Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
Hostname: page-component-586b7cd67f-rdxmf Total loading time: 0 Render date: 2024-11-28T07:11:59.723Z Has data issue: false hasContentIssue false

4 - The High-Level Language Aptitude Battery (Hi-LAB)

Development, Validation, and Use

from Part I - Revisiting and Refining Aptitude Tests

Published online by Cambridge University Press:  27 May 2023

By
Meredith Hughes ,
Ewa Golonka ,
Alison Tseng  and
Susan Campbell
Edited by
Zhisheng (Edward) Wen ,
Peter Skehan  and
Richard L. Sparks
Zhisheng (Edward) Wen
Affiliation:
Hong Kong Shue Yan University
Peter Skehan
Affiliation:
Institute of Education, University of London
Richard L. Sparks
Affiliation:
Mount St Joseph University
Get access

Summary

The High-Level Language Aptitude Battery (Hi-LAB) measures the cognitive and perceptual abilities hypothesized to be important for adults to reach advanced levels of foreign language proficiency (Doughty, 2019; Doughty et al., 2010; Linck et al., 2013). This chapter will provide a historical overview of the Hi-LAB and its use, starting from the selection of constructs to measure, development of the battery, exploration of the battery’s measurement properties, and its use today. Over 15 years of work have been dedicated to selecting, refining, and validating the measures of the battery. We will explore how University of Maryland researchers as well as those of wider academia have used the battery to explore aspects of language aptitude, most notably, perhaps, the potential for Hi-LAB to inform language aptitude-by-treatment interventions. Potential directions for future work will also be discussed, pointing ahead to how the battery can continue to provide valuable aptitude information for language learning across populations, including language learners themselves, language instructors, academic researchers, and organizations who are interested in training personnel in new languages.

Keywords

language aptitudeHi-LABaptitude-by-treatmentreliabilityvalidity
Type
Chapter
Information
Language Aptitude Theory and Practice , pp. 73 - 93
Publisher: Cambridge University Press
Print publication year: 2023

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Brooks, P. J., Kempe, V., & Sionov, A. (2006). The role of learner and input variables in learning inflectional morphology. Applied Psycholinguistics, 27(2), 185–209.Google Scholar
Carroll, J. B. (1965). The prediction of success in intensive foreign language training. In Glaser, R. (ed.), Training, Research, and Education. New York: Wiley, pp. 87–136.Google Scholar
Carroll, J. B. (1990). Cognitive abilities in foreign language aptitude: Then and now. In Parry, T. S. & Stansfield, C. W. (eds.), Language Aptitude Reconsidered. Washington, DC: Center for Applied Linguistics, pp. 11–29.Google Scholar
Carroll, J. B., & Sapon, S. (1959). Modern Language Aptitude Test (MLAT). San Antonio, TX: Psychological Corporation. Republished in 2002 at Rockville, MD: Language Learning and Testing Foundation.Google Scholar
Cronbach, L., & Snow, R. (1977). Aptitudes and Instructional Methods: A Handbook for Research on Interactions. New York: Irvington.Google Scholar
Doughty, C. J. (2019). Cognitive language aptitude. Language Learning, 69(S1), 101–126. https://doi.org/10.1111/lang.12322Google Scholar
Doughty, C. J., Campbell, S. G., Mislevy, M. A., Bunting, M. F., Bowles, A. R., & Koeth, J. T. (2010, December). Predicting near-native ability: The factor structure and reliability of Hi-LAB. In Selected Proceedings of the 2008 Second Language Research Forum. Somerville, MA: Cascadilla Proceedings Project, pp. 10–31).Google Scholar
Doughty, C. J., Campbell, S. G., Mislevy, M., Kenyon, D., & Fidelman, C. (2008). TTO 2105 Technical Report E.1.1: Research Design (Technical Report). College Park, MD: University of Maryland Center for Advanced Study of Language.Google Scholar
Doughty, C., Campbell, S. G., Bunting, M. F., Bowles, A. R., & Haarmann, H. (2007). Final M.4 Deliverable: The development of the High-Level Language Aptitude Battery (Technical Report). College Park, MD: University of Maryland Center for Advanced Study of Language.Google Scholar
Gass, S., & Mackey, A. (2006). Input, interaction, and output: An overview. Themes in SLA research. AILA Review, 19(1), 3–17.Google Scholar
Goo, J. (2012). Corrective feedback and working memory capacity in interaction-driven L2 learning. Studies in Second Language Acquisition, 34(3), 445–474.Google Scholar
Granena, G. (2019). Cognitive aptitude and L2 speaking proficiency: Links between LLAMA and Hi-LAB. Studies in Second Language Acquisition, 41(2), 313–336. https://doi.org/10.1017/S0272263118000256Google Scholar
Huber, D. E., & O’Reilly, R. C. (2003). Persistence and accommodation in short-term priming and other perceptual paradigms: Temporal segregation through synaptic depression. Cognitive Science: A Multidisciplinary Journal, 27(3), 403–430.Google Scholar
Jackson, S. J., Tseng, A. M., Tare, M., & Hughes, M. M. (2017). The Role of Language Aptitude and Language Learning Background at FSI: Validity of the MLAT and Hi-LAB as Measures of Language Aptitude (Technical Report). College Park, MD: University of Maryland Center for Advanced Study of Language.Google Scholar
Linck, J. A., Hughes, M. M., Campbell, S. G., et al. (2012). Hi-LAB Identified Successful High-Proficiency Language Learners: Results of the Group Discrimination Study (Technical Report). College Park, MD: University of Maryland Center for Advanced Study of Language.Google Scholar
Linck, J. A., Hughes, M. M., Campbell, S. G., et al. (2013). Hi-LAB: A new measure of aptitude for high-level language proficiency. Language Learning, 63(3), 530–566. https://doi.org/10.1111/lang.12011Google Scholar
Long, M. H. (1985). Input and second language acquisition theory. In Gass, S. & Madden, C. (eds.), Input in Second Language Acquisition. Rowley, MA: Newbury House, pp. 377–393.Google Scholar
Meara, P. M. (2005). LLAMA Language Aptitude Tests. Swansea, UK: Lognostics.Google Scholar
Mislevy, M. A., Linck, J. A., Campbell, S. G., et al. (2010). Predicting High-Level Foreign Language Learning: A New Aptitude Battery Meets Reliability Standard for Personnel Selection Tests (Technical Report). College Park, MD: University of Maryland Center for Advanced Study of Language.Google Scholar
Perrachione, T. K., Lee, J., Ha, L. Y. Y., & Wong, P. C. M. (2011). Learning novel phonological contrasts depends on interactions between individual differences and training paradigm design. Journal of the Acoustical Society of America, 130(1), 461–472.Google Scholar
Petersen, C. R., & Al-Haik, A. R. (1976). The development of the Defense Language Aptitude Battery (DLAB). Educational and Psychological Measurement, 36(2), 369–380. https://doi.org/10.1177/001316447603600216Google Scholar
Robinson, P. (2001). Individual differences, cognitive abilities, aptitude complexes and learning conditions in second language acquisition. Second Language Research, 17(4), 368–392. https://doi.org/10.1177/026765830101700405Google Scholar
Sheen, Y. (2007). The effect of focused written corrective feedback and language aptitude on ESL learners’ acquisition of articles. TESOL Quarterly, 41(2), 255–283.Google Scholar
Tseng, A., Greiner, J., Levitas, D., et al. (2015). The Hi-LAB Longitudinal Predictive Validity Study: Second Year Accomplishments and Next Steps (Technical Report). College Park, MD: University of Maryland Center for Advanced Study of Language.Google Scholar
Vatz, K., Tare, M., Jackson, S., & Doughty, C. J. (2013). Aptitude–treatment interaction studies in second language acquisition: Findings and methodology. In Granena, G. & Long, M. H. (eds.), Sensitive Periods, Language Aptitude, and Ultimate L2 Attainment. Amsterdam: John Benjamins, pp. 273–292.Google Scholar
Yilmaz, Y., & Granena, G. (2019). Cognitive individual differences as predictor of improvement and awareness under implicit and explicit feedback conditions. The Modern Language Journal, 103(2), 686–702. https://doi.org/10.1111/modl.12587Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×