4. 1.1 推論 (inference) の定義
“information that is activated during reading yet not explicitly
stated in the text”
(van den Broek, 1994, p. 556)
“encoded (non explicit) features of the meaning of a text”
(McKoon & Ratcliff, 1989, p. 335)
“text base arguments and propositions that were not explicitly
mentioned in a message”
(Singer, 1994, p. 480)
推論とは，明示的には記述されていないが，テキストから暗示される
内容の理解。
5. 1.1 推論 (inference) の定義
“there has been little effort to unveil, on a scientific basis, either
the specific process involved in inferential generation among
L2 readers or the conditions affecting it”
(Koda, 2005, p. 152)
“we need heavy-duty inference about the place of inference in L2
text comprehension”
(Koda, 2005, p. 153)
L2読解における推論については，研究結果の蓄積が求められる。
6. 1.2 推論の例
The spy threw the report into the fire. The ashes floated up.
(Singer & Ferreira, 1983).
= The report was burned. (causal antecedent)
A burglar surveyed the garage set back from the street…The
criminal slipped away from the street lamp.
(McKoon & Ratcliff, 1980).
= The “criminal” refers to the “burglar”. (referential)
As the pitcher release the ball, the boy raised his bat and the ball
went directly towards him.
(Virtue et al., 2006).
= The boy will hit the ball. (predictive)
7. “Consequently, it is unclear whether the differences between the
studies are due to the type of inference, …or to the different
requirements of the tasks, or when the test was presented.”
(p. 378)
1.3 推論研究のメソドロジー
Keenan, J. M., Potts, G. R., Golding, J. M., & Jennings, T. M. (1990).
“Which elaborative inferences are drawn during reading? A
question of methodologies”
10. 文章を読解したあとに覚えている内容を書き出させ，推論情報の産出率を分
析する (Klin et al., 1999; Murray & Burke, 2003)。
2.1 筆記再生課題
As the pitcher released the ball, the boy raised his bat and the ball
went directly towards him.
ピッチャーはボールを投げ，それがまっすぐ来たところでバッターはボール
を打ち返した。
筆記再生課題 (written recall task)
○ 協力者のL2熟達度によらず，実施しやすい
△ 推論は読解しながら行われたものでなく，読解後の課題によって促された可能
性がある
△ エラー誘発の課題である
推論が生成されていれば，推論情報の誤産出率が増加する。
11. 2.1 筆記再生課題
筆記再生課題の例 (Nahatame, 2015, Experiment 1)
Mean Recall Rates (%) of Target Inferences in Experiment 1 (N = 29)
Strong constraint Weak constraint
M SD M SD
Motivational 22.41 21.49 3.45 8.77
Consequence 5.17 10.31 0.86 4.64
17. 3.2 語彙性判断課題
語彙性判断課題 (lexical decision task)
△ L2学習者を対象に行う場合は，協力者の熟達度や目標語の要因などを
慎重に検討する必要がある。
“a certain threshold level of L2 proficiency is needed for reliable automatic
priming effects to occur, as these effects rely on the participants’ ability to access
and process lexical representations in an automatic manner, with a reasonable
degree of accuracy.” (Elgort, 2011, p. 371).
目標語の長さ，頻度，親密度などがL2の語彙性判断の反応や時間に影響を
与える。 (de Groot, Borgwaldt, Bros & van den Eijnden, 2002; 横川, 2006)
18. 3.2 語彙性判断課題
語彙性判断課題 (lexical decision task)
In L2 reading research use of the lexical decision task can be problematic; its validity
and reliability is yet to be established. The task requires judgment on whether or not the
given letter string is a real L2 word (presumably involving graphophonemic and/or
graphomorphemic analysis). How adequately does it reflect the particular inference
(concept) in activation for limited FL students (esp. those from linguistically distant L1
background). Inference generation and encoding are conceptual processing which is L1
based for most FL students. Linguistic processing (letter strings, words, and parsing)
may be not automatic for these students. I think that the issue of (mental) translation
and connection between general knowledge and L1 versus L2 (e.g., Kroll & Stewart,
1994) should also be addressed. (from a reviewer)
△ L2学習者を対象に行う場合は，協力者の熟達度や目標語の要因などを
慎重に検討する必要がある。
19. 0
200
400
600
800
1000
1200
1400
1600
1800
2000
2200
Non-I Non-N Stra-I Stra-N
正反応時間(ms)
Higher
3.2 語彙性判断課題
語彙性判断課題の例 (Nahatame, 2015, Experiment 3)
Non-orienting reading Strategic orienting reading
Inference Neutral Inference Neutral
M SD M SD M SD M SD
Higher 873 253 892 272 935 288 1,050 345
Lower 874 205 875 172 910 240 917 241
目標語を高頻度語 (JACET, 2003)，高親密度語 (横川, 2006) に限定。
*
d = 0.51
*
Mean Correct Lexical Decision Times (ms) of Target Words in Experiment 3 (N = 37)
d = 0.36
0
200
400
600
800
1000
1200
1400
1600
1800
2000
2200
Non-I Non-N Stra-I Stra-N
正反応時間(ms)
Lower
20. 3.3 有意味性判断課題
有意味性判断課題 (meaningfulness judgment task)
推論を促す文脈の読解直後に推論を端的に表す1文が提示され (e.g, The
boy hits the ball)，それが意味を成す文であるかどうかを判断する課題 (井関，
2006)。正反応時間が主要な分析対象となる。
○ 推論情報の即自的な活性化を適切に反映するとされ，推論を命題単位で測
定できる。
△ L2学習者を対象に行う場合は，協力者の熟達度や目標文の要因などを慎
重に検討する必要がある。
推論の活性化により，反応時間が促進される (priming)。
21. 0
1000
2000
3000
4000
5000
6000
Predictive Disconfirming Neutral
正反応時間(ms)
Higher
3.3 有意味性判断課題
有意味性判断課題の例 (Nahatame, 2015, Experiment 5)
主要な単語を高頻度語 (JACET, 2003)，高親密度語 (横川, 2006) に限定。
Predictive Disconfirming Neutral
Proficiency M SD M SD M SD
Higher 1,793 390 1,915 530 2,121 530
Lower 2,223 476 2,325 807 2,688 906
d = 0.71
*
Mean Correct Response Times (ms) for the MJT in Experiment 5 (N = 36)
d = 0.39
*
0
1000
2000
3000
4000
5000
6000
Predictive Disconfirming Neutral
正反応時間(ms)
Lower
22. 3.4 視線計測
視線計測 (eye-tracking)
推論を促す文脈の直後に推論を肯定・否定する情報を読解させ (e.g.,
Suddenly, the ball dropped in front of the bat and fell into the catcher’s
mitt.)，その情報の注視時間や注視割合を分析する (Calvo et al., 2001)。
推論内容と実際のテキスト内容の一致・不一致により，特定の情報の注
視時間や割合が増減する。
○ 読解中のプロセスを，自然な条件下で検証できる。
○ 読解の初期処理や後期処理の区別が可能である。
△ 推論の検証が間接的である。
24. 0
200
400
600
800
1000
1200
1400
1600
1800
2000
Inference Control
注視時間(ms)
Lower
3.4 視線計測
視線計測の例 (Nahatame, 2015, Experiment 6)
Suddenly, the ball dropped in front of the bat and fell into the catcher’s mitt.
Wrap-Up Times (ms) of Target Sentences (N = 18)
Inference Control
Proficiency M SD M SD
Higher 712 189 724 295
Lower 1,317 367 929 290
*
d = 1.17
0
200
400
600
800
1000
1200
1400
1600
1800
2000
Inferece Control
注視時間(ms)
Higher
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