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Learning The TensorFlow Way of Linear Regression

#artificialintelligence

We will loop through batches of data points and let TensorFlow update the slope and y-intercept. Instead of generated data, we will use the iris dataset that is built into the Scikit Learn. Specifically, we will find an optimal line through data points where the x-value is the petal width and the y-value is the sepal length. We choose these two because there appears to be a linear relationship between them, as we will see in the graphs at the end. We will also talk more about the effects of different loss functions in the next section, but for now we will use the L2 loss function.


How observability helps Quill in its mission to help kids write better

#artificialintelligence

One of the concerns as schools closed at the height of the COVID-19 lockdown earlier this year was its impact on the progress of already disadvantaged pupils. Denied in-person attention as they grappled with remote learning, would they fall even further behind? The response from many teachers across the US was to turn to Quill, a non-profit organization dedicated to helping low-income students improve their writing skills, which in less than six weeks saw over a million new students sign up for its online service. With just 22 members of staff, including a six-person software engineering team, the sudden demand was a test of the organization's resilience, driving its total user population above three million. For us, that was a huge spike in new users.


How Can Machine Learning Help the Teaching Profession?

#artificialintelligence

The COVID-19 crisis has forced millions of teachers around the world to rapidly learn how to use technology to effectively support student learning and assessment, stay connected with their students, experiment with teaching models, and reduce the workload so they can focus on teaching. There are many promising solutions that are helping teachers become more effective, including new technologies such as machine learning (ML), artificial intelligence (AI) and optimised workflows. For example, Revisely is an education company that helps teachers give better feedback on students' writing assignments, such as essays and papers. It saves teachers time by offering built-in comment sets and doing a plagiarism check on student work, among other features. In addition, teachers can track the performance of students on all assignments throughout their learning journey.


How can Machine Learning help the Teaching Profession?

#artificialintelligence

The COVID-19 crisis has forced millions of teachers around the world to rapidly learn how to use technology to effectively support student learning and assessment, stay connected with their students, experiment with teaching models, and reduce the workload so they can focus on teaching. There are many promising solutions that are helping teachers become more effective, including new technologies such as machine learning (ML), artificial intelligence (AI) and optimised workflows. For example, Revisely is an education company that helps teachers give better feedback on students' writing assignments, such as essays and papers. It saves teachers time by offering built-in comment sets and doing a plagiarism check on student work, among other features. In addition, teachers can track the performance of students on all assignments throughout their learning journey.


ByteDance Launches New App for AI English Learning Aimed at Beginners

#artificialintelligence

ByteDdance's subsidiary Beijing Diandiankankan Technology announced yesterday to release a new AI English learning App named KaiYanJianDanXue(开言简单学, literally translated as Open Language Easy Learning), which is regarded as the beginner-friendly version of Open Language. According to the introduction of the product in the App Store, the functions of this new product mainly include providing scenario learning videos and online courses from North American teachers, improving pronunciation via AI technology, and offering learners individualized learning and reviewing plans. Zhang Yiming, the founder and CEO of ByteDance, regards that the combination with technology will be an inevitable trend in future education sector. From 2017 onwards, ByteDance started to launch educational products in succession such as Learning app Haohao Xuexi (means study well), online English learning platforms GoGoKid and aiKID, English learning app Tangyuan English, and AI English learning product for children from 2 to 8-year-old named GuaGuaLong.


Can AI Replace Teachers To Grade Student Essays? A Lesson From US Schools

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In countries like the US, artificial intelligence is already being used at a large scale to evaluate student essays, saving educational institutes money and time. According to reports, at least 21 states in America have deployed some type of automated scoring, from middle school to college level. Students are being graded on their essays using such AI systems designed by different vendors for highly important tests like the Graduate Record Examinations (GRE). While educators in the US say they are not going back to using human teachers for essay grading, it has received major backlash from parents particularly those from state school systems. But, it's not all great when it comes to automated grading.


From high school English teacher to Software Engineer at a Machine Learning company (Podcast)

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On today's episode of the podcast, I got to chat with software engineer Jackson Bates who lives and works in Melbourne, Australia. Jackson used to be a high school English teacher, but gradually taught himself to code and landed a pretty sweet gig as a React dev, partly by chance. Today he works part time as a developer, part time as a stay at home dad, and volunteers his time with various open source projects. Jackson grew up in England, and studied English in school. Although going into education seemed a logical choice, he dabbled in other fields - like working at a prison cafeteria - for a while before landing a teaching job.


Algorithms are grading student essays across the country. Can this really teach kids how to write better?

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Algorithms are grading student essays across the country. So can artificial intelligence really teach us to write better? Todd Feathers, who wrote about AI essay grading for Motherboard, called up every state in the country and found that at least 21 states use some form of automated scoring. "The algorithms are prone to a couple of flaws. One is that they can be fooled by any kind of nonsense gibberish sophisticated words. It looks good from afar but it doesn't actually mean anything. And the other problem is that some of the algorithms have been proven by the testing vendors themselves to be biased against people from certain language backgrounds."


Flawed Algorithms Are Grading Millions of Students' Essays

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Every year, millions of students sit down for standardized tests that carry weighty consequences. National tests like the Graduate Record Examinations (GRE) serve as gatekeepers to higher education, while state assessments can determine everything from whether a student will graduate to federal funding for schools and teacher pay. Traditional paper-and-pencil tests have given way to computerized versions. And increasingly, the grading process--even for written essays--has also been turned over to algorithms. Natural language processing (NLP) artificial intelligence systems--often called automated essay scoring engines--are now either the primary or secondary grader on standardized tests in at least 21 states, according to a survey conducted by Motherboard.


eRevise: Using Natural Language Processing to Provide Formative Feedback on Text Evidence Usage in Student Writing

arXiv.org Artificial Intelligence

Writing a good essay typically involves students revising an initial paper draft after receiving feedback. We present eRevise, a web-based writing and revising environment that uses natural language processing features generated for rubric-based essay scoring to trigger formative feedback messages regarding students' use of evidence in response-to-text writing. By helping students understand the criteria for using text evidence during writing, eRevise empowers students to better revise their paper drafts. In a pilot deployment of eRevise in 7 classrooms spanning grades 5 and 6, the quality of text evidence usage in writing improved after students received formative feedback then engaged in paper revision.