Small Vocabulary Research Articles

A Concurrent Validity Study of the Mullen Scales of Early Learning (MSEL) and the MacArthur-Bates Communicative Developmental Inventory (CDI) in Infants with an Elevated Likelihood or Diagnosis of Autism.

Infants at elevated likelihood for or later diagnosed with autism typically have smaller vocabularies than their peers, as shown by the Mullen Scales of Early Learning (MSEL) and the MacArthur-Bates Communicative Developmental Inventory (CDI). However, the extent to which MSEL and CDI scores align remains unclear, especially across clinical and non-clinical populations. This study examined whether the concurrent validity of the MSEL and CDI differs based on autism likelihood and diagnosis. Data from 720 14-month-old infants were analysed, grouped by likelihood (elevated vs. typical) and diagnosis at 36 months (diagnosed vs. not diagnosed). Vocabulary scores were compared across both likelihood and diagnostic groups. Moderate correlations were observed between the MSEL and CDI in most groups (rs range = [.34-.58]). One exception was that the expressive scores of elevated likelihood infants on the MSEL and CDI were more closely associated than the expressive scores of typical likelihood infants. Diagnosed infants had lower vocabulary scores than non-diagnosed peers on both the MSEL and CDI. The elevated likelihood group showed lower scores on the MSEL but not the CDI compared to typical likelihood infants. The moderate correlations suggest that the MSEL and CDI assess different aspects of language in infancy. These associations were weaker than previously reported in autistic children. Differences in vocabulary scores across likelihood and diagnostic groups highlight the need for further research to understand the association between these measures.

Follow-up of expressive language and general development at 12, 18 and 36 months for children with no canonical babbling at 10 months

ABSTRACT Little is known about the developmental trajectories in children who do not use canonical babbling (CB) at 10 months. The aim was to examine how speech, language, cognitive and motor abilities developed in children without CB. For 15 children identified as not having CB, consonant production, expressive vocabulary and general development were assessed at 12, 18 and 36 months from audio–video recordings. Twelve (79%) children still lacked CB at 12 months. At 18 months, six (40%) had parent-reported expressive vocabulary results below the 10th percentile, and two (14%) did not use dental/alveolar stops. The percentage of consonants correct for the group was at the level of peers at 36 months (89%, SD 0.17), but the group had fewer established target consonants than age norms. Most children had a small expressive vocabulary in comparison with Swedish age norms for younger children as well as with age-matched norms for other Nordic languages. The general development (Bayley-III) for three children (21%) who did not use speech was 1–2 SD below the average range in at least one domain (cognitive, language or motor), but the results for the whole group were within the average range. In conclusion, the heterogeneity in early consonant development in the study group resembles that of children in clinical groups with known risk for speech and language difficulties and the expressive vocabulary resembles that of children with delayed expressive vocabulary. For about one-fifth of the children, the absence of canonical babbling at age 10 months could be seen as an early sign of a more comprehensive developmental disability.

Detecting chord tone alterations and suspensions

Chord detection is the task of assigning chord labels to segments of an input musical piece. The labels are typically drawn from a pre-defined vocabulary in which each symbol comprises at least a root pitch and a chord quality. In this paper, we introduce a post-processing method that takes as input a musical score with such labels and adds chord tone alterations such as suspensions to them. Although it is an important aspect of harmonic analysis, it is infeasible to do so by simply adding features to the labels in the vocabulary, given the multiplicative effect on vocabulary sizes which can already be over 1000. We evaluate our method using both ground truth input and input derived from a chord detection model, showing that it outperforms a strong heuristic baseline in both cases. Furthermore, we show that our model can be used to detect the rarer chord qualities from the model's output alterations, potentially enabling chord detection models to be trained on small vocabularies containing only the more common (and easier to identify) chord qualities (e.g. only triads).

Teaching Modeling in Introductory Statistics: A Comparison of Formula and Tidyverse Syntaxes

When incorporating programming into a statistics course, there are many pedagogical considerations. In R, one consideration is the particular R syntax used. This article reports on a head-to-head comparison of a pair of introductory statistics labs, one conducted in the formula syntax, the other in tidyverse. Pre- and post-surveys show minimal differences between labs, with students reporting a positive experience regardless of section. Analysis of YouTube and RStudio Cloud data shows interesting distinctions. The formula section appeared to watch a larger proportion of pre-lab videos, but spend less time computing. Conversely, the tidyverse section watched a smaller proportion of videos and spent more time computing. The tidyverse labs were slightly longer in terms of lines of code and minutes of videos. The tidyverse labs exposed students to more distinct R functions, but reused functions more frequently. Both labs relied on a relatively small vocabulary of functions, which can provide a starting point for instructors interested in teaching introductory statistics in R. The instructor experience of teaching the two syntaxes diverged when discussing relationships between categorical variables, as well as working with numeric variable summary statistics. This work provides additional evidence for instructors looking to choose between syntaxes for introductory statistics.

Applying Problem-Based Classroom Learning to Assist Students in increase Students’ Speaking Skill

The purpose of this study was to elucidate how SMPN 3 Asembagus class VIII students could benefit from problem-based learning interactions in order to improve their speaking skills in 2023–2024. This study used classroom action research (CAR) as its research approach. They have an extremely small vocabulary, which makes it difficult for them to speak English. As a result, students require an additional teaching strategy known as problem-based learning (PBL) to develop their speaking skills. The objective of this research was to determine how to use problem-based learning as a teaching strategy to improve the speaking skills of students and their academic achievement. The action research was carried out in some manner. These procedures included the pre-test, post-test, and the cycle that starts with planning, acting, observing, and reflecting. Methods for gathering data include testing, documentation, and observation. This method was used in exams, in-class activities, observations, documentation, and student evaluations of both themselves and their peers. The study's findings indicated that there had been a quantitative improvement in the students' speaking skills. Additionally, students engaged more fully in the oral instruction and learning process. In summary, the eighth grade students in SMPN 3 Asembagus were able to speak English more fluently and effectively thanks to the great and efficient use of problem-based learning. As a result, the students' speaking skills improved, as is clear from the preceding result, and this strategy contributed favorably to the improvement of speaking skills. This approach is useful for making the process of teaching students to speak English more pleasurable.

Arithmetic with language models: From memorization to computation

A better understanding of the emergent computation and problem-solving capabilities of recent large language models is of paramount importance to further improve them and broaden their applicability. This work investigates how a language model, trained to predict the next token, can perform arithmetic computations generalizing beyond training data. Binary addition and multiplication constitute a good testbed for this purpose, since they require a very small vocabulary and exhibit relevant input/output discontinuities making smooth input interpolation ineffective for novel data. We successfully trained a light language model to learn these tasks and ran a number of experiments to investigate the extrapolation capabilities and internal information processing. Our findings support the hypothesis that the language model works as an Encoding–Regression–Decoding machine where the computation takes place in the value space once the input token representation is mapped to an appropriate internal representation.

Social interactions offset the detrimental effects of digital media use on children's vocabulary.

Young children's rapid vocabulary growth during the first few years is supported by input during social interactions with caregivers and, increasingly, from digital media. However, the amount of exposure to both sources can vary substantially across socioeconomic classes, and little is known about how social interactions and digital media use together predict vocabulary in the first few years of life. The current study takes a first step toward examining whether increased social interactions with other individuals may buffer the potentially detrimental effects of digital media use on language among a socioeconomically diverse sample. 305 caregivers of children between 17 and 30-months completed questionnaires about their family demographics, their child's technology use, and the child's daily routines and social interactions. Findings suggest children who experience fewer human interactions and greater technology exposure have smaller vocabularies than their peers who socialize more and use less technology, and this disparity becomes greater as children get older. Moreover, the number of social interactions moderates the link between SES, digital media, and vocabulary such that the negative impact of digital media on vocabulary for children from low SES households can be offset with increased social interactions. Together, this suggests that increasing the amount of human interactions may serve as a protective factor for vocabulary outcomes in a world where digital media use is prominent.

읽기곤란 초등학생의 하위 유형별 어휘 중재 효과

The purpose of this study is to explore the heterogeneity of subtypes among elementary school students with reading difficulties and to determine the effects of the vocabulary intervention program. The participants of the study were 200 students from S city in Gyeonggi-do, who participated in the 'Saerabaeum' reading intervention program, a cooperative educational project between S University and S city from 2021 to 2023. A universal screening test was conducted on 4,747 students in grades 3-5 of elementary schools participating in the project over three years, from which 200 students with reading difficulties were selected. Tier 2 level small group reading interventions were provided, and the heterogeneity of subtypes was identified using Latent Profile Analysis (LPA). In addition, to assess the effect of the vocabulary instruction over time, hierarchical linear modeling (HLM) was utilized based on the scores of five vocabulary tests including pre-tests, 1st through 3rd progress monitoring tests, and post-tests for 85 students who received vocabulary instruction. Finally, the baseline scores and slopes of progress for students who received individual vocabulary intervention at the Tier 3 level and those who received small group vocabulary intervention at the Tier 2 level were plotted using graphs functions in the Excel. The discussion and significance of each research result suggest effective vocabulary intervention methods and models for students struggling with reading.

Infant-directed communication: Examining the many dimensions of everyday caregiver-infant interactions.

Everyday caregiver-infant interactions are dynamic and multidimensional. However, existing research underestimates the dimensionality of infants' experiences, often focusing on one or two communicative signals (e.g., speech alone, or speech and gesture together). Here, we introduce "infant-directed communication" (IDC): the suite of communicative signals from caregivers to infants including speech, action, gesture, emotion, and touch. We recorded 10min of at-home play between 44 caregivers and their 18- to 24-month-old infants from predominantly white, middle-class, English-speaking families in the United States. Interactions were coded for five dimensions of IDC as well as infants' gestures and vocalizations. Most caregivers used all five dimensions of IDC throughout the interaction, and these dimensions frequently overlapped. For example, over 60% of the speech that infants heard was accompanied by one or more non-verbal communicative cues. However, we saw marked variation across caregivers in their use of IDC, likely reflecting tailored communication to the behaviors and abilities of their infant. Moreover, caregivers systematically increased the dimensionality of IDC, using more overlapping cues in response to infant gestures and vocalizations, and more IDC with infants who had smaller vocabularies. Understanding how and when caregivers use all five signals-together and separately-in interactions with infants has the potential to redefine how developmental scientists conceive of infants' communicative environments, and enhance our understanding of the relations between caregiver input and early learning. RESEARCH HIGHLIGHTS: Infants' everyday interactions with caregivers are dynamic and multimodal, but existing research has underestimated the multidimensionality (i.e., the diversity of simultaneously occurring communicative cues) inherent in infant-directed communication. Over 60% of the speech that infants encounter during at-home, free play interactions overlap with one or more of a variety of non-speech communicative cues. The multidimensionality of caregivers' communicative cues increases in response to infants' gestures and vocalizations, providing new information about how infants' own behaviors shape their input. These findings emphasize the importance of understanding how caregivers use a diverse set of communicative behaviors-both separately and together-during everyday interactions with infants.

Interpretable Compositional Representations for Robust Few-Shot Generalization.

We propose Recognition as Part Composition (RPC), an image encoding approach inspired by human cognition. It is based on the cognitive theory that humans recognize complex objects by components, and that they build a small compact vocabulary of concepts to represent each instance with. RPC encodes images by first decomposing them into salient parts, and then encoding each part as a mixture of a small number of prototypes, each representing a certain concept. We find that this type of learning inspired by human cognition can overcome hurdles faced by deep convolutional networks in low-shot generalization tasks, like zero-shot learning, few-shot learning and unsupervised domain adaptation. Furthermore, we find a classifier using an RPC image encoder is fairly robust to adversarial attacks, that deep neural networks are known to be prone to. Given that our image encoding principle is based on human cognition, one would expect the encodings to be interpretable by humans, which we find to be the case via crowd-sourcing experiments. Finally, we propose an application of these interpretable encodings in the form of generating synthetic attribute annotations for evaluating zero-shot learning methods on new datasets.

Exploring auditory recognition: Native Japanese listeners' perception of frequent and infrequent English words in noise with varied phonological neighborhood densities

Native Japanese listeners identified English words embedded in noise (SNR + 6dB) produced by native American English and Japanese speakers. The identical word list used in our previous study (Nozawa and Wayland 2023) was employed. Listeners responded by typing the words they heard. The findings revealed no discernible impacts of phonological neighborhood density, possibly due to the small vocabulary size limiting competition from other words. However, frequent words exhibited greater precision in recognition compared to infrequent words. Despite the introduction of noise, the overall accuracy of responses did not experience a substantial impact. Nevertheless, specific words like “class” and “club,” initially nearly perfect in accuracy without noise, dropped to 0% accuracy. Most errors included phoneme substitution rather than phoneme addition or deletion, and in / CVC/ words, the onset consonant was identified substantially better than the vowel and the coda consonant. Initial consonant clusters, such as /br/, / kl/, and /pl/, were frequently perceived as /l/ or /r/, leading to the initial stops or fricatives being missed. Errors encompassed the substitution of phonemes with others that are not typically perceptually assimilated into the same native language (L1) categories, which would not be revealed through predefined multiple-choice identification or discrimination tasks.

A Picture Guessing Game to Improve English Skill at Sdn Baruh 1

One of the difficulties students often experience in learning English is reading and speaking. Reading and speaking are activities that occur every day both at school, at home or in public places. Students in Indonesia experience difficulties when understanding reading and speaking English, mainly due to a lack of practice, the small vocabulary they have, and the lack of knowledge about appropriate English reading comprehension strategies. To improve the English language skills of students at Baruh 1 Elementary School, namely in the form of a picture guessing game to improve English language skills at Baruh 1 Elementary School. The approach used in this study is a descriptive qualitative research approach. The results of this study can be concluded that 6 students were very receptive and able to use English, because previously they had taken English lessons outside of school. 2 students are still classified as moderate in using English, they still experience a little difficulty in learning English. but he can know a little vocabulary used in learning English. 2 students still do not accept to use English, because they are not fluent in reading and cannot even read, so they find it difficult to do learning, including learning English. One of the most important skills implemented through deployment is the guessing game. Researchers use games as a learning medium. The picture guessing game is an activity that makes us more relaxed and fun. Based on research results, the proportion of success is 75%. The English picture guessing game for SDN Baruh 1 students is suitable for use and needs to be developed by increasing the number of pictures and adding the number of other categories, so that it can increase vocabulary in English. with picture game media to improve English learning, students are more enthusiastic in learning English and can train students' vocabulary, how to speak, where students are more efficient and more confident.

Reading Challenges in Elementary School Students' English as a Foreign Language

This study looked into the types of comprehension-related reading issues that fourth-grade kids faced, the factors that influence reading difficulties, and the efforts made by these students, who were between the ages of 11 and 12, to overcome their reading difficulties. The study used a qualitative method to try to understand the reading challenges of English as a foreign language. Twenty-two fourth-graders served as the research subjects. Questionnaires, documentation, and interviews were employed in the data collection process. Qualitative data analysis was the method employed. The study's findings showed that 15 students had trouble reading and that they had trouble understanding English reading texts when they were given by their teachers. Fourth-grade pupils' difficulties reading English was caused by an internal factor: they were less motivated to learn English in class and had a smaller vocabulary. Regarding the external component, the school library contained no references to English-reading books. It is evident from the previous results that fourth-grade elementary school kids struggle with reading.

Effectiveness of Increasing Vocabulary and Constructing Sentences for High Class 4/5/6 SDLB for the Deaf Using the MMR Method with Video Media at SLB Riverkids and SLB Putra Jaya

Deafness is a condition where a child experiences problems with his ability to hear. Deaf children have a small vocabulary. The small vocabulary is caused by poor listening skills so that children are unable to accept new vocabulary which results in difficulties in communicating. Apart from difficulties in communication, they also have difficulty in constructing sentences. One step that can overcome the above problem is to apply the Maternal Reflective Method (MMR). The Reflective Maternal Method (MMR) emphasizes the mother's way of teaching language to children, where the teaching is carried out scientifically. The aim of this research is to analyze MMR on the ability of deaf children in adding vocabulary and constructing sentences. This type of research is Quasi Experimental research with a one group pretest posttest design, which applies five pretests and five posttests. Analysis technique for testing hypotheses using the SPSS 25 for Windows program.The research results showed a significant difference between the pretest results and the posttest results. This is proven by the output results obtained p is 0.000, which means p<0.05 then H0 is rejected and Ha is accepted. This means that there is a significant increase in the vocabulary and sentence learning outcomes of deaf students.The conclusion of this research is that the Maternal Reflective Method (MMR) can influence the addition of vocabulary and sentence construction in deaf children

Using TikTok as a Tool for English Vocabulary Learning in the EFL Context

One of the most crucial components of studying a language is learning its vocabulary. Without sufficient vocabulary, communication becomes problematic. However, research shows that Saudi Arabian university students have a small English vocabulary size. Many technological tools exist in the literature for increasing students’ vocabulary size, including TikTok videos. TikTok has become one of the most popular social media platforms for producing and sharing videos. Because students’ perception of tools used in the classroom determine the tools’ success, investigating their perception of using TikTok videos for English vocabulary learning is essential. In this study, a quantitative research design was used to investigate students’ perception toward using TikTok as an English vocabulary learning tool in the EFL context. A descriptive quantitative methodology was adopted to analyze data from 115 female students at King Abdulaziz University. According to the findings, most students have a positive perception toward the use of TikTok videos as a vocabulary learning tool. These findings suggest that TikTok videos can be used to increase students’ English vocabulary size. The current study proposes an alternative pedagogical means for teaching English vocabulary to language teachers who want to help their students expand and develop their vocabulary.

SignRing

Sign language is a natural language widely used by Deaf and hard of hearing (DHH) individuals. Advanced wearables are developed to recognize sign language automatically. However, they are limited by the lack of labeled data, which leads to a small vocabulary and unsatisfactory performance even though laborious efforts are put into data collection. Here we propose SignRing, an IMU-based system that breaks through the traditional data augmentation method, makes use of online videos to generate the virtual IMU (v-IMU) data, and pushes the boundary of wearable-based systems by reaching the vocabulary size of 934 with sentences up to 16 glosses. The v-IMU data is generated by reconstructing 3D hand movements from two-view videos and calculating 3-axis acceleration data, by which we are able to achieve a word error rate (WER) of 6.3% with a mix of half v-IMU and half IMU training data (2339 samples for each), and a WER of 14.7% with 100% v-IMU training data (6048 samples), compared with the baseline performance of the 8.3% WER (trained with 2339 samples of IMU data). We have conducted comparisons between v-IMU and IMU data to demonstrate the reliability and generalizability of the v-IMU data. This interdisciplinary work covers various areas such as wearable sensor development, computer vision techniques, deep learning, and linguistics, which can provide valuable insights to researchers with similar research objectives.

Receptive Vocabulary Size of Omani Post-Basic Education Graduates

This descriptive study examined the receptive vocabulary size of Omani post-basic education graduates. Also, it investigated the relationship between receptive vocabulary size and language proficiency among these students. Finally, it examined differences in receptive vocabulary size with respect to gender. The sample consisted of 294 Omani post-basic education graduates (183 males and 111 females) who were enrolled in foundation programs at Sultan Qaboos University. The study instrument was the Vocabulary Level Test Version B, which was developed by Nation (1983) and revised by Schmitt, Schmitt, and Clapham (2001). The study found that the Omani post-basic graduates had a small receptive vocabulary of approximately 1,725 word families. It also found a statistically significant relationship between students’ receptive vocabulary size and their language proficiency. Finally, it revealed statistically significant differences in receptive vocabulary size with respect to gender in favor of female students. Accordingly, the researcher provides recommendations for practice and further research.

Vocabulary Change in Process Writing: Effect of Text Structure Instruction

Abstract The purpose of this study, conducted as a follow-up study of Oshima (2020), was to examine whether Japanese EFL students’ use of vocabulary changed after being given lessons on explicit instruction on text structure and process writing. Two groups of college students—the beginner-level group writing a descriptive essay and the advanced-level group writing an argumentative essay—wrote an outline, the first draft (D1), the second draft (D2), and the final draft (FD), and I examined the differences in lexical richness between students’ D1 and FD with New Word Level Checker (Mizumoto, 2021). The results showed that both groups’ drafts had changed in the number of words used (tokens), the number of unique words used (types), and the number of lower frequency words used. This study’s finding also supports the importance of choosing an appropriate measurement to analyze students’ vocabulary levels. For Japanese students, 1K-word bands, which have been widely used in previous literature, seem too broad to capture their small vocabulary improvement.

Twenty-month-olds categorically discriminate similar sounding vowels regardless of vocabulary level, an event related potentials (ERP) study.

The current study investigated whether vocabulary relates to phonetic categorization at neural level in early childhood. Electoencephalogram (EEG) responses were collected from 53 Dutch 20-month-old children in a passive oddball paradigm, in which they were presented with two nonwords "giep" [ɣip] and "gip" [ɣɪp] that were contrasted solely by the vowel. In the multiple-speaker condition, both nonwords were produced by twelve different speakers; while, in the single-speaker condition, one single token of each word was used as stimuli. Infant positive mismatch responses (p-MMR) were elicited in both conditions without significant amplitude differences. When the infants were median split based on vocabulary level, the large and small vocabulary groups showed comparable p-MMR amplitudes yet different scalp distribution in both conditions. These results suggest successful phonetic categorization of native similar sounding vowels at 20 months, and a close relationship between speech categorization and vocabulary development.

Frequent vs. infrequent words shape toddlers' real-time sentence comprehension.

We examined how noun frequency and the typicality of surrounding linguistic context contribute to children's real-time comprehension. Monolingual English-learning toddlers viewed pairs of pictures while hearing sentences with typical or atypical sentence frames (Look at the… vs. Examine the…), followed by nouns that were higher- or lower-frequency labels for a referent (horse vs. pony). Toddlers showed no significant differences in comprehension of nouns in typical and atypical sentence frames. However, they were less accurate in recognizing lower-frequency nouns, particularly among toddlers with smaller vocabularies. We conclude that toddlers can recognize nouns in diverse sentence contexts, but their representations develop gradually.