summary and interpretation. In addition to analysing the connection between heart rate and anxiety ratings, the upward and downward trends or slopes in the line graph of participants’ reactions were assessed to track the periods in which anxiety was rising and falling. The inspiration for this approach was Newton’s famous laws of motion which were taken as analogous to the ‘motion of emotion.’ In essence, the tendency to experience anxiety was taken to be subject to external influences that provide impetus to change the emotional trajectory of the participant, either upward toward more anxiety or downward toward lower anxiety. The slope of the resulting line of anxiety ratings reflects the strength of the resulting force of change. Connecting multiple sources of data gathered in real time allowed the researchers to address the challenge of coordinating different data sets on multiple timescales.
This study showed how dynamic perspectives can challenge assumptions from more traditional studies, such as the correlation studies that are prevalent in the literature. Certainly there is value in taking long term stability into consideration, as typically less anxious speakers prepared and performed differently than the typically anxious ones. However, the anxiety reaction of a usually less anxious speaker seemed to be different from those more accustomed to the experience. Traditional quantitative methods would have glossed over this unusual case, treating its variability from the norm as error.
Anxiety + enjoyment
Although anxiety has been well studied in SLA, other emotions have not been widely investigated. There is a recent series of studies on language enjoyment that provide a positive emotional counterpart to the large number of anxiety studies that exist. Many of the enjoyment studies use the Dewaele and MacIntyre (2014) Foreign Language Enjoyment scale (Dewaele & MacIntyre, 2016; Dewaele et al., 2016; Dewaele et al., 2017).
Boudreau et al. (2018) studied the dynamics of not one but two emotions, anxiety and enjoyment. The idiodynamic approach allows for studies of the coordinated actions of different emotions. The challenge was to conceptualize how the emotions might jointly operate. Although prior questionnaire-style research showed a significant negative correlation between them ranging between −0.24 and −0.34, the size of the correlation suggests anxiety and enjoyment are not mutually exclusive or opposite ends of the same continuum. From a CDST perspective, the challenge was to measure the emotions with two separate ratings. The solution was to employ the idiodynamic software twice, once to get ratings of anxiety and a second time to get ratings for enjoyment, in counter-balanced order. A second challenge was to show the relationship between anxiety and enjoyment during free-flowing communication. The solution was to create meaningful segments of time wherein a communicative event occurred, such as during a complete, fluent utterance on a single topic, and then examine the coordinated trends for anxiety and enjoyment. Doing so allowed a description, within segments, of the periods in time where anxiety rises and enjoyment falls (indicative of negative correlation), and the reverse tendency of falling anxiety and rising enjoyment (also indicative of a negative correlation). Further, there were occasions where anxiety and enjoyment both were increasing at the same time, a pattern not predicted by the negative correlation found in questionnaire research. Furthermore, results showed that the various correlational patterns were found even within the same person, suggesting that the relationship between anxiety and enjoyment can change from negative to positive based on what is happening in the communication context. The results of this study show the value of CDST concepts such as emergence, dynamic stability and soft assembly.
Teacher stress
The teacher has been a somewhat neglected topic in the psychology of language learning, with much more of the focus placed on learner psychology. Prior research suggests that language teaching can be a stressful occupation (Hiver & Dörnyei, 2015).
A study currently underway is examining teacher stress using the experience sampling method (Talbot et al., 2019). Experience sampling has been a preferred method of studying flow experiences in daily life (Csikszentmihalyi, 2014). The method provides research participants with a device (e.g. a pager or smartphone) that beeps at various points in time during the day. After receiving the beep, respondents answer questions about the activity they were performing at the moment. The method allows researchers to collect data in real time, as immediately as possible. Our study examined sources of teacher stress and uplifts, which are moments of positivity. We sought a diverse sample of teachers who were willing to install a new app on their phone. The app administered established, multi-item questionnaires on topics such as personality, wellbeing and stress (assessed on one occasion, not dynamically) along with multiple daily notifications (8 per day) to assess current stress levels dynamically through a series of structured responses that quickly described the context in which the beep arrived (e.g. I am in school, I am at home, etc.) as well as self-ratings of stress or uplifts.
The study examined 47 teachers, producing data points numbering in the tens of thousands. Summarizing that data is a challenge. On the one hand, individual level data analysis allows tracking of stress ratings over the time frame of the study. We can contextualize those fluctuations using information from questionnaires (teacher personality, wellbeing, life stressors) and demographic information. Yet this is not (yet) a description of a complex dynamic system. We have identified three teachers who scored high and three who scored low in wellbeing for case study analysis that triangulates information about the teacher and changes in stress over time. The challenge we face as researchers is to integrate the data to show the interactions among factors that contribute to teachers’ stress as part of the system of teachers’ emotional reactions to events, and not simply that there are highs and lows in the dynamics in stress ratings over time. We will look closely at the changes in stress ratings over time, asking questions such as ‘how quickly do those ratings change?’, ‘what is the teacher doing when she/he is making the ratings?’ and ‘how might additional information such as employment status or family context be factored into the changes in stress reaction?’ Preliminary results show the complex patterns of stress reactions in which a teacher’s home life, relationships, obligations, leadership activities and so on are interacting with both teaching and non-teaching activities to create stress on some occasions and uplifts on other occasions. Our plan is to identify the signature dynamics related to stress for the teachers who have high wellbeing scores and those with low wellbeing scores to see if there are discernible differences between the teachers. After the case studies are complete, the rest of the data set can be interrogated using the case study information to focus analysis. The data present challenges because a large number of data points need to be summarized without losing the complex interactions they show.
Self
The self in its various guises has been an increasing focus of research in SLA (Mercer & Williams, 2014). As a notion, it has been fragmented into various constructs designed to capture various aspects of self and typically reflecting different research perspectives. For example, self-efficacy is very tightly defined and typically measured through questionnaires, whereas identity is more broadly defined and connected to specific social roles and contexts, and is typically the focus of qualitative work.
Mercer (2015) has defined the self as a complex dynamic system. She has studied how the self functions on different levels of perception and across different timescales. The focus has been on how the different facets and aspects of self interact to create an overall emergent sense of self. In her 2015 study, Mercer focused on the dynamics of the self on different timescales. To do this, she collected data with four volunteer students on the timeframe of seconds/minutes using idiodynamic software, across minutes/hours within class using a survey, across days/weeks using journals and across weeks/months using interviews. The data were analysed on each level for dynamics and these were compared. She found that there were similar patterns of dynamics and ‘if… then’ signature dynamics (Mischel, 2004) across timescales. This refers to patterns where IF this happens, THEN this is likely to happen. These findings raise interesting questions about the role of fractalization in the dynamics of systems and thus the possibility of predicting dynamic patterns across timescales. The challenge for researchers is how to best integrate dynamic research across different timescales.
In summary, this brief overview of specific research reveals how studies designed and implemented from a CDST perspective are beginning to show some of the possibilities afforded by the approach. WTC, motivation, anxiety, enjoyment, stress