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Part of
Methods in Study Abroad Research: Past, present, and future
Edited by Carmen Pérez-Vidal and Cristina Sanz
[Research Methods in Applied Linguistics 4] 2023
► pp. 33–58

Chapter 2
Quantitative approaches in L2 research abroad

| Temple University
| The University of Tennessee, Knoxville
This chapter provides an overview and discussion of quantitative research designs that investigate learning outcomes in immersion settings abroad. We begin with a brief introduction to the underlying assumptions, key concepts, and overarching goals of quantitative research approaches for investigating learner development. We then summarize the core contributions of quantitative approaches in study abroad research, with attention to primary study designs, instruments, and measures employed to examine linguistic outcomes, individual differences, and other central aspects of learners’ experiences abroad. This section is followed by a critical discussion of the main methodological limitations associated with this strand of research. Lastly, we propose ways to address these limitations and to achieve more robust and generalizable findings in future quantitative study abroad research.
Keywords: quantitative designs, validity, reliability, generalizability, correlational/associational, experimental/quasi-experimental, statistics, between- vs. within-subjects designs, multisite research
Article outline
  • Introduction
  • Core contributions of quantitative approaches
    • Types of study design
    • Linguistic outcome measures
    • Global proficiency measures
    • Oral production measures: Complexity, accuracy, and fluency
    • Measures of linguistic knowledge and processing
    • Other tools and measures
    • Individual difference measures
    • Psychosocial factors
    • Linguistic factors
    • Cognitive factors
    • Learner experiences and language contact measures
  • Limitations
    • Methodological design
    • Instruments and operational measures
    • Statistical considerations
  • Strategies and guiding principles for addressing limitations
    • Recommendation 1: Expand within-subjects designs
    • Recommendation 2: Adopt a systematic selection of instruments and measures
    • Recommendation 3: Employ robust and other advanced statistical techniques
    • Recommendation 4: Adopt mixed-methods approaches
  • Conclusion
  • References
Published online: 3 February 2023
DOI logo
https://doi.org/10.1075/rmal.4.02zal
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