Language Teaching Research
© The Author(s) 2021
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Engagement in language
learning: A systematic review
of 20 years of research
methods and definitions
Florida State University, USA
Ali H. Al-Hoorie
Royal Commission for Jubail and Yanbu, Saudi Arabia
Joseph P. Vitta
Rikkyo University and Kyushu University, Japan
Florida State University, USA
At the turn of the new millennium, in an article published in Language Teaching Research in 2000,
Dörnyei and Kormos proposed that ‘active learner engagement is a key concern’ for all instructed
language learning. Since then, language engagement research has increased exponentially. In this
article, we present a systematic review of 20 years of language engagement research. To ensure
robust coverage, we searched 21 major journals on second language acquisition (SLA) and applied
linguistics and identified 112 reports satisfying our inclusion criteria. The results of our analysis
of these reports highlighted the adoption of heterogeneous methods and conceptual frameworks
in the language engagement literature, as well as indicating a need to refine the definitions and
operationalizations of engagement in both quantitative and qualitative research. Based on these
findings, we attempted to clarify some lingering ambiguity around fundamental definitions, and to
more clearly delineate the scope and target of language engagement research. We also discuss
future avenues to further advance understanding of the nature, mechanisms, and outcomes
resulting from engagement in language learning.
Phil Hiver, Florida State University, 1114 West Call Street, G128 Stone Building, Tallahassee, FL 32306,
1001289LTR0010.1177/13621688211001289Language Teaching ResearchHiver et al.
2 Language Teaching Research 00(0)
L2 engagement, methodological synthesis, qualitative research, quantitative research, student
engagement, systematic review
Engagement defines all learning. Learning requires active involvement on the part of the
learner, and action is the defining characteristic of learner engagement (Mercer, 2019).
In the everyday sense, engagement has a generic meaning related to being occupied or
busy doing something. However, in the realm of teaching and learning, engagement
extends beyond this and refers to the amount (quantity) and type (quality) of learners’
active participation and involvement in a language learning task or activity. An engaged
learner is actively involved in and committed to their own learning, and without engage-
ment meaningful learning is unlikely. The growing recognition for the importance of
engagement in contemporary education has also made it one of the most popular research
topics in education, to the extent that it has been described as ‘the holy grail of learning’
(Sinatra et al., 2015, p. 1). Specifically in language learning, the notion of learner action
for learning is deeply embedded in the dominant paradigms of communicative and con-
structivist language learning and teaching, which view language use and interaction as
critical for language development. Furthermore, the predominant line of thinking in
many theoretical understandings of language acquisition (e.g. cognitive-interactionist
approaches, sociocultural theory and complexity/dynamic systems theory) is also that
learning occurs through meaningful use of the language. As such, it is apparent why
learner engagement has come to be of particular interest to scholars and practitioners in
the field of language learning. The domain of language learning has begun to build on the
considerable body of work in the learning sciences and educational psychology (Fredricks
et al., 2019), extending it in domain-specific ways (Hiver, Al-Hoorie & Mercer, 2021b).
Considering this wave of interest in engagement, it seems that it is both appropriate
and necessary to assess this body of empirical work and evaluate the strength of its con-
tribution to the field by examining the methods and conceptual frameworks adopted in
language learning (L2) engagement research (Oga-Baldwin, 2019). In the present review
of 20 years of L2 engagement research, we had two main objectives. Our first aim was
to look back at the methodological characteristics of previous empirical L2 engagement
research in second language acquisition (SLA) and applied linguistics to note trends and
tendencies in designs and analytical choices. By defining the shape of existing research
designs, we can take stock of study quality and chart a path forward, evaluate what evi-
dence it has provided for specific domains of study, and what conclusions this empirical
work has allowed the field to draw relative to shared concerns and issues. In addition to
methodological characteristics, we were also interested in the conceptual application of
definitions and operationalizations of engagement across various subdomains of lan-
guage education. Study design and analytical choices in empirical work are often
informed by rigorous conceptual or theoretical understandings of relevant constructs.
For this reason we intended to explore whether there were limitations and potential areas
to clarify lingering ambiguity around fundamental definitions, and more clearly deline-
ate the scope and target of L2 engagement research. This dual focus will, we hope, allow
Hiver et al. 3
us to identify future directions for engagement research that will continue to advance our
understanding of the ways and means by which learners pursue meaningful participation
in language learning and use.
To our knowledge, this is the first systematic review and synthesis of engagement
research in language learning. In the wider educational research literature, reviews syn-
thesizing research on student engagement are centered on conceptual and theoretical
issues (e.g. Lawson & Lawson, 2013; Reschly & Christenson, 2012). None have been
methodological. And, because theory and conceptual models have proven so diverse, the
methods used to study student engagement reflect this heterogeneity. For instance, there
has been no attempt to meta-analyse empirical engagement reports in educational
research (Christenson et al., 2012; Fredricks et al., 2019). Consequently, when consider-
ing methodological aspects and study quality, we followed recommendations to examine
broader and more generic methodological issues first as these can inform later reviews
that assess more fine-grained aspects of study quality (Siddaway et al., 2019). In our
review we aimed to survey the methods employed by L2 engagement researchers broadly,
looking at generic characteristics such as research objectives, design and methodological
orientation, sampling characteristics, data elicitation measures, and analytical strategies.
We turn now to outlining the topic, scope, and rationale for the present review.
II Defining engagement
1 Characteristics of language learning engagement
The central characteristic of engagement in learning is the notion of action (Skinner &
Pitzer, 2012). While there are differing perspectives and definitions of engagement, this
feature of engagement as action is consistent across definitions and frameworks (Reschly
& Christenson, 2012). As mentioned above, engagement refers to how actively involved
a student is in a learning task and the extent to which that physical and mental activity is
goal-directed and purpose-driven.
A second characteristic is that engagement is highly context-dependent. A learner’s
engagement does not emerge in a vacuum. It is in part a product of cultures, communi-
ties, families, schools, peers, classrooms and specific tasks and activities within those
classrooms (e.g. Finn & Zimmer, 2012; Pianta et al., 2012; Shernoff, 2013). These dif-
ferent contextual layers influence each other and extend their influence across various
layers of engagement. For example, academic engagement in school settings is a long-
term form of action that covers months or years, but within a specific classroom at
school, there are task-level forms of engagement that function at a timescale of minutes
Third, engagement always has an object. It is possible, for instance, to be engaged
with a topic, a person, a situation, or in an activity or task. This means that while defini-
tions have often focused on the intrapersonal components of engagement, there must also
be a commensurate understanding of its situated characteristics. An understanding of the
‘person-environment fit’ (Reschly & Christenson, 2012, p. 13) of learners in their learn-
ing contexts can better reveal how engagement impacts learning, and how it can be
enhanced. Engagement is inherently situated. As such, engagement research must be
clear about the contexts and the timescales of relevance to engagement.
4 Language Teaching Research 00(0)
A final characteristic is that engagement is dynamic and malleable (Appleton et al.,
2008). Although research investigating developmental trajectories of engagement
remains rare (e.g. Aubrey et al., 2020), this characteristic provides a promising point of
direct action for educators as it suggests that learners can become more engaged with the
right kinds of intrapersonal and contextual conditions (Fredricks et al., 2004). This also
indicates the potential for well-constructed interventions exploring the dynamism of
learning engagement on various timescales (Reschly & Christenson, 2012).
2 Dimensions of language engagement
Scholars posit at least three (though sometimes four or more) core dimensions of engage-
ment. A main strand of work in the field suggests that engagement is manifested not only
in its behavioral facet (i.e. individuals’ qualitative behavioral choices in learning), but
also in demonstrations of action through the cognitive (i.e. learners’ mental activity in the
learning process) and social dimensions (i.e. relations between interlocutors that support
interaction and learning), as well as in students’ emotional responses to learning tasks
and peers (Baralt et al., 2016; Henry & Thorsen, 2020; Lambert et al., 2017).
Behavioral engagement corresponds with the amount and quality of learners’ active
participation in learning, and early L2 research operationalized behavioral engagement by
measuring word counts and turn counts (Bygate & Samuda, 2009; Dörnyei & Kormos,
2000; Platt & Brooks, 2002). Examples of behavioral engagement in L2 learning include
learners’ voluntary involvement in speaking, interactional initiative, time on task, the
amount of semantic content produced while on task, and persistence on task without the
need for support or direction (Philp & Duchesne, 2016). Whereas all domains of engage-
ment involve some degree of action, more recent reviews view behavioral engagement as
students’ expenditure of effort on learning tasks, the quality of their participation, and
their degree of active involvement in the learning process (Sang & Hiver, 2021). While
more subjective than conventional dichotomous perceptions (i.e. of being on-task vs. off-
task), this perspective of behavioral engagement taps into the quality action and opens the
possibility for researchers to link behavioral engagement to other dimensions.
Cognitive engagement refers to learners’ mental effort and mental activity in the pro-
cess of learning. Learners are cognitively engaged when they exhibit deliberate, selec-
tive, and sustained attention to achieve a given task or learning goals (Reeve, 2012;
Svalberg, 2009). In L2 classroom settings, research on cognitive engagement has focused
primarily on verbal manifestations, including peer interactions, students’ questioning,
hesitation and repetition, volunteering answers, exchanging ideas, offering feedback,
providing direction, informing and explaining. In addition to such negotiation of mean-
ing, others see language-related episodes (LREs) as fitting indicators of cognitive
engagement (e.g. Baralt et al., 2016; Lambert et al., 2017; Svalberg, 2017). Non-verbal
communication, private speech and exploratory talk (i.e. learner discourse that occurs as
they attempt to make sense of learning) are also seen by some as further indicators of this
dimension (see, for example, Hiver et al., 2021b). In addition to these more obvious
communication cues, it is also possible to study cognitive engagement through nonver-
bal cues such as body language, facial expressions, eye movements and body positioning
(Fredricks & McColskey, 2012).
Hiver et al. 5
In L2 instructional settings, emotional engagement is often manifested in learners’
personal affective reactions as they participate in target language-related activities or
tasks. Emotionally engaged learners are characterized as having a ‘positive, purpose-
ful, willing, and autonomous disposition’ towards language, associated learning tasks,
and peers (Svalberg, 2009, p. 247). Expressions of discrete positive emotions such as
enjoyment, enthusiasm, and anticipation are thought to be representations of students’
affective engagement, whereas negative emotions such as anxiety, boredom, frustra-
tion and anger demonstrate emotional disengagement or disaffection (Mercer, 2019).
Emotional engagement is considered to have a key impact on other dimensions of
engagement because the subjective attitudes or perceptions learners carry with them
in a class or through language-related tasks are fundamental to the other dimensions
of engagement (Dao, 2019; Henry & Thorsen, 2020). Affective engagement is, there-
fore, related to learners’ attitudes towards learning contexts, the members in that con-
text, the learning tasks, and their own participation in learning (Skinner et al., 2009;
Social engagement, too, occupies a central place in language learning (Philp &
Duchesne, 2008; van Lier, 2004). The social aspect of engagement is defined in light of
the social forms of activity and involvement that are prominent in communities of lan-
guage learning and use including interaction with interlocutors, and the quality of such
social interactions (Linnenbrink-Garcia et al., 2011; Mercer, 2019). The social dimen-
sion can be distinguished from other forms of engagement when considering that it is
explicitly relational in nature and its purpose is interaction with and support of others.
Social engagement underlies the connections among learners in terms of the learner’s
affiliation with peers in the language classroom or community, and the extent of their
willingness to take part in interactional episodes, turn-taking and topic development, and
collaborative activities with others (e.g. Lambert et al., 2017). This dimension of engage-
ment is also linked to phenomena such as reciprocity, mutuality, and other prosocial
expressions of affiliation that are manifested in empathetic discourse moves such as
learners’ willingness to listen to one another or pay attention to teacher talk (Storch,
2008). Social engagement also pertains to learners’ active connection to the learning
environment (Järvelä & Renninger, 2014).
III Relating engagement to learning
1 Importance of engagement for language learning theory
Given the multiple dimensions and the diverse topical areas of concern that engagement
touches on, including task-based learning and L2 interaction, engagement can be posi-
tioned as a meta-construct that unites many separate lines of research within the field. A
prime example of this is in the domain-specific framework of Engagement with Language
(EWL) that originates in Svalberg’s (2009, 2017) work on how language awareness is
developed. In her work on the topic, she offers the following definition: ‘In the context
of language learning and use, Engagement with Language is a cognitive, affective, and/
or social process in which the learner is the agent and language is the object (and some-
times vehicle)’ (Svalberg, 2009, p. 247).
6 Language Teaching Research 00(0)
One point that drives work on engagement for language learning is the object of the
learner’s attention and engagement. For Svalberg (2009), the focus is clearly on the lan-
guage itself. This EWL gives rise to the critical notion of language awareness, which has
been connected with language acquisition by some researchers (Svalberg, 2017). Much
of the work on EWL itself has focused on language as the object being studied and the
form of interaction in classroom tasks. This is equally the case in related areas of inquiry
such as L2 interaction research using LREs (Storch, 2008; Swain & Lapkin, 2001). This
focus on language as the process of learning and the outcome of learning is especially
pronounced in L2 interaction research.
Another important dimension of this work has been a consideration of attention,
which is critical to engagement – that is, a learner must direct their attention to tasks and
to connections between language form and its meanings in use in order to be truly
engaged. While there are marked parallels to Schmidt’s (2001) pioneering work on notic-
ing, the field of language learning is still notoriously divided regarding the role of delib-
erate attention and awareness in language acquisition (Rebuschat, 2015). Yet, as Philp
and Duchesne (2016) explain, attention itself is the gatekeeper of our working memory,
and the ultimate currency of instructed L2 settings. Because engagement is ‘the major
force of learning’ (Ellis, 2019, p. 48), engagement research in language learning raises
critical questions about the link to implicit and explicit learning mechanisms and knowl-
edge, and the elements that learners’ attention is being directed to – whether that is for-
mal features of the language, the task, the content and/or the social interaction.
This also raises important questions about what is considered as an indicator or proxy
of engagement. In a considerable number of studies looking at engagement in language
learning, the indicators of engagement have centered around the quantity, quality, and
form of individual learner discourse and participatory behavior (Baralt et al., 2016;
Lambert & G. Zhang, 2019). However, there are likely to be other indicators of learner
engagement (e.g. Dao et al., 2019; Z. Zhang, 2020), given the less visible dimensions of
engagement (e.g. cognition and affect). Additionally, given the typical format of lan-
guage learning contexts, the interaction that defines language development, and the
social nature of all language interaction, Svalberg (2009) stresses the importance of
social indicators of engagement within language learning processes. Adopting broader,
more inclusive markers of engagement is likely to make this domain relevant to all areas
of language acquisition research.
2 Importance of engagement for language learning practice
In both language learning and in educational research and practice more generally, one
of the appeals of engagement as a construct is that it can provide a broad portrait of how
students think, act, and feel in instructional settings (Oga-Baldwin, 2019). Engagement
is intertwined with many other individual and situational factors and relates to broad
aspects of students’ and teachers’ functioning in school contexts (Mystkowska-Wiertelak,
2020). High learner engagement has been linked to many positive outcomes in educa-
tion. These include high levels of academic persistence, effort and achievement, high
academic aspirations and increased mental health and low dropout rates and reduced
high-risk behaviors (Christenson et al., 2012).
Hiver et al. 7
There are also important policy implications of L2 learner engagement. In formal L2
classroom settings language development is a driver of equity. However the emphasis on
standards, outcomes and teacher accountability has intensified. With the progress and
achievement of L2 students under greater scrutiny than ever, students need to be engaged
to actually succeed (Hiver et al., 2021b). In many educational systems, the makeup of the
local communities that schools serve has become more linguistically and culturally
diverse, pushing schools and teachers to manage a broader, more ambitious role in sup-
porting their community. This is also perhaps why many educational systems keep close
tabs on student engagement and disengagement to identify students who are struggling
and might benefit from targeted interventions (Fredricks et al., 2019).
Engagement also resonates with practitioners because it is easily understood as an
essential ingredient for learning and for quality instruction. Educators across the globe,
in language education and beyond, increasingly recognize the difficulties of keeping
learners engaged and focused on their learning in the face of a myriad of distractions
(Mercer & Dörnyei, 2020). What many teachers witness in their daily classrooms is
closely related to learner attention and action: these are problems of engagement.
Studying engagement brings together teaching and learning perspectives, and for this
reason it can help to identify the classroom and instructional conditions that shape stu-
dent outcomes and build meaningful involvement and participation (Fredricks et al.,
IV Aims and research questions
The L2 research community has witnessed a growth in interest and activity around the
construct of engagement over the last two decades. This points to a clear desire to probe
the nature of engagement, capture the necessary conditions for engagement, explore the
development of engagement over time, and uncover ways to maintain and sustain learn-
ers’ engagement as well as re-engage disaffected students (Hiver et al., 2021b). However,
several unsettled issues that might hamper this program of research have yet to be
resolved. The first and foremost of these is related to the fuzziness surrounding how
engagement is defined and operationalized. Engagement still suffers from a jingle (i.e.
different terms being used to refer to identical notions or constructs) and jangle (i.e. the
same terminology being used to describe distinct notions and constructs) in the way it is
defined and operationalized (see also Reschly & Christenson, 2012). Given the variety
of operational definitions used across studies it is common to discover, for instance, that
one researcher’s conceptualization of cognitive engagement is used as another’s meas-
urement of behavioral engagement.
In addition to such operational issues, other challenges relate to eliciting, measuring and
analysing this multidimensional construct. In particular, the large variation in the measure-
ment of this construct has made it challenging to compare findings across studies. To date,
the most frequently used approach in evaluating engagement is self-report, an indirect
measure of the construct (Fredricks & McColskey, 2012). However, as some reviews of
designs and measurement techniques for engagement show, too few valid and psycho-
metrically sound indirect measures of student engagement exist with which to assess the
multidimensional nature of engagement (Hofkens & Ruzek, 2019). Exacerbating matters,
8 Language Teaching Research 00(0)
some view engagement as an outcome that predicts learning, while others consider it a
resource progressively built during the process of learning (Symonds et al., 2019).
To assess the unique contribution of engagement to student learning and development
across these dimensions as accurately as possible, it is essential to take stock of existing
operational definitions, study designs, and analytical strategies in the field. As 20 years
have passed since the first study explicitly investigated engagement in language learn-
ing, it is time to look back at this body of research and systematically review it. As men-
tioned above, we approached this systematic review project with two parallel objectives
– one descriptive and one substantive. These correspond with our research questions. On
the basis of a body of research spanning the 20 years from 2000 to 2020, we asked the
following research questions:
Research question 1: What are the methodological characteristics of engagement
studies in the field (including trends in study design and analytical choices)?
Research question 2: What conceptual definitions and operationalizations of
engagement are adopted in empirical reports?
Research question 3: What, if any, areas for improving engagement study quality
1 Report pool creation
We constructed the report pool through a sequential process: 1) journal selection, 2)
automated search, and then 3) report exclusion/inclusion. Our aim was to ensure robust
coverage by compiling a pool of all studies on engagement in language learning from
major field-specific journals.
In line with recent L2 research syntheses (see, for example, Andringa & Godfroid,
2020) we restricted our analysis to reports published in L2 journals in the Web of
Science’s Social Science Citation Index (SSCI) as these journals have been observed to
present high-quality research (for a rationale on exclusive SSCI focus, see also X. Zhang,
2020). We must concede however that this exclusive focus is not without challenge. L2
research syntheses, especially meta-analyses such as Bryfonski and McKay (2019) and
Vitta and Al-Hoorie (2020), have alternatively included reports from a divergent range of
databases with calls for unpublished reports. Such comprehensiveness is in line with
Norris and Ortega (2000), and the rationale for such comprehensiveness includes the
mitigation of selection and publication biases where large and significant effects are
favored to be published (Fanelli, 2010). With systematic reviews, however, there appears
to be a trend to focus on the SSCI to capture the methods and research aspects published
in the journals which the field trusts as both robust and consistent (for a similar rationale,
see also Zou et al., 2020). Thus, there is precedent for the current study’s SSCI focus, but
we acknowledge that doing so presents a representativeness limitation.
As the SSCI does not have a specific sub-category for L2 or applied linguistics jour-
nals (Vitta & Al-Hoorie, 2017), we reviewed two recent comprehensive reviews of SSCI
L2 journals to systematically construct the SSCI journal list (Al-Hoorie & Vitta, 2019;
Hiver et al. 9
X. Zhang, 2020), and combined their respective journal lists (n = 20 journals).
Subsequently, the decision was made to include the journal Language Awareness given
that seminal research on L2 engagement has been published there (e.g. Svalberg, 2009,
2017). A total of 21 journals (see Appendix 1) were selected from which the report pool
Each journal was searched using the ‘engagement’ keyword and date of publication
was set at 01-01-2000 to 02-02-2020 in accordance with our research questions. We
restricted the keyword search to titles, abstracts, and keywords. This decision was
intended to avoid the false negatives likely to arise from the more generic use of the term
engagement in applied linguistics research.1 Such restriction also enhances the replica-
bility of our approach. The journal searches were conducted using the Scopus platform
as Scopus allowed for a parsimonious title-abstract-keyword (TITLE-ABS-KEY) while
facilitating an easy download of reports bibliometric data. To ensure that Scopus that not
omit relevant reports, redundancy checks followed using ProQuest, EBSCOhost, Web of
Science, and manual checks of journal websites. At the end of the journal searches (pro-
cess shown in Figure 1), there were 13,710 unique reports in the 21 journals published
Field-specific SSCI journals
searched using keyword and
date of publication (k= 13,710)
EBSCOhost, Web of Science)
searched for redundancy
Unique reports identified (k= 351)
by screening abstracts, titles, and
(k= 351) screened
excluded (k= 104)
inspected (k= 247)
for eligibility against
Reports unrelated or
(k = 140) further
Studies included in
final pool for
synthesis and coding
Figure 1. PRISMA flow chart illustrating journal search and report pool creation process.
Source. Moher etal., 2009.
10 Language Teaching Research 00(0)
within our selected time range. Of these, 351 reports were automatically selected by the
keyword search and 247 were retained as empirical reports via manual inspection. A
second researcher inspected these empirical judgments and 100% agreement was
observed ( = 1).
The resulting 247 reports were then coded by the authors using the categorization scheme
in Table 1, which operationalizes L2 engagement as the amount (quantity) and/or type
(quality) of learners’ active participation and involvement in a language learning task
(see, for example, Hiver et al., 2021b). At the end of this process, 112 empirical reports
were retained (for number of reports by year, see Figure 2). Within these selected reports,
there was further differentiation, as highlighted in Table 1 where a report was coded as
being either a bona fide L2 engagement report as defined above (k = 39) or an ambigu-
ous one (k = 73; i.e. a study that adopts a generic notion of engagement as participatory
behavior of any kind within a language learning context).
These reports were then coded individually by a team of 3 trained coders using a
detailed categorization scheme (see supplementary material) that included descriptive
markers such as study aim and unit of analysis as well as more substantive descriptors
such as indicators included in operational measurement. To validate these judgments,
one researcher independently coded 30% of reports. The observed interrater agreement
(75.7%) approached the conventional 80% threshold (McHugh, 2012) and the observed
kappa ( = .612, p < .001) was within a magnitude range (.60 ⩽ ⩽ .79) considered to
be either substantial (Landis & Koch, 1977) or moderate (McHugh, 2012). As with
Plonsky (2013) who had a value (.56; 82% agreement) below conventional thresholds,
we highlight the conservative nature of kappa especially as possible categories increase
(Brutus et al., 2010). Thus, we consider the reliability of the coding to be acceptable but
we concede that future researchers may improve upon it.
Research question 1: Methodological characteristics
Starting with the characteristics of participants found in engagement research, as
expected a range of sample sizes and participant age groups were included (Table 2).
Fifteen studies included a sample of ⩽ 5. A similar number of studies in this pool sam-
pled between 6 and 20 participants (18.7%), 51 to 100 participants (15.2%), and 101 to
500 participants (17.9%). The largest single category was studies with between 21 and
50 participants (25%), and the biggest sample size in the article pool was N = 43,463
(Mdn = 31; IQR = 85.75, 12–97.75). Three studies featured multiple samples, and
two did not specify any sample size information. Table 2 also presents an overview of
participant ages in engagement research. Studies with younger participants were
clearly the minority, with 63 studies (56.3%) sampling either university students or
adults aged 18 or older. The rarest were studies with participants aged seven years and
younger (3 studies) followed by those with respondents aged 7–12 (8 studies). Fifteen
Hiver et al. 11
studies featured multiple, mixed age groups, while the age of participants was unspeci-
fied in 7 studies.
Although we expected equal representation of a variety of research contexts in the
study pool, as Table 3 shows, foreign and second language learning contexts accounted
for 100 studies (89.3%) of the total. Other research contexts were only minimally pre-
sent, such as bilingual/multilingual language contexts (4.5%), and a mix of several of
these within the same study (2.7%). Various instructional settings were also part of this
pool. In addition to the 56 studies (50%) which took place in conventional instructed
language settings, our pool showed that the next most frequent instructional setting was
online, app-based, or a virtual learning environment (19.6%). Only a handful of engage-
ment studies have been conducted in immersion environments, in study abroad contexts,
Table 1. Report pool summary.
Category Explanation / definitional description
(k = 140)
This study relates to a generic notion of engagement as participatory
action within broad social or learning contexts that are exclusive of or
tangential to language learning. Examples of this include:
engag* in communication
engag* with first language (L1) speakers
engag* in technology use
report (k = 73)
This study adopts a generic notion of engagement as participatory
behavior of any kind within language learning contexts with no additional
focus or elaboration on its substantive meaning. There is ambiguity or no
specific information regarding how that engagement is conceptualized,
operationalized, and/or measured. There is a low bar concerning what
forms of learner participation/behavior are indicative of ‘engagement’ or
‘engaging’. Examples include:
‘. . . students in this study engaged in reading for two hours per week.’
‘. . . the learners engaged with the app in the online interface.’
‘. . . engagement with others in groupwork was mixed.’
‘. . . engaging with the text was seen as important by participants.’
Bona fide L2
report (k = 39)
This study examines the amount (quantity) and/or type (quality) of
learners’ active participation and involvement in a language learning
task/activity, whether in a classroom setting or other instructed setting
(online, study abroad, etc.). Additionally, this study adopts a specific
definition of engagement as deliberate attention to and volitional action
for language learning that is operationalized and measured through
(among others) behavioral, cognitive, affective, or social indicators. This
engagement is directed either to language learning tasks/activities as the
process or vehicle for learning (e.g. task engagement) or to language itself
as the outcome of learning (EWL).
12 Language Teaching Research 00(0)
in content-based language classrooms, language for specific purposes classrooms, or
with a combination of these. Furthermore, only 3 studies investigated engagement in
untutored, naturalistic language learning.
Participants also represented various first language (L1) backgrounds and target L2s
(Table 3). We categorized roughly 20 different L1s here based on their geographical
origin for the sake of parsimony (i.e. some studies featured multiple languages). The
majority of L1s were languages of Asian origin, followed by European and Middle
Eastern languages. An additional 22.3% of studies we reviewed included participants
Table 2. Participant characteristics.
1–5 15 13.4
5 < N ⩽ 20 21 18.7
20 < N ⩽ 50 28 25
50 < N ⩽ 100 17 15.2
100 < N ⩽ 500 20 17.9
N > 500 6 5.3
Multiple samples 3 2.7
Unclear sample 2 1.8
Young children (< 7) 3 2.7
Primary school (7–12) 8 7.1
Secondary school 16 14.3
University (18+) 48 42.9
Other adult (25+) 15 13.4
Multiple, mixed age groups 15 13.4
Unclear 7 6.3
Note. Largest sample size in pool is N = 43,468.
Figure 2. Studies filtered from initial search by year of publication.
Hiver et al. 13
with mixed L1s (25 studies), and 1 study did not specify participants’ first language(s).
When it comes to target languages being learned, far fewer languages were featured.
Among these, what stands out is the dominance of L2 English, accounting for just over
Table 3. Contextual characteristics under study.
Foreign language 68 60.7
Second language 32 28.6
Bilingual/multilingual 5 4.5
Heritage 0 0.0
Mixed 3 2.7
Unclear 4 3.6
Generic instructed setting 56 50.0
Online/app/VLE 22 19.6
Language for specific purposes (e.g. EAP) 13 11.6
Immersion 4 3.6
Uninstructed setting 3 2.7
Study abroad 3 2.7
CLIL 2 1.8
Mixed 8 7.1
Unclear 1 0.9
Participant first language (L1):
Asian languages 40 35.8
European languages 38 34.0
Middle Eastern languages 8 7.1
Multiple/mixed 25 22.3
Unclear 1 0.9
Target second language (L2):
English 79 70.5
Finnish 1 0.9
French 4 3.6
German 4 3.6
Icelandic 1 0.9
Japanese 2 1.8
Latin 1 0.9
Norwegian 1 0.9
Russian 1 0.9
Spanish 6 5.4
Swedish 2 1.8
Multiple/mixed 6 5.4
Unclear 4 3.6
Notes. k = 112. The multiple/mixed category includes additional languages including Czech, Dutch, Hungar-
ian, Korean, Mandarin Chinese, Portuguese, and Swahili, among others. VLE = virtual learning environment;
CLIL = content and language integrated learning; EAP = English for academic purposes.
14 Language Teaching Research 00(0)
70% in the pool. Though we only included reports written in English, this imbalance is
perhaps not surprising given the global importance of L2 English (Dörnyei & Al-Hoorie,
2017). It also stands in contrast to the relatively low frequency of other languages that
are, arguably, equally widespread and important target languages. Spanish was the sec-
ond most represented L2 in our pool (5.4%), while some world languages were featured
in just a single study. Six studies featured learners of multiple and mixed languages, and
4 studies did not specify the target language in question.
As mentioned earlier, one point of interest in this study was to examine the conceptual
definitions and operationalizations of engagement adopted in empirical reports across
various domains of language learning. Having excluded 140 reports from the initial pool
(see Table 1) due to their use of the term engagement as a non-specific catch-all or syno-
nym for activity in language learning – i.e. with no additional focus or elaboration on its
substantive meaning – we expected more precise and focused definitions in the remain-
ing 112 reports. However, Table 4 shows that 65.2% of reports in this pool (73 studies)
adopted a generic notion of engagement as participatory behavior of any kind within
language learning contexts. Notably, there was a low bar concerning what forms of
learner participation/behavior were indicative of engagement such that nearly any desul-
tory student behavior counts as ‘engagement’ or ‘engaging’. These reports featured
ambiguity or no specific information regarding how that engagement is conceptualized,
operationalized, and/or measured. The remaining 39 studies (34.8%) adopted a specific
definition of engagement as deliberate attention to and volitional action for language
learning. These studies examined the amount (i.e. the quantity) and/or type (i.e. the qual-
ity) of learners’ active participation and involvement in a language learning task, whether
in a classroom setting or other instructed setting. In these studies, engagement was
directed either to language learning tasks/activities as the process or vehicle for learning
or to language itself as the outcome of learning.
Table 4. Definition and domain of engagement.
Clear, focused 39 34.8
Generic, ambiguous 73 65.2
Operational domain of engagement:
Cognitive 23 20.5
Behavioral 59 52.7
Emotional 24 21.4
Social 4 3.6
Language domain-specific 13 11.6
Engagement with language (EWL) 4 3.6
Language related episodes (LRE) 6 5.6
Disengagement 3 2.7
Unclear 17 15.2
Notes. k = 112. Number of studies for Operational Domain may not sum to 112 because multiple domains of
engagement were coded in several studies.
Hiver et al. 15
We additionally coded the operational subdomains of engagement adopted in all
reports. In line with generally accepted definitions of engagement as action, the behav-
ioral domain was featured most often (52.7%), followed by relative parity between the
cognitive (20.5%) and emotional (21.4%) domains of engagement. A handful of studies
explored the social domain of engagement (3.6%) and language domain-specific aspects
of engagement (11.6%) applicable only to a particular domain of language learning (e.g.
oculomotor engagement, shared reading engagement). EWL and LREs were featured in
3.6% and 5.6% of reports respectively, and were coded as separate categories given that
these each combine several operational domains of engagement. Disengagement was the
explicit focus of very few studies (2.7%). Finally, in over 15% of reports, we were unable
to ascertain which operational domain(s) of engagement had been adopted or were the
area of focus. This finding, coupled with the very large number of reports (65.2%) that
did not feature a clear definition and/or operationalization of the construct itself in the
first instance is a genuinely puzzling state of affairs, one that we will devote more atten-
tion to in our discussion.
Returning to study design characteristics (Table 5), we looked at the general approach
to study design as well as the method adopted in the reviewed studies. Nearly two thirds
of reports in the pool (55 studies) were observational cross-sectional studies. More than
15% of studies (17 studies) adopted longitudinal observational designs, and an additional
14.3% were quasi-experimental. The overall approach to study design was ambiguous in
the remaining 24 studies. Examples of these include studies of machine translation-
assisted editing of student writing, pedagogical priorities in a flipped classroom, learn-
ers’ use of metalanguage in interaction, and graduate student writing in a community of
practice – all presumably legitimate topics of focus within the rubric of student engage-
ment, but accompanied by inadequate detail about the overall approach or study setup.
Table 5 further shows that choice of method was split across qualitative (35.7%), quan-
titative (37.5%), and mixed methods studies (26.8%). Our review showing this near pro-
portionate split and the prominent adoption of mixed and multi-method studies may
mirror growing trends in the field to value multiple methods as equally productive and
integrate methods as an innovative way forward (Hiver, Al-Hoorie & Larsen-Freeman,
Table 5. Study design.
Quantitative 42 37.5
Qualitative 40 35.7
Mixed 30 26.8
Cross-sectional 55 63.4
Longitudinal 17 15.2
Quasi-experimental 16 14.3
Unclear 24 21.4
Note. k = 112.
16 Language Teaching Research 00(0)
Turning now to the study aims and the purposes for which the engagement construct
featured in studies (Table 6), we found that many studies (33%) adopted engagement as
the outcome of interest or as the dependent variable (e.g. in quantitative designs). The
next most frequent study aim was found in studies (25.6%) examining engagement as a
predictor of language learning and use; also analogous to the independent variable in
quantitative studies. A further 23.2% of studies investigated the dimensions and make-up
of engagement in a more descriptive way. Although theorizing on the topic plays a clear
role in driving empirical work and the operational domains adopted in respective studies
(see Table 5), this exploratory strand of work on the composition of engagement remains
prominent in the report pool. Only 9 reports had as their aim to study the processes and
mechanisms of developing engagement. By itself, this seems to signal a preference in
most studies for viewing engagement as a product rather than a process. Finally, in 46
reports engagement was coded as being incidental to the study aims. This is cause for
some concern as it means that 41.1% of engagement studies were self-labeled as such but
were not actually doing engagement research per se. Examples of this include studies in
which engagement was listed in the keywords and abstract or reviewed as part of the
background literature or theoretical framework but did not subsequently feature in data
elicitation, data analysis, or the presentation and discussion of results. We return to this
finding later when reflecting critically on our research questions. Finally, Table 6 shows
that the unit of analysis in these studies was split across the group-level (56.3%) and
individual-level (28.6%). The remaining 16.1% of studies adopted texts as their unit of
Closely related to the study design characteristics we reviewed above are the choices
of data elicitation methods and data analytical strategies. We found that a range of indi-
rect and direct measures and techniques for data collection were present in reviewed
studies (Table 7). The techniques most frequently adopted were surveys or question-
naires (42 studies; 37.5%) and interviews or focus groups (34 studies; 30.3%), both
forms of self-report. Other commonly used data elicitation methods included lesson
Table 6. Purpose of study.
Engagement as predictor of learning/behavior 29 25.6
Engagement as the outcome of interest 37 33.0
Dimensions and make-up of engagement 26 23.2
Process of developing engagement 9 8.0
Engagement incidental to study aims 46 41.1
Unit of analysis:
Individual 32 28.6
Group 63 56.3
Texts 17 16.1
Notes. k = 112. Number of studies for Study Aim may not sum to 112 due to studies employing the con-
struct of engagement for multiple purposes.
Hiver et al. 17
observations, tasks, tests, analysis of written samples of learner language, and oral lan-
guage/interaction samples. Other data sources used more sparsely included field notes,
stimulated recall, journals or diaries, and think-aloud protocols. Nine studies featured
other types of data elicitation tools such as samples of student academic work or class
artifacts, screen captures, or chat logs. The fact that studies generally do not rely on a
single form of data or adopt exclusively indirect (i.e. self-report) measures of engage-
ment is a promising finding, and one future work should build on.
Looking also at analysis techniques, it was not surprising – given the large number of
studies that were qualitative in design or that adopted qualitative data collection tech-
niques – that qualitative coding and analysis methods were employed in roughly half the
reviewed studies (55 studies; 49.1%). This included qualitative data analysis techniques
such as inductive thematic coding, grounded theory analysis, conversation and discourse
analysis, or ethnographic analysis. Examining other data analytical strategies further
revealed studies that relied on descriptive statistics (16.1%) and studies that adopted
conventional inferential statistical analyses (30.3%). These included analyses such as
chi-square tests, parametric and non-parametric correlations, t-tests and analyses of vari-
ance (ANOVA), and linear regression analysis. A handful of other advanced multivariate
Table 7. Analytical strategy.
Survey/questionnaire 42 37.5
Interview/focus group 34 30.3
Lesson observation 24 21.4
Tasks 23 20.5
Tests 22 19.6
Written language sample 19 16.9
Oral language/interaction sample 18 16.1
Stimulated recall 6 5.4
Journals/diaries 5 4.5
Field notes/memos 5 4.5
Think-aloud protocols 3 2.7
Other (class artifacts, screen capture, chat logs) 9 8.0
Unclear 5 4.5
Qualitative coding/analysis 55 49.1
Descriptive statistics 18 16.1
Conventional inferential statistics 34 30.3
Advanced multivariate statistics 14 12.5
Other (microgenetic, Bayesian) 5 4.5
Unclear 9 8.0
Notes. k = 112. Number of studies for Data Collection and Analysis Technique may not sum to 112 respec-
tively due to many studies eliciting multiple forms of data and adopting multiple techniques for analysing
18 Language Teaching Research 00(0)
statistical analyses were used (14 studies) including factor analysis, Rasch analysis,
mixed effects modeling, and latent variable modeling (i.e. SEM). We also found a num-
ber of instances (9 studies; 8.0%) in which the data analysis technique was either unclear
or unspecified – examples of this include unintuitive descriptions such as ‘data were
identified and coded’, ‘interviews were transcribed and analysed’ or ‘data analysis was
conducted recursively.’ The finding that such key design details remain ambiguous in a
number of studies is again cause for concern, and one we will return to below in our
Research question 2: Operationalizations of L2 engagement
The current report pool was also informative regarding the measures or indicators used
to assess student engagement (Table 8). As previous reviews show (e.g. Finn & Zimmer,
2012) studies of student engagement often tend to include a range of obfuscating ante-
cedents, indicators, and facilitators, at times collecting, analysing, and reporting data on
these measures simultaneously. Here we focused specifically on indicators of the various
subdomains of engagement included in studies in this pool. This included indicators
measured through direct and indirect means.
Indicators used to assess the cognitive domain relate to deliberate, selective, and sus-
tained mental effort on the part of learners. Included here are indicators that reference
mental activity more broadly such as focus (7.1% of total pool), attention (5.6%), and
self-regulation (3.6%), as well as those marked by the quality of such mental activity
including depth of processing (2.7%), negotiation of meaning or form (2.7%), and men-
tal elaboration (4.5%). Additional indicators related to higher-order mental effort
included monitoring (0.9%) and metacognitive capacities (1.8%). Several indicators
used to tap into cognitive engagement were unrelated to the type and quality of learners’
mental effort in the process of learning. Some were either too narrow in focus (i.e. build-
ing linguistic knowledge), tangential in nature (e.g. motivational intensity), or a conse-
quence resulting from cognitive engagement (e.g. understanding/comprehension).
Turning to indicators of behavioral engagement, many were related to the degree
learners were actively involved in the learning process and the quality of their participa-
tion more generally. This includes indicators such as active participation (11.6%), effort
expended (8.9%), task completion (18.7%), and time on task (9.9%). Other indicators
were specific to individuals’ involvement in language learning such as interaction and
language use (23.2%), number of spoken turns (4.5%) or written texts/posts (3.6%), out-
of-class language use (3.6%), or instances of practice (2.7%). As with the other domains
of engagement, several measures used as indicators of behavioral engagement were
ambiguous and fell outside the scope of the engagement construct (e.g. learner agency
and vocabulary learning).
Indicators of emotional engagement included general affective responses (1.8%) and
positive appraisals (1.8%), as well as dispositions such as interest (3.6%), satisfaction
(0.9%), and enthusiasm (1.8%). Several studies adopted discrete emotions such as
enjoyment (3.6%) or emotional responses such as laughter (0.9%) as indicators of emo-
tional engagement. This domain, however, is marked by the greatest number of ambigu-
ous and extraneous indicators. This includes indicators that tap into qualitatively distinct
Hiver et al. 19
Table 8. Comparison of indicators of engagement included in operational definitions.
kPercentage Sample studies
Alertness, focus 8 7.1 Tragant & Vallbona, 2018
Attentiveness, attention 6 5.6 Park & Warschauer, 2016
*Building linguistic knowledge 2 1.8 Yang, 2011
Elaborating and clarifying content 5 4.5 Lambert etal., 2017
Extent/depth of processing 3 2.7 Storch & Wigglesworth, 2010
Mental activity 3 2.7 Lee, 2020
Meta-cognitive behaviors 2 1.8 Andujar etal., 2019
Monitoring 1 0.9 Zhang, 2016
*Motivational intensity 2 1.8 McEown etal., 2014
Negotiation of meaning/form 3 2.7 Newton, 2013
Strategy use/self-regulation 4 3.6 Andujar etal., 2019
*Understanding/comprehension 3 2.7 Zhang, 2016
Active participation, involvement 13 11.6 Huang, 2011; Stroud, 2017
Attendance 1 0.9 Cheng & Lee, 2018
Effort expended 10 8.9 Fouz-González, 2017; Matthews &
O’Toole, 2015; Wang etal., 2019
Goal-directed behavior 1 0.9 Henry & Thorsen, 2018
Interaction/language use 26 23.2 Huh & Suh, 2018; Kibler etal., 2017;
Sauer & Ellis, 2019
*Learner agency 1 0.9 Knight etal., 2017
Number of speech repairs 1 0.9 Qiu & Lo, 2016
Number of submissions, posts, or
4 3.6 Gelan etal., 2018; Yang etal., 2016
Number of turns/quantity of
5 4.5 Aubrey, 2017; Lambert & Zhang, 2019
On-task behavior/task completion 21 18.7 Balaman & Sert, 2017; Friðriksdóttir,
2018; Moore, 2013
Out-of-class language use 4 3.6 Macis & Schmitt, 2017
*Out-of-class learning 1 0.9 Lai etal., 2015
Persistence 1 0.9 Lambert etal., 2017
Practice 3 2.7 J.S. Lee, 2020
Time on task 11 9.9 Cho, 2019; Rienties etal., 2018;
Stengers etal., 2016
*Vocabulary learning 1 0.9 Arndt & Woore, 2018
Affective response 2 1.8 Cho & Castañeda, 2019; Lopez etal.,
Enjoyment 4 3.6 Oga-Baldwin & Nakata, 2017
Enthusiasm 2 1.8 Qiu & Lo, 2016
*Experience of flow 5 4.5 Cox & Montgomery, 2019; Liu etal.,
20 Language Teaching Research 00(0)
kPercentage Sample studies
*Feelings of autonomy 1 0.9 Kearney & Ahn, 2014
Interest 4 3.6 Lo & Hyland, 2007
*Intrinsic motivation 1 0.9 Thorne, 2003
Laughter 1 0.9 Hasegawa, 2018
Positive appraisals 2 1.8 Llinares & Dalton-Puffer, 2015
Satisfaction 1 0.9 Fox etal., 2014
*Sense of meaningfulness 1 0.9 Henry & Thorsen, 2018
*Sense of purposefulness 2 1.8 Kearney & Ahn, 2014
*Willingness to engage 4 3.6 Kearney & Ahn, 2014
Sense of community/belonging 1 0.9 Fox etal., 2014
Supportiveness of others 1 0.9 Kearney & Ahn, 2014
*Peers’ motivation contagion 1 0.9 Tanaka, 2017
Affiliation in discourse 1 0.9 Lambert etal., 2017
Language domain-specific 13 11.6 Huh & Suh, 2018; Jalkanen & Vaarala,
2013; Krulatz etal., 2018; Niu &
Helms-Park, 2014; Shapiro & Waters,
2005; Suvorov, 2015
Language-related episodes (LREs) 6 5.6 Edstrom, 2015; Fortune & Thorp,
2001; Storch, 2008; Zeng &
Engagement With Language (EWL) 4 3.6 Svalberg, 2012
Disengagement 3 2.7 Allen etal., 2014; Andujar etal., 2019;
Notes. Full references to the studies cited in this table are listed in the supplementary material. k = 112.
Number of studies across indicators may not sum to 112 as studies included multiple indicators. Number of
studies within a domain may not correspond with numbers in Table 4 as studies included multiple indicators
of a single domain. * Indicators marked with an asterisk are ambiguous and fall outside the scope of the
engagement construct; for completeness, we have classified these in their nearest domain.
Table 8. (Continued)
constructs such as flow (4.5%), intrinsic motivation (0.9%), or autonomy (0.9%).
Emotional engagement should be manifested in learners’ personal affective reactions as
they participate in target language-related activities or tasks. This is why the use of
indicators that relate to antecedents or outcomes of emotional engagement like a sense
of meaningfulness (0.9%), a sense of purposefulness (1.8%), or the willingness to
engage (3.6%) are ambiguous at best.
Only 4 studies in the entire pool investigated social engagement. The indicators
adopted here included a sense of community/belonging (0.9%), one’s supportiveness of
others (0.9%), and affiliation in discourse (0.9%). In this domain too, seemingly unre-
lated indicators were found (i.e. motivation contagion). Language domain-specific indi-
cators (11.6%) were those related to a specifically circumscribed area and only applicable
to that domain of language learning (e.g. oculomotor engagement or shared reading
Hiver et al. 21
engagement). LREs (5.6%) and EWL (3.6%) are listed as separate categories here given
that these indicators each combine multiple operational domains of engagement.
Disengagement indicators were rare (3.6%) and were coded as a separate category here
because they include measures from multiple domains (e.g. boredom, apathy, and frus-
tration = emotional disengagement; avoidance = behavioral disengagement).
Having described prominent design and analytical choices from engagement studies in
the field as well as the conceptual definitions and operationalizations of L2 engagement
adopted in these empirical reports, we turn now to a discussion of the areas this review
has highlighted for improving engagement study quality, which relates to our final
1 Methodological issues
One positive trend in studies we reviewed was the inclusion of multiple measurements
and complementary data sources to tap into domains of L2 engagement. Such studies
have provided a valuable understanding of the nature and function of the various dimen-
sions of engagement and their role in learners’ development, particularly at the aggregate
level. The fact that studies generally do not rely on a single form of data or adopt exclu-
sively indirect (i.e. self-report) measures of engagement is a distinct strength, and one
that future work should capitalize on by continuing to supplement indirect measures with
direct measures of the relevant domains of L2 engagement (Zhou et al., 2021). Going
forward, there will be clear value in increased use of skill- and domain-specific measures
of engagement as well as measures that allow the dynamics of engagement (e.g. how it
is sustained and how it deteriorates) to be investigated. Areas not yet explored in this
report pool include implicit measures of engagement that can tap into the subconscious
side of engagement and technology-driven real-time, authentic data (i.e. big data) that
can be used to test hypotheses and the effectiveness of different interventions. Advancing
the measurement of engagement has potential to open entirely novel avenues of research
and increase the depth of insights obtained from this research.
Secondly, the sample size characteristics of the studies reviewed, in combination
with several other design characteristics, highlight the prevalence of group-based and
cross-sectional designs in existing L2 engagement research. Capturing general profiles
in L2 engagement or studying the tendencies and patterns of groups of learners has
shown where teacher practice is likely to have an immediate and sustained impact.
Operational and design choices in L2 engagement research can have an important
impact on the research-practice interface that results from work on the topic. Here too,
there is potential for more individual-based work that looks beyond isolated aspects of
student engagement, pooled across participants. The level of granularity in a study’s
sample, unit of analysis, and design can be fine-tuned by varying the agent (the indi-
vidual student vs. a group), the task (individual L2 tasks vs. a course of learning), and
the time (a momentary timescale vs. an ongoing developmental timescale) (Symonds
et al., 2019). Individual-based designs that examine intra-individual variation can shed
22 Language Teaching Research 00(0)
light on the more proximal processes of engagement that are specific to momentary
language learning such as those involved in particular learning tasks (e.g. attention,
processing, retrieval, reconstruction) and provide new insights that complement
advances already made in the field.
Third, from our review we found very little work either assessing the malleability of
engagement, investigating the dynamics of its development, or focusing on re-engaging
disengaged and disaffected students. Student engagement is not static or immutable – it
can change. How it is dynamic, under what conditions, and for whom remains unclear
from the current body of work. Our analysis shows that student engagement is most often
conceptualized as a desired outcome, and this is a sound design choice in many instances.
With some small design modifications, however, it is possible to take more explicit tem-
poral considerations into account and contribute to an expanding picture of this topical
area. This can be done, for example, by investigating the role of teachers, peers, and
learning tasks on the development of engagement over time, and examining how class-
room learning opportunities, assessments, and extramural interests and experiences
influence learners’ engagement. There are also other means through which engagement
can be studied to foreground the ways in which it is dynamic and emergent. Engagement
can be studied as the process or activity through which development occurs, as a vehicle
to better understand how learners’ achieve success, or as a mediator in the mechanisms
of learning and development. These are all in line with the growing trend of taking time
and change into account in research designs (Hiver, Al-Hoorie & Evans, under review)
in order to reflect the way learners develop in interaction with the environment syn-
chronically and diachronically.
2 Operational and definitional issues
First and foremost, our review has shown that the issue of definition needs further atten-
tion in L2 engagement research. Engagement models can be used to inform pedagogy
and bolster student performance only to the extent that engagement itself and its compo-
nents are well defined and clear for researchers and practitioners to understand. As our
analysis shows, fewer than 35% of studies reviewed featured a clear definition and/or
operationalization of the construct itself. If further work is to contribute substantively to
this domain, this is a concern that must be addressed. Put in a larger context, the aims of
the studies might also shed light on these definitional concerns: a large number of reports
(41%) were self-labeled as engagement studies and included engagement in the key-
words and abstract, or mentioned engagement in a review of background literature. On
closer scrutiny of these reports, however, engagement did not feature in any data elicita-
tion, data analysis, or the presentation and discussion of results. If engagement is inci-
dental to nearly one in two reports in this pool, it should not be surprising that such a
large number of studies adopted such generic, unfocused, or potentially ambiguous oper-
ational definitions of engagement within language learning contexts.
Looking more closely at definitional issues, our review showed that a range of subdo-
mains were featured in reports, with behavioral engagement the most frequent and social
engagement the least frequent. However, coding these specific domains was not always
straightforward given the lack of explicit detail and transparency in the operational
Hiver et al. 23
descriptions across many reports. For example we had to extrapolate from notions such
as students’ preparation, text reconstruction, linguistic sensitivity, and sense-making
which domain of engagement was being targeted (if any) in reports. Ultimately, in over
15% of reports, we were unable to ascertain which operational domain of engagement
had been adopted or was the area of focus. In addition to domain-specificity, our review
also showed that even when combining EWL and LREs with other L2-specific defini-
tions only roughly 20% of the measures adopted were skill- or language learning-spe-
cific. The issue of whether domain-general (i.e. academic participation) definitions are
adequate for the field or if measures should be skill- and language learning-specific
straddles both conceptual and methodological territory. More focused measurements are
often more informative psychometrically and reflect a more mature and sophisticated
theoretical framing of a construct. However, like the early work on student engagement
outside our field (for one review, see Reschly & Christenson, 2012), many of the studies
we reviewed seem to suffer from conceptual haziness and lack of focus.
With regard to measures and indicators of engagement adopted more specifically, our
analysis revealed that many indicators used by studies in the report pool were ambiguous
and fell outside the scope of the engagement construct. For example, our earlier review
of the literature makes clear that engagement functions as a precursor to learning.
However, several indicators in the cognitive and behavioral domains did not distinguish
engagement from learning or comprehension/understanding, confusing a necessary
antecedent with a desired outcome. Indicators in the domain of emotional engagement in
particular were also marked by imprecision regarding their intensity. Some indicators
were more prosaic (e.g. satisfaction) or categorical (e.g. interest), while others equated
qualitatively and functionally distinct notions such as flow, a supercharged mental and
emotional state that emerges from engaging in an activity, with emotional engagement.
Many indicators also featured overlapping notions and invited unnecessary complexity
into the accompanying conceptual definitions. As just one example, goal-directed behav-
ior is an indicator that combines goal-setting (a cognitive indicator) with strategic pursuit
(a behavioral indicator).
There were also lingering issues with murkiness in many reports regarding the dis-
tinctions between engagement and constructs such as motivation, agency, autonomy,
and strategy use. In many cases these were used as indicators or proxies for engage-
ment. To elaborate on just one comparison, action is key in distinguishing engagement
from motivation. Motivation represents initial intention and engagement is the subse-
quent action (see Noels et al., 2019). The ways in which learners engage in L2 learning
are no doubt linked to their initial intent to participate in learning. Still, the consensus is
that motivation is meaningfully distinct from engagement in the sense that the intensity
and the quality of student involvement in the learning activity or environment (engage-
ment) differs from the forces that energize and direct that behavior (motivation) (Martin
et al., 2017). These concerns may strike some as merely semantic in nature, but such
imprecision in thinking no doubt affects study design and methodological choices, ren-
dering results and conclusions potentially invalid. It is no doubt also the case that appli-
cation to classroom-level research and practice is near impossible unless theoretical and
conceptual boundaries are both coherent and consistent in the field. Our review, there-
fore, highlights the importance of specifying the boundaries of the engagement con-
struct and its indicators to increase clarity in this body of empirical work.
24 Language Teaching Research 00(0)
3 Pedagogical implications
The reports we have reviewed pointed out some pedagogical implications which we
review here. First, because engagement is at the core of all language learning, we feel
there would be a meaningful return on investment for fundamental work in establishing
clear definitions and toolkits for assessment that help practitioners better understand how
the various dimensions of engagement interact with one another, and whether there are
phenomenological differences in how individuals experience engagement across various
settings (see also Dao et al., 2019; Egbert, 2020; Z. Zhang, 2020).
Second, it is clear that language pedagogy must sharpen its focus on the necessary
conditions for engagement. Language instruction must also attend to issues of what
makes language learning engaging for students both inside and outside of classroom set-
tings, what conditions are part of an engaging instructional context, what makes for
engaging language learning tasks and how these differ across groups of culturally and
linguistically diverse learners with varied levels and learning objectives (Nakamura
et al., 2020). Many reports point out the importance of task characteristics in generating
engagement, whether these relate to the level of support provided, challenge built into
tasks, or choice, sequencing, and focus of the task (see also Dao, 2019, 2020; Lambert
et al., 2017; Lambert & G. Zhang, 2019; Phung, 2017).
With regard to the ways teachers can build language learning environments that are
engaging, it seems that many of the pedagogical implications to come out of our review
have to do with technology. For example there are interesting suggestions about engag-
ing students using video games, synchronous CMC tools, authentic social media and
web-based uses of language, and other affordances to establish rapport and increase L2
interaction during online exchanges (see, for example, Henry, 2019; Henry & Thorsen,
2020). Similar suggestions include connecting learners with both L1 and L2 speakers of
the language to raise their awareness of the different varieties of the language through
cross-cultural communication. These ideas seemingly blur the lines between classroom
language learning and extramural language development, and although they may be
unstructured in nature they reflect more meaningful purposes for language use while also
stimulating learner engagement (Mercer, 2019).
Finally, identifying disaffected learners and disengaging learning environments is an
important way to shed light on the policies, practices and contextual influences that pro-
vide a disincentive for active learner involvement and meaningful participation. Engaged
language learners develop further and faster, and benefit from many desirable ‘side-
effects’ such as deeper interest, greater motivation, and stronger self-efficacy and persis-
tence (Egbert, 2020). By comparison, chronic disengagement and lack of interest in
language learning can lead to passivity and feelings of alienation from teachers and peers
in the learning environment, unfocused and wasted attention and effort for learning, and
poor persistence and commitment to learning more broadly. This highlights the impor-
tance of targeted interventions that can help disengaged learners recapture their energy
for action and rediscover their appetite for meaningful involvement in language learning.
Doing so should also include an appropriate focus on student voices and perspectives and
encourage an upward trajectory towards personal investment in language learning (see
also Aubrey et al., 2020; Mercer, 2019; Mystkowska-Wiertelak, 2020).
Hiver et al. 25
Engagement is a dynamic, multidimensional construct comprising situated notions of
cognition, affect and behaviors – including social interactions – in which action is a req-
uisite component. Our review of the past 20 years of work in this area has been revealing.
The purpose of our review was to take stock of empirical work in the field and draw
conclusions across the subdomains of language education (e.g. classroom settings, tech-
nology assisted learning), based on the totality of this research. In particular, we exam-
ined the methodological characteristics of previous empirical L2 engagement research as
well as the conceptual definitions and operationalizations of engagement.
While engagement research has avoided some of the pitfalls of other instructed SLA
and psychology of language learning domains (e.g. general language motivation
research), notably the overreliance on self-report measures and leap to pedagogical
claims that are not substantiated by empirical evidence and hypothesis testing, there are
still areas to be addressed in future research. Examples include increasing the use of
longitudinal and individual-based investigations uncovering the dynamic nature of
engagement as well as interventions targeting disengaged and disaffected learners. Work
is also needed to enhance the conceptual and definitional precision of engagement and its
different subdomains. The definitional/conceptual issues that are persistent across the
studies reviewed raises the question of whether engagement represents a concept too
broad to be meaningful or if it is in fact a helpful construct. We believe it is meaningful,
and suggest that future success in researching the construct be reflected by greater opera-
tional/definitional transparency in empirical studies. We look forward to scholars in the
field taking up the call to clarify definitional concerns in order to broaden and sharpen
our understanding of how engagement connects to other aspects of language learning
and teaching processes in diverse settings. Future work on L2 engagement, whether it
privileges an exploratory or experimental paradigm, will no doubt build on the field’s
understanding and advance the quantity and quality of work, opening up new avenues of
research that will lead to a richer, more informative and more diverse range of studies in
language learner engagement.
We would like to thank Hyejin An and Dr. Samuel Reid for their assistance with coding the report
The author(s) received no financial support for the research, authorship, and/or publication of this
Phil Hiver https://orcid.org/0000-0002-2004-7960
Ali H. Al-Hoorie https://orcid.org/0000-0003-3810-5978
Joseph P. Vitta https://orcid.org/0000-0002-5711-969X
26 Language Teaching Research 00(0)
Supplemental material for this article is available online.
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Appendix 1. List of journals.
Bilingualism: Language and Cognition
Computer Assisted Language Teaching
English for Specific Purposes
English Language Teaching Journal (Oxford)
Foreign Language Annals
International Review of Applied Linguistics in Language Teaching (IRAL)
Journal of English for Academic Purposes
Journal of Second Language Writing
Language Assessment Quarterly
Language Learning & Technology
Language Teaching Research
Modern Language Journal
Studies in Second Language Acquisition