Another thought provoking thread on machine personalized learning from Ben Williamson
Tag: Personalised Learning
Can the technologies automating jobs also help workers learn the skills they’ll need to find new work in the changing economy? This AI learning startup thinks so.
The idea of AI tracking every movement in education and providing for our next step is an interesting proposition. I am just concerned why ethics comes after the supposed solution:
“Our goal is to build an ethics review board that has teeth, is diverse in both gender and background but also in thought and belief structures. The idea is to have our ethics review panel ensure we’re building things ethically,” Talebi said.
What happens if the ethics board says the whole thing is unethical?
Personally, I am left wondering if the supposed personalized ‘results’ are worth the reward? There is talk of scraping even more data:
Going forward, Ahura hopes to add to its suite of biometric data capture by including things like pupil dilation and facial flushing, heart rate, sleep patterns, or whatever else may give their system an edge in improving learning outcomes.
Next we will be measuring the pupils of every staff member to maximise market gains? Is this what education is for?
The challenge, I think, is to express to readers this drudgery not only in contrast to the fantasies of shiny and efficient teaching machines – stories about robot teachers or otherwise – but also as the same sort of drudgery that today’s ed-tech dictates. Calling it “personalized learning” doesn’t make today’s computer-based instruction any more exciting. I promise you.
During the plenary session I was asked by a delegate to explain the difference between ‘personal learning’ and ‘personalised learning’. I explained by pointing out the marvellous structure of the
Jerónimos Monastery, just across the road from the conference centre. Having visited there previously, I could see a useful analogy. Personal learning, I explained, is walking across the road and doing an ad hoc tour of the buildings and artefacts to see what I could learn about the history and culture of Jerónimos Hiring a personal guide who knows a lot more about the history and culture of the place, and touring it with him/her would be personalised learning. I would be scaffolded in my discovery of the place, and I might learn a little more than if I simply wandered around on my own.
Steve Wheeler differentiates between personal and personalised learning. This is different to Graham Wegner’s discussion of personalised versus personalized learning.
I love Parkruns with other folks and I love running and cycling on my own; each has its own merits and issues. One of the strands which emerged in my study was that both planned, formal experiences and less formal, unstructured experiences each have their place. Some people might prefer one over the other, some find value in both. There are valid reasons why sometimes everyone needs to be following the same programme at the same time. However, teachers learning through Twitter clearly gain a great deal from being able to choose paths which address their individual needs and suit their contexts. Perhaps they are flâneurs/flâneuses? Perhaps we could be taking the best from both worlds?
Ian, your discussion of the benefits of formal and informal reminds me of Graham Wegner’s discussion of personalised versus personalized. It has me thinking though that where there are two options we can have a tendency to alienate one of them. I am subsequently rethinking this and the benefits of different options.
“Teachers were overwhelmed and their stress levels skyrocketed. Data about student outcomes is useful, but it should be kept in the classroom. It should not be about clicking thousands of boxes. Data needs to help us inform teaching decisions, not determine them.” Correna Haythorpe
This is a reminder of the dependencies involved in the move to such things as ‘personalised Learning’. Whether it be clear progressions or concensus, much of these decisions undermine any notion of agency and again focus on ‘learnification‘.
There are three points about the risks of what ISTE deployed at their conference to know: (1) the ‘smart badge’ is a really effective locator beacon, transmitting signals that are trivial to intercept and read, (2) you can’t turn it off, and (3) most people I spoke to had no idea how it worked. (I freaked out more than a few people by telling them what their badge number was by reading it from my phone. Most of those incidents ended up with ‘smart badges’ being removed and destroyed.)
Doug Levin reflects on the introduction of ‘smart badges’ at ISTE. Really just a Bluetooth tracking device that then allowed vendors (and anyone for that matter) to collect data on attendees. Levin hacked a badge to unpacking their use. He explains that with little effort they could be used by anybody to track somebody:
Downloading a free mobile app, as I did, an attacker could easily track a specific badge and be notified when it goes out of or comes into range. With little technical skill, an attacker could use it to approach someone outside of the convention center (at a bar or restaurant or tourist attraction) and by employing social engineering techniques attempt to gain their trust. I myself was able to identify that there were over a dozen ISTE conference participants on my train platform on Wednesday morning bound for Chicago O’Hare. When one ISTE participant entered my train car at a later stop, that was trivial to identify. While there were no other ISTE participants on my flight back to the DC area, I located two badges in the baggage claim area (likely packed in someone’s luggage or carry-on).
Audrey Watters suggests that, “ISTE has helped here to normalize surveillance as part of the ed-tech experience. She suggests that it is only time that this results in abuse. Mike Crowley wonders why in a post-GDPR world attendees are not asked for consent? If this is the future, then maybe Levin’s ‘must-have’ guide will be an important read for everyone.
Researchers have begun to propose using genetic data from students to personalize education. Bringing genetics into education is highly controversial. It raises significant concerns about biological discrimination and rekindles long debates about eugenics and the genetic inheritance of intelligence.
Precision education represents a shift from the collection of assessment-type data about educational outcomes, to the generation of data about the intimate interior details of students’ genetic make-up, their psychological characteristics, and their neural functioning.
Ben Williamson breaks down the idea of precision through the use of data and how it might apply to education.
Current understandings of human nature and human learning suggest that human beings are differently talented (Gardner, 1983, 2006) and have different desires and interests (Reiss, 2000, 2004). Thanks to the diversity in the environment in which they are born, humans also have different experiences that interact with their natural talents and interests to give each person a unique, jagged profile of abilities and desires, stronger in some areas and weaker in others (Ridley, 2003; Rose, 2016). In other words, everyone has a handsome leg and, at the same time, a deformed leg.
This is the introduction to Yong Zhao’s new book Reach for Greatness: Personalizable Education for All. It continues some of the ideas Rose discussed in his book, The End of Average. However, on first glance it seems to overlook other aspects to education, such as society.
One quote that caught my attention was the association between experiences and greatness:
experiences have costs and risks. Every experience requires time, and some require money and extra effort. Thus, adults want every activity their children experience to be positive, to lead to some desirable outcome. They don’t want their children to waste their time, energy, or money, or worse, to have experiences that may have a negative impact. Responsible adults naturally have a tendency to prescribe experiences for children. The result is that many children are allowed to have only experiences deemed to be beneficial and safe by adults.
I think that this is where the difference between individual and society stands out, in that you cannot have people achieving their own sense of greatness if the access to experiences is not equitable. This was not something discussed in a recent debate on the ABC around private vs. public education.
I am also intrigued by the link with Wagner’s work too, and am interested in its association with the wider discourse around personalization and how this differs from ‘personalised’ learning.
PersonaliSed learning for me involves student choice, students helping define the direction of the learning and students showcasing their learning in ways that are personal. Education technology’s role in this scenario is an enabler allowing the student access to information that they want, connection to resources and people that can help them in that learning and to create their own solution / product / showcase. PersonaliZed learning wants the technology to be in control, pushing or elevating the student through pre-determined content and concepts – Khan Academy without the choice is what springs into my head. Like you point out, the Z version promises what the s version has been shown to be capable of but reduces it all down to (in your words) “various modular ‘fun’ activities under the trending veneer of gamification.”
So what do we do? Educate ourselves. Follow critical educators on Twitter, read books that expose corporate interests, and support the work of people like Audrey Watters who act as independent journalists.
Another thought provoking read Benjamin. I really like your call for people to educate. I am also intrigued by your four filters:
- Funding
- Expertise
- Ideology
- Flak
I think that they provide a useful framework to get started. I just wonder about the entry point for many teachers who are already a part of the ‘learning machine’? I agree about supporting those like Watters and mobilising. I wonder if this is a part of what Howard Stevenson and Alison Gilliland describe as a ‘democratic professionalism’.
My question and concern is whether a structural systemic knowledge is enough? I really like Ben Williamson’s approach focusing on the assemblage:
In this broad sense, a data assemblage includes: (1) particular modes of thinking, theories and ideologies; (2) forms of knowledge such as manuals and textbooks; (3) financial aspects such as business models, investment and philanthropy; (4) the political economy of government policy; (5) the materiality of computers, networks, databases and analytics software packages; (6) specific skilled practices, techniques and behaviours of data scientists; (7) organizations and institutions that collect, broker or use data; (8) particular sites, locations and spaces; and (9) marketplaces for data, its derivative products, its analysts and its software.source
An example of this is his work around ClassDojo. What I think is useful about this approach is that it incorporates skills into the wider critical discussion. For me, that is a part of my interest in Google’s GSuite. That is also, in part, what drives me to do my ‘eLearn Update’ newsletter. I just wonder if there is a limit to dialogue from the outside?
Apologies if this is a complete misreading Benjamin.