scholarly journals Bayesian vocabulary tests

2021 ◽  
pp. 177-205
Author(s):  
Paul M. Meara ◽  
Inma Miralpeix
Keyword(s):  
Bayesian Statistics ◽  
Bayesian Methods ◽  
Vocabulary Test ◽  
Proficiency Levels ◽  
L1 And L2 ◽  
Picture Prompts

This paper proposes a new way of looking at productive vocabulary in L1 and L2 speakers. An experiment was conducted where 160 participants provided six words for five different picture prompts they were presented with. Data from this minimal vocabulary test was analysed using Bayesian statistics in order to decide whether a set of responses were generated by an L1 speaker or by an L2 advanced learner. Results obtained provide some interesting insights into the viability of minimal vocabulary tests (small sets of words can carry large amounts of information on vocabulary use), as well as some indications of how Bayesian methods could help us explore productive vocabularies of L2 speakers at different proficiency levels.

scholarly journals Does Proficiency Level Affect Learners’ Lexical Access in L1 and L2?

2021 ◽  
Vol 15 (1) ◽  
pp. 56-67
Author(s):  
Muzakki Bashori
Keyword(s):  
Lexical Access ◽  
Doctoral Degree ◽  
Degree Programs ◽  
Language Performance ◽  
Proficiency Levels ◽  
Paired Samples ◽  
Proficiency Level ◽  
Doctoral Degree Programs ◽  
Insignificant Difference ◽  
L1 And L2

Proficiency level is one important factor that contributes to learners’ language performance. Learners with higher proficiency levels tend to perform lexical access better and faster than those with lower proficiency. This study aims to investigate whether proficiency level affects lexical access in L1 and L2. The research involved seven Indonesian university students of master’s and doctoral degree programs at a university in the Netherlands who possess different proficiency levels. Two scrambled texts in the participants’ L1 and L2 were employed to test the participants. Meanwhile, the paired-samples t-test and correlation analysis were used to report the experiment. The results revealed an insignificant difference and a negative correlation between proficiency level and the number of errors and reading time. However, on average, the more proficient learners outperformed the less proficient, thus indicating that they may possess more complex lexical access in L1 and L2. Further studies are needed to provide other useful insights on this topic.

What Teachers Need to Know About English Language Learners' Translanguaging in the Classroom

2019 ◽  
pp. 109-126
Author(s):  
Laila Aghai
Keyword(s):  
English Language Learners ◽  
Language Learners ◽  
English Language ◽  
Native Language ◽  
Esl Students ◽  
Negotiation Of Meaning ◽  
Qualitative Research Study ◽  
Proficiency Levels ◽  
L1 And L2 ◽  
The U.S

This qualitative research study focuses on English language learners who are continuing their education in the U.S. high schools and examines their translanguaging in the classroom. When students are learning a second language, they use their linguistic repertoire and their knowledge in English and their native language for negotiation of meaning. In order to gain a better understanding of the students' translanguaging, one ESL teacher and 10 ESL students were interviewed and observed in a classroom. The ESL students spoke Arabic as their native language and had beginning to intermediate proficiency levels. The findings of the study showed that English language learners use various strategies to make the content comprehensible by making connections between their knowledge in their L1 and L2.

Using eye-tracking to examine the role of first and second language glosses

2020 ◽  
pp. 136216882092856
Author(s):  
Hyeonah Kang ◽  
Soo-Ok Kweon ◽  
Sungmook Choi
Keyword(s):  
Second Language ◽  
Eye Tracking ◽  
Vocabulary Test ◽  
Eye Tracker ◽  
Reading Behaviors ◽  
Word Forms ◽  
Comprehensive Picture ◽  
L1 And L2 ◽  
The Relationship

This study employs eye-tracking to investigate how first (L1) and second language (L2) glosses affect lexical uptake and reading behaviors in L2 learners of English. The study also explores the relationship between lexical uptake and reading behaviors as a function of gloss type. To investigate this, 81 Korean university students were asked to read a baseline passage with no gloss or the same passage with glosses in the study’s L1 (Korean) or L2 (English). Their eye movements were recorded with an eye tracker as they read, and they were subsequently asked to respond to two vocabulary tests. Analyses of eye-tracking data and vocabulary test scores revealed that the presence or absence of L1 and L2 glosses might produce differences in lexical uptake and dissimilar attentional mechanisms. For instance, the study found that L1 and L2 glosses failed to significantly enhance the acquisition of visual word forms, whereas both types of glosses were significantly effective in consolidating form–meaning associations. Additionally, correlation analyses indicated that the relationship between reading behaviors and lexical acquisition might differ depending on gloss type. Ultimately, our findings provide a more comprehensive picture of L1 and L2 gloss effects, and have significant implications for L2 pedagogy.

Pointing backward and forward

2016 ◽  
Vol 7 (1) ◽  
pp. 89-116 ◽  
Author(s):  
Franco Pauletto ◽  
Camilla Bardel
Keyword(s):  
Qualitative Analysis ◽  
Native Speakers ◽  
Data Sets ◽  
Advanced Level ◽  
Discourse Marker ◽  
Proficiency Levels ◽  
Social Actions ◽  
Different Types ◽  
L1 And L2 ◽  
Qualitative Analyses

In this study, we analyze the kind of actions L1 and L2 speakers of Italian perform by prefacing their responsive turns with the discourse marker be’. As a baseline, the article begins with an analysis of how native speakers of Italian use be’. We then carry out quantitative and qualitative analyses of the use of be’ in a number of L2 learners at different proficiency levels from three data sets of different types of interactions between students and native speakers of Italian. In the qualitative analysis, we adopt a conversation analytic perspective. The results suggest that both native speakers and L2 speakers, from intermediate to advanced level, perform a variety of social actions by be’-prefacing their responsive turns.

scholarly journals Bayesian statistics meets sports: a comprehensive review

2019 ◽  
Vol 15 (4) ◽  
pp. 289-312
Author(s):  
Edgar Santos-Fernandez ◽  
Paul Wu ◽  
Kerrie L. Mengersen
Keyword(s):  
Bayesian Statistics ◽  
Bayesian Methods ◽  
Bayesian Computation ◽  
Sports Analytics ◽  
Software Packages ◽  
Model Complex ◽  
Comprehensive Survey ◽  
Number Of Publications ◽  
Combine Information ◽  
Sports Activities

AbstractBayesian methods are becoming increasingly popular in sports analytics. Identified advantages of the Bayesian approach include the ability to model complex problems, obtain probabilistic estimates and predictions that account for uncertainty, combine information sources and update learning as new data become available. The volume and variety of data produced in sports activities over recent years and the availability of software packages for Bayesian computation have contributed significantly to this growth. This comprehensive survey reviews and characterizes the latest advances in Bayesian statistics in sports, including methods and applications. We found that a large proportion of these articles focus on modeling/predicting the outcome of sports games and on the development of statistics that provides a better picture of athletes’ performance. We provide a description of some of the advances in basketball, football and baseball. We also summarise the sources of data used for the analysis and the most commonly used software for Bayesian computation. We found a similar number of publications between 2013 and 2018 as compared to those published in the three previous decades, which is an indication of the growing adoption rate of Bayesian methods in sports.

In praise of Ecumenical Bayes

2011 ◽  
Vol 34 (4) ◽  
pp. 206-207 ◽  
Author(s):  
Michael D. Lee
Keyword(s):  
Statistical Analysis ◽  
Bayesian Statistics ◽  
Bayesian Methods ◽  
Bayesian Models

AbstractJones & Love (J&L) should have given more attention to Agnostic uses of Bayesian methods for the statistical analysis of models and data. Reliance on the frequentist analysis of Bayesian models has retarded their development and prevented their full evaluation. The Ecumenical integration of Bayesian statistics to analyze Bayesian models offers a better way to test their inferential and predictive capabilities.

Null-hypothesis tests are not completely stupid, but Bayesian statistics are better

1998 ◽  
Vol 21 (2) ◽  
pp. 215-216 ◽  
Author(s):  
David Rindskopf
Keyword(s):  
Hypothesis Testing ◽  
Bayesian Statistics ◽  
Statistical Methods ◽  
Bayesian Methods ◽  
Null Hypothesis ◽  
Hypothesis Tests ◽  
Null Hypothesis Testing ◽  
Preferred Solutions ◽  
The Way

Unfortunately, reading Chow's work is likely to leave the reader more confused than enlightened. My preferred solutions to the “controversy” about null- hypothesis testing are: (1) recognize that we really want to test the hypothesis that an effect is “small,” not null, and (2) use Bayesian methods, which are much more in keeping with the way humans naturally think than are classical statistical methods.

Bayesian Basics and the Scientific Hypothesis

2019 ◽  
pp. 143-160
Author(s):  
Bradley E. Alger
Keyword(s):  
Model Selection ◽  
Hypothesis Testing ◽  
Conceptual Framework ◽  
Bayesian Statistics ◽  
Bayesian Methods ◽  
Bayes Theorem ◽  
Testing Framework ◽  
Parameter Evaluation ◽  
Bayesian Procedures ◽  
Scientific Hypothesis

This chapter covers the basics of Bayesian statistics, emphasizing the conceptual framework for Bayes’ Theorem. It works through several iterations of the theorem to demonstrate how the same equation is applied in different circumstances, from constructing and updating models to parameter evaluation, to try to establish an intuitive feel for it. The chapter also covers the philosophical underpinnings of Bayesianism and compares them with the frequentist perspective described in Chapter 5. It addresses the question of whether Bayesians are inductivists. Finally, the chapter shows how the Bayesian procedures of model selection and comparison can be pressed into service to allow Bayesian methods to be used in hypothesis testing in essentially the same way that various p-tests are used in the frequentist hypothesis testing framework.

Bayesian Statistics in Archaeology

2018 ◽  
Vol 47 (1) ◽  
pp. 435-453 ◽  
Author(s):  
Erik Otárola-Castillo ◽  
Melissa G. Torquato
Keyword(s):  
Bayesian Inference ◽  
Bayesian Statistics ◽  
Bayesian Methods ◽  
Null Hypothesis ◽  
Significance Testing ◽  
Archaeological Research ◽  
Historical Overview ◽  
Spatial Analyses ◽  
Null Hypothesis Significance Testing ◽  
Statistical Framework

Null hypothesis significance testing (NHST) is the most common statistical framework used by scientists, including archaeologists. Owing to increasing dissatisfaction, however, Bayesian inference has become an alternative to these methods. In this article, we review the application of Bayesian statistics to archaeology. We begin with a simple example to demonstrate the differences in applying NHST and Bayesian inference to an archaeological problem. Next, we formally define NHST and Bayesian inference, provide a brief historical overview of their development, and discuss the advantages and limitations of each method. A review of Bayesian inference and archaeology follows, highlighting the applications of Bayesian methods to chronological, bioarchaeological, zooarchaeological, ceramic, lithic, and spatial analyses. We close by considering the future applications of Bayesian statistics to archaeological research.

Bayesian Statistics in Sociology: Past, Present, and Future

2019 ◽  
Vol 45 (1) ◽  
pp. 47-68 ◽  
Author(s):  
Scott M. Lynch ◽  
Bryce Bartlett
Keyword(s):  
Social Science ◽  
Bayesian Statistics ◽  
Bayesian Approach ◽  
Bayesian Methods ◽  
Bayes Theorem ◽  
Widespread Application ◽  
Software Packages ◽  
The Future ◽  
Direct Use ◽  
The Bayesian Approach

Although Bayes’ theorem has been around for more than 250 years, widespread application of the Bayesian approach only began in statistics in 1990. By 2000, Bayesian statistics had made considerable headway into social science, but even now its direct use is rare in articles in top sociology journals, perhaps because of a lack of knowledge about the topic. In this review, we provide an overview of the key ideas and terminology of Bayesian statistics, and we discuss articles in the top journals that have used or developed Bayesian methods over the last decade. In this process, we elucidate some of the advantages of the Bayesian approach. We highlight that many sociologists are, in fact, using Bayesian methods, even if they do not realize it, because techniques deployed by popular software packages often involve Bayesian logic and/or computation. Finally, we conclude by briefly discussing the future of Bayesian statistics in sociology.

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