Letter Fluency in Malayalam-English Typical Bilinguals

Abstract

Introduction

I. INTRODUCTION

Speaking is a complex and unique ability of human beings that involves expressing thought in spoken words and phrases. A core operation in speech production is the preparation of words from a semantic base. According to Levelet (1990) during a conversation, an adult individual produces approximately two to three words per second from a huge repository or mental dictionary known as mental lexicon.

Word retrieval is core to language production and some researchers prefer to employ verbal fluency tasks to explore lexical access (Mousavi, Nazari & Jahan, 2020). Successful retrieval requires executive control over cognitive processes such as selective attention, selective inhibition, mental set shifting, internal response generation and self-monitoring.

Verbal fluency can be defined as the ability to generate words with speed and accuracy, it involves accessing one’s own vocabulary repertoire or mental lexicon and retrieving the target word (John, Rajasekhar & Guddattu 2018). It has been used in relation to executive functions and cognitive processes such as long-term memory, attention, speed of information processing, inhibition and working memory (Elst, Boxtel, Breukelen and Jolles, 2016).

Tests of verbal fluency evaluate an individual’s ability to retrieve specific information within restricted search parameters. The two most common parameters assessed in verbal fluency tests are phonemic fluency (letter fluency, initial letter fluency, phonological fluency, formal fluency or letter-cue word generation), assessed by asking the examinee to generate words beginning with a single letter and semantic fluency (category fluency or semantic- cue word generation), tested by asking the examinee to generate semantic category exemplars (most commonly names of animals). In the standard version of the task, participants are given 60 seconds to produce as many words as they can. Usually, only the productivity score (i.e., the raw number of legal words) is calculated. (Lezak, Howieson, Loring, Hannay and Fischer, 2004).

Letter fluency task allow participants to must generate a word from a phonemic category instead of from a semantic category, which is complex because phonemic generation is not a common strategy in word retrieval, nor is there an obvious congruency with the organization of words in some representational system (Strauss, Sherman and Spreen, 2006)

Vonk, Rizvi, Lao and Brickman (2018) stated that verbal fluency tasks are thought to be mediated by frontal brain regions for letter fluency and temporal regions for category fluency.

Literature for both clinical and experimental research, provides evidence on verbal fluency tasks as being sensitive to various adult neurological conditions such as frontal and temporal injury, Parkinson’s disease, schizophrenia, depression, Alzheimer’s disease, multiple sclerosis and traumatic brain injury (Monsch & Bondi,1994; Winocur, Leach & Freedman, 1998; Fridriksson, Moser, Shaw & Rorde, 2017; Spironelli, Calogero & Stegagno, 2011).

Verbal fluency tasks are quick and easy to administer as a part of neuropsychological assessment protocol in healthy adults and in clinical populations. However, there are only a few studies that analyzed word retrieval difficulties and their relationship to executive control processes using verbal fluency tasks in bilinguals.

II. REVIEW OF LITERATURE

The ability to retrieve a correct word from thousands of words requires a fundamental component of cognition, which is a thorough categorization skill. This process of categorization is lifelong, growing in complexity with maturation and widening of the knowledge of the world around them (Carneiro, Albuquerque and Fernandez, 2008)

Children around the globe grew up listening and learning multiple languages. As the bilingual population grows worldwide, the clinical population involving bilingual speakers also increases.

Therefore, it is critical to understand the relationship between lexical and executive control in the bilingual clinical population to improve assessment and treatment approaches (Patra, Bose and Marinis, 2020).

Bilingual is defined as having or using two languages especially as spoken with the fluency characteristics of a native speaker; a person using two languages especially habitually and with control like that of a native speaker and bilingualism as the constant oral use of two languages (Webster, 1961). OR as by Myers- Scotton (2009) Bilingualism is the ability to use two or more languages sufficiently to carry on a limited casual conversation.

Bilingualism and multilingualism, in recent times, have largely become the rule and not the exception due to global expansion. The increased global mobility resulted in an increment in the number of people who have become bilingual at all levels of society. Bilingualism can influence people in their social-communicative, emotional, cultural, metalinguistic, cognitive, and neurological areas. In India however, this has always been the case due to the vast history and cultural differences. Indian census (2001) reports that 19.44 percent are bilinguals and 7.22 percent are trilingual. The evidence on whether multilingualism leads to even greater benefits than bilingualism is scant.

Cummins (2001) showed that children who have exposure to different languages gain various degrees of oral language use (OLU). They master oral language use in both languages at an early age or the second language would interrupt the learning of the primary language, thus causing delays in both languages, also children learning a second language may show a lag in one language for a period typically the language that is not spoken in their home. The level of development of children’s mother tongue is a strong predictor of their second language development.

The cognitive ability of monolingual children and bilingual children are compared and found out that bilinguals achieve higher scores in tests of mental flexibility, understanding the conversational origin of names, distinguishing between semantic similarity and phonetic similarity, and non-verbal problem-solving tasks (Benelli & Gandolfi, 1979; Bialystok, 1986; Galambos & Goldin- Meadows, 1990)

Green (1998) studied Mental control of the bilingual lexico- semantic system, and theorized that certain areas of neurocognitive functioning within the executive domain are reinforced by processes related to bilingualism, resulting primarily from the practice of mentally switching between translations of two or more languages and selectively utilizing the language appropriate to the context, while simultaneously inhibiting other known languages.

Researches on bilingualism have typically investigated language processing and executive control mechanisms separately. As a result, dichotomous bilingual consequences have been observed relative to monolinguals, specifically, bilingual limitations on language tasks and bilingual advantages on executive control tasks (Bialystok, Craik, Green and Gollan, 2009).

Tests of verbal fluency evaluate an individual’s ability to retrieve specific information within restricted search parameters (Lezak, Howieson, Loring, Hannay and Fischer, 2004). Both category fluency (e.g., list animals) and letter fluency (e.g., list words that begin with /k/) place demands on semantic memory and executive control functions. However, letter fluency places greater demands on executive control than category fluency, making this task well-suited to investigating potential bilingual advantages in word retrieval. (Friesen, Luo, Luk and Bialystok, 2014).

Verbal Fluency tasks provide measurements of a wide range of cognitive functions, such as (1) executive function (e.g., systematic search, cognitive flexibility, and processing speed), (2) working memory and semantic memory, (3) language, (4) verbal ability, which requires speaking and knowledge of words (Moura, Simoes and Pereira, 2014).

Hazin, Leite, Oliveira and Marques (2016) tried to document normative data on verbal fluency tasks in children by considering gender, age, education, and geopolitical region of origin with auxiliary purposes in the neuropsychological diagnosis of disorders that occur with executive changes No effect of gender on the children's performance was found. However, significant differences between age groups were observed, with better performance in letter tasks in older children and better performance in letter tasks compared with category tasks. Significant regional differences in performance on the letter VF task were observed. These results reinforce the importance of regional normative data in countries with high regional cultural variations, such as Brazil.

Shao, Janse, Visser and Meyar (2014) examined the contribution of verbal ability and executive control to verbal fluency performance in 82 older adults and found that the performance on the letter and category fluency tasks was related to indicators of vocabulary size, lexical access speed, updating, and inhibition ability. In regression analysis the number of words produced in both fluency tasks was predicted by updating ability and the speed of the first response was predicted by vocabulary size and for category fluency, only lexical access speed.

Gaillard, Sachs, Petrella and Hunter (2003) in their fMRI study of verbal fluency in children and adults, gain the insight into maturation of language neural networks. They suggest that the younger children may have less consolidated and more bilateral representation of language processing areas.

Nouri, Moradi, Zardkhaneh and Zahedian (2012) traced the influence of bilingualism on the letter and category fluency tasks. Participants were 1,600 monolingual and bilingual children from Iran, required to generate as many words within 3 minutes with nine Persian letters and thirty-one categories. Bilingual children generated more words than monolingual children in the letter fluency task. However, Persian monolinguals generated significantly more words than both bilingual groups in the category fluency task. They stated bilingualism can be both advantageous and disadvantageous and produce a dissociative effect.

A. Neuroanatomical Correlates of Verbal Fluency

Research in adult studies on neuroanatomical correlates of verbal fluency has revealed the role of extensive and sophisticated neuroanatomical networks and distinct regions of neuronal activation. Increased activation has been reported in the left hemisphere (left dorsolateral prefrontal cortex, left premotor, supplementary motor cortex, left inferolateral temporal lobe, superior-middle temporal gyrus, left posterior inferior parietal lobe, insula, precuneus and anterior cingulate gyrus), right dorsolateral and medial frontal region, left pre-supplementary motor area-dorsal caudate nucleus–ventral anterior thalamic loop, Basal ganglia (caudate nucleus and putamen), cerebellum and hippocampus (Petrosini & Molinari, 2000; Meinzer & Flaisch, 2009; Flaisch & Harnish, 2012; Leib, Tuscher & Tadi, 2014; Methqal, Marsolais & Wilson,2019; Newman, Murray & Paek, 2020)

Studies documented the evidence of coordinated activity of a number of brain areas, during the verbal fluency production of children developing typically, particularly the frontal lobe; left dorsolateral prefrontal gyrus, inferior frontal gyrus, mesial frontal areas, including supplementary motor area, thalamus and left parietal lobe, inferior parietal lobe, posterior supramarginal gyrus, changes in the cortical thickness by middle childhood (Brown, Lugar & Coalson, 2005; Porter, Collins & Luciana, 2011; Tamekuchi, Hashimoto, Honda, Miyamura & Abo, 2011; Gaillard, Sachs, Balsamo, & Mckinney, 2023).

Though both children and adults activated similar regions, predominantly in the left inferior and middle frontal cortex, differences were noted in regions associated with language including the perisylvian regions surrounding Wernicke's and Broca's areas in the left hemisphere (Gaillard, Sachs, Ahmed, Petrella & Braniecki 2000; Gaillard, Pannier, Mott, Barnett &Theodore 2003; Porter, Collins, Muetzel Lim & Luciana 2011). These findings indicate that word production during verbal fluency tasks requires an extensive neural network different from an adult population with an age-related difference in activation patterns in terms of wider cortical activation in children. This greater activation was attributed to developmental plasticity for the ongoing organization of neural networks, which underlie language capacity.

The neuroanatomic correlates of verbal fluency have also been studied among disordered populations of children and adults. Verger, Levin & Jurado (2001) reported that the recovery pattern was slower in younger children as compared to older children (with a head injury) and that the effect was greater for frontal lesions involving the left hemisphere on phonemic fluency. The authors interpreted this as the reflection of the more established functional involvement of the left frontal region in the expressive language of older children.

Medina, Guibert, Sadler and Paul (2011) reported smaller activation in the left dorsal inferior frontal gyrus with no activation in the posterior superior temporal gyrus in children with Specific Language Impairment. The presence of right dominant activation of the anterior insula and ventral inferior frontal gyrus in comparison with the control group was also reported.

Puga, Ekonen, Pintos and Lascombes (2020) analyzed the performance of verbal fluency in participants with neurodevelopmental disorders - low intellectual performance, attention deficit hyperactive disorder, and dyslexia. Participants with low intellectual performance showed lower phonological and semantic fluency scores than participants with attention deficit hyperactive disorder and a lower performance in semantic fluency than the dyslexia group. 

B. Factors Affecting Verbal Fluency

Studies have examined the evidence for the variables showing a positive influence on verbal fluency performance. Phonemic and semantic fluency improves during childhood and adolescence and shows a mild decline in old age. Increases from childhood to adulthood have been associated with significant gains in semantic memory and executive functions during this period (Fichman, Machado, Santos, Carvalho, Fernandes & Koening, 2009). Educational level has a significant influence on both phonemic and semantic fluency tasks, with higher levels of education associated with better performance (Aziz, Khatar, Emara, Tawfik, Rasheedy, Muhammedin & Qassem, 2017). Authors have found little evidence of gender differences in the number of words generated on either phonemic or semantic fluency (Mathuranath, Kumar, Mathew, Annamma & Cherian, 2003). Cultural and linguistic factors are also an important and sometimes underestimated influence on neuropsychological assessment. The influence of psychosocial factors such as socioeconomic status, educational background, and profession of the caregiver on verbal fluency performance has been documented (Ardila & Rosselli, 1994; Hurks, Schrans, Meija, Wassenberg, Feron & Jolles, 2010).

Mathuranath, Cheriyan, Alexander and Sharma (2010) examined the effects of age, education, and gender on the verbal fluency task of 153 cognitively unimpaired older individuals (Malayalam speakers). They concluded that level of education significantly affects letter fluency and age inversely affects category fluency with no effects of gender on any of the verbal fluency tasks.

D’cruz, Rajarathnam and Pravinkumar (2013) compared 3 groups of Insightly unimpaired, 150 subjects (20- 50 years, 60- 75 years and above 75 years) with minimum 6th standard education. Semantic category verbal fluency test and verbal mental tracking test were administered. The result reflected that verbal fluency declined significantly with aging. Significant deflections were not observed in terms of cognitive inflexibility and executive dysfunction.

Dr. Acharya (2014) surveyed the evidence for the effects of the medium of instruction (English and Kannada) irrelevant of gender on phonemic fluency in primary school students, aged between 8-9 years using the Controlled Oral Word Association Test. The reflected outcome was, English medium students have more phonemic fluency than Kannada medium students.

Kishiyama, Boyce, Jimenez, Perry and Knight (2009) compared the performance of the semantic fluency task (28 children, mean age 9.5 years), the children from lower socioeconomic background performance score was less than children from higher socioeconomic backgrounds.

Hurks, Wassenberg, Meijs and Jolles (2010), by conducting research on 294 healthy Dutch-speaking children, found that a higher mean level of parental education is associated with significantly better animal verbal fluency, and design fluency (structured and unstructured test versions were administered).

Ardila and Rosselli (1994) reported lower performance among children from low socioeconomic status in Columbia. They attributed the low performance to the impoverished educational experience children received in school in terms of teachers, teaching facilities and infrastructure.

Thus, to summarize, children growing up learning bilingual oral languages gain various degrees of oral language use and the bilingualism of a given person may vary with time. Children typically become proficient in both languages at an early age, or show concern that the second language would interrupt the learning of the first language, thus causing delays in both languages; also, children learning a second language or two languages simultaneously may show a lag in one language for a period, typically the language that is not spoken in their home. Since the development in the second language is partially a function of the level of oral language use of the first language, it affects the phonemic generations in the phonemic verbal task. In India where, a second language is only introduced at schooling, exposure and experience in the language are essential factors to be noted.

Verbal fluency task in bilinguals was reported to be slower and more effortful retrieval for each word produced, due to interference from the nontarget language (Sandoval, Gollan, Ferreira, & Salmon, 2010). But recent studies have indicated a second effect attributable to vocabulary size. When language OLU is matched, bilinguals perform better on letter fluency (which depends more extensively on cognitive control. The research also puts forward varied results for the effect of age, education, and linguistic and psychosocial aspects on phonemic fluency.

C. Need Of The Study

Bilinguals vary in degree of proficiency in their two languages and the bilingualism of a given person may vary with time. There is a need to find the phonemic fluency capacity, in L1 (Malayalam) and L2 (English), especially in typical children to understand the vocabulary size for each letter. Understanding verbal fluency norms among typical children is paramount for the interpretation of verbal fluency among the disordered populations.  The lack of demographically adjusted norms had been a major obstacle for childhood research using verbal fluency. In children, the evaluation of verbal fluency performance needs to be understood from a developmental and linguistic perspective as these factors influence performance. Clearly, there is a need for a deeper understanding of the elusive nature of verbal fluency in typical children for enhancing its utility to a greater extent in pediatric disorders. Generally, the practice by both medical professionals and speech-language pathologists dealing with the population is to compare the norms based on the Western population. The currently available normative data relates to Western samples, inappropriate for evaluating Indian children. Linguistic factors (differences in word length, frequency of words/letters between languages), socio-cultural dissimilarity, extrinsic factors (differences in tasks) and developmental variations, prevent following a universal protocol of verbal fluency testing. The present study will facilitate an understanding of the lexical access of bilingual children developing normally.

III. METHOD

A. Aim

The aim of the present study was to compare the performance of letter fluency in Malayalam (L1) and English (L2) between group I- Government school and group II- CBSE school typical children.

B. Participants

In order to carry out the study, 20 children (both male and female) for each group aged 8 to 10 years were selected from Government Higher Secondary School in Kulashekharapuram, and Sree Narayana Central School in Kayamkulam. The selected children were Malayalam- English bilinguals.

C. Inclusion Criteria

Children included in the study are based on teachers’ reports/school records. The candidacy filter was based on the following criteria:

1. Children between the ages of 8 to 10 years.
2. Currently in lower primary education.
3. Bilingual children (Malayalam- English) with Malayalam as their first language.

D. Exclusion Criteria

The exclusion was done based on direct observation, teachers’ reports, school records, and parental information obtained through telephonic interviews.

1. Children with a history of neurological disorders, developmental disorders, language difficulties, motor limitations, and hearing deficits.
2. Children requiring special educational placement.

E. Procedure

A pre-examination semi-structured interview was conducted to collect the demographic data (age, gender, education level, medical history, communication, psychiatric history, scholastic performance, and economic status) of each participant were studied.

In order to check their language proficiency in each language, Language Experience and Proficiency Questionnaire (LEAP-Q) was administered to each participant. Assessment of Language Development- A Manipal Manual (ALD- MM) was used to measure each child's receptive and expressive language skills.

The task of verbal fluency was Phonemic fluency/ Letter fluency. The letter which occurred most frequently in the word-initial position in each language was considered.

For Malayalam /p/, /n/ and /k/ sounds were considered. These letters were selected based on the ratio of words in neuropsychological evaluations in Malayalam (Mathuranath, George, Cherian, Alexander and Sarma, 2009).

 For English /f/, /a/ and /s/ sounds were considered. Borkowski, Benton and Spreen (1967) identified a series of easy letters based on word frequency in English.

Flashcards containing the target phonemes were presented and the subject is instructed to produce as many words (nouns excluding names and places) within the restricted time period (60 seconds). The children were instructed to do the task both in Malayalam and English.

The scores were calculated based on the responses elicited within the stipulated time.

The examiner gave an indication to each child by saying start. A stopwatch was used to track the time and recordings were done in PRAAT software using hp laptop with a Sony INZONE H9 headset.

F. Analysis

Score 1 was given to the responses having a proper noun.

Score 0 was given to the responses lacking nouns.

For the analysis purpose, the Total Number of Correct Words (TNCW) was used - the total number of correct words produced during each type of fluency task was calculated by excluding

a) Intrusions (words not an exemplar of the category or letter specified),

b) Perseverations (repetitions of any correct words already given as a response)

c) Morphological variants (example: bus, buses)

For the scoring purpose, the raw score of the total number of correct words obtained was retained, instead of being converted to percentage scores. This was done as the percentage of the correct words generated did not provide meaningful information on fluency performance, as compared to the reporting of the raw number of words generated (Troyer, 2000). For example, if the child says “cat, dog, cow, buffalo, ox, cat, lion” the total number of correct words was considered as six.

IV. RESULT AND DISCUSSION

The present study evaluates phonemic fluency performance in 40 Malayalam- English typical bilinguals. The scores were obtained from group I- 20 Government school children and group II- 20 CBSE school children were subjected to statistical analysis and the results derived are discussed below.

Figure 1.1

Showing the mean for L1 and L2 of total 40 participants

From Figure 2.1 and Table 2.1, it can be concluded that while comparing the letter fluency task score there is no significant difference between the mean and standard deviation of participants in Group 1 and Group 2. The only significant score obtained was when comparing the score of stimulus /f/ for L2.

V. DISCUSSION

Based on the result 100% of children in group I (Government school) and group II (CBSE school) showed better performance for English (L2) than that of their native language Malayalam (L1). While comparing the performance between the government and CBSE school children no significant difference was observed except for the stimulus /f/ in L2 and the present study is the first of its kind in the Indian languages comparing the letter fluency in L1 and L2.

Children from all age groups were seen to generate words on Initial Letter Fluency, by clustering words together that shared similar phonemic properties. The most common strategies employed by children for organizing the word retrieval during Initial Letter Fluency task included the generation of words that began with the same initial two letters (e.g., /kuppi/-/ku??l/) and also words beginning with same initial two syllables (e.g., /ka?ud?a/, /ka?ug?n/). Few children attempted to generate words following semantic rules when they were unable to generate more words based on phonemic characteristics. One example noted during analysis included the production of phonemically related words belonging to body parts (e.g., /n??z/, /n??jl/, /nek/).

The Letter Fluency task involves no heuristic searches for items (Azuma, 2004; Leggio, Silveri & Petrosini, 2000) from the semantic stores. The task of Initial Letter Fluency, as Wood, Abbott and Jackson (2001) explained, is neither a natural component of language processing nor follows the familiar access route to the lexicon like the Semantic Category Fluency task. It involves the intentional use of strategic search for broader and less defined phonological levels of word representation which makes the organization’s task more effortful, demanding and difficult. During the Initial Letter Fluency task, the participants need to avoid searching based on semantic criteria involving the meaning of words and follow the orthographic route involving the feature of the surface structure of the words.

The decrease in scores in Malayalam can be plausibly attributed to the presence of greater average word length and longer words being used more frequently in daily use. While the average word length has been reported to be around five in English, it has been reported to be near 10.255 (the highest among the Indian languages) with the average number of syllables per word in Malayalam being 4.44 (Bharati and Varsha, 2002).

Further evidence regarding differences in performance on Initial Letter Fluency tasks comes from the study by Borkowski, Benton & Spreen (1967), which indicated that vocabulary size for each letter differed resulting in varied dictionary frequency for each letter.

Researchers maintain the deliberate vocabulary learning and teaching are the best predictors of effectual vocabulary development (Elgort, 2011; Laufer, 2005). In a meta?analysis of numerous L2 vocabulary learning studies, Schmitt (2008) concluded that every language course must explicitly focus on vocabulary to maximize learning and long?term retention of lexical items. He points to the major role that explicit learning tasks play in the vocabulary acquisition process.

Huckin and Coady (1999) in their study on the role of incidental learning in the acquisition of a foreign language concluded that incidental learning is central to second language vocabulary development of primary school children.

Malik and Asnur (2017) reported that the use of smartphones and media helps students to improve their foreign language by accessing foreign - language speakers, their songs and vocabulary.

Deborah (2006) in her study to find the effects that technology has on second language learning stated that the effect of the technology-enhanced curriculum made L2 learning easier and technology is a powerful tool with tremendous effects in all areas, from language skills (i.e., reading, listening, speaking, and writing) as well as providing students with the opportunity to (1) become more global and (2) develop higher-level critical thinking skills.

Conclusion

Verbal fluency measures have been well-researched in the adult population, research on these measures in children is scanty. Despite the potential of this analysis as a measure of word retrieval in children, it is not generally used in clinical or experimental studies with typically developing children or children with brain injury. Moreover, with literature support of verbal fluency measures being sensitive to neurodevelopment, there is a lack of clarity on the performance of these instruments in children or how they are dependent on various factors. The lack of Indian norms for these tests, as well as the paucity of information concerning the relationship between the different measures in children, has hindered the full use of this important diagnostic instrument, limiting their function to that of merely describing children’s linguistic abilities. The present study analysed and compared the performance in the letter fluency task of L1 (Malayalam) and L2 (English) among typical bilingual children. The study also focussed on comparing the performance of letter fluency tasks between the students of Government school and CBSE school. 40 children were selected after administering the Language Experience and Proficiency Questionnaire (LEAP-Q) and Assessment of Language Development (ALD). These children were divided into Group I of 20 students from a government school and Group II of 20 students from a CBSE school, ages ranging from 8 years to 10 years. The performance in letter fluency was evaluated using /p/, /n/ and /k/ sounds for Malayalam and /f/, /a/ and /s/ sounds for English. Based on the result all the 40 children in group I and group II showed better performance in English (L2) than that of their native language Malayalam (L1). While comparing the performance between the government school children and CBSE school children no significant difference can be observed except for the stimulus /f/ in L2. To summarise, we can say that letter fluency in the English language is better than that of the native language Malayalam. The implementation of Foreign language classrooms, Medium of instruction and Medium of communication in school and the influence of media might have a positive impact and promote the use of L2 thereby improving the fluency and concrete second language abilities. A. Limitations Of The Study Only the Letter fluency task in Verbal fluency was considered. The age group selected for the sample was 8 to 10 years. A large sample size would have yielded more reliable results. B. Future Implication Can be done with more sets of sounds. Category fluency in Verbal fluency can also be assessed. Comparison between the age groups can be done. A comparative study of the performance of girls and boys can be done.

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