IB 1A5 (=E1R86), 1L1 (=E1R05) , IIB E2R40 , 2011 L7 URL - - PowerPoint PPT Presentation

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IB 1A5 (=E1R86), 1L1 (=E1R05) , IIB E2R40 , 2011 L7 URL - - PowerPoint PPT Presentation

IB 1A5 (=E1R86), 1L1 (=E1R05) , IIB E2R40 , 2011 L7 URL : http://clsl.hi.h.kyoto-u.ac.jp/~kkuroda/lectures/11B-KU/KU-2011B-L07-slides.pdf ( ) substituting for


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SLIDE 1

2011-12-08 (木)

英語 IB 1A5 (=E1R86), 1L1 (=E1R05), 英語 IIB E2R40, 2011 L7

このスライドは次のURLから入手できます:

http://clsl.hi.h.kyoto-u.ac.jp/~kkuroda/lectures/11B-KU/KU-2011B-L07-slides.pdf

黒田 航 (非常勤) substituting for 出口雅也 (非常勤)

Thursday, December 8, 2011

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SLIDE 2

連絡 1/2

✤ 2011年11月24日(木)の講義を12月27日(火)に振替え ✤ 2012年1月12日(木)は休講

✤ 2012月1月9日(月)から13日(金)まで松江で開催される Global

WordNet Associationに参加

✤ 2012年2月2日が最終日=ボーナス試験 (L=13に相当)

✤ 出席する時間帯は自主的に変更してよいです

✤ 1,2時限目: 西棟共同12 ✤ 3時限目: 西棟共同03

Thursday, December 8, 2011

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SLIDE 3

連絡 2/2

✤ Fast Readingのため

✤ 12月8日,15日,22日,27日は ✤ 共同東棟 22教室 ✤ その後の2回は元の教室に戻る

✤ 教室変更なし ✤ 2Rのみ

✤ 1月19,26日は The Feynman Lectures on Physicsの聴き取り

Thursday, December 8, 2011

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SLIDE 4

講義資料

✤ 聴き取り用の教材は次の Web ページから入手可能

✤ http://clsl.hi.h.kyoto-u.ac.jp/~kkuroda/lectures/KU-11B.html

✤ 授業時間外での予習や復習に利用して下さい

✤ 特にボーナス試験対策には有効でしょう

✤ 速読に関して完全に同じことはできませんが,工夫

します

Thursday, December 8, 2011

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SLIDE 5

本日の予定

✤ 前半60分

✤ L6の結果の報告と正解の解説

✤ 後半30分

✤ QuickReaderを使った速読訓練 ✤ A Study in Scarlet by Arthur Conan Doyle の Chapter 1

Thursday, December 8, 2011

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SLIDE 6

速読訓練の設計思想

✤ 強制的に “読み流し” を実現

✤ 仮説: “読み流し” も “聞き流し” 同様に 外国語習得に有効なのでは?

✤ 話しコトバは “聞き流し” が可能

✤ 誰でも最初は聞き流すしかない ✤ 聞き流しが外国語習得に有効であることは実証済み

✤ 書きコトバは “読み流し” 不可能

✤ 読みは誰もが自分独自のテンポで行なうので,読み流しができない Thursday, December 8, 2011

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SLIDE 7

Date

L6の聴き取り課題の結果

Thursday, December 8, 2011

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SLIDE 8

採点法

✤ 点数

✤ 完全正解 1.0 (◯で表示) ✤ 不完全解 0.5 (△で表示)

✤ 評価基準

✤ 素得点 S = ◯の数 + (△の数)/2 ✤ 正答率 P = ◯の数/S ✤ 成績評価用の得点: S* = 100 × S/問題の総数 (e.g., 30)

✤ 採点誤りがあるかも知れません

✤ たし算を時々間違うので,該当者は報告して下さい

Thursday, December 8, 2011

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SLIDE 9

出題への評価

Q1: Quant 1: Quantity uantity Q2: Diffic 2: Difficulty ulty Av. Stdev Max Min Av. Stdev Max Min 1A5 3.17 0.38 4 3 2.39 0.50 3 2 2R 3.11 0.51 4 2 2.52 0.58 3 1 1L1 3.15 0.36 4 3 2.50 0.53 3 1.5

調査の回答は表に書いて下さい

Thursday, December 8, 2011

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SLIDE 10

平均得点の変遷

Thursday, December 8, 2011

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SLIDE 11

L6の得点分布 1A5, 2R, 1L1

✤ 参加者: 85人

✤ 平均: 67.15

✤ 標準偏差: 8.59

✤ 最高: 88.00; 最低: 46.00

✤ 得点グループ数=1

Thursday, December 8, 2011

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SLIDE 12

L6の得点分布 1A5

✤ 受講者数: 23人

✤ 平均: 67.22 [16.80/n] 点

✤ 標準偏差: 10.51 [ 2.63] 点

✤ 最高: 88.00 [22.00/n] 点 ✤ 最低: 48.00 [12.00/n] 点

✤ n = 25

✤ 得点グループ数=4?

Thursday, December 8, 2011

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SLIDE 13

L6の得点分布 2R

✤ 受講者数: 28人

✤ 平均: 63.57 [15.89/n] 点

✤ 標準偏差: 7.29 [ 1.82] 点

✤ 最高: 88.00 [22.00/n] 点 ✤ 最低: 46.00 [11.50/n] 点

✤ n = 25

✤ 得点グループ数=2?

Thursday, December 8, 2011

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SLIDE 14

L6の得点分布 1L1

✤ 受講者数: 34人

✤ 平均: 70.06 [17.51/n] 点

✤ 標準偏差: 7.16 [ 1.79] 点

✤ 最高: 82.00 [20.50/n] 点 ✤ 最低: 50.00 [12.50/n] 点

✤ n = 25

✤ 得点グループ数=1?

Thursday, December 8, 2011

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SLIDE 15

平均正答率の変遷

Thursday, December 8, 2011

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SLIDE 16

L6の正解率分布 1A5, 2R, 1L1

✤ 参加者: 85人

✤ 平均値: 0.59

✤ 標準偏差: 0.12

✤ 最高値: 0.86; 最低値: 0.24

✤ 正答率のグループ数=2

Thursday, December 8, 2011

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SLIDE 17

L6の正答率分布 1A5

✤ 参加者: 23人

✤ 平均: 0.60; 標準偏差: 0.14 ✤ 最高: 0.86; 最低: 0.24

✤ 正答率のグループ数=4?

Thursday, December 8, 2011

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SLIDE 18

L6の正答率分布 2R

✤ 参加者: 28人

✤ 平均: 0.54; 標準偏差: 0.12 ✤ 最高: 0.86; 最低: 0.26

✤ 正答率のグループ数=5?

Thursday, December 8, 2011

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SLIDE 19

L6の正答率分布 1L1

✤ 参加者: 34人

✤ 平均: 0.63; 標準偏差: 0.10 ✤ 最高: 0.83; 最低: 0.47

✤ 正答率のグループ数=2?

Thursday, December 8, 2011

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SLIDE 20

L6の正解

Thursday, December 8, 2011

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SLIDE 21

TED講演を暗記する

✤ 質問

✤ “講演を暗記するといいよ”と言われても,どうやればいいの?

✤ 答え

✤ 何度も聴いていると,講演の断片を聞いて,どこの部分かピンと

来るようになれば,それで十分

✤ 朗読できるようにならんでもええのです

✤ 要点

✤ 話の内容が(だいたい)わかったと思っても,聴くのを止めないこと Thursday, December 8, 2011

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SLIDE 22

誤りの傾向

✤ 1. placed it ⇒ placed, cased

(it), tasted, tested

✤ 2. dyslexia ⇒ disselective,

disrect, discrets, dislecsys

✤ 3. retards ⇒ returns, reters,

retours, litters, retires

✤ 4. perplexed me ⇒

{complexed, compressed} me, fleximy

✤ 5. brain ✤ 6. diagnose ⇒ diagnosis ✤ 7. misleading ⇒

missleading, misreading

✤ 8. disorders ⇒ disorder,

sorted, sold

✤ 9. applied it ⇒ applied,

apried, opried, apprize, upright, upride

✤ 10. abnormality ✤ 11. calculations ⇒

culcularation(s), calicuration (s), caliculation(s)

✤ 12. clinical ⇒ crinical,

creature

✤ 13. India ⇒ (this) year, hear,

anywhere, dear, NULL

✤ 14. autism ⇒ ortism, outism,

autisttism, altism

✤ 15. ground(-)breaking ⇒

round, grand-{braking, breaking}, grand-taking

✤ 16. mimicked ⇒ mimiced,

limicked, limited

✤ 17. enrolled into ⇒ enrol

(into), inroad, load,

✤ 18. seizures ⇒ seasures ✤ 19. attention deficit ⇒

attention, attentional

✤ 20. behavioral ⇒ behavial,

behavior, behavier

✤ 21. treatment ✤ 22. suffered ⇒ sufferd ✤ 23. disabilities ⇒ disability,

disactivities

✤ 24. puzzle ⇒ pazzle, pazle,

puzzul, pazule, puzzel

✤ 25. brains, brain(-)waves ⇒

brain{face, ness, raise, base, ways, makes, lace, mize, made, less, base}

Thursday, December 8, 2011

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SLIDE 23

01/12

✤ When I was 10 years old, um, a cousin of mine took me

  • n a tour of his medical school. And as a special treat he

took me to the pathology lab and took a real human brain out of the jar and [1. placed it] in my hands.

✤ And there it was, the seat of human consciousness, the

powerhouse of the human body, sitting in my hands. And that day I knew that when I grew up, I was going to become a brain doctor, scientist, something or the other.

Thursday, December 8, 2011

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SLIDE 24

02/12

✤ Years later, when I finally grew up, my dream came true.

And it was while I was doing my Ph.D. on the neurological causes of [2. dyslexia] in children that I encountered a startling fact that I’d like to share with you all today.

✤ It is estimated that one in six children— that’s one in six

children, suffer from some developmental disorder. This is a disorder that [3. retards] mental development in the child and causes permanent mental impairments, which means that each and every one of you here today knows at least

  • ne child that is suffering from a developmental disorder.

Thursday, December 8, 2011

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SLIDE 25

03/12

✤ But here’s what really [4. perplexed me]. Despite the fact

that each and every one these disorders originates in the brain, most of these disorders are diagnosed solely on the basis of observable behavior.

✤ But diagnosing a [5. brain] disorder without actually

looking at the brain is analogous to treating a patient with a heart problem based on their physical symptoms, without even doing an ECG [electrocardiogram] or a chest X-ray to look at the heart.

Thursday, December 8, 2011

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SLIDE 26

04/12

✤ It seemed so intuitive to me. To [6. diagnose] and treat a

brain disorder accurately, it would be necessary to look at the brain directly. Looking at behavior alone can miss a vital piece of the puzzle and provide an incomplete, or even a [7. misleading], picture of the child’s problems. Yet, despite all the advances in medical technology, the diagnosis of brain [8. disorders] in one in six children still remained so limited.

Thursday, December 8, 2011

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SLIDE 27

05/12

✤ And then I came across a team at Harvard University that

had taken one such advanced medical technology and finally [9. applied it], instead of in brain research, towards diagnosing brain disorders in children. Their groundbreaking technology records the EEG [electroencephalogram] or the electrical activity of the brain in real time, allowing us to watch the brain as it performs various functions and then detect even the slightest [10. abnormality] in any of these functions, vision, attention, language, audition. A program called Brain Electrical Activity Mapping then triangulates the source of that abnormality in the brain.

Thursday, December 8, 2011

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SLIDE 28

06/12

✤ And another program called Statistical Probability Mapping

then performs mathematical [12. calculations] to determine whether any of these abnormalities are clinically significant, allowing us to provide a much more accurate neurological diagnosis of the child’s symptoms. And so I became the head of neurophysiology for the [13. clinical] arm of this team. And we’re finally able to use this technology towards actually helping children with brain disorders. And I’m happy say that I’m now in the process of setting up this technology here in [14. India].

Thursday, December 8, 2011

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SLIDE 29

07/12

✤ I’d like to tell you about one such child, whose story was

also covered by ABC News. Seven year-old Justin Senigar came to our clinic with this diagnosis of very severe [14. autism]. Like many autistic children his mind was locked inside his body. There were moments when he would actually space out for seconds at a time. And the doctors told his parents he was never going to be able to communicate or interact socially, and he would probably never have too much language.

Thursday, December 8, 2011

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SLIDE 30

08/12

✤ When we used this [15. groundbreaking] EEG

technology to actually look at Justin’s brain, the results were startling. It turned out that Justin was almost certainly not autistic. He was suffering from brain seizures that were impossible to see with the naked eye, but that were actually causing symptoms that [16. mimicked] those of autism.

Thursday, December 8, 2011

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09/12

✤ After Justin was given anti-seizure medication, the change

in him was amazing. Within a period of 60 days, his vocabulary went from two to three words to 300 words. And his communication and social interaction were improved so dramatically, that he was [17. enrolled into] a regular school and even became a karate superchamp.

✤ Research shows that 50 percent of children, almost 50

percent of children diagnosed with autism are actually suffering from hidden brain [18. seizures].

Thursday, December 8, 2011

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SLIDE 32

10/12

✤ These are the faces of the children that I have tested with

stories just like Justin. All these children came to our clinic with a diagnosis of autism, [19. attention deficit] disorder, mental retardation, language problems. Instead, our EEG scans revealed very specific problems hidden within their brains that couldn’t possibly have been detected by their [20. behavioral] assessments.

✤ So these EEG scans enabled us to provide these children

with a much more accurate neurological diagnosis and much more targeted [21. treatment].

Thursday, December 8, 2011

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SLIDE 33

11/12

✤ For too long now, children with developmental disorders

have suffered from misdiagnosis while their real problems have gone undetected and left to worsen. And for too long, these children and their parents have [22. suffered] undue frustration and desperation.

✤ But we are now in a new era of neuroscience, one in which

we can finally look directly at brain function in real time with no risks and no side effects, non-invasively, and find the true source of so many [23. disabilities] in children.

Thursday, December 8, 2011

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SLIDE 34

12/12

✤ So if I could inspire even a fraction of you in the audience

today to share this pioneering diagnostic approach with even

  • ne parent whose child is suffering from a developmental

disorder, then perhaps one more [24. puzzle] in one more brain will be solved. One more mind will be unlocked. And

  • ne more child who has been misdiagnosed or even

undiagnosed by the system will finally realize his or her true potential while there’s still time for his or her brain to recover. And all this by simply watching the child’s [25. brainwaves].

✤ Thank you. (Applause)

Thursday, December 8, 2011

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SLIDE 35

Date

QuickReaderを使った速読訓練

Thursday, December 8, 2011

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SLIDE 36

教材

✤ 作品 ✤ A Study in Scarlet

✤ Sherlock Holmes 連作の第一作

✤ 作者

✤ Arthur Conan Doyle

✤ 19世紀イギリスの作家) Thursday, December 8, 2011

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SLIDE 37

Readibility Ratings

http://www.addedbytes.com/lab/readability-score/

Agatha Christie Arthur Conan Doyle Lafcadio Hearn John Dewey Charles Darwin Adam Smith Nicolo Machiave lli Charles Babbage Flesch- Kincaid 5.10 8.30 9.50 11.60 13.00 17.10 18.10 18.60 Gunning- Fog Score 7.60 10.80 12.20 15.00 16.90 20.60 20.90 22.80 Coleman- Liau 9.80 8.70 9.10 12.90 11.50 11.60 10.30 13.90 SMOG 6.10 7.90 7.80 11.00 12.00 13.30 11.90 15.80 Automated Readability 3.80 7.50 10.30 12.70 13.70 19.00 21.30 20.60 Average 6.48 8.64 9.78 12.64 13.42 16.32 16.50 18.34

Thursday, December 8, 2011

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SLIDE 38

課題 1/2

✤ 単語再認課題 (Word Recognition Task)

✤ 読んだ文章に現われた単語と現われなかった単語を識別

✤ 注意

✤ 速読訓練は始めての試み ✤ 速読訓練の効果測定に有効な課題は知られていません

✤ 私も試行錯誤です

✤ 課題の設計はやり直すかも知れません

Thursday, December 8, 2011

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SLIDE 39

課題 2/2

✤ 読んだ文章に

✤ 現われた単語に [ ○ ] ✤ 現われていない単語に [ × ]

✤ をつける ✤ 確信がもてないのは自然

✤ 潜在記憶/プライミング効果のおかげで,単語認識ができていれば,不

思議と当る

✤ 予告

✤ 次回以降は,後半60分が速読 [2 x 30minの課題 ]

Thursday, December 8, 2011

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SLIDE 40

Thursday, December 8, 2011