A Pedagogical Shift Needed for Digital Success
Student agency is one of the most powerful improvements that technology can provide. This is the ultimate goal in my opinion, but to begin to set the stage for consistent, effective use a uniform pedagogical shift has to be our focus when it comes to digital learning. The Rigor Relevance Framework provides a solid lens to look at the learning tasks that students are engaged in and redesign them in ways that move away from telling us what they know and instead showing whether or not they actually understand.
This simple, yet powerful shift can be applied to all digital activities. Now I full understand there is a time and place for basic knowledge acquisition and recall, especially at elementary level. However, the goal should be an evolution in pedagogy, especially assessment, where students can demonstrate conceptual mastery in a variety of ways. Instead of using technology to ask students what the capitol is of a state or country ask them to create a brochure using a tool of their choice and explain why the capitol is located where it is. When designing digital learning tasks think about how students can demonstrate understanding aligned to standards by:
It is important to understand that the verbs above should apply to a range of innovative learning activities, not just those involving digital tools. By moving away from the use of technology to support low-level learning tasks we can really begin to unleash it’s potential while providing students with greater relevance through authentic work. This shift will take some time, but the ultimate learning payoff is well worth it. Below are some examples of how my teachers made this shift when I was the principal at New Milford High School:
Lend a critical lens to your digital learning activities to being to develop more activities where students demonstrate what they understand as opposed to what they just know. As pedagogy evolves in step with technology, a key to success will be to ensure that meaningful, high-level, and valuable learning results.
February 27, 2017 at 12:51PM
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A recent article about the use of Googles Cloud Vision API and a series of interactions on our collective Tweeting has provoked some thinking about how technology is potentially going to change the way we carry out learning and assessment even more radically that we think.
The article in Forbes magazine describes how the Googles Cloud Vision tool was tasked with analysing over a quarter of a billion images published by online news outlets from all countries around the world to see what kind of narrative developed. It documented and collated data on faces, people, places, OCR, to name a few, at unprecedented levels and to a degree that would simply not be possible by humans alone. This deep learning analytics process has brought a new visual aspect to the process of analysis and which is different from the normal data based approach.
This story, combined with our conversation this week on the alternative uses of MOOC’s other than for their primary intended purpose (I have a significant bunch of learners on my open course that I am sure are using it to practice their creative English writing skill) leads me to believe that a future in which high functioning learning analytics combined with new forms of continuous, iterative (and perhaps even micro-iterative) assessment could provide us with the ability to use single learning artifacts for multiple purposes and possibly even in combination with ones that have no currently viable connection. It may develop in to a matrix of knowledge and assessment that is so hugely complex that AI’s would simply have to manage all the connections. The plus side though, is that it could result in the creation of specializations and competencies even more vastly different from that which we have today or has been previously posited through the use of technology before.
Engineering and social sciences combinations, geology and human resources, economics and space travel, who knows. The possibilities are probably limitless..
I’m pleased to say that this weeks ethnography piece has been progressing quite well since I made the decision to jump form my original open course on Learing Analytics to the entirely different subject on the power of colour through the Future Learn MOOC platform.
In comparison to the first course the new one on the subject of colour, its interpretation, physical characteristics, the way humans perceive and its application in design and living has been explosive. From the very get-go the subject has fostered a multitude of commentary, feedback and activity beyond just the topic of the programme which has provided a proverbial smorgasbord of ethnographic angles upon which to base this mini study.
Being an intrinsically creative subject the interaction has been expressive and, well, colorful.
What has been especially interesting is that, due to the ethnographic angle I have undertaken with this course, I feel much more the observer than the participant. This is my 10th MOOC and my 6th on Future Learn but never before did I pay much attention to the backgrounds of the participants, the frequency of comments made or the emergence of dominant voices which have the ability to present and lead a topic. Some of Boyd and Ellison’s work as alluded to in Lister (2009) as well as inputs from Baym have provided a unique angle to view the progression of the MOOC from. I found myself particularly enamored with the comment ‘typing oneself into being’!
Another emerging observation is that this MOOC is not necessarily taken by people to learn about the subject it self. Some participants, its appears, are taking the programme to improve their written English, and are using the community aspects to practice presenting questions, responding in kind or trying to develop conversation. How this puts a spin on the use of the OER!
What has also emerged, and what reflects what was highlighted in the Lister reading, is that much like Wikipedia, much of the interaction and commentary is driven by a small number of very active users (the 80/20 rule).
I’ve still not found evidence of any kind of greater community or one that is even emerging but their is mostly certainly evidence of micro-communities who have found common themes upon which to interact.
The study continues….