At Drexel University, this Thursday and next Thursday evenings. Six speakers bring a variety of expertise to cover different facets of the use of, and rationale for, facilitated communication (FC/RPM/S2C) in individuals with autism!
You can register here: https://drexel.qualtrics.com/
With the help of my readers, I've found out about several typos in my recent books that went undetected by me, my editors, and my early readers. They also went undetected by Microsoft Word and Grammarly. (I have not found Grammarly helpful for style, but it is useful for catching some typos).
But what about ChatGPT? Surely a technology that can mimic human texts so convincingly that professors are to turning to AI detection tools (to determine whether their students actually wrote their papers themselves) should be able to take an existing paper and detect all its typos.
The issue is that proofreading entails text processing, while text-generation, especially when it comes to AI, does not. For text generation, AI can rely solely on statistics and pattern recognition--specifically, the patterns and frequencies of certain words or structures in gigantic amounts of data it's been fed. It can then use these patterns and frequencies to generate text that is similar to the texts it was trained on--specifically, those texts that, based on their patterns, are most statistically relevant to the prompt.
No need, here, for AI to actually understand anything. Nor does it appear to, as we see, for example, in Catherine's recent posts.
Most text processing, in contrast, cannot rely on statistics and pattern recognition (the one apparent exception being the text processing that goes into detecting the likelihood that a paper was generated by AI). Most text processing, that is, involves something more akin to comprehension. To summarize, AI needs to understand the main points; to simplify, it needs to understand well enough to paraphrase; and to detect many common writing errors--e.g., whether "or" should have been "of", or vice versa ("careful reading of good writing" vs. "careful reading or good writing")--comprehension is crucial. Comprehension, in turn, involves:
1. Word, sentence, paragraph, and text-level semantics and pragmatics (including subtle forms of negation like "mixed up with" and irony).
2. Knowledge of how linguistic meaning maps onto real-world phenomena, including sensory experience. For this, we may need ambient robots that can process not just visual information (parsing the world into a 3D model of shapes and colors), but also auditory information (including phonological information), and tactile and chemical information.
Not surprisingly, AI seems nowhere near able to scale what some in the field have called the "barrier of meaning."
The irony is that proofreading, summarizing, and simplifying are much more useful than text-generating, which probably raises more problems than it solves.
More useful but so much more difficult--at least for AI.
Cross-posted at FacilitatedCommunication.org).
In my last four posts, I critiqued the arguments in Gernsbacher and Yergeau’s 2019 article that ToM (Theory of Mind) tests lack empirical validity—in particular, that the original test results with autistic subjects have failed to be replicated, and that the tests themselves fail to converge on a meaningful psychological construct and fail to predict autism-related traits and empathy and emotional understanding.
Morton A. Gernsbacher, Professor of Psychology, University of Wisconsin
Gernsbacher and Yergeau’s final line of argument concerns the question of whether the ToM tests, as is generally claimed, tap into the ability of autistic people to infer other people’s goals and desires. Here they return to the argument made in Gernsbacher et al. (2008), and claim that “autistic people of all ages skillfully understand other persons’ intentions, goals, and desires.” In support of this claim, they cite several dozen studies. The problem here is that, as I discussed earlier, the kinds of intentions, goals, and desires are all basic, instrumental level goals, intentions, and desires—the kind represented by instrumental physical activities like reaching, pulling apart, and inserting. Thus, we are not talking about social goals and intentions like making a good impression, or complex psychological desires like romantic interest.
And, indeed, what some of the articles (e.g., Aldridge, 2008; Colombi et al., 2009; Carpenter et al., 2001; Falck-Ytter, 2010; Berger and Ingersoll, 2014; Fitzpatrick et al., 2013) show is that autistic individuals are no more impaired in their ability to detect intentions, goals, and desires vis-à-vis concrete, visible, physical tasks—reaching, pulling apart, inserting— than other people are, even when the actors performing these activities fail to achieve them.
On occasion, as Liebal et al. (2008) have found, the ability of individuals with autism to understand intentions vis-à-vis concrete tasks extends to an ability and willingness, in some cases, to help a person fulfill those intentions: whether in helping the person reach something, pick up something the person dropped accidentally, or cooperate with the person in taking apart a container. However, compared to a group of developmentally delayed children, Liebal et al. found that fewer children with autism provided help and, when the person ceased performing a task, they made fewer attempts to reengage them and were poorer in their attempts to coordinate eye gaze with them. This suggests that, while the ability to infer these sorts of physical intentions may be intact in autism, the ability to share intentions is impaired. Colombi et al. (2009) agree, noting the difficulty that autistic individuals have with imitation and joint attention.
Berger and Ingersoll (2014) found that autistic children were able to use social-communicative indicators like facial expressions to infer whether an act (say, dropping an object) was deliberate or accidental. However, they also found that autistic children made these distinctions less often than typically developing children do—because they attended less frequently to faces. Vivante et al. (2011), meanwhile, found that high-functioning autistic participants could make inferences about intention based on people’s facial expressions, but not based on their head movements and gaze shifts. (We should note here that the facial expressions involved in this study are less challenging than the more subtle, eye-area facial expressions assessed by the Eyes test, which is where individuals with autism show difficulty). Finally, Fitzpatrick et al. (2013) found that autistic children, while able to infer and imitate intentional tasks, have more difficulty with tasks that involve synchronizing their movements with others.
As seen, much of the research on the ability of autistic children to infer intentions has focused on instrumental tasks. And as Berger and Ingersoll (2014) note, various researchers have pointed out that the sorts of tasks involved in these studies—reaching, pulling apart, inserting—“may not provide a true measure of the ability to infer the intentions of others.” Perhaps autistic children would perform equally well when watching robots perform the same actions. Or perhaps, as Vivanti et al. (2011) suggest, their inferences about intentions are based, in part, on the characteristics and/or standard use of the objects being acted upon (as when someone centers an object with a hole in it around a dowel). In support of this hypothesis, Vivanti et al. cite a study by Boria et al. (2009) that found that children with autism had difficulty inferring intent when the actor’s intentions did not match the conventional use of the object.
Colombi et al. (2009), furthermore, argue that understanding intentions may not be the same as sharing intentions and that it is sharing intentions (i.e., cooperating) that lies at the heart of the social deficits of autism. And Fitzpatrick et al. (2013) found that ToM tasks and intentionality tasks correlate with distinct psychological factors, which suggested that these tasks “may not be measuring the same underlying construct.” Fitzpatrick et al. propose, in particular, that sharing intentions correlates with lower-level perceptual and attentional dimensions of social competence (“social attention”), while ToM tasks correlate with higher-level cognitive socio-cognitive factors (“social knowledge”).
Some of the research cited by Gernsbacher and Yergeau, however, goes beyond findings about the ability of autistic participants to infer intentions. Kerr and Durkin (2004), for example, propose that eliminating the language confounds in explicit ToM tests eliminates the performance difference between verbal-age-matched autistic and non-autistic subjects. Notably, the autistic participants in Kerr and Durkin’s study were far below the higher verbal mental age that other studies have shown to be a prerequisite for passing the false-belief ToM tests in autism. The problem with Kerr and Durkin’s study, however, is that it’s not clear that the various measurements truly probed the ability to make inferences relating to beliefs. Children were taught that a thought bubble “shows what X is thinking”, such that, when asked which object a character was thinking about, they named the object depicted within the thought bubble rather than an object in the scene outside the thought bubble. But it’s unclear whether all the participants truly understand the bubble’s contents as a thought, as opposed to simply learning to look in the bubble when they hear the word “thinking.”
This calls into question Kerr and Durkin’s main finding. In their experiment, the participants were shown scenes in which the contents of a box were invisible, an object next to the box was visible, and a character with a picture of a different object in the thought bubble over his/her head was shown looking into the box. When participants were asked “What is in the box?”, both autistic and non-autistic participants named the object in the thought bubble, not the object next to the box. Kerr and Durkin take this as an indicator of ToM: an ability to attribute beliefs to other people. They do not rule out the alternative, non-ToM-based strategy of process of elimination: one object is clearly next to the box and not in it. As for the object inside the thought bubble, it is harder to see it as having a definite spatial relationship with the box (i.e., as being above the box): the graphic outlines of the thought bubble separate it from the scene, and if it were part of the scene, it would have to be somehow suspended in the air. These two factors make the object in the thought bubble a much better candidate for being the object in the box than the object next to the box is.
McAleer et al. (2011)’s study is similarly unconvincing. High-functioning adults and non-autistic controls were shown videos of actors enacting scenes of chasing, fighting, following, guarding, playing, and flirting. Both groups did equally well in identifying which interaction was being depicted. But these depictions involved only bodily movements, not facial expressions or gestural or verbal communication. Playing, for example, was enacted as a game of tag. Flirting was enacted by one actor moving to another actor, circling that person twice and moving back to their original position, then the other actor doing the same thing, and then, finally, the two walking off together. The authors propose that correctly identifying the flirting scenes involves ToM processing. But, as in Kerr and Durkin (2004), such identification could have been the product of non-ToM reasoning—for example, process of elimination. Given the other options, the double circling and then walking off together is not the best candidate for chasing, fighting, following, guarding, or playing. This means that even participants who were unfamiliar with the concept of flirtation may still have been able to infer which label was most likely.
Li et al. (2019) and Channon et al. (2011), meanwhile, looked at sensitivity to deliberate vs. accidental harm in making moral judgments. They find that autistics, like typically developing children, tend to judge deliberate acts more harshly. But the only ToM reasoning involved in this study is that of distinguishing intentional acts from unintentional ones—and this is not considered one of the core ToM impairments in autism. Channon et al. (2011) also found that the judgments of the autistic subjects were influenced more strongly by what was subjectively foreseeable by the perpetrator. The authors claim that calculating this subjective foreseeability requires an appreciation of the perpetrator’s internal beliefs. But, in fact, the participants are told explicitly what the perpetrators subjectively foresaw (e.g., “Nick himself thinks the virus is aggressive and is likely to cause serious damage.”). Furthermore, as the authors themselves note, autistic individuals may to some extent simply be applying “learned social rule”, and that
[o]ver-reliance on the rigid implementation of learned rules rather than more mentalistic or intuitive interpretations based on subtle nuances of the context could account for the more extreme blame judgments in those with AS in the present study.
Gernsbacher and Yergeau also cite Green et al. (2017), who examined the ability of autistic participants, compared with IQ-matched controls, to view a picture of a social interaction and then choose which of four pictures appearing below it shows the “same kind of interaction.” While Green et al. found no performance differences between the two groups, nor any correlations with autism trait severity, they note that they did not measure reaction time. They do not rule out, therefore, the possibility that the two groups used different processes, with the non-autistic groups making more intuitive judgments. Indeed, Green et al. propose that, while autistic individuals are “capable of using social analogic reasoning ‘effortfully’, it does not come spontaneously.”
Russell and Hill (2001)’s paper focuses on the ability to mentalize about oneself—which, again, is not the sort of ToM deficit generally attributed to autism. Looking at autistic children and IQ-matched controls whose mental ages ranged from 4 to 10 years, they found that both groups were equally able to distinguish outcomes that they desired or achieved from outcomes that they had originally intended. The two groups were also equally successful in a version of the Smarties experiment in which participants were only asked about their own beliefs (“Before I opened the lid of the box, what did you think was in the box?”). At the same time, the autistic group, as expected, performed worse than the comparison group on a Sally-Ann-like false-belief test. All this is consistent with current views of autism as involving perspective-taking deficits (along with other social deficits), as opposed to deficits in self-awareness.
Four additional studies only looked at high-functioning autism (HFA). Vivanti et al. (2011) found that children and adolescents with HFA increased their attention to a person’s face when he/she performed an action in an “irrational” way, as if seeking information about motivation. While this suggests some intact ToM skills, these may be specific to HFA.
Cole et al. (2018) found that HFA adults, as compared with typical controls, displayed typical eye fixation patterns when observing deliberate vs. intentional actions. On the other hand, they also report that the autistic adults had difficulty reporting on the actors’ intentions in the different scenarios. Their conclusion: “Adults with ASD displayed explicit but not implicit mentalizing deficits.”
Sebanz et al. (2005) focus on action representation (the representation of other people’s actions) as opposed to ToM (e.g., the mental representations of other people’s beliefs). Their participants were high functioning enough that they were able to solve first and second-order ToM tasks. Sebanz et al.’s findings—that these autistic participants behaved similarly to non-autistic controls depending on whether a co-participant’s prompt in a go/no-go task coincided with their own go/no-go prompt—do not relate to ToM skills in autism.
Finally, Ponnet et al. (2005)’s study found that high-functioning adults with PDD (a mild form of autism akin to Asperger’s Syndrome) were as able as their non-autistic counterparts to infer the thoughts and feelings of their interaction partner during an 8-minute first-time conversation. However, they also acknowledge that the PDD participants may, over the years, have learned scripts for “an initial conversation of the get-acquainted type,” and that such conversations may not present the same kinds of inferencing challenges as longer and non-initial conversations do. Despite this—but in line with the oft-observed deficit in social initiation seen in autism—Ponnet et al. found that two thirds of the conversations were initiated by the control (non-autistic) adult. Also in line with observations about individuals with HFA, they found that the PDD participants spoke for longer periods of time but made less eye contact, and that fewer of the thoughts and feelings they reported focused on their interaction partner. Finally, Ponnet et al. caution that their PDD participants had IQs far above normal and had been recruited “on the basis of their good performance on previous mind-reading tasks”, reminding us that:
Many researchers have stressed the role of both verbal and chronological age in the performance on theory of mind tasks and have suggested that intelligence might compensate for conceptual perspective taking strategies.
Many of these studies, thus, provide, at best, circumscribed support for Gernsbacher and Yergeau’s contention that “autistic people of all ages skillfully understand other persons’ intentions, goals, and desires.”
But one of the last experiments cited by Gernsbacher and Yergeau would appear to undermine their case as much as it supports it. Hubert et al. (2007) showed participants point-light displays of actions (lifting, hopping, pushing, clapping…), subjective states (itchy, bored, tired, cold), and basic emotional states (surprised, sad, frightened, angry, happy). They found that the autistic participants were just as able as the non-autistic controls to integrate the point-light displays into a holistic image and to identify the actions and subjective states. On the other hand, “they were significantly poorer at labeling emotional displays, suggesting that they are specifically impaired in attending to emotional states”:
For instance, participants with autism would describe the point-light display depicting afraid as someone who walks forwards and then goes back or a person who walks sideways, or the point-light display depicting anger as someone who jumps.
In short, the research on the ability of autistic individuals to infer other people’s goals and desires shows that this largely depends on whether the goals are instrumental or social in nature:
REFERENCES:
Aldridge, M. A., Stone, K. R., Sweeney, M. H., & Bower, T. G. R. (2000). Preverbal children with autism understand the intentions of others. Developmental Science, 3, 294–301. https://doi.org/10.1111/1467-7687.00123
Berger, N. I., & Ingersoll, B. (2014). A further investigation of goal-directed intention understanding in young children with autism spectrum disorders. Journal of Autism and Developmental Disorders, 44, 3204–3214. https://doi.org/10.1007/s10803-014-2181-z
Boria, S., Fabbri-Destro, M., Cattaneo, L., Sparaci, L., Sinigaglia, C., Santelli, E., Cossu, G., & Rizzolatti, G. (2009). Intention understanding in autism. PloS one, 4(5), e5596. https://doi.org/10.1371/journal.pone.0005596
Carpenter, M., Pennington, B. F., & Rogers, S. J. (2001). Understanding of others’ intentions in children with autism. Journal of Autism and Developmental Disorders, 31, 589–599. https://doi.org/10.1023/A:1013251112392
Channon, S., Lagnado, D., Fitzpatrick, S., Drury, H., & Taylor I. (2011). Judgments of cause and blame: Sensitivity to intentionality in Asperger’s syndrome. Journal of Autism and Developmental Disorders, 41, 1534–1542. https://doi.org/10.1007/s10803-011-1180-6
Cole, E. J., Slocombe, K. E., & Barraclough, N. E. (2018). Abilities to explicitly and implicitly infer intentions from actions in adults with autism spectrum disorder. Journal of Autism and Developmental Disorders, 48, 1712–1726. https://doi.org/10.1007/s10803-017-3425-5
Colombi, C., Liebal, K., Tomasello, M., Young, G., Warneken, F., & Rogers, S. J. (2009). Examining correlates of cooperation in autism: Imitation, joint attention, and understanding intentions. Autism, 13, 143–163.
Falck-Ytter, T. (2010). Young children with autism spectrum disorder use predictive eye movements in action observation. Biology Letters, 6, 375–378. https://doi.org/10.1098/rsbl.2009.0897
Fitzpatrick, P., Diorio, R., Richardson, M. J., & Schmidt, R. C. (2013). Dynamical methods for evaluating the time-dependent unfolding of social coordination in children with autism. Frontiers in Integrative Neuroscience, 7, Article 21. https://doi.org/10.3389/fnint.2013.00021
Gernsbacher, Sauer, Geye, Schweigert, and Goldsmith (2008), Why does joint attention look atypical in autism. Child Development Perspectives 2(1), 38-45. doi/full/10.1111/j.1750-8606.2008.00039.x
Gernsbacher, M. A., & Yergeau, M. (2019). Empirical Failures of the Claim That Autistic People Lack a Theory of Mind. Archives of scientific psychology, 7(1), 102–118. https://doi.org/10.1037/arc0000067
Green, A. E., Kenworthy, L., Gallagher, N. M., Antezana, L., Mosner, M. G., Krieg, S., . . . Yerys, B. E. (2017). Social analogical reasoning in school-aged children with autism spectrum disorder and typically developing peers. Autism, 21, 403–411. https://doi.org/10.1177/1362361316644728
Hubert, B., Wicker, B., Moore, D. G., Monfardini, E., Duverger, H., Da Fonseca, D., & Deruelle, C. (2007). Recognition of emotional and non-emotional biological motion in individuals with autistic spectrum disorders. Journal of Autism and Developmental Disorders, 37, 1386–1392. https://doi.org/10.1007/s10803-006-0275-y
Kerr, S., & Durkin, K. (2004). Understanding of thought bubbles as mental representations in children with autism: Implications for theory of mind. Journal of Autism and Developmental Disorders, 34, 637–648. https://doi.org/10.1007/s10803-004-5285-z
Li, T., Decety, J., Hu, X., Li, J., Lin, J., & Yi, L. (2019). Third-party sociomoral evaluations in children with autism spectrum disorder. Child Development. Advance online publication. https://doi.org/10.1111/cdev.13206
Liebal, K., Colombi, C., Rogers, S. J., Warneken, F., & Tomasello, M. (2008). Helping and cooperation in children with autism. Journal of Autism and Developmental Disorders, 38, 224–238. https://doi.org/10.1007/s10803-007-0381-5
McCleery, A., Divilbiss, M., St-Hilaire, A., Aakre, J. M., Seghers, J. P., Bell, E. K., & Docherty, N. M. (2012). Predicting social functioning in schizotypy: An investigation of the relative contributions of theory of mind and mood. Journal of Nervous and Mental Disease, 200, 147–152.
Ponnet, K., Buysse, A., Roeyers, H., & De Corte, K. (2005). Empathic accuracy in adults with a pervasive developmental disorder during an unstructured conversation with a typically developing stranger. Journal of Autism and Developmental Disorders, 35, 585–600. https://doi.org/10.1007/s10803-005-0003-z
Russell, J., & Hill, E. L. (2001). Action-monitoring and intention reporting in children with autism. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 42, 317–328. https://doi.org/10.1111/1469-7610.00725
Sebanz, N., Knoblich, G., Stumpf, L., & Prinz, W. (2005). Far from action-blind: Representation of others’ actions in individuals with autism. Cognitive Neuropsychology, 22, 433–454. https://doi.org/10.1080/02643290442000121
Vivanti, G., McCormick, C., Young, G. S., Abucayan, F., Hatt, N., Nadig, A., . . . Rogers, S. J. (2011). Intact and impaired mechanisms of action understanding in autism. Developmental Psychology, 47, 841–856. https://doi.org/10.1037/a0023105
As I've noted elsewhere, metaphors proliferate in the typed output that is extracted from autistic individuals via facilitated communication (as in “My senses always fall in love / They spin, swoon”, attributed to Deej).
But at the same time that the pseudoscience of autism attributes metaphorical language to autistic individuals, much of the science of autism would appear, perhaps a bit prematurely, to preclude it.
This is a topic I address in my recent book:
Here's an edited extract on the topic from an old post:
“I found
it, hiding between bed and chest.”
Not a particularly remarkable statement, except that it came from a child with
a neurological condition that supposedly makes this sort of language
inaccessible.
The neurological condition, mild-moderate autism;
and the language in question, the non-literal language the child used to depict
his bathrobe as an entity that hides itself.
Personification is a subtype of metaphor in which a non-human entity is
compared to a person. Metaphors are often claimed to be an area in
which autistic children struggle—and there are even experiments that back up
this claim (though more recent studies have called this into question). The problem, supposedly, is inherent to autism: autistic
individuals are said to have difficulty with non-literal language in general.
So is this child really that unusual among his peers? Or might it be that a great many
more people on the autistic spectrum have a much greater
capacity for figurative language than we give them credit?
To see what it takes to grasp the figurative sense of “hiding,” it’s useful to
divide instances of metaphor (and personification in particular) into three
categories:
1. Frozen metaphors: phrases
2. Generalized, conventionalized metaphors
3. Novel, creative metaphors
Frozen metaphors are metaphors expressed in fixed expressions—“music to my
ears”; “boiling mad”--that are used so often that they’re practically
idiomatic. Indeed, some of what has been claimed to be examples of metaphor
(see here and here) might just as
easily be classified as idioms or idiomatic expressions: “an angel,” “a snake,”
“a pig,” “a rock,” “bubbly,” or “sweet” (said of a person); “warm,” “cold,”
“dark,” “light,” “up,” “down,” “blue,” or “sour” (said of a mood); “heated”
(said of an argument); “spinning” (said of someone’s head); “loud” (said of
colors); “reeks of” (as in “suggests”); “fishing for” (as in “seeking”), “a
melting pot,” “a broken heart,” “the light of my life,” “the apple of my eye,”
and “emotional rollercoaster.” Like idiomatic expressions, these phrases/usages
can be learned one by one just as individual vocabulary words are.
Generalized, conventionalized metaphors are the ones that linguist George
Lakoff and philosopher Mark Johnson talk about in Metaphors We Live By: standard, general metaphors that form the basis for more
particular ones. Here are two sets of generalized metaphors from Lakoff and
Johnson:
ARGUMENT IS WAR
And here’s my elaboration of their personification metaphor: ENTITIES ARE HUMAN/SENTIENT/PURPOSEFUL The engine is tired.
Here's an update of an old post, based on an article I published in the Atlantic, The Common Core is Tough on Kids with Special Needs, that I think is just as relevant today as it was 9 years ago.
Some people have cited the following passage from the Common Core
State Standards as allowing teachers "a huge amount of leeway" to provide their special needs students with what they need:
Teachers will continue to devise lesson plans and tailor instruction to the individual needs of the students in their classrooms.
The Standards set grade-specific standards but do not define the intervention methods or materials necessary to support students who are well below or well above grade-level expectations. No set of grade-specific standards can fully reflect the great variety in abilities, needs, learning rates, and achievement levels of students in any given classroom. However, the Standards do provide clear signposts along the way to the goal of college and career readiness for all students.
It is also beyond the scope of the Standards to define the full range of supports appropriate for English language learners and for students with special needs. At the same time, all students must have the opportunity to learn and meet the same high standards if they are to access the knowledge and skills necessary in their post–high school lives.
For all this leeway, however, serious problems remain:
1. Large numbers of special ed students are mainstreamed into
regular classrooms based on calendar age rather than mental age. I.e., if you
turned 13 by September 1st and are not so severely
intellectually impaired that you spend all your time in a special ed classroom,
you attend 8th grade classes even if cognitive testing shows you
reading at a 4th grade level.
2. Specific CC standards are pegged to specific grade
levels (e.g., 8th grade).
3. The CC standards name specific sets of texts, including Shakespeare
and America's Founding Documents, that all students should read, as well as
specific levels of reading passage complexity, exemplified by sample texts (and
sample reading assignments) in its well-known Appendix B, and, again pegged
to specific grade levels (e.g., 8th grade).
Putting it all together, we have all mainstreamed 13-14-year-olds, even those
reading at a 4th grade level, expected to make their way through passages whose
complexity matches that of Mark Twain's Tom Sawyer, for example, this one:
Inspired by the splendor of his own act, he took without an outcry the most merciless flaying that even Mr. Dobbins had ever administered; and also received with indifference the added cruelty of a command to remain two hours after school should be dismissed—for he knew who would wait for him outside till his captivity was done, and not count the tedious time as loss, either.
So is it really the case that teachers have "tremendous
leeway"? More importantly, do most teachers perceive that they have
tremendous leeway? Here's how I opened my article:
In a recent discussion board thread on reading comprehension challenges in autism, a special-education teacher commented that her students can’t understand the assigned reading passages. “When I complained, I was told that I could add extra support, but not actually change the passages,” she wrote. “It is truly sad to see my students’ frustration.”
This student isn't alone; she's echoing what I'm hearing from a great many students, most of whom are already teachers of special needs students, many of whom are extremely frustrated by the CC Standards.
Are all of them misinterpreting the Standards?
To some extent, the answer to that question is irrelevant. When large numbers
of flesh and blood students are deprived of the developmentally
appropriate reading assignments that they depend on in order to maximize their
progress in reading, it doesn't matter whether or not this deprivation occurred
because of correct or incorrect interpretations of the Common Core Standards.
All that matters is that they aren't getting what they need.
Furthermore, there's flexibility and then there's flexibility. Letting teachers
decide what reading level is appropriate for their students is one thing; the
Common Core does not do this. Instead, it tells them what the reading
level has to be and leaves it up to them to somehow figure out what
"supports" or "intervention methods" or
"materials" will somehow give all students
meaningful access to texts at this reading level. This is a very
different sort of "flexibility."
Imagine being told: "You need to climb this 200-foot cliff,
but don't worry, we're giving you all the flexibility you want because
we're not telling you how to do it or providing you with any specific
materials."
Of course, some people may simply helicopter their way to the
top of the cliff. Likewise, some educators may, as I discuss in my
article, essentially give away the answers or otherwise fake their way through
things. Or they may convince themselves that students have attained standards when
objective, independent testing would reveal otherwise.
But the ultimate problem, the one that trumps all others, is that no
amount of "supporting" and "intervening" and
"differentiating" and IEP writing makes any difference in the world
if the curricular content assigned to special needs students doesn't
match their levels of developmental readiness.
The elimination or downplaying by more and more colleges of applicant SAT scores, along with a recent article on why that's a bad idea, reminded me of an old OILF post.
The article highlights how the SATs used to benefit a type of student that today we might call "neurodivergent":
the kind who is bright and talented but who had failed to live up to their potential in class. These students tended to be the brilliant dreamers; they were the ones in possession of uncommon cognitive skills, but who performed poorly in knowledge-based exams because of bad time management, resistance to the indignities of organised education, or an inability to prioritise school over their own interests. For decades, excellent SAT scores got students into colleges that they wouldn’t ordinarily get into, creating opportunities to find diamonds in the rough who had perhaps never found their footing in school.
We Need More
Tests, Not Fewer, argues John D. Mayer, a professor of
psychology at the University of New Hampshire and author of “Personal
Intelligence: The Power of Personality and How It Shapes Our Lives," in a
recent Op-Ed in the New York Times.
He begins by talking about how effectively tests capture people's later
accomplishments, as well as more elusive aspects of cognitive potential and
personality:
Research indicates that mental tests do predict people’s patterns
of behavior in consequential ways. For instance, graduate students’ G.R.E.
scores are correlated with the ratings faculty members later give them, their
likelihood of remaining in a program, and the impact of their publications (as
measured by citations). And tests like the NEO-PI-R that measure social and
emotional traits like conscientiousness and agreeableness can predict a
person’s longevity and likelihood of staying married.
In addition, tests are our only way to study and attempt to
understand ineffable mental qualities like intelligence, openness to experience
and creativity. They help make the mysteries of mental life tangible.
Neuroscientists use them to discover who excels in particular mental abilities,
and to try to identify the parts of the brain responsible.
So far so good. All this sounds reasonable and plausible. Over the
last century, a whole host of different tests have emerged that predict,
apparently with increasing accuracy, more and more aspects of cognition and
personality.
Much less clear, however, is how these tests should be used. One
good use, in Meyer's opinion, is in college admissions:
What if, in addition to the SAT, students were offered new tests
that measured more diverse abilities? For future artists or musicians, there
are tests that measure divergent thinking — a cornerstone of creativity largely
ignored by the SAT. For future engineers, there are tests that measure spatial
reasoning. And new measures of “personal intelligence” — the ability to reason
about a person’s motives, emotions and patterns of activities — may also tell
us something important about students’ self-knowledge and understanding of
others.
But considering non-academic skills like social skills, and,
arguably, divergent thinking, smacks of the "best graduates" over
"best students" strategy, discussed in Malcolm Gladwell's 2005 New
Yorker article Getting In, that was used by
Harvard, Yale and Princeton to limit the numbers of Jewish matriculates back in
the mid-20th century--and that is probably being used by those same schools to
limit the numbers of Asian students today. Should admissions favor those who
look like they will have the most "successful" careers after college
(as measured, typically, by fame and fortune) over those who look like they
will do best in college classes?
Colleges, of course, aren't monoliths, and different insiders will have different answers to this question. Professors, presumably, prefer students who show up to class, pay attention, contribute to discussions, write the best papers and problem sets, and have the greatest potential to master the course material; development officers, presumably, favor those who will donate the most money and generate the most publicity for their alma maters.
Ethics, I believe, are firmly on the side of the professors.
First of all, taken to its extreme, a best-graduates policy has
you favoring not only those with certain types of social skills, leadership
skills, and creative skills, but also those with certain physical traits and
family resources. Beauty, stature, and family wealth and connections, after all,
are correlated with future earnings and fame. Thus, in addition to the existing
discrimination against Asians and nerds and Aspies you'd have (to the extent
that this is not already the case--cf. legacy admissions) discrimination
against the vertically-impaired, the not-so-good-looking, and those
from disadvantaged socio-economic backgrounds.
Second of all, what is the purpose of these non-profit, government-funded, academic institutions called colleges? Is it to coast off of those who will have a certain type of showy, real-world success regardless of how much, or how little, they actually teach them? Or is it to recruit, challenge and inspire the most academically advanced and motivated students and help them reach their academic capacities, both by teaching them well inside the classroom, and by providing fora--cafeterias, quadrangles, and common rooms--where they can interact among themselves, conversing, arguing, and bouncing ideas around, in ways that many of them have never before had the opportunity?
In a recent article at the New York Post, “free range kids” proponent Lenore Skenazy inadvertently promotes what all the available evidence suggests is the opposite of a free range childhood: spending hours drifting one’s finger over a letterboard and, in response to subtle subconscious cues and not so subtle prompts from the person holding up the board, slowly picking out one letter after another in sequences that sometimes number several dozen letters long.
Talk about helicopter parenting! This is about as bad as it gets.
If you want to provide these kids with a free-range childhood, then help them learn independent, efficient communication–not pseudo-communication in which they depend on an adult to get in their space and constantly prompt them to keep going. At least one of these kids can speak: he pronounces the word “letterboard” fluently and intelligently. Why is no one helping him develop his speech skills? Why is no one teaching these kids ten-finger typing? The actual answer, of course, is that this kind of communication doesn’t lend itself to cuing the way hovering your index finger over a held-up letterboard does. But the claim made by Skenazy, who only cites S2C and RPM proponents rather than autism experts and scientists, is that these children, and other non-speaking kids, have fine-motor control difficulties (there’s no evidence of that) and that pointing at a specific letter on a letterboard “with your whole arm” is a fine-motor movement (it isn’t).
Skenazy is certain she’s a careful enough observer to know that these kids weren’t being cued. After all, as she points out, no one was actually touching them while they typed. Skenazy seems to have no concerns or questions about the letterboards not being stationary.
As I wrote in a comment on her piece:
Sorry, but unless you’re an expert in subtle cuing, first-hand observation is extremely misleading. If you read up on the autism spectrum and on language and literacy acquisition in autism, you’ll see how unlikely all this is. Extraordinary claims require extraordinary evidence, and practitioners, if you ask them, will come up with all sorts of reasons why they won’t subject this to rigorous testing. For more information and a repository of research on this, see https://www.facilitatedcommunication.org/
In recent posts, cross-posted at FacilitatedCommunication.org, I critiqued the arguments in Gernsbacher and Yergeau’s 2019 article (“Empirical Failures of the Claim That Autistic People Lack a Theory of Mind”) that ToM tests lack empirical validity—in particular, that the original test results with autistic subjects have failed to be replicated, and that the tests themselves fail to converge on a meaningful psychological construct and fail to predict autism-related traits.
As the article continues, Gernsbacher and Yergeau turn to the extent to which ToM tests predict empathy and emotional understanding. Here, too, their arguments are problematic. The ToM tests the authors consider here are:
The Eyes Test, which measures the ability to recognize emotions from facial information that is restricted to a rectangular region around the eyes
The false-belief tests, which measures the ability to make inferences about the beliefs held by (or about) individuals who are missing key pieces of information
First, as before, some of Gernsbacher and Yergeau citations do not include participants with autism, and so their relevance here is unclear. In addition, once again, some of these results are not surprising, given what specific ToM tests measure. Gökçen et al. (2016) found “non-significant correlations between measures tapping cognitive and affective empathy.” Wilson (2014) reported similar results. Peterson (2014) found that false-belief tests were not correlated with teacher reports of affective empathy behaviors like “offering comfort to a child who is in distress”. And Melchers et al. (2015) found that the Eyes test “barely” correlated with participants’ self-reported assessments of empathy.
But there’s no reason to think that the cognitive perspective-taking skills measured by the false-belief tests would relate directly to emotional empathy and emotional understanding, or that facial expression reading skills are the only determining factor in empathy.
In addition, as I discussed in my previous post, there is the issue of the heterogeneity of the autism spectrum. Lombardo et al., (2015), recall, identify two discrete groups, only one of which had difficulty with Eyes test. Yet both groups, they report, were similar on measures of empathy. Relatedly, there are Baron-Cohen et al. (2015)’s gender-specific results, which also pertain to his Empathy Quotient test. Baron-Cohen et al. found a tight correlation between high performance on Eyes test and high Empathy Quotient scores, but only in autistic females.
Finally, one of the papers cited by Gernsbacher and Yergeau, namely Olderbak et al. (2015), while underscoring the language confound in the Eyes test (discussed in my previous post), still notes that this test is also correlated, if not as strongly as language levels are, with cognitive empathy and emotion perception.
Gernsbacher and Yergeau’s next claim is that ToM tests fail to correlate with everyday social skills. Most of the studies they cite here pertain to non-autistic groups—in particular, individuals with schizophrenia and epilepsy. Two studies—Frith et al. (1994) and Sparrevohn & Howie (1995)—while they do address autism, do not address social behavior. Several smaller studies, however, do address autism and social behavior.
Bennett et al. (2013) found that performance on the Eyes test was correlated with language and adaptive functioning in the communication domain, but not in the social domain. Fombonne et al. (1994) found that, after controlling for language, there was no correlation between performance on false-belief tasks and social behavior. Similarly, Joseph & Tager-Flusberg (2004) found that false-belief tests do not correlate with reciprocal social interaction. Finally, Prior et al. (1990) found that performance on an emotion recognition task and on false-belief tests were only weakly related to parent- reported social behavior.
In line with what we discussed earlier, however, the fact that the cognitive perspective-taking skills measured by the false-belief tests do not relate directly to social behavior, or that facial expression reading skills are not a significant factor in social functioning, may simply mean that these tests are picking up different aspects of the social weaknesses underlying autism, which may vary from individual to individual.
Moreover, one of the tests, Hughes et al. (1997), reaches the opposite conclusion about whether ToM tests correlate with everyday social skills:
This study offers a (small) cross-cultural replication of recent work suggesting that differences in the mentalising skills of children with autism are reflected in the everyday social behaviour of this group.
Next, Gernsbacher and Yergeau turn to the correlation—or, they claim, lack thereof—between ToM tests and social attention, cooperation, anticipation, persuasion, deception, and avoidance. Of the studies with autistic subjects, one focuses instead on autobiographical memory, whose relationship to these other phenomena is unclear. Four other studies are relevant. Angus et al. (2015) found no correlation in autism between passing second-order false-belief tests and being able to prepare oneself for a social interaction by anticipating its likely form and content. Burnside et al. (2017) found no correlation between performance on an implicit false-belief test and measures of social motivation. And Chin and Bernard-Opitz (2000) found that teaching conversation skills does not improve performance on first and second-order false-belief tests. The common theme here, however, may simply be that cognitive perspective-taking is largely independent from other social skills.
The fourth study that Gernsbacher and Yergeau cite, however, does not support their claim. Peterson, Slaughter, & Wellman (2018) find that false-belief performance predicts skills at persuasion.
Finally, Gernsbacher and Yergeau turn to the correlation—or lack thereof—between ToM tests and peer relations and pro-social behavior. Here, two studies involve autistic children.
Begeer et al. (2010) used a novel cognitive perspective-taking test—an interactive task in which participants had to pay attention to which objects were visible to their partners. Begeer et al. compared performance on this task to performance on another task in which participants heard a narrative about an interaction and then were asked to retell it, explaining behavior like trembling hands or a sudden departure from a room. The authors found that despite performing as well as typically developing controls on the cognitive perspective-taking task, they tended not to use any words pertaining to mental states or emotions in their story retellings. Once again, we see a disconnect between cognitive perspective-taking skill and other aspects of psychosocial awareness.
Travis et al. (2001), meanwhile, found a disconnect between performance on both false-belief tests and affective (or emotional) perspective taking, on the one hand, and level of engagement in peers on the playground and pro-social behavior in a structured laboratory test, on the other. Affective perspective taking was measured by the child’s ability to match a depiction of one of the four basic emotions—happy, sad, angry, scared—along with its verbal label, to a character in a vignette who experienced one of these emotions. Again, these disconnects between measurements may simply reflect that different measurements are measuring different, largely unrelated aspects of social awareness/behavior. Pro-social behavior may be largely unrelated to performance on false-belief tests and the understanding of basic emotions because it is, perhaps, largely a function of social motivation.
To sum up:
It’s true that certain ToM tests—particularly the tests measuring facial expression reading or deductions about false beliefs—have failed to predict emotional empathy and emotional understanding.
But this may simply reflect that some social phenomena in autism (e.g., pro-social behavior like peer-engagement, conversational skills, and offering comfort to those in distress) may be more a function of social motivation than of facial-expression reading skills or of cognitive perspective-taking ability.
Autism is a heterogeneous disorder that affects individuals who, as individuals, also vary in ways that are unrelated to autism. It’s not surprising, therefore, that we find variations in social motivation and facial-expression reading skills that aren’t perfectly correlated, one with the other. After all, the same sorts of variation occur in the non-autistic population.
REFERENCES:
Angus, D. J., de Rosnay, M., Lunenburg, P., Meerum Terwogt, M., & Begeer, S. (2015). Limitations in social anticipation are independent of imaginative and Theory of Mind abilities in children with autism but not in typically developing children. Autism, 19, 604–612. https://doi.org/10.1177/1362361314537911
Baron-Cohen, S., Bowen, D. C., Holt, R. J., Allison, C., Auyeung, B., Lombardo, M. V., . . . Lai, M. C. (2015). The “Reading the Mind in the Eyes” Test: Complete absence of typical sex difference in ∼400 men and women with autism. PLoS ONE, 10, Article e0136521. https://doi.org/10.1371/journal.pone.0136521
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