Journal of Language and Social Psychology
2021, Vol. 40(1) 136 –153
© The Author(s) 2020
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The Identity Crisis in
Ali H. Al-Hoorie1, Phil Hiver2,
Tae-Young Kim3, and Peter I. De Costa4
The 40th anniversary of the Journal of Language and Social Psychology occurs around the
corner of another anniversary, the language motivation field reaching 60 years. At this
occasion, we pause to reflect on the contribution of language motivation research to
language teaching practice. We argue that this contribution has been negligible and
put forward two main reasons. The first is related to an identity crisis in the language
motivation field, falling at the intersection of applied linguistics, education, and
psychology; the second is the marginalization of the role of context. To address these
issues, we first present insights from two perspectives—sociocultural theory and
complex dynamic systems theory—and then propose three solutions to incorporate
these insights: (1) moving from the abstract notion of “motivation” to the more
tangible construct of “engagement”, (2) encouraging rigorous transdisciplinary
research, and (3) taking advantage of the potential of artificial intelligence to translate
research findings into practice.
motivation, language teaching, sociocultural theory, complex dynamic systems theory,
perezhivanie, artificial intelligence, student engagement
1English Language and Preparatory Year Institute, Royal Commission for Jubail and Yanbu, Jubail
Industrial City, Saudi Arabia
2Florida State University, Tallahassee, FL, USA
3Chung-Ang University, Seoul, South Korea
4Michigan State University, East Lansing, MI, USA
Ali H. Al-Hoorie, English Language and Preparatory Year Institute, Royal Commission for Jubail and
Yanbu, P. O. Box 10099, Jubail Industrial City, 31961, Saudi Arabia.
964507JLSXXX10.1177/0261927X20964507Journal of Language and Social PsychologyAl-Hoorie et al.
Al-Hoorie et al. 137
As the language motivation (LM) field has reached 60 years since it was founded
(Al-Hoorie, 2017; Al-Hoorie & MacIntyre, 2020; Gardner & Lambert, 1959), it seems apt
to stop and reflect on its achievements to date. Notably, this is not the first time in the his-
tory of the field that LM researchers have stopped to question the direction the field was
taking, as a similar self-reflection took place in the early 1990s. Problematizing the then-
dominant framework pioneered by Robert Gardner (1979, 1985, 2010), Crookes and
Schmidt (1991) called for a “reopening” of the research agenda in order to accommodate
more classroom-friendly LM research. That challenge to the status quo culminated in
what came to be known as the Modern Language Journal debate on LM (Dörnyei, 1994a,
1994b; Gardner & Tremblay, 1994a, 1994b; Oxford, 1994; Oxford & Shearin, 1994),
where leading scholars exchanged views on what aspects of motivation had been unduly
overlooked. A general take-home lesson from this debate was that the field had overem-
phasized the social macro-perspective of motivation—represented in integrative motiva-
tion in particular—at the expense of its cognitive underpinnings and contextual factors.
The field subsequently entered a new phase described by some as the cognitive–situated
period (Dörnyei & Ryan, 2015) and the educational period (Al-Hoorie, 2017).
In this article, we reflect on the extent to which LM research has achieved the goal
of informing language teaching practice. We argue that its success has been limited.
We attribute this to an “identity crisis” afflicting LM researchers. LM falls at the inter-
section of applied linguistics, education, and psychology (among others), which
requires proportionately wide-ranging graduate training and later rigorous transdisci-
plinary investigations. We then propose solutions stemming from Vygotskian socio-
cultural theory and complexity theory in the hope of addressing this gap.
Has Research Informed Teaching Practice?
Today, there is skepticism about whether applied linguistics research has indeed trans-
formed into the classroom-friendly enterprise that can enlighten teaching. As Larsen-
Freeman (2015, p. 271) observed, “research has been less consequential in affecting
practice widely” than one would have expected it to be. Countless MA, PhD, and
peer-reviewed articles are produced every year, but are then left unread by classroom
practitioners. This led Maley (2016) to wonder whether the oft-repeated phrase “fur-
ther research is needed” is a mantra taken too far, as academic research has consis-
tently failed to address the daily concerns of language teaching professionals. The
sobering reality, as reflected in one fairly large-scale multi-national study (Borg,
2009), is that hardly more than 15% of the surveyed teachers reported reading the lit-
erature regularly, citing, among other things, the irrelevance of academic research
findings to their local classroom contexts. Another more recent survey by Marsden
and Kasprowicz (2017) reached comparable conclusions, a result the researchers
described as “bleak” (p. 613).1
While it is hard to dispute that research has, occasionally, come up with some non-
intuitive ideas that have the potential to enhance classroom practice (see Hattie, 2009;
Paran, 2017), few would disagree that “[r]esearch is not the primary basis of [language
teaching] knowledge for the practitioner” (Ur, 2012, emphasis added). The sheer
138 Journal of Language and Social Psychology 40(1)
volume of academic research published almost daily dwarfs the modest contribution
this research has made to date, raising the question of whether research into language
teaching should now be considered overrated. Not surprisingly, some have gone as far
as to describe academic researchers as “mere extras in the language-teaching opera-
tion” (Medgyes, 2017, p. 494) and their role as “parasitical” (p. 496), and thus mostly
failing to meet the ethical obligations that researchers ought to uphold when working
in collaboration with their teacher partners (De Costa, 2015; De Costa et al., 2020).
Some progressive language teaching approaches, like Dogme (Meddings & Thornbury,
2009), hardly make an attempt to forge connections with language learning research.
In the LM field more specifically, the situation is not very different. Considering that
attitudes and motivation are perceived as an easy target, numerous novice researchers
have jumped on its bandwagon (Ushioda, 2016). Perhaps motivated by journal editorial
policies, modern-day LM papers usually end with some variation of “pedagogical appli-
cations” that more often than not do not logically and unambiguously follow from the
results of the research—a classic case of misapplied linguistics (see Han, 2007; Swan,
2009). Book-length treatments on motivational “strategies” and “techniques” have also
started to proliferate. These strategies are sold to teachers as recipes for application
rather than being proposed to fellow researchers as hypotheses for investigation, even
though they have mostly emerged from superficial observational and self-report sources
of data. Such pseudo-applications, as we would refer to them, can do more harm than
good to the credibility of the LM field (Al-Hoorie, 2018).
While we do not discount the expertise practitioners build over years of experience,
having all spent decades in language classrooms ourselves, as educational researchers
we must also concede that the evidentiary basis for what passes as effective, high-lever-
age language pedagogy must come from an empirical understanding of how people learn
languages in instructed settings (Han & Nassaji, 2019; What Works Clearinghouse,
n.d.). In order to help the reader evaluate the contribution the LM field has made to lan-
guage teaching, we suggest a simple three-pronged approach. We invite readers to con-
sider how many motivational applications satisfy the following criteria:
1. Originality: The application is not a common-sensical practice that the average
teacher (Sato & Loewen, 2018), or even an uninformed observer (Maley,
2016), can figure out on their own and without the labor-intensive academic
research conducted by teams of PhD holders.
2. Source: The application originates from or is significantly reshaped by the LM
field, rather than being borrowed and repackaged from existing educational
and psychological theories. This is to establish whether our field is a mere
subsidiary consumer of these “mainstream” fields, and whether our field actu-
ally contributes to their dialog in meaningful ways.
3. Methodology: The effectiveness of this application to classroom practice has
been demonstrated through independently replicated (preferably pre-registered)
experimental interventions whose effect sizes are considered substantial enough
to warrant educational implementation—or through a sufficiently evidence-
based transferability argument in other research paradigms.
Al-Hoorie et al. 139
We suspect that the list of LM applications satisfying these criteria would be very
short. Indeed, it is no secret that “[g]ood teachers know far more about motivating stu-
dents than the sum of knowledge that can be gained from research” (Henry et al., 2019,
p. 15). A counterargument might argue that the LM field is still in its infancy, aged just
60 years as noted earlier—or even 30 years since the shift to classroom-oriented research.
However, first, motivation is one of the most popular research topics, showing an expo-
nential increase in quantity year after year (Boo et al., 2015). At the same time, the qual-
ity of much of this work, we would argue, has not seen a corresponding upward trend
(e.g., Al-Hoorie & Al Shlowiy, 2020; Hiver & Al-Hoorie, 2020a). Second, as mentioned
above, many language researchers do list such pseudo-applications routinely, and super-
ficially, in their publications. It would indeed be a solemn cause for self-reflection if an
avalanche of research over several decades has not produced some motivational applica-
tions satisfying the three criteria we proposed above.
We acknowledge that, by nature, progress in the human and social sciences is slower
than in the hard sciences (cf. Meehl, 1978). Consider for example advances in the medi-
cal and technological arenas. Dewaele (2019) additionally argued that the advent of
complexity theory with its rethinking of generalizability might have slowed down con-
tribution to practice (though see Hiver & Al-Hoorie, 2020b, for an in depth treatment of
this topic). Along these lines, one veteran motivation scholar openly declared:
We are not doing science, we are doing the difficult stuff. Science was developed for the
physical world. We deal with the symbolic world of abstract conceptualizations such as
motivation, intention, goals, rewards, wishes, imagined futures. So we don’t do science;
we only explore phenomena of interest. (John Schumann, cited in Dörnyei & Ryan, 2015,
Obviously, exploring phenomena of interest is one thing, and claiming to inform
teachers about how to do their job more effectively is quite another. Giving advice to
teachers has become de rigueur of late, which strikes us as antithetical to engaging in
necessary critical reflection on theory and the limits of available empirical evidence.
In this paper, we probe why LM research has been hampered from making genuine
and direct contributions to teaching. We first argue that this status quo has resulted to
a large extent from an identity crisis in our field. We then make the case that a second
major factor is the marginalization of the role of context. We present insights from
Vygotsky’s sociocultural theory and complexity theory to address the vital role of
context, and then contemplate ways to translate these insights into practice.
Identity Crisis: Three Factors
Although scholars with a social agenda may see it as having a sociological dimension
(Clément & Norton, submitted; Norton, 2020), motivation is generally seen by LM
researchers as a psychological construct. Indeed, “the psychological dimension will not
go away but is likely to take up an increasingly central position” (Dörnyei, 2019a, p. 33).
140 Journal of Language and Social Psychology 40(1)
Despite this heavy flavor of psychology in motivation, LM researchers typically gradu-
ate from (applied) linguistics and language departments, where they study a mixture of
courses on theoretical linguistics and on practical aspects of language teaching—the
latter having “virtually no linguistic foundation” (Dörnyei, 2019a, p. 28). Some of these
departments may additionally offer one or two courses on the psychology of language,
but this is inadequate to equip the new generation of researchers with the tools, skills,
and methods necessary for systematic research on psychological phenomena. LM
researchers therefore spend years training as applied linguists, but end up doing psychol-
ogy research. Many would probably agree that these years of training would be rela-
tively squandered if the linguistics knowledge gained is not actually utilized in and
applied to subsequent LM research. (Indeed, one does not need a degree in linguistics to
read and understand the latest and most cutting-edge LM literature.) Thus, LM research-
ers, in effect, graduate from the “wrong” departments.
In recognition of the psychological nature of LM, a growing number of LM
researchers identify as language learning psychologists. They now have their own
International Association for the Psychology of Language Learning, which oversees a
biannual Psychology of Language Learning (PLL) conference and a dedicated psy-
chology journal (Journal for the Psychology of Language Learning). There is also a
growing interest in positive psychology in LM (Al-Hoorie, 2017; Dewaele et al., 2019;
Pitts, 2019); it would be rather unusual to do positive psychology research but then
claim not be a psychologist. At the same time, our engagement with the latest in psy-
chological research is still not at an optimal level. And, as psychologists, we “do not
have the option of ignoring the new psychological approaches” (Dörnyei, 2019a, p.
33). As is often seen in reference lists, our field seems to make little attempt to keep up
with the latest findings and methods in either psychology or psycholinguistics (Oga-
Baldwin et al., 2019). Beyond citing a few classics, mostly published in the 1980s and
1990s, there is generally little indication of an interest to enter into a conversation with
mainstream psychologists—let alone publish in their flagship journals.2 As a sign of
this identity crisis, language and linguistics departments have produced a generation
of motivation researchers with “minimal formal training in the other core discipline,
psychology” (Mercer & Ryan, 2016, p. 3).3
The Fundamental Difference Curse
Another factor that contributes to this identity crisis is the longstanding belief that
language learning is substantively different from learning other school subjects. Since
language has a social element related to an out-group, learning a foreign language is
presumed to have deep identity and cultural implications (e.g., Dörnyei, 2003, 2009;
Gardner, 1985, 2010; Williams, 1994), somehow making it “a special case” (Ushioda,
2012). In fact, this idea “has been accepted by researchers all over the world, regard-
less of the actual learning situation they were working in” (Dörnyei, 2005, p. 67) and
is considered a “breakthrough” that has “rightfully influenced the motivation research
[for] decades” (Dörnyei, 1994b, p. 519). This view has been described as the funda-
mental difference hypothesis (Al-Hoorie & Hiver, 2020).
Al-Hoorie et al. 141
While there is hardly any direct empirical evidence to support this hypothesis, there
is actually some evidence to the contrary. Some research shows that motivational pro-
cesses of language learning and of learning other school subjects are comparable (see
Al-Hoorie & Hiver, 2020; Lalonde & Gardner, 1993; MacIntyre et al., 2012).
Furthermore, researchers interested in other school subjects have expressed similar
sentiments to those found in the LM field. For example, there is a decade of evidence
that identity, emotions, social and political factors, both inside and outside of school,
can have an impact on learning mathematics (e.g., Boaler, 2002; Darragh, 2016;
Gutiérrez, 2013; Nasir & de Royston, 2013). Indeed, if LM researchers believe that
their area of study is somehow unique, then it would be logical to also believe that
psychology and education are the wrong places to look for insight. This fundamental
difference myth has apparently contributed to an egocentric isolation of our field, fur-
ther impeding its development. Crucially, this isolation stems not only from a rigid
paradigmatic perspective. As noted by De Costa et al. (2017; see also De Costa et al.,
2019), theory, paradigm, and methodology are inextricably linked. Isolation leads to
methodological limitations, a point to which we turn next.
The Questionnaire Curse
LM research has its roots in individual differences (see, for example, Dörnyei, 2006).
Individual differences research (e.g., on personality and intelligence) typically involves
asking participants a set of questions and then using their responses to predict impor-
tant outcomes. When LM researchers turned their attention to the classroom, the meth-
odology of this paradigm—represented in questionnaire-heavy research designs—has
persisted. Regrettably, the most popular outcome variable in contemporary LM litera-
ture is self-reported intended effort. This convenient outcome variable is sometimes
euphemistically called motivated behavior and at other times simply the criterion
measure “sometimes with capital C and M” (Al-Hoorie, 2018, p. 740). Combined with
the accessibility of user-friendly software crunching such self-report data at will, moti-
vation research has become obsessed with designs that “relate one measure based on
verbal report to another measure based on verbal report” (Gardner, 2010, p. 73). The
most popular research design has become administering self-report questionnaire
scales to measure both independent and dependent variables, and then presenting
tables of correlations showing significance asterisks (Al-Hoorie, 2018). This wide-
spread methodological practice is why Ushioda (2016), based on Meara’s (2009)
observation, describes a large proportion of LM research as “boring and predictable”
and “rather dull” (p. 565).
As a natural consequence of this flood of boring motivational research (pardon the
oxymoron), a growing number of major applied linguistics journals have implemented
blanket desk-reject policies to submissions of such exclusively observational research.
Just as Gardner and Tremblay (1994a) cautioned from the very beginning during the
Modern Language Journal debate, claims based on observational findings are prob-
lematic and can sometimes be “of no value” (p. 366). Instead, we need more empirical
evidence that is interventional in nature (although we, of course, do acknowledge the
142 Journal of Language and Social Psychology 40(1)
value of sound descriptive research explaining phenomena that would have otherwise
gone unnoticed). Mere correlations, even if camouflaged with sophisticated proce-
dures like structural equation modeling, remain observational and usually cannot shed
direct light on whether a motivational or pedagogical application is effective (Hiver &
Al-Hoorie, 2020a, 2020b). Unlike other language areas where the number of instruc-
tional interventions can reach double the amount of observation research (Plonsky,
2013), LM interventions remain a rare commodity.
The Role of Context
To be clear, we are not advocating an anti-research position. We do acknowledge the
contribution of academic research, especially to “macro,” policy-level aspects. In gen-
eral education, for example, there have been important insights about issues such as
lesson duration, spaced repetition over days and weeks, and flipped learning. In lan-
guage research more specifically, we have obtained rich insights from areas such as
language testing, materials development, and curriculum design. However, when it
comes to actual classroom teaching, teachers are required to make constant, split-sec-
ond decisions to adapt to changing and evolving contexts (Hiver et al., 2019). Asking
teachers to learn how to teach from research findings is akin to asking an individual to
learn how to drive or swim through reading books sans actual practice. Books might
help in some respects (e.g., explaining rules, giving general tips), but in the end drivers
and swimmers have to refine their skills through sustained practice and by trial and
error due to the complex and unpredictable nature of context. This is precisely why
understanding the role of context is so essential. In the following sections, we present
two perspectives on context and then try to synthesize insights from them into class-
Vygotskian Sociocultural Theory
Veresov and Mok (2018) emphasize that in any developing system, it is essential to
approach the theme of investigation as a unit, not as separate elements. A dialectical
approach using superordinate concepts can provide clues to understanding the complex-
ity of motivation in each language learner. One such superordinate concept is per-
ezhivanie, which refers to “emotional experience” or “lived experience” (Veresov &
Mok, 2018, p. 89; see also Vygotsky, 1994). According to perezhivanie, an individual
learner and their environment are two crucial considerations. Individual learners with
different previous learning histories, backgrounds, and genetic makeup will perceive and
place value on the environment differently. In this sense, perezhivanie can be a useful
epistemological tool to illuminate the differential effects of the environment among lan-
guage learners. Lantolf and Swain (2020) argue that this conceptualization helps explain
why the effect of the environment on individual development is not deterministic, “a
charge that was, and continues to be, leveled by those who are uncomfortable with a
theory claiming that the source of psychological development resides in the social envi-
ronment” (p. 84). In other words, though we may find very general trends, every learner
Al-Hoorie et al. 143
creates still a unique perezhivanie. Veresov and Mok (2018) therefore argue: “it is only
through examination of perezhivanie that we can come to understand the specific per-
sonal and situational characteristics that determined these aspects of the children’s social
situations of development at a particular moment” (p. 92).
The proposal to prioritize the subjective, differential impact of the environment on
the language learner can also be found in the concept of affordances (van Lier, 2004).
Developed initially by Gibson (1979), an ecological understanding of affordances can
be distinguished from the environment. While the environment may be full of poten-
tial, it becomes meaningful to the learner only if they realize this potential. Affordances
are therefore “what is available to the person to do something with” (van Lier, 2004,
p. 90). To synthesize arguments from Vygotsky (1994) and van Lier (2004), when a
language learner perceives the importance of the environment at the personal level, the
environment is transformed into an affordance that enables a learner to experience
perezhivanie. The experience of perezhivanie, in turn, significantly affects the learn-
er’s more discrete motivational characteristics. For example, reconstruction of self-
efficacy creates the potential for the learner to further perceive the environment
differently when a new dialectical motivational cycle commences.
Similarly, language learning motivation, as it is incubated, maintained, and possibly
terminated in a subjectively perceived environment, requires long-term investigation to
identify its ontogenetic influence on the learner’s language development over their
lifespan. Ontogenesis is distinguished from microgenesis, or “the momentary instances
of concrete, practical activity in which subjects engage with the world around them”
(Cross, 2010, p. 439). In contrast, ontogenetic investigation refers to the accumulated
accounts of personal, microgenetic “aha” moments, which require substantial longitu-
dinal analysis of individual language learners as unique agentic beings. A “personal”
timeline encapsulating the past, present, and future is essential to account for a learner’s
motivation. This point is affirmed by some language identity researchers such as Norton
(2013), who views identity as “the way a person understands his or her relationship to
the world, how that relationship is constructed across time and space, and how the per-
son understands possibilities for the future” (p. 4). Perceived experiences of success or
failure in language learning are connected to the learner’s current level of motivation,
which, in turn, creates a fertile ground for the learner’s future motivational outlook. In
this regard, Ushioda’s (2009) person-in-context relational view may need to expand to
and encompass a history-in-person ontogenetic view (Donato & Davin, 2018). Donato
and Davin (2018) state that ontogenetic development is
the history of a single human being and is situated in relation to one’s sociocultural and
historical circumstances and the tools that have been derived from one’s involvement in
situated social practices that are currently used to mediate and regulate mental functioning.
One of the main ways complex dynamic systems theory can help language researchers
to rethink the essence of motivation is to conceptualize LM as a complex system
144 Journal of Language and Social Psychology 40(1)
situated in context. Complex systems consist of a number of components embedded in
context, interacting with each other interdependently, and changing over time in sys-
tem-wide patterns of behavior (Hiver & Al-Hoorie, 2016). This relational unit of anal-
ysis has encouraged scholars to think about how parts of the whole relate to each other
and, in contrast to much of the existing work, to adopt a view of motivation as more
organic and constrained more by contextual affordances (Nolen et al., 2015). Once
researchers are able to view motivation as relational and context-dependent, a com-
panion principle to this shift in thinking is that context shapes complex system behav-
ior and its outcomes (Ushioda, 2009). This notion of interdependence within a language
learning context and the phenomena under investigation is not new in the study of
language development and use (Ushioda, 2016), but it has thus far been peripheral to
mainstream LM. It is only recently that the notion of LM as a complex system situated
in context has come to be discussed more explicitly in LM research (e.g., Hiver &
Papi, 2019), and we anticipate that a more explicit consideration of this notion will
yield future enhancements in to research designs.
The openness of complex systems to the environment gives rise to context-depen-
dent behaviors, and this means that LM development and outcomes cannot be fully
understood by breaking them into discrete parts (Hiver & Larsen-Freeman, 2020).
This person–context interdependence (see also Ushioda, 2009) encourages a concep-
tual shift to view context as an intrinsic, core part of all motivated thought and action.
The main research implication of this viewpoint is that LM is always situated and
contextually constrained (e.g., Joe et al., 2017; Papi & Hiver, 2020). This assumption
is also grounded in the idea that adaptation and development are not based on pre-
existing or hard-wired motivational mechanisms separate from the immediate context
of which a system is part (Larsen-Freeman, 2017). Instead, in particular contexts, soft-
assembled mechanisms that involve a particular adaptation of the system in its envi-
ronment are viewed as a major mechanism for motivational change. Such soft-assembled
aspects of motivation are only realized within the immediate context of a situation or
task (Larsen-Freeman & Cameron, 2008), and involve only the tools and structures
that are currently available and necessary to the language learner. Simply put, complex
systems in LM are embedded within an environment and are an integral constitutive
part of that context. For this reason, contextual factors will now need to be understood
as key dimensions of the system itself (Overton & Lerner, 2014; Rauthmann et al.,
2015). Thus, LM can no longer be conceived of exclusively as a conventional, modu-
lar independent variable. Consequently, the broad contribution of complex dynamic
systems theory to future advances in LM is its potential ability to “explain the dynamic
development of real people in actual contexts” (Dörnyei, 2017, p. 87).
Translating These Insights into Practice
The complex and multifaceted nature of LM described above makes us wonder whether
it is possible for our understanding to even approximate the abstract notion of motiva-
tion, let alone provide teachers with workable pedagogical recommendations. A more
realistic endeavor may be to shift attention to the more tangible and actionable construct
Al-Hoorie et al. 145
of engagement (Hiver et al., 2021). Studying learner engagement allows us to take into
account motivation but in specific tasks, in certain environments, and under certain con-
ditions. As Dörnyei (2019b) explains, engagement offers “a natural way of mapping the
most important facets of the learning experience, which in turn allows us to capture the
key aspects in measurable terms” (p. 25). In the LM field, such contextual-level analysis
has been relegated to the role of an elusive shadow. Dörnyei (2019b) posits two possible
reasons for this situation: the historical roots of context and its under-theorized nature,
and the over-emphasis on the “self” in recent literature (Al-Hoorie, 2018).
To better conceptualize the dynamic, diachronic transformational nature of the lan-
guage learning experience in context, we also need to cast a wider net that recognizes
and accommodates various crucial environmental factors (i.e., school contexts, sylla-
bus, the teaching materials, learning tasks, peers, teachers). It is hard to fathom how
this task can be accomplished competently without transdisciplinary research (De
Costa & Norton, 2017; Hiver et al., in press; The Douglas Fir Group, 2016). As men-
tioned above, many LM researchers seem to “self-train” in psychology after complet-
ing formal education as (applied) linguists. This leads to a situation akin to eclecticism,
and even though it “has assumed a meaning of almost the highest praise. . . eclectic
positions have never yet led to success” (Leont’ev, 1978, p. 46). Self-training in other
disciplines is not the most efficient approach to transdisciplinary research.
Transdisciplinary research is less about individual researchers gaining (shallow)
expertise in multiple disciplines, and more about a group of researchers with (deep)
expertise in different disciplines teaming up to address a phenomenon of common
interest (Hiver et al., in press). From this perspective, LM becomes the arena where
researchers meet and collaborate after they obtain training and expertise in their
respective fields (e.g., linguistics, psychology, sociology, economics, neuroscience,
genetics, etc.). When linguists, trained formally as linguists, bring in their linguistics
knowledge and team up with psychologists, they would most likely produce more
quality research than would linguists-turned-psychologists.
The fruit of such transdisciplinary collaboration, while certainly illuminating and
informative, will eventually reach the same roadblock when it comes to translating
LM research findings to actual classroom practices. Research findings are invariably
generic and need to be localized and adapted to a large extent—in turn making research
contribution secondary and peripheral. At the same time, the best teaching is personal-
ized and adapted to accommodate the individual learner’s motivation, needs, and his-
tory. The teacher, in the traditional sense, would find it overwhelming to process all
this data for each individual learner considering the large number of students that
teachers have to deal with, per class, usually for just one semester before a new batch
of students comes in.
One way out of this vicious cycle draws from artificial intelligence (Dodigovic,
2005). Artificial intelligence has the potential to efficiently automate the teaching pro-
cess, taking into account the individual learner’s history, current skill, and anticipated
challenges, more than a human teacher ever could. For example, researchers have
started exploring the potential of chatbots in education (e.g., Pham et al., 2018; Yang
& Evans, 2019). In theory, such chatbots can be programmed to provide an adaptive
146 Journal of Language and Social Psychology 40(1)
learning experience (i.e., identifying the learner’s current proficiency level and pre-
senting appropriate tasks), to recognize student linguistic input despite their develop-
mental and typing errors, to detect subtle improvement and deterioration in performance
and adjust tasks accordingly, to apply evidence-based motivational (even game-like)
principles, to account for each student’s individual learning history ontogenically, to
integrate data from physiological markers to determine real-time mood, fatigue, anxi-
ety, and other emotions—which can even be unconscious to the learner themselves—
and to do all that in a human-like fashion so that one cannot tell whether they are
interacting with another human or a machine. This promises to create a personalized
learning experience with the “virtual agent” being available for 24 hr a day on the
learner’s smart device. Considering that youngsters nowadays seem to enjoy spending
time more on their phones than talking with other people, artificial intelligence would
bring about a revolution in language learning.
The rise of artificial intelligence, machine learning, and virtual reality would lead
to a drastic transformation in the traditional educational process. In fact, these devel-
opments will push the field to rethink the role of teachers and instructional designers
when technology becomes—rather autonomously—able to provide language input,
process student output, and provide meaningful feedback to enhance language learn-
ing. In a similar vein, it is anyone’s guess what teacher preparation will look like in an
era of artificial intelligence. As an illustration, it is not unimaginable that, as artificial
intelligence takes a stronger hold and accumulates massive amounts of personal data
on students, privacy laws might constrain teachers’ access to students’ private data.
Will this once more reduce the role of the teacher to that of a “technician”? Whether
we take the ominous outlook that artificial intelligence foreshadows the death of the
language teacher, or more optimistically believe that a human touch will always
remain indispensable, few would question the fact that teacher education will need to
anticipate and adapt to a redefinition of the teacher’s role.
Most existing LM literature would consequently be at risk of becoming obsolete
after the artificial intelligence revolution. Indeed, the “T” in ELT and TESOL might
come to stand for Technology at some point. If that is the case, it is likely that LM
research will continue being disengaged from everyday classroom reality without a
means like artificial intelligence to translate its findings to practice.
In this article, we have presented what some might consider a sharp self-critique of the
body of LM research. We believe that it is important for a healthy discipline to engage
in critical reflection over its achievements. The implicit assumption in the whole LM
literature is that researchers have a doctor–patient relationship with language teachers,
though in reality if the whole LM literature were to suddenly disappear, this would
hardly make a dent in everyday teaching practice. The impact of research on practice
has generally speaking been “negligible, even zero” (Morrison & van der Werf, 2016,
p. 351) and “at best disappointing; silence is a powerful condemnation” (p. 352; see
also Hiver & Dörnyei, 2017, on teacher immunity).
Al-Hoorie et al. 147
In LM, the calls to move away from the social element of motivation, then repre-
sented in integrative motivation, has not led to the classroom-friendly research schol-
ars had hoped for. The cognitivization of motivation has not been accompanied by a
comparable and corresponding emphasis on context. To date, probably the best advice
to give to a novice teacher is not to bury themselves in recently-published LM research,
but to simply rely on experience and trial and error, and perhaps a good mentor. But
this state of affairs is not a promising sign for the maturity or the contribution of our
field to language teaching practice.
We have also argued that although most LM researchers already acknowledge that
motivation is fundamentally psychological, a large proportion of LM researchers do
not explicitly identify as psychologists earlier in their career and education. This
acknowledgment has to reflect on the formal training of researchers as well as in jour-
nal policies, conference guidelines, and grant requirements. We have also argued that
there is an urgent need for more transdisciplinary research to further our understanding
of language-inflected motivation. An important part of this transdisciplinary research
for the future might include the role of artificial intelligence and how it can transform
teaching as we know it today.
Finally, the call for transdisciplinary research is reminiscent of the tale Gardner and
Tremblay (1994b) told during the Modern Language Journal debate about two friends
whose disagreement about the glass being half-full or half-empty led to discussions
about various interesting topics long into the evening “but they parted good friends
knowing that they had both profited immensely from the conversation” (p. 524).
We would like to thank Ema Ushioda, Jean-Marc Dewaele, John Schumann, Mirosław Pawlak,
Tammy Gregersen, Paul Tremblay, and W. L. Quint Oga-Baldwin for their valuable comments
on an earlier draft.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship,
and/or publication of this article.
The author(s) received no financial support for the research, authorship, and/or publication of
Ali H. Al-Hoorie https://orcid.org/0000-0003-3810-5978
Phil Hiver https://orcid.org/0000-0002-2004-7960
1. In recent years, Marsden and colleagues have set up the OASIS database (https://oasis-
database.org/about) which is a repository of summaries (one-page descriptions of research
148 Journal of Language and Social Psychology 40(1)
articles) in order to make research into language learning and teaching openly available
and easily accessible to anyone who might be interested in applied linguistics research.
2. Publishing in psychology journals might additionally be challenging for LM researchers
due to, among other things, methodological expectations. This point further underscores
the need to reconsider graduate training for future LM researchers. We thank Jean-Marc
Dewaele for this comment.
3. As one reviewer suggested, researchers can self-train in psychology and other disciplines
after completing their formal education. It would be disconcerting to rely on this strategy
broadly in a field, rather than rethinking education in the first place. Moreover, one criti-
cism of self-training is that it can be amateurish in nature.
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Ali H. Al-Hoorie is an assistant professor at the English Language and Preparatory Year
Institute, Royal Commission for Jubail and Yanbu, Saudi Arabia. He completed his PhD in
Applied Linguistics at the University of Nottingham under the supervision of Professors Zoltán
Dörnyei and Norbert Schmitt. His research interests include motivation theory, research meth-
odology, and complexity. His books include Research Methods for Complexity in Applied
Linguistics (with Phil Hiver) and Contemporary Language Motivation Theory: 60 Years Since
Gardner and Lambert (1959) (with Peter MacIntyre).
Phil Hiver (PhD, University of Nottingham) is an assistant professor of Foreign & Second
Language Education at Florida State University. His published research takes a complex and
dynamic view of individual differences in language learning and explores their interface with
instructed language development and language pedagogy. He is co-author (with Ali Al-Hoorie)
of Research Methods for Complexity Theory in Applied Linguistics (Multilingual Matters).
Tae-Young Kim (PhD OISE/University of Toronto) is a professor in the Department of English
Education at Chung-Ang University, Seoul, South Korea. His research interests center around
L2 learning and teaching (de)motivation, and the contribution of sociocultural theory and activ-
ity theory to L2 motivation.
Peter I. De Costa is an associate professor at Michigan State University. An educational lin-
guist by training, his research areas include emotions, identity, ideology and ethics as they relate
to second language acquisition, second language teacher education and language-in-education
policy. He also studies social (in)justice issues. He is the co-editor of TESOL Quarterly.