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Unconscious Attitudes toward L2 Speakers



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Breaking Theory: New Directions
in Applied Linguistics
Proceedings of the 48th Annual Meeting
of the
British Association for Applied Linguistics
3-5 September 2015
Aston University, Birmingham
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Unconscious Attitudes toward L2 Speakers
Ali H. Al-Hoorie
Unconscious Attitudes toward L2
Ali H. Al-Hoorie
Nottingham University, UK
The English Language Institute, Jubail Industrial
College, Saudi Arabia
The most common instrument used in attitude and motivation studies is the
questionnaire. The researcher asks a group of respondents some questions,
and the answers to these questions form the empirical basis for theory
development (a similar logic applies to qualitative interviews). The
underlying assumption of this approach is that the respondent is able to
recognize and articulate the determinants of their behavior. This view is in
line with Gordon Allport’s (1953, p. 114) view that “simple, conscious report
is the whole truth. It can be taken at its face value.”
However, motivational psychologists have been increasingly moving away
from this view. It is now taken for granted by most researchers that there are
more influences than those reportable in questionnaires, and more than meets
the eye. If this is the case, then researchers need tools that can tap into these
unconscious (or implicit) influences. One of the most commonly used tools
is the Implicit Association Test.
What is the Implicit Association Test?
The Implicit Association Test (IAT, Greenwald, McGhee, & Schwartz, 1998)
is a computerized reaction-time measure. Participants classify a series of
stimuli either to the right or left of the screen depending on their semantic
meaning. As an illustration, imagine that a study was designed to measure
attitudes toward English and Arabic. In this case, words like Pleasant and
Unpleasant are paired with each of English and Arabic. In the first condition,
Arabic may be paired with Pleasant and English with Unpleasant (see Figure
1). In the second condition, the pairing is reversed so that Arabic is now
paired with Unpleasant while English with Pleasant. The score is calculated
by comparing the reaction time in each condition. Most Arabic speakers find
it easier to perform the task when Arabic is paired with Pleasant, whereas
most English people find the opposite easier.
Breaking Theory: New Directions in Applied Linguistics
Aston University, Birmingham
Figure 1: A trial of the IAT. The correct answer here would be the left pair
because the stimulus Honest belongs to Pleasant.
Just as its name suggests, the IAT measures an ‘association’ between two
words. It is ‘implicit’ because most people are unaware of these associations
and usually find their own results surprising. Whether these associations also
qualify to be considered an attitude has been a subject of debate. However,
an increasing number of empirical studies are showing that implicit
associations indeed predict meaningful outcomes and behaviors that are
consistent with the claim that these associations are attitudes (e.g., see
Rudman, 2008, for a review).
More specifically, the most interesting findings come from tests of known-
groups validity and predictive validity. As for known-groups validity,
research shows that the IAT is capable of correctly distinguishing among
members of different groups in accordance with our a priori knowledge of
them, such as reliably determining the participant’s gender, nationality, and
even affiliation to a group artificially created in the laboratory (for a review,
see Lane, Banaji, Nosek, & Greenwald, 2007). As for predictive validity, a
range of criterion variablesincluding behavioral, judgmental, and
physiological measureshave been successfully predicted by the IAT in
various areas including consumer references, political preferences,
personality traits, sexual orientations, and close relationships.
Unconscious Attitudes toward L2 Speakers
Ali H. Al-Hoorie
In one meta-analysis, the predictive validity of the IAT averaged r = .274,
and the IAT and self-report measures displayed incremental validity, in that
each predicted criterion variance over and above that predicted by the other
measure alone (Greenwald et al., 2009). In another meta-analysis (Oswald et
al., 2013), the average predictive validity was lower (r = .15) in the area of
racial discrimination. However, the latter meta-analysis was criticized for
including correlations that were not theoretically expected, which suppressed
the resulting correlation (Greenwald, Nosek, & Banaji, 2015).
As an illustration of this type of research, consider a study by Glaser and
Knowles (2008). The researchers examined the relationship between the
implicit stereotype associating Blacks with guns and the tendency to shoot
Blacks faster than Whites in a computer simulation game (known as the
‘Shooter Bias’). The participants viewed pictures of Blacks or Whites
holding either a weapon or a benign object. Although the task was to shoot
individuals holding a weapon regardless of their skin color, participants with
a stereotype associating Blacks with guns (especially those with low
motivation to control their prejudice) misidentified Blacks as holding guns
more frequently.
Implicit attitudes in second language learning
In the remainder of this chapter, I will give a brief summary of two initial
studies I conducted using the IAT in the area of second language (L2)
learning. In the first study, Arab learners of English (N = 365) who were
studying in the UK performed the IAT and completed a questionnaire. The
results showed that learners with explicitimplicit congruence (i.e., with
favorable attitudes toward English both explicitly and implicitly) were
significantly more open to the L2 group than were learners with explicit
implicit incongruence (i.e., favorable at the explicit level only). These results
showed that the IAT scores behave in a theoretically meaningful way.
The first study did not include a measure of actual L2 achievement because
the participants came from various universities and language institutes in the
UK. Therefore, no standardized measure of their achievement was available.
However, the implicit test would become much more useful if it can also
predict who would (not) be successful in the L2. The second study therefore
included a measure of L2 achievement in order to test the hypothesis that
implicit attitudes are also associated with L2 achievement.
The second study involved learners (N = 311) studying English at one
institution in Saudi Arabia. The participants performed the Single-Target
Breaking Theory: New Directions in Applied Linguistics
Aston University, Birmingham
Implicit Association Test (ST-IAT, Wigboldus, Holland, & van
Knippenberg, 2005), which is a variation of the IAT that can use one
category only (e.g., English without having to compare it with Arabic). In
addition to successfully replicating the first study, the results of the second
study showed that learners who scored higher in the implicit test did achieve
higher in the L2 course.
Going back to Gordon Allport’s above-mentioned claim that simple self-
report is ‘the whole truth’, the results of these two studies demonstrate that
self-report may not constitute the whole truth after all. This is because
expressing positive attitudes toward at the explicit level does not always
reflect positive attitudes at the implicit level as well. Researchers should
therefore examine implicit attitudes in order to find out whether they are in
harmony or in conflict with explicit attitudes, and this cannot be done by
self-report measures alone.
When it comes to L2 learning, the results presented above show that an
implicit dimension exists. They also demonstrate that explicitimplicit
harmony and conflict are related to both attitudes and achievement in L2
learning. These findings are encouraging, as they open up a whole new line
of inquiry with ample research opportunities for L2 motivation researchers.
Gordon W. Allport (1953). The trend in motivational theory. In American Journal of
Orthopsychiatry 23:1, pp107-119.
Jack Glaser & Eric D. Knowles (2008). Implicit motivation to control prejudice. In
Journal of Experimental Social Psychology 44, pp164-172.
Anthony G. Greenwald, Debbie E. McGhee & Jordan L. K. Schwartz (1998).
Measuring individual differences in implicit cognition: The Implicit Association
Test. In Journal of Personality and Social Psychology 74:6, pp1464-1480.
Anthony G. Greenwald, Brian A. Nosek & Mahzarin R. Banaji (2015). Statistically
small effects of the Implicit Association Test can have societally large effects. In
Journal of Personality and Social Psychology 108:4, pp553-561.
Anthony G. Greenwald, T. Andrew Poehlman, Eric Luis Uhlmann & Mahzarin R
Banaji (2009). Understanding and using the Implicit Association Test: III. Meta-
analysis of predictive validity. In Journal of Personality and Social Psychology
97:1, pp1741.
Kristin A. Lane, Mahzarin R. Banaji, Brian A. Nosek & Anthony G. Greenwald
(2007). Understanding and using the Implicit Association Test: IV. What we
know (so far) about the method. In Bernd Wittenbrink & Norbert Schwarz (eds),
Implicit Measures of Attitudes. Guilford Press, New York, pp59102.
Unconscious Attitudes toward L2 Speakers
Ali H. Al-Hoorie
Frederick L. Oswald, Gregory Mitchell, Hart Blanton, James Jaccard & Philip E.
Tetlock (2013). Predicting ethnic and racial discrimination: A meta-analysis of
IAT criterion studies. In Journal of Personality and Social Psychology 105:2,
Laurie A. Rudman (2008). The validity of the Implicit Association Test is a scientific
certainty. In Industrial and Organizational Psychology 1:4, pp426429.
Daniël H. J. Wigboldus., Rob W. Holland & Ad van Knippenberg (2005). Single
Target Implicit Associations. Unpublished manuscript.
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Aston University, Birmingham
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This article reports a meta-analysis of studies examining the predictive validity of the Implicit Association Test (IAT) and explicit measures of bias for a wide range of criterion measures of discrimination. The meta-analysis estimates the heterogeneity of effects within and across 2 domains of intergroup bias (interracial and interethnic), 6 criterion categories (interpersonal behavior, person perception, policy preference, microbehavior, response time, and brain activity), 2 versions of the IAT (stereotype and attitude IATs), 3 strategies for measuring explicit bias (feeling thermometers, multi-item explicit measures such as the Modern Racism Scale, and ad hoc measures of intergroup attitudes and stereotypes), and 4 criterion-scoring methods (computed majority-minority difference scores, relative majority-minority ratings, minority-only ratings, and majority-only ratings). IATs were poor predictors of every criterion category other than brain activity, and the IATs performed no better than simple explicit measures. These results have important implications for the construct validity of IATs, for competing theories of prejudice and attitude-behavior relations, and for measuring and modeling prejudice and discrimination. (PsycINFO Database Record (c) 2013 APA, all rights reserved).
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This review of 122 research reports (184 independent samples, 14,900 subjects) found average r = .274 for prediction of behavioral, judgment, and physiological measures by Implicit Association Test (IAT) measures. Parallel explicit (i.e., self-report) measures, available in 156 of these samples (13,068 subjects), also predicted effectively (average r = .361), but with much greater variability of effect size. Predictive validity of self-report was impaired for socially sensitive topics, for which impression management may distort self-report responses. For 32 samples with criterion measures involving Black-White interracial behavior, predictive validity of IAT measures significantly exceeded that of self-report measures. Both IAT and self-report measures displayed incremental validity, with each measure predicting criterion variance beyond that predicted by the other. The more highly IAT and self-report measures were intercorrelated, the greater was the predictive validity of each.
Greenwald, Poehlman, Uhlmann, and Banaji (2009; GPUB hereafter) reported an average predictive validity correlation of ̄r = .236 for Implicit Association Test (IAT) measures involving Black-White racial attitudes and stereotypes. Oswald, Mitchell, Blanton, Jaccard, and Tetlock (2013; OMBJT) reported a lower aggregate figure for correlations involving IAT measures (̄r = .148). The difference between the estimates of the 2 reviews was due mostly to their use of different policies for including effect sizes. GPUB limited their study to findings that assessed theoretically expected attitude-behavior and stereotype-judgment correlations along with others that the authors expected to show positive correlations. OMBJT included a substantial minority of correlations for which there was no theoretical expectation of a predictive relationship. Regardless of inclusion policy, both meta-analyses estimated aggregate correlational effect sizes that were large enough to explain discriminatory impacts that are societally significant either because they can affect many people simultaneously or because they can repeatedly affect single persons. (PsycINFO Database Record (c) 2014 APA, all rights reserved).
Abstract Implicit Association Tests (IATs) often reveal strong associations of self with positive rather than negative attributes. This poses a problem,in using the IAT to measure associations involving traits with either positive or negative evaluative content. In two studies, we employed non-bipolar but evaluatively balanced Big Five traits as attribute contrasts and explored correlations of IATs with positive (e.g. sociable vs. conscientious) or negative (e.g. reserved vs. chaotic) attributes. Results showed,(a) satisfactory internal consistencies for all IATs, (b) explicit–explicit and implicit–implicit correlations that were moderate to high and comparable,in strength after both were corrected for attenuation and (c) better model fit for latent variable models that linked the implicit and explicit measures to distinct latent factors rather to the same factor. Together, the results suggest that IATs can validly assess the semantic aspect of trait self-concepts and that implicit and explicit self-representations are, although correlated, also distinct constructs. Copyright # 2008 John Wiley & Sons, Ltd. Key words: implicit personality self-concept; semantic associations; valence associa- tions; Big Five Often we realize very quickly whether we like or dislike something or somebody,without
This research examines whether spontaneous, unintentional discriminatory behavior can be moderated by an implicit (nonconscious) motivation to control prejudice. We operationalize implicit motivation to control prejudice (IMCP) in terms of an implicit negative attitude toward prejudice (NAP) and an implicit belief that oneself is prejudiced (BOP). In the present experiment, an implicit stereotypic association of Blacks (vs. Whites) with weapons was positively correlated with the tendency to “shoot” armed Black men faster than armed White men (the “Shooter Bias”) in a computer simulation. However, participants relatively high in implicit negative attitude toward prejudice showed no relation between the race-weapons stereotype and the shooter bias. Implicit belief that oneself is prejudiced had no direct effect on this relation, but the interaction of NAP and BOP did. Participants who had a strong association between self and prejudice (high BOP) but a weak association between prejudice and bad (low NAP) showed the strongest relation between the implicit race-weapons stereotype and the Shooter Bias, suggesting that these individuals freely employed their stereotypes in their behavior.
An implicit association test (IAT) measures differential association of 2 target concepts with an attribute. The 2 concepts appear in a 2-choice task (2-choice task (e.g., flower vs. insect names), and the attribute in a 2nd task (e.g., pleasant vs. unpleasant words for an evaluation attribute). When instructions oblige highly associated categories (e.g., flower + pleasant) to share a response key, performance is faster than when less associated categories (e.g., insect & pleasant) share a key. This performance difference implicitly measures differential association of the 2 concepts with the attribute. In 3 experiments, the IAT was sensitive to (a) near-universal evaluative differences (e.g., flower vs. insect), (b) expected individual differences in evaluative associations (Japanese + pleasant vs. Korean + pleasant for Japanese vs. Korean subjects), and (c) consciously disavowed evaluative differences (Black + pleasant vs. White + pleasant for self-described unprejudiced White subjects).
Motivational theory today seems to be turning a corner in the road of scientific progress. This article pay special attention to the problem of psychodiagnostic methods. For the successes and failures of these methods can teach us much about psychodynamic theory. In addition to irrationalism modern dynamic psychology has developed another earmark: geneticism. The original instincts laid down in our nature are regarded as decisive, or if not, then the experiences of early childhood are held to be crucial. At this point, the leading nondynamic school of thought, stimulus-response psychology, joins forces with geneticism. Before such an adequate conceptualization can be achieved there is one current dogma in motivational theory that demands re-examination. This doctrine-found in instinctivism, psychoanalysis, and in stimulus-response psychology-operates to keep us on a primitive level of theorizing. In unhealthy motivation, unbalancing mechanisms have the upper hand. The individual represses ineffectively; repressed motives erupt in autistic gestures, in tantrums, in nightmares, in compulsions, perhaps in paranoid thinking. When studying a person's motives one is seeking to find out what that person is trying to do in this life, including of course what he is trying to avoid, and what he is trying to be. Most people, suspected, can tell what they are trying to do in this life with a high degree of validity, certainly not less on the average than the prevailing validity of projective instruments. (PsycINFO Database Record (c) 2013 APA, all rights reserved)