1,294 Matching Annotations
  1. Last 7 days
    1. gram matrix must be normalized by dividing each element by the total number of elements in the matrix.

      true, after downsampling your gradient will get smaller on later layers

  2. Oct 2019
    1. Coming back to Rhizomatic Learning, I am therefore left mulling over how +dave cormier has successfully ‘managed the MOOC’. I must be honest that the word ‘manage’ may be slightly misleading, inferring incorrectly a sense of power and control, I think that instead what the course has done is instigate learning throughout. In some respect this has now been coordinated by everyone, although Dave has ‘set’ the tasks and facilitated the communications and conversations. However, as was demonstrated by +Mariana Funes‘ post, much was left to the community to continue the learning.

      On Dave Cormier and Rhizomatic Learning

    1. The vertical bar on the letter T represents the depth of related skills and expertise in a single field, whereas the horizontal bar is the ability to collaborate across disciplines with experts in other areas and to apply knowledge in areas of expertise other than one's own.

      T shaped knowledge

  3. Sep 2019
    1. One of the most useful features in Xcode is the Filename search. You can open it with the keyboard shortcut Shift + Command + O.

      Found what I was looking for to jump to file in Xcode

    1. Think-pair-share

      They're used to death, but for good reason. There are few things better than a good TPS for getting students warmed up for discussion. One can even allow the TPS to inform the entire lesson: if the TPS results in a class-generated set of questions or learning objectives, teach from that, or plan to teach from it in the next class session.

    1. The confidence of knowing that once something is added to Anki it won't be forgotten is intoxicating

      Intoxicating

    2. And for the last three years, I've added EVERYTHING to Anki. Bash aliases, IDE Shortcuts, programming APIs, documentation, design patterns, etc. Having done that, I wouldn't recommend adding EVERYTHING

      Put just the relevant information into Anki

    3. Habit: Whenever I search StackOverflow, I'll immediately create a flashcard of my question and the answer(s) into Anki.

      Example habit to make a flashcard

    4. Anki seems more common among software engineers
    5. Engineers are creatures of habit. Make reviewing your flashcard app your first work task (or the train, the toilet right before Candy Crush). Stop StackOverflowing "how do i amend my git commit" five times every month.

      Spaced repetition is a solution to googling 5 times a month the same thing

    6. Outside of medical students and language learning apps like Duolingo, spaced repetition isn't common. It's not as cool as cramming, but it works. Medical students use it to memorize those awful thousand page textbooks. Duolingo uses it because it's effective

      The most popular appliers of spaced repetition:

      1. Medical students
      2. Duolingo users
    7. But Why Option 3?

      Why spaced repetition is superior to cramming (reviewing just a week before the exam):

      1. Cramming rarely works after it passes from short-term memory. How many cram sessions do you remember from high school?
      2. Evenly spaced reminders sort-of works, but you'd have to review all your knowledge at every interval, which doesn't sound scalable/fun/have a social life.
      3. Our brains work best with exponentially spaced reminders.
    8. Spaced repetition is a remembering technique that will remind you concepts at spaced intervals to maximize memory retention efficiently

      Spaced repetition Spaced repetition

    9. Kyle had a super hero ability. Photographic memory in API syntax and documentation. I wanted that and I was jealous. My career was stuck and something needed to change. And so I began a dedicated journey into spaced repetition. Every day for three years, I spent one to three hours in spaced repetition

      Spaced repetition as a tool for photographic memory in API syntax and documentation

    1. “I think SM is only good for a small minority of learners. But they will probably value it very much.”

      I totally agree with it

    2. “Anki is a tool and SuperMemo is a lifestyle.”

      Anki vs SuperMemo

    3. Using either SRS has already given you a huge edge over not using any SRS: No SRS: 70 hours Anki: 10 hours SuperMemo: 6 hours The difference between using any SRS (whether it’s Anki or SM) and not using is huge, but the difference between Anki or SM is not

      It doesn't matter as much which SRS you're using. It's most important to use one of them at least

    4. A: Read an article from start to finish. ONLY THEN do you import parts into Anki for remembering B: Incremental Reading: interleaving between reading and remembering

      Two algorithms (A and B) for studying

    5. in SM, learning and remembering are blended into one: you read (learn) and review (remember) at the same time. Incremental Reading is essentially “spaced repetition-ing” your reading

      Super Memo combines learning + remembering

    6. In Anki, you are only doing the remembering part. You are not reading anything new in Anki

      Anki is for remembering

    7. Learning = reading and understanding new things Remembering = memorizing what you learned

      Learning vs remembering

    1. At the moment, GPT-2 uses a binary search algorithm, which means that its output can be considered a ‘true’ set of rules. If OpenAI is right, it could eventually generate a Turing complete program, a self-improving machine that can learn (and then improve) itself from the data it encounters. And that would make OpenAI a threat to IBM’s own goals of machine learning and AI, as it could essentially make better than even humans the best possible model that the future machines can use to improve their systems. However, there’s a catch: not just any new AI will do, but a specific type; one that uses deep learning to learn the rules, algorithms, and data necessary to run the machine to any given level of AI.

      This is a machine generated response in 2019. We are clearly closer than most people realize to machines that can can pass a text-based Turing Test.

    1. Supporting Personalised Learning Frequently mentioned throughout the interviews was the goal of allowing learners to explore their personal interests, culture and social context through assessment. Several participants sought to design assessment that allowed learners to tap into these aspects of their personal lives. Where learners could exercise choice and pursue projects of personal interest, a greater sense of ownership was observed. James commented that “they love the idea that they are in control of what they do”, when given more choice around assessment. Other participants suggested it was possible to have learners working on projects that could benefit their personal lives or professional trajectories as part of formal coursework. In her final assignment, Olivia provides the learners “absolute free reign in terms of what kind of a thing they produced.” Learners use their creative interests to develop resources for the course, as Olivia reflects “some opted for essays still, but other students created digital timelines, infographics, podcasts, comic books, videos.” Personalisation of assessment was suggested to allow learners to represent and situate themselves authentically and creatively through their work.

      Giving learners more autonomy in their learning is a great pedagogical principle, and in the context of the article focusing on learning design, I can see how this fits with "open" as it does require that the course design needs to be more "open" as in flexible to allow for this kind of learner autonomy. There is overlap here between authentic learning and open pedagogy.

    1. you don’t have to learn alone. In fact, it is the uniqueness of the people with which you learn and the discussions you have together that make what you learn unforgettable

      Team work applies also into learning

    2. being able to communicate what you’ve learned is one of the main skills that differentiates a good developer from a great one (IMHO).

      Know how to explain what you just learned

    3. When facing procrastination, think of process over product. I often procrastinate when I’m overwhelmed by the thought, “Ok, I have to get X done”. Instead, it can be beneficial to think, “Ok, I will spend an hour on X” — which isn’t overwhelming, doesn’t require a long breakdown of tasks, and gets me started (90% of the battle)

      Solution to procrastination

    4. Know when to apply a particular concept is as important as knowing how.

      Use cases are more important than we think of

    5. Spread it out over many sessions and over many different modes of learning.

      Don't learn everything in a single session!

    6. test yourself as you’re encountering new material. Recall is a simple example of this mini-testing.

      Recall = mini-testing

    7. taking a couple minutes to summarize or recall material you are trying to learn

      It's worth to take the time to ponder

    8. Recently, I found this great application called Highly (you should use this!). They make it really simple to highlight any article that I’m reading on the web using a Chrome extension.

      This inspired me to make a research of similar applications (such as Liner), and finally end up with hypothes.is

    9. Highlighting or underlining are also techniques that often lead to this illusion of learning. On the other hand, brief notes that summarize keys concepts are much more effective.

      Indeed… Therefore, let's leave a note here :)

    10. First, survey and priming — this involves scanning a book or the syllabus of a course, for example, to get a general idea of the bigger picture. Second, observe an example. Then, do it yourself. And, finally, do it again and again in different contexts.

      Chunk the knowledge

    11. take breaks, meditate, think about other things, and give yourself plenty of time in both modes.

      Give yourself some free time while learning

    1. many instructional designers and others adjacent to the field have responded swiftly with critiques that range from outright rejection of the term, to general skepticism about the concept, to distrust for its advocates and their support of learning analytics and outcomes-based learning.

      Why the rejection of the term? Is it too mechanical?

    1. Because documentation of student learning impacts may not reflect the core objectives of all CTLs — and because this investigation is resource-intensive

      Measuring impact of on student learning outcomes is resource-intensive. This makes me think of the Tracer project.

    1. Deep Learning for Search - teaches you how to leverage neural networks, NLP, and deep learning techniques to improve search performance. (2019) Relevant Search: with applications for Solr and Elasticsearch - demystifies relevance work. Using Elasticsearch, it teaches you how to return engaging search results to your users, helping you understand and leverage the internals of Lucene-based search engines. (2016)
    2. Elasticsearch with Machine Learning (English translation) by Kunihiko Kido Recommender System with Mahout and Elasticsearch
    1. moderating discussion forums

      I don't know if I would consider this a routine task considering the amount of facilitation a good discussion often requires. Perhaps moderating a forum related to routine support questions where the questions might be "when is my term paper due", or "how do I access the course syllabus" could be routine posts in a discussion forum. But when you get into forums where learner discourse is key to the learning process, the moderating is not routine, or that moderating is even the right word to use to frame those discussions as these types of discussion forums often require a facilitator, not a moderator.

    1. Since all neurons in a single depth slice share the same parameters, the forward pass in each depth slice of the convolutional layer can be computed as a convolution of the neuron's weights with the input volume.[nb 2] Therefore, it is common to refer to the sets of weights as a filter (or a kernel), which is convolved with the input. The result of this convolution is an activation map, and the set of activation maps for each different filter are stacked together along the depth dimension to produce the output volume. Parameter sharing contributes to the translation invariance of the CNN architecture. Sometimes, the parameter sharing assumption may not make sense. This is especially the case when the input images to a CNN have some specific centered structure; for which we expect completely different features to be learned on different spatial locations. One practical example is when the inputs are faces that have been centered in the image: we might expect different eye-specific or hair-specific features to be learned in different parts of the image. In that case it is common to relax the parameter sharing scheme, and instead simply call the layer a "locally connected layer".

      important terms you hear repeatedly great visuals and graphics @https://distill.pub/2018/building-blocks/

    1. Here's a playground were you can select different kernel matrices and see how they effect the original image or build your own kernel. You can also upload your own image or use live video if your browser supports it. blurbottom sobelcustomembossidentityleft sobeloutlineright sobelsharpentop sobel The sharpen kernel emphasizes differences in adjacent pixel values. This makes the image look more vivid. The blur kernel de-emphasizes differences in adjacent pixel values. The emboss kernel (similar to the sobel kernel and sometimes referred to mean the same) givens the illusion of depth by emphasizing the differences of pixels in a given direction. In this case, in a direction along a line from the top left to the bottom right. The indentity kernel leaves the image unchanged. How boring! The custom kernel is whatever you make it.

      I'm all about my custom kernels!

    1. We developed a new metric, UAR, which compares the robustness of a model against an attack to adversarial training against that attack. Adversarial training is a strong defense that uses knowledge of an adversary by training on adversarially attacked images[3]To compute UAR, we average the accuracy of the defense across multiple distortion sizes and normalize by the performance of an adversarially trained model; a precise definition is in our paper. . A UAR score near 100 against an unforeseen adversarial attack implies performance comparable to a defense with prior knowledge of the attack, making this a challenging objective.

      @metric

  4. Aug 2019
    1. And they have largely moved beyond the mental model of universal design (UD) in the physical environment, which is static, bounded, and predictable—instead designing interactions according to UDL, which sees interactions as dynamic, open, and emergent.

      Really interesting point here about the limit of the "curb cut" metaphor.

    1. The goal is to build a better web thanks to the contribution and collaboration of a diverse set of personalities and thinkers: visual learners; physical learners; social learners; and everyone in-between.
    2. Though the web has evolved, its methods for training future web developers have not. Sure, the resources are more attractive now. They’re better written and more easily findable. But they continue to be geared toward a very narrow kind of person. They’re generally online, self-guided, impersonal, and novice-unfriendly.
    1. HTM and SDR's - part of how the brain implements intelligence.

      "In this first introductory episode of HTM School, Matt Taylor, Numenta's Open Source Flag-Bearer, walks you through the high-level theory of Hierarchical Temporal Memory in less than 15 minutes."

    1. Using multiple copies of a neuron in different places is the neural network equivalent of using functions. Because there is less to learn, the model learns more quickly and learns a better model. This technique – the technical name for it is ‘weight tying’ – is essential to the phenomenal results we’ve recently seen from deep learning.

      This parameter sharing allows CNNs, for example, to need much less params/weights than Fully Connected NNs.

    2. The known connection between geometry, logic, topology, and functional programming suggests that the connections between representations and types may be of fundamental significance.

      Examples for each?

    3. Representations are Types With every layer, neural networks transform data, molding it into a form that makes their task easier to do. We call these transformed versions of data “representations.” Representations correspond to types.

      Interesting.

      Like a Queue Type represents a FIFO flow and a Stack a FILO flow, where the space we transformed is the operation space of the type (eg a Queue has a folded operation space compared to an Array)

      Just free styling here...

    4. In this view, the representations narrative in deep learning corresponds to type theory in functional programming. It sees deep learning as the junction of two fields we already know to be incredibly rich. What we find, seems so beautiful to me, feels so natural, that the mathematician in me could believe it to be something fundamental about reality.

      compositional deep learning

    5. Appendix: Functional Names of Common Layers Deep Learning Name Functional Name Learned Vector Constant Embedding Layer List Indexing Encoding RNN Fold Generating RNN Unfold General RNN Accumulating Map Bidirectional RNN Zipped Left/Right Accumulating Maps Conv Layer “Window Map” TreeNet Catamorphism Inverse TreeNet Anamorphism

      👌translation. I like to think about embeddings as List lookups

    1. As log-bilinear regression model for unsupervised learning of word representations, it combines the features of two model families, namely the global matrix factorization and local context window methods

      What does "log-bilinear regression" mean exactly?

    1. The reward system in the brain can be triggered by the anticipation of all kinds of rewards, from points or praise.

      This is interesting. The reward system is triggered by the anticipation of the reward, not the actual reward itself.

    1. Retrieval practice boosts learning by pulling information out of students’ heads (by responding to a brief writing prompt, for example), rather than cramming information into their heads (by lecturing at students, for example). In the classroom, retrieval practice can take many forms, including a quick no-stakes quiz. When students are asked to retrieve new information, they don’t just show what they know, they solidify and expand it. Feedback boosts learning by revealing to students what they know and what they don’t know. At the same time, this increases students’ metacognition — their understanding about their own learning progress. Spaced practice boosts learning by spreading lessons and retrieval opportunities out over time so that new knowledge and skills are not crammed in all at once. By returning to content every so often, students’ knowledge has time to be consolidated and then refreshed. Interleaving — or practicing a mix of skills (such as doing addition, subtraction, multiplication, and division problems all in one sitting) — boosts learning by encouraging connections between and discrimination among closely related topics. Interleaving sometimes slows students’ initial learning of a concept, but it leads to greater retention and learning over time.

      How can I build this into my curriculum?

    1. Genus Species + Species Hybrids Example

      Great examples of remixes in the real world

    2. Lessig (2005) provides a range of examples of the kinds of digital remix practices that in his view constitute “the more interesting ways [to write]” for young people. These include remixing clips from movies to create “faux” trailers for hypothetical movies; setting remixed movie trailers to remixed music of choice that is synchronized to the visual action; recording a series of anime cartoons and then video-editing them in synchrony with a popular music track; mixing “found” images with original images in order to express a theme or idea (with or without text added); and mixing images, animations and texts to create cartoons or satirical posters (including political cartoons and animations), to name just a few types. We accept this conceptual extension of “writing” to include practices of producing, exchanging and negotiating digitally remixed texts, which may employ a single medium or may be multimedia remixes. (We also recognize as forms of remix various practices that do not necessarily involve digitally remixing sound, image and animation, such as paper-based forms of fanfiction writing and fan-producing manga art and comics, which continue to go on alongside their hugely subscribed digital variants.

      There are all very good examples. The great thing is, that as a language teacher there are so many different types of media that the students can really hone in on their interests.

    3. where someone creates a cultural product by mixing meaningful elements together (e.g., ideas from different people with ideas of one’s own), and then someone else comes along and remixes this cultural artefact with others to create yet another artefact.

      I think this could be fun to with students in Spanish. I can introduce music, poems, art and have students remix them.

  5. Jul 2019
    1. Communities of practice are one of the ways in which experiential learning, social constructivism, and connectivism can be combined, illustrating the limitations of trying to rigidly classify learning theories. Practice tends to be more complex.
      • Constructivism - roots in the philosophical and psychological viewpoints of this century, specially Piaget, Bruner and Goodman. Learning occurs when the mind filters inputs from the world to produce its unique reality. The mind is believed to be the source of all meaning, direct experiences with the environment are considered critical. It crosses both categories by emphasizing the interaction between learner and the real world.

      • Social constructivism would emphasize critical experiences between the learner and other learners and mentors.

      • Connectivism is the integration of principles explored by chaos, network, complexity and self-organization theory. A lot of the content is now offloaded to the machine that was previously residing within the learner.

    1. Open learning, also known as open education

      requires a open, sharing, collaborative environment. Promotes pedagogical dialogue. OER have potential to transcend "geographic, economic, or language barriers". Also, OER strengthens digital literacy.

    2. e-purpose.

      Creative Commons covers 4 areas of practice: -re-use: right to verbatim reuse content

      • revise: right to change/ modify the content -remix: right to combine original or revised with new content -redistribute: right to make and share copies of content

      great for expanding, exploring, sharing and remixing content in the educational world.

    3. free to use and access, and to re-purpose.

      open learning is influential in areas of design, practice, pedagogy, and theory in education. Open Education Resources at the K-12 level are fundamental to OL.

    4. Open learning

      defined as "set of practices, resources, and scholarship that are open to the public and that are accessible, free to use and access, and re-purpose"

    1. We will discuss classification in the context of supportclassificationvector machines

      SVMs aren't used that much in practice anymore. It's more of an academic fling, because they're nice to work with mathematically. Empirically, Tree Ensembles or Neural Nets are almost always better.

    1. Find Native Speakers

      This is a great idea to engage students. I have thought about it before but I have not yet put it into practice. I did pen pal letters one year but snail mail was too slow. I am going to try an incorporate this idea even more.

    1. for caring adults, teachers, parents, learners and their peers to share interests and contribute to a common purpose. The potential of cross-generational learning and connection unfolds when centered on common goals.

      important to have a caring, experienced community to rely on and learn from

    2. Powered with possibilities made available by today’s social media, this peer culture can produce learning that’s engaging and powerful.

      this is what makes connected learning modern

    3. For more than a century, educators have strived to customize education to the learner. Connected Learning leverages the advances of the digital age to make that dream a reality — connecting academics to interests, learners to inspiring peers and mentors, and educational goals to the higher order skills the new economy rewards.

      good summary quote

    1. Implication means co-occurrence, not causality!
    2. Given a set of transactions, find rules that will predict the occurrence of an item based on the occurrences of other itemsin the transaction
    1. Hanauer (2012) contends that “language learning within these settings is defined overwhelmingly in linguistic, structural, and cognitive terms. Thus the language learner at the center of this system becomes nothing more than an intellectual entity involved in an assessable cognitive process” (p. 105). In this assessable cognitive instruction, students are not afforded the opportunity to use English as a social semiotic tool for expressing their own personal feelings (emotions), opinions, and stories as lived experience as well as for enacting social practices.

    1. organizations and caring adults can form partnerships, broker connections across settings, and share on openly networked platforms and portfolios.

      This is where networking, both in person and online, could come into play.

    2. earners need to feel a sense of belonging and be able to make meaningful contributions to a community in order to experience connected learning. Groups that foster connected learning have shared

      I don't think real positive change or learning can occur unless a student feels safe, welcomed, and like they belong. See Maslow's hierarchy of needs.

    3. hrough collaborative production, friendly competition, civic action, and joint research, youth and adults make things, have fun, learn, and make a difference together.

      shared interests and collaboration are instrumental for connected learning; reminds me of the phrase "great minds think alike"

    4. They do this by being sponsors of what youth are genuinely interested in — recognizing diverse interests and providing mentorship, space, and other resources.

      sponsorship/adult support in connected learning = important to learning success and an important resource

    5. Learning is irresistible and life-changing when it connects personal interests to meaningful relationships and real-world opportunity.

      absolutely true. passion+learning+education= change in the world for good

    6. embraces the diverse backgrounds and interests of all young people.

      importance of diversity in connected learning will heighten cultural awareness

    1. Personalized learning, though premised on differentiating one student from another, has seemed to work best when it attends, first and foremost, to the needs of teachers as a group. If tech is, indeed, merely a tool of personalized learning, then what does that make the teacher?
    2. Various sources told me that personalized learning, when aided by screens, is a bad fit for vulnerable students—those from low-income families, ethnic and racial minorities, kids with special needs, and English-language learners. In some areas of the country, including Providence, these groups account for almost the entire population of public schools. But the experience of personalized learning is, indeed, personal, and exceptions abound
    3. Other personalized-learning advocates told me that execution is everything.

      And isn't this the same case as in traditional teaching?!

    4. Yet the academic and policy research behind it is thin.

      And sadly this doesn't seem to have prevented a huge swath of schools to switching over to the idea. Isn't the purpose of a pilot program to do just that--pilot it to see if the data show it's a good idea to spread to other schools?!

    5. Teachers at Orlo Avenue Elementary said that, while they supported their principal’s decision to adopt Chromebook-based personalized learning, it had undoubtedly created a lot more work, with no accompanying pay raise.

      This is a major issue. And shouldn't all the ed-tech involved actually be lowering this sort of cost and not dramatically increasing it? Isn't that half the point?!

    6. Personalized learning argues that the entrepreneurial nature of the knowledge economy and the gaping need, diversity, and unmanageable size of a typical public-school classroom are ill-served by the usual arrangement of a teacher lecturing at a blackboard.
    1. To understand what has happened, we only need to look at the history of writing and printing to note two very different consequences (a) the first, a vast change over the last 450 years in how the physical and social worlds are dealt with via the inventions of modern science and governance, and (b) that most people who read at all still mostly read fiction, self-help and religion books, and cookbooks, etc.* (all topics that would be familiar to any cave-person).
    1. In Reader, Come Home: The Reading Brain in a Digital World, Maryanne Wolf talks about how technology has led to more skimming rather than reading slowly and carefully. She talks about the benefits of “cognitive patience.” And she reminds us that reading quickly isn’t what makes someone a good reader.
    1. Compared with neural networks configured by a pure grid search,we find that random search over the same domain is able to find models that are as good or betterwithin a small fraction of the computation time.
  6. Jun 2019
    1. To interpret a model, we require the following insights :Features in the model which are most important.For any single prediction from a model, the effect of each feature in the data on that particular prediction.Effect of each feature over a large number of possible predictions

      Machine learning interpretability

    1. Balance exploration and exploitation: the choice of examples to label is seen as a dilemma between the exploration and the exploitation over the data space representation. This strategy manages this compromise by modelling the active learning problem as a contextual bandit problem. For example, Bouneffouf et al.[9] propose a sequential algorithm named Active Thompson Sampling (ATS), which, in each round, assigns a sampling distribution on the pool, samples one point from this distribution, and queries the oracle for this sample point label. Expected model change: label those points that would most change the current model. Expected error reduction: label those points that would most reduce the model's generalization error. Exponentiated Gradient Exploration for Active Learning:[10] In this paper, the author proposes a sequential algorithm named exponentiated gradient (EG)-active that can improve any active learning algorithm by an optimal random exploration. Membership Query Synthesis: This is where the learner generates its own instance from an underlying natural distribution. For example, if the dataset are pictures of humans and animals, the learner could send a clipped image of a leg to the teacher and query if this appendage belongs to an animal or human. This is particularly useful if your dataset is small.[11] Pool-Based Sampling: In this scenario, instances are drawn from the entire data pool and assigned an informative score, a measurement of how well the learner “understands” the data. The system then selects the most informative instances and queries the teacher for the labels. Stream-Based Selective Sampling: Here, each unlabeled data point is examined one at a time with the machine evaluating the informativeness of each item against its query parameters. The learner decides for itself whether to assign a label or query the teacher for each datapoint. Uncertainty sampling: label those points for which the current model is least certain as to what the correct output should be. Query by committee: a variety of models are trained on the current labeled data, and vote on the output for unlabeled data; label those points for which the "committee" disagrees the most Querying from diverse subspaces or partitions:[12] When the underlying model is a forest of trees, the leaf nodes might represent (overlapping) partitions of the original feature space. This offers the possibility of selecting instances from non-overlapping or minimally overlapping partitions for labeling. Variance reduction: label those points that would minimize output variance, which is one of the components of error. Conformal Predictors: This method predicts that a new data point will have a label similar to old data points in some specified way and degree of the similarity within the old examples is used to estimate the confidence in the prediction.[13]
    1. Throughout the past two decades, he has been conducting research in the fields of psychology of learning and hybrid neural network (in particular, applying these models to research on human skill acquisition). Specifically, he has worked on the integrated effect of "top-down" and "bottom-up" learning in human skill acquisition,[1][2] in a variety of task domains, for example, navigation tasks,[3] reasoning tasks, and implicit learning tasks.[4] This inclusion of bottom-up learning processes has been revolutionary in cognitive psychology, because most previous models of learning had focused exclusively on top-down learning (whereas human learning clearly happens in both directions). This research has culminated with the development of an integrated cognitive architecture that can be used to provide a qualitative and quantitative explanation of empirical psychological learning data. The model, CLARION, is a hybrid neural network that can be used to simulate problem solving and social interactions as well. More importantly, CLARION was the first psychological model that proposed an explanation for the "bottom-up learning" mechanisms present in human skill acquisition: His numerous papers on the subject have brought attention to this neglected area in cognitive psychology.
    1. By comparison, Amazon’s Best Seller badges, which flag the most popular products based on sales and are updated hourly, are far more straightforward. For third-party sellers, “that’s a lot more powerful than this Choice badge, which is totally algorithmically calculated and sometimes it’s totally off,” says Bryant.

      "Amazon's Choice" is made by an algorithm.

      Essentially, "Amazon" is Skynet.

    1. This problem is called overfitting—it's like memorizing the answers instead of understanding how to solve a problem.

      Simple and clear explanation of overfitting

    1. Many writers have highlighted the power of the global digital tribe, particularly the way groups tend to solve problems more effectively than individual experts (Surowiecki, 2009). We read of how groups can self-organise and co-ordinate their actions in connected global environments (Shirky, 2008) and that there seems to be no limit what a tribe can do when it is given the appropriate tools (Godin, 2008). Mobile and personal technologies that are connected to global networks have afforded us with the priceless ability to collaborate and cooperate in new and inventive ways (Rheingold, 2002), and allow us to rapidly self organise into new collective forces (Tapscott and Williams, 2008). Connected technology not only gives us access to existing knowledge, it encourages and enables us to create new knowledge and share it widely to a global audience.

      I am enjoying this series Steve. A book that has influenced my thinking on the topic has been Teaching Crowds by Jon Dron and Terry Anderson.

      One thing that I am left wondering is how the benefits and affordances change and develop over time? I was left thinking about this while reading Clive Thompson’s new book Coders compared with his last book Smarter Than You Think.

      Also posted on Read Write Collect

  7. May 2019
    1. disruptive of formal education and enabling of student-centered and interest-driven learning

      To what extent are these actually at odds?

    1. oundaries between different learning and discourse spaces (e.g., public vs. private, formal educationvs. workplace learning) are to be crossed if not totally dissolved

      This is probably a long-term goal of mine that I might as well own up to.

    1. Professors base these grades on a combination of factors and values, such as 10% participation, 20% homework, 30% final exam, and 40% group project. Digital adaptive learning tools can do this too, and then take the student’s score and match it with the next best skill in the subject’s overall scope and sequence.

      This is interesting. This could be interesting in design.

    2. Adaptive learning does not fit easily into the status quo. Besides having to use a blended learning model, in which class-time is divvied up between traditional and electronic learning, teachers must be willing to let students progress at their own pace.

      Could this fit within a trades model?

    3. This is different to simply providing differentiated content for students. For instance, if a learner was not in class during a period when a particular skill was introduced, and years later was learning a new skill that built on that prior knowledge, that learner would struggle. Adaptive sequencing tools could help that student go back to find this gap and learn this content first, rather than following the same sequence as everyone else

      This could be very powerful in trades training.

    4. Practice Engine

      This is brilliant. Start simple and then ramp it up for practice.

    5. A fixed-form assessment is one in which the items are preselected, and every student is tested on the same set of questions (e.g. a final exam).

      fixed form assessment vs. adaptive assessment.

    6. Let’s break these down a little further

      Content, Assement, sequence. The three places adaptive learning occurs.

    7. How do we use testing – or assessment – not simply to rank students but as meaningful windows into why they struggle to learn? And the big one: Can changes in digital curriculum help close the aching achievement gap?

      OMG YES!!!

    8. we define digital adaptive learning tools as education technologies that can respond to a student’s interactions in real-time by automatically providing the student with individual support

      Definition of adaptaive learning

    9. Knewton alone has raised nearly $160 million.

      interesting

    10. The tools, however, are not a panacea. For several reasons, it’s unlikely that a single tool will ever be able to take over a student’s education and direct them to every single thing they should do. Nor is it likely that we would want it to, as a critical part of education is building student agency – helping students own their learning, make decisions, become lifelong learners, and develop their metacognitive skills.

      YES!

    11. But a critical challenge correctly noted in this report, written by EdSurge and supported by Pearson, is to decipher just what it means for a learning technology to be adaptive.
    12. Adaptive learning is an enormously promising field. Educators worldwide are using adaptive tools to change their practice. The tools are growing and gaining acceptance in classrooms.
    1. A PLE can be entirely controlled or adapted by a student according to his or her formal and informal learning needs, however not all students possess the knowledge management and the self-regulatory skills to effectively use social media in order to customize a PLE to provide the learning experience they desire.

      Teaching students to become self-regulated learners

    1. policy change index - machine learning on corpus of text to identify and predict policy changes in China

  8. Apr 2019
    1. Annotation Profile Follow learners as they bookmark content, highlight selected text, and tag digital resources. Analyze annotations to better assess learner engagement, comprehension and satisfaction with the materials assigned.

      There is already a Caliper profile for "annotation." Do we have any suggestions about the model?

    1. game for students, Calculation Nation from the National Council of Teachers of Mathematics is a wonderful resource.

      math game for summer

    2. Beat Summer Slide: The Parent Summer Checklist

      read this

    1. ive into equations: When plunging into a pool, have your child calculate the volume and weight of the water and the rate at which the pool will fill or drain. Be a meteorologist: Track summer weather and convert daily temperatures from Celsius to Fahrenheit and monitor monthly rainfall. Show the relevance: Invite your child to help you prepare poolside treats. Encourage them to use measuring cups and proportion snacks into different size bowls. Connect Math & Language: If your child excells at language, then use that subject as a platform to help them excel in math. Give them picture books and nonfiction texts to read that focus on math. Turn errands into learning opportunities: While at the grocery store, have your child figure out which box of crackers is closest to the $2.50 price point and count the kiwis as they put them in the bag. Add some education to your road trips: Distract your child from asking “Are we there yet?!” by creating paper tickets that identify all the rest stops along the way, so they can practice time and distance on the ride there. Make your beach day mathematical: Have your child arrange their seashells into piles of 3 or 5, and use those piles as the basis for multiplication and subtraction activities. Note Numbers:Have your child pay close attention to numbers found on clocks, cereal boxes, the kitchen calendar and the local newspaper. Have tell you how many articles are on page B4 of the paper and calculate how long they’ve been awake for. Pay close attention to menus: Whether you go out for dinner or order in, there’s bound to be a menu involved. Have your child pinpoint the price specific item, or list items that range between $10 and $15, or calculate how much a hamburger and a juice would cost. Change it up: Give your child a pile of coins–the bigger the assortment, the better! Have them find as many coin combinations as possible that equal the price of a beach ball.

      math ideas

    1. Even organized sports teach children about mathematics, rules, teamwork, planning, and so on. Likewise, a family game like Scrabble is about linguistics, psychology, mathematics, memory, competition, and doggedness. It’s about mastering the rules.

      even sports and family games help...

    1. Updated! 10 Online Summer Learning Opportunities]

      list of ten fun activities...lots of tech stuff

    1. S.M.A.R.T. Cases are boxed kits that include science activities and supplementary materials that make it a complete learning package for young people. S.M.A.R.T. Cases are sponsored by the Torrance Refining Company.  WHY IS THIS CASE SO “S.M.A.R.T.”? S.M.A.R.T. Cases are science kits designed for hands-on learning. They come with the tools and resources to make learning fun and easy. The Next Generation Science Standards (NGSS) requires that students engage in practice-rich activities that support their use of the case contents to figure out and explain complex phenomena and make connections to principles that cut across the content areas (NRC, 2012; NGSS Lead States, 2013). With the assistance of faculty at Torrance Unified School District, each case was evaluated for grade level and compliance with the framework for the NGSS.

      check one out for presentation

    1. Topic: Reading Classroom Ideas 10 Kids Summer Reading Programs We Love Summer reading is better reading. <img alt='' src='https://secure.gravatar.com/avatar/2f903edaa3cdf06132a636fea64aea4e?s=44&#038;d=mm&#038;r=g' srcset='https://secure.gravatar.com/avatar/2f903edaa3cdf06132a636fea64aea4e?s=88&#038;d=mm&#038;r=g 2x' class='avatar avatar-44 photo' height='44' width='44' /> Shellie Deringer on June 13, 2017 .contest-social .share-links svg, .share-links svg { top: 50%; left: 0px; } #atftbx p:first-of-type { display: none; } .entry-content .addthis_toolbox, .entry-content .addthis_button, .entry-header .addthis_toolbox, .entry-header .addthis_button { margin: 0 !important;} .at-style-responsive .at-share-btn { padding: 0 !important;} AddThis Sharing ButtonsShare to FacebookFacebookShare to TwitterTwitterShare to PinterestPinterest <img width="800" height="450" src="https://s18670.pcdn.co/wp-content/uploads/GettyImages-504870144-e1497380601900.jpg" class="attachment-full size-full wp-post-image" alt="kids summer reading programs" srcset="https://s18670.pcdn.co/wp-content/uploads/GettyImages-504870144-e1497380601900.jpg 800w, https://s18670.pcdn.co/wp-content/uploads/GettyImages-504870144-e1497380601900-272x153.jpg 272w, https://s18670.pcdn.co/wp-content/uploads/GettyImages-504870144-e1497380601900-400x225.jpg 400w, https://s18670.pcdn.co/wp-content/uploads/GettyImages-504870144-e1497380601900-768x432.jpg 768w, https://s18670.pcdn.co/wp-content/uploads/GettyImages-504870144-e1497380601900-217x122.jpg 217w, https://s18670.pcdn.co/wp-content/uploads/GettyImages-504870144-e1497380601900-490x275.jpg 490w, https://s18670.pcdn.co/wp-content/uploads/GettyImages-504870144-e1497380601900-556x312.jpg 556w, https://s18670.pcdn.co/wp-content/uploads/GettyImages-504870144-e1497380601900-660x370.jpg 660w, https://s18670.pcdn.co/wp-content/uploads/GettyImages-504870144-e1497380601900-300x169.jpg 300w" sizes="(max-width: 800px) 100vw, 800px" /> ;new advadsCfpAd( 361210 );Next to the benefits of playing and swimming all summer long, reading is just about the most important thing kids can do this summer. We put together this list of free kids summer reading programs to help keep the learning going over the next few months. Share these kids summer reading programs with your students and their families! 1. Barnes & Noble Summer Reading for Kids <img class="alignnone size-medium wp-image-365078" src="https://s18670.pcdn.co/wp-content/uploads/barnes-and-noble-400x112.png" alt="" width="400" height="112" srcset="https://s18670.pcdn.co/wp-content/uploads/barnes-and-noble.png 400w, https://s18670.pcdn.co/wp-content/uploads/barnes-and-noble-220x62.png 220w, https://s18670.pcdn.co/wp-content/uploads/barnes-and-noble-300x84.png 300w" sizes="(max-width: 400px) 100vw, 400px" /> This program begins in May and runs through September. Kids can earn a FREE book after they read eights books and log them on the reading sheet. The Barnes and Noble kids summer reading program is only available to children in grades 1-6. Only one book is available for each child who completes a reading journal and choice must be made from the selected books available at the store.

      Reading programs

    1. READS for Summer Learning.[14] In READS, which has been iteratively modified over several randomized trials, students receive eight books in the mail over the summer that are matched to their reading level and interests. Along with each book, students receive a tri-fold paper that leads them through a pre-reading activity and a post-reading comprehension check. Students are asked to mail the postage-prepaid tri-fold back; families receive reminders when tri-folds are not returned.

      great idea to add to presentation

    2. An early comprehensive review of the literature summarized several findings regarding summer loss.[2] The authors concluded that: (1) on average, students’ achievement scores declined over summer vacation by one month’s worth of school-year learning, (2) declines were sharper for math than for reading, and (3) the extent of loss was larger at higher grade levels.

      research to use

    1. focus on collaboration, connection, diversity, democracy, and critical assessments of educational tools and structures

      Also critical assessments of authority structures, truth claims, value judgments...

    1. PBL) isan instructional method in which students lear

      Problem based learning is an instructional method in which students learn through facilitated problem solving. Problem based curricula provide students with guided experience in learning through solving complex, real-world problems. Rating: 9/10

    1. Emotional learning involves meddling with deeply personal, private aspectsof workers’ lives in an effort to influence and shape their emotions, some-times with constructive and sometimes with destructive results. Two aspectsof emotion have particular relevance in the workplace: emotional intelli-gence and emotion labor.
  9. learn-us-east-1-prod-fleet01-xythos.s3.us-east-1.amazonaws.com learn-us-east-1-prod-fleet01-xythos.s3.us-east-1.amazonaws.com
    1. Articulate what they know; 2. reflect on what they have learned; 3. support the internal negotiation of meaning making; 4. construct personal representations of meaning; and 5. support intentional, mindful thinking

      what technology should do in an online course to reach adults

    2. Since online learning has a different setting from the conventional classroom,online educators need to use some special techniques and perceptions to leadto success. Moreover, adults have special needs and requirements as learnerscompared with children and adolescents, thus online educators should knowhow adults can learn best because of their special characteristics. Philosophicaland methodological shifts also affect instruction. Many researchers havesuggested that constructivism should be applied in distance education. Thus,this paper attempts to examine the impact of constructivism in online learningenvironments when focusing on adult learners. The author develops the con-nection between constructivism and adult learning theory. In addition, thepaper proposes instructional guidelines using the constructivist approach inonline learning for adults.
  10. s3.us-east-1.amazonaws.com s3.us-east-1.amazonaws.com
    1. Workplace-relatedlearningis learning that is related to the firm in which the learner is employed and that is supported at least to some extent by their employer, but that is notfoundationalor higher education. Individuals may engage in this type of learning for the purposeof learning a new job, improving their job performance, for professional development, as an employee benefit or because it is required by legislation.
    2. Key dimensions of adult learning activities

      form, provider, payer, purpose, duration, design, delivery, instructor quality, credential

    3. Fivebroad types of adult learning

      Adult learning types including Foundational, higher education, workplace, personal, social. Includes a list of examples of the types of learning this includes in each category.

    1. The  Use  of  Mobile  Devices  for  Academic  Purposes  at  the  University  of  Washington:  Current  State  and  Future  Prospects

      Professional development opportunities and incentives for faculty to integrate mobile devices and as a teaching and learning tool.

    1. Can Tablet Computers Enhance Faculty Teaching?

      Studies faculty provided with tablet computers and peer mentoring workshops to help increase understanding and use of mobile devices in pedogogical approaches

    1. The ITL department at The Ohio State University at Mansfield has six primary themes: (a) developmentally appropriate practice, (b) integrated curriculum, (c) literature-based instruction, (d) classroom-based inquiry, (e) diversity and equity issues, and (f) technology integration. The goal for technology integration, like the other themes in the program, is to integrate the theme into each course of the program, when appropriate. For example, instructors find ways to integrate children’s literature into each of the methods courses, whether it is a mathematics, science, or social studies methods course. The goal is to integrate the common themes of the program throughout the methods courses and the other graduate courses leading up to student teaching.