Renato Pavlekovic
-
Email
r.pavlekovic@essex.ac.uk -
Location
Colchester Campus
Profile
- Explicit and implicit knowledge and their interface
- Aptitude for implicit and explicit learning
- Measures of cognitive individual differences
- Linear and nonlinear mixed-effects modeling
- Factor analysis and structural equation modeling
- Unsupervised learning (k-means and hierarchical)
Biography
Renato is a data scientist and quantitative researcher at the University of Essex, specializing in the cognitive processes involved in second language (L2) learning. His research explores how individual differences such as language aptitude and working memory impact L2 acquisition. A key aspect of his work is examining how these cognitive abilities interact with L2 proficiency and the difficulty of linguistic structures. With expertise in both cross-sectional and longitudinal research designs, Renato applies advanced statistical and machine learning techniques to analyze language learning patterns. His methodological approach includes regression analysis, multilevel modeling, structural equation modeling, and unsupervised learning methods like cluster analysis. His work bridges data science and cognitive research, leveraging quantitative methods to uncover insights into how cognitive abilities influence language learning outcomes. Committed to advancing the field, Renato is developing and validating measures of both implicit and explicit learning aptitude, along with language assessment tools that gauge implicit and explicit knowledge. His current work focuses on improving the reliability and validity of existing tasks aimed at measuring implicit aptitude, with the broader objective of eventually developing a comprehensive battery of tests for assessing implicit aptitude more effectively. Ultimately, his goal is to contribute to the development of more effective language learning strategies that benefit both research and teaching. Renato is also dedicated to sharing his findings through academic publications, conferences, and collaborations. Published work: - Pavlekovic, R., & Roehr-Brackin, K. (2024). Aptitude for Explicit and Implicit Learning. Journal of the European Second Language Association, 8(1), 117. https://doi.org/10.22599/jesla.117 - Roehr-Brackin, K., Baranowska, K., Pavlekovic, R., Scheffler, P. (2024). The role of individual learner differences in explicit language instruction. The Modern Language Journal. https://doi.org/10.1111/modl.12963 - Roehr-Brackin, K., Loaiza, V., & Pavlekovic, R. (2023). Language learning aptitude in older adults. Journal of the European Second Language Association, 7(1), 115. https://doi.org/10.22599/jesla.93 Under review: - Pavlekovic, R. (under review). At the interface of language aptitude and L2 knowledge. - Pavlekovic, R., & Roehr-Brackin, K. (under review). Finding the tipping point: Proficiency as a mediator of cognitive ability in L2 learning. Studies in Second Language Acquisition. - Roehr-Brackin, K. & Pavlekovic, R. (under review). Language learning aptitude as a predictor of late-life L2 learning at beginner level. Language Teaching Research. Work in preparation: - Pavlekovic, R. (in preparation). Validity and reliability of language aptitude and working memory measures in SLA. - Roehr-Brackin, K., Baranowska, K., Pavlekovic, R., Scheffler, P. (in preparation). Inductive instruction at beginner level: The contribution of metalinguistic awareness at the earliest stages of adult L2 learning. Language Awareness. Recognizing the challenges faced by researchers in accessing affordable and specialized tools, Renato founded LinguisticLab.org, a web-based platform for conducting cognitive and psycholinguistic experiments, including tasks like the Serial Reaction Time (SRT) task and the Operation Span (OSPAN) task. Unlike other available tools which are often expensive and not tailored for linguistic research LinguisticLab.org provides free, accessible resources, with plans to expand the range of experiments offered in the near future.
Qualifications
-
BSc Computer Science (2016)
-
MA TESOL (2018)
-
PhD Applied Linguistics (2025)
Research and professional activities
Thesis
Language learning aptitude and working memory in L2 acquisition: The role of proficiency and structure difficulty
This study examines how language aptitude influences L2 learning, focusing on proficiency and linguistic structure difficulty. Findings reveal that explicit aptitude is crucial at lower proficiency, while implicit aptitude gains importance at advanced levels. Structure difficulty amplifies the effects of explicit aptitude but not implicit aptitude. The research supports the multicomponential nature of aptitude and highlights a bidirectional interface between implicit and explicit knowledge.
Supervisor: Dr Karen Roehr-Brackin
Research interests
Explicit and implicit knowledge and learning
As a researcher in second language acquisition, my focus is on the investigation of explicit and implicit language knowledge. Explicit knowledge involves conscious awareness of the linguistic structure, while implicit knowledge is acquired subconsciously through exposure and interaction. Understanding the interaction of these knowledge types (the interface issue) is crucial for effective second language learning. My research provides insights into effective second language learning methods.
Language aptitude and working memory in SLA
Explicit and implicit language aptitude and working memory play a significant role in second language acquisition. Specifically, the intricate interplay between these factors is critical for comprehending individual differences in SLA. My research aims to investigate this interplay and its effect on successful SLA by examining the extent to which language aptitude and working memory predict second language proficiency, as well as the underlying mechanisms that mediate this relationship.
Reaction time measures in applied linguistics
My research interest lies in the use of reaction time (RT) experiments in applied linguistics. Specifically, I am interested in developing and validating RT-based measures to assess various aspects of language processing in second language contexts. RT experiments have the potential to provide valuable insights into the cognitive mechanisms underlying language use and acquisition. I aim to contribute to the refinement and advancement of RT methods for investigating language processing.
Measures of explicit and implicit language aptitude
I focus on validating and refining the measures of explicit and implicit language aptitude, such as LLAMA (Language Learning and Aptitude Measurement in Adults) and SRT (Serial Reaction Time) tasks. LLAMA (putatively) measures explicit and implicit language aptitude, while SRT measures implicit language aptitude. By exploring their relationship with other factors like working memory I aim to deepen the understanding of individual differences in second language learning.
Statistical models in linguistics
My research interest lies in exploring the application of advanced statistical techniques, such as Rasch analysis, regression analysis, factor analysis, and structural equation modeling in the examination of complex linguistic data. Specifically, I am focused on developing innovative and robust statistical methods that can effectively model and interpret linguistic data, with the ultimate goal of contributing to the advancement of the field of applied linguistics.
