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Computer Science Questions and Answers
How can we use such data to answer larger scale questions about early experiences with programming? To maximize discussion time at the workshop, paper presentation times will be very short.
Last week, I was in a research meeting with Bob Bain, a history and education professor here at U. He said that all learning in history starts from a problem. That gave me pause.
Bob explained that he defines problem as John Dewey did, as something that disturbs the equilibrium. We each have our own stories that we use to explain the world, and these make up our own personal equilibria.
A good history teacher sets up these conflicts, disequilibria, or problems.
Bob says it can be easy enough to create, simply by showing two contrasting accounts of the same historical event. Research in the learning sciences supports this definition of learning.
Computer Science Interview Questions and Answers
No one teaches it to us. We are not taught to have goals, nor to attempt to develop plans to achieve those goals by adapting old plans from similar situations. We need not be taught this because the process is so basic to what comprises intelligence. Learning is a natural act. Those were roles I was familiar with. Bob was describing a different role. Bob got me thinking about the role of the teacher in the computer science class.
We can sometimes be a guide, a coach, and orchestrator — when students are working away on some problem or project. But sometimes, we have to be the provocateur. We should always start from a problem. In science education, this is easy. Kids naturally do wonder why the sky is blue, why sunsets are more red, why heat travels along metal but not wood, and why stars twinkle.
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But in introductory classes, students already use a computer without problems. They may not see enough of real computing to wonder about how it works. The teacher has to generate a problem, inculcate curiosity — be a provocateur.
We should only teach something when it solves a problem for the student. A lecture on variables and types should be motivated by a problem that the variables and types solve. Nobody remembers things they will need in the future.
Learning results when you need new knowledge to resolve the current problem, disequilibria, or conflict. There is no public data on trans workers or other gender minorities. For black workers, the picture is even worse. For example, only 2.
Given decades of concern and investment to redress this imbalance, the current state of the field is alarming. Without a doubt, those percentages do not match the distribution of gender and ethnicity in the population at large. But we already know that participation in CS does not match the population.
How do the AI distributions match the distribution of gender and ethnicity among CS researchers? A sample to compare to is the latest graduates with CS PhDs. Only 1. From an ethnicity perspective, Google, Facebook, and Microsoft are doing surprisingly well.
The AI Now Institute report is concerned about intersectionality.
Multiple Choice Questions in Computer Science
The issues of women are not identical across ethnicities.Bob was describing a different role. Reviewer's Comments from Earlier Editions "very highly recommended to all those whose activities bring them anywhere within spitting distance of computers.
Jan Even a miraculous encounter with a "businessman" named Gideon is forgotten http: Feb Details if other: Fabozzi, , Art, pages. Priya Patel.