The relational, co-temporal, contemporaneous, and longitudinal dynamics of self-regulation for academic writing

Mohammed Saqr,Olga Viberg,Ward Peeters

doi:10.1186/s41039-021-00175-7

Abstract

Writing in an academic context often requires students in higher education to acquire a new set of skills while familiarising themselves with the goals, objectives and requirements of the new learning environment. Students’ ability to continuously self-regulate their writing process, therefore, is seen as a determining factor in their learning success. In order to study students’ self-regulated learning (SRL) behaviour, research has increasingly been tapping into learning analytics (LA) methods in recent years, making use of multimodal trace data that can be obtained from students writing and working online. Nevertheless, little is still known about the ways students apply and govern SRL processes for academic writing online, and about how their SRL behaviour might change over time. To provide new perspectives on the use of LA approaches to examine SRL, this study applied a range of methods to investigate what they could tell us about the evolution of SRL tactics and strategies on a relational, co-temporal, contemporaneous and longitudinal level. The data originates from a case study in which a private Facebook group served as an online collaboration space in a first-year academic writing course for foreign language majors of English. The findings show that learners use a range of SRL tactics to manage their writing tasks and that different tactic can take up key positions in this process over time. Several shifts could be observed in students’ behaviour, from mainly addressing content-specific topics to more form-specific and social ones. Our results have also demonstrated that different methods can be used to study the relational, co-temporal, contemporaneous, and longitudinal dynamics of self-regulation in this regard, demonstrating the wealth of insights LA methods can bring to the table.

Highlights

There has been a growing interest in the application of data-driven methods to study self-regulated learning (SRL) in online learning spaces, including in online spaces dedicated to language learning
In order to study students’ self-regulated learning (SRL) behaviour, research has increasingly been tapping into learning analytics (LA) methods in recent years, making use of multimodal trace data that can be obtained from students writing and working online
The findings show that learners use a range of SRL tactics to manage their writing tasks and that different tactic can take up key positions in this process over time

Summary

Introduction

There has been a growing interest in the application of data-driven methods to study self-regulated learning (SRL) in online learning spaces, including in online spaces dedicated to language learning. Saqr et al RPTEL (2021) 16:29 the peer collaboration process in online writing activities (Wang, 2019), on how it influences the development of language learner autonomy (Peeters & Ludwig, 2017), and on the ways it can enhance productive skills like writing and speaking in a foreign language (Viberg et al, 2020a, b, c) Studies on these processes and dynamics are increasingly applying learning analytics (LA) methods to better understand student behaviour online in order to design new ways of assisting and supporting them in their learning trajectory (cf Viberg et al, 2020a, b, c; Viberg et al, 2020a, b, c). In a recent study, Peeters et al (2020) have demonstrated that foreign language learners can use a number of SRL tactics—i.e., specific activities students undertake to govern their learning, such as making a plan of study or reflecting on their performance—to guide their academic writing process in computer-supported collaborative learning (CSCL) settings, and found that there is a significant positive correlation between students’ application of those tactics and their learning outcomes

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