OLDaily

Learn from machine learning
David Weinberger, Aeon, 2021/11/19

This is a lovely post from David Weinberger that accords almost perfectly with my own thoughts on the matter. I think it represents what will become an emerging (and transformational) consensus. Some excerpts:“In the cry ‘We don’t know how machine learning works!’ we hear that these models do indeed work”; “MLMs work because they’re better at reading the world than we are”; and “Our encounter with MLMs doesn’t deny that there are generalisations, laws or principles. It denies that they are sufficient for understanding what happens in a universe as complex as ours.” Or as I say sometimes: words are too blunt an instrument for managing something so complex as knowledge.

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Teacher Education in the Emergency: a MOOC-Inspired Teacher Professional Development Strategy Grounded in Critical Digital Pedagogy and Pedagogy of Care
Virginia Rodés, Mariana Porta, Lucia Garófalo, Carolina Rodríguez Enríquez, Paperity, 2021/11/19

I found the subject matter of the post more compelling than the presentation (which is written quite passively, often in the subjunctive, and layered deep in theory). It describes the development and delivery of a teacher professional development (TPD) MOOC along the following lines: "The methodology focused on the teachers’ own course redesign, proposing a cycle, based upon a continuous reflection on their practices, addressing the ideation and implementation process that would be involved in the migration from their face-to-face proposals to ERT." Yes, we could talk about care, collaboration and learner-centered design, but to me, the main features of the course were that it was short, tied directly to practice, and based in concepts already familiar to the teachers.

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Web3, Crypto & Learning
Mercedes Bent, 0x11f8…f74281, 2021/11/19

This is part of what we should be expecting in learning technology in the medium to long term future and falls under the heading of what I have been calling 'e-learning 3.0', or 'distributed learning technology'. This article focuses on the crypto side of it. It is one of very few articles out there to use a hash as an address - notice that it works just fine, and you could use the hash to verify the authenticity of the content that I'm delivering to you. The ecosystem it describes includes such components as distributed autonomous organizations (DAO), proofs of skills, career funding, and freelancing.

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EduCOR: An Educational and Career-Oriented Recommendation Ontology
Eleni Ilkou, Hasan Abu-Rasheed, Mohammadreza Tavakoli, Sherzod Hakimov, Gábor Kismihók, Sören Auer, Wolfgang Nejdl, International Semantic Web Conference, 2021/11/19

Why develop yet another recommendation ontology? The authors write, "In the plethora of educational and e-learning ontologies, we find the majority of ontologies in the domain of application or task-specific. Only a small minority were developed to describe the learning domain and learner data " This paper describes the ontology, provides some use case examples, and discusses evaluation. "The ontology is designed to enable learning material repositories to offer learning path recommendations, which correspond to the user’s learning goals, academic and psychological parameters, and the labour-market skills that are achieved from the learning path." Additional resources: video presentation, slides, resource page, ontology page, and Github.

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I don't agree with Cognitive Load Theory (CLT). Here's Why
Terry Freedman, ICT & Computing in Education, 2021/11/19

I solve cryptograms in my head. I think most anyone could, with (perhaps) some instruction and practice. This is only one of the many ways I can manage large quantities of information at the forefront of my thinking, and to me this to me makes a mash of cognitive load theory. I mean, think about it: if cognitive load theory were really a thing, we couldn't perform common tasks with multiple simultaneous inputs, such as driving a car. Terry Freedman offers similar considerations in his expression of doubt bout cognitive load theory. How it came to be a cornerstone of (instructivist) learning theory is a mystery to me.

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Is the ADDIE model outdated or still relevant?
Kris Taylor, TaughtUp, 2021/11/19

Here's a blast from the past. It's the model based on a five-step process for developing learning resources: Analysis, Design, Development, Implementation and Evaluation (ADDIE). "I would not define ADDIE as outdated as it is still the most thoroughly used instructional design process," writes Kris Taylor. This article describes each of the steps in some detail, looks at the strengths and weaknesses of ADDIE, and compares it to the Successive Approximation Model (SAM). "ADDIE has a more structured, waterfall-like modality, which helps ensure all tasks are completed by a specific time, similar to a project management process," writes Taylor, while "SAM allows IDs to conduct multiple phases at once to be more iterative and more agile than ADDIE."

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