First and second graders’ interpretation of Standard American English morphology across varieties of English

Abstract

While African American English (AAE) and Standard American English (SAE) share many features, there are also differences that could affect comprehension. This article examines how 1st and 2nd grade AAE- and SAE-speaking children interpret sentences containing shared lexical and morphological (i.e., plural –s) forms as compared to sentences containing forms that do not regularly occur in AAE (past tense –ed, 3rd person present –s, future contracted –’ll). Using a picture-choice task the study found that while all children correctly interpreted shared forms, only the SAE-speakers, but not the AAE-speakers, successfully interpreted SAE tense morphology. In addition, the AAE-speakers showed no grade-related changes in performance. This suggests that linguistic differences may impact educational access for AAE-speaking students. These, and other implications, are discussed.

Keywords

African American English comprehension educational equity tense morphology

In the United States, a much higher proportion of African American than European American children perform at ‘below basic’ at all grade levels (National Assessment of Educational Progress, 2009). Researchers have highlighted a number of factors that contribute to this performance difference, including racism and stigma (Steele & Aronson, 1995), cultural differences (Fagundes, Haynes, Haak, & Moran, 1998), and poverty or low SES (Brookes-Gunn & Duncan, 1997). Another potential factor affecting academic performance is language variety (Craig & Washington, 1994; Craig, Connor, & Washington, 2003; Labov, 1972; Rickford & Rickford, 1995); if a child has difficulty understanding the language of the classroom and/or test, he or she will be at a disadvantage compared to peers who do. Although this is typically thought of with respect to children who are English language learners, it may also be a factor for children whose home language is a non-mainstream variety of English, such as African American English (AAE).

AAE is a rule-governed and systematic variety of English spoken by many children entering schools in the United States (Craig, Thompson, Washington, & Potter, 2003; Craig & Washington, 2004). The primary variety of English used in mainstream American classrooms, however, is Standard American English (SAE). While AAE and SAE share many features, there are also systematic differences (Ball, 1994; Craig & Washington, 2004; Fasold & Wolfram, 1970; Green, 2002a, 2002b; Labov, 1972; Rickford, 1999; Torrey, 1972; Washington & Craig, 2002). Given the overt similarities, one might assume that AAE and SAE are mutually intelligible, and to some degree they are. The differences between the two, however, can give rise to subtle misinterpretations that may go unnoticed by speakers of either AAE or SAE and therefore result in only partial understanding, a phenomenon referred to as pseudo-comprehension (Stewart, unpublished remarks, cited in Roy, 1987). With respect to AAE and SAE, tense morphology is a prime candidate for pseudo-comprehension. Tense and aspect are often conveyed through different morphemes in the two varieties, however, the lexical items being modified (i.e., verbs) are more or less shared. Thus, because only a few morphemes in the utterance differ, one can potentially understand the main content of an utterance, but misunderstand when or how it occurred.

This situation is further complicated by at least two additional factors. Typically, discourse contains other spoken cues to tense (e.g., lexical cues such as yesterday). Thus, listeners could rely on these other cues to temporally situate the discourse, relieving the necessity to correctly interpret tense morphology. In addition, in classroom contexts, familiar routines and non-linguistic cues can provide the listener with additional information to guide responses and behavior, further masking the fact that the speech itself may not be completely (or correctly) interpreted (Miller & Paul, 1995). Notably, such cues are generally absent in formal tests and assessments.

Thus, linguistic differences between home and classroom language have the potential to impact the academic performance of children who are speakers of non-mainstream varieties of English. In order to demonstrate this potential relationship, controlled studies are necessary to test how specific linguistic differences between AAE and SAE affect the comprehension of SAE. If AAE-speakers’ comprehension is indeed affected, this would suggest that specific linguistic differences can impact academic performance. Moreover, if the task is devoid of contextual and non-linguistic support, this would further suggest a possible independent contribution of linguistic differences on school failure that may not be evident in the day-to-day lives of AAE-speaking children in the classroom. Thus, the present study examines how school-aged AAE-speakers comprehend SAE tense morphology in the absence of other contextual cues, as compared to their SAE-speaking peers.

Tense markers in SAE

Here we describe the SAE tense morphemes examined in the present study, and how they function (or not) in AAE. Tense morphemes were selected primarily because they can differ greatly between the two varieties. Because the focus of the present study is the comprehension of SAE by AAE-speakers, we do not directly discuss the tense/aspect system of AAE, which makes more numerous and fine-grained distinctions than SAE, often using different morphemes (see Fasold & Wolfram, 1970; Green, 2002a; Labov, 1972; Rickford, 1999).

In SAE, –ed is the principle past tense morpheme (e.g., he played). Although –ed can occur in AAE, it is not obligatory and does not seem to mark past tense (Fasold & Wolfram, 1970; Labov, 1972). Similarly, SAE obligatorily requires 3rd person present –s to indicate subject–verb agreement (number) and tense/aspect (e.g., he plays), however, it is only sometimes produced by AAE-speakers (Labov, 1972; Torrey, 1972), and when it occurs, does not seem to function as a grammatical marker (Fasold & Wolfram, 1970). Note that this is not a general issue with –s; plural –s on nouns functions similarly in both varieties (Ball, 1994; Fasold & Wolfram, 1970; Green, 2002b; Labov, 1972; Torrey, 1972). In SAE, future can be indicated by a free standing word (i.e., will), but in casual conversation it is often contracted to –’ll (e.g., he’ll play), and it is this contracted form which is different in AAE. Although AAE marks the future, it generally uses the full form will and derived forms of going to do so (Green, 2002a; Labov, 1972).

Previous studies of AAE speakers’ comprehension of SAE¹

Existing studies of AAE-speaking children’s comprehension of SAE offer conflicting evidence, although the majority find that comprehension is negatively affected. In particular, it appears that specific differences between the AAE and SAE linguistic systems lead to impaired comprehension. For example, de Villiers and Johnson (2007) used a picture-choice task to investigate whether 4- to 6-year-old AAE- and SAE-speakers could use SAE 3rd person present –s as a cue to number, tense/aspect, and to differentiate between verbs and noun-compounds. While SAE-speakers showed a significant age-related increase in their general understanding of SAE 3rd person present –s, the AAE-speakers showed chance performance, regardless of age. Their finding is supported by work by Ball (1994), Johnson (2005), and Torrey (1972), who report similar results for 3rd person present –s.

Difficulty is not limited to –s, however; Labov (1972) reports that teenage AAE-speakers showed no sensitivity to the meanings indexed by SAE past tense –ed during sentence correction and reading tests. Interestingly, speaking rate may further impact comprehension of SAE: as speaking rate increases, comprehension, as indexed by a picture-choice task, was found to decrease for 6- to 9-year-old AAE-speaking children, but not their SAE-speaking peers (Nelson & McRoskey, 1978). Related, research has found a significant negative correlation between children’s production of AAE and outcomes on standardized tests using SAE (Craig, Thompson, Washington, & Potter, 2004; Craig & Washington, 2004). While this latter study does not speak directly to comprehension, it is possible, indeed likely, that comprehension difficulties underlie the relationship. In sum, these findings strongly suggest that linguistic differences between AAE and SAE can impair the comprehension of SAE in AAE-speaking children.

Other studies, however, have failed to find differences. For example, Hall, Turner, and Russell (1973) found that 6- and 10-year-old AAE-speaking boys interpreted SAE past tense –ed and 3rd person present –s in similar ways as their SAE-speaking peers. Perhaps even more striking, several studies have found that the linguistic system used in the study (AAE or SAE) does not seem to influence comprehension of SAE test items (see e.g., Johnson & Simons, 1973; Marwit & Neumann, 1974), or instructions (Hall & Freedle, 1973). This suggests that the AAE-speaking children tested were equally competent at understanding AAE and SAE. Relatedly, recent research suggests that degree of AAE usage does not influence performance on SAE morphological awareness tasks, whereas literacy skills do (Apel & Thomas-Tate, 2009). SAE literacy skills, however, are found to be negatively related to AAE usage (see e.g., Charity, Scarborough, & Griffin, 2004; Connor & Craig, 2006; Craig & Washington, 2004). Overall then, prior research provides conflicting evidence as to whether AAE-speaking children’s comprehension of SAE is impacted.

Although some of the discrepancies may be due to differences between the studies in the structures or morphemes examined, there are methodological differences as well, some of which make it difficult to draw firm conclusions. First, not all previous studies have included an independent measure of language use, equating ethnicity with linguistic system (e.g., Hall et al., 1973; Hall & Freedle, 1973). However, not every African American speaks AAE, nor is every AAE-speaker African American (Nelson & McRoskey, 1978; Rickford, 1999). Moreover, the level of exposure to AAE and SAE may differ across individuals and communities creating a heterogeneous group both in terms of language use and exposure type (Green, 2002b; Roy, 1987). Thus, it is not always clear that the African American children tested actually used AAE as their primary language variety. Second, the comprehension tasks have not always been designed such that the form under investigation was critical for correct interpretation, or with sensitivity to the AAE grammatical system and the differences between AAE and SAE. These methodological factors could influence results such that AAE-speakers’ comprehension of SAE would appear better than it actually is, at least when trying to extend the results to the morphemes we are interested in: if the child were actually an SAE-speaker, then the forms are part of his or her native variety and so should be interpretable, and if the AAE-speaking child can interpret the sentence using other, shared, forms, his or her comprehension should not be impaired relative to an SAE-speaker.

The present study

Our study was designed to examine how young AAE-speakers comprehend specific SAE morphemes while addressing some of the limitations of the previous work. First, we confirmed each individual’s linguistic group assignment via a production task. Second, we assessed general language development (apart from morphology) and collected non-verbal IQ estimates to ensure that there were no general differences in language or cognitive abilities between the groups. Third, in order to rule out overall comprehension problems, we compared performance on sentences where we would expect comprehension difficulties with sentences where we would not, and used stimuli that did not allow for correct interpretation using other cues. Lastly, to reduce linguistic inhibition or accommodation (Rickford, 1999) and hypercorrection (Fasold & Wolfram, 1970; Labov, 1972), participants interacted with an experimenter who spoke both AAE and SAE natively.

We used a picture-choice task to examine participants’ comprehension of SAE tense morphology (past tense –ed, 3rd person present –s, and future contracted –’ll). In the test sentences, SAE tense morphology provided the only cues for correct comprehension. Thus, only those children who are sensitive to these morphemes should show successful performance. In addition, while much recent research has focused on how young AAE-speakers interpret 3rd person present –s (e.g., de Villiers & Johnson, 2007; Johnson, 2005; Johnson, de Villiers, & Seymour, 2005), less research has focused on how other SAE tense morphemes are interpreted. The present study therefore investigates how AAE-speaking children interpret not just 3rd person present –s, but SAE tense morphology more broadly.

Two types of control items were also included. One type contained overt temporal words, such as yesterday. Previous studies have shown that such words are acquired by preschool age (Pawlak, Oehlrich, & Weist, 2006), and so should be easily understood by our participants. The second type contained either lexical cues to number or plural –s. Because these cues are shared by AAE and SAE, all children should show comparable performance on the control items.

Participants were 1st and 2nd grade AAE- and SAE-speakers. These grades were selected given our interest in language variety and school performance: 1st grade is when formal assessment using SAE (e.g., classroom performance, standardized tests) often begins. Second graders were included because they have additional exposure to SAE relative to the 1st graders that could remedy earlier comprehension differences.

Methods

Participants

Twenty-three 1st and 22 2nd graders participated in this study. One additional 1st grade SAE-speaker failed the training task (see below) and so did not complete the study.

Each child was identified as an AAE- or SAE-speaker during an informal pre-experiment interaction with a researcher who spoke AAE and SAE natively. These initial assessments were confirmed using a production task, described below. There were 11 1st grade AAE-speakers (3 males; 8 females, M_age = 6;3, age range 6;1–6;6), 12 1st grade SAE-speakers (4 male; 8 female, M_age = 6;3, age range 6;0–6;6), 11 2nd grade AAE-speakers (3 male; 8 female, M_age = 7;2, age range 6;11–7;4), and 11 2nd grade SAE-speakers (4 male; 7 female, M_age = 7;4, age range 7;0–7;6). The AAE-speaking group comprised 22 African American children, the SAE-speaking group, 20 European American and 3 African American children.

Children were recruited from two public schools in the San Francisco Bay Area and received a toy for participating. Thirty-one children, 22 AAE-speakers and 9 SAE-speakers, came from one school. The other 14 children, all SAE speakers, came from the other. Prior to participation, teachers filled out a language background questionnaire for each child. The teachers identified all children as typically developing with no history of hearing or language problems. Interestingly, the teachers identified all students as only speaking SAE and rated all students equally, and very high, on the production and comprehension of SAE. Teacher ratings relating to language variety were, therefore, not predictive of actual performance, a point we return to in the discussion.

Procedure

Consent forms were sent home with children from participating classrooms. Only children with parental consent were asked to take part. Children were tested individually at their school in one 35–40 minute session. Prior to participation, the study was explained to the child and he or she was asked to assent. Only assenting children continued. The children then completed two language production tasks, the comprehension task and a non-verbal IQ estimate, in that order. Training was conducted by one of two African American experimenters who self-identified as a native speaker of AAE and SAE. These experimenters were familiar with and comfortable using the pronunciation, vocabulary, and grammar of both varieties, and training was conducted in each child’s native language variety. This established rapport with the children and served to indirectly acknowledge and permit the use of either variety during testing. All sentences in the comprehension task were in SAE only, and were administered by an animal puppet displayed on a stage, hiding the second (European American) experimenter who controlled it. The experimenter spoke slowly and deliberately so that all relevant morphology was clearly perceptible.

Language production tasks

Sentence repetition

The initial language assessment was confirmed using a sentence repetition task adapted from Piestrup (1973). This task was selected because it was originally developed and used with AAE-speaking children from the San Francisco Bay Area, the same area (and thus dialect) that our participants were recruited from. Participants heard a sentence in SAE and were asked to repeat it. Sentences contained features that contrast in the two varieties. AAE-speakers generally change such sentences to be more congruent with AAE (Charity et al., 2004; Piestrup, 1973), while SAE-speakers usually repeat the sentences verbatim. Productions were audio-taped and later transcribed for analysis. See Appendix A for the sentences used in this task.

Elicited production

Children saw four related pictures and were asked to tell a story describing what they saw. Narratives were audio-taped and later transcribed and analyzed for overall level of language development.

Comprehension task

Children were shown panoramas of pictures that depicted both male and female characters of different ethnicities engaged in non-stereotyped activities (see e.g., Figure 1). While looking at the panoramas the child heard a sentence spoken in SAE by the puppet. Sentences were produced such that no sounds necessary for correct comprehension were obscured by following sounds. The child’s task was to select the picture from the panorama that best matched the sentence they heard. The panoramas were constructed (and paired) such that only one picture matched the content of the sentence entirely. Participants’ responses were hand-scored at the time of presentation.

Figure 1.

Example Time Block panoramas.

Stimuli were arranged into three blocks of trials, Time Block 1, Number Block 1, and Time Block 2. For the Time Blocks the stimuli consisted of two panoramas of three picture frames each in which the same character was engaged in different actions, as in Figure 1. For each panorama, frames 1 and 3 showed different actions (e.g., reading and walking). The actions in frames 1 and 3 of panorama 1 always corresponded to the actions in frames 3 and 1 of panorama 2, respectively. Frame 2 always showed sleeping, which served as the temporal boundary marker that identified the actions in the 1st and 3rd frames as past, present, or future. Thus, the two panoramas showed the same actions, but occurring at different points in time in each. In this way, sentences could not be correctly interpreted using only the verb (since two frames always depicted the same action) or temporal information (since two frames always depicted the same time-point).

Children received explicit training in how to utilize ‘sleeping’ as a temporal boundary marker separately for each Time Block. For the past/present block, participants were told the actions in frame 1 occurred yesterday (past) and the actions in frame 3 occurred today (present) because ‘sleeping (frame 2) always separates yesterday (frame 1) from today (frame 3).’ The present/future contrasts were in a separate block and here children heard the same instructions except that past and present were replaced by present and future respectively. Although this manipulation may seem difficult, all children understood the task as evidenced by their performance on the control items.

There were three types of sentences in the Time Blocks: (1) control sentences containing overt temporal markers (e.g., Yesterday she walked from the library), (2) test sentences that only contained tense morphology (e.g., She walked from the library), and (3) filler sentences. Note that correct comprehension of the test sentences is only possible if the child correctly interprets the morphological cues. This contrasts with the control sentences; although the control sentences also included obligatory SAE tense morphology, they could always be interpreted using just the overt lexical temporal markers and not the morphological cues. The control sentences occurred at the beginning of each Time Block to ensure that participants understood the prior training. Only participants who correctly answered two out of three control sentences continued to the other sentences. If a participant failed, they were retrained; if they failed again, they were excluded from the study. (Only one child failed twice.) Two 1st grade SAE-speakers and one 1st grade AAE-speaker were retrained and passed the second time. The performance of these children did not differ from those who succeeded the first time.

In Number Block trials participants saw two pictures. One showed an action involving one object and the other showed the same action with multiple objects (e.g., holding one vs. many cards). Participants heard sentences that contained plural –s (plural –s only trials, e.g., She has cards) or lexical cues to number (lexical number trials, e.g., She has some cards). This block provided an important additional control condition as plural –s is shared by AAE and SAE: if the AAE-speaking children have difficulty with morphology in general, their performance on the plural –s and tense morphology trials should be similar; however, if the difficulty is only with morphology that is not part of their native language variety, AAE-speaking children should perform just as well as the SAE-speaking children on plural –s.

Each child heard 14 test (four –ed, six –s, four –’ll), 10 control (six time, four number), and nine filler sentences. Within each Time Block, children first received three control sentences, followed by the test and filler sentences. Sentences were arranged so that no more than two sentences containing the same contrast appeared in a row. In addition the target frames never appeared in the same place more than twice in a row. There were 17 sentences in the past/present block (three control, four –ed, four –s, six fillers), 12 in the present/future block (three control, four –’ll, two –s, three fillers), and four in the Number Block (two lexical, two plural –s). The two Time Blocks were always separated by the Number Block, and their order (past/present first, present/future first) was counterbalanced. To ensure that performance was not simply due to vocabulary, we constructed two different sentence lists that were counterbalanced across participants. See Appendix B for the control and test sentences.

Non-verbal IQ tasks

We administered the picture completion subtest of the Wechsler Intelligence Scale for Children, 3rd Edition (WISC-III), and the cube design subtest of the Universal Nonverbal Intelligence Test (UNIT) to obtain a non-verbal IQ estimate. For the picture completion subtest, participants see pictures of objects/scenes with a missing element, and their task is to identify what is missing. For the cube design subtest, participants see abstract, geometric designs, and have to reconstruct the design using color-coded cubes. These subtests were chosen because they have high correlations with full-scale IQ scores from their respective tests (see UNIT, 1996; WISC-III, 1991). Full-scale IQ tests were not administered due to time limits imposed by schools.

Results

Sentence repetition

Children heard sentences spoken in SAE and were asked to repeat them. The sentences contained features that contrast in AAE and SAE. A native speaker of both varieties checked the initial transcriptions for accuracy at the word level. Intercoder reliability exceeded 99%. Transcriptions were then coded for phonological (e.g., My friend has a little kitten changed to My fren has a lil’ kien) and morphosyntactic (e.g., Charles said he’d be in the class after lunch changed to Charles say he in the class after lunch) differences from the target SAE sentence.

Table 1 shows the mean number of alterations produced by participants. Children identified as AAE-speakers produced significantly more alterations of both types than children identified as SAE-speakers (phonological: F_(1,41) = 62.30, p < .001, $η_{p}^{2}$ = .603; morphosyntactic: F_(1,41) = 90.58, p < .001, $η_{p}^{2}$ = .688). There were no significant differences between the grades (phonological: F_(1,41) = 1.80, p = .188, $η_{p}^{2}$ = .042; morphosyntactic: F_(1,41) = 1.63, p = .209, $η_{p}^{2}$ = .038), and no significant interactions between linguistic group and grade (phonological: F_(1,41) = 0.20, p = .657, $η_{p}^{2}$ = .005; morphosyntactic: F_(1,41) = 0.40, p = .532, $η_{p}^{2}$ = .010). Moreover, no individual identified as an AAE-speaker was within two standard deviations of the respective SAE comparison group’s mean total (combined phonological and morphosyntactic), confirming the initial assessments.²

Table 1.

Mean number of phonological and morphosyntactic alterations by linguistic group and grade.

Linguistic group	Grade	Phonological	Morphosyntactic
AAE	1	3.27 (0.47)	4.91 (0.58)
	2	3.00 (0.23)	4.64 (0.49)
SAE	1	1.00 (0.27)	1.17 (0.32)
	2	0.45 (0.16)	0.36 (0.24)

Note: Values enclosed in parentheses represent standard error.

Elicited production

Children saw four related pictures and made up a story describing them. These narratives were transcribed using the segmentation criteria for communication units (C-units), defined as an independent clause and its modifiers (see Craig et al., 2003). C-units were transcribed into Systematic Analysis of Language Transcripts files (Miller & Chapman, 2003–7). Following Craig et al. (2003), the samples were scored for average C-unit lengths in words, syntactic complexity (based on Craig & Washington, 1994), and expressive vocabulary (number of different words used). We also calculated the type/token ratio in the narratives, a measure of semantic complexity. Scores are shown in Table 2.

Table 2.

Mean systematic analysis of language transcript measures by linguistic group and grade.

	Linguistic group
	AAE		SAE
Measurement	1st grade	2nd grade	1st grade	2nd grade
C-unit length	8.48 (0.94)	9.75 (0.62)	8.76 (0.73)	9.68 (0.91)
Syntactic complexity	49.90 (13.85)	54.03 (13.88)	55.32 (9.27)	52.27 (9.13)
Expressive vocabulary	19.45 (2.26)	28.64 (2.54)	19.75 (0.79)	27.00 (1.93)
Semantic complexity	0.65 (0.03)	0.59 (0.03)	0.57 (0.02)	0.61 (0.03)

Note: Values enclosed in parentheses represent standard error.

Separate ANOVAs were conducted for C-unit length, syntactic complexity, expressive vocabulary, and semantic complexity with linguistic group assignment and grade as between-subjects factors. The AAE- and SAE-speakers demonstrated similar performances on these measures: there were no significant differences between the linguistic groups (C-unit length: F_(1,41) = 0.02, p = .896, $η_{p}^{2}$ = .000; syntactic complexity: F_(1,41) = 0.03, p = .876, $η_{p}^{2}$ = .001; expressive vocabulary: F_(1,41) = 0.12, p = .734, $η_{p}^{2}$ = .003; semantic complexity: F_(1,41) = 0.81, p = .374, $η_{p}^{2}$ = .019). There were also no significant differences between the grades for C-unit length (F_(1,41) = 1.86, p = .180, $η_{p}^{2}$ = .043), syntactic complexity (F_(1,41) = 0.00, p = .963, $η_{p}^{2}$ = .000), and semantic complexity (F_(1,41) = 0.09, p = .763, $η_{p}^{2}$ = .002), however, 2nd graders produced a significantly greater number of different words than did the 1st graders (F_(1,41) = 17.61, p < .0001, $η_{p}^{2}$ = .300). Importantly, there were no significant interactions between linguistic group and grade on any of these measures (C-unit length: F_(1,41) = 0.05, p = .830, $η_{p}^{2}$ = .001; syntactic complexity: F_(1,41) = 0.09, p = .760, $η_{p}^{2}$ = .002; expressive vocabulary: F_(1,41) = 0.24, p = .624, $η_{p}^{2}$ = .006; semantic complexity: F_(1,41) = 3.41, p = .072, $η_{p}^{2}$ = .077). Thus, the two groups were similar in terms of general language development.

Non-verbal IQ

Individual raw scores were converted into standard scores, shown in Table 3. There were no significant differences between linguistic groups (F_(1,41) = 0.03, p = .867, $η_{p}^{2}$ = .001) or grades (F_(1,41) = 0.08, p = .782, $η_{p}^{2}$ = .002), and no significant interaction (F_(1,41) = 0.13, p = .725, $η_{p}^{2}$ = .003), indicating that the children were similar in non-verbal IQ.

Table 3.

Mean non-verbal IQ estimate by linguistic group and grade.

Linguistic group	Grade	IQ estimate
AAE	1	101.83 (1.18)
	2	98.96 (1.38)
SAE	1	99.46 (1.61)
	2	99.80 (1.17)

Note: Values enclosed in parentheses represent standard error.

Comprehension task

Participants were asked to select the picture that best matched a spoken SAE sentence. Responses were scored correct if the participant chose the picture that corresponded to both the correct time and action. A second coder checked these scores for accuracy from the videotape. Accuracy exceeded 99% and any discrepancies were resolved using the videotaped responses.³ Results are discussed separately for control and test items.

Control items

Figure 2 (top) shows the mean percent correct on the control items by linguistic group and grade. In the Time Block, two of the four non-sleep pictures match the verb, and in the Number Block one of the two pictures matched the number information. Thus chance performance, indicated by a dashed line, is 50% for both. Error bars represent standard error.

Figure 2.

Mean percent correct on control (top) and test (bottom) items by grade and language variety.

Time control items contained shared temporal words and, as expected, all children showed similar performance on these items. There were no significant main effects for linguistic group (F _(1,41) = 2.99, p = .091, $η_{p}^{2}$ = .068), grade (F_(1,41) = 2.27, p = .140, $η_{p}^{2}$ = .052), or item type (F_(2,82) = 0.14, p = .866, $η_{p}^{2}$ = .004). There were also no significant interactions: linguistic group and grade (F_(1,41) = 0.18, p = .672, $η_{p}^{2}$ = .004), item type and linguistic group (F_(2,82) = 0.14, p = .866, $η_{p}^{2}$ = .004), item type and grade (F_(2,82) = 1.21, p = .303, $η_{p}^{2}$ = .029), and item type, linguistic group, and grade (F_(2,82) = .73, p = .485, $η_{p}^{2}$ = .018). Next, we investigated whether the responses to the time control items were different from chance. Because no significant effects were found, we used the combined responses from all participants in the analyses. All three times differed significantly from chance: past (t₍₄₄₎ = 18.76, p < .001, $η_{p}^{2}$ = .889), present (t₍₄₄₎ = 16.91, p < .001, $η_{p}^{2}$ = .867), and future (t₍₄₄₎ = 15.46, p < .001, $η_{p}^{2}$ = .845).

All participants also performed well on the number control items (Figure 2, top), which contained shared lexical or morphological (plural –s) cues. Again, there were no significant main effects: linguistic group (F_(1,41) = 0.12, p = .727, $η_{p}^{2}$ = .003), grade (F_(1,41) = 1.29, p = .262, $η_{p}^{2}$ = .031), or item type (F_(1,41) = 1.08, p = .305, $η_{p}^{2}$ = .026). There were also no significant interactions: item type and linguistic group (F_(1,41) = 0.96, p = .759, $η_{p}^{2}$ = .002), item type and grade (F_(1,41) = 0.97, p = .331, $η_{p}^{2}$ = .023), linguistic group and grade (F_(1,41) = 0.02, p = .886, $η_{p}^{2}$ = .001), and item type, grade, and linguistic group (F_(1,41) = 0.97, p = .331, $η_{p}^{2}$ = .023). We then investigated whether the responses to the number control items differed from chance, again using the combined responses. Both differed significantly from chance: lexical number (t₍₄₄₎ = 13.27, p < .001, $η_{p}^{2}$ = .800), plural –s (t₍₄₄₎ = 16.91, p < .001, $η_{p}^{2}$ = .867).

The results from the control items therefore indicate that participants (1) could perform the task, and (2) interpreted shared lexical information and grammatical morphology in a similar way.

Test items

Test items contained only SAE morphology (–ed, –s, and –’ll) as a cue to tense.⁴ Chance performance again is 50%. Figure 2 (bottom) shows the mean percent correct for the test items by grade and linguistic variety. Here the AAE- and SAE-speakers differed dramatically in their performance. There was a significant main effect of linguistic group (F_(1,41) = 49.12, p < .0001, $η_{p}^{2}$ = .545) and a marginally significant effect of grade (F_(1,41) = 3.98, p = .053, $η_{p}^{2}$ = .089), but no significant effect of test item type (F_(2,82) = 0.68, p = .510, $η_{p}^{2}$ = .016). There was also a significant interaction between linguistic group and grade (F_(1,41) = 5.34, p = .026, $η_{p}^{2}$ = .115), a marginally significant interaction between linguistic group and test item type (F_(2,82) = 2.99, p = .056, $η_{p}^{2}$ = .068), but no significant interactions between grade and test item type (F_(2,82) = 1.22, p = .300, $η_{p}^{2}$ = .029), or linguistic group, grade, and test item type (F_(2,82) = 0.43, p = .653, $η_{p}^{2}$ = .010). Measures of effect size ( $η_{p}^{2}$ ) indicate that linguistic group assignment explained the most variance in the sample, more so than grade or test item type.

The significant interaction between linguistic group and grade appears to be driven by the better performance of the 2nd grade SAE-speakers relative to the 1st grade SAE-speakers, a pattern not true for the AAE-speaking children. To test this possibility, we performed separate ANOVAs for each linguistic group. No significant effects were found for the AAE-speakers: grade (F_(1,20) = 0.04, p = .843, $η_{p}^{2}$ = .002), test item type (F_(2,40) = 0.52, p = .598, $η_{p}^{2}$ = .025), interaction of grade and test item type (F_(2,40) = 0.11, p = .897, $η_{p}^{2}$ = .005). In contrast, for the SAE-speakers, there was a significant main effect of grade (F_(1,21) = 11.58, p = .003, $η_{p}^{2}$ = .355) and test item type (F_(2,42) = 4.80, p = .013, $η_{p}^{2}$ = .186). However, there was no significant interaction between grade and test item type (F_(2,42) = 2.45, p = .099, $η_{p}^{2}$ = .104). Thus, the 2nd grade SAE-speakers generally have higher performance on the test items than their 1st grade counterparts, something not true of the AAE-speakers. However, these differences are small and not significant in all but one case (–ed: F_(1,22) = 0.81, p = .378, $η_{p}^{2}$ = .037; –’ll: F_(1,22) = 3.85, p = .063, $η_{p}^{2}$ = .155; –s: F_(1,22) = 12.01, p = .002, $η_{p}^{2}$ = .364). It thus appears that the significant interaction between linguistic group and grade is largely driven by the 1st grade SAE-speakers’ relatively poorer performance on the test items containing –s. For further discussion of this particular effect see Beyer and Hudson Kam (2009) and Johnson et al. (2005).

The significant main effect of linguistic group shows that regardless of grade or test item type, the AAE-speakers performed worse than the SAE-speakers. We therefore examined whether the AAE-speakers’ performance differed from chance. (As grade was not significant, the data were combined.) It did not, for any of the morphemes tested: –ed (t₍₂₁₎ = 0.55, p = .589, $η_{p}^{2}$ = .014), –’ll (t₍₂₁₎ = −0.37, p = .715, $η_{p}^{2}$ = .006), and –s (t₍₂₁₎ = 1.40, p = .176, $η_{p}^{2}$ = .085).

Discussion

Because SAE is the primary variety of English used in mainstream American classrooms, the ability to understand SAE is crucial for educational success. However, many children begin school speaking a different variety of English, such as AAE. Although structural differences between AAE and SAE have been documented and described, it remains unclear how these differences affect comprehension, especially in children entering school. The present study addressed this, and examined how 1st and 2nd grade AAE-speakers interpret SAE. In particular, we focused on past tense –ed, 3rd person present –s, and future contracted –’ll, SAE morphemes that do not regularly appear in AAE. We anticipated that the AAE-speakers would fail to interpret these morphemes, unlike their SAE-speaking peers.

The present results confirm our prediction: the global comprehension patterns for the test items accord with differences between the children’s native language varieties. Performance on shared lexical and morphological items showed a very different pattern. All children performed similarly well on these control items, suggesting that the lower performance by the AAE-speakers on the test items is not due to task difficulty or an inability to interpret morphology. We also ruled out general differences in language ability and non-verbal IQ as alternative explanations for our pattern of results. Moreover, these comprehension differences do not disappear during the first two years of schooling. While the learning of SAE morphology by AAE-speaking children may be ongoing during this time period, these findings suggest that mere exposure to SAE is insufficient to support the complete learning of these specific SAE morphemes, at least by 2nd grade. This accords with a great deal of research done on the acquisition of classroom English by child English language learners (e.g., Fillmore, 1982, 1991).

The present results (measuring the comprehension of SAE) are different from the trends found for the production of AAE, where two main shifts have been found. The first is a decrease in the number (but not types) of AAE morphosyntactic features between kindergarten and 1st grade (Craig & Washington, 2004). The second is a decrease in the number of AAE phonological features between 2nd and 3rd grade (Craig, Thompson, et al., 2003). Although the degree of decrease of AAE features in production appears to be positively correlated with reading achievement (Craig & Washington, 2004), this does not directly inform when (or how) AAE-speaking children become sensitive to the meaning of (non-shared) SAE morphemes, and how this is affected by schooling. For example, even though the 2nd graders in our study did not show any sensitivity to SAE tense morphology during comprehension, it is quite possible that over time AAE-speaking children do learn these morphemes via exposure.

However, even if they are learned by a later grade, a substantial amount of time will have been spent at a disadvantage, and at a particularly important stage of the educational process. Data indicate that children who perform well in 1st grade, for instance, are 1.5–2 times more likely to graduate from high school than those who perform more poorly, and that the relationship between performance in 1st grade and graduation is stronger than that between performance in later grades and graduation rates (Ensminger & Slusarcick, 1992). Our results therefore strongly support the notion that like English language learners, young AAE-speaking children could benefit from direct instruction. We are not making any claims about the value or status of AAE, and by no means are we suggesting that AAE is deficient as a linguistic system. Rather we are asserting that, since performance in school is highly dependent on competence in SAE, any student whose home language background is different should receive language-based intervention, although our results do not speak to the question of which teaching strategies would be best (see also Green, 2002b; Roy, 1987).

It is worth noting that teachers may not always identify language variety as a potential problem for their AAE-speaking students (Roy, 1987), thus appropriate language-based interventions may not be offered to students who are otherwise quite capable of learning. This lack of appropriate language-based intervention for students who speak non-mainstream varieties of English, therefore, may unnecessarily impede academic success. Our data clearly demonstrate the potential for this to happen: the children’s teachers did not identify their students as AAE-speakers on the language questionnaire, and rated the comprehension and production of SAE very high for all students. These ratings are in direct conflict with our results. A likely explanation for this is the setting in which teachers typically interact with their students. Specifically, in settings with a great deal of routine, such as classrooms, a person may act in ways which suggest that he or she fully understands due to knowledge of the context, and expected behavior in that context (Miller & Paul, 1995). Moreover, teachers may frequently use shared forms, such as yesterday, which children can rely on to interpret the sentence as a whole, without interpreting the SAE morphology. Unfortunately, many of these cues are not available on written tests, an area where many linguistic minority students do particularly poorly (National Assessment of Educational Progress, 2009). If indeed the teachers’ ratings reflect children’s abilities to perform successfully via the use of contextual and pragmatic knowledge, we would expect to see greater disparities between AAE- and SAE-speakers on written vs. oral evaluations (see also Green, 2002b).

We do not mean to suggest that linguistic differences are the only cause of difficulties in school. Social factors such as cultural differences (Fagundes et al., 1998), as well as racism and stigma (Steele & Aronson, 1995) also affect the academic achievement of students, especially those who speak AAE. Moreover, poverty and low SES are well known to be negatively correlated with academic achievement (see e.g., Brookes-Gunn & Duncan, 1997), and these factors may be particularly relevant for AAE-speakers; twice as many African American children, when compared to majority children, are being raised in poverty (US Census Bureau, 2002). Although we did not collect SES information for individual children, it was the case that the AAE-speaking children generally came from neighborhoods with lower overall SES, as indicated by the proportion of students in their schools eligible for the federal free or reduced lunch program, as compared to the SAE-speakers. Differences in SES could therefore have influenced our findings. In order to rule out SES-related explanations as much as possible, we ensured that our participants were similar in terms of actual abilities, namely general language ability and IQ. Moreover, our participants only showed performance differences on precisely those items that are not shared by the two varieties, something that would not be predicted if SES were the main factor leading to comprehension differences.

Poverty and low SES do not just affect African American children; any child reared in such an environment may be negatively affected. Moreover, the pervasive school failure of African American students cuts across class lines (Ogbu, 2003). Thus, while poverty and SES are clearly important when considering the academic achievement of AAE-speaking children, they cannot entirely explain the academic achievement gap between AAE- and SAE-speaking children (Craig, Thompson, et al., 2003). Our results strongly suggest that linguistic differences are an important additional factor, as they should differentially impact the academic achievement of AAE- and SAE-speakers, regardless of poverty or SES background.

Our intent was to test the hypothesis that comprehension difficulties exist for young AAE-speaking children when encountering spoken SAE, and that the difficulties are highly dependent on the contextual support (or lack thereof) provided for meaning apprehension. This last point was intended to demonstrate how linguistic differences might affect performance in some contexts but not others, and in so doing, hide the fact that linguistic differences do play a role in the difficulties faced by AAE-speaking students. More research is needed to investigate the link between comprehension and scholastic performance more directly (see Terry, Hendrick, Evangelou, & Smith, 2010). This situation is not unique to the United States. In fact, in many societies, the educational achievement of children who do not speak the language variety used in school may be impaired due to comprehension difficulties (see e.g., Wheldall & Joseph, 1986). However, each situation will be unique in terms of the linguistic items at issue, given the particulars of the language varieties involved.

Clearly, no single factor in isolation is responsible for the academic difficulties experienced by many AAE-speaking students, and future research must continue to investigate the role social factors play, as well as how they interact with linguistic factors. In addition, future research must investigate how the comprehension of SAE grammatical features patterns across schooling – not just 1st and 2nd grade – in order to provide a more complete picture of how AAE-speaking students are affected by these linguistic differences. Such studies, with a larger sample size, could also address potential gender, SES, and cultural differences in the acquisition of SAE during schooling, as well as begin to link these comprehension difficulties to academic performance at an individual level. Future studies like these are necessary because in modern societies which value equality, like the United States, the potential for academic achievement should not be limited by linguistic background. We must therefore add to and refine our current understanding of how linguistic differences impact the academic performance of AAE-speaking students because as the present study clearly demonstrates, linguistic factors do have a role to play in the academic outcomes of AAE-speaking students, and therefore cannot be ignored.

Footnotes

Appendix A

Below are the directions and sentences for the sentence repetition task (adapted from Piestrup, 1973). The parts of these SAE sentences in bold text represent phonological and morphosyntactic features that contrast AAE and SAE.

Directions: I want you to listen carefully. I’m going to say some sentences to you. Then I want you to say them after me, one at a time. Are you ready? Ok, say the sentence after me.

Appendix

Appendix B

Below are the stimulus sentences (control and test) for List One and List Two.

	Item	List One	List Two
Control	Past	Yesterday he jogged from the store.	Yesterday he jogged from the store.
	Past	She played baseball yesterday.	She played baseball yesterday.
	Present	Today he carries an apple.	Today he carries an apple.
	Present	She eats pizza today.	She eats pizza today.
	Future	Tomorrow she’ll talk to the teacher.	Tomorrow she’ll talk to the teacher.
	Future	He’ll eat a sandwich tomorrow.	He’ll eat a sandwich tomorrow.
	Plural –s/Lexical number	She walks a dog.	She walks her dogs.
		She has cards.	She has some cards.
		She takes dogs for a walk.	She takes a dog for a walk.
		She has a card.	She has cards.
Test	Past tense –ed	He jogged to the store.	He walked to the store.
		She played baseball.	He played ball.
		She carried the book.	He carried the apple.
		She walked from the library.	He walked from school.
	3rd person present –s	He runs from school.	She walks from the library.
		He keeps the apple.	She keeps the book.
		He holds the ball.	She holds the baseball bat.
		She leaves the playground.	He leaves the store.
		She talks loudly to her teacher.	He talks with his friends.
		She eats pizza.	He eats a sandwich.
	Future contracted –’ll	He’ll be talking to his friends.	She’ll be talking with the teacher.
		After talking with his friends, he’ll eat a sandwich.	After eating a sandwich, he’ll talk to his friends.
		He’ll talk with his friends.	She’ll talk loudly to her teacher.
		He’ll eat a sandwich.	She’ll eat pizza

Acknowledgements

We would like to thank Amy Finn, Andrew Silva, James Edwards, and Kim Carter for help collecting and scoring data. We would also like to thank the children, their parents, their teachers, and their schools for their participation and help with the project.

Funding

This work was partially supported by a Diebold Fellowship and a University of California, Berkeley Psychology Department Research Grant awarded to Tim Beyer and a Hellman Family Faculty Fund research award to Carla Hudson Kam.

Notes

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First and second graders’ interpretation of Standard American English morphology across varieties of English

Abstract

Keywords

Tense markers in SAE

Previous studies of AAE speakers’ comprehension of SAE 1

The present study

Methods

Participants

Procedure

Language production tasks

Sentence repetition

Elicited production

Comprehension task

Non-verbal IQ tasks

Results

Sentence repetition

Elicited production

Non-verbal IQ

Comprehension task

Control items

Test items

Discussion

Footnotes

Appendix A

Appendix

Acknowledgements

Funding

Notes

References

Previous studies of AAE speakers’ comprehension of SAE¹