A Dynamic Systems Study on Complexity, Accuracy, and Fluency in English Writing Development by Chinese University Students

Abstract

This study investigated the development of lexical complexity, sentence complexity, accuracy, and fluency in the English writing of 22 Chinese university students from the perspective of Complex Dynamic Systems Theory (CDST). Compositions were assigned 30 times over the course of one academic year through Pigaiwang, an online platform that automatically evaluates writing. A modified retrodictive modeling approach was adopted. Specifically, a longitudinal cluster analysis was used to examine emergent prototypes. A moving correlation analysis and retrodictive interviews were conducted to study the signature dynamics that produce each prototype. At each collection, the 22 student compositions were classified into two clusters. One cluster contained those students who performed better than average in accuracy, but worse in the other three variables. The other cluster comprised those students with the opposite performance. Students moved continuously between the two clusters; and their change trajectories can be categorized into three prototypes: a continuously stable type, an initially variable and then stable type, and a continuously variable type. Case studies of three students representing the three emergent prototypes indicated that the signature dynamics for the three prototypes were related to dynamic interactions among different variables and dynamic changes in affect-related elements in the form of writing interests, motivation, and strategies. The initial conditions and the feedback from Pigaiwang acted as key control parameters in shaping the prototypes. The continuously variable prototype developed their writing proficiency to the greatest extent and had the most variability. Based upon the findings, implications for teaching L2 writing are discussed.

A Systematic Review of Second Language Acquisition from the Perspective of Complex Dynamic System Theory

“…The innumerable individual and extraneous variables that impact second language acquisition make this development a dynamic one. A few of such variables include affect, motivation, environmental factors (Khomeijani et al, 2020;Zhang et al, 2022), age of onset (Pfenninger, 2022), first language fluency, individual learner investment, amount of available free time, and competition among learners (Kliesch & Pfenninger, 2021).…”

“…While the value of the contributions and findings of group studies even with few data points is undeniable, such studies are unable to keep track of the unique and flexible developmental trends of each learner. Some of the numerous cognitive and environmental factors that impact the dynamic development of a second language include motivation, anxiety, memory capacity, age, aptitude, intelligence, available learning time, available knowledge, level of education, maturity, and the amount of exposure to the new language (de Bot et al, 2007;Kliesch & Pfenninger, 2021;Zhang et al, 2022). For example, the study conducted by Piniel and Csizér (2015) indicated that learners with higher degrees of motivation and lower degrees of anxiety had more variable developmental patterns in comparison with others.…”

“…Such investigated areas include complexity, accuracy, and fluency (CAF) in speaking (Larsen-Freeman, 2006;Lowie et al, 2017;Sauer &Ellis, 2019), andwriting (Larsen-Freeman, 2006;Spoelman & Verspoor, 2010;Verspoor et al, 2021;Zhang et al, 2022), in addition to vocabulary (Caspi & Lowie, 2013;Zheng, 2016), and pronunciation (Munro & Derwing, 2008). A number of previous studies have also examined how the dynamic development of a second language is influenced by issues such as self-concept (Mercer, 2011), motivation (Han & Hiver, 2018;Lowie & Verspoor, 2019;Nitta & Baba, 2015;Nitta & Baba, 2018;Zhang et al, 2022), individual differences (Lowie & Verspoor, 2019;Nitta & Baba, 2018;Pfenninger, 2022), and also corrective feedback (Fogal & Koyama, 2022). While these factors are indeed impactful on language developmental patterns, it does not mean that grouping learners by these variables can necessarily result in exactly similar learning patterns.…”

“…As can be seen in Figure 4, the number of data points that the studies had were rather evenly distributed and they were not densely clustered around a specific number. As the most repeated number of data points, participants were tested 30 times in five of the conducted studies (Baba & Nitta, 2014;Baba & Nitta, 2021;Chang & Zhang, 2021;Evans & Larsen-Freeman, 2020;Zhang et al, 2022). The Frequencies of Timespans…”

Longitudinal Investigation: Impact of Production-Oriented Approach on Chinese University Students’ English Writing and Speaking Proficiency

“…In this context, particularly within the realm of higher education, there exists a critical need for a paradigm shift that addresses the persistent challenges faced by university students in their English communication skills (Hu et al, 2023), notably in writing and speaking (Lin & Liu, 2022;Yang, 2020). Despite the substantial emphasis on English language instruction, students often encounter deficiencies in complexity, accuracy and fluency (CAF) in their expressive abilities (Wang & Han, 2021;Zhang et al, 2022), raising concerns amplified by the recognition that effective English communication skills are integral not only to academic success but also to participating meaningfully in a globalized society and workforce (Hu et al, 2022). Amidst these challenges, the Production-Oriented Approach (POA) has recently emerged in China's academia as a promising pedagogical strategy designed to address the shortcomings of traditional foreign language (L2) instruction characterized by an over-emphasis on linguistic forms (Zhang, 2020b).…”