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JOURNAL OF APPLIED LINGUISTICS AND TESOL (JALT)
Vol.7.No.4 2024
45
INTERACTING WITH THE AUDIENCE: METADISCOURSE MARKERS IN TOP TEN
IMPACT FACTOR JOURNAL ARTICLE ABSTRACTS IN APPLIED LINGUISTICS
Shazia Aziz1, Dr Fakhira Riaz 2
Fatima Jinnah Women University, Rawalpindi
ORCID ID: 1 0000-0001-9566-5053 , 2 0000-0002-6369-4498
Abstract
This is a corpus-based investigation of interactional metadiscourse used in the top ten impact factor journal article
abstracts in Applied Linguistics published during 3 consecutive years, i.e., from 2019 to 2021. Using a corpus
(IFALA 2019-2021) of the 3 years’ abstracts compiled during an earlier study of lexical density measures (Aziz &
Riaz, 2024), ten sub-corpora were compiled and the markers were studied using Ant Conc software. The hedges
were found to be the most frequent occurrence among the markers, and personal mentions were minimal. It points
out that keeping in view the increasing trend of the empirical nature of studies in Applied Linguistics, authors are
relying on the scientific findings to speak for themselves and not influence the opinions of readers by being present
or emphasizing claims. Moreover, they are careful enough to give margin for alternate interpretations to the
discourse community they are addressing i.e., the scholars and practitioners in Applied Linguistics by not being
emphatic about claims, not introducing personal judgments and not engaging the readers much. This study
contributes by adding 15 more items to the metadiscourse markers’ list proposed by Hyland (2005).
Keywords: attitude markers; corpus-based; boosters; impact factor; engagement markers;
hedges; interactional metadiscourse; self-mentions
1.Introduction
One of the most effective ways to represent interaction is through metadiscourse, which is the
―commentary on a text‖ produced by the text producer while writing or speaking. The author's
rhetorical cognizance of the recipient/audience as a discourse participant who may be engaged,
led, and influenced by a text that is both understandable and compelling through the selection of
metadiscourse devices (Hyland & Jiang, 2018). The things that most obviously indicate the
writer's or reader's presence in a text, organize propositional discourse, and reveal the writer's
viewpoint are the subject of metadiscourse analysis (Hyland, 2005). One of the most popular
methods for analyzing academic writing is metadiscourse analysis because it allows authors to
regulate how they establish their presence, convey claims of expertise, and interact with the
audience (Pearson & Abdollahzadeh, 2023).
This study analyses the interpersonal metadiscourse markers‘ use abstracts of the articles
published in the top 10 Applied Linguistics impact factor journals between 2019-2021. Due to
the dialogic and persuasive nature of the abstract genre, we focused on studying the interactional
metadiscourse markers in our corpus of Applied Linguistics journals. Though some researchers
have conducted a bundle-driven analysis of metadiscourse markers, too, but since abstract is a
brief genre, we considered just studying sentence-initial bundles might bring very minimal
results that would not be representative of the whole corpus. Moreover, without context, it would
be difficult to gauge the overall presence of the authors, their stance and engagement with the
audience. Hence, we conducted this analysis on whole texts of the abstracts in our corpus IFALA
2019-2021(Aziz & Riaz, 2024).
2. Literature Review
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46
Academic writing is a crucial evaluation instrument that necessitates mastery of abilities
including evidence-based reasoning and critical thinking (Irvin, 2010). Academic arguments, in
contrast to ordinary arguments, need to be well-structured and fully backed by evidence in order
to effectively communicate points of view and enhance the writer's and audience's
comprehension of the subject (Huan & Hong, 2024). Language skills improve communication
(Javaid et al., 2023; Ramzan et al., 2023; Ikramullah et al., 2023). This is achieved through the
use of metadiscourse among other things. Hence, it has been an important area of research since
the last 40 decades. Metadiscourse is a significant linguistic feature. It helps the recipient to
―organize, interpret and evaluate the information given‖ (Crismore et al., 1993 p. 40).
The producer's comments on a text is known as metadiscourse (Jiang & Hyland, 2018). Here, we
adopt an interpersonal viewpoint and concentrate on metadiscourse as a toolkit of tools at
authors' disposal for structuring a discourse or determining their position with regard to the
discourse's subject matter or audience. Hyland & Jiang (2018) investigated how, over a 50-year
period, professional writing metadiscourse changed across many fields. They observed a large
increase in interactive characteristics and a significant drop in interactional kinds after
conducting a diachronic analysis of a of 2.2 million-word corpus of papers published in the top
ranked journals across four fields. The disciplines of discursive soft knowledge have
significantly decreased, whereas science topics have increased significantly, according to
interactional metadiscourse.
Authors including Atkinson (1999), Bazerman (1988), Banks (2008), Salager-Meyer
(1999), and Valle (1999) also found significant changes in scientific research articles. Hyland &
Jiang (2018) investigated if there was any truth to the widely-heard assertion that academic
writing has gotten more casual in recent years (Hyland & Jiang, 2017). They discovered that
although this may be true in the hard sciences, the social sciences appeared to be moving in the
other way. By using a variety of metadiscourse strategies to create a text that is both
understandable and compelling, a writer may engage, direct, and sway the reader as a participant
in the discourse. This rhetorical awareness is known as interaction. It focuses on the components
that indicate the writer's point of view, arrange propositional discourse, and most plainly imply
the writer's or reader's presence in the text (Hyland, 2005). Thus, metadiscourse serves to both
structure coherent discourse and serve as a collection of rhetorical decisions that assist the writer
engage readers and project their perspective.
Academic writing is fundamentally about persuading readers to trust and adopt a certain
viewpoint. This persuading takes place in a disciplinary context, which binds the writers to
present their points in alignment with their audience‘s expectations and the field‘s genre
conventions. In the process, writers try to anticipate disagreements and present their arguments
according to the assumptions of the disciplinary community. Metadiscourse is very instrumental
in determining this interaction. Pioneered by Harris (1959) and further advanced in the field of
Applied Linguistics by Vande Kopple (1985) and Crismore (1989) among others, metadiscourse
refers to the way language imparts information as well as guides readers in understanding that
information. By employing rhetorical strategies like offering commentary, directly addressing
readers, etc., writers can control the way their messages are perceived. Metadiscourse helps
authors achieve this along with making academic writing more persuasive and coherent.
Hyland's (2004, 2005) model of metadiscourse provide a widely acclaimed framework
for analysing the rhetorical strategies text producers employ in order to engage the audience. The
JOURNAL OF APPLIED LINGUISTICS AND TESOL (JALT)
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framework refers to two kinds: interactive metadiscourse markers and interactional
metadiscourse markers.
―Interactive markers are those focusing on organizing discourse in a way that helps readers
navigate the text and recover the intended meanings. These include:
Transitions i.e., the features that indicate links between ideas, such as addition, contrast
and consequence (e.g., ―thus‖, "but‖ etc.,).
Frame markers i.e., features that signal text boundaries or indicate structural organization
e.g., topic shifts and sequencing (e.g., "to conclude").
Endophoric markers i.e., references to other portions of the text that guide readers (e.g.,
"noted above").
Evidentials i.e., references and citations sources external to the text (e.g., "Haris
contends").
Code glosses i.e., rephrasing or explanations of information to help understanding (e.g.,
"for instance").
Interactional resources focus on the participants of the interaction and display the writer's
persona and a tenor consistent with community norms. They include:
Hedges withhold the writer's full commitment to a statement
(might/perhaps/possible/about)
Boosters express certainty and emphasise the force of propositions (in fact/definitely/it is
clear)
Attitude markers express the writer's attitude to propositions, conveying surprise,
obligation, agreement, importance, and so on (unfortunately/I agree/surprisingly).
Engagement markers explicitly address readers by focusing their attention or including
them in the text through second person pronouns, imperatives, questions and asides.
(consider/note that)
Self-mentions explicit reference to authors (I, we, our, my, etc.)‖ (Hyland & Jiang, 2018)
This framework is a representation of a long-standing scholarly interest in the pragmatic aspects
of discourse (Chafe & Nichols, 1986; Crismore, 1989; Nystrand, 1989;).
The function of interactional metadiscourse in various academic genres—particularly
abstracts—has been the subject of several investigations. For example, Hyland (2000) points out
that abstracts are a crucial place for metadiscourse, where authors need to convince readers of the
study's significance while providing a brief summary of the research. Interactional markers can
be strategically used in abstracts to support assertions, emphasize the importance of results, and
draw readers in by reflecting expectations or common knowledge.
Research has shown that using metadiscourse devices in a variety of genres has
advantages (Hyland, 1998, 2005). The term "metadiscourse" describes the language strategies
authors employ to structure their writing, draw readers in, and express their viewpoint on the
subject matter (Hyland, 2005). It is essential for directing readers through the work, building the
reader-author rapport, and encouraging engagement. Interactional metadiscourse has been
thoroughly studied in academic writing because it controls the writer-reader relationship.
According to Hyland and Tse (2004), writers can reveal their attitude toward their ideas and
engage their audience in a personal conversation through interactional metadiscourse.
These indicators strengthen persuasion, let writers anticipate probable objections from
readers, and strike a balance between assurance and caution. Moini & Salami (2015) studied
engagement and stance markers in author guidelines of journals published by leading publishers
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in Humanities and Social Sciences and found engagement features to be significantly higher in
frequency than stance markers. Abbas & Shehzad (2018) conducted a study on the exclusive
pronouns used by authors in research articles published in Pakistani research journals covering
both soft and hard fields. Their findings indicate that the pronouns used by authors exhibit a bi-
covalent and tri-covalent metadiscursive bond, indicating a multifunctional interpersonal role for
author exclusivity.
Researchers have also started studying the diachronic transformations in employing these
markers e.g., Hyland & Jiang (2018) studied it in research articles in 4 fields published over a
period of 50 years, and Huan & Hong (2024) studied this aspect in reviews of Linguistics books
over 20 years using Hyland‘s (2005) Interpersonal model. The findings indicate that these
markers were used consistently during the course of the study years. They discovered that among
interactional metadiscourse, hedges were the most common, followed by engagement indicators
and other elements. Between 2002 and 2022, they did see a little decrease in interactional
indicators, though. Using a diachronic viewpoint, Gillaerts and Van de Velde (2010) concentrate
on three characteristics of abstractions from a single subject. Hyland and Jiang look at journals
with high impact factors in two different fields.
Researchers studying metadiscourse are also becoming interested in spoken genres, despite their
lack of research. For example, Metadiscourse signals in academic oral presentations in English
language and discipline-based classrooms were examined by Singh et al. in 2023. They
discovered that the employment of both types of metadiscourse markers varied little throughout
courses. Yang (2023)
investigated Interactional Metadiscourse Features in English speeches prepared by Chinese
university students.
Some researchers have also recently conducted a bundle-driven analysis of
metadiscourse. Li et al. (2017) and Huang (2024) e.g., employed a bundle-driven approach to
studying metadiscourse markers. Huang (2024) used a bundle-driven approach to examine
interactional metadiscourse bundles in the argumentative writing of Chinese College students.
Their examination of IMBs revealed that attitude indicators and self-mentions are often used to
accomplish interpersonal communication in written texts.
Saidi and Karami (2024) carried out a cross-move study of interactional metadiscourse markers
in abstracts published in Iranian and foreign history journals, realizing the close relationship
between movements and metadiscourse. Both in the worldwide corpus and in Iranian abstracts,
they discovered a high frequency of introduction, purpose, and product shifts. In both sets of
abstracts, the category of interactional metadiscourse indicators that appeared the most
frequently was boosters.
Hedges were more frequently used by the local authors while the international
researchers made a higher use of self-mentions.
In their 2023 systematic review, Pearson & Abdollahzadeh examine the study on
metadiscourse in academic discourse through an analysis of high-quality empirical papers that
were published between 1990 and 2021. They discovered that cross-sectional corpus-based
analysis utilizing intercultural rhetoric was employed in more than 80% of study projects. About
37% of corpus-based studies adhered to the "thin" tradition, prioritizing marker frequency counts
above interpretations that are context specific.
Research has revealed that Metadisourse is discipline specific as well. Metadiscourse works
as a "recipient design filter,"(Hyland & Jiang, 2018) making it clear how the authors want the
JOURNAL OF APPLIED LINGUISTICS AND TESOL (JALT)
Vol.7.No.4 2024
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recipients to interpret their messages, and thus, it demonstrates the writer‘s understanding of the
discourse community that they are addressing (Hyland, 2005; Hyland & Tse, 2004), and the
particular discipline they are interacting with.
Early in the 1990s, studies on academic metadiscourse were conducted. Most of these
studies compared English writings with those produced in other languages (Hu & Cao, 2011;
Mur Dueñas, 2011) or by non-native English speakers (Hong & Cao, 2014; Li & Wharton,
2012). Previous study has examined English literature, such as research articles, with an
emphasis on abstracts and introductions (e.g., del Saz Rubio, 2011; Gillaerts & Van de Velde,
2010). Comparisons across disciplines and genres are frequent. As an illustration of the
disparities in goals across various genres, Kawase (2015) discovered that writers employ more
metadiscourse in research article openings than in PhD theses.
Studies conducted across disciplines have yielded particularly valuable insights, pointing
out differences in the application of metadiscourse not only in research articles (e.g., Cao & Hu,
2014; Jiang & Hyland, 2018), but also in undergraduate textbooks (Hyland, 1999), postgraduate
dissertations (Charles, 2006), undergraduate essays (Noble, 2010), and academic book reviews
(Tse & Hyland, 2006). Language challenges impact higher education whereas cognitive impact
of discourse and artificial intelligence enhance language communication (Javaid et al., 2024).
Bruce (2010) noted that there are notable distinctions between the essays written by students in
sociology and English, pointing out that they use distinct textual resources and rhetorical
devices.
These studies reveal the diverse ways disciplines approach academic persuasion, showing
how conventions emerge through participation in specific academic communities, thereby
reflecting shared contexts and norms.
Top-tier publications employ highly developed rhetorical tactics, according to research on
metadiscourse in quality journals. Scholarly research across cultures and disciplines (Hyland,
2005; Gillaerts & Van de Velde, 2010) has shown that esteemed journals typically display a
deliberate balancing act among metadiscourse indicators in order to optimize comprehensibility
and reader interaction. In order to fulfill the demands of a worldwide audience, journals with
greater impact factors typically require a more rigid structure and stronger engagement tactics.
More in-depth research has recently been done on the metadiscourse policies of
prestigious Applied Linguistics publications. In a significant study, e.g., Pho (2020) examined
the interactional markers found in abstracts from high-impact publications. The study discovered
that in order to walk the tightrope between authority and humility, good writers employ a mix of
hedges and boosters. Additionally, engagement markers and self-mentions are consistently
employed in these journals, demonstrating a tendency toward personalizing the discourse and
speaking directly to the reader—a characteristic that strengthens the authorial presence.
Another research by Basturkmen (2021) looked at articles and found that writers in
prestigious journals are using engagement indicators like rhetorical questions and direct appeal to
readers ("we") more frequently. These techniques work well for engaging readers in the
discussion and highlighting the study's importance. Moreover, self-mentions—which were
formerly frowned upon in scholarly writing—have gained acceptance in high-impact journal
abstracts, especially in Applied Linguistics though its frequencies have declined over the years
according to Hyland & Jiang‘s (2018) diachronic study.
While previous research has presented useful insights into the role of interactional
metadiscourse markers in journal abstracts, there are still gaps that warrant further exploration.
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Given the evolving nature of academic writing conventions, the growing emphasis on open
science, and the increasing pressure on scholars to produce impactful, globally recognized
research, metadiscourse is an important dimension to study in the current context. Even while
earlier studies have provided insightful information on the function of interactional
metadiscourse in journal abstracts, this recent period is noteworthy because academic writing
traditions are undergoing transformations as shown by diachronic studies in the field (Hyland &
Jiang, 2018) and the review of literature(Pearson & Abdollahzadeh, 2023), open science is
becoming more and more important, and scientists are under more and more pressure to produce
influential, internationally acknowledged research.
3. Corpus and method
The 10 sub-corpora from our corpus of the abstracts of the top 10 Applied Linguistics journals
published between 2019 and 2021, IFALA 2019–2021(Aziz & Riaz, 2024), were examined for
this work. In all, there were 1172 abstracts using 199172 tokens. Table 1 gives a description of
the corpora: Table 1: IFALA 2019-2021 Corpus Description
Journal
Abbreviated
title
Impact
Factor
No of
abstracts
No of
tokens
Applied
Linguistics
APP Ling
5.7
116
19156
Computer
Assisted
Language
Learning
Comp Assis
Lang Learn
4.7
109
20,689
Modern
Language Journal
Mod Lang J
4.7
104
18937
Language
Learning
Lang Learn
4.6
87
12994
Lang Learning
and Technology
Lang Learn &
Tech
4.3
47
8862
International
Journal of
Bilingual
Education
INT J BILING
EDUC
4.1
219
38368
Studies in Second
Language
Acquisition
STUD
SECOND
LANG ACQ
3.9
121
19253
Language
Teaching
Research
Lang Teach R
3.8
105
18929
Journals of
Second Language
Writing
J SECOND
LANG WRIT
3.5
71
13184
Bilingualism-
Language and
Cognition
BILING-
LANG COGN
3.5
193
28489
1172
199172
JOURNAL OF APPLIED LINGUISTICS AND TESOL (JALT)
Vol.7.No.4 2024
51
Total
Source: 2021 Journal Impact Factor, JCR 2021, Clarivate JCR,
Clarivate
In accordance with Hyland & Jiang (2018) and Huan & Hong (2024), AntConc software version
3.5.9 was used to ascertain the types and frequencies of interactional metadiscourse indicators as
recommended by Hyland (2005). Using the concordance tool Antconc, we next searched each of
the 10 sub-corpora for the components included in Hyland's (2005) list of the most common
interpersonal metadiscourse markers in academic writing (Anthony, 2011). The original common
context size was ten tokens on either side of the marker. The phrase was extended to 15 tokens,
and if necessary, to 20 tokens on each side, when the context within a 10-token range was
insufficient to fully comprehend the statement.
Figure 1 Screenshot of Concordance lines from Antconc Software
Moreover, additional items were added that were unique to our corpora and were not on
the list provided. Their frequencies were discovered in line with Hyland & Jiang's (2020) claim
that the 500 items suggested by Hyland (2005) serve only as a starting point for disciplinary
JOURNAL OF APPLIED LINGUISTICS AND TESOL (JALT)
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52
analysis and that metadiscourse is fundamentally an open category to which new items can be
added by the writers in accordance with the contextual needs. Furthermore, frequency counts
only show patterns of metadiscourse occurrence in uneven-sized corpora since metadiscourse is
frequently realized by signals that might extend to clause or sentence length (Hyland & Jiang,
2018). In order to ensure that these items performed as metadiscourse (in accordance with the
aforementioned criteria), the concordance lines constituting each manifestation of the markers
listed were personally reviewed, and unnecessary incidences were removed. Before reaching a
consensus, the two writers individually went through a sample of some cases, reaching an inter-
rater agreement of 95%. Next, in order to facilitate cross-corpora comparison, the findings were
normalised to per 1000 words.
We attach the list of markers examined in appendices A through E, per the
recommendation of Pearson and Abdollahzadeh's (2023) systematic review; present a list of the
articles included, clarify how metadiscoursal function was checked, and provide examples
illustrating difficult coding decisions for ensuring transparency.
4.Findings and discussion:
Using the concordance function and manual analysis of context, the frequencies of the five
interpersonal metadiscourse markers were noted down. The raw frequencies of the metadiscourse
indicators included in the abstracts of each sub-corpus and publication are displayed in Table 2
below.
Table 2: Raw Frequencies of Interactional Metadiscourse Markers in IFALA 2019-2021 Corpus
Category
Ap
p
Lin
g
Com
p
Assi
s
Lan
g
Lear
n
Mo
d
Lan
g J
Lan
g
Lear
n
Lan
g
Lear
n &
Tec
h
INT J
BILIN
G
EDUC
STUD
SECO
ND
LANG
ACQ
Lan
g
Teac
h R
J
SECO
ND
LANG
WRIT
BILIN
G-
LANG
COGN
Tot
al
Hedges
232
181
152
157
70
440
235
213
104
339
212
3
Boosters
162
131
110
102
04
235
181
129
115
220
138
9
Self-
mentions
165
75
106
118
22
156
91
65
46
130
974
Engagem
ent
markers
100
64
54
36
02
153
178
105
123
87
902
Attitude
marker
39
29
20
24
07
78
37
35
21
60
350
Total
698
480
442
437
105
1062
722
547
409
836
573
8
As the total no of tokens can‘t be controlled in corpus studies, to make the data comparable, the
raw frequencies were normalized to one thousand words. The normalized frequencies of the
markers are shown in Table 3 below.
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:
Table 3: Normalised Frequencies of Interactional Metadiscourse Markers (per 1000 words) in in
IFALA 2019-2021 Corpus
Category
APP
Lin
g
Com
p
Assi
s
Lan
g
Lear
n
Mo
d
Lan
g J
Lan
g
Lear
n
Lan
g
Lear
n &
Tec
h
INT J
BILIN
G
EDU
C
STUD
SECO
ND
LANG
ACQ
Lan
g
Teac
h R
J
SECO
ND
LANG
WRIT
BILIN
G-
LANG
COGN
Tota
l
Hedges
12.1
1
8.75
8.03
12.0
8
7.90
11.47
12.21
11.2
5
7.89
11.90
10.6
6
Boosters
8.46
6.33
5.81
7.85
0.45
6.12
9.40
6.81
8.72
7.72
6.97
Self-
mentions
8.61
3.63
5.60
9.08
2.48
4.07
4.73
3.43
3.49
4.56
4.89
Engagem
ent
markers
5.22
3.09
2.85
2.77
0.23
3.99
9.35
5.55
9.33
3.05
4.53
Attitude
marker
2.04
1.40
1.06
1.85
0.79
2.03
1.92
1.85
1.59
2.11
1.76
Total
36.4
4
23.2
0
23.3
4
33.6
3
11.8
5
27.68
37.50
28.9
0
31.02
29.34
28.8
1
Findings and discussion
As Table 3 presents, attitude markers were found to be the least frequently used in the corpora
i.e., 1.76 times per 1000 words overall, and the most frequent markers are hedges with a
frequency of 10.66 per 1000 words overall. This shows that the authors try to keep the abstracts
as objective as possible by giving minimal chances for personal opinions affecting the
perceptions of the audience, and also try to allow for different interpretations of the claim by
using more hedges. Boosters are next in maximum frequency after hedges, i.e., 6.96 per 1000
words.
Self-mentions were 4.89 per 1000 words and engagement markers were 4.53 per 1000
words in the whole corpus. Overall, the use of metadiscourse markers in the corpus was found to
be 28.81 per 1000 words, which is quite similar to 38.882 found by Yasmeen (2019) in Social
Sciences abstracts; and Šandová‘s (2021) diachronic study of article abstracts spanning 4 decades
which found a decline of interpersonal metadiscourse markers from 43.25 per 1000 words in the
1980‘s to 35.01 in the 1990s and 31.89 in the 2000s and further 25.98 in the 2010‘s.
As shown in bold in the appendices, this study found some additional items apart from those
suggested by Hyland‘s (2005) list of markers. We added these markers to the list by Hyland in
the respective categories: Hedges, Boosters, and Self-mentions, on the basis of their occurrence
in the present corpus. They are given in Table 4:
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Table 4: Additional markers found in IFALA 2019-2021 Corpus
Hedges
General
Certain
Most
Main
Believe
Boosters
Well-established
Determined
Co-determined
Self-mentions
The writers
The writers‘
The researcher
The researcher‘s
The researchers
The researchers‘
Ours
Moreover, it was realised that the given lists use British spelling of expressions like ‗analyse‘,
but it was revealed during analysis that some abstracts in the corpus had used the American
spelling, too i.e., ‗analyze‘. So, both spellings were considered while finding and counting the
markers in such cases where two alternate spellings exist. It is suggested that an option be added
to the list to cater to alternate/American spelling, too for an inclusive representation. The
following parts of the section discuss the findings regarding the 5 interpersonal markers in
greater detail.
Hedges
In line with Hyland & Jiang (2018), hedges were found to be the most frequent devices among
interactional markers in IFALA 2019-2021 corpus. However, this feature is not used by Applied
Linguists as much now as they were used in earlier years of the field since 1965 (Hyland &
Jiang, 2018). Noting the decline in the use of hedges in Applied linguistics over time, Hyland
and Jiang (2018) observe that there is a decrease in words that express hypotheticalness (would),
possibilities (may, may, and could), and presumption (should and ought). Rather than depending
on the consistency of logical reasoning or the whims of observable facts, writers tend to employ
hedges to arrive at more speculative interpretations by relying on the ambiguity inherent in
human judgment. We observe the same in our corpus, e.g.,
We argue that online interactions with members of the target culture can
be as beneficial as studying abroad and that it is at least more beneficial
than traditional classroom language learning in the development of L2
learners‘ perceived ICC. (Lee & Song, 2019).
Hedges are frequently a wise choice for authors since they let them indicate that their
assertions are tentative and open to criticism at the time of writing (Hyland & Jiang, 2018). By
lowering the confidence of their statements, authors can more carefully connect their new
assertions with the current thinking of a disciplinary readership and deliver their arguments in a
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55
more nuanced manner. For example, we can observe writers adopting a position that strives to
include readers in their validation of statements in these cases.
The word ―certain‘ was added to the list of hedges because in some cases, it pointed out non-
specific quantities or entities e.g.,
begins when the participants encounter
a need to use a
certain
(
for them, unknown) word and ends when
they use
in reading self-efficacy were
significantly greater for learners of
certain
profiles who received strategy-based
instruction, with implications for
as the word ‗certain‘ also occurred with words other than those suggested by Hyland‘s (2005) list
i.e., ‗amount‘, ‗extent‘ and ‗extent‘ as in the example above. In a context like the above, it serves
as a hedge in the sense of ―not specific‖ or ―some but not all.‖ So, in such cases, ―certain‖ was
counted as a hedge.
Interestingly, there were some examples of double hedges used simultaneously within one
context e.g., ―typically assumed‘, seems to suggest‖, ‗seems likely‘ as in the following cases:
are related to concreteness in a
more nuanced way as
typically
assumed in conceptual metaphor theory:
metaphors high in the
A recent study on reading non-
adjacent collocations seems to
suggest
similar processing advantages as for
adjacent collocations (Vilkaitė 2016), but
an impact on their daily life.
Indeed, if the caller
seems
likely not to produce this upshot report, it is
There may be further explanations to the frequent use of hedges in the courpus e.g., one
reason could be to express the possibility that the same study may yield different findings if it
is replicated. Moreover, it could imply that the findings may not be overgeneralised. In some
other cases, the researcher(s) may be investigating a complex phenomenon subject to
multiple interpretations.
Boosters
As Hyland and Jiang (2018) contend, the most obvious indicators of a writer's authorial standing
are most likely attitude markers and boosters, which convey the writer's dedication to and
emotional evaluations of the topic. However, in the present corpus, boosters were less frequently
used than hedges. Moreover, it was observed that boosters were mostly used in recommendations
instead of making a strong claim on personal notions e.g.,
Teachers should consider error types so that DDL can
promote accurate error correction in L2 writing and serve
as a practical option in L2 classrooms (Satake, 2020).
This supports the finding made by Hyland and Jiang (2016a). The most prominent and frequent
boosters i.e., ‗demonstrate‘, ‗demonstrated‘ and ‗showed‘ (see Appendix B) pointed towards the
study‘s findings instead of the writer‘s beliefs. This shows a more scientific and evidential stance
than a personal one.
The word ‗certain‘ has different connotations, which were checked in context to decide where to
put it e.g. ―certain‖ meaning ―sure‖ was counted as a booster.
Self-mentions
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Vol.7.No.4 2024
56
Self-mentions enable authors to be more present in their writings by indicating their
presence, accepting accountability for their words and deeds, and taking ownership of their
interpretations (Hyland & Jiang, 2018). When self-mentioned in data interpretations and
claims of innovation, it conveys a more intimate and direct authorial involvement.
However, the authors are less frequently mentioning themselves recently than in the past.
As can be seen in Appendix C, in our IFALA 2019-2021 Corpus, self-mentions made a %
of the total. It is noteworthy that in case of a single author, self-mention was rare but it was
generously used in case of plural authors. So, out of a total of 974 self-mentions, 132 were
singular [I (64), me (1), my (53), the researcher (13), the researcher‘s (1)], and in case of more
than one author, it was 852 [we (621), us (18), our (193), the authrors (5), the authors‘ (2), the
researchers (1), the researchers‘ (2)]. ‗The writer‘s‘ was used once in the journal Language
Learning and Technology, but its context did not refer to the author, so it was not counted. So it
suggests that authors use personal mentions more for a purpose of expressing community
consciousness and not as an expression of the self.
Engagement markers
Engagement markers made 4.53 per 1000 words only as shown in Table 3. As Appendix D
demonstrates, the most prominent engagement markers included consider (n=23), contrast
(n=28), demonstrate (n=34), determine (n=28), develop (n=42), find (n=22), increase (n=25),
key (n=50), measure (n=30), our (n=41), should(n=50), show(n=152), and we (n=116). As
mentioned in case of personal mentions too, engagement markers were used to established a
consciousness of the community to which the writer and the audience belong.
In this study, we will look at the predictive validity of a practical, low-stakes, web-based
academic reading and vocabulary screening test.
Attitude Markers
As can be seen in Appendix E, ‗appropriate‘ (n=29) , ‗even‘ (n=64), ‗important‘ (99),
‗importantly‘ (20), and ‗interest‘ (29) were the most frequent expressions among attitude markers
while the rest occurred very sparingly in the whole corpus. Since affect is rarely expressed in
academic research writing (Biber et al., 1999) and is typically implied rather than explicitly
stated, attitude indicators came from a considerably smaller base. However, since they are a
marked decision, they have a bigger impact when they do happen and convey strong opinions,
whether favorable or unfavorable.
A less definite capacity to depend on the persuasive efficacy of in-group understandings of
procedures, ideas, and the relevance of findings may thus be somewhat offset by more
interventionist engagement strategies that actively guide readers toward certain points of view.
5. Conclusion
In conclusion, though interactional metadiscourse markers play a vital role in article abstracts,
and help authors communicate effectively enhancing reader engagement, managing persuasion,
and building rapport with the audience, this study did find a moderate use of them owing to the
gradually increasing empirical nature of studies in Applied Linguistics.
This study has contributed by adding 15 more items to the list of interpersonal
metadiscourse markers that future researchers can explore in their corpus/data/contexts. It was
JOURNAL OF APPLIED LINGUISTICS AND TESOL (JALT)
Vol.7.No.4 2024
57
found that personal mentions were used more as a plural, i.e., in case of more than one author,
and less in case of a single author, as shown in Appendix C (Plural nouns and pronouns being
more than singular), which indirectly shows authors‘ desire to display a sense of community
engagement and collectivity.
Moreover, the use of attitude markers is also scarce. This is consistent with the findings
of Hyland and Jiang (2018), who found that, in contrast to earlier times, authors are currently
utilizing fewer features to express their opinions and interact directly with readers. The social
circumstances that metadiscourse aids in constructing are intimately tied to its application.
Although reader awareness of the text has increased elsewhere, nearly all interactional measures
have seen a considerable reduction in the discursive soft knowledge categories.
The decrease in their use in applied linguistics thus indicates a shift in the way writers
perceive their readers and the appropriate degree of certainty they might feel comfortable with.
Consequently, when calculating conviction, it seems wise to invest in a claim, which often
depends on what readers in the field are likely to accept. Less hedges (and boosters) than in the
past suggest a more measured approach to epistemic attitude and cautious handling of authorial
interference. This might be connected to what some have seen as a rise in scientism in the social
sciences as a result of a stronger emphasis on science in its predominate techniques and
approaches (e.g. Glynos & Howarth, 2007).
According to Hyland & Jiang (2018), Applied Linguistics was a relatively new field in
1965 with limited literature and an emphasis on first-hand reports of language instruction. The
way assertions are argued and accepted has been significantly impacted by the increase of
empirically oriented research, the discipline's progress to include a larger range of concerns, and
the vast extension of the literature supporting its academic objectives.
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Appendix A: Frequencies of Hedges in IFALA 2019-2021 Corpus
Interactional Dimension of Metadiscourse
Frequencies of Hedges in IFALA 2019-2021 Corpus
Hedges
Appli
Com
Mod
Lang
Langu
Interna
Studie
Lang
Jour
Bilingu
To
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Vol.7.No.4 2024
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ed
Lingu
istics
puter
assist
ed
Lang
uage
Lear
ning
ern
Lang
uage
Jour
nal
uage
Lear
ning
age
Learn
ing
and
Techn
ology
tional
Journa
l of
Biling
ual
Educat
ion
and
Biling
ualism
s in
Secon
d
Langu
age
Acqui
sition
uage
Teac
hing
Rese
arch
nal
of
Seco
nd
Lang
uage
Writi
ng
alism:
Langua
ge ad
Cogniti
on
tal
Almost
3
0
2
0
0
6
1
0
0
4
16
About
1
0
0
0
0
2
0
0
0
0
03
Appare
nt
1
0
0
0
0
0
0
0
0
1
02
Appare
ntly
0
0
0
0
0
0
0
0
0
0
00
Appear
2
0
0
0
0
2
1
0
2
1
08
Appear
to be
0
0
0
0
0
0
0
0
0
0
0
Appear
ed
0
2
1
0
0
8
5
0
0
6
22
Appear
s
2
0
0
0
1
2
1
2
0
3
11
Approx
imately
0
0
2
1
0
1
0
1
0
0
05
Argue
12
0
2
3
2
16
1
6
1
1
44
Argued
1
0
1
0
0
9
1
1
0
5
18
Argues
2
0
1
0
0
4
0
2
1
0
10
Around
1
0
0
0
2
12
0
2
5
2
24
Assum
e
0
1
0
0
0
0
1
0
0
2
04
Assum
ed
2
1
2
1
0
1
0
0
0
3
10
Believe
d
0
0
0
0
0
0
4
4
1
0
09
Broadl
y
1
2
2
1
0
0
0
0
0
0
06
C
e
r
t
a
i
0
0
0
0
0
0
0
0
0
0
0
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Vol.7.No.4 2024
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n
a
m
o
u
n
t
Certain
extent
0
0
0
0
0
0
0
0
0
0
0
Certain
level
0
0
0
0
0
0
0
0
0
0
0
Claim
1
0
0
3
0
3
2
2
1
2
14
Claime
d
0
0
0
0
0
2
2
0
0
1
05
Claims
3
0
1
2
0
0
3
0
2
1
12
Could
3
18
5
9
3
11
9
6
0
10
74
Couldn
‘t
0
0
0
0
0
0
0
0
0
0
0
Doubt
0
0
0
0
0
0
1
0
0
0
01
Doubtf
ul
0
0
0
0
0
0
0
0
0
0
0
Essenti
ally
0
1
0
0
0
0
1
0
0
0
02
Estimat
e
0
0
1
0
0
0
2
0
2
1
06
Estimat
ed
0
0
0
2
0
0
0
0
1
1
04
Fairly
1
0
0
0
0
0
0
0
0
0
01
Feel
0
0
1
0
1
2
2
0
1
0
07
Feels
0
0
0
0
0
0
0
0
0
0
0
Felt
0
1
1
0
0
1
0
1
2
0
06
Freque
ntly
7
2
3
2
0
11
3
2
2
1
33
From
my
perspecti
ve
0
0
0
0
0
0
0
0
0
0
0
From
our
perspecti
ve
0
0
0
0
0
0
0
0
0
0
0
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Vol.7.No.4 2024
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From
this
perspect
ive
1
0
0
0
0
0
0
0
0
01
Generall
y
6
2
2
3
0
9
5
6
0
5
38
Guess
0
0
1
0
0
0
0
0
0
0
01
In
general
1
2
2
0
2
0
1
3
1
0
12
In most
cases
0
0
0
0
0
0
0
1
0
0
01
In
m
ost
ins
ta
nc
e
0
0
0
0
0
0
0
0
0
0
0
In my
opinion
0
0
0
0
0
0
0
0
0
0
0
In my
view
0
0
0
0
0
0
0
0
0
0
0
In our
opinion
0
0
0
0
0
0
0
0
0
0
0
In our
view
0
0
0
0
0
0
0
0
0
0
0
In this
view
0
0
0
0
0
0
0
0
0
0
0
Indicate
7
15
10
1
6
28
8
11
0
24
11
0
Indicate
d
4
15
7
6
11
10
13
9
5
6
86
Indicate
s
0
2
1
1
0
2
2
1
0
2
11
Largely
4
1
9
1
1
11
5
3
1
8
44
Likely
6
1
3
5
1
5
6
3
0
4
34
Little
6
6
4
0
2
16
9
15
10
6
74
Mainly
2
4
1
1
0
3
2
1
3
2
19
May
17
9
9
13
6
44
28
15
0
47
18
8
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May be
5
4
6
3
1
0
5
5
0
0
29
Might
7
8
5
6
2
12
9
3
0
5
57
Mostly
2
2
1
2
0
10
1
3
1
1
23
Not
und
erst
ood
0
0
0
0
0
0
0
0
0
0
0
Often
13
4
11
8
0
19
8
11
0
12
86
On the
whole
0
0
0
0
0
0
0
0
0
0
0
Ought
0
0
0
3
0
1
4
1
2
1
12
Perhaps
1
0
0
0
0
1
0
1
1
2
06
Plausibl
e
0
0
0
0
0
0
0
0
0
0
0
Plausibl
y
0
0
0
0
0
0
0
0
0
0
0
Possible
7
6
2
3
1
9
1
11
0
8
48
Possibl
y
1
1
0
0
0
1
1
0
0
5
09
Postulat
e
0
0
0
0
0
0
0
0
0
0
0
Postulat
ed
0
0
0
0
0
0
0
0
0
0
0
Postulat
es
0
0
0
0
0
1
0
1
0
0
02
Presum
able
0
0
0
0
0
0
0
0
0
0
0
Presum
ably
0
0
0
1
0
0
1
0
0
0
02
Probabl
e
0
0
0
0
0
0
1
1
0
0
02
Probabl
y
0
0
0
1
0
0
0
0
0
0
01
Quite
1
1
0
0
0
2
0
1
1
1
07
Rather
x
2
0
3
2
0
0
2
0
1
0
10
Relative
ly
2
1
1
0
2
8
2
7
5
5
33
Roughl
y
0
0
0
0
0
0
2
0
0
0
02
Seems
3
1
1
3
0
4
0
2
0
4
18
JOURNAL OF APPLIED LINGUISTICS AND TESOL (JALT)
Vol.7.No.4 2024
65
Should
4
8
3
4
2
19
0
7
4
1
52
Someti
mes
3
0
0
1
0
1
1
2
1
4
13
Somew
hat
0
0
0
1
0
0
1
1
1
3
07
Sugges
t
13
9
15
16
10
35
23
17
18
41
19
7
Sugges
ted
7
9
0
8
2
12
8
4
5
11
66
Sugges
ts
4
3
5
4
1
14
8
6
4
22
71
Suppos
e
0
0
0
0
0
0
0
0
0
0
0
Suppos
ed
0
0
0
0
0
0
0
0
0
0
0
Suppos
es
0
0
0
0
0
0
0
0
0
0
0
Suspec
t
0
0
0
0
0
0
0
0
0
0
0
Suspec
ts
0
0
0
0
0
0
0
0
0
0
0
Tend
to
2
0
0
0
1
0
1
0
0
2
06
Tended
to
0
1
2
0
0
0
1
0
0
0
04
Tends
to
1
0
0
0
0
2
0
0
0
0
03
To
my
kno
wle
dge
0
0
0
0
0
0
0
0
0
0
0
Typical
3
0
0
2
0
3
1
1
0
7
17
Typical
ly
4
0
1
6
1
5
2
1
1
6
27
Uncert
ain
0
0
0
0
0
0
0
0
1
1
02
Uncert
ainly
0
0
0
0
0
0
0
0
0
0
0
Unlikel
y
0
0
0
0
0
1
0
1
0
0
02
Unclea
r
1
0
2
0
1
2
1
1
1
7
16
JOURNAL OF APPLIED LINGUISTICS AND TESOL (JALT)
Vol.7.No.4 2024
66
Unclea
rly
0
0
0
0
0
0
0
0
0
0
0
Usuall
y
0
0
1
2
0
1
1
0
0
1
06
Would
5
5
1
1
3
4
1
5
2
4
31
Would
n‘t
0
0
0
0
0
0
0
0
0
0
0
Gener
al
4
2
5
7
0
4
8
3
4
17
54
Certai
n
5
4
2
1
2
4
5
0
3
3
29
Most
30
15
6
16
2
33
11
15
6
8
14
2
Main
4
11
4
1
1
11
4
2
1
8
47
Believ
e
1
1
1
0
0
0
2
3
0
0
08
Total
232
181
152
157
70
440
235
213
104
339
21
23
Appendix B: Frequencies of Boosters in IFALA 2019-2021 Corpus
Interactional Dimension of Metadiscourse
Frequencies of Boosters in IFALA 2019-2021 Corpus
Boosters
Appli
ed
Lingu
istics
Com
puter
assist
ed
Lang
uage
Lear
ning
Mod
ern
Lang
uage
Jour
nal
Lang
uage
Lear
ning
Langu
age
Learn
ing
and
Techn
ology
Interna
tional
Journa
l of
Biling
ual
Educat
ion
and
Biling
ualism
Studie
s in
Secon
d
Langu
age
Acqui
sition
Lang
uage
Teac
hing
Rese
arch
Jour
nal
of
Seco
nd
Lang
uage
Writi
ng
Biling
ualism:
Langu
age ad
Cognit
ion
To
tal
Actuall
y
1
0
0
0
0
0
0
0
0
0
1
Always
2
1
2
1
0
4
3
0
0
0
13
Appare
nt
1
0
0
0
0
0
0
0
0
1
2
Believe
1
1
1
0
0
0
2
3
0
0
8
Believe
d
0
0
0
0
0
1
4
4
3
0
12
Believe
0
0
0
0
0
0
0
0
0
0
0
JOURNAL OF APPLIED LINGUISTICS AND TESOL (JALT)
Vol.7.No.4 2024
67
s
Beyond
5
2
7
1
2
8
1
3
0
3
32
Beyond
doubt
0
0
0
0
0
0
0
0
0
0
0
By far
0
0
0
0
0
0
0
0
0
0
0
Certain
5
0
0
0
0
0
5
1
3
0
14
Certain
that
0
0
0
0
0
0
0
0
0
0
0
Certainl
y
0
0
0
0
0
0
1
0
0
0
1
Certaint
y
0
0
0
1
0
0
0
2
0
2
5
Clear
1
5
0
0
0
11
6
3
1
3
30
Clearly
2
0
2
0
0
2
1
0
0
0
7
Conclu
sively
0
0
0
0
0
0
0
0
0
0
0
Decide
dly
0
0
0
0
0
0
0
0
0
0
0
Definit
e
0
0
0
0
0
0
4/1
0
0
0
1
Definit
ely
0
0
0
0
0
0
0
0
0
0
0
Demon
strate
7
2
7
2
0
6
4
2
5
8
43
Demon
strated
5
7
5
7
0
7
1
8
3
14
57
Demon
strates
6
2
1
0
0
1
2
1
0
1
14
Determ
ine
7
3
1
2
0
3
7
6
2
3
34
Doubt
0
0
0
0
0
0
1
0
0
0
1
Doubtle
ss
0
0
0
0
0
0
0
0
0
0
0
Essenti
al
0
1
1
1
0
5
1
1
0
0
10
Establis
h
1
1
0
1
0
2
0
0
2
0
7
Establis
hed
3
1
3
1
1
6
1
2
0
4
22
JOURNAL OF APPLIED LINGUISTICS AND TESOL (JALT)
Vol.7.No.4 2024
68
Even if
1
2
0
0
0
0
0
1
0
0
4
Evident
1
1
0
0
0
1
1
1
1
2
8
Evidentl
y
0
0
0
0
0
0
0
0
0
0
0
Find
8
4
0
1
0
3
1
1
0
4
22
Finds
1
1
0
0
0
1
0
0
0
0
3
Found
15
20
24
21
0
42
25
26
22
38
23
3
I believe
0
0
0
0
0
0
0
0
0
0
0
In fact
1
0
0
0
0
0
1
0
0
0
2
Incontes
table
0
0
0
0
0
0
0
0
0
0
0
Incontes
tably
0
0
0
0
0
0
0
0
0
0
0
Incontro
vertible
0
0
0
0
0
0
0
0
0
0
0
Incontro
vertibly
0
0
0
0
0
0
0
0
0
0
0
Indeed
1
1
0
2
0
2
2
3
0
2
13
Indisput
able
0
0
0
0
0
0
0
0
0
0
0
Indisput
ably
0
0
0
0
0
0
0
0
0
0
0
It is
clear
0
0
0
0
0
0
0
0
0
0
0
It is
known
that
0
0
0
0
0
0
0
0
0
0
0
Know
0
0
1
0
0
3
2
0
0
2
8
Known
6
2
3
4
0
15
7
4
2
10
53
Must
5
1
0
2
0
1
3
0
4
1
17
Never
0
0
1
1
0
0
1
0
1
0
4
No
doubt
0
0
0
0
0
0
0
0
0
0
0
Obvious
1
0
0
0
0
0
1
0
0
0
2
Obvious
ly
0
0
0
0
0
1
0
0
0
0
1
Of
course
0
0
0
0
0
0
0
0
0
0
0
Prove
1
0
1
0
0
0
0
0
0
0
2
JOURNAL OF APPLIED LINGUISTICS AND TESOL (JALT)
Vol.7.No.4 2024
69
Proved
2
1
0
0
0
2
1
1
1
0
8
Proves
1
0
0
0
0
0
0
0
0
0
1
Realize/
se
0
0
0
0
0
0
0
0
0
0
0
Realize
d/sed
0
1
0
0
0
0
0
1
1
0
3
Realizes
ses
0
0
0
0
0
0
0
0
0
0
0
Really
0
0
0
0
0
1
0
0
0
0
1
Should
4
8
3
4
0
19
0
7
4
1
50
Show
28
12
14
11
0
25
15
11
13
24
15
3
Showed
14
36
22
34
0
26
58
31
19
74
31
4
Shown
9
5
6
3
0
5
6
3
2
11
50
Shows
13
1
4
1
0
10
3
2
6
1
41
Sure
0
0
0
0
0
0
0
0
1
0
1
Surely
0
0
0
0
0
0
0
0
0
0
0
The
fact
that
1
0
0
0
0
0
0
0
0
0
1
Think
0
1
0
0
0
3
1
0
1
0
6
Thinks
0
0
0
0
0
0
0
0
0
0
0
Though
t
0
0
0
0
0
1
0
0
0
3
4
Truly
0
0
0
0
0
0
0
0
0
0
0
Undeni
able
0
0
0
0
0
0
0
0
0
0
0
Undeni
ably
0
0
0
0
0
0
0
0
0
0
0
Undisp
utedly
0
0
0
0
0
0
0
0
0
0
0
Undou
btedly
0
0
0
0
0
0
0
0
0
0
0
Well
2
4
16/1
1
0
10
8
1/21
the
rest
as
well
as
17
5
49
Well
0
1
0
0
0
0
0
0
0
0
1
JOURNAL OF APPLIED LINGUISTICS AND TESOL (JALT)
Vol.7.No.4 2024
70
known
Withou
t doubt
0
0
0
0
0
0
0
0
0
0
0
Won‘t
0
0
0
0
0
0
0
0
0
0
0
True
0
1
0
0
0
3
0
0
1
6
Well-
establi
shed
0
0
0
0
1
2
0
0
0
0
3
Deter
mined
0
2
0
0
0
3
3
0
0
2
10
Co-
determ
ined
0
0
0
0
0
0
0
0
1
0
1
Total
162
131
110
102
04
235
181
129
115
220
13
89
Appendix C: Frequencies of Self-mentions in IFALA 2019-2021 Corpus
Interactional Dimension of Metadiscourse
Frequencies of Self-mentions in IFALA 2019-2021 Corpus
Self-
mentio
n’s
Appli
ed
Lingu
istics
Com
puter
assist
ed
Lang
uage
Lear
ning
Mod
ern
Lang
uage
Journ
al
Lang
uage
Lear
ning
Langu
age
Learni
ng
and
Techn
ology
Interna
tional
Journa
l of
Biling
ual
Educat
ion
and
Biling
ualism
Studie
s in
Secon
d
Langu
age
Acqui
sition
Lang
uage
Teac
hing
Rese
arch
Journ
al of
Seco
nd
Lang
uage
Writi
ng
Bilingu
alism:
Langua
ge and
Cogniti
on
To
tal
I
25
3
5
0
0
14
4
8
5
0
64
Me
01
0
0
0
0
0
0
0
0
0
01
Mine
0
0
0
0
0
0
0
0
0
0
0
My
01
1
2
0
0
2
0
47
0
0
53
We
89
47
73
100
12
100
73
0
27
100
62
1
Us
06
3
3
2
1
2
1
0
0
0
18
Our
35
19
22
16
7
35
11
8
10
30
19
3
The
author
0
0
0
0
0
0
0
0
0
0
0
The
author‘
0
0
0
0
0
0
0
0
0
0
0
JOURNAL OF APPLIED LINGUISTICS AND TESOL (JALT)
Vol.7.No.4 2024
71
s
The
author
s
2
1
1
0
0
1
0
0
0
0
05
The
author
s’
0
0
0
0
0
0
1
1
0
0
02
The
writer
0
0
0
0
0
0
0
0
0
0
0
The
writer‘
s
0
0
0
0
0
0
0
0
0
0
0
The
writer
s
0
0
0
0
0
0
0
0
0
0
0
The
writer
s’
0
0
0
0
0
0
0
0
0
0
0
The
resear
cher
4
1
0
0
1
1
1
1
4
0
13
The
resear
cher’s
1
0
0
0
0
0
0
0
0
0
1
The
resear
chers
0
0
0
0
1
0
0
0
0
0
1
The
resear
chers’
1
0
0
0
0
1
0
0
0
0
2
Ours
0
0
0
0
0
0
0
0
0
0
0
Total
165
75
106
118
22
156
91
65
46
130
97
4
Appendix D: Frequencies of Engagement Makers in IFALA 2019-2021 Corpus
Interactional Dimension of Meta discourse
Frequencies of Engagement Makers IFALA 2019-2021 Corpus
Engage
ment
Makers
Appli
ed
Lingu
istics
Com
puter
assist
ed
Lang
uage
Lear
Mod
ern
Lang
uage
Jour
nal
Lang
uage
Lear
ning
Langu
age
Learn
ing
and
Techn
ology
Interna
tional
Journa
l of
Biling
ual
Educat
Studie
s in
Secon
d
Langu
age
Acqui
Lang
uage
Teac
hing
Rese
arch
Jour
nal
of
Seco
nd
Lang
uage
Biling
ualism:
Langu
age ad
Cognit
ion
To
tal
JOURNAL OF APPLIED LINGUISTICS AND TESOL (JALT)
Vol.7.No.4 2024
72
ning
ion
and
Biling
ualism
sition
Writi
ng
The
reader's
0
0
0
0
0
0
0
0
0
0
0
About
0
0
0
0
0
0
0
0
0
0
0
Add
3
0
1
0
0
0
0
0
1
0
5
Allow
1
1
0
0
0
0
0
1
2
0
5
Analyse/
analyze
3
0
0
0
0
0
0
4
1
1
9
Apply
1
0
0
0
0
0
0
2
0
0
3
Arrange
0
0
0
0
0
0
0
0
0
0
0
Assess
5
4
0
1
0
0
5
3
2
0
20
Assume
0
0
0
0
0
0
1
0
0
1
2
By the
way
0
0
0
0
0
0
0
0
0
0
0
Calculat
e
0
0
0
0
0
0
0
0
1
1
2
Choose
0
0
0
0
0
0
0
2
0
0
2
Classify
0
1
0
0
0
0
0
0
0
0
1
Compar
e
3
1
0
0
0
2
4
0
2
0
12
Connect
2
0
0
0
0
0
0
0
1
0
3
Consider
3
2
2
0
0
6
0
3
5
2
23
Consult
0
0
0
0
0
0
1
0
0
0
1
Contrast
3
0
2
3
0
5
4
2
2
7
28
Define
0
0
0
0
0
1
0
0
0
0
1
Demonst
rate
7
1
4
2
0
6
4
2
0
8
34
Determi
ne
4
1
1
1
0
3
7
6
2
3
28
Develop
7
5
4
2
0
11
1
4
8
0
42
Do not
0
0
1
0
0
7
6
0
0
0
14
Employ
0
0
1
0
0
2
1
1
1
0
6
Ensure
0
2
0
0
0
1
0
0
1
0
4
Estimate
0
0
1
0
0
0
2
0
2
1
6
JOURNAL OF APPLIED LINGUISTICS AND TESOL (JALT)
Vol.7.No.4 2024
73
Evaluate
0
5
1
0
0
2
2
1
3
1
15
Find
8
2
0
1
0
3
1
1
2
4
22
Follow
0
0
0
0
0
2
1
1
1
0
5
Go
0
0
0
0
0
0
0
1
1
0
2
Have to
0
1
0
0
0
2
0
0
0
0
3
Imagine
0
0
0
0
0
1
0
0
0
0
1
Incident
ally
0
0
0
1
0
0
1
1
0
1
4
Increase
0
4
0
0
0
6``
5
6
0
4
25
Input
0
0
0
0
0
0
0
0
0
0
0
Insert
0
0
0
0
0
0
0
0
0
0
0
Integrat
e
0
5
1
0
0
5
0
0
0
1
12
Key
7
4
2
0
0
19
4
1
8
5
50
Let
0
1
0
0
0
0
0
0
0
0
1
Let us
0
0
0
0
0
0
0
0
0
0
0
Let x
0
0
0
0
0
0
0
0
0
0
0
Let x =
y
0
0
0
0
0
0
0
0
0
0
0
Let's
0
0
0
0
0
0
0
0
0
0
0
Lets
0
0
0
0
0
0
0
0
0
0
0
Let's
0
0
0
0
0
0
0
0
0
0
0
Look at
0
0
0
0
0
1
1
0
0
0
2
Mark
1
0
0
0
0
0
0
0
0
1
2
Measur
e
0
1
4
0
0
0
12
3
2
8
30
Mount
0
0
0
0
0
0
0
0
0
0
0
Must
5
1
0
2
0
1
3
0
4
1
17
Need to
0
0
0
0
0
0
1
3
0
4
8
Note
2
0
0
0
0
0
0
0
0
0
2
Notice
0
0
0
0
0
0
0
0
0
0
0
Observe
0
0
0
0
0
0
1
1
0
0
2
One's
0
0
0
0
0
0
1
0
0
0
1
Ones
0
0
0
0
0
/1
0
0/1
0
0/3
5
Order
0
2
0
0
0
0
0
0
7
0
9
Ought
0
0
0
2
0
0
0
0
2
1
5
Our
0
0
7/22
2
0
9
11
8
0
4
41
Pay
0
0
0
0
0
2
0
1
1
0
4
JOURNAL OF APPLIED LINGUISTICS AND TESOL (JALT)
Vol.7.No.4 2024
74
Picture
0
0
0
0
0
0
0
0
1
0
1
Prepare
0
0
0
0
0
0
0
3
1
0
4
Recall
0
0
0
0
0
0
0/22
3/0
0
0
0
Recover
0
0
0
0
0
0
0
0
0
0
0
Refer
0
0
0
0
0
0
0
0
0
0
0
Regard
1
0
0
0
0
0
0
0
2
0
3
Remem
ber
0
0
0
0
0
0
2
0
0
0
2
Remove
0
0
0
0
0
0
0
0
0
0
0
Review
2
0
0
1
0
1
0
4
1
0
9
See
0
1
1
0
0
2
2
2
2
0
10
Select
0
0
0
0
0
0
1
0
0
0
1
Set
0
0
0
1
0
0
2
7/4
3
0
10
Should
4
8
3
4
0
19
0
7
4
1
50
Show
28
11
14
11
0
25
15
11
13
24
15
2
State
0
0
0
0
0
0
0
1
6
0
7
Suppose
0
0
0
0
0
0
0
0
0
0
0
Take a
look
0
0
0
0
0
0
0
0
0
0
0
Take as
example
0
0
0
0
0
0
0
0
0
0
0
Think
0
0
0
0
0
2
0
0
1
0
3
Think
about
0
0
0
0
0
0
0
0
0
0
0
Think
of
0
0
0
0
0
0
0
0
0
0
0
Turn us
0
0
0
0
0
0
0
0
0
0
0
Us
0
0
0
0
0
1
1
0
0
0
2
Use
0
0
4
2
2
2
1
0
0
0
11
We
0
0
0
0
0
2
73
14
27
0
11
6
You
0
0
0
0
0
1
0
0
0
0
1
Your
0
0
0
0
0
0
0
0
0
0
0
Total
100
64
54
36
02
153
178
105
123
87
90
1
Appendix E: Frequencies of Attitude Markers in IFALA 2019-2021 Corpus
Interpersonal Dimension of Metadiscourse
Frequencies of Attitude Markers in IFALA 2019-2021 Corpus
Attitude
Appl
Com
Mod
Lang
Langu
Interna
Studie
Lang
Jour
Bilingu
To
JOURNAL OF APPLIED LINGUISTICS AND TESOL (JALT)
Vol.7.No.4 2024
75
Markers
ied
Ling
uistic
puter
assist
ed
Lang
uage
Lear
ning
ern
Lang
uage
Jour
nal
uage
Lear
ning
age
Learn
ing
and
Techn
ology
tional
Journa
l of
Biling
ual
Educat
ion
and
Biling
ualism
s in
Secon
d
Langu
age
Acqui
sition
uage
Teac
hing
Rese
arch
nal
of
Seco
nd
Lang
uage
Writi
ng
alism:
Langua
ge ad
Cogniti
on
tal
Admitte
dly
0
0
0
0
0
0
0
0
0
0
0
Amazin
gly
0
0
0
0
0
0
0
0
0
0
0
Approp
riately
1
0
0
0
0
1
0
0
0
0
2
Agree
0
0
0
0
0
1
0
1
1
1
4
Agrees
0
0
0
0
0
0
1
0
0
0
1
Amazed
0
0
0
0
0
0
0
0
0
0
0
Amazin
g
0
0
0
0
0
0
0
0
0
0
0
Approp
riate
6
6
0
1
0
13
0
1
2
0
29
Astonis
hed
0
0
0
0
0
0
0
0
0
0
0
Astonis
hing
0
0
0
0
0
0
0
0
0
0
0
Correctl
y
0
0
1
0
0
2
0
0
0
0
3
Curious
ly
0
0
0
0
0
0
0
0
0
0
0
Curious
0
0
0
0
0
0
0
0
0
0
0
Disappo
inting
0
0
0
0
0
0
0
0
0
0
0
Disagre
e
0
0
0
0
0
0
0
0
0
0
0
Desirab
le
0
0
0
3
0
0
0
4
1
2
10
Desirab
ly
0
0
0
0
0
0
0
0
0
0
0
Disappo
inted
0
0
0
0
0
0
0
0
0
0
0
Disappo
0
0
0
0
0
0
0
0
0
0
0
JOURNAL OF APPLIED LINGUISTICS AND TESOL (JALT)
Vol.7.No.4 2024
76
intingly
Disagre
ed
0
0
0
0
0
0
0
0
0
0
0
Disagre
es
0
0
0
0
0
0
0
0
0
0
0
Dramati
c
1
0
0
0
0
0
0
0
0
0
1
Dramati
cally
0
0
0
0
0
0
0
0
0
0
0
Even
4
6
2
5
1
14
10
5
2
15
64
Essentia
l
0
1
1
1
0
4
1
1
0
0
9
Essentia
lly
0
1
0
0
0
0
1
0
0
0
2
Even x
-
-
-
-
-
-
-
-
-
-
0
Expecte
d
0
1
0
1
0
2
1
0
0
4
9
Expecte
dly
0
0
0
0
0
0
0
0
0
0
0
Fortuna
tely
0
0
0
0
0
0
0
0
0
0
0
Fortuna
te
0
0
0
0
0
0
0
0
0
0
0
Have to
0
1
1
0
0
0
0
0
0
0
2
Hopeful
ly
0
0
0
0
0
0
0
0
0
0
0
Hopeful
0
0
0
0
0
0
0
0
0
0
0
Importa
nt
12
6
9
6
3
31
7
11
4
10
99
Importa
ntly
2
1
0
1
1
0
3
2
0
10
20
Interest
4
1
3
0
0
2
5
6
5
3
29
Interesti
ngly
0
2
0
0
0
0
0
2
0
3
7
Inappro
priate
0
0
0
0
0
1
0
0
1
1
3
Inappro
priately
1
0
0
0
0
0
0
0
0
0
1
Interesti
ng
1
0
0
0
0
1
0
0
0
0
2
Prefer
0
0
0
0
0
0
0
0
0
0
0
Pleased
0
0
0
0
0
0
0
0
0
0
0
JOURNAL OF APPLIED LINGUISTICS AND TESOL (JALT)
Vol.7.No.4 2024
77
Prefera
ble
0
0
0
0
0
0
0
0
0
0
0
Prefera
bly
0
0
0
0
0
0
0
0
0
0
0
Preferre
d
0
0
1
0
0
1
0
0
0
2
4
Must
5
1
0
1
0
1
3
0
4
1
16
Ought
0
0
1
3
0
1
4
0
0
1
10
Remark
able
0
1
0
0
0
1
0
0
0
0
2
Remark
ably
1
0
0
0
1
0
0
0
0
0
2
Surprisi
ngly
1
1
0
2
0
2
0
0
0
1
7
Shocke
d
0
0
0
0
0
0
0
0
0
0
0
Shockin
g
0
0
0
0
0
0
0
0
0
0
0
Shockin
gly
0
0
0
0
0
0
0
0
0
0
0
Striking
0
0
0
0
0
0
1
2
0
0
3
Striking
ly
0
0
0
0
0
0
0
0
0
0
0
Surpris
ed
0
0
0
0
0
0
0
0
0
0
0
Surprisi
ng
0
0
0
0
1
0
0
0
0
0
1
Unfortu
nate
0
0
0
0
0
0
0
0
0
0
0
Unfortu
nately
0
0
0
0
0
0
0
0
0
0
0
Unusua
lly
0
0
0
0
0
0
0
0
0
0
0
Underst
andably
0
0
0
0
0
0
0
0
0
0
0
Unbelie
vable
0
0
0
0
0
0
0
0
0
0
0
Unbelie
vably
0
0
0
0
0
0
0
0
0
0
0
Underst
andable
0
0
0
0
0
0
0
0
0
0
0
Unexpe
cted
0
0
0
0
0
0
0
0
1
5
6
JOURNAL OF APPLIED LINGUISTICS AND TESOL (JALT)
Vol.7.No.4 2024
78
Unexpe
ctedly
0
0
1
0
0
0
0
0
0
0
1
Unusua
l
0
0
0
0
0
0
0
0
0
0
0
Usual
0
0
0
0
0
0
0
0
0
1
1
Total
39
29
20
24
07
78
37
35
21
60
35
0
ABOUT THE AUTHORS
Shazia Aziz is an Assistant Professor of English at COMSATS University Islamabad, Lahore
Campus. Her area of specialization is English Linguistics. She has vast experience in teaching
at graduate and postgraduate level and research. Her interests include but are not limited to
Genre Analysis, Ecolinguistics, Climate Change Discourse, Media and Discourse, ELT
Business Communication and Computer-Mediated Communication. She is a well-cited author
of scores of research articles in journals of national and international repute and a book
chapter published by the Cambridge University Press. She also won a research productivity
award and a fellowship under a scholar exchange program for a semester at Duke University
North Carolina, USA. She also serves as a reviewer for many reputed international journals.
Moreover, she has presented at several conferences and has also conducted several faculty
training workshops during her career. This work is from her PhD dissertation done under
supervision of Fakhira Riaz (PhD).
Fakhira Riaz Ph.D., is an Assistant Professor at the English Department of Fatima Jinnah Women
University, Rawalpindi, Pakistan. Her main research interests include corpus linguistics,
phraseology, and vocabulary studies. She is currently working on a project focused on
phraseology in academic writing.
