# data[].attributes.headline
이 템플릿 이용해주세요

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이 템플릿 이용해주세요

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https://docs.google.com/spreadsheets/d/1mdx9iJfPfiMW6E-EjleMMnF5hOczMN0WdEMdqKLwHB0/copy?usp=sharing

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피드백 자동화가 가능합니다.

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피드백 자동화가 가능합니다.

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https://docs.google.com/spreadsheets/d/1aIoqh7DGLbIAqGskfAlBYdsUpUod05rfCmfLyYm2IUw/edit?usp=sharing

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https://youtu.be/lYZgJsURrHw

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선생님이면 6만원 무제한 전자책 혜택 누리세요!!!

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2. 이 원서를 주교재로 사용하였습니

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2. 이 원서를 주교재로 사용하였습니다.

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교재1.
이 도서는 원서 Everybody Lies 에서 도출할 수 있는 Discussion Questions 들입니다. 이 내용들을 토대로 학생들이 유의미한 질문을 구성할 수 있도록 하였습니다.

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참고자료 1.이 원서의

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참고자료 1.

이 원서의 내용으로 수업을 재구성했습니다.

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https://convertio.co/kr/epub-pdf/

epub 파일의 경우 pdf로 변환을 시켜줍니다. 매우 유용하게 활용하실 수 있씁니다.

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전자 출판

국제 디지털 출판 포럼에서 개발 한 형식입니다. 그것은 XML- 및 CSS 스타일의 XHTM 기반의 선택적 사용을 특징으로한다. 이 형식의 기본 특징은 가능한 다른 기기 디스플레이에 이미지를 적용 할 수있다 재 배열 텍스트 (바꿈)의 사용이다. ePub 파일은의 .epub 확장자를 가진 압축 아카이브입니다.

PDF 형식

PDF는 어떤 언어를 사용하여 어도비 시스템즈에 의해 설계 전자 문서 형식입니다 포스트 스크립트가 있습니다. 이 형식은 Adob​​e Reader에서 문서를보기위한 공식 프로그램입니다. 대부분의 경우, PDF 파일은 래스터 및 벡터 그래픽과 텍스트 형태, 자바 스크립트와 다른 종류의 항목에서 작성된 스크립트 텍스트의 조합입니다.

epub 파일(들) 업로드

컴퓨터, Google Drive, Dropbox, URL에서 선택하거나 이 페이지에서 드래그하여 선택해 주세요.

pdf로 선택

pdf 또는 기타 필요한 결과 형식을 선택하세요(200가지 이상의 형식 지원)

내 pdf 다운로드

파일 변환을 실행한 뒤 바로 pdf 파일을 다운로드할 수 있습니다

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몇 초 만에 EPUB 파일은 PDF 파일로 변환하세요. 100% 무료, 쉽고 안전하게 사용하세요! Convertio — 어떤 파일에 문제가 생기더라도 해결가능한 고급 온라인 툴.

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https://www.pdfdrive.com/

위 사이트가 차단될 경우, 이 사이트를 사용하면 됩니다. 차단된적은 없습니다.

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교육청에서 차단했으나, 아래의사이트는 정상 작동합니다. 즐겨찾기 강추합니다. 찾는데 힘들었습니다.ㅠㅠ

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교육청에서 차단했으나, 아래의사이트는 정상 작동합니다. 즐겨찾기 강추합니다. 찾는데 힘들었습니다.ㅠㅠ

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https://libgen.st/

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Library Genesis is a scientific community targeting collection of books on natural science disciplines and engineering.

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새로운 결론을 요구하는 텍스트

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새로운 결론을 요구하는 텍스트

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https://medium.com/marketing-in-the-age-of-digital/what-are-the-limitations-of-big-data-for-marketers-5b0eae79c234

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Based on my research, there are a variety of limitations to "Big Data" for marketers. According to , Big Data analytics is "the process of drawing from large sets of data." This set of data being referred to is a ginormous sea of data that needs to be sifted through and sorted constantly. There are many revelations that can come from that huge data pile, or the data may mean nothing at all to a marketer. It all depends on the depth of your analysis and on what you're looking for in your research. Some of the many limitations are as follows....

1. Finding Meaningful Correlations in Data
The pool of data that you work with as a marketer is so large, it is sometimes difficult to sift through. There can be many correlations you may make between different variables in your data. However, making these correlations, doesn't always mean anything significant. It is possible that the relationships between variables are insignificant. This process can be a waste of time and effort, or can be very worthy. The important part of this process is figuring out where in your correlations there is actually causation and where there isn't.

2. Figuring out Which Questions to be Asking
The data you're working with can lead to a slew of assumptions and "answers," but it is imperative to make sure you're asking the right questions and answering them with your findings. Even though you might be finding "answers," you need to make sure they answer questions consistent with your business goal. You might discover important data, but it may not be helpful in answering the question you're looking for that will help you achieve your goals.

3. Security of Data
"Big data analytics is prone to data breach" ( Ciklum). Information and inferences you come up with and pass along to others could easily get leaked to customers and competitors. This creates additional limitations because data needs to have additional layers of security, which leads to the next point of transferability of data.

4. Transferability of Data
Usually only people with specialized skills and knowledge can efficiently reach Big Data and use it, because it needs to be secured with firewalls or private clouds. Therefore, it may be difficult to transfer and use data between multiple teams and consistently keep up with analysis. For example, if you're working on a huge initiative that involves a lot of time allotment and you find a huge discovery, it might be difficult to track data that confirms your discovery. There is such a tremendous amount of data and it may be difficult to get to it, so consistent research endeavors are often a difficult task.

5. Discrepancies in Data Collection
Tools used to collect big data might not be 100% effective. There is so much data and so many different ways to collect it, collection could get complicated. In addition, many data collection programs used in present day tend to change the results of their searches day to day, which can skew results and ultimately even change them. Therefore, correlations and analysis of data could change frequently due to changing data patterns.
https://www.ciklum.com/blog/limitations-of-big-data-analytics/
https://www.forbes.com/sites/gregsatell/2013/03/06/the-limits-of-big-data-marketing/?sh=23d513bc6c71
https://marketingland.com/7-limitations-big-data-marketing-analytics-117998
A Final Limitation in the Data
In addition to these limitations in the physical data itself, there are also limitations to the use of computers and machines to analyze the data. The reality is that computers are becoming increasingly capable of performing human-like activities and analysis. However, no matter how advanced computers get, they'll never actually be humans. Their insights will likely never be able to incorporate experience into their assumptions. Marketers need experiences of life like "strik[ing] our in little league, hav[ing] their heart broken, see[ing] their children born or know[ing] many of the joys and sorrow that make life worth living" to find a passion point and create a phenomenal campaign ( Forbes). Marketers need to be a part of the process to connect to people and continue to reach them in a meaningful way.

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What Are the Limitations of Big Data for Marketers?

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Based on my research, there are a variety of limitations to "Big Data" for marketers. According to Ciklum.com, Big Data analytics is "the process of drawing from large sets of data." This set of data...

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https://scienceon.kisti.re.kr/aiq/mlsh3/selectAIQMlshList.do

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연구주제, 연구방법, 연구결과에 대한 상세 분류 문장 의미 태그를 기반으로 요약 서비스를 제공

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https://beta.albus.org/

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Albus, AI App, explore any topic - powered by ChatGPT

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Albus, AI App, explore any topic - powered by ChatGPT

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Albus is an AI app that explores any topic you like from different perspectives. Think of it as Google meets Pinterest. Enjoy the early beta. Welcome and have fun.

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https://www.pewresearch.org/short-reads/2021/03/17/cable-and-satellite-tv-use-has-dropped-dramatically-in-the-u-s-since-2015/

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Cable and satellite TV use has dropped dramatically in the U.S. since 2015

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The share of Americans who say they watch television via cable or satellite has plunged from 76% in 2015 to 56% this year.

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https://docs.google.com/spreadsheets/d/1f1fEa5xntsbvmk8KqVk3C-rC9nphGtE5pn6DXb_x9MM/edit?usp=sharing

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빅데이터 분석 주제잡기-홀수반-2차검토

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https://voyant-tools.org/?corpus=a9d882b6afc75fe3f98554a2e573e4dc

What is most interesting is the contrast between Romeo’s word corpus before and after the marriage. It almost foreshadows the events to come without even reading the text. Before Romeo is married to Juliet, the word “love” is mentioned the most (Voyant Tools: Reveal Your Texts). After he is married, however, “death” is mentioned eighteen times, making it the number one word used. In context, “death” is used to describe how it would be better than being separated from his Juliet, revealing how both he and Juliet are dramatic and impulsive in their adolescence. Juliet is the second most mentioned word at twelve times depicting how he may be more devoted to her, rather than only searching for someone to love. Similar to Juliet’s topic flower, Romeo’s topic flower after marriage becomes more complex involving more layers and more red petals, portraying art. What is interesting is that Romeo and Juliet’s topic flowers after marriage resemble each other significantly. Not only is Juliet heavily influenced by Romeo, but Romeo seems to have changed in personality as well after the two are married. Although, after comparing both Romeo and Juliet’s text in a Wordle cloud, besides “love” and “death,” “Romeo” stands out the most as Juliet mentions his name more than Romeo mentions Juliet.

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그래프/표/차트 표현하는 영어 모방하기

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그래프/표/차트 표현하는 영어 모방하기

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https://www.pewresearch.org/short-reads/2021/03/17/cable-and-satellite-tv-use-has-dropped-dramatically-in-the-u-s-since-2015/

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Cable and satellite TV use has dropped dramatically in the U.S. since 2015

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The share of Americans who say they watch television via cable or satellite has plunged from 76% in 2015 to 56% this year.

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https://search.naver.com/search.naver?where=news&query=%EB%84%B7%ED%94%8C%EB%A6%AD%EC%8A%A4%20cgv&sm=tab_opt&sort=0&photo=0&field=0&pd=3&ds=2020.03.07&de=2020.03.25&docid=&related=0&mynews=0&office_type=0&office_section_code=0&news_office_checked=&nso=so%3Ar%2Cp%3Afrom20200307to20200325&is_sug_officeid=0

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넷플릭스 cgv : 네이버 뉴스검색

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‘넷플릭스 cgv’의 네이버 뉴스검색 결과입니다.

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네이버 데이터랩으로 (넷플릭스, cgv 비교)

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네이버 데이터랩으로 (넷플릭스, cgv 비교)

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https://datalab.naver.com/keyword/trendResult.naver?hashKey=N_ab9290361b5527a1a4bb0a43fa542546

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네이버 데이터랩 : 검색어트렌드

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네이버 통합검색에서 검색된 검색어와 검색횟수를 기간별/연령별/성별로 조회할 수 있습니다.

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구글 트렌드로 키워드의 분포/지역별특성 분석하기_넥플릭스와 cgv 비교

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구글 트렌드로 키워드의 분포/지역별특성 분석하기_넥플릭스와 cgv 비교

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https://trends.google.com/trends/explore?date=all&geo=KR&q=%EB%84%B7%ED%94%8C%EB%A6%AD%EC%8A%A4,cgv&hl=ko

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https://www.majormap.net/

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학과, 대학, 직업 정보 가 궁금할 땐

463,556명이 전공을 추천받았습니다!

나와 찰떡궁합인 학과가 궁금하다면?
내 관심사에 걸맞는 학과를 찾아보세요.

학과추천 받기

관심 교과와 키워드만 선택하세요.
관심사와 관련도 높은 학과를 추천해 드려요.
추천학과 및 각 학과별 연관학과까지 탐색하며
목표를 설정해 보세요!

학과추천 받아보기

학과 커리큘럼을 분석한
워드 클라우드로 학과 특성을 알려드려요.
흥미있는 키워드를 클릭하면
관련학과도 살펴볼 수 있어요!

학과 커리큘럼이 반영된
선택교과를 추천해 드려요.
고교학점제도 메이저맵과 준비하세요!

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메이저맵 - 성공적인 진학을 위한 학교, 학과, 직업정보 서비스

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메이저맵 - 성공적인 진학을 위한 학교, 학과, 직업정보 서비스

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미디어에 관심있는 ㄴ학생은 Netflix, Moive 를 비교할 수 있어요

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미디어에 관심있는 ㄴ학생은 Netflix, Moive 를 비교할 수 있어요

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https://books.google.com/ngrams/graph?content=Netflix%2CMovie&year_start=1800&year_end=2019&corpus=en-2019&smoothing=0

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내가 생각하는 키워드의 분포 찾아보기

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내가 생각하는 키워드의 분포 찾아보기

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https://books.google.com/ngrams/

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https://typeset.io/

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Chat with PDF and conduct your literature review faster using SciSpace. Discover 200M+ papers or upload your own PDF, highlight text or ask questions, and extract explanations and summaries.

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챗GPT 활용 개별화 학습자료 제공

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챗GPT 활용 개별화 학습자료 제공

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https://docs.google.com/spreadsheets/d/1D9WJ2xOkSyqrQgAWPe0ULzV7w8eVNSBsMc2FOB-Ia7M/edit#gid=284901175

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Create a new spreadsheet and edit with others at the same time -- from your computer, phone or tablet. Get stuff done with or without an internet connection. Use Sheets to edit Excel files. Free from Google.

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https://www.classcard.net/set/12945874

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85 Cards | application : [명] 적용, 지원, precisely : [부] 정확히, frequency : [명] 빈도, 빈번, 주파수, equation : [명] 방정식, reminder : [명] 상기시키는 것, bizarre : [형] 특이한, axis : [명] 축, 중심선, applause : [명] 박수갈채, span : [명] 기간, 범위, mighty : [형] 강력한, 장대한, bypass : [명] 우회로, censor : [명] 검열관, fewer : [형] 보다 적은, planning : [명…

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밑줄친 부분의 의미를 자신의 언어로 말하기(녹음과제)

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밑줄친 부분의 의미를 자신의 언어로 말하기(녹음과제)

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https://a.ttd.ac/OLVNOD

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하이라이트로 표기된 부분의 저자의 의도를 2분이내로 자신의 언어로 설명하세요

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테드강의 듣고 딕테이션 하기

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테드강의 듣고 딕테이션 하기

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https://a.ttd.ac/NYZMOE

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테드 강연듣고 빈칸 채워 넣기

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학생들 지식영역 형성평가(어휘,문법,듣기,말하기,순서배열)

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학생들 지식영역 형성평가(어휘,문법,듣기,말하기,순서배열)

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https://l.ttd.ac/QWXME

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TED 강의에 대한 대본입니다.

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TED 강의에 대한 대본입니다.

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https://docs.google.com/document/d/1-gpBTtNUzKbQb4xxBhFwkPAEuFLKkXHkj9fipFpo4Ak/edit?usp=sharing

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Erez Lieberman Aiden: Everyone knows that a picture is worth a thousand words

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TED 강의입니다. 학생들은 이 부분을 미리 학습해와서, 빅데이터 분석에 대한 아이디어를 얻습니다.

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TED 강의입니다. 학생들은 이 부분을 미리 학습해와서, 빅데이터 분석에 대한 아이디어를 얻습니다.

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https://www.ted.com/talks/jean_baptiste_michel_erez_lieberman_aiden_what_we_learned_from_5_million_books

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한림대학교의 디지털인문학 결과물 전시회입니다. 프로젝트수업에 대한 아이디어를 얻을 수 있어요. 

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한림대학교의 디지털인문학 결과물 전시회입니다. 프로젝트수업에 대한 아이디어를 얻을 수 있어요. 

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https://sites.google.com/view/dah-hallym

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한림대학교 디지털인문예술

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Mission 세상을 통찰하는 인문사회적 소양과 세련되고 창의적인 디지털 역량으로 더 나은 미래를 디자인한다. To design a better future with humanistic insights and creative digital competency.

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하버드 대학교 디지털 인문학 강좌로 디지털 인문학을 이해하는데 큰 도움이 됩니다.

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하버드 대학교 디지털 인문학 강좌로 디지털 인문학을 이해하는데 큰 도움이 됩니다.

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https://www.edx.org/course/introduction-to-digital-humanities

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As primary sources of information are more frequently digitized and available online than ever before, how can we use those sources to ask new questions? How did Chinese families organize themselves and their landscapes in China's past? How did African slaves from different cultures form communities in the Americas? What influences informed the creation and evolution of Broadway musicals? How can I understand or interpret 1,000 books all at once? How can I create a visualization that my students can interact with? The answers to these questions can be explored using a wide variety of digital tools, methods, and sources.

As museums, libraries, archives and other institutions have digitized collections and artifacts, new tools and standards have been developed that turn those materials into machine-readable data. Optical Character Recognition (OCR) and the Text Encoding Initiative (TEI), for example, have enabled humanities researchers to processvastamounts of textual data. However, these advances are not limited just to text. Sound, images, and video have all been subject to these new forms of research.

This course will show you how to manage the many aspects of digital humanities research and scholarship. Whether you are a student or scholar, librarian or archivist, museum curator or public historian - or just plain curious - this course will help you bring your area of study or interest to new life using digital tools.

More about this course

What the term "digital humanities" means in different disciplines.

How common digital tools work and examples of projects using them.

How various file types can be used to create, gather, and organize data.

How to use command-line functions to analyze text.

How to use free tools to create visual text analysis.

Expand what you'll learn

Lesson 1: Digital Humanities and Data

Explain the term "digital humanities," and how it is understood across humanities disciplines.

Describe the research journey as a partnership between researcher and library collections and staff.

List examples of the limits of classification.

Describe the implicit and explicit hierarchies that are created when gathering and analyzing data.

Distinguish between what counts as data and what does not.

Identify different data formats and how they fit into a research workflow.

Lesson 2: Digital Humanities Projects and Tools

List tools of data analysis that can be applied to text in any language, space, networks, images, and statistical analysis.

Evaluate existing digital platforms based on features that can be used for data analysis within different fields such as literature, history, art, and music.

Lesson 3: Acquiring, Cleaning, and Creating Data

Identify the differences between unstructured, semi-structured, and structured data.

Distinguish between different file types, their definitions, and applications.

Apply intellectual property rights to the downloading and sharing of data.

Practice different ways of downloading or creating data.

Lesson 4: The Command Line

Understand how command line functions work.

Apply command line functions to text files.

Create smaller text files from larger files using command line prompts.

Lesson 5: Working with Tools - Voyant

Create data from multiple text files using Voyant.

Compare data results across text files using visualizationin Voyant.

Expand syllabus

Pursue a Verified Certificate to highlight the knowledge and skills you gain

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As primary sources of information are more frequently digitized and available online than ever before, how can we use those sources to ask new questions? How did Chinese families organize themselves and their landscapes in China's past? How did African slaves from different cultures form communities in the Americas?

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PBL 에 대한 생각 공유해보기