OLDaily

Bruno Latour
Olga Ioannou, connecting data to information to knowledge, 2018/10/29

This is a nice two-minute journey through the thought of Bruno Latour, a French philosopher, anthropologist and sociologist who argued that scientific facts are the result of social construction in a network of scientific dialogue, instrumentation and institutions. "Day-to-day research — what he termed science in the making — appeared not so much as a stepwise progression toward rational truth as a disorderly mass of stray observations, inconclusive results and fledgling explanations" ... which is a pretty good description of my own work. Latour was also instrumental in the development of Actor-Network Theory (ANT) whereby "a scientific instrument, a scrap of paper, a photograph, a bacterial culture — could acquire enormous power because of the complicated network of other items, known as actors, that were mobilized around it."

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Here's What I Covered In My 4 DevLearn Presentations
Mel Milloway, Blog, 2018/10/29

Mel Milloway had a pretty busy conference. In his first session he has "the audience go through my Is It Edible? activity and guess what JavaScript was used." Thast's a nice way to do a "how do do it with Javacript" session. The second presentation showed "research on Design Systems and .. my own system for learning experiences." The third showcased "a game based xAPI enabled project" - you can play the game and see your statements coming in live via an embed on a blog post. Awesome. The final talk presented a "mock VR retail scenario that captures xAPI data." (p.s. check out the tab of this article when you move to another tab - there a lovely script that changes the title and icon to "Please don't go".)

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Towards Better Frameworks for Social Media Data Archiving
Axel Bruns, Snurblog, 2018/10/29

Snurblog summarizes a number of presentations from the recent iCS Symposium on Challenges to Studying Disinformation, including this keynote from Katrin Weller. It addresses some of the challenges in collectiong and sharing data from social media platforms. Successful data sharing "depends on sufficient answers to three critical perspectives: methodological, legal, and ethical. Researchers did not share datasets because of legal uncertainty, because they knew they had broken some platform rules in gathering their own datasets, or because they could not find a workable balance between scientific benefit and potential legal risks." P.S. while Katrin Weller discusses the difficulty of accessing social media data the vast bulk of her considerable output is locked behind subscription paywalls, so I can't read it.

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Learner Model's Utilization in the e-Learning Environments
Vija Vigale, Laila Niedrite, University of Latvia, 2018/10/29

This is quite a good paper describing the need for, creation of, and use of a learner model in support of adaptive learning. In current systems, the learner model is at the core of such systems. In conjunction with a domain mode, which maps the learning required in a field, the adaptive system employs an adaptive model to generate the activity, resource or intervention required. Learner data can be static or dynamic, includes personal data, pedagogic, preference, system experience, cognitive, history, interests and assessment data.The article details a number of learner model (LM) construction techniques. methods, and systems used for LM techniques. This is good technical stuff clearly written and accessible to most readers. Via e-learning , conocimiento en red.

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