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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

Understanding the impact of machine learning will be crucial to adjusting our search marketing strategies -- but probably not in the way you think. Columnist Dave Davies explains.

There are many uses for machine learning and AI in the world around us, but today I’m going to talk about search. So, assuming you’re a business owner with a website or an SEO, the big question you’re probably asking is: what is machine learning and how will it impact my rankings?

The problem with this question is that it relies on a couple of assumptions that may or may not be correct: First, that machine learning is something you can optimize for, and second, that there will be rankings in any traditional sense.

So before we get to work trying to understand machine learning and its impact on search, let’s stop and ask ourselves the real question that needs to be answered:

What is Google trying to accomplish?

It is by answering this one seemingly simple question that we gain our greatest insights into what the future holds and why machine learning is part of it. And the answer to this question is also quite simple. It’s the same as what you and I both do every day: try to earn more money.

This, and this alone, is the objective — and with shareholders, it is a responsibility. So, while it may not be the feel-good answer you were hoping for, it is accurate.

Author:  Dave Davies

Source:  http://searchengineland.com/heck-machine-learning-care-265511

Categorized in Others

Everyone has the ability to learn a life-changing skill not just this year, but in the next 6 months.

By life-changing, I mean something that can have a positive impact in your life moving forward, even if it’s something you can’t envision today. Certain skills we can immediately reap the benefits of, while others will be life-changing when we least expect it.

In this article, we’ll share 8 life-changing skills you can learn in 6 months, where you can learn them, and how you can get started today.

1. Speed reading

Bill Gates has been known to state that if he had one superpower, it would be the ability to read faster. What Bill and the rest of the mega-successful understand is that knowledge is power. The ability to process information faster from books, articles, and reports is what will help us learn faster, and therefore improve each aspect of our life faster as well.

Where you can start learning: Speed reading courses are becoming more popular, as more people realize how important it is with the limited time we have. You can check out free courses like Read Speeder or you can start learning how to use Spritzlet, which allows you to speed read articles online with a browser extension.

xl_Spritz

2. Public speaking

Research shows that people fear public speaking more than death itself. There’s something terrifying about being in front of dozens or hundreds of people, and exposing yourself completely. It’s when you’re most vulnerable, but learning how to public speak is a life-changer.

Warren Buffett has given advice to recent graduates that the number one skill you can have to succeed is public speaking skills. Everything from communication, confidence, and sales is developed when you develop your public speaking skills.

Where you can start learning: Luckily, there are great communities out there like Toastmasters that organize local meetups all around the world. You’ll find amazing public speakers that are looking to get to the next level to beginners that are just getting started. Check out Toastmasters’ website here.

ProSolutions National 2006

3. Spanish

As the third most spoken language in the world, the ability to speak Spanish will allow you to reach over 500M people around the world. No matter where you live, knowing how to speak Spanish is becoming increasingly more important, with the Hispanic population and economy spreading quickly worldwide. If you’re living in the US, this is even more important, with over 30% of the population being Hispanic.

Spanish is also on this list, because it’s one of the easiest languages to learn. Sure, Mandarin is an important language to learn, but it’s an incredibly difficult one to learn. If we were to measure the level of importance and the time to learn for all the languages available, Spanish would make it to the top of the list.

One of the biggest reasons why people never reach fluency in any foreign language is: using the wrong method, and lack of time. In this free course on how to learn a new language in 90 days, there’s proven research which points out how humans best learn.

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It turns out that humans retain only 5% of what we learn from lectures, 20% of what we learn from apps (visual cues), and 90% of what we learn from immediate immersion. Yet, how do 90% of learn a new foreign language? Language schools (lectures), books, Duolingo (apps), etc that don’t provide the real-life immersion required for our brains to learn faster.

Where to get started: If you want the most effective way to learn a language, learning from real-life interactions is the best way to do it. There are great websites like Rype, which offers Spanish coaching for busy people, solving the issue of lack of time and bringing real-life immersion to your screen. With Rype, you can book as many lessons as you want, at any time of the day, any day of the week, allowing you to fit it into your schedule, no matter how busy you are.

Rype

4. Accounting

If you’re looking to get into business, accounting is one of the core fundamentals you’ll need to succeed. While you don’t need to be an expert, you definitely should understand the basics.

This skill can also be used to manage your personal finances, to meet your financial goals, and having more control over your life.

Where to get started learning: If you didn’t learn accounting in school, no worries. You can either teach yourself using books, or check out free accounting courses online.

taxes-accounting-business

5. Microsoft Excel

Most people reading this probably have a basic understanding of Microsoft Excel Spreadsheet. While this is a good start, there are so many powerful functionalities that are hidden, which could make your life a lot easier.

Excel is also a great asset to have whenever you’re looking for a job, as many corporations rely on Excel to organize and manage multiple parts of the business.

Where to get started learning: With the popularity of Excel, you can find tons of free resources and videos online to learn. Check out Excel ExposureLynda, and Excel with Business.

6. Blogging/Vlogging

Blogging is a powerful tool if you want to spread your ideas, build your brand, or grow your business. Since it was introduced, blogging has taken on a life of its own, and today there are ~2M blog posts being written on a daily basis.

Where to get started learning: Anyone can start blogging today. All you need is a content-management system like WordPress, which is completely free. Personally, I think the best way to start learning how to blog is to just start writing. There are techniques you can learn on how to promote your blog, but the best way to grow your blog is to write great content.

7. Weight training

Yes, weight training is a skill. It’s not as advanced as learning how to code, nor will it take as long as learning a new language, if you just want to learn the basics.

We’re not promising that you’ll get a body like Arnold Schwarzenegger, but you will see much faster results for whatever goal you have, just by understanding how to workout properly. And of course, when you’re dealing with an activity that involves physical strain, you’ll always want to caution yourself.

Where to get started learning: There are amazing body builders that are sharing all of their secrets for free on Youtube. You can check out Bodybuilding.com’s Youtube channel to get started.

Weight-Training

8. Photo and video editing

In the digital world that we live in, from Youtube, Instagram, and Facebook, there is no avoiding photos and videos. In fact, social media has increasingly gone away from text sharing and almost everything to photo and video editing.

Where to get started learning: For photo editing, you can use Photoshop. For video editing, you can use iMovie or Final Cut Pro. Keep in mind, there are dozens of editing software tools for video and photo editing, but what’s more important are your editing skills, not the tool itself.

Check out education websites like CreativeLIVE or Skillshare, where you can learn from experts themselves on how to best use design and software tools.

photoshop_3d_lights1

Author:  Sean Kim

Source:  http://www.lifehack.org/384473/10-life-changing-skills-you-can-learn-less-than-6-months

Categorized in Others

While robots and computers will probably never completely replace doctors and nurses, machine learning/deep learning and AI are transforming the healthcare industry, improving outcomes, and changing the way doctors think about providing care.

Machine learning is improving diagnostics, predicting outcomes, and just beginning to scratch the surface of personalized care.

Imagine walking in to see your doctor with an ache or pain. After listening to your symptoms, she inputs them into her computer, which pulls up the latest research she might need to know about how to diagnose and treat your problem.  You have an MRI or an xray and a computer helps the radiologist detect any problems that could be too small for a human to see. Finally, a computer looks at your medical records and family history and compares that with the best and most recent research to suggest a treatment protocol to your doctor that is specifically tailored to your needs.

Industry analysts IDC predict that 30 percent of providers will use cognitive analytics with patient data by 2018.  It’s all starting to happen, and the implications are exciting.

Diagnosis

CBI insights identified 22 companies developing new programs for imaging and diagnostics. This is an especially promising field into which to introduce machine learning because computers and deep learning algorithms are getting more and more adept at recognizing patterns — which, in truth, is what much of diagnostics is about.

An IBM-backed group called Pathway Genomics is developing a simple blood test to determine if early detection or prediction of certain cancers is possible.

Lumiata has developed predictive analytics tools that can discover accurate insights and make predictions related to symptoms, diagnoses, procedures, and medications for individual patients or patient groups.

Treatment

IBM’s Watson has been tasked with helping oncologist make the best care decisions for their patients.  The Care Trio team has developed a three-pronged approach that helps doctors devise and understand the best care protocols for cancer patients.

The CareEdit tool helps teams create clinical practice guidelines that document the best course of treatment for different types of cancers. CareGuide uses the information from CareEdit into a “clinical decision support system” to help doctors choose the right treatment plan for an individual patient. And CareView is an analysis tool that can evaluate the outcome of past clinical decisions and identify patients who received different treatments than the recommendations. This kind of retrospective can help doctors refine their guidelines, closing the circle back to the CareEdit tool.

The team hopes that the Care Trio will improve clinical outcomes and increase survival rates for cancer patients while still reducing treatment costs for providers. The first version is currently being deployed at a large cancer treatment center in Italy.

In a completely different field, Ginger.io is developing an app to remotely deliver mental health treatments. The app allows people to analyze their own moods over time, learn coping strategies that have been developed by doctors, and access additional support as needed.

Follow up care

But the advances don’t stop with diagnosis or treatment.

One of the biggest hurdles in health care is hospital readmittance. Doctors around the world struggle with how to keep their patients healthy and following their treatment recommendations when they go home.

AiCure is using mobile technology and facial recognition technologies to determine if a patient is taking the right medications at the right time to help doctors confirm that the patient is taking their medications and alert them if something goes wrong.

NextIT is developing a digital health coach, similar to a virtual customer service rep on an ecommerce site. The assistant can prompt questions about the patient’s medications and remind them to take the medicine, ask them about symptoms, and convey that information to the doctor.

The Caféwell Concierge app uses IBM’s Watson’s natural language processing (NLP) to understand users health and wellness goals and then devise and provide the right balance of nudges and alerts so users can meet their targets and the app can reward them.

And this is just the beginning.  As these technologies develop, new and improved treatments and diagnoses will save more lives and cure more diseases. The future of medicine is based in data and analytics.

Source : http://www.forbes.com/

Categorized in Online Research

Majorities of Americans think local libraries serve the educational needs of their communities and families pretty well and library users often outpace others in learning activities. But many do not know about key education services libraries provide

As a rule, libraries’ performance in learning arenas gets better marks from women, blacks, Hispanics, those in lower-income households, and those ages 30 and older.

Majorities of adults say their local libraries are serving the educational needs of their communities and their own families at least ‘pretty well’

At the same time, many do not know that libraries offer learning-related programs and materials such as e-books, career and job resources, and high school certification courses.

Library users think of themselves as lifelong learners

Additionally, these views arise in a context where strong majorities of adults consider themselves “lifelong learners” and libraries around the country are working to fit their programs and services into local educational ecosystems – both the formal parts of it (such as schools) and the informal parts of it (such as “do it yourself” learning opportunities). Arecent Pew Research report found that 73% of adults say the label “lifelong learner” applies “very well” to them. Additionally, 74% of adults have participated in personal learning experiences of various kinds in the previous 12 months – we call them personal learners.And 63% of full- and part-time workers have taken courses or done training on the job to improve their skills in the past year – we called them professional learners.

Recent library users overwhelmingly embrace those ideas and activities. Fully 97% of those who used a library or bookmobile in the past 12 months say that the term “lifelong learner” applies “very well” or “pretty well” to them and a similar share of library website users (98%) also strongly identified with being lifelong learners.

Moreover, 84% of those who visited a library in the past 12 months fit our definition of personal learner, compared with 66% of those who had not recently visited a library or bookmobile. Recent library users are more likely than others to read “how to” publications, take courses related to personal interests, attend learning-related events and meetings, and take online courses.

Interestingly, among workers, recent library users are no more likely than others to fall into the category of professional learners.

Library usage continues to evolve

Use of libraries drifts down, while use of library websites levels offIn addition to examining the role of libraries as contributors to people’s learning, this survey also continued the Center’s benchmarking of library usage. Some 78% of adults say they have ever gone to a library, while 44% say they went to a library or bookmobile in the past 12 months.

The findings indicate a downward drift in the number of those who use physical library facilities in any given year. In our first survey on this in November 2012, 53% of adults had visited a library or bookmobile in the past 12 months.

Over the same period, the use of library websites has leveled off. In 2013, 30% of adults had used a library website over the past 12 months, while the new finding is that 31% have done so in the past year. Additionally, we found that 9% of adults had used a library-related app in the past 12 months – a first time reading for this question.1

Notable shares of Americans do not know that libraries offer learning-related programs and materials

Many do not know if their local libraries offer key learning and education resources A significant number of libraries have added education- and learning-related material, often in digital form or available on the internet. This survey shows that a portion of adults are aware of those activities, but many do not know about them, including:

E-book borrowing: Fully90% of public libraries have e-book lending programs, according to Information Policy and Access Center (IPAC) at the University of Maryland, and 62% of adults say they know that their local libraries have such programs. At the same time, 22% say they do not know whether e-book lending is done by their libraries and another 16% say it is not done by their community libraries.

Online career and job-related resources: Some 62% of local libraries offer such resources, according to IPAC, and 41% of adults in our survey say they know their local libraries have such material. Still, 38% say they do not know if such resources are offered by their local libraries and another 21% say their libraries do not offer career- and job-related resources.

Online GED or high school equivalency classes: Some 35% of local libraries offer GED prep courses and materials, according to IPAC, and 26% of adults say they know their local libraries offer such programs. Yet nearly half (47%) say they do not know if such programs are offered by their local libraries and another 27% say these kinds of classes are not available in their communities.

Programs on starting a new business: Some 33% of local libraries offer such programs, according to IPAC, and 24% of adults say their local libraries offer programs on starting a new business. About half (47%) say they do not know if their local libraries do that and another 28% say their public libraries do not offer programs for starting a new business.

Online programs that certify that people have mastered new skills: 24% of adults say their local libraries offer such programs. However, about half of adults (49%) say they do not know if such programs are being offered and another 27% say they are not offered by their local libraries. There are no data about how many libraries offer such programs.

 

1. Library users and learningsx

Adults who use libraries and visit library websites are often ahead of the crowd when it comes to being learners, engaging with information and embracing technology.

Fully 97% of those who visited a library or bookmobile in the past 12 months say the assertion “I think of myself as a lifelong learner” applies to them “very well” or “somewhat well.” And 98% of those who have used a library website in the past year feel the same way.

A recent Pew Research Center report about lifelong learning and technology found that 74% of adults participate in learning activities that make them “personal learners.” That is, they had done at least one of several activities, such as reading how-to materials or taken courses in pursuit of learning more about personal interests or hobbies in the past 12 months.

Some 23% of personal learners have pursued those interests at libraries in the past 12 months. The personal learners who are among the most likely to have used libraries for these kinds of enrichment activities include those in households earning less than $50,000 (29% of the personal learners have done so), those ages 65 and older (30% of this cohort have done so) and women (27% of the personal learners in this cohort have done so).

In our earlier report, it was also noted that 63% of those who are working (either full time or part time) are “professional learners,”2 those who said in the past 12 months they had participated in job-related learning activities that either upgraded their skills or prepared them for new jobs. That amounts to 36% of the entire adult population. Some 9% of professional learners have pursued their classes or training at libraries.

It is often the case that library users are more likely than others to pursue a variety of learning experiences in all kinds of venues and formats and to say they have reaped benefits from those learning activities. The rest of this chapter will provide the latest data about who uses libraries, library websites and library mobile apps and then will examine the ways in which library users – as learners – participate in learning activities and profit from them.

The number of those visiting library buildings is trending down, while the number of library website users has leveled off

Use of libraries drifts down, while use of library websites levels offThis survey finds that 78% of adults have ever gone to a library, while 44% say they went to a library or bookmobile in the past 12 months. The findings indicate a downward drift in the number of those who use physical library buildings in any given year. In November 2012 when Pew Research Center began tracking library usage, 53% of adults said they had used a library or bookmobile in the past 12 months. And the numbers have moved lower since then.

Over the same period, the use of library websites has leveled off. In 2012, 25% of adults had used a library website over the past 12 months, and the new finding is that 31% have done so in the past year.3

Fully 84% of those who visited a library in the past 12 months are personal learners, which compares with 66% of those who visited a library less recently or who have never been to a library. And 86% of those who visited a library website in the past year can be categorized as personal learners, compared with 69% of other adults.

In addition to asking about use of the library buildings and library websites, we asked a separate and new question in this survey about use of library apps. While 12% of adults said they have used one at some point in their lives, some 9% said they have used a library app in the past 12 months. Overall, in the past 12 months, 50% of adults interacted with a library through its facility, website or app.

Those who use libraries and their digital materials are more likely to be parents of minors, women, under age 50, and better educated

When it comes to the demographic traits of library users, this survey’s findings parallel previous patterns the Center has documented. Those who have visited a library or bookmobile in the past 12 months are more likely to be women, parents of minor children and those with higher levels of education. Younger adults ages 18 to 29 are more likely than their elders to have used libraries during the previous year. And those less likely to have recently visited a library include Hispanics and those who live in rural areas.

The same basic patterns hold for those who have used a library website in the past 12 months. When it comes to people’s use of mobile apps offered in connection with libraries, people’s level of education is the most noteworthy demographic difference tied to usage.

Women, young adults, higher-educated adults and parents are among the most likely to have visited libraries and used library websites

Library users self-identify as lifelong learners and as people interested in new information

Library users are more likely to describe themselves as ‘lifelong learners’Fully 79% of those who have used a library or bookmobile in the past 12 months say the statement “I think of myself as a lifelong learner” describes them “very well.” Another 18% say the statement describes them “somewhat well.” That compares with 69% of those who did not use a library in the past 12 months who think the label of lifelong learner apply “very well” to them.

Similarly, library users are more likely than others to agree with the statements that 1) they like to gather as much information as they can when they come across something unfamiliar and 2) they often find themselves looking for new opportunities to grow as a person.

Library users are also somewhat more likely to think that all people should be in a learning posture in at least some domains. For instance, those who have visited a library in the past 12 months are more likely than those who haven’t to think it is “very important” for people to make an effort to learn new things about their local community (73% vs. 68%) and to learn new things that are happening in society, such as developments in science, technology, entertainment or culture (74% vs. 65%).

Library users are major technology adopters

Library users are more likely to be digital technology usersPeople who used a library or bookmobile in the past year are more likely than non-library users or less-recent users to be technology users.

  • Internet – 93% of those who used a library or bookmobile in the past 12 months are internet users.
  • Smartphones – 76% of those who used a library or bookmobile in the past 12 months are smartphone users.
  • Home broadband – 74% of those who used a library or bookmobile in the past 12 months are home broadband users.
  • Social media – 74% of those who used a library or bookmobile in the past 12 months are social media users.

The same gaps in digital technology adoption appear between users and non-users when it comes to those who have used a library website or used a library app during that time period.

Library users stand out as ‘personal learners’

Library users are more likely to pursue personal learning activitiesThe Center identified personal learners by asking questions about a variety of activities related to personal enrichment and pursuits and found that those who visited libraries or used library websites in the past year stand apart from others in each of the pursuits queried.

The same patterns also apply when comparing those who have used public library websites or mobile apps in the past 12 months with those who have not.

Library users use various locales for enrichment when they pursue personal learningWhen it comes to where people pursue their personal interests, more recent library users are not only more likely to use libraries for personal learning, but they also are more likely to use several other locales. In the nearby chart, the only place where there is no statistically meaningful difference between those who have visited a library in the past 12 months and those who have not involves using the internet for personal learning.

The 74% of adults who fit our description of personal learners were asked about several possible reasons they might pursue these informal educational activities, and those who had used the library in the past 12 months stood apart from others for several of those reasons:

  • 84% of the personal learners who had visited a library or bookmobile in the past 12 months said they wanted to learn something that would make their life more interesting or full. That compares with 76% of the personal learners who had not recently used a library who felt that way.
  • 67% of the personal learners who had recently visited a library said they wanted to learn something that would allow them to help others more effectively. Some 60% of those who had not recently visited a library cited that as a motive.

Recent library users did not show significant differences with others when it comes to other possible reasons for being a personal learner. Some 60% of all personal learners said they pursued these interests in the past 12 months because they had some extra time on their hands; 36% said they wanted to turn their hobby into something that generated income; and 33% said they wanted to learn things that would help them keep up with the schoolwork of their children, grandchildren or other kids in their lives.

Recent library users are more likely to cite benefits from personal learning than others

Library users are more likely to cite positive impacts from personal learningAsked about some potentially helpful or satisfying outcomes from the personal learning they had done in the past 12 months, those who had visited a library in the past 12 months were more likely to say their personal learning had a notable impact. That means library users were more likely to say their personal learning experience helped them feel more capable; opened up new perspectives about their lives; helped them make new friends; made them feel more connected to their local community; and got them more involved in volunteer activities.

The same patterns about impact also apply when comparing those who have used public library websites or mobile apps in the past 12 months with those who have not.

The Center did not ask the kind of follow-up questions that could explain these differences. It is possible they arise from the fact that recent library users are somewhat more civically oriented than others. It also might stem from the fact that library users feel more enthusiastic about learning, as a rule.

Those who use library websites are more likely to be professional learners in many contexts

At the same time Pew Research Center identified personal learners through questions about activities that might lead to individual enrichment, the Center also identified professional learners by asking questions about whether those with full- or part-time jobs had taken a class or gotten extra training in the past 12 months. Overall, 63% of working Americans (or 36% of all adults) fit the definition of “professional learners,” and they got that extra knowledge:

  • To learn, maintain or improve job skills
  • For a license or certification needed for a job
  • To help get a raise a promotion at work
  • To help get a new job with a different employer
  • Because they were worried about possible downsizing where they work

Library website users are more likely than others to have participated in professional learning for several purposesThose who had visited a library or bookmobile in the past 12 months were not significantly more likely than others to do any of the job-related learning or training activities. However, those who had used library websites in the past 12 months were more likely to have done them than others. This might be a consequence of workers being more likely than non-workers to be internet users and that the materials at libraries can be relatively reasonably accessible via the library website.

As noted above, 13% of professional learners got their training or pursued their skills development at a library. The one statistically significant difference on this issue involved Hispanic professional learners. Some 16% of Hispanic professional learners got some work-related training at a library, compared with 8% of whites and 9% of blacks who are professional learners. Otherwise, there were no notable demographic distinctions among those who did their job-related learning at the library.

When it comes to the impact of job- or professional-training activities, the professional learners who also used the library within the past 12 months were more likely than others to say this extra learning:

  • Expanded their professional network: 69% of the professional learners who also were recent library users said their job-related learning expanded their professional network. That compares with 62% of others who said they got this benefit.
  • Helped them advance within their current company or organization: 52% of the professional learners who had recently used the library say their job-related learning helped them advance with their current employer. That compares with 43% of the professional learners who not recent library users.

There were no differences among the professional learners who were also recent library users when it came to two other possible impacts of their new learning: 1) enabling them to find a new job inside or outside their current organization (29% of all professional learners got that benefit) and 2) helping them consider a different career path (27% of all professional learners got that benefit).

2. How people view libraries as part of community educational systems

Substantial majorities of Americans are serving the needs of their communities and their own families at least pretty well.

Some 37% say their local libraries serve the needs of their communities “very well” and another 39% say “pretty well.” At the same time, 34% say their local libraries serve them and their families “very well” and 36% say “pretty well.” While the share is small for those who fell negatively about how libraries are performing in their local education scene, it is worth noting that 12% said they “don’t know” when the question involves libraries and community education systems and 7% said “don’t know” when the issue is about how libraries are serving their own needs and those of their families.

Majorities of adults say their local libraries are serving the educational needs of their communities and their own families at least ‘pretty well’

Those who use libraries feel relatively satisfied with their performance in learning situations, particularly women, blacks, Hispanics, those in lower-income households and those ages 30 and older

Women, minorities, those in poorer households, and those ages 30 and over are more likely to say libraries serve their needs ‘very well’There are pronounced differences among various groups when it comes to the most positive responses on these questions. Those who have visited a library or bookmobile in the past 12 months are more likely than others to say libraries are performing “very well” when it comes to educational services, as are those who self-identify as “lifelong learners.”

In addition, as a rule, libraries’ performance in learning arenas gets better marks from women, blacks, Hispanics, those in lower-income households, and those ages 30 and older. This next section will sort through that material, especially focusing on people who answered that libraries perform “very well” for their communities and their own families:

Library users: Those who have visited a library or bookmobile in the past 12 months and those who have used library websites are more positive about the way libraries fit into community educational ecosystems and the way they serve respondents and their families. Some 45% of recent library visitors say their local library meets their communities’ education needs “very well,” compared with 31% of those who were not recent library visitors who feel that way. Similarly, 45% of recent library users say libraries serve the educational needs of them and their families “very well,” compared with 26% of those who have not visited a library in the past year.

Lifelong learners: Those who say that the term “lifelong learner” applies “very well” to them are also more likely than others to say libraries are doing well in serving their community and personal needs. Some 39% of lifelong learners say libraries are doing “very well” in serving their communities’ learning and educational needs, compared with 32% of those who do not define themselves as lifelong learners. In addition, 37% of lifelong learners say libraries serve the educational activities of them and their families “very well,” compared with 27% of others who say that.

Personal learners and professional learners: Interestingly, there are not major differences between personal learners and others and professional learners and others in their responses to both questions about libraries and their communities and libraries and their families. Personal learners are a bit more likely than others to say libraries do “pretty well” at serving their communities’ educational needs (42% vs. 33%) and “pretty well” at serving the educational needs of them and their families (38% vs. 31%). However, there are not differences either among professional learners and others as well as personal learners and others when it comes to those who say libraries do “very well” at both tasks.

Women: Women are more likely than men to be library users and women are also more likely to have the most positive views about the role of libraries in community and personal learning activities. Some 41% of women believe that their public libraries serve the learning and educational needs of their communities “very well,” compared with 34% of men who believe that. Similarly, 38% of women say their public libraries serve the educational needs of themselves and their families “very well,” compared with 31% of men.

Race and ethnicity: African-Americans and Hispanics are more likely than whites to say that libraries serve the learning and education needs of their communities “very well.” Some 45% of both minority groups say that, while 34% of whites support that idea. Meanwhile, whites are more likely than others to say libraries serve community education needs “pretty well.” In addition, 43% of blacks and 42% of Hispanics say that libraries serve the learning and educational needs of them and their families “very well,” compared with 32% of whites who say that. Again, whites are more likely to say libraries serve their personal educational needs “pretty well.”

Lower income: Those living in households earning less than $50,000 are more likely than those in higher-income households to say that libraries serve community learning needs “very well”: 40% of those in lower-income households say that, compared with 32% of those in households earning $50,000 or more. Similarly, 38% of those in households earning less than $50,000 say libraries serve their and their families’ learning and educational needs “very well,” compared with 31% of those living in higher-income households.

Those over age 30: Those ages 30 and older are somewhat more likely than young adults to have the most positive views about how libraries serve the learning interests of their patrons and communities: 27% of those ages 18 to 29 say libraries serve the educational needs of their communities “very well,” compared with 40% of those ages 30 and older. Similarly, 29% of young adults say they believe libraries have served the educational needs of themselves and their families “very well,” compared with 36% of those ages 30 and over who say that.

Notable shares of Americans do not know that libraries offer learning-related programs and materials

Many do not know if their local libraries offer key learning and education resources A significant number of libraries have added education- and learning-related material to their archives and their program offerings, often in digital form or available on the internet. This survey shows that some Americans are aware of these activities, but many do not know about them or believe they are not available in their communities:

  • E-book borrowing: Fully90% of public libraries have e-book lending programs, according to Information Policy and Access Center (IPAC) at the University of Maryland, and 62% of adults say they know that their local libraries have such a program. At the same time, 22% say they do not know whether e-book lending is done by their libraries and another 16% say it is not done by their community libraries.Among those most likely to say they do not know if their local libraries lend e-books: men, rural residents and those without college degrees. Among those most likely to say their local libraries do not lend e-books: blacks, Hispanics, people living in households earning less than $30,000 and non-internet users.
  • Online career and job-related resources: Some 62% of local libraries offer such resources, according to IPAC, and 41% of adults say in our survey they know their local libraries have such material. Still, 38% say they do not know if such resources are offered by their local libraries and another 21% say their libraries do not offer career- and job-related resources.Among those most likely to say they do not know if their local libraries have resources for jobs and careers: whites, those with less than college degrees and those living in households earning $50,000 or more. Among those most likely to say their local libraries do not have career-related resources: men, blacks, Hispanics, people living in households earning less than $30,000, and those whose education stopped with a high school diploma.
  • Online GED or high school equivalency classes: Some 35% of local libraries offer GED prep courses and materials, according to IPAC, and 26% of adults say they know their local libraries offers such programs. Yet nearly half (47%) say they do not know if such programs are offered by their local libraries and another 27% say these kinds of classes are not available in their communities.Among those most likely to say they do not know if their local libraries provide GED classes: whites, those with at least some college experience and those in households earning $50,000 or more. Among those most likely to say their local libraries do not offer high school equivalency classes: blacks, Hispanics, adults under age 30, those with high school diplomas or less and suburban residents.
  • Programs on starting a new business: Some 33% of local libraries offer such programs, according to IPAC, and 24% of adults say their local libraries offer such programs. About half (47%) say they do not know if their local libraries do that and another 28% say their public libraries do not offer programs for starting a new business.Among those most likely to say they do not know if their local libraries provide programs for starting a new business: whites, those with some college experience and those in households earning $50,000 or more. Among those most likely to say their local libraries do not offer programs for starting a new business: blacks, Hispanics, adults under age 30, those with high school diplomas or less and suburban residents.
  • Online programs that certify that people have mastered new skills: Some 24% of adults say their local libraries offer such programs. However, about half of adults (49%) say they do not know if such programs are being offered and another 27% say they are not offered by their local libraries. There are no data about how many libraries offer such programs.Among those most likely to say they do not know if their local libraries provide programs that certify that people have mastered new skills: women, whites, those ages 30 and older, those with college experience and those in higher-income households. Among those most likely to say their local libraries do not offer certification programs: men, blacks, Hispanics, adults under age 30, and those with high school diplomas or less.

 

Acknowledgments

This report was made possible by The Pew Charitable Trusts, which received support for the project through a grant from the Bill & Melinda Gates Foundation. It is a collaborative effort based on the input and analysis of the following individuals:

Primary researchers

Lee Rainie, Director, Internet, Science, and Technology Research
Andrew Perrin, Research Assistant
John Horrigan, Senior Researcher

Research team

Maeve Duggan, Research Associate
Aaron Smith, Associate Director, Research
Claudia Deane, Vice President, Research
Margaret Hefferon, Research Assistant

Editorial and graphic design

Margaret Porteus, Information Graphics Designer       

Communications and web publishing

Shannon Greenwood, Assistant Digital Producer
Dana Page, Senior Communications Manager

Methodology

The Educational Ecosystem 2015 Survey, sponsored by Pew Research Center, obtained telephone interviews with a nationally representative sample of 2,752 adults living in the United States. Interviews were conducted via landline (nLL=963) and cellphone (nC=1,789; including 1,059 without a landline phone). The survey was conducted by Princeton Survey Research Associates International (PSRAI). The interviews were administered in English and Spanish by Princeton Data Source, LLC from Oct. 13 to Nov. 15, 2015. Statistical results are weighted to correct known demographic discrepancies. The margin of sampling error for the complete set of weighted data is ±2.1 percentage points. For results based on Internet users4 (n=2,428), the margin of sampling error is ±2.3 percentage points.

Details on the design, execution and analysis of the survey are discussed below.

DESIGN AND DATA COLLECTION PROCEDURES

Sample Design

A combination of landline and cellular random-digit-dial (RDD) samples was used to represent all adults in the United States who have access to either a landline or cellular telephone. Both samples were provided by Survey Sampling International, LLC (SSI) according to PSRAI specifications.

Numbers for the landline sample were drawn with equal probabilities from active blocks (area code + exchange + two-digit block number) that contained one or more residential directory listings. The cellular sample was not list-assisted, but was drawn through a systematic sampling from dedicated wireless 100-blocks and shared service 100-blocks with no directory-listed landline numbers.

Contact Procedures

Interviews were conducted from Oct. 13 to Nov. 15, 2015. As many as seven attempts were made to contact every sampled telephone number. Sample was released for interviewing in replicates, which are representative subsamples of the larger sample. Using replicates to control the release of sample ensures that complete call procedures are followed for the entire sample. Calls were staggered over times of day and days of the week to maximize the chance of making contact with potential respondents. Interviewing was spread as evenly as possible across the days in field. When necessary, each telephone number was called at least one time during the day in an attempt to complete an interview.

For the landline sample, interviewers asked to speak with the youngest adult male or female currently at home based on a random rotation. If no male/female was available, interviewers asked to speak with the youngest adult of the other gender. This systematic respondent selection technique has been shown to produce samples that closely mirror the population in terms of age and gender when combined with cell interviewing.

For the cellular sample, interviews were conducted with the person who answered the phone. Interviewers verified that the person was an adult and in a safe place before administering the survey. The cellular respondents were offered a post-paid cash reimbursement for their participation.

WEIGHTING AND ANALYSIS

Weighting is generally used in survey analysis to compensate for sample designs and patterns of non-response that might bias results. The sample was weighted to match national adult general population parameters. A two-stage weighting procedure was used to weight this dual-frame sample.

The first stage of weighting corrected for different probabilities of selection associated with the number of adults in each household and each respondent’s telephone usage patterns5

This weighting also adjusts for the overlapping landline and cell sample frames and the relative sizes of each frame and each sample.

The first-stage weight for the ith case can be expressed as:

PI_2016.04.07_Learning-and-Libraries_M-01

Where SLL = the size of the landline sample
FLL = the size of the landline sample frame
SCP = the size of the cell sample
FCP = the size of the cell sample frame
ADi = Number of adults in household i
LLi=1 if respondent has a landline phone, otherwise LL=0.
CPi=1 if respondent has a cellphone, otherwise CP=0.

The second stage of weighting balances sample demographics to population parameters. The sample is balanced to match national population parameters for sex, age, education, race, Hispanic origin, region (U.S. Census definitions), population density and telephone usage. The Hispanic origin was split out based on nativity: U.S. born and non-U.S. born. The white, non-Hispanic subgroup was also balanced on age, education and region.

The basic weighting parameters came from the U.S. Census Bureau’s 2013 American Community Survey (ACS) data.6 The population density parameter was derived from Census 2010 data. The telephone usage parameter came from an analysis of the July-December 2014 National Health Interview Survey.7

Weighting was accomplished using Sample Balancing, a special iterative sample weighting program that simultaneously balances the distributions of all variables using a statistical technique called the Deming Algorithm. Weights were trimmed to prevent individual interviews from having too much influence on the final results. The use of these weights in statistical analysis ensures that the demographic characteristics of the sample closely approximate the demographic characteristics of the national population. Table 1 compares weighted and unweighted sample distributions to population parameters.

Table 1: Sample Demographics

Effects of Sample Design on Statistical Inference

Post-data collection statistical adjustments require analysis procedures that reflect departures from simple random sampling. PSRAI calculates the effects of these design features so that an appropriate adjustment can be incorporated into tests of statistical significance when using these data. The so-called “design effect” or deff represents the loss in statistical efficiency that results from systematic non-response. The total sample design effect for this survey is 1.28.

PSRAI calculates the composite design effect for a sample of size n, with each case having a weight, wi as:

PI_2016.04.07_Learning-and-Libraries_M-03

In a wide range of situations, the adjusted standard error of a statistic should be calculated by multiplying the usual formula by the square root of the design effect (√deff ). Thus, the formula for computing the 95% confidence interval around a percentage is:

PI_2016.04.07_Learning-and-Libraries_M-04

where is the sample estimate and n is the unweighted number of sample cases in the group being considered.

The survey’s margin of error is the largest 95% confidence interval for any estimated proportion based on the total sample – the one around 50%. For example, the margin of error for the entire sample is ±2.1 percentage points. This means that in 95 out every 100 samples drawn using the same methodology, estimated proportions based on the entire sample will be no more than 2.1 percentage points away from their true values in the population. It is important to remember that sampling fluctuations are only one possible source of error in a survey estimate. Other sources, such as respondent selection bias, questionnaire wording and reporting inaccuracy, may contribute additional error of greater or lesser magnitude.

RESPONSE RATE

Table 2 reports the disposition of all sampled telephone numbers ever dialed from the original telephone number samples. The response rate estimates the fraction of all eligible samples that were ultimately interviewed. Response rates are computed according to American Association for Public Opinion Research standards.8 Thus the response rate for both the landline and cellular samples was 9%.

Table 2. Sample DispositionSource : http://www.pewinternet.org/2016/04/07/libraries-and-learning-methodology/
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