scholarly journals Vocabulary knowledge in relation to memory and analysis: An approximate replication of Milton's (2007) study on lexical profiles and learning style

2013 ◽  
Vol 46 (3) ◽  
pp. 335-354 ◽  
Author(s):  
Paul Booth
Keyword(s):  
Linear Relationship ◽  
Learning Style ◽  
Low Frequency ◽  
Approaches To Learning ◽  
Vocabulary Knowledge ◽  
Vocabulary Size ◽  
Aptitude Tests ◽  
The Individual ◽  
Individual Profiles ◽  
Vocabulary Recognition

This paper presents an approximate replication of Milton's (2007) study on lexical profiles and learning style. Milton investigated the assumption that more frequent words are acquired before less frequent ones. Using a vocabulary recognition test (X-Lex) to measure vocabulary size, Milton found that L2 English group profiles show a linear relationship between greater knowledge of high frequency words and lesser knowledge of low frequency items. The profiles also showed variability in individual profiles. Milton hypothesised that the individual differences in profiles are partly attributable to different approaches to learning, as elicited via language aptitude tests of memory and analysis. Learner profiles that showed a linear relationship with vocabulary frequency scored higher on analysis; learners who had irregular profiles scored higher on memory. The aim of this replication is to confirm whether learning style helps to determine what L2 lexis is learnt. It duplicates the vocabulary size test and the memory and analysis tests. However, the replication uses regression analyses, rather than a single ANOVA, to determine whether memory or analysis contributes to vocabulary knowledge. Moreover, the participants’ L1 backgrounds are mixed, and they are older. The results from this replication do not support Milton's findings, but a post-study supports the notion that at low proficiency there is a relationship between memory and vocabulary size. It is concluded that neither memory nor analysis is related to patterns in lexical profiles, but that memory contributes to vocabulary size.

English Students’ Vocabulary Size and Level at a Private University in West Java, Indonesia

Humaniora ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 75-81
Author(s):  
Fenty Lidya Siregar
Keyword(s):  
Language Learning ◽  
Undergraduate Students ◽  
Low Frequency ◽  
Private University ◽  
Reading Program ◽  
Vocabulary Knowledge ◽  
Extensive Reading ◽  
Vocabulary Size ◽  
West Java ◽  
Word Families

The research investigated the EFL (English as a Foreign Language) undergraduate students’ vocabulary knowledge (size and level). The research involved 40 second-semester students who were enrolling in two reading courses at an English Department in a private university in West Java, Indonesia. Vocabulary Size Test by Nation and Beglar; and Vocabulary Level Test by Webb, Sasao, and Ballance were used to gain data. It is found that the participants’ average vocabulary size is 8.732,5 word-families. The finding of the research also reveals that only ten students master 1.000-5.000 word-levels. It means that despite a big vocabulary size that many students have, 75% of them only know a limited high and mid-frequency vocabulary. The findings imply that the students still need to read graded readers to master high and mid-frequency levels. The current research project also indicates that the students might have met more low-frequency words than high and mid-frequency words in their language learning prior to their current extensive reading program.

scholarly journals The Vocabulary Knowledge of Saudi EFL Tertiary Students

2019 ◽  
Vol 12 (5) ◽  
pp. 55
Author(s):  
Sultan Altalhab
Keyword(s):  
Low Frequency ◽  
Vocabulary Knowledge ◽  
Vocabulary Test ◽  
Vocabulary Size ◽  
High Quality ◽  
Authentic Texts ◽  
The Mean ◽  
Basic Level

This study examines the vocabulary knowledge of 120 Saudi tertiary students in order to scrutinise their ability to communicate in English. A vocabulary test constructed by Nation and Beglar (2007) was utilised in the study. The findings revealed that the mean vocabulary size of Saudi EFL tertiary students was roughly 3000 words. Nevertheless, most of the participants achieved low scores in the vocabulary low frequency levels. Some participants were unable to answer any item correctly in these low and mid frequency levels. This suggests that while those students might be able to communicate at a basic level, dealing with reading simplified texts and comprehending listening materials, they may struggle with reading authentic texts, producing a high quality of writing and watching English TV programmes and films.

Passive vocabulary size and speed of meaning recognition

2001 ◽  
Vol 1 ◽  
pp. 7-28 ◽  
Author(s):  
Batia Laufer ◽  
Paul Nation
Keyword(s):  
Word Frequency ◽  
Native Speakers ◽  
Response Times ◽  
Word List ◽  
Vocabulary Knowledge ◽  
Vocabulary Size ◽  
Speed Test ◽  
Speed Of Response ◽  
The Relationship ◽  
Vocabulary Recognition

This paper examines the relationship between fluency and vocabulary size, and also between fluency and word frequency level. Fluency was operationalised as the time learners need to recognize meanings of words sampled from different frequency levels. It was measured by a computerised vocabulary recognition speed test (VORST). The test was given to 488 native and non-native speakers who were divided by vocabulary size into four groups. The four groups were compared on speed of response to the 3000 level and University Word List (UWL) words. Speed was also correlated with vocabulary size. Additionally, response times to different frequency levels were compared for each subject. Results suggest that speed of retrieval is moderately related to vocabulary size and word frequency. Non-native speakers’ increase in speed lags behind increase in vocabulary size. Non-native speakers also respond more slowly to less frequent words. Responses of native speakers, on the other hand, are more homogeneous across subjects and across vocabulary frequencies. Speed of retrieval cannot be fully predicted from vocabulary knowledge and therefore speed tests should supplement tests of vocabulary size and depth.

Developing a lexical profiler for spoken French L2 and Italian L2

2011 ◽  
Vol 11 ◽  
pp. 75-93 ◽  
Author(s):  
Camilla Bardel ◽  
Christina Lindqvist
Keyword(s):  
Word Frequency ◽  
Low Frequency ◽  
Vocabulary Knowledge ◽  
Word Knowledge ◽  
Group Level ◽  
Proficiency Levels ◽  
Individual Profiles ◽  
Profiling Analysis

This study is a follow-up to Lindqvist et al. (to press), where we investigated lexical frequency profiles of learners of French and Italian at different proficiency levels. By analyzing the proportion of low-frequency words used by the learners, we could distinguish proficiency levels that differ significantly at group level and correspond to morphosyntactic proficiency levels. However, some individual results within the groups indicated a need to analyze individual profiles in order to get a better picture of the actual quality of the learner’s vocabulary knowledge. The present study focuses on thematic vocabulary and cognates among the low-frequency words used by learners at different proficiency levels. We suggest that investigating qualitative aspects of learners’ word knowledge is a fruitful complement to traditional lexical profiling analysis. Such a combination can lead to a more complete picture of learners’ lexical profiles. Although we are aware that word frequency is known to be a powerful factor in vocabulary acquisition, our on-going research aims at developing a more general lexical profiler that integrates additional aspects that we have found to be relevant for learnability.

scholarly journals Passive vocabulary size and speed of meaning recognition: are they related?

2020 ◽  
Author(s):  
Paul Nation ◽  
B Laufer
Keyword(s):  
Word Frequency ◽  
Native Speakers ◽  
Response Times ◽  
Word List ◽  
Vocabulary Knowledge ◽  
Vocabulary Size ◽  
Speed Test ◽  
Speed Of Response ◽  
The Relationship ◽  
Vocabulary Recognition

This paper examines the relationship between fluency and vocabulary size, and also between fluency and word frequency level. Fluency was operationalised as the time learners need to recognize meanings of words sampled from different frequency levels. It was measured by a computerised vocabulary recognition speed test (VORST). The test was given to 488 native and non-native speakers who were divided by vocabulary size into four groups. The four groups were compared on speed of response to the 3000 level and University Word List (UWL) words. Speed was also correlated with vocabulary size. Additionally, response times to different frequency levels were compared for each subject. Results suggest that speed of retrieval is moderately related to vocabulary size and word frequency. Non-native speakers’ increase in speed lags behind increase in vocabulary size. Non-native speakers also respond more slowly to less frequent words. Responses of native speakers, on the other hand, are more homogeneous across subjects and across vocabulary frequencies. Speed of retrieval cannot be fully predicted from vocabulary knowledge and therefore speed tests should supplement tests of vocabulary size and depth.

scholarly journals Passive vocabulary size and speed of meaning recognition: are they related?

2020 ◽  
Author(s):  
Paul Nation ◽  
B Laufer
Keyword(s):  
Word Frequency ◽  
Native Speakers ◽  
Response Times ◽  
Word List ◽  
Vocabulary Knowledge ◽  
Vocabulary Size ◽  
Speed Test ◽  
Speed Of Response ◽  
The Relationship ◽  
Vocabulary Recognition

This paper examines the relationship between fluency and vocabulary size, and also between fluency and word frequency level. Fluency was operationalised as the time learners need to recognize meanings of words sampled from different frequency levels. It was measured by a computerised vocabulary recognition speed test (VORST). The test was given to 488 native and non-native speakers who were divided by vocabulary size into four groups. The four groups were compared on speed of response to the 3000 level and University Word List (UWL) words. Speed was also correlated with vocabulary size. Additionally, response times to different frequency levels were compared for each subject. Results suggest that speed of retrieval is moderately related to vocabulary size and word frequency. Non-native speakers’ increase in speed lags behind increase in vocabulary size. Non-native speakers also respond more slowly to less frequent words. Responses of native speakers, on the other hand, are more homogeneous across subjects and across vocabulary frequencies. Speed of retrieval cannot be fully predicted from vocabulary knowledge and therefore speed tests should supplement tests of vocabulary size and depth.

scholarly journals Comparing Two Measures of L2 Depth of Vocabulary Knowledge Using the Association With Vocabulary Size

2021 ◽  
Author(s):  
Ali Dabbagh ◽  
Mostafa Janebi Enayat
Keyword(s):  
Significant Contribution ◽  
Word Association ◽  
Low Frequency ◽  
Vocabulary Knowledge ◽  
Vocabulary Size ◽  
Efl Learners ◽  
Word Association Test ◽  
Vocabulary Depth ◽  
Two Measures ◽  
Knowledge Scale

Abstract This study compared two tests of second language (L2) depth of vocabulary knowledge, namely the word association test (WAT) and vocabulary knowledge scale (VKS), with respect to their associations with vocabulary size. The same relationships were further examined separately for the five word-frequency bands of the vocabulary size test. To this end, 115 English as a Foreign Language (EFL) learners took the WAT, VKS, and Vocabulary Levels Test (VLT). Results of multiple linear regression analyses indicated that: (a) while both measures of vocabulary depth were predictive of the VLT, the WAT had a higher association with the dependent variable; (b) both the WAT and VKS were predictive of the high-frequency vocabulary, with the relationships being more significant for the WAT; (c) the WAT could significantly predict the mid-frequency vocabulary, whereas the VKS had no significant contribution; and (d) while the VKS was significantly associated with the low-frequency vocabulary, the WAT had no significant contribution to the prediction of this level. The findings are interpreted with reference to the suitability of both the WAT and VKS depending on the type of input, expected response, and desired frequency of the target words.

An Active Learning Approach to Teaching Social Determinants of Health

2020 ◽  
Vol 6 (4) ◽  
pp. 266-273
Author(s):  
Jeanita W. Richardson
Keyword(s):  
Active Learning ◽  
Learning Style ◽  
Social Determinants ◽  
Learning Approach ◽  
Learning Style Preferences ◽  
Open Discussion ◽  
Approach To Teaching ◽  
The Individual ◽  
Style Preferences ◽  
The Impact

This active learning exercise is designed to deconstruct the impact of social determinants through the assumption of randomly selected personas. As an active learning exercise, it provides opportunities for discussion, problem solving, writing, and synthesis, while incorporating multiple learning style preferences. Part 1 involves assessing the individual social determinants at work. Part 2 involves exploring ways said determinants can enhance community health through collaboration. Assumption of personas unlike one’s own facilitates an open discussion of social position and ranges of factors influential to health without potentially evoking a sense of defensiveness associated with personal privilege (or the lack thereof).

scholarly journals Measuring the contribution of specialist vocabulary knowledge to academic achievement: disentangling effects of multiple types of word knowledge

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Ahmed Masrai ◽  
James Milton ◽  
Dina Abdel Salam El-Dakhs ◽  
Heba Elmenshawy
Keyword(s):  
Academic Achievement ◽  
Academic Success ◽  
Success Factors ◽  
Vocabulary Knowledge ◽  
The Other ◽  
Word Knowledge ◽  
Academic Vocabulary ◽  
Vocabulary Size ◽  
Two Factors ◽  
The Impact

AbstractThis study investigates the idea that knowledge of specialist subject vocabulary can make a significant and measurable impact on academic performance, separate from and additional to the impact of general and academic vocabulary knowledge. It tests the suggestion of Hyland and Tse (TESOL Quarterly, 41:235–253, 2007) that specialist vocabulary should be given more attention in teaching. Three types of vocabulary knowledge, general, academic and a specialist business vocabulary factors, are tested against GPA and a business module scores among students of business at a college in Egypt. The results show that while general vocabulary size has the greatest explanation of variance in the academic success factors, the other two factors - academic and a specialist business vocabulary - make separate and additional further contributions. The contribution to the explanation of variance made by specialist vocabulary knowledge is double that of academic vocabulary knowledge.

Collective oscillations in bubble clouds

2011 ◽  
Vol 680 ◽  
pp. 114-149 ◽  
Author(s):  
ZORANA ZERAVCIC ◽  
DETLEF LOHSE ◽  
WIM VAN SAARLOOS
Keyword(s):  
Frequency Response ◽  
Acoustic Field ◽  
Low Frequency ◽  
Acoustic Energy ◽  
Viscous Damping ◽  
Edge States ◽  
Bubble Cloud ◽  
Collective Oscillations ◽  
The Individual ◽  
Bubble Oscillations

In this paper the collective oscillations of a bubble cloud in an acoustic field are theoretically analysed with concepts and techniques of condensed matter physics. More specifically, we will calculate the eigenmodes and their excitabilities, eigenfrequencies, densities of states, responses, absorption and participation ratios to better understand the collective dynamics of coupled bubbles and address the question of possible localization of acoustic energy in the bubble cloud. The radial oscillations of the individual bubbles in the acoustic field are described by coupled linearized Rayleigh–Plesset equations. We explore the effects of viscous damping, distance between bubbles, polydispersity, geometric disorder, size of the bubbles and size of the cloud. For large enough clusters, the collective response is often very different from that of a typical mode, as the frequency response of each mode is sufficiently wide that many modes are excited when the cloud is driven by ultrasound. The reason is the strong effect of viscosity on the collective mode response, which is surprising, as viscous damping effects are small for single-bubble oscillations in water. Localization of acoustic energy is only found in the case of substantial bubble size polydispersity or geometric disorder. The lack of localization for a weak disorder is traced back to the long-range 1/r interaction potential between the individual bubbles. The results of the present paper are connected to recent experimental observations of collective bubble oscillations in a two-dimensional bubble cloud, where pronounced edge states and a pronounced low-frequency response had been observed, both consistent with the present theoretical findings. Finally, an outlook to future possible experiments is given.

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