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Google to offer users the option to auto-delete location history and web search data that it harvests

Google is to give users the choice of being able to automatically delete their search and location history after three months.

It announced the auto-delete tools for location history data, as well as web browsing and app activity, which will be rolled out in the coming weeks.

Last November Google was accused of misleading about location tracking after consumer groups from seven European nations asked their privacy regulators to take action against the search engine giant.

google logo mountainview 011

Location tracking

Consumer groups from the Netherlands, Poland, Czech Republic, Greece, Norway, Slovenia and Sweden, all filed GDPR complaints against Google’s location tracking.

They alleged that Google is tracking the movements of millions of users in breach of the European Union’s privacy laws.

Google, of course, is already facing a lawsuit in the United States for allegedly tracking phone users regardless of privacy settings.

That lawsuit was filed after an investigation by the Associated Press found that a number of Google services running on Android and Apple devices determine the user’s location and store it, even when Google’s “Location History” setting is switched off.

It should be remembered that Google had already allowed users to manually delete the data it harvests when they use its products such as YouTube, Maps and Search.

But now it trying to give users more control by offering auto-delete tools.

“And when you turn on settings like Location History or Web & App Activity, the data can make Google products more useful for you – like recommending a restaurant that you might enjoy, or helping you pick up where you left off on a previous search,” wrote David Monsees, product manager of search in a blog posting.

Auto-delete

“We work to keep your data private and secure, and we’ve heard your feedback that we need to provide simpler ways for you to manage or delete it,” Monsees added.

“You can already use your Google Account to access simply on/off controls for Location History and Web & App Activity, and if you choose – to delete all or part of that data manually,” he wrote. “In addition to these options, we’re announcing auto-delete controls that make it even easier to manage your data.”

Essentially, the user will give a time limit to choose for how long you want your data to be saved. This could be 3 months or 18 months.

Any data older than that will be automatically deleted from your account on an ongoing basis.

“These controls are coming first to Location History and Web & App Activity and will roll out in the coming weeks,” Monsees wrote. “You should always be able to manage your data in a way that works best for you–and we’re committed to giving you the best controls to make that happen.”

It should be noted that there will be no auto-delete of YouTube watch history or voice commands issued via Home and Assistant.

[Source: This article was published in silicon.co.uk By Tom Jowitt - Uploaded by the Association Member: James Gill]

Categorized in Search Engine

Ever had to search for something on Google, but you’re not exactly sure what it is, so you just use some language that vaguely implies it? Google’s about to make that a whole lot easier.

Google announced today it’s rolling out a new machine learning-based language understanding technique called Bidirectional Encoder Representations from Transformers, or BERT. BERT helps decipher your search queries based on the context of the language used, rather than individual words. According to Google, “when it comes to ranking results, BERT will help Search better understand one in 10 searches in the U.S. in English.”

Most of us know that Google usually responds to words, rather than to phrases — and Google’s aware of it, too. In the announcement, Pandu Nayak, Google’s VP of search, called this kind of searching “keyword-ese,” or “typing strings of words that they think we’ll understand, but aren’t actually how they’d naturally ask a question.” It’s amusing to see these kinds of searches — heck, Wired has made a whole cottage industry out of celebrities reacting to these keyword-ese queries in their “Autocomplete” video series” — but Nayak’s correct that this is not how most of us would naturally ask a question.

As you might expect, this subtle change might make some pretty big waves for potential searchers. Nayak said this “[represents] the biggest leap forward in the past five years, and one of the biggest leaps forward in the history of Search.” Google offered several examples of this in action, such as “Do estheticians stand a lot at work,” which apparently returned far more accurate search results.

I’m not sure if this is something most of us will notice — heck, I probably wouldn’t have noticed if I hadn’t read Google’s announcement, but it’ll sure make our lives a bit easier. The only reason I can see it not having a huge impact at first is that we’re now so used to keyword-ese, which is in some cases more economical to type. For example, I can search “What movie did William Powell and Jean Harlow star in together?” and get the correct result (Libeled Lady; not sure if that’s BERT’s doing or not), but I can also search “William Powell Jean Harlow movie” and get the exact same result.

BERT will only be applied to English-based searches in the US, but Google is apparently hoping to roll this out to more countries soon.

[Source: This article was published in thenextweb.com By RACHEL KASER - Uploaded by the Association Member: Dorothy Allen]

Categorized in Search Engine

The new language model can think in both directions, fingers crossed

Google has updated its search algorithms to tap into an AI language model that is better at understanding netizens' queries than previous systems.

Pandu Nayak, a Google fellow and vice president of search, announced this month that the Chocolate Factory has rolled out BERT, short for Bidirectional Encoder Representations from Transformers, for its most fundamental product: Google Search.

To pull all of this off, researchers at Google AI built a neural network known as a transformer. The architecture is suited to deal with sequences in data, making them ideal for dealing with language. To understand a sentence, you must look at all the words in it in a specific order. Unlike previous transformer models that only consider words in one direction – left to right – BERT is able to look back to consider the overall context of a sentence.

“BERT models can, therefore, consider the full context of a word by looking at the words that come before and after it—particularly useful for understanding the intent behind search queries,” Nayak said.

For example, below's what the previous Google Search and new BERT-powered search looks like when you query: “2019 brazil traveler to usa need a visa.”

2019 brazil

Left: The result returned for the old Google Search that incorrectly understands the query as a US traveler heading to Brazil. Right: The result returned for the new Google Search using BERT, which correctly identifies the search is for a Brazilian traveler going to the US. Image credit: Google.

BERT has a better grasp of the significance behind the word "to" in the new search. The old model returns results that show information for US citizens traveling to Brazil, instead of the other way around. It looks like BERT is a bit patchy, however, as a Google Search today still appears to give results as if it's American travelers looking to go to Brazil:

current google search

Current search result for the query: 2019 brazil traveler to USA need a visa. It still thinks the sentence means a US traveler going to Brazil

The Register asked Google about this, and a spokesperson told us... the screenshots were just a demo. Your mileage may vary.

"In terms of not seeing those exact examples, the side-by-sides we showed were from our evaluation process, and might not 100 percent mirror what you see live in Search," the PR team told us. "These were side-by-side examples from our evaluation process where we identified particular types of language understanding challenges where BERT was able to figure out the query better - they were largely illustrative.

"Search is dynamic, content on the web changes. So it's not necessarily going to have a predictable set of results for any query at any point in time. The web is constantly changing and we make a lot of updates to our algorithms throughout the year as well."

Nayak claimed BERT would improve 10 percent of all its searches. The biggest changes will be for longer queries, apparently, where sentences are peppered with prepositions like “for” or “to.”

“BERT will help Search better understand one in 10 searches in the US in English, and we’ll bring this to more languages and locales over time,” he said.

Google will run BERT on its custom Cloud TPU chips; it declined to disclose how many would be needed to power the model. The most powerful Cloud TPU option currently is the Cloud TPU v3 Pods, which contain 64 ASICs, each carrying performance of 420 teraflops and 128GB of high-bandwidth memory.

At the moment, BERT will work best for queries made in English. Google said it also works in two dozen countries for other languages, too, such as Korean, Hindi, and Portuguese for “featured snippets” of text. ®

[Source: This article was published in theregister.co.uk By Katyanna Quach - Uploaded by the Association Member: Anthony Frank]

Categorized in Search Engine

John Mueller from Google gave one of the clearest and easiest to understand explanations on how Google uses machine learning in web search. He basically said Google uses it for "specific problems" where automation and machine learning can help improve the outcome. The example he gave was with canonicalization and the example clears things up.

This is from the Google webmaster hangout starting at 37:47 mark. The example is this "So, for example, we use machine learning for canonicalization. So what that kind of means is we have all of those factors that we talked about before. And we give them individual weights. That's kind of the traditional way to do it. And we say well rel canonical has this much weight and redirect has this much weight and internal linking has this much weight. And the traditional approach would be to say well we will just make up those weights, at those numbers and see if it works out. And if we see that things don't work out we will tweak those numbers a little bit. And with machine learning what we can essentially do is say well this is the outcome that we want to have achieved and machine learning algorithms should figure out these weights on their own."

This was the first part of the answer around how Google debugs its search algorithm.

Here is the full transcript of this part.

The question:

Machine learning has been a part of Google search algorithm and I can imagine it's getting smarter every day. Do you as an employee with access to the secret files know the exact reason why pages rank better than others or is the algorithm now making decisions and evolving in a way that makes it impossible for humans to understand?

John's full answer:

We get this question every now and then and we're not allowed to could provide an answer because the machines are telling us not to talk about this topic. So it's I really can't answer. No just kidding.

It's something where we use machine learning in lots of ways to help us understand things better. But machine learning isn't just this one black box that does everything for you. Like you feed the internet in on one side the other side comes out search results. It's a tool for us. It's essentially a way of testing things out a lot faster and trying things out figuring out what the right solution there is.

So, for example, we use machine learning for canonicalization. So what that kind of means is we have all of those factors that we talked about before. And we give them individual weights. That's kind of the traditional way to do it. And we say well rel canonical has this much weight and redirect has this much weight and internal linking has this much weight. And the traditional approach would be to say well we will just make up those weights, at those numbers and see if it works out. And if we see that things don't work out we will tweak those numbers a little bit. And with machine learning what we can essentially do is say well this is the outcome that we want to have achieved and machine learning algorithms should figure out these weights on their own.

So it's not so much that machine learning does everything with canonicalization on its own but rather it has this well-defined problem. It's working out like what are these numbers that we should have there as weights and kind of repeatedly trying to relearn that system and understanding like on the web this is how people do it and this is where things go wrong and that's why we should choose these numbers.

So when it comes to debugging that. We still have those numbers, we still have those weights there. It's just that they're determined by machine learning algorithms. And if we see that things go wrong then we need to find a way like how could we tell the machine learning algorithm actually in this case we should have taken into account, I don't know phone numbers on a page more rather than just the pure content, to kind of separate like local versions for example. And that's something that we can do when we kind of train these algorithms.

So with all of this machine learning things, it's not that there's one black box and it just does everything and nobody knows why it does things. But rather we try to apply it to specific problems where it makes sense to automate things a little bit in a way that saves us time and that helps to pull out patterns that maybe we wouldn't have recognized manually if we looked at it.

Here is the video embed:

Here is how Glenn Gabe summed it up on Twitter:

Glenn Gabe@glenngabe
Glenn Gabe@glenngabe

More from @johnmu: Machine learning helps us pull out patterns we might have missed. And for debugging, Google can see those weights which are determined by ML algos. If there is something that needs to be improved, Google can work to train the algorithms: https://www.youtube.com/watch?v=5QxYWMEZT3A&t=38m53s 

[Source: This article was published in seroundtable.com By Barry Schwartz - Uploaded by the Association Member: Robert Hensonw]

Categorized in Search Engine

Google has seemingly put the final nail in the coffin for Adobe Flash, the once-popular video and animation player that's become less relevant as newer web standards like HTML5 have taken over.

The company announced on Monday that its search engine will stop supporting Flash later this year, and that it will ignore Flash content in websites that contain it. The search engine will also stop indexing SWF files, the file format for media played through the Flash Player. Google noted that most users and websites won't see any impact from this change. 

The move has been a long time coming for Flash. Adobe announced in 2017 that it was planning to end-of-life Flash by ceasing to update and distribute it at the end of 2020, and Flash is already disabled in Chrome by default. When it made the announcement, Adobe said it was working with partners like Apple, Microsoft, Facebook, Google, and Mozilla to smoothly phase out Flash.

Flash was once a critical technology that enabled content creators to easily implement media, animations, and games  in their websites during the earlier days of the web. If you frequently played online games in your web browser in the early 2000s, you'll probably remember that Flash plugin was a necessity. 

But as new web standards like HTML5 and WebGL have risen in popularity, there became less of a need for Flash. Plus, as time went on, Flash became more prone to security concerns — including one vulnerability highlighted by security blog Naked Security which surfaced last year that would have made it possible for hackers to execute malicious code via a Flash file.

[Source: This article was published in businessinsider.com By Lisa Eadicicco - Uploaded by the Association Member: David J. Redcliff] 

Categorized in Search Engine

Don't try to optimize for BERT, try to optimize your content for humans.

Google introduced the BERT update to its Search ranking system last week. The addition of this new algorithm, designed to better understand what’s important in natural language queries, is a significant change. Google said it impacts 1 in 10 queries. Yet, many SEOs and many of the tracking tools did not notice massive changes in the Google search results while this algorithm rolled out in Search over the last week.

The question is, Why?

The short answer. This BERT update really was around understanding “longer, more conversational queries,” Google wrote in its blog post. The tracking tools, such as Mozcast and others, primarily track shorter queries. That means BERT’s impact is less likely to be visible to these tools.

And for site owners, when you look at your rankings, you likely not tracking a lot of long-tail queries. You track queries that send higher volumes of traffic to your web site, and those tend to be short-tail queries.

Moz on BERT. Pete Meyers of Moz said the MozCast tool tracks shorter head terms and not the types of phrases that are likely to require the natural language processing (NLP) of BERT.

dr.pete

RankRanger on BERT. The folks at RankRanger, another toolset provider told me something similar. “Overall, we have not seen a real ‘impact’ — just a few days of slightly increased rank fluctuations,” the company said. Again, this is likely due to the dataset these companies track — short-tail keywords over long -tail keywords.

Overall tracking tools on BERT. If you look at the tracking tools, virtually all of them showed a smaller level of fluctuation on the days BERT was rolling out compared to what they have shown for past Google algorithm updates such as core search algorithm updates, or the Panda and Penguin updates.

Here are screenshots of the tools over the past week. Again, you would see significant spikes in changes, but these tools do not show that:

mozcast 800x348

serpmetrics 800x308

algoroo 800x269

advancedwebranking 800x186

accuranker 800x245

rankranger 800x265

semrush 800x358

SEO community on BERT. When it comes to individuals picking up on changes to their rankings in Google search, that also was not as large as a Google core update. We did notice chatter throughout the week, but that chatter within the SEO community was not as loud as is typical with other Google updates.

Why we care. We are seeing a lot of folks asking about how they can improve their sites now that BERT is out in the wild. That’s not the way to think about BERT. Google has already stated there is no real way to optimize for it. Its function is to help Google better understand searchers’ intent when they search in natural language. The upside for SEOs and content creators is they can be less concerned about “writing for the machines.” Focus on writing great content — for real people.

Danny Sullivan from Google said again, you cannot really optimize for BERT:

johan

Continue with your strategy to write the best content for your users. Don’t do anything special for BERT, but rather, be special for your users. If you are writing for people, you are already “optimizing” for Google’s BERT algorithm.

[Source: This article was published in searchengineland.com By Barry Schwartz - Uploaded by the Association Member: Joshua Simon]

Categorized in Search Engine

On a Google Webmaster Hangout someone asked about the role of H1s on a web page. John Mueller responded that heading tags were good for several reasons but they’re not a critical element.

SEO and H1 Headings

One of the top rules for Search Engine Optimization has long been adding keywords to your H1 heading at the top of the page in order to signal what a page is about and rank well.

It used to be the case, in the early 2000’s. that adding the target keyword phrase in the H1 was mandatory. In the early 2000’s, if the keywords were not in the H1 heading then your site might not be so competitive.

However, Google’s ability to understand the nuances of what a page is about have come a long way since the early 2000’s.

As a consequence, it is important to listen to what Google’s John Mueller says about H1 headings.

Can Multiple H1s be Used?

The context of the question is whether a publisher is restricted to using one H1 or can multiple H1 heading tags be used.

This is the question:

“Is it mandatory to just have one H1 tag on a web page or can it be used multiple times?”

Google’s John Mueller answered that you can use as many H1s as you want. He also said you can omit using the H1 heading tag, too.

John Mueller’s answer about H1 heading tags:

“You can use H1 tags as often as you want on a page. There’s no limit, neither upper or lower bound.”

Then later on, at the end of his answer, he reaffirmed that publishers are free to choose how they want to use the H1 heading tag:

“Your site is going to rank perfectly fine with no H1 tags or with five H1 tags.”

H1 Headings Useful for Communicating Page Structure

John Mueller confirmed that H1 headings are good for outlining the page structure.

What he means is that the heading elements can work together to create a top level outline of what your page is about. That’s a macro overview of what the web page is about.

In my opinion, a properly deployed heading strategy can be useful for communicating what a page is about.

The W3c, the official body that administers HTML guidelines, offers an HTML validator that shows you the “outline” of a web page.

When validating a web page, select the “Show Outline” button. It’s a great way to see a page just by the outline that your heading elements create.

show outline
Choosing the “Show Outline” option in the W3C HTML Validator will show you the overview of what your page looks like as communicated by your heading elements. It’s a great way to get a high level snapshot view of your page structure.

Here are Mueller’s comments about the H1 heading element:

“H1 elements are a great way to give more structure to a page so that users and search engines can understand which parts of a page are kind of under different headings.

So I would use them in the proper way on a page. And especially with HTML5 having multiple H1 elements on a page is completely normal and kind of expected.”

H1 Headings and SEO

John Mueller went on to reaffirm that the lack of a headings or using many H1s was not something to worry about. This is likely due to Google doesn’t need or require H1 headings to rank a web page.

This should be obvious to anyone who works in digital marketing. Google’s search results are full of web pages that do not feature H1 headings or that use them for styling purposes (a misuse of the heading tag!).

There are correlation studies that say that XX percentage of top ranked sites use headings. But those studies ignore that modern web pages, particularly those that use WordPress templates, routinely use Headings for styling navigational elements, which will skew those correlation studies.

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Here’s what Mueller observed:

“So it’s not something you need to worry about.

Some SEO tools flag this as an issue and say like Oh you don’t have any H1 tag or you have two H1 tags… from our point of view that’s not a critical issue.”

H1 Headings Useful for Usability

Mueller’s on a roll in this answer when he begins talking about heading tags in the context of usability.

I have found that, particularly for mobile, heading tags help make a web page easier to read. Properly planned headings help communicate what a web page is about to a user and visually helps break up a daunting page of text, making it easier to read.

Here’s what Mueller said:

“From a usability point of view maybe it makes sense to improve that. So it’s not that I would completely ignore those suggestions but I wouldn’t see it as a critical issue.”

Takeaways about Heading Tags

  1.  Use as many H1 heading elements as you like
  2. They are useful for communicating page structure to users and Google
  3. Heading elements are useful for usability

Updated: About Mueller’s Response

I read some feedback on Facebook that was critical of Mueller’s response. Some felt that he should have addressed more than just H1.

I believe that Mueller’s response should be seen in the context of the question that was asked. He was asked a narrow question about the H1 element and he answered it.

Technically, Mueller’s answer is correct. He answered the question that was put to him.  So I think  John should be given the benefit of that consideration.

However, I understand why some may say he should have addressed the underlying reason for the question. The person asking the question likely does not understand the proper use of heading elements.

If the person knew the basics of the use of heading elements, they wouldn’t have asked if it’s okay to drop H1 elements all over a web page. So that may have needed to be addressed.

Again, not criticizing Mueller, the context of his answer was focused on H1 elements.

The Proper Use of Heading Elements

I would add that the proper use of all the heading elements from (for example) H1 to H4 is useful. Nesting article sub-topics by using H2, H3 and sometimes H4 can be useful for making it clearer what a page is about.

The benefits of properly using H1 through H4 (your choice!) in the proper way will help communicate what the page is about which is good for bots and humans and will increase usability because it’s easier to read on mobile.

One way to do it is to use H1 for the main topic of the page then every subtopic of that main topic can be wrapped in an H2 heading element. That’s what I did on this article.

Should one of the subtopics itself diverge into a subtopic of itself, then I would use an H3.
Screenshot 1

 

 

 

 

 

 

 

 

Heading Elements and Accessibility

The heading elements also play an important role with making a web page accessible to site visitors who use assistive devices to access web content.

ADA Compliance consultant, Kim Krause Berg, offered these insights from the point of view of accessibility:

We use one H1 tag at the top to indicate the start of the content for assistive devices and organize the remainder from(H2-H6)similarly to how an outline would appear.

 The hierarchy of content is important for screen readers because it indicates the relationship of the content to the other parts of content.
Content under headings should relate to the heading. A bad sequence would be starting out with an(H3, then H1) 

Heading Elements are More than a Place for Keywords

Keyword dumping the heading tags can mask the irrelevance of content. When you stop thinking of heading tags as places to dump your keywords and start using them as headings that communicate what that section of the page is about, you’ll begin seeing what your page is really about. If you don’t like what you see you can rewrite it.

If in doubt, run your URL through the W3C HTML Validator to see how your outline looks!

Watch the Webmaster Hangout here:
https://youtu.be/rwpwq8Ynf7s?t=1427

[Source: This article was published in searchenginejournal.com By Roger Montti - Uploaded by the Association Member: Robert Hensonw]

Categorized in Search Engine

Friends, you're going to wish you were still making the scene with a magazine after reading this sentence: Google's web trackers are all up in your fap time and there's pretty much nothing (except maybe using a more secure browser like Firefox, read up on cybersecurity tips from the EFF, refusing to sign into a Google account and never going online without the protection of a VPN) that anyone can do about it.

From The Verge:

Visitors to porn sites have a “fundamentally misleading sense of privacy,” warn the authors of a new study that examines how tracking software made by tech companies like Google and Facebook is deployed on adult websites.

The authors of the study analyzed 22,484 porn sites and found that 93 percent of them leak data to third parties, including when accessed via a browser’s “incognito” mode. This data presents a “unique and elevated risk,” warn the authors, as 45 percent of porn site URLs indicate the nature of the content, potentially revealing someone’s sexual preferences.

According to the study, trackers baked up by Google and its creepy always-watching-you subsidiaries were found on over 74% of the porn sites that researchers checked out... for purely scientific reasons, of course. And the fun doesn't stop there! Facebook's trackers appeared on 10% of the websites and, for the discerning surveillance aficionado, 24% of the sites the researchers checked in on were being stalked by Oracle. According to The Verge, "...the type of data collected by trackers varies... Sometimes this information seems anonymous, like the type of web browser you’re using, or your operating system, or screen resolution. But this data can be correlated to create a unique profile for an individual, a process known as “fingerprinting.” Other times the information being collected is more obviously revealing like a user’s the IP address or their phone’s mobile identification number.

It's enough to give someone performance anxiety.

[Source: This article was published in boingboing.net By SEAMUS BELLAMY - Uploaded by the Association Member: Jay Harris]

Categorized in Search Engine

The Internet has made researching subjects deceptively effortless for students -- or so it may seem to them at first. Truth is, students who haven't been taught the skills to conduct good research will invariably come up short.

That's part of the argument made by Wheaton College Professor Alan Jacobs in The Atlantic, who says the ease of search and user interface of fee-based databases have failed to keep up with those of free search engines. In combination with the well-documented gaps in students’ search skills, he suggests that this creates a perfect storm for the abandonment of scholarly databases in favor of search engines. He concludes: “Maybe our greater emphasis shouldn’t be on training users to work with bad search tools, but to improve the search tools.”

His article is responding to a larger, ongoing conversation about whether the ubiquity of Web search is good or bad for serious research. The false dichotomy short-circuits the real question: “What do students really need to know about an online search to do it well?” As long as we’re not talking about this question, we’re essentially ignoring the subtleties of Web search rather than teaching students how to do it expertly. So it’s not surprising that they don’t know how to come up with quality results. Regardless of the vehicle--fee databases or free search engines--we owe it to our students to teach them to search well.

So what are the hallmarks of a good online search education?

SKILL-BUILDING CURRICULUM. Search competency is a form of literacy, like learning a language or subject. Like any literacy, it requires having discrete skills as well as accumulating experience in how and when to use them. But this kind of intuition can't be taught in a day or even in a unit – it has to be built up through exercise and with the guidance of instructors while students take on research challenges. For example, during one search session, teachers can ask students to reflect on why they chose to click on one link over another. Another time, when using the Web together as a class, teachers can demonstrate how to look for a definition of an unfamiliar word. Thinking aloud when you search helps, as well.

A THOROUGH, MULTI-STEP APPROACH. Research is not a one-step process. It has distinct phases, each with its own requirements. The first stage is inquiry, the free exploration of a broad topic to discover an interesting avenue for further research, based on the student's curiosity. Web search, with its rich cross-linking and the simplicity of renewing a search with a single click, is ideally suited to this first open-ended stage. When students move on to a literature review, they seek the key points of authority on their topic, and pursue and identify the range of theories and perspectives on their subject. Bibliographies, blog posts, and various traditional and new sources help here. Finally, with evidence-gathering, students look for both primary- and secondary-source materials that build the evidence for new conclusions. The Web actually makes access to many --

but not all -- types of primary sources substantially easier than it's been in the past, and knowing which are available online and which must be sought in other collections is critical to students’ success. For example, a high school student studying Mohandas Gandhi may do background reading in Wikipedia and discover that Gandhi's worldview was influenced by Leo Tolstoy; use scholarly secondary sources to identify key analyses of their acquaintance, and then delve into online or print books to read their actual correspondence to draw an independent conclusion. At each step of the way, what the Web has to offer changes subtly.

TOOLS FOR UNDERSTANDING SOURCES. Some educators take on this difficult topic, but it's often framed as a simple black-and-white approach: “These types of sources are good. These types of sources are bad.” Such lessons often reject newer formats, such as blogs and wikis, and privilege older formats, such as books and newspaper articles. In truth, there are good and bad specimens of each, and each has its appropriate uses. What students need to be competent at is identifying the kind of source they're finding, decoding what types of evidence it can appropriately provide, and making an educated choice about whether it matches their task.

DEVELOPING THE SKILLS TO PREDICT, ASSESS, PROBLEM-SOLVE, AND ITERATE. It's important for students to ask themselves early on in their search, “When I type in these words, what do I expect to see in my results?” and then evaluate whether the results that appear match those expectations. Identifying problems or patterns in results is one of the most important skills educators can help students develop, along with evaluating credibility. When students understand that doing research requires more than a single search and a single result, they learn to leverage the information they find to construct tighter or deeper searches. Say a student learns that workers coming from other countries may send some of their earnings back to family members. An empowered searcher may look for information on [immigrants send money home], and notice that the term remittances appears in many results. An unskilled searcher would skip over words he doesn't recognize know, but the educated student can confirm the definition of remittance, then do another search, [remittances immigrants], which brings back more scholarly results.

TECHNICAL SKILLS FOR ADVANCED SEARCH. Knowing what tools and filters are available and how they work allows students to find what they seek, such as searching by colordomainfiletype, or date. Innovations in technology also provide opportunities to visualize data in new ways. But most fundamentally, good researchers remember that it takes a variety of sources to carry out scholarly research. They have the technical skills to access Web pages, but also books, journal articles, and people as they move through their research process.

Centuries ago, the teacher Socrates famously argued against the idea that the written word could be used to transmit knowledge. This has been disproved over the years, as authors have developed conventions for communicating through the written word and educators have effectively taught students to extract that knowledge and make it their own. To prepare our students for the future, it's time for another such transition in the way we educate. When we don’t teach students how to manage their online research effectively, we create a self-perpetuating cycle of poor-quality results. To break that cycle, educators can engage students in an ongoing conversation about how to carry out excellent research online. In the long term, students with stronger critical thinking skills will be more effective at school, and in their lives.

[Source: This article was published in kqed.org By Tasha Bergson-Michelson - Uploaded by the Association Member: Patrick Moore]

Categorized in Search Engine

Overview | Do Internet search engines point us to the information that we need or confuse us with irrelevant or questionable information? How can Internet users improve their searches to find reliable information? What are some ways to perform effective searches? In this lesson, students conduct Web searches on open-ended questions and draw on their experiences to develop guides to searching effectively and finding reliable information online.

Materials | Computers with Internet access

Warm-Up | Invite students to share anecdotes about times when they used an Internet search engine to look for information and found something they were not expecting, or when they could not find what they were looking for.

After several students have shared, ask for a show of hands of students who have experienced frustration using an Internet search engine. Then ask: How often do you use search engines? Which ones do you use most? Why? What are the most common problems you face when searching? Do you consider yourself a skilled searcher? Do you have any search strategies? Do you search the Internet more for personal reasons and entertainment, or more for school? Do you believe that improving your Internet searching skills will benefit you academically? Socially? Personally?

Give students the following search assignment, from The New York Times article “Helping Children Find What They Need on the Internet”: “Which day [will] the vice president’s birthday falls on the next year?” (Alternatively, give students a multistep question that relates to your subject matter. For example, a geography teacher might ask “How many miles away is Shanghai?”) Tell students to type this question into Google, Bing or any other favorite search engine, and have them share the top results in real-time. Did the answer appear? If not, what’s the next step to take to get this question answered?

Ask: What information do you need to be able to answer the question? Ideas might include the name of the vice president, the date of his birthday, and a copy of next year’s calendar. Have them try to find this information and keep working until they can answer the question. (You may want to add a competitive component to this activity, rewarding the student who finds out the right answer the fastest.)

When one or more students have found the answer, have one student take the class through the steps he or she took to find the answer; if possible, do this on a screen so that everyone can watch. Along the way, ask probing questions. What keywords did you type into the search engine? Why did you choose these words? Which results did you click on? Why did you choose those sources over the others on the page? How many steps did it take? Are you sure the sources are reliable and that the answers are correct? How can you tell? How would you verify the information? If time permits, play around by using different keywords and clicking on different results, to see how the search for the answer to the question changes.

To end this activity, ask: What did you notice about the search to find the answer to this question? Did this exercise give help you understand something new about Internet searching? If so, what?

When considering children, search engines had long focused on filtering out explicit material from results. But now, because increasing numbers of children are using search as a starting point for homework, exploration or entertainment, more engineers are looking to children for guidance on how to improve their tools.

Search engines are typically developed to be easy for everyone to use. Google, for example, uses the Arial typeface because it considers it more legible than other typefaces. But advocates for children and researchers say that more can be done technologically to make it easier for young people to retrieve information. What is at stake, they say, are the means to succeed in a new digital age.

Read the article with your class, using the questions below.

Questions | For discussion and reading comprehension:

  1. What problems does the article mention that children run into when they use search engines?
  2. What suggestions have been offered for how search engines can improve their product to lessen children’s problems searching?
  3. Do you search using keywords or questions? How does the article characterize these two types of searching?
  4. Have you tried using images or videos to search? How does the article characterize this type of searching?
  5. What advice would you give to Internet search engine developers for how they should improve their product? Do you think any of the improvements mentioned in the article are particularly promising? Why?

Activity | Before class, ask teachers of several different subjects for questions that they have asked or will ask students to research on the Internet. Alternatively, collect from students their own research questions – for another class or for a personal project, like I-Search. Be sure that the questions are sufficiently open-ended so that they cannot be answered definitively with a quick, simple search – they might contain an element of opinion or interpretation, rather than just be a matter of simple fact.

Put the class into pairs, and provide each pair with the following multipart task:

  • Seek to answer your assigned question by conducting an Internet search.
  • You must use different search engines and strategies, and keep track of how the search “goes” using the various resources and methods.
  • Once you find an answer that you are confident in, do another search to verify the information.
  • When you are finished, evaluate the reliability of all of the Internet resources that you used.
  • Prepare to tell the story of your search, including what worked and what didn’t, anything surprising that happened, things that would be good for other searchers to know, “lessons learned,” etc.

Provide pairs with the following resources to research their assigned topics. Let them know that these are starting points and that they may use additional resources.

Search Engines, Metasearch Engines, and Subject Directories:

Choosing Effective Search Words:

Evaluating Source Reliability:

When pairs have completed their research, bring the class together and invite pairs to share their stories. Then tell them that they will use their notes to create a page for a class guide, in booklet or wiki form, on how to use Internet search engines effectively for research, to be made available to the school community to help other students. As much as possible, the tips and guidance in the guide should be illustrated with the students’ stories and examples.

Tell students that their booklet/wiki entries should or might include the following, among other types of guidance and insight:

  • Ways and examples of using keywords and Boolean logic effectively.
  • Ineffective examples of keyword searches that result in too much, too little or useless information.
  • Examples of how to sequence searches and why.
  • Sites they find that answer their question and how they can tell whether these pages are reliable.
  • Any information they found that was questionable or incorrect, where they found it, and how they discovered that it was wrong.
  • Why it is important to scroll past the top result to pages listed farther down the page or on a later page in order to find complete answers to the question.
  • How using different search engines yielded different results.

In addition to the handbook or wiki, you might also have students make their own videos, à la the Google ad “Parisian Love,” chronicling their search.

Going Further | Students read the New York Times Magazine article “The Google Alphabet,” by Virginia Heffernan, who writes the column “The Medium,” and keep a tally of the number of advertisements and commercial sites that they see while doing schoolwork on the Internet for one or two days.

Then hold a class discussion on advertising and commercial interests on the Internet. If students are using the Internet to complete their homework, are schools requiring students to expose themselves to corporate advertisements in order to succeed academically? Do any ethical questions arise around the prevalence of corporate advertising in Web searching for academic purposes?

Alternatively or additionally, students develop ideas for the search engines of the future, like ways to use and find images, audio and video, rank results and so on, and “pitch” their ideas to classmates acting as search engine developers.

And for fun, students might try to come up with “Googlewhacks.”

Standards | From McREL, for Grades 6-12:

Technology
2. Knows the characteristics and uses of computer software programs.
3. Understands the relationships among science, technology, society, and the individual.

Language Arts
1. Demonstrates competence in the general skills and strategies of the writing process.
4. Gathers and uses the information for research purposes.
7. Uses reading skills and strategies to understand and interpret a variety of informational texts.

Life Work
2. Uses various information sources, including those of a technical nature, to accomplish specific tasks.

[Source: This article was published in nytimes.com By Sarah Kavanagh And Holly Epstein Ojalvo - Uploaded by the Association Member: Rene Meyer]

Categorized in Search Engine

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