I would like to propose two new terms – Network Based Training (NBT – an evolution from the WBT which followed from the CBT) and Network Led Training (NLT – an evolution from Instructor Led Training/ILTs). I would like to focus on the network nature of these terms rather than the training connotation in the light of the discussion we are having around Connectivism, especially around groups and networks.
Let me define Network based training as a framework for sense making for the autonomous learner that leverages the principles of network learning and Network led training as concerted efforts by a learning formation (defined as a range in the continuum between groups and networks or connectives & collectives) to facilitate and drive learning initiatives across the formation.
- Traditional training (read WBTs and ILTs) has long depended upon structure, control, unity, instructor/teacher/instructional designer primacy and cohesion. Network based and Network led training emphasize open, non-linear, participative, emergent, diverse and autonomous learning.
- Traditional training has focussed on specific formats, styles and design methodologies for the development of training. NBTs and NLTs focus on harvesting connective knowledge across a variety of very fluid formats and styles of contributors and enabling continuous extension & expansion of this knowledge.
- Traditional training is focused on deterministic attempts to achieve predefined learning outcomes. NBTs and NLTs focus on ability and capacity of the learner to adapt to fast changing conditions recognizing sensitive dependence on initial conditions and on an overall end-goal rather than on predefined outcomes.
Traditional training, if designed and implemented effectively, has some key benefits.
- Firstly, effective training content provides a format for content that is the result of a lot of effort around presentation of key concepts using visualization, language and instructional techniques. These are not skills that the average blogger has, for example. This is key because language and visualization can make the difference between obscurity and meaning.
- Secondly, traditional training content makes some definite assumptions about the state of knowledge and characteristics of the learner that provides a plateau from which the learner can ascend. This helps in situating the difficulty and complexity of the learning itself for the learner.
- Thirdly, traditional training is able to provide a pathway or guidance (even if in a very limited manner, cost of development is a big consideration here) to the learner and possible framework for sense making that is (however) distilled from an expert.
- Fourthly, there are a large number of interactive lecture delivery techniques, gaming & simulation led techniques and visualization techniques that have been extremely effective. As of now, I am not able to situate these within connectivist-speak and relate them to network learning. But I am convinced that these are too important to be left out of the discourse.
- Fifthly, there is a mechanism for evaluation that is critical to quantize for network learning. Without it, connectivist approaches could well become infructuous in a wide variety of training administration contexts, something that should never happen.
These benefits directly impact the learning experience in terms of available time, level of comprehension of materials, ability to navigate complex content etc. which are key experience factors in today’s fast moving information environment.
If we look at material covered in the first week of the course, it seems much more intelligible now than previously, not because it was not articulated well enough in this instance, but because a whole lot of us had to negotiate several plateaus in between through collaborative activities given that we were standing on different plateaus when we started. The instructors modelled and demonstrated while we learners reflected and practiced.
However, the sequence of week wise topics is just one single pathway that learning designers could have taken. The learning ecology that was created and extended was just one example. The content itself is not exactly conducive to meet the constraints of time, though (and availability of time is also a variant across participants) and this is a challenge, at least for me.
The design of NBTs and NLTs then have to be situated in principles of network learning but cannot ignore key benefits of effective traditional training materials and delivery techniques.
What would be key factors in the design of such NBTs, NLTs. A lot has been said on the learning ecology (e.g. learnscapes), learning technology (Web 2.0), connection forming & social network analytics among other ideas and all seems extremely useful. I think there are some more factors that deserve attention.
- Firstly, we should look at the concept of distributed, associative knowledge and learning as the network metaphors to see what representations could, at a network level, be found suitable to identify (say) learning how to fly a plane or (say) what is Paris. An example could be a concept map.
- Secondly, we should look at the individual “dot” in the pattern more closely. By this I mean to focus on how information or knowledge contained in the constituents of a pattern (which are by themselves patterns) can be represented.
- Thirdly, we should try and see how these patterns could be published as well as accessed when we want to at an individual level. I see this as problems with technology (e.g. authoring tools that generate high quality animations are few and restricted) and communication strategy/design (e.g. awareness about how to write a blog post so that it communicates what you really want to communicate), both of which are critical if we are to learn or teach.
- Fourthly, the similarities between patterns and the relationships between them together become important tools for the educators. Concepts could be taught/learnt using similar learning patterns (e.g. an astronomical phenomenon of a particular arrangement of stars that looks like a kite – one learning pattern that looks like another – I learn the same way he learns) or by using similar & related domain/knowledge patterns (e.g. I learn how to write a recursion based program in BASIC using a pattern of how it was done in C++).