This site explains the features that instructional designers or others would integrate with personalized design. Based on a graphic, it may have been meant for K-12 students, but appears applicable to other forms of learning as well. This appears to be more credible and more informative than other pages I have found so far. rating 4/5

This page is meant to demonstrate what personalized learning 'looks like' and that seems to mean the principles or characteristics that it has. This page relates to kids, not adults, but the principles mostly seem relevant to adults just as much as kids. I do not know enough about this topic to evaluate the information quality, but the aspects I can evaluate, such as the writing and presentation, seem to suggest at least moderate credibility. rating 2/5

This blends a discussion of professional development and personalized learning. This relates to the professional development of teachers, which I think I will shift my focus to since I am not finding public health education resources as I had hoped. This page discusses underlying cultural or other practices that contribute to professional development of this type. rating 2/5

This is a research based report (of which I have found few) that connects professional development and personalized learning. I had hoped to find links that applied to health care and have not found a great many so far, but this article, which is more oriented toward professional development for teachers, still has applications since public health education professionals participate in many of the same practices. rating; 5/5

I am not familiar with the sponsor, Capterra. This page describes what they consider the best e-learning apps for business. The article seems to have credible citations (such as Gartner). I notice that some of the apps may be limited to individuals whose organizations use a particular LMS. rating 3/5

train and develop your staff with mobile apps I am not sure why the first two components of this page are included, but there is a bulleted list of contexts or applications of mobile apps for e-learning, such as leadership training, onboarding, and integrating interns who are part of the organization. This is interesting but I do not yet know how essential it is.

10 awesome ways to use mobile learning for employee training This is an article about strategies and applications of mobile learning for employee development. A number of ideas are presented. I lack the knowledge base to evaluate the soundness, novelty, etc. of these ideas. There are screen shots and they are interesting enough but give only a limited idea of the concept being discussed. rating 3/5

This is a round-up article that describes four apps that employees can use for mobile learning. The apps are Udemy, Skill Pill, Designjot, and BoostHQ. It is not appropriate for me to evaluate the information quality; however, this particular source (eLearning industry) generally produces accurate articles. rating 4/5

This does not necessarily seem to be of top quality but it is the only item I have found so far that addresses just in time training specifically within healthcare. It does not do so in great depth. It does briefly address technology and mobile learning but not in a way that is tremendously insightful. rating 2/2

This article explains just in time learning (such as that which can be done via devices) within the context of higher education. My interest is in public health education, but at this moment, I am not sure how much I can narrow in on that topic, so I will save this for now. This is obviously not a scholarly article but is of some interest nonetheless. rating 2/5

Edward Thorndike's three laws of learning. The page does not explain this, but his theories came out in about 1900. His three laws of learning appear to be relevant to our course work. This simple page features black text on a white page. It is brief and it simply describes the three laws of learning. rating 5/5

This is Bloom's taxonomy of cognitive objectives. I selected this page because it explains both the old and new versions of the taxonomy. When writing instructional objectives for adult learning and training, one should identify the level of learning in Blooms that is needed. This is not the most attractive presentation but it is one of the more thorough ones. rating 4/5

This page, Top Tools for Learning, is updated every year. It lists and briefly describes the top tech tools for adult learning. For the current (2018) list, they are YouTube, PowerPoint, and Google Search. The list proceeds through the top 200 and there are links to each tool. The purpose of this page is to list them; tutorials, etc. are not offered. Rating 4/5

Campus Technology magazine This is the website for a magazine that is also published on paper. Articles are freely accessible (a subscription is not required). The design of the page is messy and as with any magazine, the content varies, but the site does give a description of the use of technology in higher education. The same technologies can sometimes be applied in adult learning in general. Rating 4/5

This link is to a three-page PDF that describes Gagne's nine events of instruction, largely in in the form of a graphic. Text is minimized and descriptive text is color coded so it is easy to find underneath the graphic at the top. The layout is simple and easy to follow. A general description of Gagne's work is not part of this page. While this particular presentation does not have personal appeal to me, it is included here due to the quality of the page and because the presentation is more user friendly than most. Rating 4/5

This page is a simply presented list of many learning theories, both popular and less well known. The layout is clean. The pages to which the listed items link are somewhat minimal in nature so this would give a basic tour or overview of the models and would allow viewers to review the names of some of the learning theories. This page does not prioritize learning theories or identify and establish those theories that are the most prominent.

Edutech wiki This page has a somewhat messy design and does not look very modern but it does offer overviews of many topics related to technologies. Just like wikipedia, it offers a good jumping off point on many topics. Navigation can occur by clicking through categories and drilling down to topics, which is easier for those who already know the topic they are looking for and how it is likely to be characterized. Rating 3/5

This is one of many discussions of Kirkpatrick's four levels of evaluation. More of the page is taken up with decoration and graphics than needs to be the case but this page is included in this list because it offers a printable guide and because the hierarchy of the four levels is clearly shown. The text itself is printed in black on a white background and it is presented as a bulleted list (the bullets are not organized as well as they could be). Nonetheless it is a usable presentation of this model. rating 3/5

This page offers general guidelines for facilitating class discussions. It is written for college environments and in usable in adult learning and training settings also. The presentation is straightforward but the content is not in depth. Part of the value of the page is links on the left side that address other teaching topics related to course design and course management. Rating 2/2

project based learning While project based learning is more frequently used with children than adults, it can be useful for limited-time instruction for adults. This is a user friendly page that provides a decent description of project based learning and also discusses the design elements and teaching practices that should be used. rating 4/5

problem based learning This gives a brief overview of problem based learning. This is a teaching method in which learners receive an ill structured problem that they continue to define and then solve. This web page serves as an overview but if one were teaching with this approach, more information would be needed than is contained on the typical introductory web page. Rating 3/5

This is better than the problem-based learning page I already posted so I will post this one too. it is easy to read and gives the instructional designer or teacher a quick and better-than-average explanation about problem based learning, which is a method of teaching in which learners form teams and learn through solving real problems. rating 4/5

This is a reasonable list of Knowles' assumptions about adult learners -- not as complete or nuanced as one might find in a textbook, but worth having a look at when starting a new project. rating: 3/5

While there are many pages that somehow 'address' adult learning, I found few insightful as I reviewed them. This page is a bit different though as it does integrate transformational learning into adult learning theory and also has a different presentation of Knowles' work that is found on many other web pages. Rating 5/5

This page is associated with Thiagi's interactive lectures, which are characterized in a book that is available via this site. This particular page involves links to types of interaction, such as games, puzzles, and so forth. It would be better to read or review the book, but since that option is not available, I will provide a link here. rating 2/5

This is one of many pages that describes team based learning. The layout and typeface make this page easy enough to read. The content is rather brief and would suffice for someone who is trying to understand this approach and decide whether it is workable for their own adult learning and training context.

Mager's tips on instructional objectives This is a very simple page that consists of black and white text without any graphics. As is, the text on the page is rather small and difficult (for me, anyway) to read, so one may wish to enlarge it. The process of creating instructional objectives in this format is explained in a clear and straightforward way. Rating 5/5

Students should be taught the material but should also be set free in order to collaborate with peers as well as technology to “tinker” and figure out the answer to the problem on their own which promotes a student centered approach to learning

NEURAL READING COMPREHENSION AND BEYOND

DEEP LEARNING WITH CONVOLUTIONAL NEURAL NETWORKS FOR IMAGE RECOGNITION: STEP-BY-STEP PROCESS FROM PREPARATION TO GENERALIZATION

Deep Learning for Chatbots

EFFICIENT METHODS AND HARDWARE FOR DEEP LEARNING

Deep Compression" can reduce the model sizeby 18?to 49?without hurting the prediction accuracy. We also discovered that pruning and thesparsity constraint not only applies to model compression but also applies to regularization, andwe proposed dense-sparse-dense training (DSD), which can improve the prediction accuracy for awide range of deep learning models. To efficiently implement "Deep Compression" in hardware,we developed EIE, the "Efficient Inference Engine", a domain-specific hardware accelerator thatperforms inference directly on the compressed model which significantly saves memory bandwidth.Taking advantage of the compressed model, and being able to deal with the irregular computationpattern efficiently, EIE improves the speed by 13?and energy efficiency by 3,400?over GPU

深度强化学习综述

深度文本匹配综述

深度强化学习综述

all kinds of text classification models and more with deep learning

reinforcement-learning code and paper tutorials

A Sensitivity Analysis of (and Practitioners’ Guide to) Convolutional Neural Networks for Sentence Classification

Differentiated Attentive Representation Learning for Sentence Classification

A Gentle Tutorial of Recurrent Neural Network with ErrorBackpropagation

A Tutorial on Deep Latent Variable Models of Natural Language

目前并没人来用attention来做机器翻译

LSTM Derivations

博客很赞！

batch normalization的出现是为了解决神经元的输入和当前计算值交互的高度依赖的问题。因为要计算期望值，所以需要拿到所有样本然后进行计算，显然不太现实。因此将取样范围和训练时的mini-batch保持一致。但是这就把局限转移到mini-batch的大小上了，很难应用到RNN。因此需要LayerNormalization.

Layer Normalization

NEURAL MACHINE TRANSLATION BY JOINTLY LEARNING TO ALIGN AND TRANSLATE

Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation

A STRUCTURED SELF-ATTENTIVE SENTENCE EMBEDDING

Contextual Word Representations: A Contextual Introduction

Deep Learning for Dialogue Systems

策略学习也是对话过程很重要的一环。 最近的策略学习过程有用基于有监督的预训练然后线上强化学习再训练的来提高学习的方案。但是这种方案有个潜在的毛病，在离线的数据中受限于数据量，线上一旦碰到了不常见的情况，容易直接恢复不来。(这个问题应该只是推断吧？有什么实证么？)

所以本文其实想说的是用一种方法来减轻线上和离线的差距。

Wait, this already happened?!

In education, learning data and analytics?

This reminds me of "personalized learning."

Do we capture this data? Can we?

How is this defined?

These apply to social annotation as well.

Are we capturing the right data/how can Hypothesis contribute to this profile?

Can H itself capture some of this data? Through the LMS?

Indeed. Just as it requires knowledge and skill to design, develop, and deliver an online learning experience, the same applies to blended learning. Making informed decisions about how to blend is deep, deep, deep.

Yeah, this is scary.

Wen和Bordes介绍了一种基于网络的端到端的任务型对话系统，这个系统将对话系统学习看成是从历史回话到系统回复的映射关系的学习问题，并且应用了一个编码解码器来训练整个系统。

这个思路很有意思，和我之前想构建一个电销员的语料库来做用户回复响应很像。这个很有可能。

I'm so glad I read Dave's post after having just read Rob Horning's great post, "The Sea Was Not a Mask", also addressing algorithms and YouTube.

Great discussion of what questions to ask about artificial intelligence and learning from Dave Cormier.

基于模型参数的迁移学习对 proformace 影响不大，当然训练更快啦。有趣的是，迁移 trained 模型参数的均值/方差统计性也可以得到不错的迁移效果。

Students can help each other learn by collaborating their efforts. Each student can bring a certain strength to the group so that they can all work out problems together

The importance of understanding the full extent of the content we are teaching is to give our students correct information. Learning incorrect information and having "misconceptions about the content area" is detrimental to our students' learning.

Helping students to have a relatable interest with their learning can help them to succeed in their futures. Making our lessons more understandable and related to their interests is important when setting up their learning environment.

When we start off the year using different teaching methods and establishing healthy relationships with our students, we can help them to grow immensely in the small amount of time that we know them.

Providing our students with opportunities to learn outside the classroom or using technology as a tool when we are teaching are good ways to get them involved in their learning and can eventually help them to take control of their learning experience all together, with us being the facilitators of knowledge.

When we understand our student's interests and build relationships with them, we can help them to love learning. We can do this collectively with our classes and we can do it with each student individually.

MXNet设计和实现简介

Recent Trends in Deep Learning BasedNatural Language Processing

GloVe: Global Vectors for Word Representation

Natural Language Processing (Almost) from Scratch

Short Text Similarity with Word Embeddings

Attention Is All You Need

Distributed Representations of Sentences and Documents - Doc2Vec

Deep contextualized word representations

BERT: Pre-training of Deep Bidirectional Transformers forLanguage Understanding

dummy encoding

Learning through layered asociations.Learning as hyperlinking.

I think we feel this way now with the internet. But its really just a certain kind of knowing and a certain kind of knowledge. It also depends on how you choose to approach that knowledge.

In other words: culture. I'm pretty sure that Engelbart would agree with the statement that someone who could order a book from a library would likely not know the best way to find a nearby water source, as the right kind of aborigine would know. Collective intelligence is a monotonically increasing store of knowledge that is maintained through social learning -- not just social learning, but teaching. Many species engage in social learning, but humans are the only primates with visible sclera -- the whites of our eyeballs -- which enables even infants to track where their teacher/parent is looking. I think this function of culture is what Engelbart would call "C work"

A Activity: 'Business as Usual'. The organization's day to day core business activity, such as customer engagement and support, product development, R&D, marketing, sales, accounting, legal, manufacturing (if any), etc. Examples: Aerospace - all the activities involved in producing a plane; Congress - passing legislation; Medicine - researching a cure for disease; Education - teaching and mentoring students; Professional Societies - advancing a field or discipline; Initiatives or Nonprofits - advancing a cause.

B Activity: Improving how we do that. Improving how A work is done, asking 'How can we do this better?' Examples: adopting a new tool(s) or technique(s) for how we go about working together, pursuing leads, conducting research, designing, planning, understanding the customer, coordinating efforts, tracking issues, managing budgets, delivering internal services. Could be an individual introducing a new technique gleaned from reading, conferences, or networking with peers, or an internal initiative tasked with improving core capability within or across various A Activities.

C Activity: Improving how we improve. Improving how B work is done, asking 'How can we improve the way we improve?' Examples: improving effectiveness of B Activity teams in how they foster relations with their A Activity customers, collaborate to identify needs and opportunities, research, innovate, and implement available solutions, incorporate input, feedback, and lessons learned, run pilot projects, etc. Could be a B Activity individual learning about new techniques for innovation teams (reading, conferences, networking), or an initiative, innovation team or improvement community engaging with B Activity and other key stakeholders to implement new/improved capability for one or more B activities.

In other words, human culture, using language, artifacts, methodology, and training, bootstrapped collective intelligence; what Engelbart proposed, then was to apply C work to culture's bootstrapping capabilities.

To me, this is the most prescient of Engelbart's future visions, and the seed for future study of culture-technology co-evolution. I talked with Engelbart about this passage over the years and we agreed that although the power of the artifacts, from RAM to CPU speed to network bandwidth, had improved by the billionfold since 1962, the "softer" parts of the formula -- the language, methodology, and training -- have not advanced so much. Certainly language, training methods and pedagogy, and collaborative strategies have evolved with the growth and spread of digital media, but are still lagging. H/LAMT interests me even more today than it did thirty years ago because Engelbart unknowingly forecast the fundamental elements of what has come to be called cultural-biological co-evolution. I gave a TED talk in 2005, calling for an interdisciplinary study of human cooperation -- and obstacles to cooperation. It seems that in recent years an interdisciplinary understanding has begun to emerge. Joseph Henrich at Harvard, for one, in his recent book, The Secret of Our Success, noted:

Drawing insights from lost European Explorers, clever chimpanzees, hunter-gatherers, cultural neuroscience, ancient bones and the human genome, Henrich shows that it’s not our general intelligence, innate brain power, or specialized mental abilities that explain our success. Instead, it’s our collective brains, which arise from a combination of our ability to learn selectively from each and our sociality. Our collective brains, which often operate outside of any individual’s conscious awareness, gradually produce increasingly complex, nuanced and subtle technological, linguistic and social products over generations.

Tracking this back into the mist of our evolutionary past, and to the remote corners of the globe, Henrich shows how this non-genetic system of cultural inheritance has long driven human genetic evolution. By producing fire, cooking, water containers, tracking know-how, plant knowledge, words, hunting strategies and projectiles, culture-driven genetic evolution expanded our brains, shaped our anatomy and physiology, and influenced our psychology, making us into the world’s only living cultural species. Only by understanding cultural evolution, can we understand human genetic evolution.

Henrich, Boyd, and RIcherson wrote, about the social fundamentals that distinguish human culture's methods of evolving collective intelligence in The Origin and Evolution of Culture:

Surely, without punishment, language, technology, individual intelligence and inventiveness, ready establishment of reciprocal arrangements, prestige systems and solutions to games of coordination, our societies would take on a distinctly different cast. Thus, a major constraint on explanations of human sociality is its systemic structure

Executive capabilities/processes compared. Latter are tied to metacognition in some learning theories. Here tacit knowledge is included in capabilities and excluded from processes (i.e. as inferior or biasing?)- if I'm reading correctly.

Learning theory.