Review of Digital language learning and teaching: Research, theory, and practice

This edited book, organized into a preface, an introduction, and 19 chapters, is grouped into two main parts: Part I, The research perspective (the first 10 chapters after the introduction) and Part II, The pedagogical perspective (the last nine chapters). Part I presents the findings of some of the doctoral research funded by Doctoral Dissertation Grants from The International Research Foundation, while Part II, written by more seasoned researchers with remarkable experience in the use of technology in language education, places a focus on key advancement in digital language learning, teaching, and assessment

Interview With Dr. Luke Plonsky

Luke Plonsky is Assistant Professor of Applied Linguistics at Northern Arizona University. His research interests include instructed second language acquisition, quantitative research methods with a specific focus on study designs, the use of statistics, research synthesis, and meta-analysis. He gave the keynote address at the Second Language Studies Symposium at Michigan State University. This interview was conducted on February 21, 2014. For more information about Dr. Plonsky, please visit his website: http://oak.ucc.nau.edu/ldp3/index.htm

An Investigation of the Predictors of Statistical Literacy in Second Language Acquisition

The use of statistics in second language acquisition (SLA) research has increased over the past 30-40 years and continues to increase in both complexity and sophistication (Gass, 2009; Loewen & Gass, 2009). The increased use of statistical procedures has drawn attention to the current state of statistical literacy among second language (L2) researchers. Statistical literacy is a critical skill to acquire on the parts of both the producers and consumers of L2 research. However, it is a relatively new research topic in the field. So, little is known regarding what factors play key roles in the development of statistical literacy. Therefore, this study attempted to investigate the predictors of statistical literacy in SLA. One hundred and twenty SLA doctoral students took a statistical background questionnaire and a discipline-specific statistics survey. A series of multiple regression analyses were conducted on the statistics survey data. The results indicated that number of statistics courses taken, quantitative research orientation, and self-training in statistics were the significant predictors of statistical literacy. In light of the findings of this study, several suggestions directed toward improving statistical literacy in the field of SLA were made

To Err is Human: An error analysis approach to Turkish as an L2

In this study we investigate which aspects of Turkish pose particular challenges for English-speaking learners. The data are from a large pool of university LCTL learners who responded to five pre-recorded speaking prompts. They audio-recorded their speech twice a semester for up to three consecutive semesters using a virtual interview assessment tool called VOICES. Each interview lasted about 10 minutes. We identified and analyzed the various types and frequencies of grammatical and lexical errors that emerged in the Turkish speech from twelve English-speaking learners of Turkish. The results indicate that English-speaking learners of Turkish had problems with the Turkish case-marking system, subject-verb agreement, singularity/plurality, near synonyms and lexical shifts. Consistent with previous L2 Turkish studies, we found that some of the errors can be attributed to the fact that Turkish is an agglutinative language while English is isolating. We discuss how analyses of this type can improve LCTL instruction

Statistical Literacy of SLA/AL Researchers

Investigating the statistical literacy of SLA /AL researchers with an objective measure. See the 'Files' tab/window to access data and materials for the study. Study published in SSLA: https://doi.org/10.1017/S027226311900054