Learning with collectives
These notes are part of a series for the book.
Outline
- Different meanings of collective
- Defining the collective
- Collectives as technologies
- Some corollaries of the collective
- Stigmergic collectives
- Non-stigmergic collectives
- Cooperative freedoms in collective learning
- Transactional distance in collectives
- Examples of collectives
- Dangers of the collective
- Design principles for collective applications
- Conclusion
Notes
Collectives are not people, but the aggregate of their actions. For example, a collective happens when people vote. Another example is the ranking aspect in search engines when the rank is based on the number of links that go to each webpage. In technology, collectives involve people’s actions plus algorithms to aggregate and make sense of the data from their actions. The result is displayed to people in a way that may influence their decisions or actions.
See also: I think there may be some interesting overlap between collectives and Andriessen’s (2005) taxonomy of communities.
Stigmergy and the Matthew Effect
Stigmergy is when a social group responds to a stimulus in such a way that their individual actions are coordinated. For example, Amazon’s product pages show the overall rating customers have given different products. Products that have more individual ratings are viewed by more people as a result, highly-rated items get even more high ratings.
The effect of following the actions of others (seen in “following” and “trending” features in social media, for example) can have good or bad results. One thing that can improve these systems is to not show up-to-the-minute results.
Stigmergic collectives can be affected by the Matthew Effect. This effect is named after Matthew 13:12 (‘Whoever has will be given more, and he will have an abundance. Whoever does not have, even what he has will be taken from him.’ — More or less, this is “the rich get richer…” or “nothing succeeds like success”.) Already-popular sites, products, etc., get more hits, which results in being even more popular, and so on.
Examples of collective features
These are collective features in common websites:
- Rating features: Facebook likes, Slashdot karma points, Amazon customer ratings, LinkedIn endorsements. ‘Even a simple rating system of “thumbs-up” or page view counters can tell a learner his or her work is valued. However, this is not particularly rich feedback, serving a motivational purpose more than offering guidance. Moreover, in some cases this can be demotivating, if it is viewed by the learner as an extrinsic reward’ (Dron and Anderson, 2014, p. 218).
- Filters: Recommender systems at Amazon and Netflix
- Analytics: Google Scholar citation data
- “Heat map” features that show popularity of articles or resources
- Network discovery: LinkedIn, Facebook, and Twitter all have “people you may know” or “people you may want to follow” features, which are derived from various data points
- Crowdsource tools: Quora, Yahoo Answers and other sites where people come together to solve a problem or answer a question
- Scheduling software: Can be an example of a collective, much in the way voting mechanisms are because they ‘allow an individual to specify a list of possible dates and others to indicate their availability’ (Dron and Anderson, 2014, p. 219).
Learning with collectives
In learning situations, collectives have a role that is similar to teachers. ‘The collective, as an emergent entity composed of a collection of people in sets, nets, and occasionally groups, plays the role of a teacher in a learning transaction, guiding, suggesting, collecting, clustering, and re-presenting the knowledge of the crowd’ (Dron and Anderson, 2014, p. 212). This can be a two-way interaction. For example, we “teach” the Netflix recommender system about what types of movies we want to be shown, based on our viewing habits.
For learners, collective tools allow them to find resources and also critically consider the usefulness of the resources they find.
Teaching with collectives
Good idea: One way to design learning courses to make use of collectives is to have learners create collections of resources. This increases learner sense of ownership and encourages their active reflection and participation. It also yields a broad range of current and useful resources, keeping the course content up-to-date at a lower cost. ‘It is best if such systems include at least some form of collective ranking, so that students can vote resources up or down, or provide implicit recommendations by clicking on links’ (Dron and Anderson, 2014, p. 223).
Problems
Collectives take on the problems of the social forms using them. They can enhance the tendency to have echo chambers. People can try to game the system, and other people will be skeptical of collectives because this sometimes happens. When used for learning, collectives can provide too much distraction from the original learning intent.