The entangled nature of first language learning, education, and literacyAbstractThe entangled relationship between first language acquisition, education, and literacy challenges conventional linguistic paradigms. This paper explores recent findings revealing the intricate interplay of these factors, particularly emphasizing the impact of education and literacy on grammatical knowledge. Drawing on studies conducted in diverse linguistic contexts, this paper argues against the universal applicability of conventional metrics such as the High Academic Attainment/Low Academic Attainment (HAA/LAA) cut-off to investigate the role of reading, advocating for a more nuanced understanding of linguistic development that considers local educational dynamics. Additionally, the paper discusses methodological challenges in studying illiterate populations and proposes alternative measures to capture the cumulative effects of language experience. Ultimately, the paper underscores the importance of interdisciplinary collaboration in developing inclusive research methodologies and educational interventions that address the diverse needs of learners worldwide. By embracing the complexities of language learning, education, and literacy, linguists can advance our understanding of human language capabilities and promote more equitable opportunities for linguistic development.IntroductionOver the last few decades, linguistics has assumed that native speakers of a language converge on the same grammatical knowledge uniformly and successfully (e.g., Chomsky 1965). However, recent studies show that individual differences in grammatical knowledge in L1 speakers is much more pervasive than it was postulated before (e.g., Dabrowska 2012). These studies show the impact of quality of input, which is modulated by education, literacy, and reading. Much of linguistics — for good or bad — has been influenced by what some call Chomsky’s hidden legacy (Christiansen & Chater 2016), and ignored effects that influence input quality.The idea that education may modulate linguistic knowledge is not surprising for several reasons — although it was and has been heavily ignored by many linguists, therefore unsurprising does not necessitate unimportant. Education is an amalgamation of opportunities for reading (becoming literate), and improving cognition. Formal education provides a stepping stone into becoming literate, and then sustaining these literacy practices (i.e., reading). It is now established that reading has a reciprocal effect on language and cognition, known as the Matthew Effect (e.g., Cunningham & Stanovich 1998) the more one reads, the better their cognition becomes, and the better their language skills become, which improve reading, which in turn improve cognition. This is a simplified way of putting it, the real entanglement may be more bidirectional than unidirectional. Secondly, a recent meta analysis shows that each year of schooling improves nonverbal IQ skills about 3 to 5 points on average (Ritchie et al. 2018).Speakers with fewer years of spent in formal education appear to demonstrate more individual differences in L1 grammatical knowledge and they appear to extract slightly different representations of constructions (both within and across groups). For instance, Dabrowska (1997) found that increasing number of years in formal education refine the use of syntactic cues in comprehending complex noun phrases in English. However, even highly educated speakers appear to differ in the way they extract generalizations from input (e.g., Gedik 2024, in prep).Several studies (e.g., Street & Dabrowska 2010; Street 2020) have used a high and low academic attainment cut (HAA and LAA, respectively) to investigate the relationship between native speakers’ performance on language tasks and education. These studies consider L1 speakers with an undergraduate degree or beyond to belong to the HAA group, and on average they have an average of 14-22 years of time spent in formal education. In contrast, LAA group consists of speakers with around 10 years of formal education. This is a considerable gap. In addition to this cut, emerging studies have also used illiterates, ex-literates, and literates as one continuum to investigate if education-related factors that were explained previously would interact with performance on language tasks. Emerging research shows that literacy may be an important predictor in predicting speakers’ performance on language tasks (Dabrowska et al. 2022, 2023; Gedik in prep).One question is the generalizibility of these “cuts” to other countries: does every country have the HAA/LAA cut? Similarly, there are countries with very low rates of illiteracy — and in WEIRD countries illiteracy is usually observed in individuals with mental disorders, rather than lack of opportunities of schooling. Many countries differ in the way they formalize education. In this paper, I will focus on Turkey as an example and argue why the HAA/LAA cut does not work for Turkey, then discuss its implications for other countries that may bear similarities. I will also argue that what we traditionally consider HAA (from a WEIRD perspective) in non-WEIRD or not-so-WEIRD countries (such as Turkey) may show as many individual differences as LAA speakers might in a traditionally WEIRD society. In doing so, I aim to invite linguists (and others in cognitive sciences) to carefully consider when using education-related measures and to take into account the local trends in education-related differences.Setting the scene: Higher Education in TurkeyIn Turkey, the education system is structured to provide a comprehensive framework for students from primary school through higher education. At the pinnacle of this system lies the university entrance exam, a crucial milestone that significantly impacts students’ educational trajectories and future career prospects. The university entrance exam, commonly known as the ”Yükseköğretim Kurumları Sınavı” (YKS), is a standardized test administered annually to assess students’ academic readiness for higher education. It is divided into two main components: the TYT (Turkish Proficiency Test) and the AYT (Academic Proficiency Test). The TYT evaluates students’ proficiency in Turkish language, mathematics, social sciences, and natural sciences, while the AYT focuses on more specialized subjects related to the student’s chosen field of study.One distinctive aspect of the Turkish education system is the tier system implemented within the university entrance exam. This tier system offers students the flexibility to choose between different exam tracks based on their academic strengths and career aspirations. The two main tiers are the standard track and the vocational track. In the standard track, students take the TYT and AYT exams, which cover a broad range of subjects and are designed for those seeking admission to traditional academic programs in universities. On the other hand, the vocational track caters to students interested in pursuing technical or vocational education. It includes additional exams tailored to specific fields such as health sciences, fine arts, or sports.Within Turkey’s tiered university entrance exam system, test takers not only face the challenge of achieving high scores but also navigating a complex ranking and admission process. After completing the exams, students are scored and ranked based on their performance relative to other test takers. However, admission to specific universities and majors is not solely determined by individual scores. Instead, each university and major sets its own minimum base score requirement.This minimum base score serves as a threshold that applicants must meet to be considered for admission to a particular university program. However, meeting this threshold does not guarantee admission. Since universities typically receive more applications than they have available spots, admission also depends on the ranking of the applicant relative to others who have applied to the same program. For instance, if two students apply to the same major at a university and one student has a higher score and ranking while listing that major as their preference, they will likely secure admission over the student with a lower score, even if they meet the minimum base score requirement, as every major also has maximum quotas.Furthermore, it is important to note that universities in Turkey vary significantly in terms of education quality and reputation. With over 200 universities across the country, there is a wide spectrum of academic offerings and institutional standards. Some universities are renowned for their research excellence, faculty expertise, and state-of-the-art facilities, while others may face challenges related to funding, infrastructure, or academic rigor. In short, where one studies significantly predicts the quality of education they will receive. This is not to say that WEIRD countries may not experience this, but it might take place to a smaller extent. Thus, while Turkey has around 8 million actively enrolled university students, of those 8 million, only very few may actually constitute a HAA group in the traditional sense.Why the HAA/LAA Cut May Not WorkFirst, I begin with evidence from a recent study conducted by Winckel & Dabrowska (2024) with L1 English speakers. These speakers were highly educated (15.5 years spent in formal education on average). When faced with very complex English sentences, print exposure – as measured by an author recognition task – over education (i.e., the number of years spent in formal education) was a more reliable variable predicting individual differences and accuracy in complex syntax comprehension (complex noun phrases, reduced relatives, X-is-difficult-answer, ditransitives). One potential criticism is that some of the constructions that Winckel and Dabrowska tested are too complex or do not constitute every day speech. However, relative clauses and ditransitives are used in spoken English frequently enough that they cannot be deemed peripheral. Therefore, measuring HAA speakers’ performance on more central or easier constructions would be interesting.One central grammatical construction is the Turkish aorist. It poses difficulties to children during acquisition since the aorist can be realized with multiple form-meaning pairings in various phonological environments. For instance, -Ar can occur with monosyllabic verbs, but -Ir can appear with monosyllabic sonorant ending verbs and multisyllabic verbs. In a recent study conducted by Gedik (2024) among a highly educated population (BA, MA, PhD holders from various universities in Ankara), print exposure accounted for more individual differences (over and above education operationalized as degree attained) in morphological productivity in nonce-verb conjugation with the Turkish aorist. Print exposure was measured using a self-reported reading questionnaire. This is quite interesting since the Turkish aorist is quite an integral part of Turkish grammar. That is, the aorist is used very frequently in spoken language as well as written language. Ideally HAA speakers should have performed at ceiling and homogenously on such a simple task that tested a central part of Turkish grammar. This shows that print exposure can influence the representation of certain constructions even among a highly educated population.In a separate study, Gedik (in prep) studies another central grammatical component of Turkish grammar: optional plural agreement. In Turkish, animate plural nouns may optionally be marked with the plural marker while speakers strongly disprefer marking the verb plural if the subject is plural inanimate. Gedik tested this construction using a timed force binary choice task in combination with print exposure and vocabulary size among 45 BA students from a high tier university. This time, print exposure was measured using an author recognition task, which is used widely in other linguistic studies investigating similar phenomena. The participants greatly differed in their use of the construction and print exposure as well as vocabulary size significantly predicted their preferences of using plural agreement. Once again, this shows that even among a highly educated sample at a good university in Turkey, reading may capture more differences than education.So the interim summary is that while in some countries, the HAA/LAA cut might work with certain constructions, in different parts of the world and in different languages (as well as constructions), print exposure might be a more viable option. This is because in such countries the number of years spent in formal education may not translate to a cumulative sustained experience with written materials. Importantly, author recognition tasks are not readily available for every language. In such circumstances, it might be useful to operationalize measuring print exposure with a self-reported reading questionnaire, although such questionnaires are known to be influenced by social desirability (e.g., Acheson et al. 2008, Gedik under review).There are instances where it is impossible to measure cumulative effects of experience with written language. After all, not every speaker is literate, or practices reading frequently. Among illiterate and ex-literate populations, print exposure cannot be utilized for obvious reasons. In such cases, there are several options that researchers have tried to approximate the cumulative effects of print exposure. These are group membership (literate, semi-literate, illiterate), 1-minute word reading (e.g., Simos et al. 2013), how long the person has received literacy instruction, and the number of years spent in formal education. Now, we discuss these measures in turn.Recently, several studies have investigated the relationship between acquiring literacy and its effects on morphosyntactic knowledge among L1 speakers. These studies (Dabrowska et al. 2022, 2023, Gedik in prep) revealed that group membership is a more reliable predictor of performance in tasks tapping into grammatical comprehension, even when compared to a continuous variable such words read correctly under 1 minute. This is quite odd since This is potentially due to the fact that the 1-minute word reading tasks measure two different constructs in different groups: in illiterate or semi-literate speakers, it potentially measures the speed at which orthographic decoding occurs whereas in literate speakers, it potentially measures the current reading fluency – which does not necessarily reflect the cumulative reading experience of a person. After all, Gedik (in prep) shows that some illiterate speakers who were learning to read overlapped in their performance of reading words with literate speakers. However, because performance in the 1-minute word reading task and group are very highly correlated (i.e., literate speakers could read more words on average than illiterate speakers), when group and the 1-minute word reading task are replaced in regression analyses, the results are highly comparable (Gedik, in prep).One important note with regard to group membership among illiterate speakers is that it is very difficult to detangle the effects of literacy, education, and cognition on grammatical performance. As Gedik (in prep) discusses, formal schooling teaches the L1 back to its native speakers, which improves cognition and language skills, which improve cognition, which improve language skills in turn and so on. Thus, specifying the cumulative effects of reading among illiterate speakers becomes extra difficult. Be that as it may, when working with illiterate speakers, group membership appears to capture more of the cumulative effects of exposure to written language, since it takes many years for grammar to be influenced by written language (cf. Dabrowska 2021).In this vein, it would make sense to include the other measures mentioned above (i.e., how long the person has received literacy instruction, and the number of years spent in formal education). However, there are several issues with these measures when working with illiterate populations. First, many illiterate speakers cannot attend school for various patriarchal or other reasons around the world. This renders using number of years in formal education useless since most participants would answer close to zero. Second, based on personal experience working with illiterate speakers and discussions with those who work with them, illiterate speakers may provide inaccurate or incomplete responses for how long they have received literacy instruction. This is because some speakers received on and off literacy instruction from friends and family, and some attend literacy classes on and off. Therefore, their answers are at best an approximation and hence do not provide to be reliable measures. Another issue with this measure is literate speakers from a certain age cohort will provide the same answer (i.e., age 7 for those above the age of 25).Where do we go from here?The exploration of the entangled nature of first language learning, education, and literacy unveils complexities that challenge traditional notions within linguistics. As evidenced by recent studies, the relationship between education, literacy, and grammatical knowledge is nuanced and multifaceted, with implications extending beyond theoretical frameworks to practical considerations in research methodology and pedagogy. Linguists need to be careful in selecting which measures to use in their studies and always consider both the population and the country specific conditions.The findings discussed above underscore the importance of reevaluating established paradigms within linguistics, particularly regarding the influence of education on linguistic competence. While conventional wisdom may suggest that higher levels of formal education equate to greater grammatical proficiency, emerging research suggests that this relationship is not straightforward. Instead, factors such as print exposure and literacy (group membership) play significant roles in shaping linguistic abilities, often surpassing the predictive power of education alone.Moreover, the context-specific nature of language acquisition and education becomes apparent when considering diverse linguistic communities and educational systems. The case of Turkey serves as a compelling example, highlighting the inadequacy of applying a universal HAA/LAA cut to measure linguistic proficiency. In non-WEIRD countries like Turkey, where educational trajectories are influenced by a myriad of socio-cultural factors and where the quality of education varies significantly among institutions, traditional metrics may fail to capture the complexities of linguistic development.Therefore, researchers must adopt a more nuanced approach to studying language and education, taking into account the unique socio-cultural contexts in which language acquisition occurs. This includes considering alternative measures of linguistic competence, such as print exposure and group membership based on literacy levels, which may better reflect the cumulative effects of language experience.Furthermore, the challenges posed by illiteracy highlight the need for innovative methodologies that accommodate diverse populations. Conventional measures such as years of formal education or duration of literacy instruction may prove inadequate for illiterate individuals, necessitating alternative approaches that account for their unique linguistic backgrounds and experiences.Moving forward, interdisciplinary collaboration between linguists, educators, and policymakers is crucial for developing inclusive research methodologies and educational interventions that address the diverse needs of learners worldwide. By embracing the entangled nature of language learning, education, and literacy, we can foster a deeper understanding of human language capabilities and promote more equitable opportunities for linguistic development.In conclusion, the entangled nature of first language learning, education, and literacy challenges conventional notions within linguistics and underscores the importance of considering diverse contexts and populations in research and practice. By embracing this complexity and adopting innovative approaches, we can advance our understanding of language acquisition and promote more inclusive educational practices globally.ReferencesAcheson, Daniel J., Justine B. Wells & Maryellen C. MacDonald. 2008. New and updated tests of print exposure and reading abilities in college students. Behavior Research Methods 40(1). 278–289.https://doi.org/10.3758/BRM.40.1.278.Chomsky, Noam. 1965. Aspects of the Theory of Syntax . MIT press.Christiansen, Morten H. & Nick Chater. 2016. 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