Linguistic Alternatives to Quantitative Research Strategies Part One: How Linguistic Mechanisms Advance Research

Combining psycholinguistic technologies and systems analysis created advances in motivational profiling and numerous new behavioral engineering applications. These advances leapfrog many mainstream statistical research methods, producing superior research results via cause-effect language mechanisms. Entire industries explore motives ranging from opinion polling to persuasive marketing campaigns, and individual psychotherapy to executive performance coaching. Qualitative research tools such as questionnaires, interviews, and focus groups are now transforming static language data into dynamic linguistic systems measurement technology. Motivational mechanisms, especially linguistic mechanisms, allow specific changes within a motive’s operations. This includes both the choices the intervention creates and its end-goal. Predictable behavior changes are impossible with popular statistical methods. Advanced linguistic research strategies employ motivational change methods with state-of-the -art language and communications modeling

Stereotype in Webkorpora: Strategien zur Suche in sehr großen Datenmengen

Research on stereotypes (as well as on similar constructs such as prejudice, image, identity, etc.) goes back around a century. Most research on stereotypes belongs to the field of psychological, social and cultural studies, with a strong focus on cognitive and socio-cultural phenomena. Since Uta Quasthoff’s pioneering analysis in 1973, there have been several linguistic studies of stereotypes, i. e. on linguistic aspects of how stereotypes are realized in language use. Linguistic research on stereotypes uses methods from disciplines such as sociolinguistics, ethnography, discourse and conversation analysis. Discursive psychology and cognitive linguistics and single studies on stereotypes have used corpus-linguistic methods to explore stereotypes in language use. Nevertheless, we state that no large-scale empirical studies have yet investigated the linguistic realization of stereotypes by using empirical data from large text corpora. In this article, we explore the potential of corpus linguistic approaches in the research on the occurrences of stereotypes in written language. By using an analysis of co-occurrences, we aim to describe the relation between associative semantic stereotypes and co-occurrences in a corpus. Our hypothesis is that the linguistic construction of stereotypes as their realization in language use reproduces stereotypic representations of cognitive conceptualizations and meaning patterns, thus, stereotypic meanings should be detectable in statistical patterns in large corpora

Linguistic Mechanisms Cause Rapid Behavior Change Part Two: How Linguistic Frames Affect Motivation

Written and spoken language contains inherent mechanisms driving motivation. Accessing and modifying psycholinguistic mechanisms, links language frames to changes in behavior within the context of motivational profiling. For example, holding an object like an imported apple feels safe until one is informed it was grown in a toxic waste dump. Instantly linguistic processing changes the apple’s meaning to dangerous. Qualitative data change from static into dynamic measures of motivational changes. Linguistic cause-effect mechanisms dramatically enhance the results and meaning of qualitative research methods, resulting new applications for behavioral engineering, including opinion polling, persuasive marketing campaigns, individual psychotherapy and executive performance coaching. Motivational mechanisms, especially linguistic frames, engineer deliberate and predictable improvements in outcomes, impossible with popular statistical methods

Statistical Machine Translation of Japanese

The purpose of this research was to find ways to improve the performance of a statistical machine translation system that translates text from Japanese to English. Methods included altering the training and test data by adding a prior linguistic knowledge, altering sentence structures, and looking for better ways to statistically alter the way words align between the two languages. In addition, methods for properly segmenting words in Japanese text through statistical methods were examined. Finally, experiments were conducted on Japanese speech to produce the best text transcription of the speech. The best statistical machine translation methods implemented resulted in improvements that rivaled the best evaluations from the 2005 International Workshop on Spoken Language Translation from which training and test data was used. Recommendations, including how the methods presented may be altered for further improvements for future research, are also discussed

An extensive empirical study of collocation extraction methods

This paper presents a status quo of an ongoing research study of collocations – an essential linguistic phenomenon having a wide spectrum of applications in the field of natural language processing. The core of the work is an empirical evaluation of a comprehensive list of automatic collocation extraction methods using precision-recall measures and a proposal of a new approach integrating multiple basic methods and statistical classification. We demonstrate that combining multiple independent techniques leads to a significant performance improvement in comparisonwith individualbasic methods. 1 Introduction an

The Effect of Task Modality in Heritage Bilingualism Research

[EN] Knowledge of the effects of task design features on linguistic performance is essential to obtain the right conclusions in linguistic research. Several studies have explored the effects of task modality in second language learners (Johnson, 1992; Murphy, 1997; Shiu, Yalçin, & Spada, 2018). These studies showed that L2 learners perform better when the stimulus is presented in written form compared to aural form. However, the effect of task modality in linguistic performance is an area that needs exploration in the field of heritage bilingualism research (Jegerski, 2018). Thus, the purpose of this study is to determine the effects of task modality on linguistic performance in heritage bilinguals. Participants in this study included 63 heritage bilinguals divided into high- and low-proficiency groups. All participants completed a proficiency test, a language background questionnaire, an aural speeded acceptability judgment task, and a written speeded acceptability judgment task. The statistical analysis revealed a significant effect of task modality on linguistic performance. High-proficiency heritage bilinguals performed significantly better (i.e., shorter reaction times) when the stimuli were presented in aural form. The results of this study contribute to the existing body on research methods in linguistic and specifically, to the effects that design features may have on linguistic performance in heritage bilinguals.Iranzo, V. (2022). The Effect of Task Modality in Heritage Bilingualism Research. Revista de Lingüística y Lenguas Aplicadas. 17:59-70. https://doi.org/10.4995/rlyla.2022.16513OJS59701

A Second Language Acquisition Toolkit for Teaching Introduction to Computing

Introduction to Computing and higher-level programming courses are common first-year engineering curricula at the university level and are key in developing logical thought processes in engineering students. Recent research has shown that employing second language acquisition (SLA) techniques to teach programming increases exam performance and student motivation compared to more classical approaches. However, the presentation of pedagogical techniques has been largely limited to higher-level languages with more intuitive linguistic analogs and has not been extended to lower-level computing course material. In this paper we present several SLA techniques and their analogs in a computing course setting and the results of implementing an SLA strategy in a first-year engineering course. Statistical analysis shows that students taught with SLA methods completed quizzes more quickly, enjoyed recitation more, and had a higher perceived value of the class when compared with students taught with non-SLA techniques.Cockrell School of Engineerin