EFL Student-Teachers’ Emotional Engagement in an Afterschool Asynchronous Digital Storytelling Task

Abstract

Digital storytelling (DST) is an innovative pedagogical approach that integrates multimedia creation, personal narrative, and autonomy in L2 education. Yet, its influence on learner engagement remains underexplored in asynchronous delivery modes and non-conventional language learning settings, common in post-pandemic instructional practice. This study thus examines the engagement patterns of 34 student-teachers of English in an afterschool asynchronous DST task about teacher identity. The study further scrutinises their emotional engagement, given its impact on other engagement domains, and its relevance for online instructional design. Data were collected through a background information questionnaire, a validated student engagement questionnaire, and semi-structured interviews that focused on emotional engagement. Questionnaire data were analysed quantitatively using descriptive statistics and repeated measures ANOVA, and interview data were examined qualitatively using thematic analysis and specific emotional engagement-related frameworks. Results indicated participants’ higher cognitive and behavioural engagement, and lower emotional engagement. Their emotional engagement comprised positive emotions and anxiety, which emerged from specific subjective task values, autonomy, and task affordances in interaction with self-imposed personal standards and perceived digital skills. These findings challenge the common conceptualisation of emotional engagement merely as positive affect in L2 tasks and signal the importance of task- and learner-related factors in an engagement-driven online L2 pedagogy.

1. Introduction

The abrupt shift to emergency remote education (ERE) during COVID-19 transformed educational practices worldwide and exposed longstanding inequities in access, preparedness, and pedagogical readiness. Teachers across disciplines were required to redesign instruction with little time, training or infrastructural support, whilst students had to adapt rapidly to new digital environments and modes of participation (Bozkurt & Sharma, 2020; Gacs et al., 2020; Rapanta et al., 2020). In second language (L2) education, these challenges were particularly acute (H. Huang & Kurata, 2024). Teachers reported feeling underprepared to implement effective online pedagogies and struggled to cultivate interaction and communication in virtual spaces (Moorhouse & Kohnke, 2021; Russell, 2020). Learners similarly faced increased cognitive and emotional burdens, ranging from unfamiliarity with digital tools to heightened anxiety, frustration, and social isolation (Dewaele et al., 2024; MacIntyre et al., 2020; Ramsin & Mayall, 2019). The ERE context thus intensified the need for pedagogical approaches that could sustain meaningful participation, flexibility, and emotional well-being.

Within such context, DST emerged as a promising methodological option that provided students with a flexible learning environment through asynchronous delivery, reducing the stress linked to synchronous participation and unstable internet connectivity (Nair & Yunus, 2021). It also supported personal expression, creativity, and willingness to communicate (García-Pastor, 2021; Luan et al., 2024; Nair & Yunus, 2021), and has continued to be a sustainable pedagogical tool for L2 education in the post-pandemic era (Luan et al., 2024). Despite its benefits, a crucial concern during COVID19, shaping online language instruction is the need to maintain learner engagement (Han et al., 2021; Oraif & Elyas, 2021; Qiu et al., 2024; Zheng et al., 2023). Although extensive research has documented the importance of engagement for successful learning in traditional classroom tasks (Mercer, 2019), less is known about how it unfolds in digital L2 tasks, particularly in asynchronous non-classroom environments. Addressing this gap is crucial, given the centrality of technology in language education and the distinct potential of such tasks to engage learners (García-Pastor, 2021; Cristofol García & Appel, 2021; Qiu et al., 2024). This study thus investigates English as a foreign language (EFL) student-teachers’ engagement as they participated in an afterschool asynchronous DST task, that is, their active involvement across behavioural, cognitive, and emotional dimensions (Hiver et al., 2021; Philp & Duchesne, 2016) with a focus on their emotional engagement, i.e., the expression of their emotions (Dao, 2024; Hiver et al., 2024), given its strong influence in other dimensions of engagement (see Baralt et al., 2016; Peng et al., 2024), and its relevance for online instructional design (Hiver et al., 2021; Pekrun & Linnenbrink-García, 2012; Philp & Duchesne, 2016; Svalberg, 2018).

Therefore, the study extends the literature on L2 learner engagement in digital tasks and contributes to DST and engagement research by going beyond synchronous classroom digital story writing (Lim et al., 2022; Miao & Li, 2024). It also enriches emotional engagement studies by adopting a qualitative approach that foregrounds learners’ subjective experiences, whilst problematizing links between positive and negative affect, and engagement and disengagement respectively (Hiver et al., 2021; Mercer, 2019). It also offers insights into how DST can support engagement and drive online L2 pedagogy.

1.1. DST in L2 Learning and Instruction

Technically, DST refers to the process of creating short digital narratives, typically two to five minutes in length, that integrate text, images, music, sound, and movement into a coherent multimodal composition through the use of video editing software and web-based applications, tools, and platforms (Oskoz, 2025). One of the defining characteristics of DST is its adaptability to users’ levels of digital competence, as the resources available for digital story creation are “virtually limitless” (Hung, 2019, p. 26). These resources range from pre-installed software commonly available on digital devices, e.g., Windows Movie Maker, iMovie, Adobe Premiere Elements, or Microsoft PowerPoint, to cross-platform open-source programs such as OpenShot and Shotcut. They also include web-based applications and tools (e.g., WeVideo, VoiceThread, StoryJumper, Moovly) and social media-based environments and communities (e.g., Wikinovel, Storybird, Second Life), among others (Robin, 2016). This wide technological ecosystem allows L2 learner to select DST tools that best align with their needs, experience, and learning objectives. As a result, they may produce relatively simple digital stories based on narrated slideshows or pre-designed multimodal templates (e.g., using Microsoft PowerPoint or StoryJumper), or more complex productions that combine multiple modes and incorporate advanced editing features, sound effects, and animations (e.g., through OpenShot).

DST has also been defined as a technology-rich methodological approach for L2 learning and instruction that aligns with constructivist principles, providing L2 learners with opportunities to learn by doing and construct knowledge through the creation of digital artefacts. By positioning learners as active producers rather than passive consumers of multimodal content (see García-Pastor, 2021), DST foregrounds multimodality and meaning-making across semiotic modes (Kress, 2003). This process fosters personalised learning experiences, learner agency, and ownership over learning, whilst supporting language and multiliteracies development. Empirical research has documented such development in terms of gains in grammar and vocabulary (e.g., Reyes-Torres et al., 2012; Yu & Wang, 2025), as well as improvements in writing, reading, speaking, and listening skills (Bai & Xian, 2024; Castañeda, 2013; Cheung, 2021; C. C. Liu et al., 2019; Oskoz & Elola, 2016a; Ramírez Verdugo & Alonso Belmonte, 2007). In addition, DST has been shown to positively influence learners’ digital competence, critical thinking, creativity, and affective factors such as motivation and engagement (e.g., Bai & Xian, 2024; Chen, 2024; Chen Hsieh & Lee, 2023; Gregori-Signes, 2014; Yao et al., 2025; Wu & Chen, 2020; Yu & Wang, 2025). These studies have focused on synchronous DST pedagogies in the classroom setting. However, research on asynchronous DST in non-classroom environments remains limited, particularly with regard to its impact on key dimensions of L2 learning such as learner engagement.

1.2. Learner Engagement in L2 Education

Studies on learner engagement in L2 education that focus on technology, have typically dealt with engagement at the task level (Dao, 2024; Mercer, 2019; Sang & Hiver, 2021) or “engagement-in-the-moment” (Reinders & Nakamura, 2021, p. 137), i.e., students’ involvement in a language learning activity as manifested in their behavioural choices, and demonstrations of action through their cognitive, social, and emotional responses (Dao, 2024; Hiver et al., 2021; Philp & Duchesne, 2016; Teravainen-Goff, 2022). Whilst cognitive engagement is related to the use of learning strategies, metacognitive knowledge, and self-regulation to understand complex concepts and master knowledge and skills (Linnenbrink & Pintrich, 2003), behavioural engagement refers to effort and persistence, as observed through on-task participation and time on task (Philp & Duchesne, 2016; Sang & Hiver, 2021). Social engagement typically involves the initiation and maintenance of interaction with peers and the teacher during task performance (Hiver et al., 2024; Mercer, 2019; Svalberg, 2009), whilst emotional engagement has been linked to students’ affective responses to the task in hand (Philp & Duchesne, 2016); their attitudes and evaluations (Phung, 2017); their willing, purposeful, and autonomous dispositions towards the task (Svalberg, 2009); and their feelings of connection to, or disconnection from interlocutors during task completion (Baralt et al., 2016; Svalberg, 2009).

Importantly, there is ongoing debate regarding the operationalisation of these engagement dimensions, which has led to inconsistencies impeding comparison of findings across studies (Dao, 2024; Sang & Hiver, 2021; Zhou et al., 2021). Additionally, their conceptual boundaries also remain controversial, prompting certain scholars to argue that behavioural engagement is not a standalone dimension, but the observable manifestation of learners’ underlying cognitive and emotional states (Dao, 2024; Reeve, 2012; Svalberg, 2021). Social engagement has also engendered scepticism, as cognitive, behavioural, and emotional processes are embedded in social interaction (Mercer, 2019). Finally, emotional engagement has also been problematic, as it has often been identified through vague indicators different from the expression of discrete emotions (Hiver et al., 2024), and has frequently been framed through a simplistic alignment of positive emotions with engagement and negative emotions with disengagement (Hiver et al., 2024; Linnenbrink & Pintrich, 2003; Reeve, 2012; Sang & Hiver, 2021). Such associations overlook the context-sensitive and complex nature of this engagement dimension, underscoring the need to combine quantitative indicators with learners’ subjective accounts to better capture its nuanced character, an approach adopted in this study and detailed below.

1.3. L2 Learner Engagement in DST

Research on L2 learner engagement in DST has typically been conducted in synchronous, classroom-based environments with young and adult EFL learners, and has focused on cognitive engagement to the neglect of other engagement domains (e.g., Hung, 2019; Y.-Y. Huang et al., 2017; C. C. Liu et al., 2016, 2017). These DST studies also suggest that engagement is shaped by interacting learner- and task-related factors, including proficiency level (Y.-Y. Huang et al., 2017), cognitive and metacognitive strategy use (Y.-Y. Huang et al., 2017; Hung, 2019), self-efficacy (C. C. Liu et al., 2016), and instructional approach (C. C. Liu et al., 2017; Y. Liu & Tse, 2022). Contrary to these studies, a smaller body of work has examined behavioural and emotional engagement alongside cognitive engagement in DST both within classroom-based synchronous settings, and afterschool asynchronous contexts. However, the findings of these investigations have limited generalizability and present certain shortcomings, such as the absence of validated instruments for measuring engagement in DST, and the lack of qualitative exploration of learners’ emotional experiences (García-Pastor, 2021; Y. Liu & Tse, 2022; Naderpour, 2022; Peng et al., 2024). In addition, some of these studies also reveal a narrow focus on (i) L2 learners, which excludes groups like pre-service teachers, an important population who must themselves learn to design engaging digital tasks; and (ii) fanfiction stories, thus overlooking other digital story genres (Naderpour, 2022; Peng et al., 2024). A synchronous classroom-based study that illustrates several of these issues is Y. Liu and Tse’s (2022). These authors explored all dimensions of engagement in EFL learners, who received classroom-based DST instruction (experimental group) and traditional lessons (control group). They reported higher levels of cognitive and behavioural engagement in the experimental group, and no significant differences for emotional engagement in both groups. However, their findings are difficult to extend to other DST research, as they used a general classroom engagement questionnaire.

More recent investigations in afterschool asynchronous settings provide valuable insights into how agency, self-efficacy, self-confidence, learning journeys, task duration, task repetition, multimodal resources, and asynchronous instruction shape engagement (García-Pastor, 2021, Naderpour, 2022; Peng et al., 2024). In particular, Peng et al. (2024) illustrated how two Japanese EFL students’ cognitive, behavioural, emotional, and social engagement fluctuated in light of how they acted upon multifarious resources for the creation of fanfiction digital stories. Naderpour (2022) reported high levels of learner agency in seven Japanese EFL students after their experiences with fanfiction DST, which led to increased engagement and enhanced in-class learning. Lastly, García-Pastor (2021) found high levels of cognitive and behavioural engagement along with lower emotional engagement in college EFL learners, who developed a DST project in an asynchronous online context. Cognitive engagement appeared associated with the self-reflection processes triggered by the task; behavioural engagement with effort and time on task; and emotional engagement with positive emotions throughout the task. Despite offering a more comprehensive view of engagement in afterschool asynchronous DST, these studies rely on non-validated measures of engagement (e.g., García-Pastor, 2021), contrary to recent methodological recommendations (Lim et al., 2022; Miao & Li, 2024), along with dealing with L2 learners and fanfiction stories (Naderpour, 2022; Peng et al., 2024). The present study intends to address these limitations by exploring the engagement of student-teachers of EFL in an afterschool, asynchronous DST task that focused on their developing teacher identities. Engagement is investigated via Zhou et al.’s (2021) validated task engagement questionnaire, with particular emphasis on emotional engagement, defined as the expression of discrete emotions related to task participation (Hiver et al., 2024), and explored in post-task semi-structured interviews with the participants. This approach allows for testing prevailing assumptions linking positive emotions to engagement and negative emotions to disengagement, whilst examining alternative interpretations grounded in learners’ own perspectives. Accordingly, the study seeks to answer the following research questions (RQs):

• RQ1. What are the engagement levels of EFL student-teachers in an afterschool asynchronous DST task about their teacher identities?
• RQ2. What are the features of their emotional engagement in this task?

2. Materials and Methods

2.1. Participants

The participants were 34 student-teachers of EFL, enrolled in a one-year Master’s degree in Secondary Education at a public Spanish university, which qualifies graduates to teach English at the secondary level. The programme combines pedagogical coursework with supervised teaching practice and emphasises reflective approaches to teacher identity development. The DST task was implemented as an optional, non-assessed afterschool activity, separate from participants’ formal coursework, and framed as a reflective professional development activity. All participants belonged to a different class group from that of the researcher and included 6 males (17.6%) and 28 females (82.4%), reflecting the overrepresentation of women commonly observed in teacher education programmes internationally (e.g., European Commission, 2021). They were aged between 24 and 40 years at the time of the study (M = 26; SD = 3.98). Most of them were in their mid-twenties, with a few older students, a pattern consistent with typical Master’s-level cohorts (

Table 1. Participants’ demographics and other characteristics.

Category	Description	n	%
Gender	Male	6	17.6
	Female	28	82.4
Age	Between 24–26	24	70.6
	Between 27–30	5	14.7
	Between 31–35	3	8.8
	Between 36–40	2	5.9
Languages	Spanish–Catalan	34	100
English proficiency	B2–C2	34	100
Additional language	French (fair command)	6	17.6

). All participants are bilingual in Spanish and Catalan and held certified English proficiency levels ranging from B2 to C2 according to the CEFR (Council of Europe, 2020). In addition, six participants (17.6%) reported a fair command of French.

Participation in the study was voluntary, and a purposive convenience sampling method was employed, targeting student-teachers in the different class groups from the researcher, who met a specific inclusion criterion: the absence of prior experience in producing an introspective digital story. This criterion was applied to ensure that all participants performed the DST task from a comparable baseline of experience. Formal ethical approval was not required for this type of educational research under institutional guidelines. Nevertheless, the study adhered to well-established ethical principles: informed consent was obtained from all participants, and they were also ensured anonymity as well as exclusive usage of their responses for research purposes.

2.2. Task and Procedure

The DST task in this study was a reflexive task (Wu & Chen, 2020), in which the student-teachers were asked to produce an individual 5 to 7-min digital story, describing experiences, beliefs, and emotions that mostly defined their language teacher “selves”. The reflection prompts guiding the task were based on the following questions: “Who are you as a teacher?”; “How have you experienced the profession thus far?”; “What do you believe language teaching should be?”; “How have you felt teaching?”; and “Which specific emotions have you experienced and why?” They were also encouraged to link these with knowledge gained in university courses and their teacher training in an attempt to trigger an introspection process that allowed for exploration of their teacher identities, and pedagogical content knowledge and multiliteracy development in English. The task was designed to be performed in their homes for 3 weeks, following the four phases of digital story creation (Oskoz & Elola, 2016b; Robin, 2016; Yang & Wu, 2012) (Figure 1).

Thus, in the pre-production phase, they needed to (i) gather information for their personal narratives; (ii) write a draft of their scripts, which received delayed feedback from the researcher; and (iii) design a storyboard, which was also checked by the latter. The production phase focused on the selection and analysis of images, along with voice recording, and the post-production phase centred on the use of DST resources, all of which were explained through guidelines provided by the researcher that contained links to video tutorials on two technologies (Microsoft PowerPoint and OpenShot). These tools were selected because of their popularity and their potential to cater to low and high-technology savvy students. Although participants could choose the DST technology, they used the proposed software, with most using OpenShot. Finally, the distribution phase is intended to make them share and discuss their DS voluntarily by watching them and writing comments about them in a shared internet space.

Table 2. Description of task phases.

Phase	Duration	Activities	Researcher Support	Tools	Outputs
Pre-production (Oskoz & Elola, 2016b; Robin, 2016; Yang & Wu, 2012)	Week 1	Gathering information for personal narratives (self-teacher and other documents, images). Drafting scripts: (i) content focus on teacher identity; (ii) language focus on grammar, vocabulary, coherence, cohesion. Designing storyboards	Delayed written feedback on scripts and storyboards	Text editor, storyboard examples from the internet	Script, storyboard
Production (Oskoz & Elola, 2016b; Robin, 2016; Yang & Wu, 2012)	Week 2	Selecting, analysing images. Recording voice-over narration	PowerPoint document on image types and functions	Digital images, audio recording devices	Image set, recorded narration
Post-production (Robin, 2016; Yang & Wu, 2012)	Week 3	Editing, assembling digital stories	PowerPoint guidelines with links to video tutorials	Microsoft PowerPoint, OpenShot (other alternatives)	Final digital story
Distribution (Robin, 2016; Yang & Wu, 2012)	End of Week 3	Sharing, watching commenting peers’ digital stories	Creation, organization, moderation of shared space	Shared online platform	Peer feedback, discussion

illustrates these steps further.

2.3. Data Collection Instruments

Zhou et al.’s (2021) validated engagement questionnaire and semi-structured interviews served as data collection instruments. Zhou et al.’s (2021) 3-scale questionnaire was administered at the end of the study to respond to RQ1. This questionnaire is based on 5-point Likert scale statements with response alternatives ranging from “strongly disagree” to “strongly agree”. The behavioural scale comprises items that refer to students’ task-related participation, effort, perseverance, and attention during their English lesson. The emotional scale contains statements on their related positive and negative emotions. Finally, the cognitive scale includes items on their use of cognitive, metacognitive, and problem-solving strategies, as well as their cognitive effort or lack of it at the task level in their English class. In this study, statements were adjusted across these scales for a more context-sensitive operationalisation of engagement (Philp & Duchesne, 2016). Item adaptations were limited to contextual reference to the DST task and did not alter the original constructs measured by the questionnaire. Cronbach’s alpha coefficients were then estimated with α = 0.79 for behavioural engagement; α = 0.82 for emotional engagement; and α = 0.80 for cognitive engagement, indicating a good level of internal consistency. The adapted questionnaire items are provided in Appendix A. Questionnaire responses are made available in the Results section of this paper.

To address RQ2, semi-structured interviews were conducted with the participants to obtain in-depth information about their task engagement, with particular attention to emotional engagement. The interviews were conducted online via Zoom, which has been reported as highly suitable for qualitative data collection from the perspective of researchers and participants (Archibald et al., 2019), and in the student-teachers’ first language (L1) to promote comfort and facilitate rich, nuanced expression of affective experience (Rolland, 2023). A semi-structured format was adopted to allow for consistency across interviews, whilst enabling participants to elaborate on personally salient emotional experiences (Kvale & Brinkmann, 2015). The interviews lasted 20–40 min each, totalling approximately 17 h and 32 min of ongoing talk. All interviews were video-recorded and transcribed. Interview questions were intended to elicit participants’ perceptions of the task (questions 1 and 2); their emotional engagement during task performance and its sources (questions 3 and 4); and the specific sources of their positive and negative emotional engagement (questions 5 and 6). The interview protocol is provided in Appendix B. Due to ethical restrictions, the raw interview data are not publicly available, but may be shared in anonymised form upon reasonable request.

2.4. Data Analysis

Participants’ responses to the engagement questionnaire were analysed using SPSS 28. Descriptive statistics were calculated for behavioural, emotional, and cognitive engagement. Data normality was assessed using Shapiro-Wilk tests as well as skewness and kurtosis values and their standard errors. No extreme outliers were detected. To examine differences in engagement across domains, a one-way repeated-measures ANOVA was computed, with engagement domain as the within-subject factor and level of engagement as the dependent variable. Mauchly’s test of sphericity indicated that the assumption was violated (W = 0.60, χ²(2) = 23.53, p < 0.001). Therefore, a Lower-Bound correction was applied. Bonferroni-adjusted pairwise comparisons were subsequently performed to identify differences between domains. Effect sizes for ANOVA were reported using partial eta squared (η²p), and Cohen’s dz for pairwise comparisons, which is appropriate for within-subject contrasts. They were then interpreted following conventional benchmarks.

The qualitative analysis of the interviews complemented the quantitative study and delved into the student-teachers’ emotional engagement. Therefore, their affective reactions to the task were first identified through emotion words and expressions in their narrated experiences, and then initially coded as specific positive and negative emotions, taking certain emotion frameworks as a starting point (Fredrickson, 2013; Pekrun & Linnenbrink-García, 2012). As an example, the statement “Me ha gustado mucho usar distintos recursos multimedia para expresarme” (I enjoyed a lot using different multimedia resources to express myself) (TC, male participant, 40) was coded as “enjoyment”, given the definition of this emotion as positive affect, characterised by happiness and contentment (Fredrickson, 2013). Through this process, recurrent affective patterns were identified and grouped into preliminary emotion categories, allowing positive and negative emotions to emerge from the data. A total of 14 emotion categories were then established. Another researcher independently analysed part of the interviews using a codebook that contained operational definitions of these categories, distinct codes for each, and illustrative examples from the data. The resulting categories from researchers’ independent analyses were compared and fine-tuned in several discussion rounds until consensus was reached in 96% of the cases. The final coding scheme, comprising the resulting codes, their corresponding emotion categories, definitions, and examples, is presented in

Table 3. Emotion categories, descriptions, and examples.

Emotion Categories	Description	Example
AMUS (amusement)	Affective state characterized by joviality, laughter.	“It was funny to hear my own voice shake”.
ANX (anxiety)	Affective state characterized by nervousness, worry.	“It created a lot of anxiety for me to have to make a video without having enough resources at my disposal”.
AWE (awe)	Affective state characterized by wonder, amazement.	“I felt admiration when I wrote about my English teacher in primary school…”.
DISC (discouragement)	Affective state characterized by insecurity, dejection.	“…I was insecure about my video and I kept changing it all the time”.
EXC (excitement)	Affective state characterized by enthusiasm, thrill.	“…when I finished it, I felt very enthusiastic and watched it again…”.
FREE (freedom)	Affective state characterized by liberty, choice.	“I have felt free by choosing what to tell and how to tell it”.
FRUS (frustration)	Affective state characterized by exasperation, defeat.	“I found myself being frustrated when something did not go the way I planned and I couldn’t reach the teacher”.
GRAT (gratitude)	Affective state characterized by thankfulness, appreciation.	“I feel thankful for this task”.
INTER (interest)	Affective state characterized by curiousness, attentiveness.	“It was interesting to think about me as teacher”.
JOY (enjoyment)	Affective state characterized by happiness, contentment.	“I really enjoyed doing it”.
LOV (love)	Affective state characterized by affection, like.	“The feelings that have marked me the most during this work have been the affection and love to remember those people and those times”.
PRID (pride)	Affective state characterized by self-assurance, satisfaction.	“I have felt really proud of my story so far”.
REL (relief)	Affective state characterized by peace, serenity.	“I felt relieved after I saw that my script was coming along”
SAD (sadness)	Affective state characterized by misery, pain.	“I have felt sad to think that many of the experiences I talk about in my story will not be repeated…”.

.

3. Results

3.1. Quantitative Results

The quantitative results for RQ1, which interrogated about the student-teachers’ levels of engagement in the digital writing task at hand, indicated that their cognitive and behavioural engagement were high (M = 4.67, SD = 0.25; M = 4.41, SD = 0.36), whereas their emotional engagement was lower albeit still elevated (M = 4.21, SD = 0.46) (

Table 4. Descriptive statistics of student-teachers’ engagement.

Engagement	M	SD	Min.	Max.	Skewness	Kurtosis
Behavioural engagement	4.41	0.36	3.29	5.00	−0.97	1.57
Emotional engagement	4.21	0.46	2.80	4.80	−1.25	2.09
Cognitive engagement	4.67	0.25	4.13	5.00	−0.27	−0.66

Note. N = 34; SE for skewness = 0.40; SE for kurtosis = 0.78.

).

Shapiro–Wilk tests indicated departures from normality for behavioural (W = 0.93, p = 0.035) and emotional engagement (W = 0.90, p = 0.004), whereas cognitive engagement did not significantly deviate from normality (W = 0.94, p = 0.053). Given the robustness of repeated-measures ANOVA to moderate normality violations and the absence of extreme outliers, parametric analyses were retained. The analysis revealed a significant main effect of engagement domain with a medium-to-large effect size (F(2, 66) = 8.79, p < 0.001, η²p = 0.21), indicating substantial differences in engagement levels across domains (

Table 5. Repeated measures ANOVA.

Source	Sum of Squares	df	MnSq	F	p	η2p
Engagement domain	3.53	1	3.53	8.79	0.006	0.21
Error (Engagement domain)	13.26	33	0.40

Note. N = 34. MnSq = mean square; η²p = partial eta squared.

).

Bonferroni-adjusted pairwise comparisons revealed that cognitive engagement was significantly higher than both behavioural engagement (t(33) = −3.92, p < 0.001, dz = 0.67) and emotional engagement (t(33) = −5.76, p < 0.001, dz = 0.99), with medium-to-large and large effect sizes, respectively. The difference between behavioural and emotional engagement did not reach statistical significance (t(33) = 2.02, p = 0.052) and was associated with a small-to-medium effect size (dz = 0.35) (

Table 6. Pairwise comparisons.

Comparison	t	df	p	dz
Behavioural vs. Emotional	2.02	33	0.052	0.35
Behavioural vs. Cognitive	−3.92	33	<0.001	0.67
Emotional vs. Cognitive	−5.76		<0.001	0.99

Note. N = 34. Bonferroni correction was applied. Effect sizes are reported as Cohen’s dz.

). These pairwise results clarify the significant omnibus effect observed in the repeated-measures ANOVA, indicating that domain differences were primarily driven by higher levels of cognitive engagement.

Participants attributed their behavioural engagement to their efforts to perform to the best of their ability despite difficulties (item 3; M = 4.61; SD = 0.49); their careful attention to the researcher’s delayed feedback (item 7; M = 4.61; SD = 0.60); and their active participation in all components of the task (item 2; M = 4.58; SD = 0.70). Reverse-coded items further indicate low levels of disengaged behaviour, such as pretending to work or attending to unrelated activities. To enhance transparency in the operationalisation of engagement dimensions, item-level descriptive statistics are reported alongside domain-level results.

Table 7. Descriptive statistics for behavioural engagement.

Behavioural Engagement	M	SD	Min.	Max.	Skewness	Kurtosis
1. I stayed focused even when it was difficult to understand.	4.02	0.79	2.00	5.00	−0.81	0.88
2. I participated actively in all the different parts.	4.58	0.70	2.00	5.00	−2.01	4.66
3. I kept trying my best even when it was hard.	4.61	0.49	4.00	5.00	−0.50	−1.85
4. I just pretended like I was working. (R)	4.61	0.49	4.00	5.00	−0.50	−1.85
5. I did other things when I was supposed to be paying attention. (R)	4.56	0.56	3.00	5.00	−0.79	−0.38
6. I paid attention and read/watched carefully the guidelines provided by the teacher.	3.85	0.92	2.00	5.00	−0.18	−0.97
7. I paid attention and read carefully the feedback provided by the teacher.	4.61	0.60	3.00	5.00	−1.36	0.94

Note. N = 34; SE for skewness = 0.40; SE for kurtosis = 0.78.

thus illustrates behavioural engagement results.

The student-teachers also reported that their levels of emotional engagement were mainly based on their desire to understand what they were learning (item 10; M = 4.82; SD = 0.38), which reveals their interest through their urge to learn and immerse themselves in it (see Fredrickson, 2013). Their emotional engagement was also related to their enjoyment in what they were learning (item 9; M = 4.64; SD = 0.73), and how proud they felt about their achievements (item 12; M = 4.64; SD = 0.65) (

Table 8. Descriptive statistics for emotional engagement.

Emotional Engagement	M	SD	Min.	Max.	Skewness	Kurtosis
8. I looked forward to a similar task in another course.	3.38	0.92	2.00	5.00	−0.12	−0.85
9. I enjoyed learning new things.	4.64	0.73	2.00	5.00	−2.25	4.87
10. I wanted to understand what I was learning.	4.82	0.38	4.00	5.00	−1.77	1.22
11. I felt good while I was doing the work.	4.26	0.70	2.00	5.00	−0.97	1.76
12. I felt proud of my accomplishments.	4.61	0.65	2.00	5.00	−2.20	6.54
13. I felt frustrated while I was doing the work. (R)	3.29	1.24	1.00	5.00	−0.30	−0.92
14. I felt anxious/nervous while I was doing the work. (R)	3.03	1.31	1.00	5.00	0.19	−1.30
15. I was bored. (R)	4.62	0.49	4.00	5.00	−0.50	−1.85
16. I didn’t want to do the work. (R)	4.68	0.72	2.00	5.00	−2.42	5.58
17. I felt that I didn’t care about the work. (R)	4.79	0.47	3.00	5.00	−2.36	5.29

Note. N = 34; SE for skewness = 0.40; SE for kurtosis = 0.78.

). Reverse-coded items further indicate low levels of disengaging emotions such as boredom, reluctance, and apathy, suggesting that participants were emotionally invested in the task. At the same time, moderate levels of challenge-related emotions, i.e., anxiety and frustration, were reported, pointing to an emotionally complex engagement profile rather than a uniformly positive affective experience.

Participants’ cognitive engagement was primarily characterised by attentive revision of their work (item 18; M = 4.67, SD = 0.47), efforts to understand and learn from their mistakes (item 21; M = 4.55, SD = 0.50), and the integration of prior knowledge with new learning during the task (item 20; M = 4.44, SD = 0.70) (

Table 9. Descriptive statistics for cognitive engagement.

Cognitive Engagement	M	SD	Min.	Max.	Skewness	Kurtosis
18. I went through my work carefully to make sure it was done right.	4.67	0.47	4.00	5.00	−0.79	−1.46
19. I thought about different ways to solve problems in my work.	4.38	0.73	3.00	5.00	−0.76	−0.72
20. I tried to connect new learning to the things I already learned before.	4.44	0.70	2.00	5.00	−1.43	2.91
21. I tried to understand my mistakes when I got something wrong.	4.55	0.50	4.00	5.00	−0.24	−2.06
22. I preferred someone to do the work for me than do the work myself. (R)	4.88	0.32	4.00	5.00	−2.48	4.43
23. I didn’t think too hard while I was doing the work. (R)	4.94	0.23	4.00	5.00	−3.92	14.24
24. I only focused on the easy parts because it was hard. (R)	4.74	0.51	3.00	5.00	−1.81	2.69
25. I did just enough to get by. (R)	4.74	0.61	2.00	5.00	−3.04	11.09

Note. N = 34; SE for skewness = 0.40; SE for kurtosis = 0.78.

). High levels of cognitive engagement were further evidenced by their rejection of cognitively disengaging behaviours such as minimal-effort task completion or avoidance of the cognitively demanding parts of the task, as reflected in the high means of reverse-coded items.

3.2. Qualitative Results

In response to RQ2, the qualitative analysis examined the features of student-teachers’ task emotional engagement in their narrated interview accounts. Fourteen emotion categories were identified (see Table 3); however, the present section focuses on those emotions that were most salient and functionally relevant to participants’ emotional engagement, as reported in their narrations, namely enjoyment (JOY), freedom (FREE), interest (INTER), and anxiety (ANX). Other emotions such as pride, excitement and frustration showed a low incidence in participants’ depictions. Amusement, awe, gratitude, love, relief, discouragement, and sadness were identified in only one or two instances. The excerpts presented below are thus illustrative examples of recurrent patterns across the interviews rather than isolated individual experiences. Emotional engagement in the interview data was predominantly characterised by these activating positive emotions and anxiety, which functioned as an indicator of high personal investment instead of emotional disengagement. These emotions emerged from the convergence of high task value and perceived control (see Dao, 2024; Pekrun & Linnenbrink-García, 2012) together with the affordances of DST for multimodal self-expression (see Oskoz & Elola, 2016a; Oskoz, 2025). The high value attributed to the DST task stemmed from its creative and identity-oriented nature, as well as participants’ perceptions of its attainability. This perception was underpinned by a sense of control, which afforded participants autonomy over content, modes, and technological choices. All these factors contributed to the emergence of the aforementioned emotions, thereby supporting sustained emotional engagement.

Enjoyment (JOY) surfaced as one of the most frequent emotions, which participants consistently associated with their appraisals of the DST task as personally meaningful and conducive to identity work. More specifically, they related their enjoyment to the creative affordances of DST, particularly the use of multimedia elements to construct and communicate their teacher identities in an authentic manner (García-Pastor, 2021). Therefore, enjoyment was not merely a hedonic response to task completion, but it was embedded in processes of meaning making and genuine identity expression, as suggested by certain engagement and DST research (e.g., Peng et al., 2024). Extract 1 illustrates this pattern:

Example 1 

(IC, female, 24). Me ha encantado usar nuevas apps, páginas web, edición y fotografía para ser creativa (JOY), así que me lo he pasado muy bien en esta tarea (JOY). He podido mostrar mi pasado y las cosas en las que creo en un docente, y eso me gusta, porque he podido mostrar quien soy realmente a otras personas (JOY). (I enjoyed working with new apps, webpages, edits and photography to be creative (JOY), so I really enjoyed this task very much (JOY). I could show my past and the things that I believe in as a teacher, and I like that, because I was able to show who I really am to others (JOY).

This excerpt exemplifies the frequent emergence of enjoyment in the data, and its grounding in creative agency and authentic self-expression, two core features of DST (Robin, 2016). Enjoyment appeared to broaden participants’ thought-action repertoires, encouraging experimentation with multimodal resources and heightened involvement in identity work (see Fredrickson, 2013), which supported sustained emotional engagement.

Freedom (FREE) emerged as the second most commonly reported emotion in the interviews. This emotion operated as a broad affective state characterised by autonomy, choice, and control over task-related decisions (Naderpour, 2022). Participants emphasised the freedom they experienced in selecting the content and modes of their digital stories in light of the flexibility of DST tools (García-Pastor, 2021; Hung, 2019; Oskoz, 2025), and indicated that such freedom typically produced enjoyment and interest. Therefore, these positive emotions frequently co-occurred in the data, generating student-teachers’ emotional engagement as shown in Example 2:

Example 2 

(CL, female, 24). Para mí ha sido un placer hacer un relato digital sobre mi identidad docente (JOY), porque me he sentido libre de elegir qué decir y cómo (FREE). (For me, making a digital story based on my teacher identity has been a pleasure (JOY), because I have felt free to choose what to say and how (FREE)).

This extract illustrates CL’s expression of freedom through explicit reference to autonomy in task decisions. Such a sense of control led her to enjoy task performance, increasing her engagement, as suggested in the engagement literature regarding autonomy and engagement (Egbert, 2003; Pekrun & Linnenbrink-García, 2012). These findings also resonate with DST research that emphasises learner agency and ownership as central to engagement in digital story writing (e.g., Bai & Xian, 2024; Naderpour, 2022).

Interest (INTER) emerged as another salient positive emotion shaping participants’ emotional engagement. It was associated with both reflective meaning-making and audience-oriented design. Thus, it was described as arising from opportunities for self-reflection regarding one’s teacher identity, as well as from the challenge of crafting engaging multimodal narratives through the use of diverse resources. These two aspects underpinning this emotion are illustrated in Examples 3 and 4:

Example 3 

(SM, female, 25). Creo que este tipo de tareas es muy interesante porque […] es agradable reflexionar con más profundidad sobre qué tipo de docentes somos o queremos ser (INTER). (I think that this type of task is very interesting because […] it is pleasant to reflect more deeply on what kind of teachers we are or we want to be (INTER)).

Example 4 

(TC, male, 40). Me interesaba mucho usar distintos recursos para captar la atención de la audiencia y que estuvieran entretenidos (INTER). (I was very interested in using different resources to catch the audience’s attention and entertain them (INTER)).

Both excerpts were coded as INTER, yet they highlight complementary aspects of interest: inward-oriented reflection and outward-oriented communicative design, respectively. Whilst the learner engagement literature has commonly highlighted the introspective dimension of interest through the conceptualisation of this emotion as creating the urge to explore, learn, and immerse oneself in novelty, thereby expanding the self (Egbert, 2003; Fredrickson, 2013), DST research has typically underscored its outward-oriented aspect through a focus on audience awareness (Robin, 2016).

Finally, anxiety (ANX) was the most salient negative emotion identified in the interviews; however, its functional role was not uniformly disengaging. Participants described anxiety both as a disengaging emotion that delayed task initiation and hindered video editing, as well as an engaging one linked to excitement, self-demands, and the desire to produce a high-quality digital story. Their accounts are thus consistent with Pekrun and Linnenbrink-García’s (2012) distinction between negative emotions that hinder engagement and those that fuel it. Example 5 illustrates anxiety as both engaging affect related to high task value and self-imposed performance standards, and disengaging affect.

Example 5 

(TC, male, 40). …hacer el video fue la parte que más me estresó, porque a veces el ordenador iba más lento y no hacía lo que querías (ANX). Así que eso me puso un poco nerviosa, porque estaba emocionada (EXC) y quería hacer un video bonito (ANX). (…video making was the most anxious part, since it was slower and sometimes the computer didn’t do what you wanted (ANX). Therefore, that made me a little nervous, because I was excited and wanted to make a nice video (ANX).

Therefore, anxiety often co-occurred with positive affect, and although temporarily disengaging, it did not undermine participants’ overall engagement, suggesting that high task value and personal investment mitigated its negative effects. This finding aligns with prior DST research showing that technical challenges that initially raise stress, ultimately support engagement and skill development (e.g., Chen Hsieh & Lee, 2023).

Taken together, the qualitative findings indicate that emotional engagement in the after-school asynchronous DST task was predominantly based on positive affect that was related to high task values and a sense of control in interaction with DST affordances. These appraisals promoted the use of multimodal resources and supported identity-related meaning-making, thus broadening participants’ learning experience by fostering experimentation, self-reflection, and persistence. Anxiety also played a salient but dual role, functioning both as an initial barrier and an activating emotion, also linked to task value and personal standards. These insights complement the quantitative results by clarifying the functional dynamics underlying the levels of emotional engagement observed, particularly the prominence of enjoyment and interest relative to other emotions.

4. Discussion

This study set out to examine EFL student-teachers’ engagement in an afterschool asynchronous DST task on their teacher identities (RQ1), as well as the features of their related emotional engagement (RQ2). By combining validated quantitative measures with qualitative interview data, it is intended to provide a more nuanced account of engagement in a non-classroom, asynchronous digital learning environment, an instructional context that has largely been underexplored in L2 engagement research. With regards to RQ1, the quantitative findings indicate high levels of behavioural, emotional, and cognitive engagement, with cognitive engagement emerging as significantly higher than behavioural and emotional engagement. These results are consistent with previous classroom studies of engagement in synchronous DST, which have reported learners’ high levels of cognitive engagement, often linked to cognitive strategy use, self-regulation, and reflection (e.g., Hung, 2019; Y.-Y. Huang et al., 2017; C. C. Liu et al., 2016). The present findings thus confirm that digital story writing remains cognitively engaging even when implemented asynchronously in out-of-class settings, suggesting that the reflective and problem-solving affordances of DST (e.g., identity exploration and revising, respectively) can also be sustained through self-regulation and learner agency in asynchronous contexts (e.g., Hung, 2019; Peng et al., 2024). Therefore, teacher-led scaffolding and synchronous interaction, albeit relevant (e.g., Castañeda, 2013; Gregori-Signes, 2014; Oskoz & Elola, 2016a), are not a prerequisite for cognitive engagement in digital story composition.

At the same time, the high levels of behavioural engagement observed in this study contrast with concerns frequently raised regarding reduced effort, persistence, and attention in asynchronous online learning (Han et al., 2021; Oraif & Elyas, 2021). Participants reported sustained effort, careful attention to feedback, and active involvement across all task phases, which indicates that fully online asynchronous environments may not necessarily be disengaging on behavioural grounds. These findings also diverge from those of Peng et al. (2024), who reported a gradual decline in behavioural engagement during an extra-curricular DST project due to the time-consuming and repetitive character of the digital composition tasks and competing academic obligations. In the present study, however, participants attributed their behavioural engagement to the personally meaningful and identity-oriented nature of the reflexive DST task, e.g., SM, female, 25: “El hecho de tener que hablar sobre mí y mi vida me animaba a querer hacer el video” (The fact that I had to talk about myself, and my life made me want to make the video). The task thus positioned the student-teachers as authors of digital narratives about their own lives (see Wu & Chen, 2020), fostering a strong sense of ownership and responsibility for learning in line with previous DST research (see García-Pastor, 2018, 2021; Nair & Yunus, 2021; C. C. Liu et al., 2019). These task features appear to have facilitated their behavioural engagement even in the absence of synchronous monitoring, which lends further support to the role of learner-generated content in enhancing engagement in L2 tasks (Lambert et al., 2016; Phung, 2017) and suggests that online asynchronous tasks need not be behaviourally disengaging when they are personally relevant and well-scaffolded.

Emotional engagement, whilst still high, was lower than cognitive and behavioural engagement at a statistically significant level only when compared to the cognitive domain. These results are consistent with DST research that emphasizes its potential to promote cognitive aspects of learning (e.g., critical thinking, creativity, and self-regulation) (Bai & Xian, 2024; Chen, 2024; Gregori-Signes, 2014; C. C. Liu et al., 2017), as well as engagement studies that focus on cognitive engagement, and mainly report gains in this engagement domain to the neglect of behavioural and emotional engagement (e.g., Hung, 2019; Y.-Y. Huang et al., 2017; C. C. Liu et al., 2016). Emotional engagement was also found to comprise both positive and negative emotions. These findings partly diverge from some DST and engagement research, in which emotional engagement was shaped by positive affect (García-Pastor, 2021; Y. Liu & Tse, 2022; Peng et al., 2024), and suggest that emotional engagement in digital story writing may be more complex and context-sensitive, as further elucidated by the qualitative findings obtained in response to RQ2.

The qualitative results thus reveal that the student-teachers’ emotional engagement mainly consisted of a constellation of certain activating positive emotions, i.e., enjoyment, freedom, and interest, alongside anxiety, which fluctuated from a potentially disengaging emotion to engaging affect embedded within an overall positive emotional ecology. These positive emotions frequently co-occurred and were linked to participants’ perceptions of task value, autonomy, and opportunities for identity expression. Task value was grounded in personal meaning, relevance, creativity, and investment in identity work, which functioned as psychological drivers of enjoyment and interest, thereby sustaining emotional engagement (see Dao, 2024). These findings resonate with DST and engagement research that reports heightened emotional engagement in digital story writing, precisely when learners perceive it as creative, relevant to their personal interests, and conducive to identity work, as well as affording opportunities to exercise choice and express personal voice (Y. Liu & Tse, 2022; Naderpour, 2022). Although enjoyment was more commonly associated with these task appraisals than interest, the latter also supported identity expression by motivating self-reflection and exploration (see Fredrickson, 2013).

Task value was also based on participants’ perceptions of the DST task as achievable, along with autonomy and perceived control, which contributed to generating freedom. These findings align with learner engagement research showing higher levels of emotional engagement in minimally constraining L2 tasks (e.g., Nakamura et al., 2021; Phung et al., 2021). More specifically, the action choice embedded in the DST task, i.e., freedom regarding work methods, pace, and effort during task performance (Phung et al., 2021), enabled student-teachers to tailor their digital stories to their preferences and abilities, thereby heightening their emotional engagement, as indicated in the following statements by one of the participants, namely, GP, female, 23: “Me encantó ir a mi ritmo probando fotos y videos míos para hacer el video” (I enjoyed working at my own pace using my pictures and videos to make the video). In addition, the optional character of the task, which was unrelated to formal coursework, further enhanced their sense of freedom by reducing performance pressure, which also promoted emotional engagement, as reflected in the following comment by JG (male, 25): “Disfruté mucho haciendo el relato digital, porque no me tenía que preocupar por ninguna nota” (I enjoyed a lot making the digital story, because I didn’t have to worry about any grade).

Anxiety mostly appeared as an affective marker of personal investment and high task value, particularly when participants perceived the task as meaningful and identity-relevant and felt compelled to meet self-imposed quality expectations. These findings are consistent with reported patterns of emotional engagement in action-choice L2 tasks, in which learners’ anxiety facilitated task completion by motivating them to perfect their work and boosting their emotional engagement (Nakamura et al., 2021; Phung et al., 2021). However, anxiety also emerged as a disengaging emotion when autonomy and perceived control over the task were temporarily disrupted by uncertainty at task onset, and insecurities regarding technical issues. As participants regained both out of a balance between these challenges and perceived self-efficacy, anxiety shifted from a disengaging to an engaging emotion, co-occurring with positive affect, as exemplified by IC’s words (female, 24): “Al hacer el video me puse nerviosa, porque había trozos negros, pero conseguí unir bien las imágenes y el video quedó perfecto” (I was anxious when editing the video, because there were black bits, but I was able to join images well, and the video turned out to be perfect). These findings echo research showing that a balance between task demands and learners’ skills fosters flow (e.g., Egbert, 2003), whilst challenging the assumption that positive emotions are inherently “task-facilitating” and negative emotions “task-withdrawing” (Reeve, 2012, p. 150) in the learner engagement literature (Hiver et al., 2024; Linnenbrink & Pintrich, 2003; Philp & Duchesne, 2016; Sang & Hiver, 2021).

5. Conclusions

This study examined EFL student-teachers’ engagement in an afterschool asynchronous digital storytelling task focusing on teacher identity. The findings indicate that the student-teachers experienced high levels of cognitive and behavioural engagement, alongside comparatively lower emotional engagement in line with much prior DST and engagement research. However, emotional engagement emerged as a dynamic construct encompassing both activating positive emotions and functional anxiety, diverging from emotional engagement patterns reported in earlier studies. While initial anxiety occasionally led to disengagement, it mainly operated as an activating emotion that supported sustained engagement and task completion. Participants’ distinct emotional engagement appeared related to high subjective task value, autonomy, and opportunities for identity expression in interaction with self-imposed performance standards and perceived digital competence. These findings respond to calls for more empirical evidence on how learners’ task perceptions shape engagement processes in L2 learning. They further extend existing research by illustrating the complex emotional dynamics underlying engagement in DST tasks, highlighting anxiety’s productive role in emotional engagement and the significant contribution of task appraisals, task affordances, and individual factors to its emergence.

Pedagogically, these results suggest that L2 teachers should design digital story writing tasks that involve reflective and creative learner-generated content, as well as freedom of action regarding content, modes, technological choices, pace and effort, whilst keeping a balance between task performance goals and students’ abilities in order to increase learner engagement. Cognitive engagement could be further enhanced by encouraging iterative revision of their work through (i) teacher and/or peer explanatory feedback, and (ii) linking prior knowledge with the new insights gained through the task. However, it is also crucial for teachers to offer substantial guidance during the initial stages of the task and the process of video editing to mitigate potential disengaging anxiety.

The study is not without limitations. First, the use of a convenience sample of EFL student-teachers from a specific learning context limits the generalizability of the findings, as well as the absence of a control group. Future studies employing larger and more diverse samples across institutional contexts and including control groups are needed to validate and extend the results obtained in this study. Additionally, the absence of guided reflective journals restricted access to participants’ ongoing cognitive and emotional processes during task engagement. Further L2 learner engagement and DST research should thus consider including such data collection instruments or similar reflective methods along with exploring the relationship between engagement, students’ learning outcomes, and other aspects of the learning process (e.g., the mediating role of feedback and scaffolding). Empirical investigation into AI use and its impact on learner engagement, agency, and authorship in DST is also timely, given the increasing role of AI-powered tools in L2 education in general, and L2 writing in particular.