interpretation   1238

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How to Learn Stuff | vextro
"My understanding of a workable, comprehensive goal for education, is something that meets and facilities the needs of students. This has to go beyond surmised vocational preparation. Needs is a semantic to soften the core of education: teaching students survival skills. It’s an obvious mistake to treat kids and students like organic computers for information to be punched into. To condescend is to lose their humanity.

What I mean is, how useful will these menus and tables of arranged factoids be under economic collapse? Or maybe our future is positive: how useful will they be under automation? If the signs can be seen it feels imperative that, in whatever way possible, mentors prepare their mentees for times of crisis. And I think the most crucial element of that is reaffirming their value as a person and an individual, by encouraging and thinking through their perspectives as a collaborative effort. Though not to complicate this rhetoric anymore: anti-capitalist education is anti-hierarchical education.

Honestly I felt a vision of what edutainment together was like playing Learn 100 Words: One at a Time! It’s a deceptively simple game, made for a deviously indulgent glorioustrainwreck’s challenge to make a hundred games. So a microgame per word; play goes rapidfire through a collection of microgames, with various styles of play: quizzes, platformers, find-an-object, each based on vocabulary someone (probably) doesn’t know. It’s good natured and very goofy. Some microgames are obviously jokes, but others are very in earnest, and are surprisingly entertaining!

Lean 100 Words is made in Clickteam software (as GT games often are) and I don’t know what version, or what parts come from official asset packs, but I do recognize the buoyant, iconic clipart-esque sprites. Backgrounds are dark, hard gradients, with chunky buttons, reminiscent of web 1.0 or even a Vasily Zotov game. A wall of retro-futuristic, full bodied synth sounds greet on start up. All of the UX has a pleasant shape and exaggerated proportions, which gets me nostalgic for edutainment games of my childhood, and more oddly, the various online classes I’ve taken in my life.

I think it’s the hardest I’ve laughed at a game in a long time too. The game’s tone is just so innocuous from the get. Like the first word (when playing alphabetically instead of randomly) is aal, and I was like, that’s a word? That’s not a word… is this game about made up words? It is a word though, it’s a really technical term that I don’t really understand. But it’s a word! The hint is, “I couldn’t find a textbook definition,” so I slowly scrolled around and eventually clicked on a textbook, and completed the game. Close enough to the real definition? Honestly, sure!

Whether it’s intentional, or a happy accident of trying to do a lot with whatever means, Learn 100 Words is a genuinely hilarious parody of edutainment games. Instrumental to this are voiceovers done by the developer of every word and accompanied hint. They’re off the cuff, not really rehearsed."

"In Learn 100 Words it’s feels fine to hear misspeak, it’s fine for hints to be somewhat mistaken, or trail off, lose their thread, because it still comes back to learning 100 words. The goofs put me at ease, like, I don’t feel self-conscious about the stuff I don’t know. This is a big contrast to the real methodical approach for a standard edutainment game, games that fuss over whether its textbook blocks are working. No matter how vibrant a game like that manages to be, it’s still cut up by a very rigid, very institution-minded push for absolute legibility. A vague, palpable desperation could be felt over their needy hope that this information is getting through to my swiss cheese brain. In other words, capitalist about its use, and condescending.

Further, Learn 100 Words doesn’t shy from expressing poetic game design, like the former microgame for abaton. Maybe the most successful “mnemonics” are associations formed by emotional impact. Getting someone to care is an obvious step to engagement, but there’s a tendency to overthink, overpolish what generates care. There’s something about candidly, simply, presenting ideas, with personality. Concepts are expressive vehicles and are sometimes better expressed by individualistic interpretations.

I don’t think the process to genuine retention, learning, growing, can be calculated. In my lifetime effective education came from mentors who felt invested in my development and were willing to learn with me. I don’t think there’s a combination of software or even other programs that will magically work. Curriculum, which edutainment is, should be about creating environments that can facilitate positive relationships, that can generate a mutual investment in growth.

The coldness of profit extraction will tinge and undermine self-determination. I remember most of the silly, complicated words I learned from playing Learn 100 Words, while I’ve absolutely struggled through other language software (some from my youth, some from the now). My point isn’t that games need to “learn” from this and try to imitate a casual friendliness, it’s that compassion is done, not imitated."
via:tealtan  games  videogames  seriousgames  gaming  play  edutainment  2017  leeroylewin  sfsh  howwelearn  education  capitalism  self-determination  tcsnmy  compassion  relationships  mentorship  howweteach  curriculum  growth  environment  interpretation  engagement  emotion  learning  humanity  automation  hierarchy  horizontality  microgames 
2 days ago by robertogreco
A Dirty Dozen: Twelve Common Metric Interpretation Pitfalls in Online Controlled Experiments

Online controlled experiments (e.g., A/B tests) are now regularly used to guide product development and accelerate innovation in software. Product ideas are evaluated as scientific hypotheses, and tested in web sites, mobile applications, desktop applications, services, and operating systems. One of the key challenges for organizations that run controlled experiments is to come up with the right set of metrics. Having good metrics, however, is not enough. In our experience of running thousands of experiments with many teams across Microsoft, we observed again and again how incorrect interpretations of metric movements may lead to wrong conclusions about the experiment’s outcome, which if deployed could hurt the business by millions of dollars. Inspired by Steven Goodman’s twelve p-value misconceptions [4], in this paper, we share twelve common metric interpretation pitfalls which we observed repeatedly in our experiments. We illustrate each pitfall with a puzzling example from a real experiment, and describe processes, metric design principles, and guidelines that can be used to detect and avoid the pitfall. With this paper, we aim to increase the experimenters’ awareness of metric interpretation issues, leading to improved quality and trustworthiness of experiment results and better data-driven decisions.
a/b  blogged  metric  interpretation 
17 days ago by aguecheek
i would take the ‘not critical enough’ gesture in a different direction. That is, the prevalent historical interpretive discourse persists in treating the most recent historical interpretations as self-evidently ‘true’ or ‘correct’. But if we have any historical awareness at all, we recognise that today’s self-evidently true conclusions are tomorrow’s risibly out-dated error. The biblical interpretation indistry invests contemporary historical discernment with an authority incommensurate with its inevitable transience. Miracle stories may be accurate or not, but the restless necessity that interpretive judgement keep changing is a matter that any casual observer can verify.
bible  interpretation 
19 days ago by ayjay
How to Use t-SNE Effectively
Great explanation of t-SNE and the pitfalls on interpreting t-SNE visualizations. Also shows what happens at different values of perplexity.
visualization  tsne  machinelearning  dimensions  perplexity  dimensionalityreduction  pitfalls  interpretation 
20 days ago by drmeme
[1602.07043] Auditing Black-box Models for Indirect Influence
"Data-trained predictive models see widespread use, but for the most part they are used as black boxes which output a prediction or score. It is therefore hard to acquire a deeper understanding of model behavior, and in particular how different features influence the model prediction. This is important when interpreting the behavior of complex models, or asserting that certain problematic attributes (like race or gender) are not unduly influencing decisions.
In this paper, we present a technique for auditing black-box models, which lets us study the extent to which existing models take advantage of particular features in the dataset, without knowing how the models work. Our work focuses on the problem of indirect influence: how some features might indirectly influence outcomes via other, related features. As a result, we can find attribute influences even in cases where, upon further direct examination of the model, the attribute is not referred to by the model at all.
Our approach does not require the black-box model to be retrained. This is important if (for example) the model is only accessible via an API, and contrasts our work with other methods that investigate feature influence like feature selection. We present experimental evidence for the effectiveness of our procedure using a variety of publicly available datasets and models. We also validate our procedure using techniques from interpretable learning and feature selection, as well as against other black-box auditing procedures."
papers  machine-learning  black-box  interpretation 
6 weeks ago by arsyed
[1708.00049] Interpretable Active Learning
"Active learning has long been a topic of study in machine learning. However, as increasingly complex and opaque models have become standard practice, the process of active learning, too, has become more opaque. There has been little investigation into interpreting what specific trends and patterns an active learning strategy may be exploring. This work expands on the Local Interpretable Model-agnostic Explanations framework (LIME) to provide explanations for active learning recommendations. We demonstrate how LIME can be used to generate locally faithful explanations for an active learning strategy, and how these explanations can be used to understand how different models and datasets explore a problem space over time. In order to quantify the per-subgroup differences in how an active learning strategy queries spatial regions, we introduce a notion of uncertainty bias (based on disparate impact) to measure the discrepancy in the confidence for a model's predictions between one subgroup and another. Using the uncertainty bias measure, we show that our query explanations accurately reflect the subgroup focus of the active learning queries, allowing for an interpretable explanation of what is being learned as points with similar sources of uncertainty have their uncertainty bias resolved. We demonstrate that this technique can be applied to track uncertainty bias over user-defined clusters or automatically generated clusters based on the source of uncertainty."
papers  active-learning  interpretation 
6 weeks ago by arsyed
'Don't take the Bible literally' says scholar who brought to light earliest Latin analysis of the Gospels
"There's been an assumption that it's a literal record of truth - a lot of the early scholars got very worried about inconsistencies between Matthew and Luke, for example.

"But for people teaching the Bible in the fourth century, it's not the literal meaning which is important, it's how it's read allegorically".....

The work is thought to have been copied out by a scholar in around 800, more than 400 years after the original was written.

Dr Houghton said the book was an “extraordinary find”. It predates better-known writings by famous scholars including St Jerome,
conclusion07  bible  interpretation 
7 weeks ago by berendes
Notes + Links / Casey A. Gollan — At once something like scales fell from the eyes....
"At once something like scales fell from the eyes. All at once something like scales fell from the eyes. Immediately something like scales fell from the eyes. Immediately something like fish scales fell from the eyes. And immediately something like scales fell from the eyes. And immediately some things that were like scales fell from the eyes. And immediately there fell from the eyes as it had been scales. And immediately there fell from the eyes as it were scales. And immediately there fell from the eyes as it had been scales. And immediately there fell from the eyes something like scales. And straightway there fell from the eyes as it were scales. Instantly something like scales fell from the eyes. Instantly there dropped from the eyes what seemed to be scales."
translation  interpretation  bible 
8 weeks ago by robertogreco
J.M. COETZEE - On the Edge of Revelation (Robert Musil)
Musil maintained
a lifelong reserve toward Freud, whom he regarded as fundamentally mistaken in assuming
that the unconscious, the repressed irrational, or what Musil preferred to call,
more vaguely, "the other condition," is accessible to the language of rationality
interpretation  literature  freud  musil 
9 weeks ago by jomc

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