How do learning affordances define niches?

A work in progress for the affordance paper.

Introduction

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?

Methods

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.

Results

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

Contributing
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
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
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

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

Sharing
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

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

Managing
system administration and content generation

Learning affordances related with social bookmarking tools at activity patterns

Collecting and storing
searching
searching
searching and collecting information collecting
Searching ideas from internet
Searching images from Internet
collecting
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
Sharing data
Sharing information with interested counterparts
sharing materials
exchanging materials
Taking into use the artifacts of shared learning activity
Sharing information with learners

Tagging
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

Conclusions

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.

seminar: Internet Swarms and Peer production

Today we have in KERG seminar two guests, Petri Kola and Juhana Kokkonen.
Topic is: Internet Swarms and Peer production

Swarm as a structure of very skillful internet users – net natives – who move from service to service using them in a very creative way. Participants have between them lose connections compared to the physical world. Traditionally if you start a volunteer organization officially people first must argue of hierarchy and rules and it slows down the process before anything real happens. In the net it is the opposite – people come together and start to develop some idea and start to put it into action step by step. People are investing a little time to see if the thing goes forward – microtrust, things do not have to succeed.

It is different from common view of web 2.0 users as amateurs, Petri believes the users are more with expertise.

How net is different from physical world?

Our concept of “how internet works” shouldn’t be developed on the basis of metaphors but real research data.

Metaphors can give us totally wrong picture how things are, eg. friction and privacy can be totally different in physical and virtual environment.

Internet happens to be a different kind of beast.

Micro contribution is something that doesn’t exist in physical world.
It is different from traditional participation systems – you can make easily contributions (eg. like in wiki).

Typical life patterns change with micro contributions.

More and more knowledge production is becoming the leading part in creating values and money.
Productivity in cognitive work depends on the right participants and resources meeting together.

Open systems better as information processing systems.

Individual physical differences are not so big as the knowledge work differences between individuals.
Out cognitive ability is different at different times of the day, we are productive when we can choose time and space.

Commons based peer networks: open systems

Compared to hierarchical organizations, it makes a lot of sense to go over organizational borders and give people initiative to choose people to work with and to choose what to do.

Yokshai Benkler: The wealth of networks: how social production transforms markets and freedom (2006).

Essential question: how to combine contributions.

What are the criteria for someone to have the permission to contribute.
In open production model there is no hierarchy about who is more competent. In digital world we have a permanent undo-possibility – if someone contributes what does not fit it can be undone.

Question is how to make difference and separate good and bad contributions.
Community can establish a system where contributions are evaluated.
Contributions can be evaluated by their merit, effect.

There must be some rules:
The rule of neutral point of view: every article should be balanced with point of uses.

Forking makes open virtual immaterial collaboration different from real production.
Community can choose the safe branch and avoid the problematic one.

Forking is an insurance for participants.

How virtual organizing is different?
Organizing to the virtual internet can be differnet from organizing physical reality.

early feedback
do something and evaluate afterwards
emergent rules
unclear borders
focus on action and achievement
short time periods for one goal
rules are more decided on the way
doesn’t look like much effort
doesnt have to succeed
the collaborations do not look like anything
you must be part of it to see the point

In lightweight organizations, if based on volunteer participation, the projects can go to sleeping mode without a problem.

Hacker attitudes from wikipedia, but many of these attitudes seem much in line how participating in swarm.

Produsage= production + usage
If production and consumption cannot be separated, it may change values, it may make to rethink what is the product.

If you are not a contributer now, you are always a potential contributor. A wiki must be constantly monitored all the time to remain the product it is.

stigmery= indirect coordination between agents or actions
It means the way how ants coordinate their action, they change their environment and it changes actions of other sin this environment.

Eric Bonabeau, a complexity theorist and the chief scientist at Icosystem Corporation in Cambridge, Massachusetts. “We’re not used to solving decentralized problems in a decentralized way. ”

Crowds tend to be wise only if individual members act responsibly and make their own decisions. A group won’t be smart if its members imitate one another, slavishly follow fads, or wait for someone to tell them what to do. When a group is being intelligent, whether it’s made up of ants or attorneys, it relies on its members to do their own part.

Karsten Heuer, a wildlife biologist, observed in 2003, when he and his wife, Leanne Allison, followed the vast Porcupine caribou herd (Rangifer tarandus granti) for five months. “It was as though every animal knew what its neighbor was going to do, and the neighbor beside that and beside that. There was no anticipation or reaction. No cause and effect. It just was.”

“In biology, if you look at groups with large numbers, there are very few examples where you have a central agent,” says Vijay Kumar, a professor of mechanical engineering at the University of Pennsylvania. “Everything is very distributed: They don’t all talk to each other. They act on local information. And they’re all anonymous.”

Charles N. Harper: “When ants bring food back to the nest, they lay a pheromone trail that tells other ants to go get more food,” Harper explains. “The pheromone trail gets reinforced every time an ant goes out and comes back, kind of like when you wear a trail in the forest to collect wood. So we developed a program that sends out billions of software ants to find out where the pheromone trails are strongest for our truck routes.”

ecological niche idea is there!

The text is not only content, but it is also a guide for participating in the project. It is both the content and the participation interface put together.

Projects parvi.fi

Tutkimusparvi: people from social media research

Swarm-like education is the model where people will be representing different stakeholders. There will be learning materials like wikibooks. The idea would be start a peer-learning process, where all the diffrenet groups contribute and learn from each other.

Mauri: when does swarm lose being a swarm, are there characteristics of swarminess

Petri: maybe swarm is a phase of getting more organized

Forking ability gives the swarm-quality.

Learning swarm wiki was started.

My reflections:
i think Petri put two different things into one that are not same at phenomenon level – awareness based dynamic small-particle behaviour centred microblogs, and wikis that are more the broad result centred less than identifying the actors.

1. some swarm phenomena in awareness systems are at particle level dynamic and convey short term feedback type of influence to changing of the ecosystem/niches in the sense why and what the others do, that is socio-emotional and task and process (activity) awareness perhaps

2. more artifact-centred wikis are systems where the long-term feedback (the pages) influences the niche more and is of more ecological impact. Focus is on what changed in the environment where the actors are living in. Maybe it is the broad situation awareness?

In embodied simulation there are some aspects from both: picking up and integrating into your action both the other actors as well as the objects (something in text either as traces of action or triggers of meaning building) that might serve as your action triggers.

Two Ed-media08 papers

This year Ed-media 2008 conference takes place in Vienna. Although i am not able to be at EdMedia this year, since i go to iCalt conference, i really regret since there will be a very interesting community meeting.

The Personal Learning Environment PLE issues are discussed at the symposium: How Social is my Personal Learning Environment (PLE)? with the participation of:
1. Sebastian Fiedler
2. Tarmo Toikkanen and Teemu Leinonen
3. Stéphane Sire et al.
4. Liliane Esnault, Denis Gillet and Annick Rossier Morel
5. Colin Milligan
6. Graham Attwell, Margarita Perez Garcia, and Steven Warburton
7. Barbara Kieslinger and Kai Pata
8. Bernadette Charlier and France Henri

Our paper with Barbara Kieslinger is:
Am I alone? The competitive nature of self-reflective activities in groups and individually

Abstract: Although it is not yet common practice, the use of personal learning environments (PLEs) has started to enter formal higher education by a number of early adopters. Some lecturers facilitate their students in making use of social software tools and networked resources for learning activities. In our contribution observations from field research that has been conducted in the context of the European research project iCamp are discussed. On a conceptual level iCamp intends to develop a learning environment design model that provides more autonomy to the learner, in terms of activities tools and resources. In the field trials students were guided towards self-reflection and self-direction activities by making use of their personal learning environments, while at the same time they were prompted to perform collaborative activities in distributed shared learning environments. Thus students and facilitators were challenged by the competitive nature of self-reflection done in single PLEs against the other-directed reflective activities done in distributed shared learning environments. This article elaborates on why collaborative activities might be hindering the individual reflective activities, and how this can be overcome.

Besides symposium, we have another paper where we elaborate the self-directing aspects in social learning environment using the data from the master course of web 2.0 from Tallinn University.

Tammets, K., Väljataga, T., & Pata, K. (2008). Self-directing at social spaces: conceptual framework for course design. Proceedings of Ed-Media 2008. Vienna: AACE, 2008.

Abstract: This paper examines the use of social spaces in order to foster self-directed learning activities in higher educational institutions. It argues that current instructional design models need to be adjusted with respect to self-direction according to the continuously changing processes in post-industrial society. Based on empirical research conducted with master students it attempts to design a conceptual framework for course design with the emphasis on self-direction in social spaces.