What do you think this image is saying? How does it relate to or comment on society? Can you relate to it personally in any way?
What is your opinion of its message?
Tell us in the comments, then read the related Opinion piece to learn more about this image.
Find many more ways to use our Picture Prompt feature in this lesson plan.
Before reading the article:
Last week, The Times reported that a teenage girl in China had found a loophole for her homework: She bought a robot that mimicked her handwriting. Instead of having to manually copy phrases or selections from a textbook dozens of times, a repetitive task common in learning Chinese, she could just teach the robot to do it for her.
What do you think: Did she cheat, or should she be applauded for her initiative? Why?
Now, read the article, “Chinese Girl Finds a Way Out of Tedious Homework: Make a Robot Do It,” and answer the following questions:
1. How did most commenters on Weibo, a popular social media platform in China, seem to feel in response to the question we pose above? With which comment do you most agree?
2. What does proficiently reading and writing in Chinese require, and why is that an argument for doing homework like this oneself?
3. What did the girl’s mother do when she discovered the robot? Why do you think she reacted that way?
4. According to the article, “The robots are a modern update to a technology that has long existed.” What examples does it give to show that?
5. What is your reaction to the last two sentences of the article? Do you think finding ways to “cut corners” on assignments is something students everywhere have always done and will always do? What examples can you give from your own experience, whether it was a shortcut you used yourself or a technique you simply observed?
Finally, tell us more about what you think:
• Feb. 28 is Digital Learning Day, which celebrates “any instructional practice that effectively uses technology to strengthen a student’s learning experience.”
What would you put in that category? In other words, when in your history as a student has a teacher used technology well to help you learn? When, on the other hand, have you been in a classroom situation where technology was not used well, and either hindered or had no real impact on your learning? Make two lists and share your ideas with your classmates. What conclusions can you draw? What recommendations about technology in school might you give your teachers?
• If you would like further fodder for thinking, in 2012 we made a list of 40 Years of Times EdTech Reporting with links to articles from 1970 to 2002, all about technology in classrooms.
In it you will find ideas for teaching and learning with the list such as choosing a piece to share with others and having them guess in what year it was written. But you could also simply choose one of the pieces to read and annotate: Put a check mark next to things that are still true today, and an X next to the things that have changed. What do your annotations reveal? Why?
Community based research is research carried out by, with and for a community. It is explicitly not carried out on their behalf by an external agency, even if the aim is to benefit them. It is intended to help them help themselves, on their own terms.
There are inspiring examples of community based research in highly diverse communities all over the world. The need for community members to conduct research into their own lives may result from long-term poverty and neglect, from sudden disastrous climatic events, or from the accumulated migration of people due to persecution or war. Whatever the reason, external assistance can be agonisingly slow, or non-existent, which leads to the question ‘what can communities do to help themselves?’ – and that is hard to answer. But we will address it more successfully if we collaborate and learn from each other, which is why we created this course Community Based Research: Getting Started.
There are 65 million people across the world who are refugees from their own land. This is one of our greatest global challenges. Displacement creates extreme conditions in which people are utterly disempowered in all aspects of their life, and are placed in a position of vulnerability, forced to depend on the kindness and help of others. Of course, they lack the help they need, but they are not helpless. Migrant communities desperately want the chance to help themselves, but need to know how to get started.
The same is true for other disadvantaged communities. Millions of people in developing countries, and even in developed countries, still live in poverty with little hope of change. Community based research could be the means for a community to discover ways of transforming their most pressing problems.
Community based research is already helping improve conditions in different communities. Local leaders and professionals, by working with the locals directly to listen to their needs, co-create potential solutions, take action, and evaluate the results.
On the course we meet some of these individuals. There is the group of mothers in a refugee camp who are convened by a local NGO to discuss how to deal with their children who do not want to go to school, and when they begin to see changes themselves, then involve other mothers in similar groups, gradually extending the impact of change.
A group of children in a Beqaa school
There is the group of young journalists, who grew up in a camp, who were given just a few weeks training by another NGO, and now run their own online news channel, portraying positive stories of what refugees can bring to their host city.
Or take the the Slum Dwellers International model, which describes how people work through an ‘action research model’ with the whole community to work out their own solutions to the common problems of no toilet, no electricity, no help from government. It’s now a model now working in 35 countries.
The scale of migration problems is massive, and it cannot be solved without the deep engagement of the people involved. This is why we’ve created the online course Community Based Research: Getting Started. Professionals, community leaders, and local people can potentially learn so much from each other – this course is an opportunity for the constructive exchange of ideas and experience.
You might want to recommend the course to colleagues, other professionals, or community leaders who need these research techniques You could promote it within your own community to work together as a group on the course as you establish your own local project. Or you could sign up as a participant to guide such research or sign up your students, and blend it in with your own research methods.
The following course in Statistics is provided in its entirety by Atlantic International University’s “Open Access Initiative” which strives to make knowledge and education readily available to those seeking advancement regardless of their socio-economic situation, location or other previously limiting factors. The University’s Open Courses are free and do not require any purchase or registration, they are open to the public.
The course in Statistics contains the following:
The Administrative Staff may be part of a degree program paying up to three college credits. The lessons of the course can be taken on line Through distance learning. The content and access are open to the public according to the “Open Access” and ” Open Access ” Atlantic International University initiative. Participants who wish to receive credit and / or term certificate , must register as students.
Statistics is the science of learning from data, and of measuring, controlling, and communicating uncertainty; and it thereby provides the navigation essential for controlling the course of scientific and societal advances (Davidian, M. and Louis, T. A., 10.1126/science.1218685). Statisticians apply Statistical thinking and methods to a wide variety of scientific, social, and business endeavors in such areas as astronomy, biology, education, economics, engineering, genetics, marketing, medicine, psychology, public health, sports, among many. “The best thing about being a Statistician is that you get to play in everyone else’s backyard.”
| Video Conference Lecture Materials |
One of the first lessons taught in Algebra is Solving Equations. This is the basis of Algebra and many other lessons taught in Algebra will rely on knowledge of this skill.
So, what is an equation?
An equation is a mathematical statement that shows that two quantities are equal.
| Video Conference |
| Lecture Materials |
Lesson 3: ANALYTIC GEOMETRY
We begin to seriously channel Euclid in this tutorial to really, really (no, really) prove things–in particular, that triangles are congruents. You’ll appreciate (and love) what rigorous proofs are. It will sharpen your mind and make you a better friend, relative and citizen (and make you more popular in general). Don’t have too much fun.
| Video Conference :Lecture Materials |
Lesson 4: DEFINITION & HISTORY OF GEOMETRY
The Babylonians replaced the older (4000 BC – 2000 BC) Sumerian civilization around 2000 BC. The Sumerians had already developed writing (cuniform on clay tablets) and arithmetic (using a base 60 number system). The Babylonians adopted both of these. But, Babylonian math went beyond arithmetic, and devloped basic ideas in number theory, algebra, and geometry. The problems they wanted to solve usually involved construction and land estimation, such as areas and volumes of rectangular objects. Some of their methods were rules that solved specialized quadratic, and even some cubic, equations.
| Video Conference Lecture Materials |
Lesson 5: Descriptive Statistics
Descriptive Statistics are typically distinguished from inferential Statistics. With descriptive Statistics you are simply describing what is or what the data shows. With inferential Statistics, you are trying to reach conclusions that extend beyond the immediate data alone. For instance, we use inferential Statistics to try to infer from the sample data what the population might think. Or, we use inferential Statistics to make judgments of the probability that an observed difference between groups is a dependable one or one that might have happened by chance in this study. Thus, we use inferential Statistics to make inferences from our data to more general conditions; we use descriptive Statistics simply to describe what’s going on in our data.
| Video Conference: |
| Lecture Materials |
Lesson 6: ANALYSIS OF DATA AND GRAPHIC OF FREQUENCY DISTRIBUTIONS
While data analysis in qualitative research can include Statistical procedures, many times analysis becomes an ongoing iterative process where data is continuously collected and analyzed almost simultaneously. Indeed, researchers generally analyze for patterns in observations through the entire data collection phase (Savenye, Robinson, 2004). The form of the analysis is determined by the specific qualitative approach taken (field study, ethnography content analysis, oral history, biography, unobtrusive research) and the form of the data (field notes, documents, audiotape, videotape).
| Video Conference: |
| Lecture Materials |
Lesson 7: PROBABILITY AND Statistics
Most experimental searches for paranormal phenomena are Statisticsal in nature. A subject repeatedly attempts a task with a known probability of success due to chance, then the number of actual successes is compared to the chance expectation. If a subject scores consistently higher or lower than the chance expectation after a large number of attempts, one can calculate the probability of such a score due purely to chance, and then argue, if the chance probability is sufficiently small, that the results are evidence for the existence of some mechanism (precognition, telepathy, psychokinesis, cheating, etc.) which allowed the subject to perform better than chance would seem to permit.
| Video Conference: |
| Lecture Materials |
Lesson 8: SAMPLING THEORY StatisticsS SAMPLING THEORY
A probability sampling method is any method of sampling that utilizes some form of random selection. In order to have a random selection method, you must set up some process or procedure that assures that the different units in your population have equal probabilities of being chosen. Humans have long practiced various forms of random selection, such as picking a name out of a hat, or choosing the short straw. These days, we tend to use computers as the mechanism for generating random numbers as the basis for random selection.
| Video Conference: |
| Lecture Materials |
Lesson 9: EXPERIMENTAL DESIGN AND THE VARIANCE
Deviations about the mean of a population is the basis for most of the Statisticsal tests we will learn. Since we are measuring how widely a set of scores is dispersed about the mean we are measuring variability. We can calculate the deviations about the mean, and express it as variance or standard deviation. It is very important to have a firm grasp of this concept because it will be a central concept throughout the course.
| Video Conference: |
| Lecture Materials |
Lesson 10: CORRELATION AND REGRESSION
Correlation and linear regression are the most commonly used techniques for investigating the relationship between two quantitative variables. The goal of a correlation analysis is to see whether two measurement variables co vary, and to quantify the strength of the relationship between the variables, whereas regression expresses the relationship in the form of an equation.
| Video Conference: |
| Lecture Materials |
We understand how busy adults do not have time to go back to school. Now, it’s possible to earn your degree in the comfort of your own home and still have time for yourself and your family. The Admissions office is here to help you, for additional information or to see if you qualify for admissions please contact us. If you are ready to apply please submit your Online Application and paste your resume and any additional comments/questions in the area provided. (Online Application) (Request Info)
Atlantic International University
800-993-0066 (Gratis en EUA)
808-924-9567 (Internacional)
Last month, Codecademy and Warby Parker came together to work on a special Learn SQL from Scratch Capstone Project. It was during this time when I met Ryan Tuck, a Data Engineer at Warby, who played a major part in this partnership. So when he decided to drop by our office for the final QA round, I had to break out my notebook and ask some questions. Enjoy.
At Warby Parker, data engineers are responsible for creating and maintaining the plumbing required to support the data and reporting needs of the business. We use software engineering practices to automate the work of data cleaning, normalizing, and model building so that data is always ready to be consumed by data analysts in every department.
On data engineering, we use Python as our general purpose programming language, as do most of the other teams in our Technology department. When it comes to databases, we use PostgreSQL for the majority of our SQL needs, and are beginning to use Amazon Athena and Google BigQuery for some of our larger datasets. We use Looker as our exclusive business intelligence entry point to all of this data.
I’ve had the privilege of working with a lot of of smart people in every department at our company to help them solve their varied data needs, from reconciling financial data with the Accounting team to automating and modeling standardized performance metrics for our team of over 200 customer experience advisors.
As part of a team of five supporting the data needs of a rapidly growing company, I’ve tried where possible to focus on helping our analysts solve their own problems. This includes helping people learn Python and commit to our codebase, guiding the creation of data models in SQL, and encouraging people to submit pull requests to add features in Looker, our BI tool.
Seeing dozens of otherwise “non-technical” colleagues opening up PRs on a daily basis, and consequently being part of the democratization of tech that we value at Warby Parker, is probably the most rewarding “project” I’ve been a part of.
One project finished recently during our first annual “Hackweek” is called Pipes, which allows anyone at the company to easily move large amounts of data from wherever to wherever (Looker, Google Sheets, PostgreSQL, BigQuery, etc) on a regular cadence, or manually through a simple one-line chatbot interface. The adoption has been overwhelmingly positive and we’re looking to grow this sort of tooling out even more.
“We use software engineering practices to automate the work of data cleaning, normalizing, and model building so that data is always ready to be consumed by data analysts in every department.”
I’ve always been drawn to analytical fields like math, and became pretty proficient in Excel during some internships in college. Once I had learned to program and learned more about data science and its applications in artificial intelligence, I knew that anything I could do to immerse myself in the world of data would be a step in the right direction.
Three and a half years ago, I landed a job as a junior software engineer at Warby Parker not fully knowing what I was in for, but am so glad I got the opportunity to help build tools to support an interesting and ever-changing data-driven culture here.
I had a background in C++, and was exposed to Python through an Intro to Data Science course. When Warby Parker hired me onto the Data team in 2015, I had never written a SQL query in my life, but picked it up quickly and within a few months started up internal SQL training classes, which I still teach on a monthly basis.
This is Bayes’ Theorem, which is an equation that describes how to update probabilities given new evidence. Two summers ago I worked on building a tool to help predict weekly fantasy football performance. Some colleagues suggested a Bayesian approach would be appropriate, since there aren’t really enough data points in an NFL season to be able to use statistical approaches that require larger datasets, and I’d want to regularly update my predictions after each player’s latest performance.
I did a deep dive into understanding the (simple) math underlying Bayes’ Theorem and came out of that experience with a whole new worldview, understanding my entire knowledge of the world as a big and intricate probabilistic model that I was continuously updating with every experience I ever have. It was pretty transformative, and I figured that was worth a tattoo.
Donald Knuth said, “Premature optimization is the root of all evil.” I’ve generally found this to be true, and try to live by it in my work. For example, I’ll generally prefer to keep a data model simple by rebuilding it for all time on a daily basis using a single SQL query instead of making a more complicated model that requires iteratively adding to a table, keeping track of state, updated timestamps, when something last ran, etc.
A wise man once said, “Duplicating data makes things go fast,” but databases are already impressively fast to begin with, without implementing anything to improve performance. Ultimately, I almost always approach a problem thinking about optimizing for my time over machine time, for readability over performance, and for introducing as little cognitive overhead as is required by the problem at hand. Only once performance issues or readability issues present themselves will some code be worth a rewrite.
Sure! Have you ever written a query that yields some result set and you think, “I’d love to query the stuff I just produced like it was a table?” Enter the WITH clause.
Suppose I have a mega query that gives the transaction summaries:
select
transactions.date as transaction_date,
sum(items.price) as total_cost,
count(*) as number_of_items
from
transactions
inner join
customers
on
customers.id = transactions.customer_id
inner join
transaction_items
on
transactions.id = transaction_items.transaction_id
inner join
items
on
items.id = transaction_items.item_id
Using WITH, I can create a temporary table within my query that I can SELECT from and treat it just like a regular old table.
I will put everything from the previous query in a parentheses and use WITH to give it the name transaction_summaries.
Then I’ll apply the date and customer filtering down below for a more readable query, to separate out all the JOIN logic from the actual WHERE filters that I want to apply on that data.
with transaction_summaries as (
select
transactions.date as transaction_date,
sum(items.price) as total_cost,
count(*) as number_of_items
from
transactions
inner join
customers
on
customers.id = transactions.customer_id
inner join
transaction_items
on
transactions.id = transaction_items.transaction_id
inner join
items
on
items.id = transaction_items.item_id
)
select
*
from
transaction_summaries
where
first_name = 'beyonce'
and
transaction_date > '2018–01–01'
order by
total_cost desc
limit
5
If you’re familiar with subqueries, this does a similar thing but makes the SQL far more readable, even if your query isn’t quite as performant as it would have been. This is essentially an implementation of the mantra “Don’t Repeat Yourself” that’s common in the world of programming.
Huge shout out to Ryan and the whole Warby Parker team for making this partnership happen. Special hat tips for behind-the-scenes support from:
It’s been an absolute pleasure. And of course, the fam at Codecademy. You know who you are. Couldn’t do it without you.
With Airbnb came a revolution of sorts in the world of vacation travel and culture. We sat down with Luba Yudasina, a YouTuber, an opera singer, and a Software Engineer on the Airbnb’s Homes Platform team, to discuss software engineering and her programming journey—from Codecademy to Airbnb!
Homes Platform’s mission is to create the building blocks to power all Homes categories. Any project undertaken by our team should be reusable and extensible in some way. This means that as a backend engineer, I have a lot of opportunities to work on impactful technical projects that create systems and services to support Homes, as well as collaborate across teams to come up with the best architectural decisions and designs.
Recently, our team wrote a blog post on classifying Room Types into categories using Machine Learning and computer vision. The room-type classification problem largely resembles the ImageNet classification problem, except our team’s model outcomes are customized room-types.
After a few experiments with various models, the team chose ResNet50 due to its good balance between model performance and computation time. To make it compatible with our use case, we added two extra fully connected layers and a Softmax activation in the end.
At Airbnb we use Ruby, Java, Kotlin, JavaScript, Swift, Ruby on Rails, React for frontend, iOS and Android for native development.
I went to the University of Waterloo in Canada—a university with the biggest co-op program in the world. Co-op means that to obtain a bachelor’s degree you must complete a certain number of internships. If you are in Engineering at Waterloo, you must complete 5 internships to graduate.
In my first and second years, I interned at chemical engineering companies and afterwards I couldn’t see myself working in the field full-time. That’s why I’m particularly grateful that I studied at Waterloo: if not for co-op, I probably would not have realized I didn’t want to work in chemical engineering until getting a full-time job after graduation.
I happened to have a lot of friends in Computer Science and Software Engineering right when I realized Chem Eng wasn’t for me. They really encouraged me to try coding, and when I decided to follow their lead I never looked back! My first online programming course was Web Development on Codecademy 🙂
“It’s a really cool time to be a software engineer and even cooler to be a female software engineer, because this is the time when women start to embrace their own unique identities and be ok with not being ‘one of the dudes.'”
-Luba Yudasina
When I decided I wanted to learn computer science on my own, my goal was to get an internship in the field because working as a software engineer at a tech company would be the best test to really know if it was for me.
I happened to be in Munich, Germany on academic exchange for a whole year when I was learning how to code, so I hustled as much as I could while being there to get experience to learn quicker and have something to put down on my tech resume.
Almost immediately after arriving in Germany, I got a part time job as a developer at a game publishing company. I had a good friend in Computer Science at my German university: her and I ended up working on an Android app as a side project, etc. When I was ready, I started preparing for technical interviews. I then leveraged my network to refer me to companies and do mock technical interviews with me.
Yelp was really random though—a Yelp recruiter looked at my LinkedIn profile and didn’t even message me, but I messaged them anyway asking about internship opportunities, and that’s how I got my interview there!
Code searching! A lot of software engineering is problem solving and a lot of it is understanding other people’s code and the reasoning behind writing it a certain way. Searching through the codebases is almost essential to my day to day. Whenever I build something new or build on top of already existing tech, I need to understand how it works and is written, and code search is vital to this.
At Airbnb we use Google’s Codesearch for these purposes, but developers (myself included) also frequently use their IDEs to search for relevant code. I mostly use RubyMine or IntelliJ (depending on the codebase I’m working with).
It’s a really cool time to be a software engineer and even cooler to be a female software engineer, because this is the time when women start to embrace their own unique identities and be ok with not being “one of the dudes.”
I think it’s particularly important to redefine the stereotypes, and I hope that with my own example I can show young girls and women interested in the field that you don’t have to give up your feminine side to be a software engineer and still be into fashion, or makeup, or art (I personally sing opera) and have other interests outside of coding and be successful in the field.
Don’t be discouraged, learn and absorb as much as you can! If you don’t understand a concept or can’t build a project right away, know that with practice, perseverance and concentration you will get there!
Take advantage of such amazing tools as Codecademy that are there for you to take and learn. Learning anything new can be frustrating, but knowing that you can do it, staying curious, asking questions and not losing your motivation is the key to success.
Huge shoutout to Luba for this insightful interview. It’s always incredibly moving to see a Codecademy learner go on to do bigger things. Go subscribe to her YouTube channel, Life of Luba.
And thank you to the whole Homes Platform/Engineering team at Airbnb for the support. Check out their wonderful open source projects on airbnb.io.
How do you feel about gym class? Do you look forward to it each day? Or do you approach it with dread? Why do you feel the way you do?
How do you feel about exercise in general? Is it something you find fun and enjoyable? Or do you actively avoid it?
Tell us in the comments, then read the related article to find out how your feelings about gym class may impact your exercise habits.
Find many more ways to use our Picture Prompt feature in this lesson plan.
1. difficult to handle or use especially because of size or weight
2. not elegant or graceful in expression
_________
The word cumbersome has appeared in 123 articles on NYTimes.com in the past year, including on Jan. 15 in “The Race to Create the Coolest Smart Home Devices Is Hotter Than Ever” by Janet Morrissey:
Buying, setting up and connecting smart devices can be costly, cumbersome, and time-consuming. Indeed, as many as one-third of smart speakers are still in their boxes, according to Forrester.
“You need people to be patient and comfortable with working through multiple steps of instruction,” he said.
Do you ever get advice from people of different generations? If so, do you find the advice insightful or helpful? Do you ever find that it misses the mark?
Last week former President Barack Obama spoke in Oakland, Calif., at a town hall for My Brother’s Keeper, an initiative to mentor young black men that he started in 2012. You can watch his speech here.
One critic believes that Mr. Obama fails to see “the beautiful and complex range of black culture.” In “Why Does Obama Scold Black Boys?” Derecka Purnell writes:
On Tuesday, former President Barack Obama spoke in Oakland, Calif., at a town hall for My Brother’s Keeper, an initiative to mentor young black men that he started after George Zimmerman killed Trayvon Martin in 2012.
He and the basketball player Stephen Curry discussed mentorship, masculinity and mass incarceration. But his scolding of black boys drew the most attention.
“If you are really confident about your financial situation,” Mr. Obama told the crowd, “you are probably not going to be wearing a eight-pound chain around your neck.”
“Because you know,” he continued, “‘Oh, I got a bank account.’ I don’t have to show you how much I got. I feel good.”
His comments disappointed me because they’re part of problematic practices, like calling out black children for having ghetto names like mine or wearing Air Jordans. Such remarks by Mr. Obama reflect his administration’s failure, and to an extent that of My Brother’s Keeper, to tackle the systemic inequality that shapes black people’s lives in America.
I went to Harvard Law School decades after Mr. Obama and his wife, Michelle, graduated. When I was there in 2014, nobody wore thick gold chains to show off their wealth. They wore thin ones to match their David Yurman bracelets. Canada Goose down jackets may as well have been part of a uniform during Boston winters. Students “summered,” took “gap years” and graduated from “Sidwell.” Harvard was the first place I saw a Rolex in real life. I wonder if it was the same model as the $15,000 Rolex that Mr. Obama wears in the Kehinde Wiley painting of him in the National Portrait Gallery.
My Brother’s Keeper’s participants are less like my wealthy law school classmates and more like my brothers, cousins and childhood friends. Like my family, many of them have no reason to be “really confident” about their financial situation. And Mr. Obama is partly to blame for that.
Black families were hit the hardest during the financial crisis. Because of falling homeownership rates and layoffs, blacks lost over half their wealth between 2005 and 2009, according to a report from the National Association of Real Estate Brokers. Instead of bailing out families, Mr. Obama bailed out banks, failing to pursue specific policies that would have addressed the decline in black homeownership rates and equity.
The economist William Darity painted a stark picture in a 2016 article in The Atlantic: “Blacks working full time have lower levels of wealth than whites who are unemployed. Blacks in the third quintile of the income distribution have less wealth (or a lower net worth) than whites in the lowest quintile. Even more damning for any presumption that America is free of racism is our finding that black households whose heads have college degrees have $10,000 less in net worth than white households whose heads never finished high school.”
Yet Michelle’s husband (as he introduced himself at the town hall) uses My Brother’s Keeper to change life outcomes for boys of colors. But its solution to financial insecurity and the racist violence that led to Trayvon’s murder are the same: community mentorship. This pales in comparison to reparations or any major social or legislative intervention that justice requires.
At the Oakland event, Mr. Obama doubled-down on his finger-wagging. “Oftentimes racism, historically in this society, sends you a message that you are less than and weak,” Mr. Obama said. “We feel like we got to compensate by exaggerating certain stereotypical ways that men are supposed to act, and that’s a trap that we fall into that we have to pull out of.”
This is also how conservatives depict black people, as the philosopher Cornel West explained in “Race Matters.” Conservatives accuse them of being lazy and demand self-improvement. Liberals pity blacks for not being able to help themselves. But, to both groups, the burden is on black people to fix themselves. Neither conservatives nor liberals sufficiently challenge racist people or institutions that have long exploited poor people and people of color.
To put it another way: Programs like My Brother’s Keeper insist on making better versions of Trayvon Martin, the black victim, instead of asking how to stop creating people like George Zimmerman, the racist vigilante. Rather than encouraging them to dismantle the systems that deepen wealth inequality, Mr. Obama tells black boys to tuck their chains.
Students, read the entire essay, then tell us:
— Have you ever noticed older generations giving advice to — and wanting to improve — young people? Have you found the advice insightful or helpful? Do you ever think that it misses the mark?
— Should older generations, as the author writes, help young people of color learn how to “tackle the systemic inequality that shapes black people’s lives in America?” Is that the most effective and empowering approach to education and meaningful social change?
— Or, should older generations instead help young people “fix themselves” — by changing what they wear, how they speak, or how they act, so they are more likely to be successful in America? And, is that approach, in the end, a better way to reduce systemic inequality?
— Are these two types of advice and mentorship mutually exclusive? Is only one approach the fair and just approach? Or can they both be effective?
— Do you think Mr. Obama is “scolding” black boys and “finger-wagging?” Is he calling out black children for making legitimate cultural choices instead of placing responsibility squarely on an unjust society? Or is he just being real about what it takes to be successful in America, based on his own experiences?
— A comment selected as a Times Pick states: “Paradoxically, international fashion trends right now are heavily derived from black hip-hop and black athletic culture. Karl Lagerfeld made heavy hip-hop derived chains a signature of his daily look. Apparently it’s ok to ‘dress black’ so long as you’re white with status.” Do you think there is a double standard for how black people and white people are supposed to dress to be successful?
Students 13 and older are invited to comment. All comments are moderated by the Learning Network staff, but please keep in mind that once your comment is accepted, it will be made public.
Before reading the article:
Did you watch the Academy Awards on Sunday night? Did your favorites win? Did you check out the red carpet looks?
Now, read the article, “Nobody Hosted the Oscars. And They Did a Fine Job of It,” and answer the following questions:
1. James Poniewozik, who wrote the article, compared watching the Academy Awards to “eating off a conveyor belt.” How did he explain this statement?
2. Who made up the “string of mini-hosts?”
3. What awards did Hannah Beachler and Ruth E. Carter win? How did they make Oscar history?
4. What does the article suggest may be the “secret” to awards shows?
5. What examples are given for the suggestion that magical moments are possible if people “get out of the way and hope?” Do you agree?
Finally, tell us more about what you think:
“What Do the Oscars Gain by Losing a Host?” — an article published in January — suggested reasons this year’s telecast may be just fine without a host. Kyle Buchanan writes:
… One of the academy’s oft-stated priorities is to trim the telecast to a slim three hours, and with no monologue nor a host to keep cutting back to, the proceedings should at least be shorter.
It’s here I should note that the host tends to be both the most overrated and underrated part of any Oscar telecast. Overrated, because after that first commercial break, the host pops up much less frequently than you might think, a format that allows presenters and winners to come to the fore. Outside of the monologue, you’re liable to remember only one other significant moment from any given Oscar host.
If you watched the Oscars on Sunday night and have seen previous ceremonies that had a host, how do the two compare? Do you think the Oscars are better with a host — or does it not matter?
Do you agree that the host’s role tends to be “the most overrated and underrated part” of the show? Explain. Nevertheless, if the Academy Awards were to feature a host or hosts next year, who would you like to see? Why?
