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ISSN: 2992-7161  
ASSESSMENT OF STUDY HABITS  
AMONG YOUNG UNIVERSITY STUDENTS  
EVALUACIÓN DE LOS HÁBITOS DE ESTUDIO  
ENTRE LOS ESTUDIANTES UNIVERSITARIOS JÓVENES  
García Parada Ricardo  
TecNM/Instituto Tecnológico de Chihuahua II  
García González Héctor  
TecNM/Instituto Tecnológico de Chihuahua II  
Barraza Álvarez Alberto Guerrero  
TecNM/Instituto Tecnológico de Chihuahua II  
Holguín Beltrán José Roberto  
TecNM/Instituto Tecnológico de Chihuahua II  
Velázquez Nava Oscar Guillermo  
TecNM/Instituto Tecnológico de Chihuahua II  
| Received: 18/02/2026 | Accepted: 22/04/2026 | Published: 24/05/2026  
This work is licensed under  
an international  
Creative Commons Attribution 4.0.  
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Abstract-- This article evaluates the study habits of 44 first-semester engineering students using Ortega’s  
(2012) Study Habits Questionnaire. The quantitative study, grounded in a post-positivist paradigm,  
examines three dimensions: study methods, task completion, and exam preparation. Results show an  
overall mean of 1.82, classified as a medium-low level. The weakest dimension was exam preparation  
(M=1.79), with 45.5% of students never finishing topics before an assessment. Female students scored  
slightly higher than males, though without statistically significant differences. The study concludes that  
students tend to prioritize formal task completion over deep cognitive strategies, and recommends  
implementing psychopedagogical programs focused on time management, reading comprehension, and  
self-regulated learning.  
Keywords-- academic performance, higher education, study habits, self-regulated learning, university  
students.  
Abstract-- Este artículo presenta una evaluación de los hábitos de estudio de 44 estudiantes de Ingeniería  
del primer semestre mediante el Cuestionario de Hábitos de Estudio de Ortega (2012). El estudio emplea  
un análisis cuantitativo, un paradigma postpositivista, y se divide en tres dimensiones: los métodos  
empleados para estudiar para el examen o la finalización de la tarea. Esto arrojó una media agregada igual  
a 1.82, correspondiente a la categoría de nivel medio-bajo. La dimensión más débil fue la preparación  
para el examen (M=1.79), que representó el 45.5% de los estudiantes que nunca cubren los temas antes  
de una evaluación. Las mujeres lograron medias ligeramente más altas que los hombres, pero sin  
diferencias significativas. Nuestra conclusión es que los estudiantes parecen prestar más atención al  
cumplimiento formal que al afrontamiento con estrategias cognitivas profundas, y se ha propuesto  
incorporar programas psicoeducativos al plan de estudios actual con el fin de fortalecer la planificación  
del tiempo, la lectura comprensiva y la autorregulación del aprendizaje.  
Keywords-- hábitos de estudio, rendimiento académico, educación superior, autorregulación del  
aprendizaje, estudiantes universitarios.  
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INTRODUCTION  
International Background  
Study habits have been recognized as one of the most relevant predictors of academic performance in  
higher education worldwide. International research has consistently documented that the way university  
students organize, plan, and execute their study routines directly impacts their academic results, their  
retention in the educational system, and their professional development.A classic reference is meta-  
analysis by Credé and Kuncel (2008) utilizing data from 72,431 college students in N = 344 independent  
studies. Their research showed that inventories of study habits, skills and attitudes represent the  
academic success factor sometimes referred to as the "third pillar" of college admissions, in that this  
area has predictive power equal to standardized admission tests or high school grades. Specifically,  
motivation to study and study skills showed the highest relationships with GPA.  
Based on Jafari, Aghaei and Khatony (2019), in a cross-sectional study the researchers studied 380  
student of medical sciences from Kermanshah, Iran and found that most students hold a moderate-level  
study habits which was 81.3% while exhibiting a direct significant relationship to academic  
performance. This research illustrates the significance of assessing study habits prior to university entry  
as a predictor of student academic risk.  
A study among a cohort of 614 undergraduate students at a large public university in the USA explored  
associations between performance (grade point average) with five health behaviours and ten daily habits  
(Reuter and Forster, 2021). Significant associations were found between sleep quality, daily breakfast  
and other healthy behaviors, and GPA. This study adds to the understanding of strategic behaviour: it  
introduces a biopsychosocial aspect into learning.  
Biwer et al. (2024), The Role of Habits in the Self-Regulated Learning of First-Year College Students  
(Higher Education). Students often use shallow processing strategies, such as stark reviewing material  
and learning information a few days before an exam instead of deeper problem solving techniques like  
spaced repetition, even if they know the benefits of ultimately doing so. Not to mention what it does to  
create a habit inertia which is one of the main barriers to enhancing our achievement level.  
Research in CBELife Sciences Education by Walck-Shannon, Rowell, and Frey (2021) evaluated the  
relationship between study practices and performance among students enrolled in a college biology  
course. The authors found that both the time students spent studying and how they scheduled and used  
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their study periods contribute to great performance on assessments. The main finding was that more  
active strategies especially retrieval practice and spacing, access to their pre-enrichment skills —  
correlating with better grades regardless of academic preparation prior to enrichment.  
Finally, Rodríguez et al. Based on data from 2010 to 2020, Abar et al. Their findings showed that  
different executive functions and self-regulation strategies in learning correlate highly with most aspects  
of student well-being, providing further support for the value of using study habits as a global measure  
of college student development.  
Latin American Context  
Study habits are a special topic of interest when assessing the preferences of university students,  
especially in the context of Latin America where high drop-out rates characterize the region. Many studies  
have reported that between 40 and 70% of university students in Latin America don not complete their  
degree programs, with deficiencies in study habits being one of the most commonly identified explanatory  
variables.  
George-Reyes, Ruiz-Ramírez, Glasserman-Morales y Olarte-Arias (2023) comparó a estudiantes  
universitarios en México y otros en Colombia para conocer la forma de estudio que tuvieron frente a la  
transformación digital provocada por la COVID-19. Their results showed major transformations in  
academic habits focusing mainly on time management in virtual environments, self-learning, and digital  
technologies acting as mediators of study processes.  
In Peru, the study by Trigos-Tapia, Espinoza-Alvarado, and Céspedes-Chauca (2022), published in the  
Revista Herediana de Rehabilitación, assessed study habits among Occupational Therapy students using  
validated instruments. Results revealed the heterogeneous levels in time management, study environment  
and academic planning dimensions highlight early diagnostic assessments during their period of  
university education.  
A study by Salamea-Nieto and Cedillo-Chalaco (2021) in Ecuador's INNOVA Research Journal  
investigated the link between study habits and motivation to learn among college students. Their findings  
confirm that motivation relates more robustly with behaviors like completing the assigned work, paying  
attention during class, and managing time than other study habits; highlighting both affective and  
volitional constructs of student behaviors by Latin American university students.  
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In Colombia, Mondragón et al. (2017) investigated the relationship between study habits and academic  
performance among mechanical engineering students, finding significant correlations between the two  
variables. This study, published in the Colombian Journal of Advanced l Technologies (RCTA),  
highlights the predictive value of study habits in exact sciences programs, where cognitive load and  
sustained practice are particularly decisive factors.  
Relatives, on the literature review, Carrillo Vargas and Bravo Bastidas (2022) performed a systematic  
review of studies about pattern study and academic performance in Latin American college students.  
Their findings highlight that, although existing research in the region predominantly supports a link of  
good study behaviour with favourable academic achievement, there is a concerning deficiency of  
longitudinal studies and validated instruments for Latin American samples.  
Chilca (2017) published a study with university students from Lima, Peru where she reported an  
association between study habits, self-esteem and academic performance (R = 0.503). The results,  
published in the journal Propósitos y Representaciones of the Universidad San Ignacio de Loyola also  
indicated that around 50% needed to change their study strategies due to inadequate ones, which  
emphasizes the need for intervention programs baseline on students habits of study at their admission to  
university.  
Study Objective  
The overall objective of this study is to evaluate study habits among college students, identifying the  
predominant patterns in their academic routines and their association with academic performance.  
Rationale for the Study  
The assessment of study habits among university students represents a line of educational research of  
high theoretical and practical relevance. From an academic perspective, study habits have been  
recognized as one of the most robust predictors of performance in higher education, according to evidence  
accumulated in the international and Latin American literature (Credé & Kuncel, 2008; Chilca, 2017).  
However, their systematic and contextualized study remains insufficient in many university systems  
across the region.  
From a practical perspective, a deep understanding of how university students study enables higher  
education institutions to design psycho-pedagogical intervention strategies aimed at reducing failure rates  
and dropout rates. In Latin America, where university dropout rates range from 40% to 70% (Carrillo  
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Vargas & Bravo Bastidas, 2022), having precise diagnostic s on study habits at the start of the university  
journey can serve as a high-impact preventive tool.  
On the other hand, the COVID-19 pandemic and the accelerated transition to online and blended learning  
modalities have significantly transformed the conditions under which students carry out their studies  
(George-Reyes et al., 2023). This context calls for new assessments that update the diagnosis of study  
habits in the post-pandemic era and consider the implications of digital environments on self-regulated  
learning.  
Finally, this study is justified from the perspective of educational equity. The literature indicates that  
deficits in study habits affect students from different socioeconomic backgrounds and academic origins  
in distinct ways (Reuter & Forster, 2021; Jafari et al., 2019). Identifying these patterns helps to highlight  
structural inequalities in access to quality higher education and to inform more inclusive institutional  
policies for academic support.  
Study Limitations  
Like all empirical research, this study acknowledges a number of limitations that must be considered  
when interpreting its results and extrapolating its conclusions:  
Cross sectional design: Since it is a cross sectional study, causal relationship with study habits and the  
academic performance cannot be established. The data only captures a snapshot of the participants’  
academic journey and provides no basis for observation of longitudinal changes.  
Self-reported: The assessment of study habits are self-perceived by students, exposing potential bias from  
social desirability. Participants might over report encouraged behaviours.  
Sample representativeness: The sample used for this survey may not be representative of all university  
student profiles since it is limited to one or a few institutions, majors and academic years. This limits how  
pervasive the results are to other contexts.  
Ecological validity: Academic performance data are collected from institutional records, and because  
grades reflect course-typical assessment factors for an instructor, they may also be poor proxies of the  
degree to which students are really learning.  
Unmeasured confounding variables: Unmeasured factors that might shape both study behaviours and  
performance such as paid employment, living environment, access to computer technology or family  
responsibilities.  
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Study context (COVID effects): Between study habits during-COVID vs what would be the comparative  
studies in person via pre-COVID settings, it is not possible to disentangle.  
DEVELOPMENT  
Research Paradigm  
This research falls within the post-positivist paradigm. This paradigm holds that, while an objective  
reality exists, it can only be apprehended imperfectly and probabilistically due to human limitations and  
the limitations of the phenomenon itself (Ramos, 2015). Furthermore, it is grounded in critical objectivity  
and the use of rigorous methods to test the proposed hypotheses (Guba & Lincoln, 1994).  
Research Approach  
The study is conducted using a quantitative approach. According to Hernández-Sampieri and Mendoza  
(2018), this approach allows for the collection of data to test hypotheses based on numerical measurement  
and statistical analysis, establishing patterns of behavior in a population. For their part, Creswell and  
Creswell (2018) note that quantitative design is ideal for examining the relationship between variables  
measured by standardized instruments.  
Participants  
Non-probabilistic convenience sampling was used. The sample consisted of 44 college students, with  
the following distribution by gender:  
Men: 25 (56.8%)  
Women: 19 (43.2%)  
Instrument  
The study uses a Study Habits Questionnaire, originally developed by Ortega (2012). This instrument  
was designed to quantitatively assess the intellectual and behavioral routines that students apply in their  
learning process.  
1. Structure and Dimensions  
The questionnaire organizes the assessment into three key dimensions that encompass a set of specific  
indicators:  
Study habits: Assesses techniques such as underlining, using a dictionary for unfamiliar terms,  
reading comprehension, memorization, consistent review, and specific planning for assessments.  
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Task completion: Focuses on the student’s ability to summarize, respond with understanding,  
prioritize order and presentation, seek external support (peers, teachers, or family), and organize  
time and tasks according to their difficulty.  
Exam preparation: Measures advance time management, selection of relevant content, and  
effectiveness in completing the studied topics.  
2. Grading System  
The instrument uses a Likert-type rating scale with three frequency levels, which allows for categorizing  
the intensity of the habit in the student:  
1. Never (1 point)  
2. Sometimes (2 points)  
3. Always (3 points)  
3. Application and Scope  
In this study, the questionnaire was administered to a sample of 44 first-semester engineering students.  
Its purpose was to establish the correlation between these habits and academic performance, which was  
measured in a complementary manner through grade reports and assessment records for the school year  
Procedure  
1. Ethics and Recruitment Phase: Informed consent was obtained from participants, guaranteeing  
anonymity and the strictly academic use of the data.  
2. Data Collection Phase: A study habits inventory was administered in digital format.  
Simultaneously, academic averages were collected from institutional records (with prior  
authorization).  
3. Organization Phase: The data were tabulated and cleaned to eliminate incomplete or atypical  
records.  
Data Analysis  
Data analysis was conducted using statistical software at two levels:  
Descriptive Analysis: Calculation of frequencies, percentages, means, and standard deviations to  
characterize the sample and the dimensions of study habits.  
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Inferential Analysis: Application of correlation tests (Pearson or Spearman) to determine the  
relationship between habits and performance. For comparisons by gender and field of study, tests  
of mean differences such as Student’s t-test or ANOVA were used.  
Data Analysis  
Sample Description  
The study habits questionnaire, based on the instrument by Ortega (2012), was administered to a total of  
44 first-semester engineering students. The sample consisted of 25 men (56.8%) and 19 women (43.2%),  
constituting a representative group of students in the early stages of their university education.  
Table 1. Sample distribution by gender.  
Gender  
Men  
n
%
25  
19  
44  
56.8%  
43.2%  
100%  
Women  
Total  
Source: Author’s own calculations.  
Results by Dimension  
The results are presented organized according to the three dimensions of the instrument: Study Methods,  
Task Completion, and Exam Preparation. The rating scale used is a three-point Likert scale: Never (1  
point), Sometimes (2 points), and Always (3 points). For the interpretation of means, the following ranges  
are considered: values between 1.00 and 1.50 correspond to a Low level; between 1.51 and 2.25, Low-  
Medium; between 2.26 and 2.75, High-Medium; and between 2.76 and 3.00, High.  
Dimension I: Study Habits  
This dimension assesses the techniques students use during the process of reading and personal study,  
including underlining, using a dictionary, reading comprehension, memorization, review, and planning  
for assessments.  
Table 2. Study Habits Results.  
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Sometimes  
(2)  
Indicator  
Never (1)  
Always (3)  
Average  
Underline as you read  
15 (34%)  
20 (45%)  
12 (27%)  
10 (23%)  
18 (41%)  
16 (36%)  
22 (50%)  
18 (41%)  
24 (55%)  
25 (57%)  
21 (48%)  
20 (45%)  
7 (16%)  
6 (14%)  
8 (18%)  
9 (20%)  
5 (11%)  
8 (18%)  
1.82  
1.68  
1.91  
1.98  
1.70  
1.82  
Use a dictionary for unfamiliar terms  
Active reading comprehension  
Content memorization  
Constant review of the material  
Specific planning for assessments  
Source: Author’s own work.  
On this dimension the overall mean is 1.82, which means that it is at a low-middle level. The indicator  
most supported by appropriate habits is to memorize the content (M; 1.98), where (56.8%) of students  
“sometimes” and only (20.5%) “always.” On the other hand, having a dictionary for unknown words  
(M=1.68) and constant reviewing of the knowledge (M=1.70) were shown to be lowest mean averages in  
this dimension which indicates that most students seldom arrange these strategies. Specifically, multiple-  
choice practice and essay prompt generation was used never by 34% to 45% of students, indicating a  
major gap in their initial study routines.  
Dimension II: Task Completion  
This dimension explores how students approach academic tasks, considering the creation of summaries,  
content comprehension, presentation of work, seeking support, and time management.  
Table 3. Task Completion Results.  
Sometimes  
Indicator  
Never (1)  
Always (3)  
Average  
1.77  
(2)  
Prepares their own summaries  
17 (39%)  
20 (45%)  
7 (16%)  
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Answers based on understanding, not  
from memory  
13 (30%)  
8 (18%)  
22 (50%)  
26 (59%)  
9 (20%)  
1.91  
2.05  
Pays attention to  
neatness  
and  
10 (23%)  
presentation of assignments  
Seeks outside support (peers/teachers)  
14 (32%)  
19 (43%)  
23 (52%)  
20 (45%)  
7 (16%)  
5 (11%)  
1.84  
1.68  
Organizes tasks by difficulty and time  
Source: Author’s own calculations.  
Dimension II is also in the low-to-middle range, with a mean of 1.85. Attention to order and presentation  
of assignments was the item with the most positive response (M=2.05) 59.1% when asked  
“sometimes” and 22.7% "always." At the other end of the scale is completing tasks ordered in terms  
attention and time available (M=1.68), with 43.2%of students reporting they never do this item. Also  
weakly indicates the writing of personal summaries (M=1.77), because students just copy information  
without adequate processing or synthesis.  
Dimension III: Exam Preparation  
This dimension measures the preparation strategies students implement in anticipation of assessments,  
covering advance time management, content selection, completion of topics, and review of notes.  
Table 4. Exam Preparation.  
Sometimes  
Indicator  
Never (1)  
Always (3)  
Average  
(2)  
Plans ahead  
18 (41%)  
14 (32%)  
20 (45%)  
20 (45%)  
23 (52%)  
19 (43%)  
6 (14%)  
7 (16%)  
5 (11%)  
1.73  
1.84  
1.66  
Selects relevant content to study  
Finish the topics before the exam  
Review notes and materials before  
the exam  
12 (27%)  
24 (55%)  
8 (18%)  
1.91  
Source: Author’s own analysis.  
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Dimension III shows the lowest performance, with an overall average of 1.79, at the lower end of the  
low-to-medium range. The most critical indicator is completing the material before the exam (M=1.66),  
where 45.5% of students reported never achieving this. Advance time management (M=1.73) also showed  
notable deficiencies, with 40.9% of students never planning ahead. This picture reveals that most first-  
semester students improvise their exam preparation, lacking systematic strategies to ensure adequate  
coverage of the material.  
Overall Results and Comparison by Gender  
The following table consolidates the means obtained by dimension, disaggregated by gender, providing  
an overview of the group’s study habits.  
Table 5. Overall Results and Comparison by Gender.  
Women  
(n=19)  
Overall  
(n=44)  
Dimension  
Men (n=25)  
Level  
Low-  
Study Modes  
1.80  
1.85  
1.82  
intermediate  
Task completion  
Exam preparation  
1.83  
1.77  
1.88  
1.82  
1.85  
1.79  
Medium-low  
Low  
Medium-  
low  
OVERALL AVERAGE  
1.80  
1.85  
1.82  
Source: Author’s own calculations.  
Overall, the group’s mean is 1.82, placing it in the lower-middle range of the instrument. Women have  
slightly higher means than men across all three dimensions, with an overall mean of 1.85 compared to  
1.80, although this difference is not statistically significant and both groups fall within the same  
classification range. The dimension with the greatest relative strength is Task Resolution (M=1.85),  
followed by Study Methods (M=1.82), while Exam Preparation (M=1.79) is the area of greatest weakness  
for the group as a whole.  
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Discussion  
The findings of this study offer a critical assessment of the academic routines of first-semester  
engineering students. The overall mean of 1.82, which places the group at a low-to-medium level, is  
consistent with the regional issue described by Carrillo Vargas and Bravo Bastidas (2022), who associate  
deficits in study habits with high dropout rates in Latin America (40% to 70%). This initial level suggests  
that students are undergoing a complex transition to higher education without the necessary tools to cope  
with the cognitive demands of their program.  
One of the most relevant points is the gap between formal compliance and the depth of learning. While  
the highest-rated indicator was attention to the order and presentation of assignments (M=2.05), cognitive  
processing tasks, such as writing one’s own summaries (M=1.77), were deficient. This phenomenon is  
consistent with the results of Biwer et al. (2024) that describe a “habit inertia,” wherein students gravitate  
towards superficial processing strategieseven while recognizing they are not optimal: passive  
memorization, for example. In this study, for memorization, the means (M=1.98) obtained was prioritized  
among the highest scores, reinforcing what is called reactive learning and non-meaningful learning.  
Dimension III (Exam Preparation) was the area of greatest weakness (M=1.79), highlighting that 45.5%  
of students never finish the material before an assessment. This lack of foresight aligns with the  
observations of Walck-Shannon, Rowell, and Frey (2021), who argue that time allocation is more critical  
than the total time invested. The improvisation observed in the sample suggests that students have not  
adopted spaced repetition practices, a technique that, according to the literature, is key to academic  
success regardless of prior preparation.  
The low ability to organize tasks by difficulty and time (M=1.68) can be interpreted in light of the  
transformations documented by George-Reyes et al. (2023). Following the COVID-19 pandemic, self-  
management in virtual environments has become a greater challenge for college students. The results  
indicate that the group has not yet managed to autonomously regulate their study processes within the  
new digital ecosystem, which increases their academic risk.  
Finally, although women showed slightly higher means (1.85 vs. 1.80), the homogeneity in the low-to-  
medium level of both genders underscores the need for a widespread intervention. As Chilca (2017) points  
out, approximately 50% of university students need to modify their study techniques upon entering  
college. The data from this study justify the design of psycho-pedagogical programs that not only teach  
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reading techniques but also strengthen self-regulation and motivation, elements that Credé and Kuncel  
(2008) refer to as the “third pillar” of academic success.  
Conclusions  
Based on the results of the Study Habits Questionnaire (Ortega, 2012) administered to 44 first-semester  
engineering students, the following conclusions emerge:  
The general level of study habits for the group is low-to-moderate (M = 1.82), emphasizing that  
intervention strategies should be applied from the first months of the semester.  
Dimension III (Exam preparation) is the most important area, where the mean was significantly low  
(M=1.79), indicating that students do not have systematic study before assessments.  
Firstly for women, on all dimensions, the means are generally higher than that of men yet not statistically  
significant.  
Most students show a willingness to formally complete assignments but lack deep cognitive strategies  
that promote meaningful learning.  
It is recommended to design and implement a study habits development program that prioritizes the areas  
of time management, comprehensive reading techniques, and exam preparation strategies.  
References  
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Original Research Article  
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Collaborative Work Table  
Role  
Author(s)  
Conceptualization  
Methodology  
Software  
García Parada Ricardo  
García González Héctor, Holguín Beltrán José Roberto  
Barraza Álvarez Alberto Guerrero, Oscar Guillermo  
Velázquez Nava  
Validation  
García Parada Ricardo  
Formal Analysis  
Research  
García González Héctor, Holguín Beltrán José Roberto  
Barraza Álvarez Alberto Guerrero, Oscar Guillermo  
Velázquez Nava  
Resources  
García Parada Ricardo  
Data Curation  
García González Héctor, Holguín Beltrán José Roberto  
Barraza Álvarez Alberto Guerrero, Oscar Guillermo  
Velázquez Nava  
Writing - Preparation of the original  
draft  
Writing - Review and editing  
Visualization  
García Parada Ricardo  
García González Héctor, Holguín Beltrán José Roberto  
Barraza Álvarez Alberto Guerrero, Oscar Guillermo  
Velázquez Nava  
Supervision  
Project Management  
Fundraising  
García Parada Ricardo  
García González Héctor, Holguín Beltrán José Roberto  
Issue 4 | Vol. 4 No. 1 | January June 2026 |  
Página 303  
Original Research Article