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Analytics: Understanding Soft vs Hard Learning Technologies
- 4. 2000s - social navigation, collective intelligence, crowd wisdom, controllable environments (e.g. Dwellings)
- 8. to help teachers know how learners are doing
- 9. to help learners know how they are doing
- 10. to help learners decide what to do next
- 11. to tell learners what to do next
- 35. to help teachers know how learners are doing
- 36. to help learners know how they are doing
- 37. to help learners decide what to do next
- 48. Softness increases the adjacent possible. Hardness increases efficiency and reduces error ( if we automated the right things)
- 49. Soft is hard and hard is easy - we need both
- 50. We need control over amount of hardness in all our technologies
- 51. Assemblies can give the best of both worlds
Notes de l'éditeur
- or, as McLuhan put it, we shape our tools and they shape us. If digital literacies are a phantom, fuzzy, moving target, then how about looking at how technologies themselves are constructed so that we can master them, rather than being mastered by them?
- I’ve been trying to discover ways that individual actions in a crowd can be used to help individuals in the crowd to learn better since late 1990s. CoFIND captured implicit and explicit traces of activities - clicks, frequencies, tags, pedagogical metadata known as qualities, bookmarks, to reveal exposed and transient user model. Explicitly self-organising through evolutionary and stigmergic mechanisms. Dwellings used dynamics of cities to self-organise - a cross between a MUD and a wiki, inhabitants moved avatars on sidewalks and built dwellings (content) - left footprints, many social navigation signs, evolutionary struggle between streets and dwellings. Moved on to more controllable technologies like Elgg. Now I’m exploring the other parts of a social system to discover the processes that are not programmed - pedagogies, processes, methods, intellectual tools, etc...
- groups - traditional fare of teaching like classes etc nets - connected people, looser, cannot see whole, only local connections sets - about counting people and their actions, anonymous, sending messages to anyone/everyone, using aggregates, averages (e.g. classroom show of hands)
- a stick is not a technology - it becomes one when we add processes to utilise its properties for a purpose. Technologies are not just tools and are not necessarily physical. e.g. manufacturing processes, organisational systems, pedagogies, writing, language itself (invented, constantly changing, not just about communication but enabling richer thought in itself)
- all, or almost all, technologies are assemblies ref W Brian Arthur Technologies are assemblies. As a species we learned to use the things around us to build other things. Language was probably the best invention for that as it let us build ideas upon ideas - conceptual structures that themselves could be used to build bigger, better structures but we see the pattern in all technologies. We use technologies to make technologies and assemble, disassemble and reassemble constantly and continuously. The more we create, the more we are able to create. But sometimes we create technologies that make things easier at the cost of inflexibility. Factories, rigid processes, mass production methods, rules, laws.
- always an assembly. all parts can be hard or soft but many are nothing to do with an external object or device.
- ref Terry Anderson. actually a process of coevolution. The soft parts interact with the hard parts, which interact with each other. But it is the soft processes that drive change and evolution
- Kauffman, in Investigations, talks of complex adaptive systems as increasing the adjacent possible - each change opens up opportunities for new change. Franklin (The Real World of Technology) calls such technologies ‘holistic’, comparing them with prescriptive technologies, which limit us as humans - mainly automation
- hard technologies, that Franklin calls prescriptive, reduce our ability to be creative. But they increase efficiency, reduce error, make things simpler and can sometimes open up new adjacent possibles themselves - a lunar orbiter, for instance, is a pretty hard technology without which we couldn’t go to the moon
- Soft as in malleable vs soft as in non mechanized - following Don Norman rather than literature on technologies in business Hard as in inflexible vs hard as in solid.
- hard technologies reduce our choices, automate, simplify, speed things up, make things cheaper, reduce opportunity for error. But the cost is creativity and flexibility.
- Softer technologies increase the adjacent possible by enabling and/or making more likely new choices to be made. More choices come at a price - we have to make them. That is one thing that makes them difficult or hard.
- By thinking of pedagogies as technologies we can ask questions about compatibility and how they interact with other technologies. May more importantly, we can see them as mechanisms that coevolve with other technologies, what terry calls the dance between technology and pedagogy. It is not a dance but a growing together. Different generations of pedagogy and other teahcing machinery have coevolved. Until machines for communication were cheap and ubiquitous, constricitivist approaches were marginal. Connectivism is all about networked people and stuff they create and consume. Behaviourist
- By thinking of pedagogies as technologies we can ask questions about compatibility and how they interact with other technologies. May more importantly, we can see them as mechanisms that coevolve with other technologies, what terry calls the dance between technology and pedagogy. It is not a dance but a growing together. Different generations of pedagogy and other teahcing machinery have coevolved. Until machines for communication were cheap and ubiquitous, constricitivist approaches were marginal. Connectivism is all about networked people and stuff they create and consume. Behaviourist
- By thinking of pedagogies as technologies we can ask questions about compatibility and how they interact with other technologies. May more importantly, we can see them as mechanisms that coevolve with other technologies, what terry calls the dance between technology and pedagogy. It is not a dance but a growing together. Different generations of pedagogy and other teahcing machinery have coevolved. Until machines for communication were cheap and ubiquitous, constricitivist approaches were marginal. Connectivism is all about networked people and stuff they create and consume. Behaviourist
- By thinking of pedagogies as technologies we can ask questions about compatibility and how they interact with other technologies. May more importantly, we can see them as mechanisms that coevolve with other technologies, what terry calls the dance between technology and pedagogy. It is not a dance but a growing together. Different generations of pedagogy and other teahcing machinery have coevolved. Until machines for communication were cheap and ubiquitous, constricitivist approaches were marginal. Connectivism is all about networked people and stuff they create and consume. Behaviourist
- By thinking of pedagogies as technologies we can ask questions about compatibility and how they interact with other technologies. May more importantly, we can see them as mechanisms that coevolve with other technologies, what terry calls the dance between technology and pedagogy. It is not a dance but a growing together. Different generations of pedagogy and other teahcing machinery have coevolved. Until machines for communication were cheap and ubiquitous, constricitivist approaches were marginal. Connectivism is all about networked people and stuff they create and consume. Behaviourist
- a move from harder to softer technologies, but there is a twist - it all depends up your point of view
- A technology that is soft for one person may be a set of chains for another. Computers are the softest machines ever invented, perhaps (language may be a contender), but only for those who use them to create other machines or who use the machines they embody to gain flexibility. For a clerk in a store operating a cash register, the opposite may be true: 'the computer says no' is the punchline of a great series of sketches on British TV but is a ubiquitous feature of life - most of us are victims most days of a machine limiting what someone can do to help us.
- Softer technologies increase the adjacent possible by enabling and/or making more likely new choices to be made. More choices come at a price - we have to make them. That is one thing that makes them difficult or hard.
- automation makes it quicker, more efficient, simpler to do things. It does so by reducing choices.
- So, back to our model, the human element is strong when we use information from analytics to make changes. The more the system itself contributes, the less control is given to humans.
- Buster Keaton being chased by mob - mob stupidity concern for the engine, not the people heath robinson (like Rube Goldberg) - pointless machines schoolroom mentality - not for the learner If we feed back the wrong thing, our systems will reinforce stupidity. We need to know what we are collecting and how it will affect behaviour. The harder the system, the greater the risks
- But, sometimes hard is the right thing. We want the best of all worlds.
- The landing is a tool to extend the adjacent possible. It moves control to the individual and the group. It has many tools that can be combined and recombined in many ways. It is a virtual velcro to pull people and things together. But it is a very soft technology and so makes some things harder. We are seeking ways to harden the soft by seeking feedback and ideas as well as observation. But the big dream is to put the hardening in the hands of the people. Eg context switcher.
- you can modify but it is better to use larger scale object to build assemblies. Assemblies can both soften and harden. If a system doesn’t do what you want, add a bit - that increases the adjacent possible. But what you add can also incorporate hardness. So - can use soft analytics to assemble the right things, hard analytics as a component to help guide when needed.