The measurement of narrative competence at the higher education level is a little studied subject. The objective of this research is to elaborate and validate a scale to measure the self-perception of the level of macronarrative competence of university students, in three dimensions: textual narrative, digital narrative and transmedia narrative. The results demonstrate the content validity of the instrument by judges' criteria; likewise, the three dimensions obtained a high acceptance through the the results of Aiken's V coefficient. The exploratory factor analysis of the macronarrative competence scale showed an adequate correlation between the items and a good sample adequacy respectively. It is concluded that the proposed scale is a valid and reliable instrument to measure self-perception of macronarrative competence.
Article Details
How to Cite
Núñez-Pacheco, R., Barreda-Parra, A., García-Candeira, M., & Aguaded, I. (2024). Design and validation of a scale of self-perception of macronarrative competence in university students. Ocnos. Journal of reading research, 23(2). https://doi.org/10.18239/ocnos_2024.23.2.418
Núñez-Pacheco, Barreda-Parra, García-Candeira, and Aguaded: Design and validation of a scale of self-perception of macronarrative competence in
university students
Introduction
Narrative is an age-old practice that has allowed human beings to express their deepest
experiences and emotions. argues that we are homo fabulators, that is, beings who tell stories thanks to the
faculty of language. For many centuries, oral narratives, mainly myths, were the means
by which an explanation of the world was given (); later, with the appearance of writing, written narratives made it possible to express
and build worlds based on words. In later centuries, new media emerged that allowed
storytelling such as cinema, hypertext, digital narrative, video games, etc.
The study of narrative has had several approaches, but mainly literary studies have
made great contributions to the approach of narrative texts. It was the Russian formalists
at the beginning of the 20th century who initiated a systematic study; later, structuralism
and, in particular, narratology contributed to the analysis of the structures of narrative
texts, which are made up of a succession of events. Their organization revolves around
a plot axis with a series of actions performed by characters in a given time and space
(). From a poststructural perspective, other pragmatic elements are considered for
the study of narrative, such as the narrator's intention, the social context in which
it is produced, the narrator's narrative competence, the audience, etc. (). From this approach, narrative must be seen beyond the structures of the story.
Here the intentionality with which it has been produced and received that matters.
The act of narrating is not only expressed in literary creations, but also in the
everyday life of human beings, mainly through oral stories.
On the other hand, telling a story using different media has given rise to new forms
of narrative expression. In the late 1980s, Joe Lambert introduced the term digital
storytelling and defined it as a narrated short film (; ). Digital storytelling has a technological support and has a multimedia character,
i.e., it presents elements of textual, visual, auditory nature, which makes it possible
to create hybrid narratives (). Its application in various fields of human endeavour has been widely accepted,
especially in education (; ; ; ; Rubegni & Landoni, 2015). Moreover, according to several studies, the use of digital
storytelling contributes to the development of several competences in students such
as communicative and narrative competence () as well as digital competence ().
At the beginning of the 21st century, coined the term transmedia storytelling to refer to the convergence of media to expand
a story on different platforms. points out that this expansion occurs “a través de diferentes sistemas de significación
(verbal, icónico, audiovisual, interactivo, etc.) y medios (cine, cómic, televisión,
videojuegos, teatro, etc.)” (). User participation is crucial in this process of story expansion. points out three characteristics of transmedia storytelling:
- character-building, and its link with other fictional characters;
- world-building, which has to do with the design of a fictional universe;
- authorship, individual or collective, and its role in the extension of the story
in other media.
The expansion of these narrative universes has been made possible, to a large extent,
by technological development in recent decades.
Traditionally, narrative competence has been related to the comprehension and production
of narrative texts, both oral and written, whose argumentative axis allows the narrated
events to present the necessary coherence and cohesion (; ). Likewise, narrative competence has been associated with literary competence, since
the narrative genre has a strong presence in universal literature mainly through novels
and short stories. This competence comprises several aspects: reading the text, knowledge
of the conventions of literary discourse and recognition of the contextualization
of the text (); it also demands from the reader a predictive, inferential, intertextual and critical
capacity (), which goes beyond a literal reading of the literary text (). From a more up-to-dated perspective of literary studies, points out that narrative competence is: "esquemática (superestructura narrativa),
semántica (macroestructura semántica o de base temática) y pragmática (macroacto del
discurso llevado a cabo mediante el relato)" (). All these approaches to narrative competence only refer to the textual level.
Given the recent technological development, there is a need to integrate the different
ways of narrating a story. For this reason, this research considers narrative competence
as the set of knowledge, skills and attitudes to understand and produce narrative
texts, digital storytelling and transmedia storytelling, and therefore proposes the
denomination of macronarrative competence, which would be composed of three dimensions:
textual narrative, digital storytelling and transmedia storytelling:
- The first dimension, textual narrative, has to do with knowledge of narrative genres
and the structure of narrative texts; that is, it is the ability to analyze, interpret,
produce and evaluate narrative texts, as well as to connect with a narrative text
on an emotional level.
- The second dimension, digital storytelling, has to do with knowledge of digital
storytelling, i.e., the ability to analyze, interpret, and evaluate digital storytelling,
as well as the ability to connect with digital storytelling on an emotional level.
- The third dimension, transmedia storytelling, has to do with knowledge of transmedia
storytelling, i.e. the ability to analyze, interpret, produce and evaluate transmedia
storytellings.
The measurement of narrative competence has been studied mainly at the child level
() and at the high school level (); however, in the field of higher education it is a field to be explored, even more
so if the aim is to integrate the textual, digital and transmedia levels, as described
above.
The proposed macronarrative competence has its correlate in other competences that
have surpassed its initial denomination, as is the case of media competence, understood
as a set of knowledge, skills and attitudes that allow to critically interact with
media messages; and is composed of six dimensions: languages; technology; interaction
processes; production and dissemination processes; ideology and values; and aesthetic
dimension (; ). Likewise, propose an "extended or augmented competence" as a holistic form that transcends
media competence and comprises in turn other competences: personal, social, civic
and cultural. Similarly, along with other researchers, within the Transmedia Literacy project, proposes a
taxonomy of 134 transmedia competencies organized into 9 dimensions: production; risk
prevention; performance, social, individual and content management; media and technology;
ideology and ethics; narrative and aesthetics. The latter is presented transversally,
since young people consume indistinctly diverse media and platforms, and are more
attracted by the stories and content than by the type of media platform used to tell
them (). Similarly, there are other proposals with a transmedia integration approach ().
The main objective of this research is to develop and validate a scale to measure
the self-perception of the level of macronarrative competence of university students
in three dimensions: textual narrative, digital storytelling and transmedia storytelling.
The central question to be answered is the following: What is the level of self-perception
that university students have about their macronarrative competence?
Materials and methods
Design and procedure
This is an instrumental cross-sectional study (). The research procedures were developed following the six stages proposed by :
1. Construct proposal: the construct "macronarrative competence" was proposed, understood
as the set of knowledge, skills and attitudes to understand and produce narrative
texts, digital storytellings and transmedia storytellings
2. Construction of the pilot instrument: the existing literature was reviewed to adequately
define the construct to be measured, and the items and the dimensional structure of
the construct were elaborated.
3. Content validation: the instrument was validated by means of expert judgment and
a qualitative application to education students. First, in relation to the expert
judgment, several judges independently evaluated the theoretically developed measurement
model, i.e., the clarity, coherence and relevance of the construct, the quality of
the wording of the items and their relevance for each subscale. These criteria were
evaluated with scores between 1 and 4. In total, eight judges with different professional
profiles participated in the activity: three specialists in communication, three specialists
in comparative literature, one in literary theory, and one in education. In addition,
four of them are of Peruvian nationality while the rest are of other nationalities:
Mexicain, Colombian and American. All of them hold a doctorate degree and have a postgraduate
degree in literature, communication and education.
Secondly, a qualitative application was carried out as a pilot test with the modifications
suggested by the experts' judgment. The purpose was to confirm that all the items
were correctly understood by the potential participants of the study.
43 students participated in the pilot test. The application was done through a self-administered
Google Forms, since as a consequence of the COVID-19 pandemic, the classes were conducted
virtually. After the application, no changes were made to the wording of the items,
since they were understood by the students.
In summary, the pilot sample was made up of university students from the Education
academic program. 30 women (69.08%) and 13 men (30.2%) from 18 to 37 years old participated
(M = 23.02, SD = 3.889), 83.7% were enrolled in the fourth year and 16.3% in the second,
third and fifth years. A Cronbanch Alpha of .930 was obtained in the total Scale (with
27 items), .787 in the Textual Narrative dimension; .874 in the Digital Narrative
dimension; and .942 in the Transmedia Narrative with 9 items in each of the three
dimensions, values that indicate the internal consistency of the instrument.
4. Instrument application to the sample (field test): this application was made through
a self-administered Google Forms. The questionnaire was sent to the students through
their institutional e-mail. An explanation of the objectives of the study, the informed
consent of the participants and the confidentiality of the information were included.
5. Estimation of psychometric properties: For the analysis of the psychometric properties
of the Scale, an exploratory factor analysis was performed on the total sample using
the maximum likelihood estimation and to ensure adequate representation of the items,
those whose factor loading was greater than .40 in any of the factors retained after
a varimax rotation were retained (; ).
6. After all these procedures, the final version of the Macronarrative Competence
Scale was obtained (See Appendix A).
Participants
The sample was non-probabilistic. A total of 883 students participated, 397 (45%)
women and 486 (55%) men, ages between 16 and 52 years with a mean of 19.88 years (SD
= 3.90). Regarding the academic characteristics of the sample, 620 (70.2%) students
belong to the social sciences (anthropology, arts, law, economics, education, literature
and linguistics, psychology, social work) and 263 (29.8%) students belong to the engineering
area (civil, electrical, industrial, mining, systems and mathematics) of a Peruvian
public university. Most of students are in the first year (69.2%) and the rest in
the second (8.6%), third (12.6%), fourth (6.3%) and fifth year (3.3%).
Procedure
Data were collected between May and October 2022. For the evaluation of narrative
competence, the Macronarrative Competence Scale was applied in Google Forms format.
The surveys were anonymous; no data were requested that would allow identification
of the participants. Participation was voluntary and informed consent was requested.
Instrument
The instrument was applied together with a brief sociodemographic questionnaire that
collects information on gender, age, professional school and year of study. Macronarrative
Competence Scale (final version after application to the pilot sample). The purpose
of the scale is to evaluate the self-perceived level of macronarrative competence
of university students. The scale comprises 27 items covering three dimensions of
macronarrative competence: textual narrative (9 items), digital storytelling (9 items)
and transmedia digital storytelling (9 items). A five-point Likert scale was used
(1 strongly disagree and 5 strongly agree). In this study a Cronbach's Alpha of .946
was obtained for the Total Scale, .869 for narrative competence, .905 for digital
competence and .917 for transmedia competence. The coefficients obtained with Cronbach's
Alpha are consistent and indicate optimal reliability.
Data analysis
For the estimation of inter-rater agreement, Aiken's V coefficients were calculated
for each of the items.
The data obtained in the field application were analyzed using the IBM SPSS Statistics
25 program. The psychometric properties of the scale were estimated through exploratory
factor analysis. Next, normality tests were performed using the Kolmogorov-Smirnov
test with a significance level = 0.05 with p-value; and corrected by .200 Lilliefors significance in the engineering
area. Normality was found in the sociodemographic variables sex and academic area.
Therefore, the parametric Student's t-test for independent samples was applied. To
measure the effect size of the differences by sex and academic area, Cohen's d was
applied: values of d ≥ .2, d ≥ .5 and d ≥ .8 represent a small, medium and large effect
size, respectively.
Results
Content validity
The aim of this study was to construct and validate a Macronarrative Competence scale.
First, evidence of the content validity of the instrument was obtained by judges'
criteria. Table 1 presents the judges' assessment of the four elements of content validity: clarity,
coherence, relevance, and pertinence. The 40 initial items of the scale are distributed
in three dimensions: items 1 to 17 correspond to textual narrative; items 18 to 31,
to digital storytelling; and items 32 to 40, to transmedia storytelling.
Table 1Inter-judge concordance results using Aiken´s V indices
N° item
Clarity
Coherence
Pertinence
Relevance
Agreeement
V Aiken
IC 95 %
Agreeement
V Aiken
IC 95 %
Agreeement
V Aiken
IC 95 %
Agreeement
V Aiken
IC 95 %
1
31
0.96
[0.62, 1]
31
0.96
[0.62, 1]
31
0.96
[0.62, 1]
30
0.92
[0.57, 0.99]
2
30
0.92
[0.57, 0.99]
31
0.96
[0.62, 1]
30
0.92
[0.57, 0.99]
30
0.92
[0.57, 0.99]
3
30
0.92
[0.70, 0.98]
32
1.00
[0, 1]
29
0.88
[0.69, 0.96]
28
0.83
[0.64, 0.93]
4
31
0.96
[0.62, 1]
32
1.00
[0, 1]
31
0.96
[0.62, 1]
31
0.96
[0.62, 1]
5
27
0.79
[0.55, 0.92]
30
0.92
[0.69, 0.98]
25
0.71
[0.46, 0.87]
26
0.75
[0.50, 0.90]
6
29
0.88
[0.53, 0.98]
30
0.92
[0.69, 0.98]
28
0.83
[0.59, 0.94]
28
0.83
[0.59, 0.94]
7
29
0.88
[0.64, 0.96]
30
0.92
[0.69, 0.98]
28
0.83
[0.59, 0.94]
27
0.79
[0.55, 0.92]
8
30
0.92
[0.57, 0.99]
32
1.00
[0, 1]
31
0.96
[0.62, 1]
31
0.96
[0.62, 1]
9
28
0.83
[0.59, 0.94]
31
0.96
[0.62, 1]
30
0.92
[0.57, 0.99]
29
0.88
[0.53, 0.98]
10
26
0.90
[0.56, 0.99]
28
1.00
[0, 1]
28
1.00
[0, 1]
28
1.00
[0, 1]
11
31
0.96
[0.62, 1]
32
1.00
[0, 1]
30
0.92
[0.57, 0.99]
30
0.92
[0.57, 0.99]
12
29
0.88
[0.64, 0.96]
31
0.96
[0.62, 1]
26
0.75
[0.55, 0.88]
27
0.79
[0.59, 0.91]
13
31
0.96
[0.62, 1]
32
1.00
[0, 1]
31
0.96
[0.62, 1]
31
0.96
[0.62, 1]
14
31
0.96
[0.62, 1]
31
0.96
[0.62, 1]
29
0.88
[0.53, 0.98]
29
0.88
[0.53, 0.98]
15
28
0.83
[0.59, 0.94]
29
0.88
[0.64, 0.96]
24
0.67
[0.47, 0.82]
25
0.71
[0.51, 0.85]
16
29
0.88
[0.64, 0.96]
31
0.96
[0.62, 1]
31
0.96
[0.62, 1]
31
0.96
[0.62, 1]
17
28
0.83
[0.59, 0.94]
32
1.00
[0, 1]
31
0.96
[0.62, 1]
30
0.92
[0.57, 0.99]
18
31
0.96
[0.62, 1]
31
0.96
[0.62, 1]
31
0.96
[0.62, 1]
30
0.92
[0.57, 0.99]
19
28
0.83
[0.59, 0.94]
32
1.00
[0, 1]
29
0.88
[0.69, 0.96]
28
0.83
[0.64, 0.93]
20
29
0.88
[0.64, 0.96]
32
1.00
[0, 1]
26
0.75
[0.55, 0.88]
23
0.63
[0.43, 0.79]
21
26
0.75
[0.50, 0.90]
31
0.96
[0.62, 1]
30
0.92
[0.57, 0.99]
28
0.83
[0.59, 0.94]
22
28
0.83
[0.59, 0.94]
31
0.96
[0.62, 1]
29
0.88
[0.64, 0.96]
28
0.83
[0.59, 0.94]
23
27
0.79
[0.55, 0.92]
30
0.92
[0.57, 0.99]
29
0.88
[0.69, 0.96]
27
0.79
[0.59, 0.90]
24
27
0.79
[0.55, 0.92]
30
0.92
[0.57, 0.99]
30
0.92
[0.57, 0.99]
28
0.83
[0.59, 0.94]
25
26
0.75
[0.50, 0.90]
31
0.96
[0.62, 1]
28
0.83
[0.49, 0.96]
25
0.71
[0.46, 0.87]
26
25
0.71
[0.46, 0.87]
32
1.00
[0, 1]
29
0.88
[0.53, 0.98]
28
0.83
[0.59, 0.94]
27
31
0.96
[0.62, 1]
32
1.00
[0, 1]
31
0.96
[0.62, 1]
31
0.96
[0.62, 1]
28
28
0.83
[0.59, 0.94]
30
0.92
[0.69, 0.98]
27
0.79
[0.59, 0.908]
26
0.75
[0.551, 0.88]
29
31
0.96
[0.62, 1]
31
0.96
[0.62, 1]
30
0.92
[0.57, 0.99]
30
0.92
[0.57, 0.99]
30
29
0.88
[0.64, 0.96]
31
0.96
[0.62, 1]
31
0.96
[0.62, 1]
31
0.96
[0.62, 1]
31
27
0.79
[0.55, 0.92]
30
0.92
[0.69, 0.98]
30
0.92
[0.69, 0.98]
29
0.88
[0.64, 0.96]
32
31
0.96
[0.62, 1]
31
0.96
[0.62, 1]
31
0.96
[0.62, 1]
31
0.96
[0.62, 1]
33
23
0.63
[0.39, 0.81]
27
0.79
[0.55, 0.92]
28
0.83
[0.59, 0.94]
26
0.75
[0.50, 0.90]
34
31
0.96
[0.62, 1]
31
0.96
[0.62, 1]
28
0.83
[0.64, 0.93]
28
0.83
[0.64, 0.93]
35
30
0.92
[0.57, 0.99]
32
1.00
[0, 1]
31
0.96
[0.62, 1]
31
0.96
[0.62, 1]
36
30
0.92
[0.69, 0.98]
30
0.92
[0.69, 0.98]
30
0.92
[0.57, 0.99]
29
0.88
[0.64, 0.96]
37
29
0.88
[0.64, 0.96]
30
0.92
[0.69, 0.98]
29
0.88
[0.64, 0.96]
29
0.88
[0.64, 0.96]
38
31
0.96
[0.6, 1]
32
1.00
[0, 1]
28
0.83
[0.64, 0.93]
28
0.83
[0.64, 0.93]
39
31
0.96
[0.62, 0.98]
32
1.00
[0, 1]
31
0.96
[0.62, 1]
31
0.96
[0.62, 1]
40
29
0.88
[0.64, 0.96]
31
0.96
[0.62, 1]
31
0.96
[0.62, 1]
31
0.96
[0.62, 1]
Note: p ≤ .05
The summary of the results of Aiken's V is shown in table 2. As can be seen the Aiken's V indices .91 in the textual narrative, .88 in the digital
storytelling and .90 in the transmedia storytelling show high agreement; but total
agreement was not reached among the judges, so the items that did not respond to the
content validity criteria were modified. The comments provided helped to improve the
wording and terminology used in some items; on the other hand, items were merged and
those that did not meet the content validity criteria were eliminated and others were
adapted according to the experts' observations. Finally, the total scale of the Macronarrative
Competence construct was composed of 27 items equally distributed in the three dimensions
of the scale (see Appendix A).
Table 2Summary of the results of Aiken´s V for the three dimensions and the total scale of
macronarrative competence
Clarity
Coherence
Pertinence
Relevance
Total
Textual narrative
0.90
0.96
0.88
0.88
0.91
Digital storytelling
0.84
0.96
0.89
0.84
0.88
Transmedia storytelling
0.89
0.94
0.90
0.88
0.90
Total
0.87
0.96
0.89
0.87
Exploratory factor analysis
Table 3 shows the results of the validity of the instrument. An exploratory factor analysis
of the Macronarrative Competence Scale was carried out.
The significance of the Bartlett Test ( = 16932.738, p < .001) and the Kaiser-Meyer-Olkin sampling adequacy measure (KMO
= .943) showed an adequate correlation between the items and good sampling adequacy,
respectively, evidencing the relevance of an exploratory factor analysis. As a result
of the exploratory factor analysis in the total sample, after a varimax rotation,
27 items were identified with a three-factor structure: textual narrative (items 1
to 9), digital storytelling (items 10 to 18) and transmedia storytelling (items 19
to 27). The set of retained factors explained 61.82% of the variance.
Table 3Results of the exploratory factor analysis. Structure matrix of the Macronarrative
Competence Scale
Factor
Item
Communality
Textual narrative
Digital storytelling
Transmedia storytelling
1
.555
.740
2
.585
.755
3
.522
.544
4
.614
.779
5
.557
.653
6
.622
.766
7
.613
.732
8
.606
.724
9
.558
.658
10
.556
.514
11
.571
.558
12
.650
.769
13
.599
.569
14
.578
.730
15
.642
.784
16
.557
.481
17
.555
.502
18
.615
.503
19
.617
.659
20
.577
.699
21
.664
.686
22
.660
.737
23
.664
.675
24
.703
.756
25
.747
.810
26
.771
.847
27
.733
.805
Differences by academic area and sex
Finally, differences by academic area and sex are explored. The means and standard
deviation are shown in tables 4 and 5. Significant differences were found, the results suggest that social science students
reported higher levels of narrative competence than engineering students, in the total
scale and in the three dimensions, with medium effect size in the total scale (0.4)
and in the digital narrative (0.47) and small effect in the textual storytelling (0.37)
and transmedia storytelling (0.2). Similarly, female students reported higher levels
of narrative competence than male students, on the total scale and on two dimensions,
with small effect size on the total scale (0.32) and digital storytelling (0.36),
and medium effect on the textual narrative (0.47). No significant differences by sex
were found in the transmedia storytelling.
Table 4Comparison of macronarrative competence and subdimensions according to academic area
Narrative competence
Social sciences
Engineering
t
p
Cohen's d
M
DS
M
DS
Textual narrativa
33.47
5.999
31.29
5.582
5.048
.000
0.37
Digital storytelling
28.23
7.371
24.71
7.584
6.436
.000
0.47
Transmedia storytelling
26.67
8.198
25.03
7.625
2.776
.006
0.2
Total scale
88.38
18.656
81.03
18.165
5.392
.000
0.4
Note: T test results asume equal variances for social sciences (n = 620) and engineering
(n= 263).
Table 5Comparison of macronarrative competence and subdimensions as a function of sex
Narrative competence
Women
Men
t
p
Cohen's d
M
DS
M
DS
Textual narrative
34.32
5.501
31.59
6.043
6.952
.000
0.47
Digital storytelling
28.66
7.513
25.98
7.469
5.304
.000
0.36
Transmedia storytelling
26.49
8.130
25.93
8.007
1.020
.308
Total scale
89.48
18.291
83.50
18.809
4.753
.000
0.32
Note: The t test results asume equal variances for sex: women (n = 397) and men (n
= 486).
Discussion and conclusions
The aim of this research was to develop and validate a scale to measure the self-perception
of the level of macronarrative competence of university students in three dimensions:
textual narrative, digital storytelling and transmedia storytelling. The proposed
scale was shown to be a valid and reliable instrument to measure self-perception of
macronarrative competence. The quantitative nature of the data allowed us to analyze
the psychometric properties of the proposed scale through content validation and,
subsequently, the reliability of the instrument.
The proposal of this instrument for measuring the self-perception of macronarrative
competence is pioneering in two ways, first because of its integrating nature of the
three levels (textual, digital and transmedia), and second because of its application
at the university level. It is also necessary to highlight that both narrative competence
and literary competence are fields that are just being explored at the higher education
level. It should not be forgotten that narrative competence is a valid means for the
development of communicative competence in general ().
Other studies have only been circumscribed to the textual level of narrative competence,
or more properly literary competence, such as the proposal by , who designed and validated a Literary Competence Battery (BCL) to measure literary
competence in adolescents, composed of three scales: Literary Concepts Scale (ECL),
Literary Procedures Scale (EPL) and Attitudes towards Literature Scale (EAL). Likewise,
other studies have related literary competence to other crucial aspects in education
such as the development of creativity. found that the relationship between literary competence and creativity is highly
significant.
Based on the findings obtained, it is necessary to rethink the approach to the teaching
of narrative and literary competence in general, since the presence of technology
in different areas of human life cannot be ignored, especially in the field of higher
education. found that transmedia storytelling technologies are not sufficiently employed in
literature-related subjects, especially in classical studies; they also found that
the study participants had expectations about the favorable use of multimedia and
trivia games, i.e., with a predisposition to the use of serious games and gamification.
Finally, the conception of the proposed instrument is congruent with theoretical proposal of an augmented competence in which the educational objectives
proposed by UNESCO and the learning of media use converge. Macronarrative competence
integrates other forms of storytelling beyond words and more in line with the use
of new technologies. The proposed scale can be used by teachers of any specialty,
mainly in the areas of literature, communication and education. The development of
macronarrative competence brings cognitive, communicative, motivational, social, etc.
benefits (). In future works, intervention programs will be applied to develop macronarrative
competence and the role of artificial intelligence in its development will also be
investigated.
Authors’ contributions
Rosa Núñez-Pacheco: Project administration; Conceptualization; Writing – original draft; Writing – review
& editing; Investigation; Resources.
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