Tag Archives: New York University

NYU Langone Health / NYU School of Medicine study: Artificial intelligence can diagnose PTSD by analyzing voices

23 Apr

Live Science described AI in What Is Artificial Intelligence?:

One of the standard textbooks in the field, by University of California computer scientists Stuart Russell and Google’s director of research, Peter Norvig, puts artificial intelligence in to four broad categories:
The differences between them can be subtle, notes Ernest Davis, a professor of computer science at New York University. AlphaGo, the computer program that beat a world champion at Go, acts rationally when it plays the game (it plays to win). But it doesn’t necessarily think the way a human being does, though it engages in some of the same pattern-recognition tasks. Similarly, a machine that acts like a human doesn’t necessarily bear much resemblance to people in the way it processes information.
• machines that think like humans,
• machines that act like humans,
• machines that think rationally,
• machines that act rationally.
Even IBM’s Watson, which acted somewhat like a human when playing Jeopardy, wasn’t using anything like the rational processes humans use.
Tough tasks
Davis says he uses another definition, centered on what one wants a computer to do. “There are a number of cognitive tasks that people do easily — often, indeed, with no conscious thought at all — but that are extremely hard to program on computers. Archetypal examples are vision and natural language understanding. Artificial intelligence, as I define it, is the study of getting computers to carry out these tasks,” he said….
Computer vision has made a lot of strides in the past decade — cameras can now recognize faces Other tasks, though, are proving tougher. For example, Davis and NYU psychology professor Gary Marcus wrote in the Communications of the Association for Computing Machinery of “common sense” tasks that computers find very difficult. A robot serving drinks, for example, can be programmed to recognize a request for one, and even to manipulate a glass and pour one. But if a fly lands in the glass the computer still has a tough time deciding whether to pour the drink in and serve it (or not).
Common sense
The issue is that much of “common sense” is very hard to model. Computer scientists have taken several approaches to get around that problem. IBM’s Watson, for instance, was able to do so well on Jeopardy! because it had a huge database of knowledge to work with and a few rules to string words together to make questions and answers. Watson, though, would have a difficult time with a simple open-ended conversation.
Beyond tasks, though, is the issue of learning. Machines can learn, said Kathleen McKeown, a professor of computer science at Columbia University. “Machine learning is a kind of AI,” she said.
Some machine learning works in a way similar to the way people do it, she noted. Google Translate, for example, uses a large corpus of text in a given language to translate to another language, a statistical process that doesn’t involve looking for the “meaning” of words. Humans, she said, do something similar, in that we learn languages by seeing lots of examples.
That said, Google Translate doesn’t always get it right, precisely because it doesn’t seek meaning and can sometimes be fooled by synonyms or differing connotations….
The upshot is AIs that can handle certain tasks well exist, as do AIs that look almost human because they have a large trove of data to work with. Computer scientists have been less successful coming up with an AI that can think the way we expect a human being to, or to act like a human in more than very limited situations…. https://www.livescience.com/55089-artificial-intelligence.html

NYU scientists used AI to diagnose PTSD which is short for Post-Traumatic Stress Disorder.

The National Institute of Mental Health defined PTSD:

Post-Traumatic Stress Disorder
Overview
PTSD is a disorder that develops in some people who have experienced a shocking, scary, or dangerous event.
It is natural to feel afraid during and after a traumatic situation. Fear triggers many split-second changes in the body to help defend against danger or to avoid it. This “fight-or-flight” response is a typical reaction meant to protect a person from harm. Nearly everyone will experience a range of reactions after trauma, yet most people recover from initial symptoms naturally. Those who continue to experience problems may be diagnosed with PTSD. People who have PTSD may feel stressed or frightened even when they are not in danger.
Signs and Symptoms
Not every traumatized person develops ongoing (chronic) or even short-term (acute) PTSD. Not everyone with PTSD has been through a dangerous event. Some experiences, like the sudden, unexpected death of a loved one, can also cause PTSD. Symptoms usually begin early, within 3 months of the traumatic incident, but sometimes they begin years afterward. Symptoms must last more than a month and be severe enough to interfere with relationships or work to be considered PTSD. The course of the illness varies. Some people recover within 6 months, while others have symptoms that last much longer. In some people, the condition becomes chronic.
A doctor who has experience helping people with mental illnesses, such as a psychiatrist or psychologist, can diagnose PTSD.
To be diagnosed with PTSD, an adult must have all of the following for at least 1 month:
• At least one re-experiencing symptom
• At least one avoidance symptom
• At least two arousal and reactivity symptoms
• At least two cognition and mood symptoms
Re-experiencing symptoms include:
• Flashbacks—reliving the trauma over and over, including physical symptoms like a racing heart or sweating
• Bad dreams
• Frightening thoughts
Re-experiencing symptoms may cause problems in a person’s everyday routine. The symptoms can start from the person’s own thoughts and feelings. Words, objects, or situations that are reminders of the event can also trigger re-experiencing symptoms.
Avoidance symptoms include:
• Staying away from places, events, or objects that are reminders of the traumatic experience
• Avoiding thoughts or feelings related to the traumatic event
Things that remind a person of the traumatic event can trigger avoidance symptoms. These symptoms may cause a person to change his or her personal routine. For example, after a bad car accident, a person who usually drives may avoid driving or riding in a car.
Arousal and reactivity symptoms include:
• Being easily startled
• Feeling tense or “on edge”
• Having difficulty sleeping
• Having angry outbursts
Arousal symptoms are usually constant, instead of being triggered by things that remind one of the traumatic events. These symptoms can make the person feel stressed and angry. They may make it hard to do daily tasks, such as sleeping, eating, or concentrating.
Cognition and mood symptoms include:
• Trouble remembering key features of the traumatic event
• Negative thoughts about oneself or the world
• Distorted feelings like guilt or blame
• Loss of interest in enjoyable activities
Cognition and mood symptoms can begin or worsen after the traumatic event, but are not due to injury or substance use. These symptoms can make the person feel alienated or detached from friends or family members.
It is natural to have some of these symptoms after a dangerous event. Sometimes people have very serious symptoms that go away after a few weeks. This is called acute stress disorder, or ASD. When the symptoms last more than a month, seriously affect one’s ability to function, and are not due to substance use, medical illness, or anything except the event itself, they might be PTSD. Some people with PTSD don’t show any symptoms for weeks or months. PTSD is often accompanied by depression, substance abuse, or one or more of the other anxiety disorders….
https://www.nimh.nih.gov/health/topics/post-traumatic-stress-disorder-ptsd/index.shtml

See, Recognizing PTSD Early Warning Signs, Matthew Tull, PhD https://www.verywellmind.com/recognizing-ptsd-early-warning-signs-2797569

Science Daily reported in Artificial intelligence can diagnose PTSD by analyzing voices:

A specially designed computer program can help diagnose post-traumatic stress disorder (PTSD) in veterans by analyzing their voices, a new study finds.
Published online April 22 in the journal Depression and Anxiety, the study found that an artificial intelligence tool can distinguish — with 89 percent accuracy — between the voices of those with or without PTSD.
“Our findings suggest that speech-based characteristics can be used to diagnose this disease, and with further refinement and validation, may be employed in the clinic in the near future,” says senior study author Charles R. Marmar, MD, the Lucius N. Littauer Professor and chair of the Department of Psychiatry at NYU School of Medicine.
More than 70 percent of adults worldwide experience a traumatic event at some point in their lives, with up to 12 percent of people in some struggling countries suffering from PTSD. Those with the condition experience strong, persistent distress when reminded of a triggering event.
The study authors say that a PTSD diagnosis is most often determined by clinical interview or a self-report assessment, both inherently prone to biases. This has led to efforts to develop objective, measurable, physical markers of PTSD progression, much like laboratory values for medical conditions, but progress has been slow.
Learning How to Learn
In the current study, the research team used a statistical/machine learning technique, called random forests, that has the ability to “learn” how to classify individuals based on examples. Such AI programs build “decision” rules and mathematical models that enable decision-making with increasing accuracy as the amount of training data grows.
The researchers first recorded standard, hours-long diagnostic interviews, called Clinician-Administered PTSD Scale, or CAPS, of 53 Iraq and Afghanistan veterans with military-service-related PTSD, as well as those of 78 veterans without the disease. The recordings were then fed into voice software from SRI International — the institute that also invented Siri — to yield a total of 40,526 speech-based features captured in short spurts of talk, which the team’s AI program sifted through for patterns.
The random forest program linked patterns of specific voice features with PTSD, including less clear speech and a lifeless, metallic tone, both of which had long been reported anecdotally as helpful in diagnosis. While the current study did not explore the disease mechanisms behind PTSD, the theory is that traumatic events change brain circuits that process emotion and muscle tone, which affects a person’s voice.
Moving forward, the research team plans to train the AI voice tool with more data, further validate it on an independent sample, and apply for government approval to use the tool clinically.
“Speech is an attractive candidate for use in an automated diagnostic system, perhaps as part of a future PTSD smartphone app, because it can be measured cheaply, remotely, and non-intrusively,” says lead author Adam Brown, PhD, adjunct assistant professor in the Department of Psychiatry at NYU School of Medicine.
“The speech analysis technology used in the current study on PTSD detection falls into the range of capabilities included in our speech analytics platform called SenSay Analytics™,” says Dimitra Vergyri, director of SRI International’s Speech Technology and Research (STAR) Laboratory. “The software analyzes words — in combination with frequency, rhythm, tone, and articulatory characteristics of speech — to infer the state of the speaker, including emotion, sentiment, cognition, health, mental health and communication quality. The technology has been involved in a series of industry applications visible in startups like Oto, Ambit and Decoded Health.” https://www.sciencedaily.com/releases/2019/04/190422082232.htm

Citation:

Artificial intelligence can diagnose PTSD by analyzing voices
Study tests potential telemedicine approach
Date: April 22, 2019
Source: NYU Langone Health / NYU School of Medicine
Summary:
A specially designed computer program can help to diagnose post-traumatic stress disorder (PTSD) in veterans by analyzing their voices.

Speech‐based markers for posttraumatic stress disorder in US veterans
First published: 22 April 2019
https://doi.org/10.1002/da.22890
Preliminary findings from this study were presented at the 16th annual conference of the International Speech Communication Association, Dresden, Germany, September 6–10, 2015.
Charles R. Marmar
Corresponding Author
E-mail address: Charles.Marmar@nyulangone.org
http://orcid.org/0000-0001-8427-5607
Department of Psychiatry, New York University School of Medicine, New York, New York
Steven and Alexandra Cohen Veterans Center for the Study of Post‐Traumatic Stress and Traumatic Brain Injury, New York, New York
Marmar and Brown should be have considered joint first authors.
Correspondence Charles R. Marmar, M.D., Department of Psychiatry, New York University School of Medicine, 1 Park Avenue, New York, NY 10016. Email: Charles.Marmar@nyulangone.org
Background
The diagnosis of posttraumatic stress disorder (PTSD) is usually based on clinical interviews or self‐report measures. Both approaches are subject to under‐ and over‐reporting of symptoms. An objective test is lacking. We have developed a classifier of PTSD based on objective speech‐marker features that discriminate PTSD cases from controls.
Methods
Speech samples were obtained from warzone‐exposed veterans, 52 cases with PTSD and 77 controls, assessed with the Clinician‐Administered PTSD Scale. Individuals with major depressive disorder (MDD) were excluded. Audio recordings of clinical interviews were used to obtain 40,526 speech features which were input to a random forest (RF) algorithm.
Results
The selected RF used 18 speech features and the receiver operating characteristic curve had an area under the curve (AUC) of 0.954. At a probability of PTSD cut point of 0.423, Youden’s index was 0.787, and overall correct classification rate was 89.1%. The probability of PTSD was higher for markers that indicated slower, more monotonous speech, less change in tonality, and less activation. Depression symptoms, alcohol use disorder, and TBI did not meet statistical tests to be considered confounders.
Conclusions
This study demonstrates that a speech‐based algorithm can objectively differentiate PTSD cases from controls. The RF classifier had a high AUC. Further validation in an independent sample and appraisal of the classifier to identify those with MDD only compared with those with PTSD comorbid with MDD is required.

Here is the press release from NYU:

NEWS RELEASE 22-APR-2019
Artificial intelligence can diagnose PTSD by analyzing voices
Study tests potential telemedicine approach
NYU LANGONE HEALTH / NYU SCHOOL OF MEDICINE
VIDEO: NYU School of Medicine researchers say artificial intelligence could be used to diagnose PTSD by analyzing voices. view more
Credit: NYU School of Medicine
A specially designed computer program can help diagnose post-traumatic stress disorder (PTSD) in veterans by analyzing their voices, a new study finds.
Published online April 22 in the journal Depression and Anxiety, the study found that an artificial intelligence tool can distinguish – with 89 percent accuracy – between the voices of those with or without PTSD.
“Our findings suggest that speech-based characteristics can be used to diagnose this disease, and with further refinement and validation, may be employed in the clinic in the near future,” says senior study author Charles R. Marmar, MD, the Lucius N. Littauer Professor and chair of the Department of Psychiatry at NYU School of Medicine.
More than 70 percent of adults worldwide experience a traumatic event at some point in their lives, with up to 12 percent of people in some struggling countries suffering from PTSD. Those with the condition experience strong, persistent distress when reminded of a triggering event.
The study authors say that a PTSD diagnosis is most often determined by clinical interview or a self-report assessment, both inherently prone to biases. This has led to efforts to develop objective, measurable, physical markers of PTSD progression, much like laboratory values for medical conditions, but progress has been slow.
Learning How to Learn
In the current study, the research team used a statistical/machine learning technique, called random forests, that has the ability to “learn” how to classify individuals based on examples. Such AI programs build “decision” rules and mathematical models that enable decision-making with increasing accuracy as the amount of training data grows.
The researchers first recorded standard, hours-long diagnostic interviews, called Clinician-Administered PTSD Scale, or CAPS, of 53 Iraq and Afghanistan veterans with military-service-related PTSD, as well as those of 78 veterans without the disease. The recordings were then fed into voice software from SRI International – the institute that also invented Siri – to yield a total of 40,526 speech-based features captured in short spurts of talk, which the team’s AI program sifted through for patterns.
The random forest program linked patterns of specific voice features with PTSD, including less clear speech and a lifeless, metallic tone, both of which had long been reported anecdotally as helpful in diagnosis. While the current study did not explore the disease mechanisms behind PTSD, the theory is that traumatic events change brain circuits that process emotion and muscle tone, which affects a person’s voice.
Moving forward, the research team plans to train the AI voice tool with more data, further validate it on an independent sample, and apply for government approval to use the tool clinically.
“Speech is an attractive candidate for use in an automated diagnostic system, perhaps as part of a future PTSD smartphone app, because it can be measured cheaply, remotely, and non-intrusively,” says lead author Adam Brown, PhD, adjunct assistant professor in the Department of Psychiatry at NYU School of Medicine.
“The speech analysis technology used in the current study on PTSD detection falls into the range of capabilities included in our speech analytics platform called SenSay Analytics™,” says Dimitra Vergyri, director of SRI International’s Speech Technology and Research (STAR) Laboratory. “The software analyzes words – in combination with frequency, rhythm, tone, and articulatory characteristics of speech – to infer the state of the speaker, including emotion, sentiment, cognition, health, mental health and communication quality. The technology has been involved in a series of industry applications visible in startups like Oto, Ambit and Decoded Health.”
###
Along with Marmar and Brown, authors of the study from the Department of Psychiatry were Meng Qian, Eugene Laska, Carole Siegel, Meng Li, and Duna Abu-Amara. Study authors from SRI International were Andreas Tsiartas, Dimitra Vergyri, Colleen Richey, Jennifer Smith, and Bruce Knoth. Brown is also an associate professor of psychology at the New School for Social Research.
The study was supported by the U.S. Army Medical Research & Acquisition Activity (USAMRAA) and Telemedicine & Advanced Technology Research Center (TATRC) grant W81XWH- ll-C-0004, as well as by the Steven and Alexandra Cohen Foundation.
Media Inquiries:
Jim Mandler
(212) 404-3500
jim.mandler@nyulangone.org
Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.

Resources:

Artificial Intelligence Will Redesign Healthcare                     https://medicalfuturist.com/artificial-intelligence-will-redesign-healthcare

9 Ways Artificial Intelligence is Affecting the Medical Field https://www.healthcentral.com/slideshow/8-ways-artificial-intelligence-is-affecting-the-medical-field#slide=2

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New York University study: Machine learning helps spot counterfeit consumer products

13 Aug

OECD reported in Global trade in fake goods worth nearly half a trillion dollars a year – OECD & EUIPO:

18/04/2016 – Imports of counterfeit and pirated goods are worth nearly half a trillion dollars a year, or around 2.5% of global imports, with US, Italian and French brands the hardest hit and many of the proceeds going to organised crime, according to a new report by the OECD and the EU’s Intellectual Property Office.
“Trade in Counterfeit and Pirated Goods: Mapping the Economic Impact” puts the value of imported fake goods worldwide at USD 461 billion in 2013, compared with total imports in world trade of USD 17.9 trillion. Up to 5% of goods imported into the European Union are fakes. Most originate in middle income or emerging countries, with China the top producer.
The report analyses nearly half a million customs seizures around the world over 2011-13 to produce the most rigorous estimate to date of the scale of counterfeit trade. It points to a larger volume than a 2008 OECD study which estimated fake goods accounted for up to 1.9% of global imports, though the 2008 study used more limited data and methodology.
“The findings of this new report contradict the image that counterfeiters only hurt big companies and luxury goods manufacturers. They take advantage of our trust in trademarks and brand names to undermine economies and endanger lives,” said OECD Deputy Secretary-General Doug Frantz, launching the report with EUIPO Executive Director António Campinos as part of OECD Integrity Week.
Fake products crop up in everything from handbags and perfumes to machine parts and chemicals. Footwear is the most-copied item though trademarks are infringed even on strawberries and bananas. Counterfeiting also produces knockoffs that endanger lives – auto parts that fail, pharmaceuticals that make people sick, toys that harm children, baby formula that provides no nourishment and medical instruments that deliver false readings.\
The report covers all physical counterfeit goods, which infringe trademarks, design rights or patents, and tangible pirated products, which breach copyright. It does not cover online piracy, which is a further drain on the formal economy… http://www.oecd.org/industry/global-trade-in-fake-goods-worth-nearly-half-a-trillion-dollars-a-year.htm

See, Remade In China: Where The World’s Fake Goods Come From [Infographic] https://www.forbes.com/sites/niallmccarthy/2016/04/19/remade-in-china-where-the-worlds-fake-goods-come-from-infographic/#5a56fb5f1b87

SAS described machine learning in Machine Learning: What it is & why it matters:

Machine learning is a method of data analysis that automates analytical model building. Using algorithms that iteratively learn from data, machine learning allows computers to find hidden insights without being explicitly programmed where to look.
The iterative aspect of machine learning is important because as models are exposed to new data, they are able to independently adapt. They learn from previous computations to produce reliable, repeatable decisions and results. It’s a science that’s not new – but one that’s gaining fresh momentum.
Because of new computing technologies, machine learning today is not like machine learning of the past. While many machine learning algorithms have been around for a long time, the ability to automatically apply complex mathematical calculations to big data – over and over, faster and faster – is a recent development. Here are a few widely publicized examples of machine learning applications that you may be familiar with:
• The heavily hyped, self-driving Google car? The essence of machine learning.
• Online recommendation offers like those from Amazon and Netflix? Machine learning applications for everyday life.
• Knowing what customers are saying about you on Twitter? Machine learning combined with linguistic rule creation.
• Fraud detection? One of the more obvious, important uses in our world today.
Why the increased interest in machine learning?
Resurging interest in machine learning is due to the same factors that have made data mining and Bayesian analysis more popular than ever. Things like growing volumes and varieties of available data, computational processing that is cheaper and more powerful, and affordable data storage.
All of these things mean it’s possible to quickly and automatically produce models that can analyze bigger, more complex data and deliver faster, more accurate results – even on a very large scale. The result? High-value predictions that can guide better decisions and smart actions in real time without human intervention…. https://www.sas.com/en_id/insights/analytics/machine-learning.html

See, What is Machine Learning? https://www.youtube.com/watch?v=f_uwKZIAeM0

Science Daily reported in Machine learning helps spot counterfeit consumer products:

A team of researchers has developed a new mechanism that uses machine-learning algorithms to distinguish between genuine and counterfeit versions of the same product.
The work, led by New York University Professor Lakshminarayanan Subramanian, will be presented on Mon., Aug. 14 at the annual KDD Conference on Knowledge Discovery and Data Mining in Halifax, Nova Scotia….
The system described in the presentation is commercialized by Entrupy Inc., an NYU startup founded by Ashlesh Sharma, a doctoral graduate from the Courant Institute, Vidyuth Srinivasan, and Subramanian.
Counterfeit goods represent a massive worldwide problem with nearly every high-valued physical object or product directly affected by this issue, the researchers note. Some reports indicate counterfeit trafficking represents 7 percent of the world’s trade today.
While other counterfeit-detection methods exist, these are invasive and run the risk of damaging the products under examination.
The Entrupy method, by contrast, provides a non-intrusive solution to easily distinguish authentic versions of the product produced by the original manufacturer and fake versions of the product produced by counterfeiters….
“The classification accuracy is more than 98 percent, and we show how our system works with a cellphone to verify the authenticity of everyday objects,” notes Subramanian.
A demo of the technology may be viewed here: https://www.youtube.com/watch?v=DsdsY8-gljg (courtesy of Entrupy Inc.)
To date, Entrupy, which recently received $2.6 million in funding from a team of investors, has authenticated $14 million worth of goods.

Citation:

Machine learning helps spot counterfeit consumer products
Date: August 11, 2017
Source: New York University
Summary:
A team of researchers has developed a new mechanism that uses machine-learning algorithms to distinguish between genuine and counterfeit versions of the same product.

Here is the NYU press release:

News Release
Researchers Use Machine Learning to Spot Counterfeit Consumer Products
________________________________________
Aug 11, 2017
Engineering, Science and Technology Research Courant Institute of Mathematical Sciences Faculty
New York City
A team of researchers has developed a new mechanism that uses machine-learning algorithms to distinguish between genuine and counterfeit versions of the same product.

A team of researchers has developed a new mechanism that uses machine-learning algorithms to distinguish between genuine and counterfeit versions of the same product. Image courtesy of Entrupy, Inc.
A team of researchers has developed a new mechanism that uses machine-learning algorithms to distinguish between genuine and counterfeit versions of the same product.

The work, led by New York University Professor Lakshminarayanan Subramanian, will be presented on Mon., Aug. 14 at the annual KDD Conference on Knowledge Discovery and Data Mining in Halifax, Nova Scotia.
“The underlying principle of our system stems from the idea that microscopic characteristics in a genuine product or a class of products—corresponding to the same larger product line—exhibit inherent similarities that can be used to distinguish these products from their corresponding counterfeit versions,” explains Subramanian, a professor at NYU’s Courant Institute of Mathematical Sciences.
The system described in the presentation is commercialized by Entrupy Inc., an NYU startup founded by Ashlesh Sharma, a doctoral graduate from the Courant Institute, Vidyuth Srinivasan, and Subramanian.
Counterfeit goods represent a massive worldwide problem with nearly every high-valued physical object or product directly affected by this issue, the researchers note. Some reports indicate counterfeit trafficking represents 7 percent of the world’s trade today.
While other counterfeit-detection methods exist, these are invasive and run the risk of damaging the products under examination.
The Entrupy method, by contrast, provides a non-intrusive solution to easily distinguish authentic versions of the product produced by the original manufacturer and fake versions of the product produced by counterfeiters.
It does so by deploying a dataset of three million images across various objects and materials such as fabrics, leather, pills, electronics, toys and shoes.
“The classification accuracy is more than 98 percent, and we show how our system works with a cellphone to verify the authenticity of everyday objects,” notes Subramanian.
A demo of the technology may be viewed here (courtesy of Entrupy Inc.).
To date, Entrupy, which recently received $2.6 million in funding from a team of investors, has authenticated $14 million worth of goods.
For a copy of the paper, “The Fake vs Real Goods Problem: Microscopy and Machine Learning to the Rescue,” please contact James Devitt, NYU’s Office of Public Affairs, at 212.998.6808 or james.devitt@nyu.edu.

Press Contact
James Devitt
James Devitt
(212) 998-6808

Employment opportunities in machine learning are expected to increase.

UDACITY described machine learning employment opportunities in :5 Skills You Need to Become a Machine Learning Engineer:

To begin, there are two very important things that you should understand if you’re considering a career as a Machine Learning engineer. First, it’s not a “pure” academic role. You don’t necessarily have to have a research or academic background. Second, it’s not enough to have either software engineering or data science experience. You ideally need both.
Data Analyst vs. Machine Learning Engineer
It’s also critical to understand the differences between a Data Analyst and a Machine Learning engineer. In simplest form, the key distinction has to do with the end goal. As a Data Analyst, you’re analyzing data in order to tell a story, and to produce actionable insights. The emphasis is on dissemination—charts, models, visualizations. The analysis is performed and presented by human beings, to other human beings who may then go on to make business decisions based on what’s been presented. This is especially important to note—the “audience” for your output is human. As a Machine Learning engineer, on the other hand, your final “output” is working software (not the analyses or visualizations that you may have to create along the way), and your “audience” for this output often consists of other software components that run autonomously with minimal human supervision. The intelligence is still meant to be actionable, but in the Machine Learning model, the decisions are being made by machines and they affect how a product or service behaves. This is why the software engineering skill set is so important to a career in Machine Learning.
Understanding The Ecosystem
Before getting into specific skills, there is one more concept to address. Being a Machine Learning engineer necessitates understanding the entire ecosystem that you’re designing for.
Let’s say you’re working for a grocery chain, and the company wants to start issuing targeted coupons based on things like the past purchase history of customers, with a goal of generating coupons that shoppers will actually use. In a Data Analysis model, you could collect the purchase data, do the analysis to figure out trends, and then propose strategies. The Machine Learning approach would be to write an automated coupon generation system. But what does it take to write that system, and have it work? You have to understand the whole ecosystem—inventory, catalog, pricing, purchase orders, bill generation, Point of Sale software, CRM software, etc.
Ultimately, the process is less about understanding Machine Learning algorithms—or when and how to apply them—and more about understanding the systemic interrelationships, and writing working software that will successfully integrate and interface. Remember, Machine Learning output is actually working software! http://blog.udacity.com/2016/04/5-skills-you-need-to-become-a-machine-learning-engineer.html

Education guidance counselors should be informed about opportunities in machine learning.

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New York University study: Low-income children missing out on language learning both at home and at school: A double dose of disadvantage

16 Apr

Educators have long recognized the importance of vocabulary in reading and learning. Francie Alexander wrote in the Scholastic article, Understanding Vocabulary:

Why is vocabulary s-o-o important?
Vocabulary is critical to reading success for three reasons:
1. Comprehension improves when you know what the words mean. Since comprehension is the ultimate goal of reading, you cannot overestimate the importance of vocabulary development.
2. Words are the currency of communication. A robust vocabulary improves all areas of communication — listening, speaking, reading and writing.
3. How many times have you asked your students or your own children to “use your words”? When children and adolescents improve their vocabulary, their academic and social confidence and competence improve, too.http://www.scholastic.com/teachers/article/understanding-vocabulary

A University of Chicago study, “Quality of early parent input predicts child vocabulary three years later,” published in the current issue of the Proceedings of the National Academy of Sciences highlights the importance of parental involvement at an early stage of learning. See more at: http://news.uchicago.edu/article/2013/06/24/giving-children-non-verbal-clues-about-words-boosts-vocabularies#sthash.V4f1L1Vb.dpuf

Science Daily reported in Low-income children missing out on language learning both at home and at school: A double dose of disadvantage:

Children from poor neighborhoods are less likely to have complex language building opportunities both in home and at school, putting them at a disadvantage in their kindergarten year, finds a new study led by NYU Steinhardt School of Culture, Education, and Human Development.
The findings, published in the Journal of Educational Psychology, suggest that language learning should involve both families and teachers in order to overcome these early disadvantages and ensure learning opportunities for vulnerable students.
“Children may go from a home with limited physical and psychological resources for learning and language to a school with similar constraints, resulting in a double dose of disadvantage,” said Susan B. Neuman, professor of childhood and literacy education at NYU Steinhardt and the study’s lead author. “Our study suggests that neighborhoods matter and can have a powerful influence on nurturing success or failure.”
Research shows that children’s academic achievement is predicted not only by their family’s socioeconomic status, but also by the socioeconomic status of their school. These two factors together have an impact on children’s access to learning resources, including adults who create language-rich opportunities when they speak with children.
“Children’s early exposure to a rich set of language practices can set in motion the processes that they use for learning to read, including the vocabulary and background knowledge necessary for language and reading comprehension,” Neuman said. “Consequently, children who have limited experience with these kinds of linguistic interactions may have fewer opportunities to engage in the higher-order exchanges valued in school….” https://www.sciencedaily.com/releases/2017/04/170414105818.htm

Citation:

Low-income children missing out on language learning both at home and at school
A double dose of disadvantage
Date: April 14, 2017
Source: New York University
Summary:
Children from poor neighborhoods are less likely to have complex language building opportunities both in home and at school, putting them at a disadvantage in their kindergarten year, finds a new study.
Journal Reference:
1. Susan B. Neuman, Tanya Kaefer, Ashley M. Pinkham. A Double Dose of Disadvantage: Language Experiences for Low-Income Children in Home and School.. Journal of Educational Psychology, 2017; DOI: 10.1037/edu0000201

Here is the press release from NYU:

News Release
A Double Dose of Disadvantage: Low-income Children Missing Out on Language Learning Both at Home and at School

Apr 14, 2017

Education and Social Sciences Research Steinhardt School of Culture, Education, and Human Development
New York City
Children from poor neighborhoods are less likely to have complex language building opportunities both in home and at school, putting them at a disadvantage in their kindergarten year, finds a new study led by NYU Steinhardt School of Culture, Education, and Human Development.
The findings, published in the Journal of Educational Psychology, suggest that language learning should involve both families and teachers in order to overcome these early disadvantages and ensure learning opportunities for vulnerable students.
“Children may go from a home with limited physical and psychological resources for learning and language to a school with similar constraints, resulting in a double dose of disadvantage,” said Susan B. Neuman, professor of childhood and literacy education at NYU Steinhardt and the study’s lead author. “Our study suggests that neighborhoods matter and can have a powerful influence on nurturing success or failure.”
Research shows that children’s academic achievement is predicted not only by their family’s socioeconomic status, but also by the socioeconomic status of their school. These two factors together have an impact on children’s access to learning resources, including adults who create language-rich opportunities when they speak with children.
“Children’s early exposure to a rich set of language practices can set in motion the processes that they use for learning to read, including the vocabulary and background knowledge necessary for language and reading comprehension,” Neuman said. “Consequently, children who have limited experience with these kinds of linguistic interactions may have fewer opportunities to engage in the higher-order exchanges valued in school.”
In this study, Neuman and her colleagues examined language-advancing resources in both the homes and schools of 70 children who recently made the transition from preschool to kindergarten. Half of the families lived in poor neighborhoods in Detroit, while the other half lived in more demographically diverse Michigan communities that were largely working class.
The researchers followed the children through their kindergarten year, conducting targeted observations in both home and school settings. During four hour-long home visits, the researchers observed the engagement between parents and their children to understand the degree of cognitive stimulation in the home and the quality of the interactions. They also conducted four half-day observations in kindergarten classrooms during which the teachers’ speaking was recorded. The researchers analyzed the language spoken by parents and teachers for both quantity (number of words spoken) and quality (using varied vocabulary and complex sentences).
These observations were combined with assessments of the children’s school readiness skills, including vocabulary knowledge and letter and word identification.
The researchers found that children in low-income neighborhoods had fewer supports for language and early literacy developments than did those in working class communities. In both settings, there were significant differences in the quality of language directed at children, but there was no difference in the quantity of language overall.
At home, parents in low-income neighborhoods used shorter sentences, fewer different words, and had lower reading comprehension than did parents from working class neighborhoods. In the classroom, children from the low-income communities attended kindergartens characterized by more limited language opportunities. Teachers used simpler sentences, less varied vocabulary, and fewer unique word types, potentially oversimplifying their language for students.
Children in all neighborhoods experienced learning across their kindergarten year, but children in the working class communities outpaced their counterparts from low-income communities, particularly in expressive vocabulary.
“We found that the quality of one’s educational opportunities is highly dependent on the streets where you live. Tragically, the children who need the greater opportunity to learn appear to be the least likely to get it,” Neuman said.
The results suggest that no matter the strength of the early boost children receive in preschool, differences in later environmental influences can either support or undermine this early advantage.
“Too often we have focused on what happens within early childhood programs instead of the environmental supports that surround them. We need to account for the multiple contexts of home and school in our understanding of children’s early development,” Neuman said.
Tanya Kaefer of Lakehead University and Ashley M. Pinkham of West Texas A&M University coauthored
the study. The research was funded by the Institute for Education Sciences, US Department of Education (R305A110038).
About the Steinhardt School of Culture, Education, and Human Development (@nyusteinhardt)
Located in the heart of Greenwich Village, NYU’s Steinhardt School of Culture, Education, and Human Development prepares students for careers in the arts, education, health, media, and psychology. Since its founding in 1890, the Steinhardt School’s mission has been to expand human capacity through public service, global collaboration, research, scholarship, and practice. To learn more about NYU Steinhardt, visit steinhardt.nyu.edu.
Press Contact
Rachel Harrison
Rachel Harrison
(212) 998-6797

The goal of parents, teachers, students, and society should be that all children succeed in obtaining a good basic education. In order to achieve this goal, children must come to school ready to learn. See, Illiteracy in America https://drwilda.wordpress.com/2011/12/07/illiteracy-in-america/

Related:

The importance of the skill of handwriting in the school curriculum https://drwilda.com/2012/01/24/the-importance-of-the-skill-of-handwriting-in-the-school-curriculum/

The slow reading movement
https://drwilda.com/2012/01/31/the-slow-reading-movement/

Why libraries in K-12 schools are important
https://drwilda.com/2012/12/26/why-libraries-in-k-12-schools-are-important/

University of Iowa study: Variation in words may help early learners read better https://drwilda.com/2013/01/16/university-of-iowa-study-variation-in-words-may-help-early-learners-read-better/

Baby Sign Language: Does It Work?
http://www.webmd.com/parenting/baby/baby-sign-language-does-it-work

Teaching Your Baby Sign Language Can Benefit Both of You http://psychcentral.com/lib/teaching-your-baby-sign-language-can-benefit-both-of-you/0002423

Where information leads to Hope. © Dr. Wilda.com
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Blogs by Dr. Wilda:

COMMENTS FROM AN OLD FART©
http://drwildaoldfart.wordpress.com/

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New York University study: Infantile memory study points to critical periods in early-life learning for brain development

19 Jul

Prolonged stress can have adverse effects on humans. Moi wrote about the Adverse Childhood Experiences Study in Study: Some of the effects of adverse stress do not go away:

Sarah D. Sparks writes in the Education Week article, Research Traces Impacts of Childhood Adversity:

Research from Dr. Shonkoff’s center and from other experts finds that positive stress—the kind that comes from telling a toddler he can’t have a cookie or a teenager that she’s about to take a pop quiz—causes a brief rise in heart rate and stress hormones. A jolt can focus a student’s attention and is generally considered healthy.

Similarly, a child can tolerate stress that is severe but may be relatively short-term—from the death of a loved one, for example—as long as he or she has support….

‘Toxic’ Recipe

By contrast, so-called “toxic stress” is severe, sustained, and not buffered by supportive relationships.

The same brain flexibility, called plasticity, that makes children open to learning in their early years also makes them particularly vulnerable to damage from the toxic stressors that often accompany poverty: high mobility and homelessness; hunger and food instability; parents who are in jail or absent; domestic violence; drug abuse; and other problems, according to Pat Levitt, a developmental neuroscientist at the University of Southern California and the director of the Keck School of Medicine Center on the Developing Child in Los Angeles…. http://www.edweek.org/ew/articles/2012/11/07/11poverty_ep.h32.html?tkn=QLYF5qldyT3U0BI0xqtD5885mihZIxwbX4qZ&cmp=clp-edweek

Here is information about the Adverse Child Experiences Study. The Centers for Disease Control and Prevention provides access to the peer-reviewed publications resulting from The ACE Study. http://acestudy.org/

https://drwilda.com/2012/11/09/study-some-of-the-effects-of-adverse-stress-do-not-go-away/

Science Daily reported in Infantile memory study points to critical periods in early-life learning for brain development:

A new study on infantile memory formation in rats points to the importance of critical periods in early-life learning on functional development of the brain. The research, conducted by scientists at New York University’s Center for Neural Science, reveals the significance of learning experiences over the first two to four years of human life; this is when memories are believed to be quickly forgotten — a phenomenon known as infantile amnesia.

“What our findings tell us is that children’s brains need to get enough and healthy activation even before they enter pre-school,” explains Cristina Alberini, a professor in NYU’s Center for Neural Science, who led the study. “Without this, the neurological system runs the risk of not properly developing learning and memory functions…”

In their study, which appears in the journal Nature Neuroscience, the researchers examined the mechanisms of infantile memory in rats — i.e., memories created 17 days after birth. This is the equivalent of humans under the age of three and when memories of who, what, when, and where — known as episodic memories — are rapidly forgotten. The phenomenon, referred as to “infantile or childhood amnesia,” is in fact the inability of adults to retrieve episodic memories that took place during the first two to four years of life.

In addressing this matter, Alberini and her colleagues compared rats’ infantile memory with that when they reached 24 days old — that is, when they are capable of forming and retaining long-term memories and at an age that roughly corresponds to humans at six to nine years old.

The episodic memory tested in the rodents was the memory of an aversive experience: a mild foot shock received upon entering in a new place. Adult rats, like humans, remember unpleasant or painful experiences that they had in specific places, and then avoid returning to them.

To do so, rodents were placed in a box divided into two compartments: a “safe” compartment and a “shock” compartment. During the experiment, each rat was placed in the safe compartment with its head facing away from the door. After 10 seconds, the door separating the compartments was automatically opened, allowing the rat access to the shock compartment. If the rat entered the shock compartment, it received a mild foot shock.

The first set of results was not surprising. The authors found infantile amnesia for the 17 day-old rats, which showed avoidance of the “shock” compartment right after the experience, but lost this memory very rapidly: a day later these rats quickly returned to this compartment. In contrast, the rats exposed to the shock compartment at 24 days of life learned and retained the memory for a long time and avoided this place — revealing a memory similar to that of adult rats.

However, remarkably, the younger rats, which had apparently forgotten the initial experience, subsequently showed they actually had kept a trace of the memory. When, later in life, these rats were prompted with reminders — i.e., they were presented with recollections of the context and the foot shock — they indicated having a specific memory, which was revealed by their avoidance of the specific context in which they received a shock at day 17 of life. These findings show how early life experience, although not expressed or remembered, can influence adult life behavior.

The findings raised the following question: what is occurring — neurologically — that explains why memories are retained by the younger rats only in a latent form but are stored and expressed long-term by older ones? Or, more specifically, what occurs during development that enhances the ability to form lasting memories?

A critical period is a developmental stage during which the nervous system is especially sensitive to environmental stimuli. If, during this period, the organism does not receive the appropriate stimuli required to develop a given function, it may be difficult or even impossible to develop that function later in life. Well-known examples of critical period-based functions are sensory functions, like vision, and language acquisition.

The study shows that there is a critical period for episodic learning and that during this period the hippocampus learns to become able to efficiently process and store memories long-term…                               https://www.sciencedaily.com/releases/2016/07/160718111939.htm

Citation:

Infantile memory study points to critical periods in early-life learning for brain development

Date:         July 18, 2016

Source:      New York University

Summary:

A new study on infantile memory formation in rats points to the importance of critical periods in early-life learning on functional development of the brain. The research reveals the significance of learning experiences over the first two to four years of human life.

Journal Reference:

  1. Alessio Travaglia, Reto Bisaz, Eric S Sweet, Robert D Blitzer, Cristina M Alberini. Infantile amnesia reflects a developmental critical period for hippocampal learning. Nature Neuroscience, 2016; DOI: 10.1038/nn.4348

Here is the press release from New York University:

Infantile Memory Study Points to Critical Periods in Early-Life Learning for Brain Development

July 18, 2016

A new study on infantile memory formation in rats points to the importance of critical periods in early-life learning on functional development of the brain. The research, conducted by scientists at New York University’s Center for Neural Science, reveals the significance of learning experiences over the first two to four years of human life; this is when memories are believed to be quickly forgotten—a phenomenon known as infantile amnesia.

“What our findings tell us is that children’s brains need to get enough and healthy activation even before they enter pre-school,” explains Cristina Alberini, a professor in NYU’s Center for Neural Science, who led the study. “Without this, the neurological system runs the risk of not properly developing learning and memory functions.”

The other authors of the study, conducted in collaboration with the Icahn School of Medicine at Mt. Sinai, included: Alessio Travaglia, a post-doctoral researcher at NYU; Reto Bisaz, an NYU research scientist at the time of the study; Eric Sweet, a post-doctoral fellow at the Icahn School of Medicine at Mt. Sinai; and Robert Blitzer, a professor at the Icahn School of Medicine at Mt. Sinai.

In their study, which appears in the journal Nature Neuroscience, the researchers examined the mechanisms of infantile memory in rats—i.e., memories created 17 days after birth. This is the equivalent of humans under the age of three and when memories of who, what, when, and where–known as episodic memories–are rapidly forgotten. The phenomenon, referred as to “infantile or childhood amnesia,” is in fact the inability of adults to retrieve episodic memories that took place during the first two to four years of life.

In addressing this matter, Alberini and her colleagues compared rats’ infantile memory with that when they reached 24 days old—that is, when they are capable of forming and retaining long-term memories and at an age that roughly corresponds to humans at six to nine years old.

The episodic memory tested in the rodents was the memory of an aversive experience: a mild foot shock received upon entering in a new place. Adult rats, like humans, remember unpleasant or painful experiences that they had in specific places, and then avoid returning to them.

To do so, rodents were placed in a box divided into two compartments: a “safe” compartment and a “shock” compartment. During the experiment, each rat was placed in the safe compartment with its head facing away from the door. After 10 seconds, the door separating the compartments was automatically opened, allowing the rat access to the shock compartment. If the rat entered the shock compartment, it received a mild foot shock.

The first set of results was not surprising. The authors found infantile amnesia for the 17 day-old rats, which showed avoidance of the “shock” compartment right after the experience, but lost this memory very rapidly: a day later these rats quickly returned to this compartment. In contrast, the rats exposed to the shock compartment at 24 days of life learned and retained the memory for a long time and avoided this place—revealing a memory similar to that of adult rats.

However, remarkably, the younger rats, which had apparently forgotten the initial experience, subsequently showed they actually had kept a trace of the memory. When, later in life, these rats were prompted with reminders—i.e., they were presented with recollections of the context and the foot shock—they indicated having a specific memory, which was revealed by their avoidance of the specific context in which they received a shock at day 17 of life. These findings show how early life experience, although not expressed or remembered, can influence adult life behavior.

The findings raised the following question: what is occurring—neurologically—that explains why memories are retained by the younger rats only in a latent form but are stored and expressed long-term by older ones? Or, more specifically, what occurs during development that enhances the ability to form lasting memories?

To address this, the scientists focused on the brain’s hippocampus, which previous scholarship has shown is necessary for encoding new episodic memories. Here, in a series of experiments similar to the box tests, they found that if the hippocampus was inactive, the ability of younger rats to form latent memories and recall them later by reminders as they got older was diminished. They then found that mechanisms of “critical periods” are fundamental for establishing these infantile memories.

A critical period is a developmental stage during which the nervous system is especially sensitive to environmental stimuli. If, during this period, the organism does not receive the appropriate stimuli required to develop a given function, it may be difficult or even impossible to develop that function later in life. Well-known examples of critical period-based functions are sensory functions, like vision, and language acquisition.

The study shows that there is a critical period for episodic learning and that during this period the hippocampus learns to become able to efficiently process and store memories long-term.

“Early in life, while the brain cannot efficiently form long-term memories, it is ‘learning’ how to do so, making it possible to establish the abilities to memorize long-term,” explains Alberini. “However, the brain needs stimulation through learning so that it can get in the practice of memory formation—without these experiences, the ability of the neurological system to learn will be impaired.”

These studies, the researchers observe, suggest that using learning and environmental interventions during a critical period may significantly help to address learning disabilities.

The research was supported, in part, by grants from the National Institute of Mental Health (R01-MH074736, R01-NS072359), part of the National Institutes of Health, and the Geneva-based Agalma Foundation.

This Press Release is in the following Topics:
Research, Arts and Science, Faculty

Type: Press Release

Press Contact: James Devitt | (212) 998-6808

Our goal as a society should be:

A healthy child in a healthy family who attends a healthy school in a healthy neighborhood ©

Resources:

The Effects of Stress on Your Body                                                                       http://www.webmd.com/mental-health/effects-of-stress-on-your-body

The Physical Effects of Long-Term Stress                                                              http://psychcentral.com/lib/2007/the-physical-effects-of-long-term-stress/all/1/

Chronic Stress: The Body Connection                                                      http://www.medicinenet.com/script/main/art.asp?articlekey=53737

Understanding Stress Symptoms, Signs, Causes, and Effects                     http://www.helpguide.org/mental/stress_signs.htm

Dr. Wilda says this about that ©

Blogs by Dr. Wilda:

COMMENTS FROM AN OLD FART ©                                                http://drwildaoldfart.wordpress.com/

Dr. Wilda Reviews ©                                                                         http://drwildareviews.wordpress.com/

Dr. Wilda ©                                                                                                                https://drwilda.com/

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University of Michigan study: How video games affect classroom teaching

18 Dec

Jordan Shapiro reported in the PJ Tech article, Study Shows Video Games’ Impact On Face-to-face Teaching:

In the past, I have covered many studies that look at the efficacy of game based learning. But a recent study from A-GAMES, a collaboration between New York University and the University of Michigan, is significant because it looks at the way games impact the learning experience and the relationship between teacher and student. It does this by considering how digital games support ‘formative assessment’ — a term educators and researchers use to describe “the techniques used by teachers to monitor, measure, and support student progress and learning during instruction.” It may sound fancy but “formative assessment” really just refers to the ongoing attention that all good teachers have always provided their students, monitoring student learning and offering ongoing and specific feedback.

A-GAMES stands for Analyzing Games for Assessment in Math, ELA/Social Studies, and Science. The project is one among many games and learning research projects funded by the Bill and Melinda Gates Foundation.

The study, entitled “Empowering Educators: Supporting Student Progress in the Classroom with Digital Games,” was undertaken by Jan Plass at NYU and Barry Fishman at University of Michigan. Surveying 488 K-12 teachers from across the U.S., they found that “more than half of teachers (57 percent) use digital games weekly or more often in teaching, with 18 percent using games for teaching on a daily basis. A higher percentage of elementary school teachers (66 percent for grade K-2 teachers and 79 percent for grade 3-5 teachers) use games weekly or more often for teaching, compared with middle school (47 percent) and high school (40 percent) teachers.”

These numbers are more or less consistent with previous studies. particularly the Level-up Learning study that the Joan Ganz Cooney Center at Sesame Workshop issued this past fall. That study focused on teachers and how their thinking about digital games in the classroom impacts actual implementation. This A-GAMES study, alternatively, is looking in more detail at the way games impact the teacher’s ability to provide personalized attention, assessment, and feedback to individual students.

The NYU/University of Michigan study found that on a weekly basis, 34 percent of teachers use games to conduct formative assessment. What are they assessing? Facts and knowledge; concepts and big ideas; mastery of specific skills. And they are doing formative assessment with games in the same way they do it with other classroom activities: observing students in class; asking probing questions; looking over their shoulders. All of this suggests that “using digital games may enable teachers to conduct formative assessment more frequently and effectively.” Game based learning seems to be aiding and supporting existing strategies rather than radically transforming the practice of teaching…

http://pjtec.info/study-shows-video-games-impact-on-face-to-face-teaching/

The University of Michigan reports the key findings:                                                                                             Key Findings

If digital games are to play a key role in classroom instruction, they must support core instructional activities. Formative assessment — techniques used by teachers to monitor, measure, and support student progress and learning during instruction — is a core practice of successful classrooms. The A-GAMES project (Analyzing Games for Assessment in Math, ELA/ Social Studies, and Science) studied how teachers actually use digital games in their teaching to support formative assessment.

In Fall 2013, 488 K-12 teachers across the United States were surveyed about their digital game use and formative assessment practices to gain insight into their relationship to one another. The survey explored three areas:

Our results reveal that the way teachers use digital games for formative assessment is related to their overall formative assessment practices. Using digital games as part of instruction may enable teachers to conduct formative assessment more frequently and more effectively.                                                 http://gamesandlearning.umich.edu/a-games/key-findings/

This study is interesting because it looks at how video games allow personalized interaction in the classroom.

Elena Malykhina of Scientific American wrote in Fact or Fiction?: Video Games Are the Future of Education:

If educational video games are well executed, they can provide a strong framework for inquiry and project-based learning, says Alan Gershenfeld, co-founder and president of E-Line Media, a publisher of computer and video games and a Founding Industry Fellow at Arizona State University’s Center for Games and Impact. “Games are also uniquely suited to fostering the skills necessary for navigating a complex, interconnected, rapidly changing 21st century,” he adds.

Digital literacy and understanding how systems (computer and otherwise) work will become increasingly important in a world where many of today’s students will pursue jobs that do not currently exist, says Gershenfeld, who wrote about video games’ potential to transform education in the February Scientific American. Tomorrow’s workers will also likely change jobs many times throughout their careers and “will almost certainly have jobs that require some level of mastery of digital media and technology,” he adds….

Perhaps the biggest impact of video games will be on students who have not responded as well to traditional teaching methods. Nearly half of the teachers surveyed say it is the low-performing students who generally benefit from the use of games, and more than half believe games have the ability to motivate struggling and special education students.

http://www.scientificamerican.com/article/fact-or-fiction-video-games-are-the-future-of-education/

See, Teachers Surveyed on Using Digital Games in Class       http://www.gamesandlearning.org/2014/06/09/teachers-on-using-games-in-class/

As with any instructional technique, there are pros and cons.

Justin Marquis Ph.D. writes in the Classroom Aid article, Debates about Gamification and   Game-Based Learning(#GBL) in Education:

The Negatives

Those who have both feet firmly in the anti-gamification camp most often argue that there are no empirical studies that demonstrate real learning from games or that the skills learned in game play do not translate to the real world. That said, however, there are real negatives that can be associated with the introduction of gamification into education:

  • Cost – A fully game-based curriculum, or even one that relies heavily on games, represents a substantial increase in cost over standard book/paper/pencil education. For starters, there is the cost of the equipment, the cost of the software, and the additional expense of training teachers in the most effective pedagogical use of the medium.
  • Distraction from other objectives – The idea that playing games pulls learners from other more valuable skills must also be addressed. The underlying premise here is that games are fairly limited in their content and the context that they present for learning. This is true….
  • Social isolation – One of the biggest ongoing criticisms of games, and technology in general, is that it promotes anti-social behavior and isolates individuals. While some of this may have been true prior to the explosion of Web 2.0 technologies, it certainly is not any longer.  The focus of most new games is in social play. While players may not be interacting face-to-face they are interacting nonetheless. In fact, these technologically mediated interactions mirror much of the real-world communication that drives our personal lives and business. The process and social norms taught by these interactions represent very real and useful skills that translate perfectly outside of games.
  • Shortened attention span – This is the criticism of all modern media, and probably was a criticism of books when Guttenberg first started mass producing them. New technologies necessitate new ways of viewing the world and the nature of knowledge. Computer games are no different. The often rapid pace of action and the immediate feedback can make people expect the same kinds of fast-paced, instantaneous response of all things….

The Positives

While the limitations above are daunting and require significant shifting of educational and societal priorities in order to be overcome, they are worth addressing, particularly if weighed against the positive effects of gamification.

  • Technological literacy – Game play promotes literacy at many different levels, from technological to socio-emotional. At the very minimum, game play supports the development of skills necessary to run a computer, but it really goes far beyond that, as the installation, upkeep, and networking required for much game play also promotes high-level literacy skills in students (Marquis, 2009).
  • Multitasking mentality – The reality of our world is that we all multitask to a certain extent, splitting our attention between multiple screen, devices, and stimuli constantly. Games enhance this ability by forcing players to balance multiple kinds of inputs simultaneously in order to be successful. Try the fun multitasking game at the end of this post to see how well you can focus on multiple inputs.
  • Teamwork – While the isolationist tendencies of gamers have long been a popular stereotype, many current games are built on a social networking paradigm that not only allows for teamwork and collaborative play, but often requires it to be successful. This is one of the key skills required for working in a hyper-connected global economy.
  • Long-range planning – While the critique of games is that they shorten players’ ability to concentrate for extended periods of time, the opposite is actually true. Game designer and researcher Jane McGonigal refers to the hyper-intense and prolonged focus that gamers can experience in well-designed games and sees importance in the concept of “blissful productivity,” where players become so absorbed in the game that they lose track of time while working hard to achieve goals….
  • Individualized instruction – Because GBL focuses on each student playing and learning for themselves, individualized instruction is a natural part of the equation. This means two things; each student can work towards mastery, and each student can work at their own pace.

Many successful educators try to appeal to their students’ interest in order to engage them. With so many children and adults currently playing video games, games represent a natural way for teachers to reach a larger audience and have fun at the same time….                                                                   http://classroom-aid.com/2013/04/07/debates-about-gamification-and-game-based-learninggbl-in-education/

There should not be a one size fits all education system. For some children, video games are an appropriate education strategy.

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New York University study: 18% of higher income kids smoke Hookah

7 Jul

Douglas Quenqua reported in the New York Times article, Putting A Crimp In the Hookah about hookah.

Kevin Shapiro, a 20-year-old math and physics major at the University of Pennsylvania, first tried a hookah at a campus party. He liked the exotic water pipe so much that he chipped in to buy one for his fraternity house, where he says it makes a useful social lubricant at parties.
Like many other students who are embracing hookahs on campuses nationwide, Mr. Shapiro believes that hookah smoke is less dangerous than cigarette smoke because it “is filtered through water, so you get fewer solid particles….”
Many young adults are misled by the sweet, aromatic and fruity quality of hookah smoke, which causes them to believe it is less harmful than hot, acrid cigarette smoke. In fact, because a typical hookah session can last up to an hour, with smokers typically taking long, deep breaths, the smoke inhaled can equal 100 cigarettes or more, according to a 2005 study by the World Health Organization.
That study also found that the water in hookahs filters out less than 5 percent of the nicotine. Moreover, hookah smoke contains tar, heavy metals and other cancer-causing chemicals. An additional hazard: the tobacco in hookahs is heated with charcoal, leading to dangerously high levels of carbon monoxide, even for people who spend time in hookah bars without actually smoking, according to a recent University of Florida study. No surprise, then, that several studies have linked hookah use to many of the same diseases associated with cigarette smoking, like lung, oral and bladder cancer, as well as clogged arteries, heart disease and adverse effects during pregnancy. And because hookahs are meant to be smoked communally — hoses attached to the pipe are passed from one smoker to the next — they have been linked with the spread of tuberculosis, herpes and other infections…
http://www.nytimes.com/2011/05/31/health/31hookah.html?emc=eta1&_r=0

Kids mistakenly think hookah is safe.

Anthony Rivas reported in the Medical Daily article, 1 In 5 High School Seniors Smoke Hookah;

Educating Them About Its Harms Is Crucial:
There’s no questioning the stigma cigarette smoking has developed over the past couple of decades. The health risks associated with smoking has led to large declines in the amount of smokers in the U.S. since the 1970s, dropping from around 40 percent to about 18 percent of adults. But as always, as one popular vice fades away, another one gains steam — or in this case, smoke. Now, a new study from New York University has determined how popular hookah smoking has become among high school seniors.
Traditionally from the Middle East, hookah involves smoking flavored tobacco from a large water pipe. It’s become increasingly popular in North America and other parts of the world, in part, because it’s believed to be less harmful to the body — the tobacco is considered to be milder. However, that’s not entirely the case because hookah smokers tend to take more puffs in one session, resulting in similar, if not worse effects than smoking.
The NYU researchers’ study involved data from the Monitoring the Future nationwide study, which follows teens’ behaviors, values, and attitudes. Of the almost 15,000 kids aged 18 involved in the study, 5,540 were questioned about their hookah use between 2010 and 2012. They discovered that 18 percent, or almost one in five high school seniors, had smoked hookah within the 12 months prior to being surveyed.
Interestingly, they also found that “students of higher socioeconomic status appear to be more likely to use hookah,” said Dr. Joseph Palamar, assistant professor of population health at NYU Langone Medical Center, in a press release. “Surprisingly, students with more educated parents or higher personal income are at high risk for use. We also found that hookah use is more common in cities, especially big cities. So hookah use is much different from cigarette use, which is more common in non-urban areas….” http://www.medicaldaily.com/1-5-high-school-seniors-smoke-hookah-educating-them-about-its-harms-crucial-291584

Citation:

Hookah Use Among US High School Seniors
1. Joseph J. Palamar, PhD, MPHa,
2. Sherry Zhou, BAb,
3. Scott Sherman, MD, MPHa, and
4. Michael Weitzman, MDb
+ Author Affiliations
1. Departments of aPopulation Health, and
2. bPediatrics and Environmental Medicine, New York University Langone Medical Center, New York, New York
Abstract
OBJECTIVES: Prevalence of hookah use is increasing significantly among adolescents. This study aimed to delineate demographic and socioeconomic correlates of hookah use among high school seniors in the United States. We hypothesized that more impoverished adolescents and those who smoked cigarettes would be more likely to use hookahs.
METHODS: Data were examined for 5540 high school seniors in Monitoring the Future (years 2010–2012), an annual nationally representative survey of high school students in the United States. Using data weights provided by Monitoring the Future, we used multivariable binary logistic regression to delineate correlates of hookah use in the last 12 months.
RESULTS: Eighteen percent of students reported hookah use in the past year. Compared with white students, black students were at lower odds for use (adjusted odds ratio [AOR] = 0.27, P < .0001). High parent education increased the odds for use (AOR = 1.58, P $50/week (AOR = 1.26, P < .05) or $11 to $50 per week from other sources (AOR = 1.35, P < .01) also increased odds for use. Males and urban students were also at higher odds for use, as were users of alcohol, marijuana, and other illicit substances. Former cigarette smokers were at higher risk, and current smokers were at highest risk for use.
CONCLUSIONS: Adolescents of higher socioeconomic status appear to be at particularly high risk for hookah use in the United States. Prevention efforts must target this group as prevalence continues to increase. http://pediatrics.aappublications.org/content/early/2014/07/01/peds.2014-0538.full.pdf+html

Here is the press release from New York University:

Jul 6 at 10:26 PM
PUBLIC RELEASE DATE:
7-Jul-2014
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Contact: Lorinda Klein
lorindaann.klein@nyumc.org
212-404-3533
NYU Langone Medical Center / New York University School of Medicine
NYU researchers find 18 percent of high school seniors smoke hookah
Higher socioeconomic status associated with higher rates of hookah use
New York, NY – July 7, 2014 – While cigarette use is declining precipitously among youth, evidence indicates that American adolescents are turning to ethnically-linked alternative tobacco products, such as hookahs, cigars, and various smokeless tobacco products, according to a recent report from the Centers for Disease Control and Prevention (CDC).
Now a new study by researchers affiliated with New York University’s Center for Drug Use and HIV Research (CDUHR), in the August 2014 edition of Pediatrics identifies how prevalent Hookah use is and which teens are most likely to be using it.
The study, “Hookah Use Among U.S. High School Seniors,” published online July 7, used data from Monitoring the Future (MTF), a nation-wide ongoing annual study of the behaviors, attitudes, and values of American secondary school students. The MTF survey is administered in approximately 130 public and private schools throughout 48 states in the US. Roughly 15,000 high school seniors are assessed annually. This study examined data from the 5,540 students (modal age = 18) who were asked about Hookah use from 2010-2012. The researchers found the annual prevalence (use in the last 12 months) of hookah use was nearly 1 in 5 high school seniors.
“What we find most interesting is that students of higher socioeconomic status appear to be more likely to use hookah,” said Joseph J. Palamar, PhD, MPH, a CDUHR affiliated researcher and an assistant professor of Population Health at NYU Langone Medical Center (NYULMC). “Surprisingly, students with more educated parents or higher personal income are at high risk for use. We also found that hookah use is more common in cities, especially big cities. So hookah use is much different from cigarette use, which is more common in non-urban areas.”
Hookah, an ancient form of smoking, in which charcoal-heated tobacco or non-tobacco based shisha smoke is passed through water before inhalation, is rapidly gaining popularity among adolescents in the US. The researchers found those students who smoked cigarettes, and those who had ever used alcohol, marijuana or other illicit substances were more likely to use hookah.
“Tobacco use and exposure to secondhand smoke are the leading preventable causes of morbidity and mortality in the US,” said a study co-author Michael Weitzman, MD, a professor of Pediatrics and of Environmental Medicine at the NYULMC. “Cigarette use has decreased by 33% in the past decade in the US, while the use of alternative tobacco products such as hookahs has increased an alarming 123%. This is especially worrisome given the public misperception that hookahs are a safe alternative to cigarettes whereas evidence suggests that they are even more damaging to health than are cigarettes.”
While the US is experiencing an alarming increase in hookah use among adolescents, Dr. Palamar does point out that “Use tends to be much different from traditional cigarette smoking. Right now it appears that a lot of hookah use is more ritualistic, used occasionally–for example, in hookah bars, and not everyone inhales.”
“However, times are beginning to change,” notes Dr. Palamar. “Now something called hookah pens, which are similar to e-cigarettes, are gaining popularity. While not all hookah pens contain nicotine, this new delivery method might normalize hookah use in everyday settings and bring use to a whole new level.”
Researchers note that social stigma toward cigarette use appears to have played a large part in the recent decrease in rates of use, but they caution that it is doubtful these new hookah pens are frowned upon as much as cigarettes. Hookah pens also come in trendy designs and colors, which may be appealing to both adolescents and adults.
“These nifty little devices are likely to attract curious consumers, possibly even non-cigarette smokers,” said Dr. Palamar. “And unlike cigarettes, hookah comes in a variety of flavors and is less likely to leave users smelling like cigarette smoke after use. This may allow some users to better conceal their use from their parents or peers.”
Researchers conclude increased normalization might lead to increases in use, and possibly adverse consequences associated with repeated use. “This portends a potential epidemic of a lethal habit growing among upper and middle class adolescents,” said Dr. Weitzman. They stress that it is crucial for educators and public health officials to fill in the gaps in public understanding about the harm of hookah smoking.
###
Researcher Affiliations: Joseph J. Palamar, PhD–NYULMC, Department of Population Health; NYU CDUHR; Sherry Zhou, MD, MSc 2015, NYULMC, Departments of Pediatrics and Environmental Medicine; Scott Sherman, MD, MPH, NYULMC, Department of Population Health; Michael Weitzman, MD, NYULMC, Departments of Pediatrics and Environmental Medicine.
Declaration of Interest: The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.
Acknowledgements: This project was not funded. The National Institute on Drug Abuse, Inter-university Consortium for Political and Social Research, and Monitoring the Future principal investigators, had no role in analysis, interpretation of results, or in the decision to submit the manuscript for publication. Monitoring the Future data were collected through a research grant (R01 DA-01411) from the National Institute on Drug Abuse (NIDA), National Institutes of Health (NIH). The content is solely the responsibility of the authors and does not necessarily represent the official views of the principal investigators, NIH or NIDA
About CDUHR
CDUHR, funded by the National Institute on Drug Abuse, is the first center for the socio-behavioral study of substance use and HIV in the United States. The Center is dedicated to increasing the understanding of the substance use-HIV/AIDS epidemic, particularly among individuals in high-risk contexts. The Center’s theme is “Discovery to Implementation & Back: Research Translation for the HIV/Substance Use Epidemic.” The Center facilitates the development of timely new research efforts, enhances implementation of funded projects and disseminates information to researchers, service providers and policy makers.
About NYU Langone Medical Center
NYU Langone Medical Center, a world-class, patient-centered, integrated academic medical center, is one of the nation’s premier centers for excellence in clinical care, biomedical research, and medical education. Located in the heart of Manhattan, NYU Langone is composed of four hospitals—Tisch Hospital, its flagship acute care facility; Rusk Rehabilitation; the Hospital for Joint Diseases, the Medical Center’s dedicated inpatient orthopaedic hospital; and Hassenfeld Children’s Hospital, a comprehensive pediatric hospital supporting a full array of children’s health services across the Medical Center—plus the NYU School of Medicine, which since 1841 has trained thousands of physicians and scientists who have helped to shape the course of medical history. The Medical Center’s tri-fold mission to serve, teach, and discover is achieved 365 days a year through the seamless integration of a culture devoted to excellence in patient care, education, and research. For more information, go to http://www.NYULMC.org, and interact with us on Facebook, Twitter, and YouTube.
About New York University College of Nursing
NYU College of Nursing is a global leader in nursing education, research, and practice. It offers a Bachelor of Science in Nursing, a Master of Science and Post-Master’s Certificate Programs, a Doctor of Philosophy in Research Theory and Development, and a Doctor of Nursing Practice degree. For more information, visit https://nursing.nyu.edu/
Contact: Lorinda Klein, NYULMC | 212.404.3533 |917.693.4846 LorindaAnn.Klein@nyumc.org
Christopher James, CDUHR | 212.998.6876 | christopher.james@nyu.edu

As with a many issues adolescents face, it is important for parents and guardians to know what is going on in their children’s lives. You should know who your children’s friends are and how these friends feel about smoking, drugs, and issues like sex. You should also know how the parents of your children’s friends feel about these issues. Do they smoke, for example, or are they permissive in allowing their children to use alcohol and/or other drugs. Are these values in accord with your values?

Resources:

1. A History of Tobacco http://archive.tobacco.org/History/Tobacco_History.html

2. American Lung Association’s Smoking and Teens Fact Sheet Women and Tobacco Use
African Americans and Tobacco Use
American Indians/Alaska Natives and Tobacco Use
Hispanics and Tobacco Use
Asian Americans/Pacific Islanders and Tobacco Use
Military and Tobacco Use
Children/Teens and Tobacco Use
Older Adults and Tobacco Use http://www.lung.org/stop-smoking/about-smoking/facts-figures/specific-populations.html

3. Center for Young Women’s Health A Guide for Teens
http://www.youngwomenshealth.org/smokeinfo.html

4. Kroger Resources Teens and Smoking
http://kroger.staywellsolutionsonline.com/Wellness/Smoking/Teens/

5. Teens Health’s Smoking
http://kidshealth.org/teen/drug_alcohol/tobacco/smoking.html

6. Quit Smoking Support.com http://www.quitsmokingsupport.com/teens.htm

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