1 . Why was school created?    1    Especially on test days, many students wonder exactly why they’re being subjected to such terrible and unusual punishment!

If you’re honest with yourself, though, you know what a great place school is.    2    . Sure, tests can be stressful, but think of how boring life would be if you didn’t get to learn new things and see other people so often!

Schools are not a new invention. You may have seen some old one-room schoolhouses that have been around for several hundred years or more.    3    .

In fact, education dates back to the very first humans ever to live on Earth. Why? To survive, every generation has found it necessary to pass on its knowledge, skills, values, and traditions to the next generation. How can they do this? Education! Each subsequent generation (后代) must be taught these things.

    4    They educated young people within the family unit. Over time, however, populations grew and societies formed.

Rather than every family being responsible for education, people soon found out that it would be easier and more efficient to have a small group of adults teach a larger group of children.    5    .

2 . Nowadays, people are increasingly interacting with others in social media environments where algorithms control the flow of social information they see. People’s interactions with online algorithms may affect how they learn from others, with negative consequences including social misperceptions, conflict and the spread of misinformation.

On social media platforms, algorithms are mainly designed to amplify (放大) information that sustains engagement, meaning they keep people clicking on content and coming back to the platforms. There is evidence suggesting that a side effect of this design is that algorithms amplify information people are strongly biased (偏向的) to learn from. We call this information “PRIME”, for prestigious, in-group, moral and emotional information.

In our evolutionary past, biases to learn from PRIME information were very advantageous: Learning from prestigious individuals is efficient because these people are successful and their behavior can be copied. Paying attention to people who violate moral norms is important because punishing them helps the community maintain cooperation. But what happens when PRIME information becomes amplified by algorithms and some people exploit (利用) algorithm amplification to promote themselves? Prestige becomes a poor signal of success because people can fake prestige on social media. News become filled with negative and moral information so that there is conflict rather than cooperation.

The interaction of human psychology and algorithm amplification leads to disfunction because social learning supports cooperation and problem-solving, but social media algorithms are designed to increase engagement. We call it functional mismatch. One of the key outcomes of functional mismatch is that people start to form incorrect perceptions of their social world, which often occurs in the field of politics. Recent research suggests that when algorithms selectively amplify more extreme political views, people begin to think that their political in-group and out-group are more sharply divided than they really are. Such “false polarization” might be an important source of greater political conflict.

So what’s next? A key question is what can be done to make algorithms facilitate accurate human social learning rather than exploit social learning biases. Some research team is working on new algorithm designs that increase engagement while also punishing PRIME information. This may maintain user activity that social media platforms seek, but also make people’s social perceptions more accurate.

Word came that the annual school sports meet would take place next Friday through Saturday. At the exciting news, the whole class burst into cheers. Without any hesitation, we set about making     1     (arrange) for the grand gala for us students.

With the sports meet approaching, we could hardly concentrate on our daily routine. Every day, we spent much of our spare time     2     (talk) about the weather for fear that the sports meet might be postponed again. Then finally came the big day, when the sports meet was held as     3     (schedule). The sports meet was pretty impressive. One of the highlights     4     (be) the parade before the start of the race. Students were marching past the podium with slogans high up in their hands, while spectators were screaming    5    (crazy). Shortly after the parade was over, the race started. Well known for running in junior high school, I     6     (recommend) to enter for the 3000-meter running race, representing my class.

Time was ticking away. Before I knew it, it was my turn to step onto the track. But all of     7    sudden, I felt a bit panicky. As I hadn’t received any training recently, I puffed and panted halfway. I was about     8     (quit) when my classmates cheered me on all the way. Anyway, I made it to the finishing line. Unable to earn a single point for my class, I was     9    low spirits. However, my friends came over and encouraged me to cheer up. It was their encouragement    10    helped heal the pain of failure.

Now two weeks have passed, but the memory still stay fresh in my mind. Disappointed as I am, I never regret taking part in the race. After all, being part of the sports meet is what I really care about.

7 . Environmental Books For Kids

It is a great book on how anyone can take action and make a difference. In it, Marcy, a young girl, wants to plant a garden in the vacant lot(空地) of her city block. The book describes every step of building a community garden for everyone to share. It comes with a handy guide on how you can start your own community garden!

This book is a wonderful story of problem-solving and perseverance (坚持不懈), as it tells the story of a young girl who decides to stop the wild wind from blowing by planting trees. It is a great read explaining the important role of trees in our lives and the planet as well as the importance of nature-based solutions.

If you want to learn more about native people and the importance of protecting water, this is the book for you. It is a story of a young girl who stands up for environmental justice (正义) and becomes an activist who fights to protect the world from pollution.

A pangolin is to be unlawfully sold at the market. Luckily for her, a little girl, who knows that pangolins are friendly animals with feelings just like humans, asks her mother to buy Pangolina and set her free. If you love animals and you want to learn more about the problems of wildlife traffic as well as the importance of protecting endangered animals, this wonderful book is a good choice.

8 . Advances in AI and machine learning have sparked interest from governments that would like to use these tools for patrolling (巡查) purposefully before hand to prevent crime. However, early efforts at crime prediction have been controversial, because they do not allow for systematic biases (偏见) in police enforcement and its complex relationship with crime and society.

University of Chicago (UC) data and social scientists have developed a new algorithm (算法) that forecasts crime by learning patterns in time and geographic locations from public data on violent and property crimes. It has demonstrated success at predicting future crimes one week in advance with approximately 90% accuracy.

The new tool was tested and validated using historical data from the City of Chicago around two broad categories of reported events: violent crimes and property crimes.

The new model isolates crime by looking at the time and spatial coordinates (坐标) of separate events and detecting patterns to predict future events. It divides the city into spatial sections roughly 1,000 feet across and predicts crime within these areas instead of relying on traditional neighborhood or political boundaries, which are also subject to bias. The model performed just as well with data from seven other US cities.

Ishanu Chattopadhyay, senior author of the study, is careful to note that the tool’s accuracy does not mean that it should be used to direct law enforcement, with police departments using it to flock to neighborhoods ahead of time to stop crime. Instead, it should be added to a toolbox of urban policies and policing strategies to address crime.

“We created a digital twin of urban environments. If you feed it data from what happened in the past, it will tell you what’s going to happen in future. It’s not magical; there are limitations, but we tested it and it works well,” Chattopadhyay said. “Now you can use this as a model tool to see what happens if crime goes up in one area, or there is increased enforcement in another area. If you apply all these different data, you can see how the system evolves in response.”