Recent Contributions of Data Mining to Language Learning Research

Abstract

This paper will review the role of data mining in research on second language learning. Following a general introduction to the topic, three areas of data mining research will be summarized—clustering techniques, text-mining, and social network analysis—with examples from both the broader field and studies conducted by the authors. The application of data mining in second language learning research is relatively new, and more theoretical and empirical support is needed in the appropriate collection, use, and interpretation of data for specific research and pedagogical objectives. The three examples that we introduce illustrate how new data sources accessible in online environments can be analyzed to better understand the optimal instructional context for corpus-based vocabulary learning (clustering technique), characteristics and patterns of collaborative written interaction using Google Docs (text mining and visualizations), and issues of access and community in computer-mediated discussion (social network analysis). Implications of these new techniques for L2 research will be discussed.

Dynamics of Language Learning Motivation and Emotions: A Parallel-Process Growth Mixture Modeling Approach

“…The present study adopts a GMM technique, a modeling-based technique with strong validity ( Warschauer et al, 2019 ), which has also been recently applied in general learning motivation research (e.g., Guay et al, 2021 ; Lee and Ju, 2021 ). GMM as an extension of the latent growth curve model (LGCM; Bollen and Curran, 2006 ) specifies two parameters (i.e., intercept and slope) that can capture the general trend and temporal changes of individual development over time.…”

A Case Study of ASEAN EFL Learners’ Collaborative Writing and Small Group Interaction Patterns in Google Docs

“…DocuViz has enabled writing teachers to visualize group interaction, member contributions, and assist in understanding L2 writing behaviour. Therefore, it can be used to help learners improve their writing skills (Olson et al, 2017), as a consequence of the visualization of changes or edits made to the shared document over time (Wang et al, 2015;Warschauer et al, 2019).…”

“…It enables a deeper understanding of content and produces better quality of writing (Abe, 2020;Coffin, 2020;Limbu & Markauskaite, 2015); it increases writing accuracy and vocabulary acquisition Dobao, 2014;Latifi, Norrozi, & Talaee, 2021;McDonough & De Vleeschauwer, 2019); and it provides opportunities for learners to brainstorm, give feedback, and create meaning (Alghasab, Hardman, & Handley, 2019;Bhowmik, Hilman, & Roy, 2019;Coffin, 2020;Dong, Y., & Liu, 2020;Storch, 2011). Some researchers have employed web-based collaborative writing (WBCW) tools such as Google Docs (henceforth GD) or Wikis to investigate learners' interaction patterns (Cho, 2017;Li & Kim, 2016;Li & Zhu, 2017;Yanguas, 2020) or different styles and characteristics of CW detected through DocuViz, a data visualization tool (Olson, Wang, Olson, & Zhang, 2017;Warschauer, Yim, Lee, & Zheng, 2019;Yim, Wang, Olson, Vu, & Warschauer, 2017). Although WBCW has gained the interest of researchers due to its writing skill potential (Ansarimoghaddam, Hoon, & Yong, 2017;McDonough & De Vleeschauwer, 2019;Yanguas, 2020), scant research has been undertaken on the collaboration and interaction occurring naturally in small groups of tertiary students from linguistically and culturally diverse backgrounds in the Association of Southeast Asian Nations (ASEAN) context.…”

The Uses of Machine Learning (ML) in Teaching and Learning English Language: A Methodical Review.

“…Papi and Teimouri (2014) classified the motivations of language learners by employing clustering techniques. It has been demonstrated by Warschauer et al (2019) that gathering algorithms can aid in the learning of new vocabulary terms. Crowther and colleagues (2020) undertook a thorough review of the applications of clustering algorithms in second-language studies, published in the second Language Studies journal.…”