A CMS “provides an instructor with a set of tools and a framework that allows the relatively easy creation of online course content and the subsequent teaching and management of that course including various interactions with students taking the course” (EDUCAUSE Evolving Technologies Committee, 2003, p. 1). Examples of a CMS include Blackboard, Angel, Sakai, Oncourse and Moogle. However, Blackboard is a good example of the confusion that exists regarding these terms as it is commonly referred to in the literature as an LMS.

The American Society for Training & Development (Learning Circuits, 2005), recommendsthese following functional requirements for a corporate LMS:

Lessons are provided based on the individual student’s learning progress.

Bailey, G. D. (1993). Wanted: A road map for understanding Integrated Learning Systems. In G. D. Bailey (Ed.), Computer-based Integrated Learning Systems (pp. 3-9). Englewood Cliffs, NJ: Educational Technology Publications.

n LMS is the infrastructure that delivers and manages in-structional content, identifies and assesses in-dividual and organizational learning or training goals, tracks the progress towards meeting those goals, and collects and presents data for super-vising the learning process of an organization as a whole (Szabo & Flesher, 2002). An LMS deliv-ers content but also handles course registration and administration, skills gap analysis, tracking and reporting (Gilhooly, 2001).

The term ILS was coined by Jostens Learn-ing, and LMS was originally used to describe the management system component of the PLATO K-12 learning system, content-free and separate from the courseware (R. Foshay, personal com-munication, October 24, 2006).

LMS has its history in another term, integrated learning system (ILS) which offers functionality beyond instructional content such as management and tracking, personalized instruction and integration across the system (Bailey, 1993; Becker, 1993; Brush, Armstrong, Barbrow, & Ulintz, 1999; Szabo & Flesher, 2002).

Research shows that people are highly likely to revisit information they have viewed in the past and to re-issue queries that they have written in the past (Jones et al., 2002, Milic-Frayling et al., 2004). In one large study, 40% of people's search results clicks were on pages that they had clicked on before over the course of a year, with 71% of these using the identical query string as before (Teevan et al., 2006a). In a survey associated with this study, 17% of interviewees reported “not being able to return to a page I once visited” as one of the “biggest problems in using the web.” Therefore, allowing search over recently viewed information can improve a user's productivity (Dumais et al., 2003). Web browsers, as opposed to search engines, can provide much of this functionality. For example, the Chrome Web browser supports information revisiting by showing a grid of thumbnail images representing a user's most frequently visited web pages, and the drop-down menu from the many browser Web address bars shows recently visited pages. Search engines themselves can provide query history, as well as history of previously selected pages if the user agrees to having that information recorded. The PubMed bioscience journal service shows recently issued queries and visited documents in a simple history display (see Figure 1.6). Similarly, many shopping Web site show recently viewed items in a graphical form. Thumbnail images have also been experimented with in search results listing, both for reminding searchers of previously visited pages and for suggesting information about the hit, such as its genre.

Around 1776, certain important people in the English colonies made a discovery that would prove enormously useful for the next two hundred years. They found that by creating a nation, a symbol, a legal unity called the United States, they could take over land, profits, and political power from favorites of the British Empire. In the process, they could hold back a number of potential rebellions and create a consensus of popular support for the rule of a new, privileged leadership.

Sputnik

"that text has been removed from the official version on the Apache site." This itself is also not good. If you post "official" records but then quietly edit them over time, I have no choice but to assume bad faith in all the records I'm shown by you. Why should I believe anything Apache board members claim was "minuted" but which in fact it turns out they might have just edited into their records days, weeks or years later? One of the things I particularly watch for in modern news media (where no physical artefact captures whatever "mistakes" are published as once happened with newspapers) is whether when they inevitably correct a mistake they _acknowledge_ that or they instead just silently change things.

If the reality is you pushed out a release that doesn't even compile, and then you spotted the typo six minutes later, that's fine, that's what the git repo should show. Don't come to me asking if there's a way to change history so that it seems as if it didn't happen that way. How does that help anybody?

it’s about writing the first draft of history. “I’m writing a lot when other people aren’t necessarily putting things out there,” he says. “You can be a great academic, but if you’re not writing all the time you’re not necessarily in people’s minds as someone they would want to ask a question to.

It is oppositional, Utopian, and completely withoutinnocence.

L.E. Phillips

Cities are cradles. Nests made of carefully knitted infrastructure holding us up. When a city's infrastructure is exposed - a hole in the pavement, arteries under sun - we're reminded of our dependence on a deeper physical reality and our implicit vulnerability as a result. We're reminded that our cities are engineered and technical places as much as they are natural expressions of the Human and the Social, whose buildings echo ancient grouping of people at work, play, or home. What we expect from infrastructure is that it works, because when it doesn't , it isn't. We want infrastructure to seamlessly integrate with the existing world — in the ground like water rather than an accessory above. After all, infrastructure is here to support us; an expression of what may be our most endemic myth, that the world is here for us. But with every receding seam, from cable to code, comes a techno-political risk. Without edges we cannot know where we are and nor through whom we speak.

it would be amiss of me to suggest that the online version of ed tech is the only one.

memoirs

manically inventive figure—really brilliant in many ways—with no particular training in design, but an intense interest in how people work.

"At the company's headquarters they created the bureaucracy to process information and make decisions about things that were taking place thousands of miles away."

He founded the Brahmo Samaj in 1828 along with Debendranath Tagore. Brahmoism began as a monotheistic reformist movement of Hinduism.

# Two commits are considered the same if they have the same tree and # the same commit and author metadata. This is how we re-identify # commits after their hash IDs have been rewritten.

The Journal was a primitive hypertext-based groupware program, which can be seen as a predecessor (if not the direct ancestor) of all contemporary server software that supports collaborative document creation (like wikis). It was used by ARC members to discuss, debate, and refine concepts in the same way that wikis are being used today.

What I think we're lacking is proper tooling, or at least the knowledge of it. I don't know what most people use to write Git commits, but concepts like interactive staging, rebasing, squashing, and fixup commits are very daunting with Git on the CLI, unless you know really well what you're doing. We should do a better job at learning people how to use tools like Git Tower (to give just one example) to rewrite Git history, and to produce nice Git commits.

The folks at Netlify created Netlify CMS to fill a gap in the static site generation pipeline. There were some great proprietary headless CMS options, but no real contenders that were open source and extensible—that could turn into a community-built ecosystem like WordPress or Drupal. For that reason, Netlify CMS is made to be community-driven, and has never been locked to the Netlify platform (despite the name).

dial-up internet uses sound waves transmitted over copper

In the early 1990s, the creators of Netscape apparently built a function that enabled each web page to be annotated by those visiting it, as a way for viewers to discuss the page’s content. But according to a [1] produced in 2013 by a nonprofit called [Hypothesis][2], the feature was turned off.

# Add auto-completion and a stored history file of commands to your Python # interactive interpreter. Requires Python 2.0+, readline. Autocomplete is # bound to the Esc key by default (you can change it - see readline docs). # # Store the file in ~/.pystartup, and set an environment variable to point # to it: "export PYTHONSTARTUP=~/.pystartup" in bash. import atexit import os import readline import rlcompleter historyPath = os.path.expanduser("~/.pyhistory") def save_history(historyPath=historyPath): import readline readline.write_history_file(historyPath) if os.path.exists(historyPath): readline.read_history_file(historyPath) atexit.register(save_history) del os, atexit, readline, rlcompleter, save_history, historyPath

for-profit tech companies — most notably Google, Apple, Facebook, and Amazon (GAFA) — built software and services that rapidly outpaced the capabilities of open protocols

Huge web properties were started during this era including Yahoo, Google, Amazon, Facebook, LinkedIn, and YouTube. In the process, the importance of centralized platforms like AOL greatly diminished.

Ancestor of all animals identified in Australian fossils

State police power was validated for the first time a few years after the end of the Revolutionary War, when Philadelphia was isolated to control the threat of yellow fever.

Dutch programmer Guido van Rossum designed Python in 1991, naming it after the British television comedy Monty Python's Flying Circus because he was reading the show's scripts at the time.

La mattina del 9 agosto 1918, cento anni fa, sei biplani monoposto SVA e un biposto dello stesso tipo, con a bordo otto aviatori italiani, entrarono nello spazio aereo di Vienna, la capitale dell’impero austro-ungarico.

The programming language was started as a side project by Dutch programmer Guido van Rossum.

Brown's Vulgar Errours.

would owe their being to me

Hans Moravec argued in 1976 that computers were still millions of times too weak to exhibit intelligence. He suggested an analogy: artificial intelligence requires computer power in the same way that aircraft require horsepower. Below a certain threshold, it's impossible, but, as power increases, eventually it could become easy.[79] With regard to computer vision, Moravec estimated that simply matching the edge and motion detection capabilities of human retina in real time would require a general-purpose computer capable of 109 operations/second (1000 MIPS).[80] As of 2011, practical computer vision applications require 10,000 to 1,000,000 MIPS. By comparison, the fastest supercomputer in 1976, Cray-1 (retailing at $5 million to $8 million), was only capable of around 80 to 130 MIPS, and a typical desktop computer at the time achieved less than 1 MIPS.

For example, take the character for east , which in the Beijingdialect has the sound “dong” (pronounced “doong,” as in Mao Ze-dong’s name). Since a Chinese character is read aloud as a single syllableand since spoken Chinese is also rather short of sounds (there are onlyabout four hundred different syllables in the whole language), it hasbeen plagued with homophones, words that sound like other words, like“soul” and “sole” or “all” and “awl” in English. It happened that thespoken word meaning “freeze” had the sound “dong.” So did a spokenword meaning a roof beam. When the Chinese went to write down thecharacter for freeze, they took the character for east and put beside itthe symbol of ice , which makes the character (“dong,” to freeze).To write down the word sounding “dong” which meant roof beam, theywrote the character east and put before it the symbol for wood mak-ing (“dong,” a roof beam).These are simple examples. Indeed, any part of the Chinese languageis simple in itself. It becomes difficult because there is so much of it to beremembered, so many meanings and allusions. When the lexicographersof later times wanted to arrange thousands of Chinese characters in adictionary, for instance, the best they could do in the absence of an al-phabet was to work out a list of 214 classifiers or “radicals,” one ofwhich was sure to be in each character in the language. These 214classifiers, for dictionary purposes, correspond to the 26 letters of our al-phabet, but are more ambiguous and less efficient. Shang writing was al-ready using “radicals” like wood, mouth, heart, hand, that indicatedcategories of meaning. From the start the governmental power of theChinese writing system was at the ruler’s disposal. Writing seems to haveemerged more in the service of lineage organization and governmentthan in the service of trade.

The language for writing React. Reason's creator also created ReactJS, whose first prototypes were written in SML, a distant cousin of OCaml. We've transcribed ReactML into ReactJS for wide adoption. A few years later, we're now iterating on the future of ReactJS through ReasonReact.

the main reason we built a new multiprocess architecture is that Chromium's multiprocess support was never contributed to the WebKit project. It has always lived in the separate Chromium tree, making it pretty hard to use for non-Chrome purposes.Before we wrote a single line of what would become WebKit2 we directly asked Google folks if they would be willing to contribute their multiprocess support back to WebKit, so that we could build on it. They said no.

Netheads vs Bellheads

Photo: Courtesy UT Health Science Center at San Antonio

Fountain

The neats: logic and symbolic reasoning[edit source] Logic was introduced into AI research as early as 1958, by John McCarthy in his Advice Taker proposal.[100] In 1963, J. Alan Robinson had discovered a simple method to implement deduction on computers, the resolution and unification algorithm. However, straightforward implementations, like those attempted by McCarthy and his students in the late 1960s, were especially intractable: the programs required astronomical numbers of steps to prove simple theorems.[101] A more fruitful approach to logic was developed in the 1970s by Robert Kowalski at the University of Edinburgh, and soon this led to the collaboration with French researchers Alain Colmerauer and Philippe Roussel who created the successful logic programming language Prolog.[102] Prolog uses a subset of logic (Horn clauses, closely related to "rules" and "production rules") that permit tractable computation. Rules would continue to be influential, providing a foundation for Edward Feigenbaum's expert systems and the continuing work by Allen Newell and Herbert A. Simon that would lead to Soar and their unified theories of cognition.[103] Critics of the logical approach noted, as Dreyfus had, that human beings rarely used logic when they solved problems. Experiments by psychologists like Peter Wason, Eleanor Rosch, Amos Tversky, Daniel Kahneman and others provided proof.[104] McCarthy responded that what people do is irrelevant. He argued that what is really needed are machines that can solve problems—not machines that think as people do.[105] The scruffies: frames and scripts[edit source] Among the critics of McCarthy's approach were his colleagues across the country at MIT. Marvin Minsky, Seymour Papert and Roger Schank were trying to solve problems like "story understanding" and "object recognition" that required a machine to think like a person. In order to use ordinary concepts like "chair" or "restaurant" they had to make all the same illogical assumptions that people normally made. Unfortunately, imprecise concepts like these are hard to represent in logic. Gerald Sussman observed that "using precise language to describe essentially imprecise concepts doesn't make them any more precise."[106] Schank described their "anti-logic" approaches as "scruffy", as opposed to the "neat" paradigms used by McCarthy, Kowalski, Feigenbaum, Newell and Simon.[107] In 1975, in a seminal paper, Minsky noted that many of his fellow "scruffy" researchers were using the same kind of tool: a framework that captures all our common sense assumptions about something. For example, if we use the concept of a bird, there is a constellation of facts that immediately come to mind: we might assume that it flies, eats worms and so on. We know these facts are not always true and that deductions using these facts will not be "logical", but these structured sets of assumptions are part of the context of everything we say and think. He called these structures "frames". Schank used a version of frames he called "scripts" to successfully answer questions about short stories in English.[108] Many years later object-oriented programming would adopt the essential idea of "inheritance" from AI research on frames.

In 1988 Apple sued Microsoft and Hewlett-Packard on the grounds that they infringed Apple's copyrighted GUI, citing (among other things) the use of rectangular, overlapping, and resizable windows. After four years, the case was decided against Apple, as were later appeals. Apple's actions were criticized by some in the software community, including the Free Software Foundation (FSF), who felt Apple was trying to monopolize on GUIs in general, and boycotted GNU software for the Macintosh platform for seven years.

Bolt, Beranek and Newman (BBN) developed its own Lisp machine, named Jericho,[7] which ran a version of Interlisp. It was never marketed. Frustrated, the whole AI group resigned, and were hired mostly by Xerox. So, Xerox Palo Alto Research Center had, simultaneously with Greenblatt's own development at MIT, developed their own Lisp machines which were designed to run InterLisp (and later Common Lisp). The same hardware was used with different software also as Smalltalk machines and as the Xerox Star office system.

In 1979, Russell Noftsker, being convinced that Lisp machines had a bright commercial future due to the strength of the Lisp language and the enabling factor of hardware acceleration, proposed to Greenblatt that they commercialize the technology.[citation needed] In a counter-intuitive move for an AI Lab hacker, Greenblatt acquiesced, hoping perhaps that he could recreate the informal and productive atmosphere of the Lab in a real business. These ideas and goals were considerably different from those of Noftsker. The two negotiated at length, but neither would compromise. As the proposed firm could succeed only with the full and undivided assistance of the AI Lab hackers as a group, Noftsker and Greenblatt decided that the fate of the enterprise was up to them, and so the choice should be left to the hackers. The ensuing discussions of the choice divided the lab into two factions. In February 1979, matters came to a head. The hackers sided with Noftsker, believing that a commercial venture fund-backed firm had a better chance of surviving and commercializing Lisp machines than Greenblatt's proposed self-sustaining start-up. Greenblatt lost the battle.

San Antonio

He has given names to some of them. “Come here, Boss Tweed,” he says.