneously or together when solving certain pedagogical aims.

The findings of ANOVA analysis (see Table 1) indicate that learners perceived the affordances differently if they focused on the activity side or if they focused on the learning landscape (tool) side when describing self-directed and collaborative learning. When learners described learning landscapes they actualized more learning affordances of social bookmarking and co-drawing tools than they did at their activity descriptions. The learning affordances related to blog, wiki, and forum usage were more frequently mentioned in case of activity descriptions compared to learning landscapes.

There was no significant difference between affordance distribution in case of individual and collaborative diagrams of activities and learning landscapes using ANOVA analysis. The ANOVA analysis indicated that in the activities with social media, the learners did not make significant differences between how they actualized affordances when learning individually with the teacher, and when participating in the group learning situations.

The cross tabulation and Chi square analysis of the distribution of the learning affordances related to activity and landscape descriptions in case of individual and group learning situations (see Table 2) demonstrated that some tendencies, indicating the different frequency of affordances similarly like in ANOVA analysis (see Table 1), were present both at individual and collaborative descriptions. For example both in individual and collaborative learning cases the learning affordances using aggregator and co-drawing tools were mentioned more frequently in case of landscapes compared with activity descriptions.

The difference between individual and collaborative distribution of affordances in landscape and activity descriptions was found in case of using social bookmarks and search engines. It was found that there were significantly more than expected affordances related to using social bookmarking tools at collaborative landscapes, and the number of affordances related to using search engines was larger at individual activity descriptions. Significantly more learning affordances were related to individual activity descriptions and blog and wiki usage. The last finding seems to be related to the activities of the course and maybe is not so general. The students of the course did individual assignments in blogs, commented each other’s blogs and worked collaboratively with wiki tool.

The cross tabulation and Chi square analysis of the distribution of the learning affordances related to individual and group learning situations in case of landscape and activity descriptions (see Table 3) indicated that search engine usage is clearly related with individual activity descriptions, while chat and aggregator-related learning affordances have been used at collaborative landscapes.

The same tendency was not apparent in case of the descriptions of collaborative learning. When describing learning affordances of collaborative landscapes the social bookmarking tool was noted significantly more than expected compared with collaborative activities.

The following figures 1 and 2 demonstrate two different niche landscapes.

Figure 1. The niche landscape of learning affordance types presented at activity descriptions

Figure 2. The niche landscape of learning affordance types presented at learning landscape descriptions

Figures 3 and 4 present learning affordance niches for the activity and landscape descriptions

Figure 3. Niche landscape from activity descriptions.

Figure 4. Niche landscape from learning landscape descriptions.

The following example presents the clear qualitative difference of learning affordances of social bookmarking tool in learning landscape and activity descriptions. The former indicates recognized new social activities and related affordances, the latter is more old-fashioned and individual centred.

Learning affordances from landscape descriptions related with social bookmarks

Advancing the software
Adding resources to the landscape
Increasing affordances
Student can change and add materials

Collecting and storing
Finding information
Searching information
Searching information
Searching information
Adding links
Important bookmarks can be collected
Links to the learning materials
Adding bookmarks
Adding necessary information
Saving information
Saving information
Collecting private bookmarks
Collecting artifacts

Tagging artifacts
Social tagging of presentations
Social tagging of feeds
Community based tagging
Social tagging
Social tagging
Social tagging of videos
Social tagging of feed channels
Adding tags for remembering important links

Filtering information
Access through tags
Receiving information for learning from different sources
Information feed to demonstrate presentations
sorting tools for oneself
searching tools with tags
receiving information
Showing tagged information feeds

tagged bookmarks can be pulled together
information feeds from links go automatically to aggregator
Pulling information feeds

Using shared resources
Sharing artifacts
Sharing with peer students
Public usage of bookmarks
Sharing presentations
Sharing information tag-based
sharing tags and impressions
sharing bookmarks

Asynchronous learning
synchronous learning
simultaneous work with team members
Working jointly
communication with team members
viewing bookmarks collaboratively for learning

system administration and content generation

Learning affordances related with social bookmarking tools at activity patterns

Collecting and storing
searching and collecting information collecting
Searching ideas from internet
Searching images from Internet
collecting information feeds
collecting links
adding links
adding links
saving the bookmarks of materials
saving data
saving the results
Saving information
Saving information
Saving materials
Saving information and artifacts

Sharing data
Sharing information with interested counterparts
sharing materials
exchanging materials
Taking into use the artifacts of shared learning activity
Sharing information with learners

Student gets familiar with tags
Student searches bookmarks with tags
adding tags to texts
Tagging important information
Tagging important posts
Tagging information
saving bookmarks with tags
choosing bookmarks with searching tags
Marking important information obtained from blogs
Connecting information data and artifacts

Individual assignments
Student starts solving the task
Reading written information
Student gets the answer
Students communicates with peer learners and finds new information
tutor gets overview of the study topics


These results suggest that some old tools (search engines) and new social tools (eg. blog, wiki) are perceived more as meditors for individual actions, while other social tools eg. aggregators and social bookmarking tools seem to be perceived more as collaborative scenes for ‘produsage’.

Final words

In general these results seem to be supporting my initial hypothesis that the perception of learning affordances of different social media tools is not happening with the same mechanism if we plan activities and if we think where we conduct these activities. These results are even more notable because students’ task was to present in parallel their learning landscape and an activity pattern at the same learning landscape.

This rises another question, whether the niches in web 2.0 environments arise with different affordance perception mechanisms (basically, are there two ends of one dimension?) – some because of particle level affordance perception that is related more to highlighting personal actions, and another due to highlighting the collaborative broad ‘produsage’ scene perception.



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