Abstract
This study examines the evolution and regulation of group-level enjoyment of online collaborative language learning. Three Chinese undergraduate learners of English as a foreign language (EFL) collaborated to finish a series of English writing tasks via an online group enabled by WeChat, a popular social instant messaging app in Chinese-speaking communities. The data were collected in three sessions over a single semester using an idiodynamic approach for participants’ ratings of enjoyment intensity and stimulated recall interviews for participants’ descriptions of emotion regulation types. The data were analysed using deductive qualitative thematic analysis and quantitative descriptive analysis. The findings indicate that group-level enjoyment fluctuated within each session of online collaborative learning and tended to last longer in later sessions. Furthermore, the participants reported enacting three different types of regulation – namely self-regulation, co-regulation, and socially shared regulation – to achieve and sustain the dynamic evolution of group-level enjoyment in online collaborative learning. Of these, socially shared regulation was the most prevalent overall, and this increased in prevalence with time. The findings also reveal specific emotion regulation processes within these three types, including planning, evaluating, and the use of emojis. The implications of the findings are discussed, and future research directions are provided.
I Introduction
Foreign language (FL) learning today is highly interactive, collaborative, and technologically enhanced (Järvenoja et al., 2015; Zou et al., 2018). Online collaboration in language learning provides opportunities for learners to practice language skills, establish new linguistic knowledge, and develop critical thinking both inside and outside the classroom (Kukulska-Hulme & Viberg, 2018). However, collaborative language learning is not only a cognitive process but also an emotional one (Poehner & Swain, 2016). Positive emotions play a crucial role in successful collaboration since they improve interaction and communication, as well as engagement in the co-construction of knowledge (Järvenoja et al., 2013). As emotions are not private reactions from an individual but rather are regulated within interpersonal interactions (Swain, 2013), positive emotions are formed and sustained through language learners’ emotional-regulatory efforts in collaborative learning. Understanding how group-level positive emotions, such as enjoyment, evolve, and how these emotions are continually regulated during online collaborative learning is an essential component of exploring how collaborative groups succeed in making their online interactions in language learning activities effective.
Recently, enjoyment has become one of the most studied positive emotions in FL learning (Y. Jiang & Dewaele, 2019). Extensive research has shown that enjoyment is a complex and dynamic state that fluctuates at the individual level, influenced by learner-internal and external contextual factors in language learners’ independent learning activities (Elahi Shirvan & Talebzadeh, 2018) and in class (Dewaele & Dewaele, 2017; Elahi Shirvan & Taherian, 2018).
However, scant evidence exists on the dynamic evolution of enjoyment at the group level and the emotion regulation mechanisms contributing to group-level enjoyment in online collaborative language learning. To fill this research gap, the present study aims to trace the dynamics of group-level enjoyment and its related emotion regulation types in an online collaborative environment where Chinese learners of English as a foreign language (EFL) worked together to accomplish a series of English writing tasks over the course of one semester.
II Literature review
1 Enjoyment in FL learning
The term ‘enjoyment’, in the context of learning, refers to a sense of satisfaction and reward derived from surpassing homeostatic constraints and stretching beyond oneself to accomplish something unexpected, especially in the face of adversity (Dewaele & MacIntyre, 2016; Li et al., 2018). It includes dimensions beyond pleasurable feeling, such as intellectual focus, heightened attention, and optimal challenge (Boudreau et al., 2018). Enjoyment is one of the most frequently and consistently experienced positive emotions for learners in FL learning (Sampson & Yoshida, 2021; Yoshida, 2020). As a core component of language learning motivation, enjoyment motivates learners to explore, be creative, and push their limits when confronted with an unfamiliar language and a new culture, thereby broadening their perspectives and facilitating the acquisition of the target language (Fredrickson, 2004; MacIntyre & Gregersen, 2012; MacIntyre & Vincze, 2017). However, in contrast to motivation, which is typically long-lasting and stable, enjoyment tends to arise from ongoing learning activities and to fluctuate dynamically throughout the learning process (Dewaele, 2015; C. Jiang & Papi, 2022). From the perspective of Complex Dynamics Systems Theory, enjoyment is a dynamic system that continually evolves under the influence of a series of internal and external factors in the ever-changing, complex world of language learning (De Bot et al., 2007; R. Wang, 2022).
In recent years, there has been a growing interest in examining the dynamic nature of enjoyment in various language learning and cultural contexts. For example, using a pseudo-longitudinal research design, Dewaele and Dewaele (2017) assessed the dynamic evolution of enjoyment among 189 secondary school FL learners in London, UK. They compared three groups of learners distinguished by age (12–13 years old; 14–15 years old; and 16–18 years old) and discovered a moderate increase in enjoyment over time. Adopting an idiodynamic approach, Elahi Shirvan and Talebzadeh (2018) explored moment-to-moment fluctuations in enjoyment during topic-related conversations among seven female university students in Iran. The idiodynamic method allowed the learners to self-rate their levels of enjoyment moment-by-moment while they viewed a playback of their own videotaped conversation processes. The results of this study revealed that enjoyment fluctuated both within and between individuals in learners’ conversations about various topics, which highlights the dynamic nature of enjoyment.
Using the same idiodynamic methodology, Boudreau et al. (2018) demonstrated that the enjoyment of 10 Canadian university learners who were studying French as a FL changed dynamically during their speech production in French. Elahi Shirvan et al. (2020) employed a variety of instruments, including open-ended interviews, journals, enjoyment thermometers, and the idiodynamic approach, to examine the dynamics of enjoyment over different timeframes during an EFL learning course. Enjoyment-related data for two adult EFL learners in Iran were collected through open-ended interviews over a time span of months, journals over weeks, enjoyment thermometers over minutes, and the idiodynamic approach over seconds. The study found that enjoyment fluctuated across a wide range of intervals, from second-to-second shifts to monthly variations, under the influence of different individual and social variables at each timescale. Elahi Shirvan and Taherian (2018) went on to conduct a longitudinal study to analyse changes in enjoyment among 367 Iranian university EFL learners enrolled in an EFL course, using latent growth curve (LGC) modeling on survey data gathered at four different time points. The study’s findings not only provided evidence for inter- and intra-individual variances in the growth patterns of enjoyment over time, but also demonstrated an increasing trend in enjoyment over time during the EFL course learning. Similarly, Elahi Shirvan et al. (2021) used a model based on longitudinal confirmatory factor analysis-curve of factors to track the dynamic changes in enjoyment in an EFL course. The data were collected via a survey of 437 adult EFL learners in Iran over four iterations, with the results indicating that language learners with lower initial levels of enjoyment saw a faster increase in enjoyment over time, whereas those with greater initial levels of enjoyment experienced a slower increase.
While the existing literature on the dynamics of enjoyment is booming, many studies have assessed enjoyment from an individual perspective, focusing narrowly on the changes in learners’ personal enjoyment during independent study (e.g. Elahi Shirvan & Talebzadeh, 2018) or traditional classroom course learning (e.g. Elahi Shirvan et al., 2021). Few studies have investigated enjoyment from a social perspective, paying attention to the fluctuations in groups’ enjoyable socioemotional climates during online collaborative language learning activities. As emotions are not solely individual but rather regulated in social context through interpersonal interactions (Poehner & Swain, 2016; Swain, 2013), more research on enjoyment needs to adopt the learning group as the unit of analysis to explore the social emergence of enjoyment in learners’ communication or collaboration (Sampson, 2022).
2 Emotion regulation
Emotion regulation is the processes through which individuals influence and manage what emotions they have, when they have them, and how they experience and express these emotions for action and goal achievement (Gross, 2015; von Scheve, 2012). Emotion regulation processes may be automatic or controlled, conscious or unconscious, and span the entire ontogenetic development of emotions (Kappas, 2011; Mesquita, 2010). Emotion regulation typically strives to boost positive emotions such as enjoyment and diminish negative emotions such as anxiety, enabling individuals to respond adaptably to situational demands (Boekaerts & Pekrun, 2015; Pekrun, 2006). Winne and Hadwin (2008) situated emotion regulation within the more general category of self-regulation in learning, treating it as a set of complex, dynamic, and recursive processes that unfold over time and vary across different situations. They proposed four loosely sequenced and recursively linked phases of regulation: (1) defining task perceptions, (2) planning, (3) enacting strategies, and (4) monitoring and evaluating. Recurrent implementation of these four regulatory processes may reduce anxiety or stress during task completion and enhance enjoyment in the learning process (Bakhtiar et al., 2018; Järvenoja et al., 2013). Järvenoja et al. (2013) extended Winne and Hadwin’s (2008) process model to a collaborative learning context. They argued that in collaborative learning, learners employ these regulatory phases to regulate themselves, each other, and the group concurrently to positively influence the group climate. In other words, three qualitatively different types of emotion regulation – self-regulation, co-regulation, and socially shared regulation – operate in collaborative learning situations to create a more emotionally pleasing social environment. Self-regulation refers to an individual process in which a person regulates their own emotions in an emotionally charged situation. Co-regulation refers to individuals’ various attempts to affect each other in an emotionally charged situation. Socially shared regulation refers to multiple individuals’ collective efforts to manage an emotionally charged situation.
In recent years, several empirical studies have investigated how learners adopt self-regulation, co-regulation, and socially shared regulation to regulate emotions during collaborative learning. For example, Panadero et al. (2015) examined the influence of self-regulation on group learning performance in the context of a collaborative essay writing task within a multi-media learning course for 103 teacher education students in a Finnish university. Their analysis revealed that group members’ self-regulatory acts, such as self-evaluating and self-consequating, could enhance their collective control over the emotional climate and interpersonal interaction of the entire group. Rogat and Adams-Wiggins (2015) specifically investigated the role of co-regulation in group’s socioemotional interactions by observing collaborative learning in two four-member groups of American middle school students. The results indicated that supportive co-regulatory acts, such as showing understanding and respect towards others, could foster less stressful socioemotional interactions than directive co-regulatory acts, such as giving orders to others. Based on video-recorded data gathered from 62 teacher education students in a mathematics course in Finland, Järvenoja et al. (2019) also found that group members did share regulatory attempts to control emotionally challenging situations together, such as their joint use of strategies to eliminate the triggers of negative emotional states.
Although research interest in the use of self-, co-, and socially shared regulation in collaborative learning is growing, there is a prevalence of cross-sectional studies and a lack of longitudinal investigations, which makes it difficult to estimate the dynamic changes of these three emotion regulation types over time. In addition, much of the research to date has focused on learners’ emotion regulation efforts in dealing with emotional challenges in face-to-face collaborative learning settings of diverse disciplines, such as multi-media (e.g. Panadero et al., 2015) and mathematics (e.g. Järvenoja et al., 2019). Little research has been conducted to examine language learners’ regulation of positive emotions such as enjoyment in an online collaborative learning context.
III Research questions
Based on the literature reviewed above, the present study aims to investigate the evolution of group-level enjoyment and of its relationship to the three types of emotion regulation during a semester-long online collaborative EFL writing program. Specifically, the following research questions are addressed:
• Research question 1: How does the group-level enjoyment of participants evolve over time as they collaborate online to complete EFL writing tasks?
• Research question 2: How do participants use different types of emotion regulation, including self-, co-, and socially shared regulation, to achieve group-level enjoyment in their online collaborative learning over time?
IV Method
1 Research context
This study was conducted in an online collaborative EFL writing program offered at a comprehensive university in Shanxi Province, China. The program is designed to help second-year English-major students at this university improve their EFL writing skills and better prepare for the Test for English Majors Band 4 (TEM4), a national EFL test that is mandatory for all English-major students in China at the conclusion of their second academic year of undergraduate study (Jin & Fan, 2011).
The program uses an 18-week semester format and was hosted via WeChat, a popular social communication app in China through which users can exchange large amounts of information via text, emojis, voices, pictures, and videos free of charge (Y. Wang et al., 2016; Zou et al., 2018). Students enrolled in this program were assigned randomly by their teachers to one of several WeChat-based groups of three or four students, in which they worked together on a series of TEM4-style writing tasks posted by teachers on an approximately weekly basis. Although the writing topics differed weekly, all of them required the students to compose essays of at least 200 words based on a 200-word piece of reading material and a writing prompt of about 50–60 words. To facilitate the online group collaboration, students were encouraged to freely use WeChat’s various communicative features (e.g. text and emojis) to present their own ideas, respond to each other’s work, negotiate a common agreement, and complete the weekly writing task. Each group’s finished assignments and chat logs on WeChat were expected to be submitted to teachers as evidence of the group members’ learning, accounting for 30% of their overall grade for the semester.
2 Participants
The research participants were three students who enrolled in the program in the Fall semester of 2019. They were randomly assigned by the teacher to a three-member WeChat group for collaborative EFL writing. One was aged 21 years and the other two were aged 20 years. All were female English major undergraduates who had studied English as their only FL for at least seven years. Their English proficiency ranged from lower intermediate to higher intermediate based on their scores in the previous semester’s English proficiency exam. Two of the three students had previously taken online courses; however, none of them had experience doing online group work. Participants were invited via a convenience sampling procedure based on their interest in and availability for this study. They were also informed that their participation or nonparticipation in the study would have no effect on their grades, and that they could withdraw at any time. Their names were replaced with pseudonyms for the sake of confidentiality.
The three-member group successfully completed all EFL writing tasks required of them in the online collaborative writing program for the winter semester of the 2019–20 academic year. Their learning performance in the program was graded as A (excellent) by the teacher, placing them in the top 20% of all students.
3 Instruments
a Screen recording
Screen Recorder is a feature of the Android mobile operating system that allows users to make screen recording videos without having to download a third-party app. The first researcher used this feature on his mobile phone to record the participants’ real-time conversations in the WeChat group. The video recordings were directly saved to his phone’s media storage in ‘.wmv’ format and then emailed to the participants for further idiodynamic research.
b Software for idiodynamic rating
The Anion Variable Tester software developed by MacIntyre and Legatto (2011) was used to capture participants’ idiodynamic ratings of enjoyment during their online conversations. Using the software, participants watched the recorded videos of their group discussion and concurrently rated their levels of enjoyment via the use of a computer mouse on a scale ranging from −10 (least enjoyable) to +10 (most enjoyable). Upon completion of the ratings, the software provided a bitmap graph that displayed a timeline of each participant’s self-rated enjoyment readings.
c Stimulated recall interview
The purpose of the stimulated recall interview was to explore the emotion regulation processes underlying the enjoyable moments the participants experienced in their online conversations. Using the enjoyment self-rating graphs generated by the software as a guide, we asked the participants to watch their recorded videos for a second time and explain the reasons for moments of high enjoyment (i.e. where they had rated their enjoyment above 0). The interview was conducted in a one-on-one and face-to-face format. The Chinese language, the participants’ mother tongue, was used during the interviews to ensure that participants could express their thoughts adequately and freely. Example interview questions were ‘You have rated your enjoyment particularly high in this interval, please explain why’ and ‘Your rating is high at 6 out of 10 in this interval, from 1 min to 1 min 30 s during your group conversation. What did you do to achieve high-level enjoyment in this interval?’
4 Data collection
We collected data from three WeChat-based online collaborative learning sessions, which occurred in the second, ninth, and sixteenth weeks of the university semester from September 2019 to January 2020. Considering that enjoyment might fluctuate over longer time frames than seconds or minutes (Elahi Shirvan & Taherian, 2018; Elahi Shirvan et al., 2020), the seven-week interval between data collection points in this study allowed for the measurement of changes in enjoyment across weeks.
The EFL writing topics provided for the three learning sessions include the controversy surrounding environmental conservation (Session 1), the benefits and drawbacks of artificial intelligence development (Session 2), and the role of parents in children’s media usage (Session 3). After obtaining participants’ consent, the first researcher used his mobile phone’s built-in screen recording tool to video record each group conversation session on WeChat. Immediately after each conversation was finished, the first researcher emailed the video recordings to participants for them to watch and rate their enjoyment levels using the Anion Variable Tester software. With the aid of the rating graphs produced by the software, we paused the video where a high-level rating (above 0) was visible and asked participants to describe any noticeable change in their enjoyment patterns. The interviews were audio recorded, transcribed, and translated for further analysis.
5 Data analysis
The data were analysed using deductive qualitative thematic analysis and quantitative descriptive analysis. The deductive thematic analysis enabled us to accurately capture the recurrent themes and patterns through several iterations of identifying the intervals of group-level enjoyment in participants’ rating graphs and the types of emotion regulation in the interviews (Marshall & Rossman, 2016). The following quantitative descriptive analysis allowed us to quantify the identified enjoyment intervals and emotion regulation types in terms of the numbers of them reported or mentioned by participants in their enjoyment rating graphs and interviews.
Specifically, the three participants’ enjoyment self-rating graphs were first grouped together to identify and quantify the intervals of group-level enjoyment that occurred throughout each of their online collaborative learning sessions (research question 1). A coding scheme based on the criteria employed by Järvenoja et al. (2018) and Mänty et al. (2020) was used to code group-level emotional valence in the collaborative learning setting. Any intervals in learning sessions that received at least two positive ratings (above 0) and no negative ratings (below 0) were coded as enjoyment-group. The frequency, overall duration, and time proportion of these identified codes were then calculated for each learning session and compared across the three sessions.
Next, the data from the interview transcripts relating to the pre-coded enjoyment-group episodes were coded to investigate the participants’ emotion regulation efforts within these episodes. The coding procedure was carried out in two phases. The focus of the first phase was to detect specific emotion regulation processes in the interview data. In this phase, the first researcher initially coded the participants’ open-ended statements using Winne and Hadwin’s (1998) classification of emotion regulation processes (see Table 1), which includes task understanding, planning, strategy use, monitoring, and evaluating. During coding, it was difficult to distinguish between monitoring and evaluating processes in the data, so they were merged into a single process. The second researcher then coded a random 20% of the participants’ statements. The resulting free-marginal kappa value was 0.81, indicating satisfactory inter-coder reliability (Fleiss et al., 2013).
Descriptions and examples of coded emotion regulation processes.
Once the first phase of coding was complete, we conducted a second phase of coding to further categorize the coded episodes of emotion regulation processes into self-, co-, and socially shared regulation. The coding scheme (see Table 2) was developed from Järvenoja et al.’s (2013) description of these three types of emotion regulation in collaborative learning. As in the first phase, the first researcher applied the coding scheme to all interview data, and the second researcher randomly chose 20% of the data to code. The free-marginal kappa value between the two researchers was 0.77, indicating satisfactory inter-coder reliability (Fleiss et al., 2013). The frequency and frequency proportion of these coded regulation types and regulatory processes within each type were calculated for each learning session and compared across the three sessions.
Description of coded emotion regulation types.
V Results
1 The dynamics of group-level enjoyment
Figure 1 presents the participants’ idiodynamic enjoyment ratings across the three sessions. The length of the online group discussion sessions they self-organized via WeChat ranged from 31.5 mins (Session 3) to 33.5 mins (Session 1) to 35.42 mins (Session 2). The idiodynamic software was programmed to record participants’ enjoyment ratings at 30-second intervals throughout each session. The horizontal axis represents the time points at which participants’ enjoyment ratings were recorded. The vertical axis provides the idiodynamic enjoyment rating scale, ranging from +10 (very high level of enjoyment) to −10 (extremely low level of enjoyment). Each participant’s ratings are shown in a different color.
Enjoyment ratings of the three participants within an online group over three sessions.
As shown in Figure 1, all three group members’ enjoyment varied from −5 to 7 in the first and second sessions and from −3 to 9 in the third session, and all three display noticeable change in enjoyment over time within each of the three sessions. Much of the variation within their enjoyment trajectories occurred in the high enjoyment band (above 0) over the course of the three sessions, signifying a generally enjoyable group climate during their online collaboration.
The specific intervals in the participants’ enjoyment rating graphs were coded as enjoyment-group when there were at least two positive ratings (above 0) and no negative ratings (below 0). These coded enjoyment-group intervals are indicated on red rectangles in Figure 1. Some identified enjoyment-group intervals were as short as 30 seconds, while others lasted up to 5 minutes. The frequency, total duration, and time proportion of these enjoyment-group intervals in each learning session were then calculated. Table 3 summarizes the details of the enjoyment-group intervals identified in the three sessions of online collaborative learning. The frequency of identified group-level enjoyment intervals decreased from Session 1 (14) to Session 2 (12) and then increased in Session 3 (15). The total duration and proportion of the enjoyable atmosphere in participants’ online collaborative learning gradually increased from Session 1 (15.25 minutes; 45.52%) through Session 2 (16.34 minutes; 46.13%) and Session 3 (18 minutes; 57.14%).
Details of enjoyment-group intervals identified in three sessions.
2 The types of emotion regulation underpinning group-level enjoyment
To explore how the participants used different types of emotion regulation (self-, co-, and socially shared) to achieve group-level enjoyment in online collaborative learning, we asked them to describe what they had done or tried to do to achieve an enjoyable atmosphere in the previously identified group-level enjoyment intervals. Table 4 displays the frequency with which participants reported using each type of emotion regulation and its relevant processes for group-level enjoyment in each session and overall. Participants reported an increasing use of socially shared regulation over time from Session 1 (9; 30.3%) to Session 2 (13, 54.2%) and Session 3 (15; 71.4%). In contrast, there was a notable decrease in the use of self-regulation over time from Session 1 (10; 37.0%) to Session 2 (5, 20.8%) and Session 3 (3; 14.3%) and the use of co-regulation over time from Session 1 (8; 29.6%) to Session 2 (6, 25.0%) and Session 3 (3; 14.3%). Overall, socially shared regulation was the most frequently used type of emotion regulation (37; 51.4%), followed by self-regulation (18; 25.0%) and co-regulation (17; 23.6%).
Frequencies of coded emotion regulation types and their relevant processes in the three sessions .
Within the category of socially shared regulation, joint planning was the process most employed to enhance group-level enjoyment across all three sessions. A good group atmosphere resulted when group members worked together to plan or develop a new and interesting idea or an effective interaction style, as the participants described:
The transmission of information in our group was relatively intensive. You know, focusing on an immature idea, everyone kept talking non-stop. It was not like I said one word, but the other responded half a minute or several minutes later. You could feel that everyone was highly enthusiastic and stayed on the task. We all liked this feeling. (Ping, Session 1, 16 min 30 s – 17 min 30 s) This week, we all worried about the low efficiency of our interaction. So, we talked about it and agreed that there should be a clearer division of labor. We roughly divided the writing task into three more manageable parts. Each of us was in charge of one part. Everyone needed to collect and organize group ideas about the part they were responsible for. This division of work made us less stressed, less anxious, and more relaxed than last week . . . We had a great time this week. (Xuan, Session 2, 12 min 56 s – 15 min 56 s) When discussing how to support the expert’s view given in the task, everyone was fully prepared and kept saying their personal ideas. Thus, it was easy for us to get each other’s points, find common ground and finally reach a consensus . . . Our discussion went so naturally and smoothly. It was such a pleasant experience. (Lin, Session 3, 11 min 51 s – 13 min 21 s)
Joint evaluating was the second-most frequently reported process of socially shared regulation throughout all three sessions. The participants found their online collaborative learning enjoyable when they started to evaluate or reflect on their progress as a group and make joint adjustments to improve their work. Examples of joint evaluation include the following:
When our collaboration came to an end, we wanted to review what we had discussed to get a clearer picture of what we had achieved in this collaboration. When we actually did this, we found some problems . . . the points mentioned by some of us were a little repetitive, and we tried to make them more concise. So, we kept finding problems and correcting these problems . . . Though we spent a lot of time in this process, it was such a wonderful and exciting experience to see our efforts finally forming a complete work. (Xuan, Session 1, 32 min 23 s – 33 min 23 s) Everyone focused on reviewing the ideas we had thought out and talked about previously one by one . . . And we all gave our judgments and opinions . . . We were so focused that we did not realize how much time had passed. Wow, that was a real and enjoyable collaboration. (Lin, Session 2, 33 min 11 s – 34 min 56 s) We reviewed our discussion and finally got three points we were satisfied with . . . The comprehensive summary could not have been done without efforts from each one of us. We trusted and encouraged each other all the time . . . We all tried to look at things from the perspective of others and be receptive to others’ opinions and suggestions. This made me feel very warm and happy. (Ping, Session 3, 28 min 21 s – 29 min 21 s)
Joint understanding of task was reported in Sessions 1 and 3, and were more numerous in the latter. Some episodes of enjoyment experienced by participants were related to their mutual engagement in establishing a shared understanding of the purposes, requirements and difficulties of the assigned writing tasks. Lin and Ping offered a typical view:
The task was quite difficult to understand for all of us at first sight. So we unanimously decided to read the reading material given in the task again and carefully reanalyse each and every sentence in this material. In doing so, we were happy to find that the task was not as difficult as we had expected. (Lin, Session 1, 1 min 23 s – 2 min 53 s) Compared with previous tasks, we all agreed that this writing task was easier to understand and discuss . . . The topic was about parent-child relations in the use of media, which was closer to our life experiences. Also, our writing teacher had given us a similar topic in class last week, so to some extent we were familiar with it. (Ping, Session 3, 51 s – 1 min 21 s)
Joint use of emojis was a strategy for the creation of an enjoyable group atmosphere that was only mentioned by participants in relation to Session 3. They adopted various facial (e.g. a smiley face) and non-facial (e.g. a thumbs-up) emojis to enliven the group atmosphere during online collaboration, as Xuan explained:
You see, at this moment, we were exchanging emojis such as a thumbs-up, a smiley face, a red heart, a dancing bear . . . In fact, writing is a relatively boring activity. If we just use words to describe what we think and feel, we may get bored. But emojis are a bit like pictures, which can express information that words cannot express and create an enjoyable experience for us. When we are stressed out or in a bottleneck, emojis make our group livelier, ensuring that our discussion goes smoothly. (Xuan, Session 3, 1 m 51 s – 2 min 51 s)
Within the category of self-regulation, self-evaluating was the most frequently reported practice, and was used across all three sessions. Participants tried to positively reframe (or re-evaluate) their own perceptions of potentially emotionally provoking situations, such as conflicting ideas or mistakes, in online collaborative learning. Examples include the following:
Here, two of them mistook conservation, a key word in the task title, as conversation. Though I did not misunderstand this word, the big mistake they had made served as a good reminder for me to take extra care in reading the material given in the tasks. Next time, say, that I take a formal exam, I will not make such a big mistake. (Xuan, Session 1, 26 min 23 s – 27 min 23 s) Despite the fact that we had opposing viewpoints about the development of artificial intelligence at this time, I persuaded myself that the disagreements could be beneficial for me, as every issue has two sides. The clashes between diverse viewpoints provided a new perspective for me to consider the merits and downsides of the advancement of artificial intelligence technology. (Lin, Session 2, 12 min 56 s – 15 min 56 s)
The participants also achieved enjoyment through a positive evaluation of their own learning abilities and performances, as Ping explained:
I was happy and comfortable at this moment because I felt proud of myself. Compared with the others, I performed better and made a greater contribution to the group work . . . I always better prepared than them . . . I was the most active member of the group. (Ping, Session 3, 21 min 48 s – 24 min 18 s)
Self-planning was the second-most frequently mentioned process of self-regulation overall and appeared in the first two sessions. The participants derived enjoyment from their personal efforts in making preparations beforehand, and in verbalizing their pre-prepared ideas and plans in front of other group members during the online group discussion. This is shown in the following interview excerpts:
Before our WeChat discussion began, I did a great deal of reading and found a lot of task-related information. I was delighted to have the opportunity to present to others what I had discovered and what I had prepared. It was my showtime, which made me feel what I had done was worthwhile. (Lin, Session 1, 11 min 23 s – 12 min 23 s) The writing topic was the controversy surrounding the development of artificial intelligence. Initially, when faced with this topic, I had no idea what I should write. So I went to the university library and found several books to get some background information about artificial intelligence. I also scanned some news on the internet about the advantages and disadvantages of artificial intelligence . . . During our discussion I was looking forward to sharing what I had found with other group members. Having the opportunity to have my own thoughts heard by others made me happy and eager to do more for our group. (Lin, Session 2, 16 min 28 s – 18 min 28 s)
The self-use of emojis was a process of self-regulation which the participants reported using in Session 3 to obtain enjoyment in online collaboration. They used emojis to help alleviate the anxiety and boredom they felt about the task and soften the serious nature of communication, as Lin explained:
The moment the group discussion began, I was anxious that I would not perform very well. So I posted several emojis in the WeChat group, such as a wide smile and a pair of waving arms, to help calm my nerves and boost my confidence . . . Emojis are super vivid and funny. Every time I posted emojis, I felt much more relaxed. (Lin, Session 3, 22 min 51 s – 23 min 51 s)
Self-understanding of task refers to group members’ individual efforts to regulate themselves while they were thinking about the purposes and requirements of the tasks. Participants mentioned it only once, in Session 1. Xuan described how her enjoyment was boosted by gaining a more accurate understanding of the task requirements:
What made me happy was that I noticed the uniqueness of the task. In most cases, writing tasks require you to express your own opinions in response to the assigned reading material. However, this time the task asked you to comment on the two points made by a person in the given material. This meant you didn’t have to add too many personal ideas. The emphasis of the requirement this time was commenting on something instead of expressing one’s own views. (Xuan, Session 1, 4 min 23 s – 4 min 53 s)
Within co-regulation, assisted planning was reported most frequently overall and was used across all three sessions. The participants experienced enjoyment when they received assistance from other group members to overcome their own difficulties in thinking about (i.e. planning) the ideas that might be needed to finish the writing task. This assistance from peers was detailed in the following interview excerpts:
Here, I had a vague idea, but I did not how to express it correctly. Lin recognized that I did not say too much in the group. So, she encouraged me to voice my inner thoughts bravely and not to be afraid of making mistakes . . . Without her help, I would not have had the courage to say what I really thought. She helped me a lot and made me really enjoy our group discussion. (Ping, Session 1, 16 min 38 s – 17 min 53 s) At this time, I was quite hesitant about which perspective I should choose to write the essay . . . So I told Ping and Lin about my doubts, trying to ask for their advice. They told me that it might be easier to write about the advantages of artificial intelligence. They listed many reasons and examples to persuade me . . . Following their lead, I was also thinking about what benefits artificial intelligence could bring to our society. With their aid, I continued to think more and go deeper, which made me very happy. (Xuan, Session 2, 21 min – 22 min) About the structure of our final work, I was wondering if it should take the form of point-by-point argumentation or a detailed description just focusing on one point. So, I raised a question to seek their [Ping and Xuan’s] advice. They reminded me that our writing teacher had answered this question already several days earlier. Even if you wrote a lot, one point was not enough. A mature piece of writing should have a clear structure with many key points . . . Their meticulous and patient explanations helped me resolve my confusion. (Lin, Session 3, 22 min 51 s – 23 min 51 s)
Another process of co-regulation was assisted understanding of task, which was primarily reported in Session 1. Participants partly owed their enjoyment to their deliberate efforts to help other group members achieve a correct understanding of the task’s purpose. Examples of assisted understanding of task include the following:
Xuan seemed to misunderstand the purpose of the task. She thought it was arguing for one of two views, but I believed the task focus was adding more things to these existing views. So, I reminded her to reread the task requirement word-by-word. Afterwards, she realized she had misunderstood the purpose of the task. Helping Xuan made me feel rewarded, fulfilled, and empowered . . . I thought it was my responsibility to lend a hand to other members if they were in difficulties, and I was happy about that. (Ping, Session 1, 5 min 23 s – 6 min 23 s)
VI Discussion
Using the idiodynamic self-rating software, the present study traced changes over time in the group-level enjoyment that the participants experienced when they collaborated online to complete a series of EFL writing tasks. A total of three specific sessions in their online collaboration were selected for data collection: one at the beginning, one in the middle, and one near the end of the semester. The emotional trajectories of the three participants exhibited substantial fluctuations within and between sessions, but the climate of the group was generally enjoyable. The calculated instances of group-level enjoyment intervals in three sessions (12–15) further indicated that the enjoyable climate was not a static state but a continually unfolding process emerging from and in turn shaping the collaborative learning process. All these findings are in line with a number of previous studies highlighting the dynamic nature of enjoyment in and across learning sessions (e.g. Boudreau et al., 2018; Elahi Shirvan & Talebzadeh, 2018; Elahi Shirvan et al., 2020). Moreover, the calculated total duration of group-level enjoyment intervals and their proportion in each learning session showed that the group’s enjoyable atmosphere tended to last longer as members’ collaboration progressed. The increase in the length of the enjoyable atmosphere over three sessions might have been influenced by the learning context, as demonstrated in previous studies (e.g. Elahi Shirvan & Taherian, 2018; Y. Jiang & Dewaele, 2019; R. Wang, 2022). In the context of online collaborative language learning, participants were restricted to chat-based communication where traditional non-verbal cues (e.g. facial expressions and body gestures) that are prevalent in face-to-face interactions were absent (Bakhtiar et al., 2018; van der Meijden & Veenman, 2005). Thus, when in-person classes were suddenly replaced with online collaboration, the lack of non-verbal cues might have made it difficult for the participants to recognize each other’s emotions and control the group atmosphere at the beginning of their group work. However, as the online collaboration proceeded, the participants may have gradually gained familiarity with the affordances embedded in the online platform, such as the multimodality on WeChat that enables participants to interact with each other flexibly via text, images, video clips, and emojis (Y. Wang et al., 2016). As they gained more comfort using all of these tools for communication, they could exert more control over their group work and maintain a friendly emotional atmosphere for a longer period of time. Hence, the participants’ gradual adaptation to the new online collaborative learning environment might have extended the duration of the whole group’s enjoyment over time.
Based on participants’ idiodynamic ratings of enjoyment, stimulated recall interviews were conducted to reveal how they employed the three types of emotion regulation (self-, co-, and socially shared) to achieve group-level enjoyment in online collaboration over time. Overall, the results showed that participants relied more on socially shared regulation than self-regulation and co-regulation for group-level enjoyment during their online collaborative learning. There are two possible reasons for this finding. First, in collaborative learning, participants work towards a common learning task, which requires them to regulate emotions together and take shared responsibility for the learning process (Järvenoja et al., 2015). To adjust and balance the group environment to be more emotionally satisfying for the productive development of group work, it is not sufficient for participants to merely regulate their own emotions or assist others; rather, they need to coordinate and integrate their efforts to manage emotions collectively (Järvenoja & Järvelä, 2009; Järvenoja et al., 2013). Thus, it is not surprising that socially shared regulation dominated participants’ collaboration to create a pleasant environment, especially when the task was challenging. Second, socially shared regulation exists at the intersection of individual and social processes, and thus always incorporates self-regulation and co-regulation (Järvelä et al., 2010; Malmberg et al., 2017). In the context of collaborative learning, participants’ self-regulation not only generates a positive emotional state for themselves, but also creates beneficial contextual conditions for the whole group’s socially shared regulation to occur (Hadwin et al., 2018). In addition, co-regulation is an essential foundation for socially shared regulation, as assistance learners offer each other can shape the way each individual looks at an emotion-inducing situation and activate their collective regulatory processes (Hadwin et al., 2018; Malmberg et al., 2017). Therefore, episodes of self-regulation and co-regulation are usually embedded in socially shared regulation.
In terms of the trends in emotion regulation over time, our results revealed an increase in the use of socially shared regulation and a decrease in the use of self-regulation and co-regulation across the three learning sessions. This finding implies that emotion regulation becomes increasingly socially shared as language learners become more familiar with their online collaborative learning setting and each other (De Backer et al., 2015). Collaborative interactions focusing on task completion might promote the emergence of increasing socially shared regulation, as task completion creates a foundation for sustained shared regulation to happen (Malmberg et al., 2017).
In addition, the interview data in our study also shed light on specific regulatory processes that participants engaged in within each type of emotion regulation. Within socially shared regulation, joint planning was the most frequently seen regulatory process across all three sessions. The popularity of joint planning within socially shared regulation might be attributed to the characteristics of the participants; compared with non-English major students, the English-major participants in this study had a relatively high level of motivation to learn English, which prompted them to focus on completing their learning tasks (Bielak & Mystkowska-Wiertelak, 2020; Ngo et al., 2017). In addition, all three participants were undergraduate language learners with at least seven years of English learning experience. As experienced language learners, they appeared to have a repertoire of techniques, such as the division of work, to overcome emotional challenges in language learning (Bielak & Mystkowska-Wiertelak, 2020).
Within self-regulation, self-evaluating was the most frequently mentioned regulatory process in general and occurred in all three sessions. The high frequency of self-monitoring and evaluating within self-regulation might also be explained by the features of the English-major participants. In contrast to learning other content, learning a FL involves not only the study of explicit knowledge but also the acquisition of implicit or unconscious knowledge (Ellis, 2005), which can be more challenging and lead to more mistakes. As English majors who regularly take courses in FL acquisition, the participants were likely to be fully aware of the inevitability of such mistakes and tried to find positive meanings in their mistakes to benefit their language learning.
Within co-regulation, assisted planning was overall the most common regulatory process, occurring in all three sessions. The popularity of assisted planning as a type of co-regulation might also be related to the English-major participants’ relatively strong motivation for language learning (Ngo et al., 2017). Completing language learning tasks is always challenging, and it can provoke multiple negative emotions such as anxiety and stress, disrupting learners’ engagement (Hashemi, 2011). To ensure an emotionally solid base on which academic tasks can be completed, learners can motivate themselves to affect or be affected by others by promoting or aligning with each other’s planning processes (Järvenoja et al., 2013).
The results from interviews also indicated that emoji use was a strategy that learners adopted both jointly and individually to regulate emotions and achieve group-level enjoyment in their online collaboration. This finding suggests that emojis might serve not only as observable indicators of emotional expressions that make up for the absence of nonverbal cues in an online chat-based environment (Dunlap et al., 2016), but also as an important mediation technique to regulate emotions online. Using a positive emoji such as a smiley face or a thumbs-up can strengthen the positive tone of a positive message and soften the negative tone of a negative message (Bai et al., 2019). At the same time, emojis can act as buffers or humorous tone indicators to avoid possible conflicts and build a harmonious atmosphere in the conversation (Kun & Yansheng, 2020).
VII Limitations and implications
Several limitations do exist in this study. First, there were only three participants, all of whom were Chinese English-major undergraduates who possessed a relatively high level of English competence and a high degree of motivation for EFL learning. Future studies could examine whether the current findings remain stable with participants recruited from other majors in Chinese universities. Second, the study focused solely on language learners’ enjoyment and emotion regulation in the context of online collaborative EFL writing. Future research could investigate how an enjoyable atmosphere fluctuates and is regulated in language learners’ online collaborative learning to develop other EFL skills, such as listening, speaking, and reading (Piniel & Albert, 2018). Third, the participants in this study were randomly assigned by their teacher to a specific online group for collaborative language learning. The random assignment of partners in collaborative learning might result in emotional experiences and emotion regulation patterns that differ from those that might occur if the partners in the groups know each other well (MacIntyre, 2019). Thus, further studies could explore how language learners regulate their emotions and experience enjoyment when completing learning tasks in collaboration with their friends or acquaintances, and whether this differs from the results of the present study.
Despite these limitations, the findings of this study have some important pedagogical implications. With the construction of knowledge being the primary task for collaborative language learning, emotions are usually perceived as by-products of learners’ collaboration that can be neglected or ignored (Kukulska-Hulme & Viberg, 2018; Swain, 2013). However, the significance and dynamic nature of group-level enjoyment in participants’ online collaboration suggests that enjoyment constitutes an essential part of learners’ collaborative learning and needs constant attention to sustain its development (Zhang et al., 2021). Therefore, during collaborative language learning, teachers should focus not only on the development of students’ linguistic knowledge, but also on the evolution of students’ emotional experiences, particularly any shifts in their enjoyment within groups (Poehner & Swain, 2016).
Our findings also highlight the importance of socially shared regulation; participants tended to use this specific type of emotion regulation primarily and increasingly to create an enjoyable atmosphere in collaborative learning. Hence, targeted support is needed in collaborative learning to promote the emergence of shared emotion regulation efforts among learners (Zhang et al., 2022). For example, at the beginning of collaborative learning, teachers may ask students to fill out ‘getting to know you’ forms, exploring their personal hobbies, interests, and working styles (Liu et al., 2023; Oakley et al., 2004). Using such an activity may help students to establish common ground via shared preferences and experiences, allowing them to activate shared regulation in emotion-inducing situations. During students’ online collaboration, teachers may also encourage them to exchange funny and interesting emojis, an emotion regulation strategy identified as a catalyst for group-level enjoyment in this study, to manage the emotional atmosphere and attain enjoyment.
Finally, self-regulation and co-regulation are also significant since both function in and contribute to group-level enjoyment in collaborative learning. Thus, teachers may use process discovery, as suggested by Winne (2015), to visualize and illustrate students’ self- and co-regulatory processes, thereby promoting the necessary awareness for self- and co-regulation. Learning analytics tools, such as the dashboards used in Greller and Drachsler (2012) study, could also potentially be used by teachers to capture real-time log data about students’ self- and co-regulatory processes and provide them with visible and personalized feedback to optimize their emotion regulation.
VIII Conclusions
Using an idiodynamic approach and video-stimulated interviews, this study examined Chinese EFL learners’ group-level enjoyment and emotion regulation in three sessions of an online collaborative English writing program. The results indicate that group-level enjoyment fluctuated dynamically within each session and tended to persist for longer periods of time in sessions later in the semester. To achieve and sustain group-level enjoyment in online collaborative learning, the language learners managed their emotional climate through three different types of regulation, namely self-regulation, co-regulation, and socially shared regulation. Compared to self-regulation and co-regulation, socially shared regulation was employed more frequently overall, and its frequency tended to increase over time. In addition, the interview data revealed specific self-, co-, and socially shared regulatory processes that learners engaged in while collaborating online to create an enjoyable group atmosphere. With further research in this area, these findings might be used to help language learners develop emotional awareness and the necessary skills of emotion regulation during online or in-person collaborative language learning.
