Received:

1-III-2023

Accepted:

12-VI-2023

Published Online:

29-VI-2023

Terminal Efficiency, Lag and Dropout in Cohorts from 2007 to 2014 of Dental Students at the University of Costa Rica

Eficiencia terminal, rezago y abandono en las cohortes del

2007 al 2014 de estudiantes de Odontología de la

Universidad de Costa Rica

Cristina Castro-Sancho DDS, Mag¹; Adrián Gómez-Fernández DDS, Mag²;

Romain Fantin MSc³; Natalia Gutiérrez-Marín DDS, Mag⁴

1. Faculty of Dentistry, Universidad de Costa Rica, San José, Costa Rica.

https://orcid.org/0000-0002-1993-3076

2. Faculty of Dentistry, Universidad de Costa Rica, San José, Costa Rica.

https://orcid.org/0000-0003-2132-0137

3. Faculty of Dentistry, Universidad de Costa Rica, San José, Costa Rica.

https://orcid.org/0000-0003-2906-3438

4. Faculty of Dentistry, Universidad de Costa Rica, San José, Costa Rica.

https://orcid.org/0000-0002-1801-9856

Correspondence to: Dra. Cristina Castro-Sancho - cristina.castro@ucr.ac.cr

ABSTRACT: Determine the terminal efficiency, lag and dropout in the cohorts of students who entered the dentistry career at the Faculty of Dentistry at University of Costa Rica in the lapse 2007 to 2014. Data from 736 files were collected. The variables considered were sex, admission age, nationality, marital status, children, admission note, domicile and high school. The data was collected from the Student Application System, the physical files, and the data base from the Supreme Court of Elections of Costa Rica. Descriptive statistics, bivariate and multivariate analysis were made, which were implemented from two logistic regression models. 98% of the students were Costa Rican, 68% women, 79% entered according to the admission note, 43% entered with an age of 18 years or less, 50% came from a public school, 77 % resided in the Greater Metropolitan Area and 95% were single and remained without children. The average terminal efficiency was 6%; 46% of students have graduated with lag, 16% are still enrolled and 32% dropped out. Sex, age, admission note, and motherhood are sociodemographic variables that are associated with terminal efficiency and dropout. The average terminal efficiency in the cohorts from 2007 to 2014 in the courses at the Faculty of Dentistry University of Costa Rica was very low, almost half of the students graduated with lag and about a third dropped out the studies. The grade from the admission note seems to be a predictor of students’ academic behavior, higher grade had more chances of graduating and less likely to dropout.

KEY WORDS: Dental students; Dental schools; Academic performance; Educational measurement; Achievement; Dentistry.

INTRODUCTION

One of the main functions of universities is teaching, where students are the most important element, so it is essential to know what happens during their university stay; and for this purpose, educational indicators such as terminal efficiency, lag and dropout are useful instruments to measure the situation and develop strategies for improvement (1).

In Costa Rica, the VII Report on the State of Education for the year 2019 (2) indicates that at the level of public universities, in each cohort, between 49% and 55% of students manage to obtain a degree. More specifically, at the University of Costa Rica (UCR), regarding the students enrolled behind, the VI Report on the State of Education for the year 2017 (3) indicates that 24% of the students have not been able to complete the study plan. Studies in the established time, however, when studying their enrollment pattern it seems to indicate that there is a low risk of dropout. Additionally, the same report indicates that around 50% of active students with many years of having entered the university are profiled as dropouts. According to a publication by the United Nations Educational, Scientific and Cultural Organization, a cohort study of students from 2002 to 2018 at UCR revealed that graduation rates in the field of health do not exceed 35%, whereas for economics and education, the percentage is higher, around 50% (4).

Tracking educational indicators is closely related to the Policies of the University of Costa Rica 2016-2020 "Excellence and Innovation with Transparency and Equity," where article 3.1.1 states: "It will implement strategies and actions in the academic-administrative and budgetary fields, based on studies on academic performance, permanence, and dropout rates, to strengthen the support processes for the student population, aiming to improve compliance with the established deadlines for completing study plans, especially in the final graduation stage, with the purpose of increasing graduation rates in all undergraduate and graduate programs, particularly in those with low indicators" (5). This monitoring is also linked to generating inputs aimed at promoting the self-assessment of a university career, improving quality, and favoring education accreditation. In this regard, the Degree in Dentistry at UCR has been accredited by the National Higher Education Accreditation System since 2009 (6). This accreditation certifies the quality of the program, the constant pursuit of academic excellence, and the need for ongoing comprehensive self-assessment (7).

Only one research has been carried out at the Faculty of Dentistry of the University of Costa Rica (FD UCR), in which some educational indicators of the 2010 cohort were established (8). Follow-up was carried out on 94 student files, from March 2010 to March 2020, the results indicate a terminal efficiency of 8.5%. It was determined that 50% of the students graduated with lag semesters (taking from one to eight semesters longer), and 9.5% remained as active dentistry students. Additionally, 32% of the students dropped out. This research is proposed due to the limited information on educational indicators, which allow visualizing student progress and developing strategies to increase university performance, with the objective of determining terminal efficiency, lag, and dropout in the cohort of students who entered the Dentistry career in the period 2007 to 2014 at the Faculty of Dentistry of the UCR.

METHODOLOGY

PARTICIPANTS

This research is a descriptive, longitudinal, and retrospective follow-up study of the cohorts of students from the FD UCR who entered from 2007 to 2014. These eight cohorts were studied until December 2021. The inclusion criteria were the records of the students who entered the UCR Dentistry career during the years 2007 to 2014 by admission grade or by transfer from another university career and whose information was available in the Student Application System (SAE by its acronym in Spanish). The exclusion criteria were the file with incomplete information.

DATA COLLECTION

The following variables were obtained from SAE: sex (male or female), age of admission to the FD UCR (age in completed years), nationality (Costa Rican or foreign), place of origin (within the Greater Metropolitan Area (GAM by its acronym in Spanish) or outside the GAM), school of origin (public, private, subsidized by maturity or school abroad), UCR admission exam grade, student status (graduated, lag or dropped out), amount of semesters that he was enrolled in the UCR Dentistry course and the entrance note (Q1, Q2, Q3 and Q4). Regarding the grade, people were categorized based on the quartiles of the first admission grades, for each year of admission: Q1 corresponds to the people who entered with a low grade (compared to the other people who entered the same year), Q4 with a high note.

The profile authorized to review the SAE does not allow access to the files of individuals who present either of these two conditions: people who obtain the note to enter the career but do not consolidate their enrollment or students who are studying postgraduate studies at the UCR.

To determine the terminal efficiency (number of students who finish a university degree in the time officially established in the study plan with which they entered the degree for the first time) (7-9), the students who finished the degree in dentistry in 12 consecutive school semesters were counted. To establish the students with lag, those who took longer than the time stipulated in the study plan to pass all the subjects and requirements of a degree (8-10) were registered, and to establish university dropouts, students who abandoned the academic program were identified, presenting more than 3 years without enrolling in any course (7, 9, 11).

The variables of marital status (single or married at admission) and having children (yes or no during all the years of study) were obtained from the digital documents of the Supreme Electoral Tribunal of Costa Rica, that contain the data from the Civil Registry.

STATISTIC ANALYSIS

Data were entered into an Excel database (Microsoft, Inc., Redmond, WA, USA), reviewed and corrected for inconsistencies to be analyzed. Descriptive statistics were performed establishing the absolute and relative frequency of the variables, as well as measures of central tendency and variability.

All the analyzes were developed in the Stata@14® program.

The dependent variable of the analysis was the status of the student, divided into three categories: graduated, dropped out, currently enrolled.

The independent variables were sex, age of admission, note of admission, transfer, having children, marital status, school, address, nationality.

The bivariate analysis presented the distribution of the dependent variable as a function of each independent variable. The current semester of students who are still enrolled, and the last approved semester of students who dropped out were also presented. The multivariate analysis was implemented from two logistic regression models. A first model had as a dependent variable the fact of having graduated in less than 16 semesters. A second model had as a variable the fact of having abandoned the degree.

ETHICAL CONSIDERATIONS

The research was approved by the Scientific Ethics Committee of the UCR (CEC-84-2022).

RESULTS

Of the total of 778 files from the eight years of this study, 736 files with complete data were obtained. 98% of the students were Costa Rican, with a predominance of women (68%), 79% entered based on the admission exam grade, 31% obtained a grade that was located in quartile 1, 43% entered with 18 years of age or less, 50% came from a public school, 77% resided in the GAM and 95% were single and remained without children throughout the period they studied dentistry degree. There was a significant difference (p<0.01) in the current status of the career (graduated, lag, dropped out) between male and female, admission note, age of entry and having children (Table 1).

In the group of 584 students who entered according to admission grade, the terminal efficiency had an average value of 6%, 46% of the students graduated with a lag, 16% of the students continue studying the degree and 32% abandoned it. In the group of 152 students who entered by transfer from other majors, the average terminal efficiency was 8%, 37% of the students graduated with a lag, 19% remain in the major and 36% abandoned it (Table 2 and Table 3).

On average, 6% of the population graduated in 12 semesters and 34% of students did so in 16 semesters or less. 16% of the subjects presented lag in their studies; 73% of lagging students are in 9th and 10th semester. 32% of the students dropped out, the semesters with the highest percentage of dropouts were the first and the second (56%) (Table 4).

The main determinant of graduation in 16 semesters or less was the admission note to the UCR. 50% of people in quartile 4 (high grade) graduated in 16 semesters or less, against 21% of people who entered with a low grade (quartile 1). The difference remained significant (OR=3.93 [2.50-6.18], p<0.01) after adjusting for the other variables. Similarly, people without children and students who entered in the years 2013 and 2014 graduated more often in 16 semesters or less (Table 5).

The two main determinants of dropping out of the degree were gender and entrance grade. More men drop out of college (40%) than women (29%), and the difference remained significant after adjusting for the other variables (OR=1.59 [1.13-2.24], p<0 .01). People who entered with a grade in the first quartile dropped out more (41%) than people who entered with a grade in the fourth quartile (23%). There was also a difference regarding age and nationality: the higher the age of admission and being a foreigner, the greater the chances of dropping out; however, this difference disappears after adjustment (Table 6).

DISCUSSION

The results of this research show that the educational indicators in the Faculty of Dentistry of the UCR did not have considerable changes in reference to the pilot study carried out in 2021 (8), since the terminal efficiency is still very low, and the dropout rate is a third of all enrolled students.

Regarding the terminal efficiency, the results indicate that it does not exceed 10%, even when considering the two modes of admission to the degree: admission based on the admission grade, where the graduation efficiency was 6%, or transfer from another program, where the percentage was 8%. This is consistent with national results reported by Brenes (2005), where it is indicated that approximately 10% of students in state universities manage to graduate within the expected time according to the study plans of different programs. It also states that less than half of the students who enter a public university manage to obtain a degree within the same institution, unlike the private universities in the study, where approximately 70% of students successfully complete their programs (14).

Internationally, the data on terminal efficiency varies greatly for different university programs. At the University of the Autonomous Regions of the Nicaraguan Caribbean Coast, the Nursing Degree reported an efficiency rate of 82.68%, while in Education Sciences, it was 81.08%, in contrast, the Intercultural Communication program had a rate of 13.33%. The high percentages in Nursing and Education Sciences carrers are due to the majority of students already working in the same field of study, so their degree represents better salary opportunities and job offers, which accelerates the graduation process (15). In Mexico, at the Instituto Tecnológico de Campeche, the area of Economic-Administrative Sciences reported a terminal efficiency of 26.6% (16), while in Nutrition, it was 68% (17). The Civil Engineering and Engineering and Technology programs had terminal efficiencies of 57.1% and 44.8%, respectively (18), and at the Universidad Juárez Autónoma de Tabasco, the Chemical Engineering degree presented 19.59% (19).

In a study conducted in Costa Rica, evaluating the terminal efficiency of different programs with cohorts from 2000 to 2004, Civil Engineering career obtained the lowest terminal efficiency rate (0.42), while Medicine showed the highest rate (1.03) (14), however, in 2019, a private university reported a terminal efficiency rate of 29.9% for the Medicine program (20).

Within the literature reported in other Dental Schools, a study of the 2000 cohort of students enrolled in the dentistry degree at the University of Panama revealed a terminal efficiency rate of 0% and an average duration of seven years for completing the program, which is two years longer than the established study plan (11). In the Faculty of Dentistry at the National University of La Plata, the terminal efficiency reported for the years 2001 and 2010 ranged between 15 and 20% (21); while, in the 2010 cohort in the dentistry degree of the Universidad Juárez Autónoma de Tabasco, a higher percentage of students (35%) managed to graduate within the designated time frame of the study plan (22). The highest graduation efficiency rate was reported at the Faculty of Dentistry of the University of the Republic, with a rate of 39% (23).

Regarding the students who managed to graduate in 16 semesters (2 years more than the stipulated study plan) or less, age, admission exam score, and maternity were variables that showed significant differences. In terms of age, younger students had a higher graduation percentage compared to their older counterparts. This aligns with the findings of Rodríguez and Zamora, who indicate that students entering higher education at 20 years old or younger have a higher survival rate (24). On the other hand, students with higher scores in the admission exam had a higher graduation rate. These findings partly support the suggestion made in the VI State of Education Report 2017 (3), which mentions that the average score on the admission test seems to be associated with the likelihood of a student successfully graduating, although further research in this regard is necessary.

In relation to motherhood, the students with this condition had lower terminal efficiency than their childless peers. This situation has also been reported in students from the Autonomous University, Mexico (25). It has been shown that maternity in university students decreases academic performance and generates a greater effort on the part of the students since they must change their study dynamics to fulfill their academic and maternal duties, and sometimes, these students can also present symptoms of stress, anxiety and depression (26-28).

Regarding student academic delays, the majority of students in this situation are in their 9th and 10th semesters, which are the year when most clinical courses are offered. Repeating courses multiple times is a significant cause of academic delays and dropout rates (20). Seara mentions another important cause of delays, which is “intentional academic lag” or “partial enrollment” (29), that occurs when some university students choose not to enroll in all the courses of a given semester. This phenomenon could be applicable to the Dentistry program, as clinical courses represent a significant workload for students, involving not only administrative logistics but also substantial academic components (8). This academic delay often persists in the final years of the program because individuals decide to continue, even if they take fewer courses. This decision is often influenced by the high economic cost associated with abandoning their studies, considering the substantial investment made in years of study (29).

An important aspect is that very few students who entered in 2013 and 2014 graduated with 16 semesters or less. This may be because 32% of the courses taught by FD UCR were canceled in 2020 due to the COVID-19 pandemic, these courses could not be virtualized due to their high content of clinical or laboratory practices (30).

Regarding dropout, almost a third of the students did not continue their degree, a very high percentage if compared to a study carried out on dentistry students at universities in Peru, where dropout was 5.63% (31). In our research, the dropout of the university degree occurred in a higher proportion when the students were in the 1st and 2nd semester of the curriculum. These data are related to what was reported in the VI Report on the State of Education (3), where it is mentioned that 45% of individuals who have not graduated from the UCR are early dropouts who left their studies in the initial semesters of the curriculum. This situation occurs at a general level in universities, since during the initial semesters, the student must go through a process of social and academic adaptation which can be very overwhelming for some subjects. The situation can also arise that students have wrong expectations about the conditions of academic and student life. Sometimes, the transition to university can involve a change in the place of residence of students who must leave home, causing more responsibilities and less time for study (29, 32).

The dropout of the studies had a statistically significant difference that was not maintained after making the final adjustment in relation to the sex, the entrance grade, age and nationality of the students, however, we consider it important to refer to these variables. The abandonment of the studies had a statistically significant difference in relation to the sex, the admission note, age and nationality of the students. Regarding sex, men dropped out more, a situation that differs from a cohort study of all students who entered the UCR between 1993-1996, where men and women dropped out similarly (33). However, a study carried out at the School of Dentistry of the Autonomous University of Nuevo León reported that women showed better grade averages than men, which could influence their permanence in the university (34). In other fields of study, such as Design at the University of Buenos Aires in Argentina, a study demonstrated that the dropout rate among women is lower than that among men. This can be attributed to learning styles, as it has been shown that women outperform men in using deep learning strategies, task evaluation, effective time management, and seeking help (35).

Regarding the admission note, the students with the lowest grades dropped out more. This result is inversely related to terminal efficiency, which indicates that a high grade in the admission exam could indeed predict that the student will have more chances of successfully completing a university degree and not dropping out.

In relation to age, older students had a higher likelihood of dropping out of the program. The results of other studies regarding this variable are diverse: some studies do not show a significant difference (36, 37), while others do demonstrate that as the student's age increases, the risk of dropping out decreases (26, 38, 39).

The nationality variable has been reported less in relation to educational indicators. In this research, nationality had a positive association with the dropout condition, being a foreigner presented more chances of not completing the degree. In a study with university students in Spain, it indicates that foreigners had a higher dropout rate (40); and a similar situation was reported in another study carried out in an argentine university where the academic performance of foreign students was lower, attributable to adaptation problems (41).

Among the strengths of this study is the methodology used, which involved tracking cohorts of Dentistry students from 2007 to 2014. A total of 736 complete records were obtained and analyzed until December 2021. In these eight generations of students, a significant variety of covariates were examined, which allowed for model adjustments and reduced bias in the results.

Another strength of this study is that it establishes, for the first time, a statistically significant relationship between certain sociodemographic variables and graduation efficiency, academic delays, and dropout rates. These findings will be valuable in generating strategies aimed at improving these educational indicators for the benefit of the student population.

One limitation that likely contextualized the results of this study was the COVID-19 pandemic. The FOd UCR experienced closure on March 11, 2020 (42). When the pandemic reached Costa Rica, academic authorities immediately urged the transition to online learning for ongoing courses in the first semester of 2020. However, 32% of the courses offered by the Faculty were deemed unviable for virtualization (30) due to their practical nature. This led to many students falling behind in their studies and several dropping out of the program.

In the future, there are plans to investigate the etiology of academic delays and dropout rates, as well as to identify which courses in the Dentistry curriculum at the UCR Dental School have the highest failure rates. Additionally, an evaluation will be conducted to determine if the data align with the cycles in which more students drop out of the program.

CONCLUSION

The average terminal efficiency in the cohorts from 2007 to 2014 in the courses at the Faculty of Dentistry University of Costa Rica was very low, almost half of the students have graduated with a lag, 16% are still enrolled, and close to one-third dropped out of their studies. The admission exam score appears to be a predictor of students' academic performance: higher scores correlate with higher chances of graduation and lower rates of dropping out. Sex, age, and motherhood are sociodemographic variables that are also associated with graduation efficiency and dropout rates.

AUTHOR CONTRIBUTION STATEMENT

Conceptualization and design: C.C.S., A.G.F. and N.G.M.

Literature review: C.C.S., A.G.F. and N.G.M.

Methodology and validation: C.C.S., A.G.F. and N.G.M.

Formal analysis: C.C.S., A.G.F. and N.G.M.

Research and data collection: C.C.S., A.G.F. and N.G.M.

Resources: C.C.S., A.G.F. and N.G.M.

Data analysis and interpretation: C.C.S., R.F., A.G.F. and N.G.M.

Writing and preparation of the original draft: C.C.S., A.G.F. and N.G.M.

Writing: review and editing: C.C.S., A.G.F. and N.G.M.

Supervision: C.C.S., A.G.F. and N.G.M.

Project administration: C.C.S., A.G.F. and N.G.M.

Acquisition of funds: Not applicable for this study.

REFERENCES

1. Peinado J., Jaramillo D. La eficiencia terminal del Centro de Investigación e Innovación Tecnológica. Rev Electron Investig Educ [Internet]. 2018; 20 (3): 126-134. Available from: https://doi.org/10.24320/redie.2018.20.3.1797%0Ahttps://redie.uabc.mx/redie/article/view/1797%0Ahttps://redie.uabc.mx/redie/article/view/1797/1687

2. Consejo Nacional de Rectores. Programa Estado de la Nación, Sétimo informe estado de la educación. [Internet]. 2019. Available from: https://estadonacion.or.cr

3. Consejo Nacional de Rectores. Programa Estado de la Nación, Sexto informe estado de la Educación. Vol. 1, Sexto informe estado de la educación. 2017.

4. Solórzano Salas J., Regueyra Edelman M.G., Esquivel Rodríguez C., Arias Mora F. (2020). Permanencia de la población estudiantil en la universidad a partir de un estudio longitudinal de cohortes en cuatro carreras. Revista Educación Superior y Sociedad (ESS), 32 (2), 100-133. https://doi.org/10.54674/ess.v32i2.252

5. Consejo Universitario. Universidad de Costa Rica. Políticas de la Universidad de Costa Rica 2016-2020 “Excelencia e Innovación con Transparencia y Equidad” publicada en La Gaceta Universitaria del 05/06/2015. Disponible en https://vra.ucr.ac.cr/wp-content/uploads/2020/06/politicas_institucionales_2016-2020.pdf

6. Filloy C., Howard M. El compromiso de mejoramiento de la Facultad de Odontología de la Universidad de Costa Rica con el Sistema Nacional de Acreditación de Educación Superior (SINAES). ODOVTOS. 2009; 11: 64-72

7. Zúñiga S., Camacho S. Referentes teóricos para un modelo de acreditación desde la evaluación y la gestión de la calidad. Revista Electrónica Educare. 2022; 26 (1), 274-292.Available from: https://dx.doi.org/10.15359/ree.26-1.15

8. Castro C. Eficiencia terminal, rezago y abandono en la cohorte del 2010 de estudiantes de Odontología de la Universidad de Costa Rica. Rev Cienc y Salud Integr Conoc. 2022; 5 (6): 75-84. Available from: https://doi.org/10.34192/cienciaysalud.v5i6.381

9. Zavaleta M., Cocon F., Pérez D. Comparativa de indicadores de la eficiencia terminal de programas educativos mediante un Sistema Estadístico de Indicadores Educativos. Rev Program Matemática y Softw [Internet]. 2018; 10 (2): 25-39. Available from: www.progmat.uaem.mx:8080/Vol10num2/vol10num2art4.pdf%0A

10. Cuellar O., Bolívar A. ¿Cómo estimar la eficiencia terminal en la educación superior? Notas sobre su estatuto teórico. Revista Educ Super [Internet]. 2006; 35 (3): 7-27. Available from: www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S0185-%0A27602006000300007&lng=es&tlng=es%0A

11. Núñez M., González E. Análisis de Cohorte para el Área de Salud: Deserción, rezago y eficiencia terminal al primer semestre del año 2000 al 2009. [Internet]. 2011. Available from: www.yumpu.com/es/document/read/14800779/analisis-de-cohorte-para-el-area-de-salud-universidad-de-panama

12. Domínguez D., Sandoval M., Cruz F., Pulido A. Problemas relacionados con la eficiencia terminal desde la perspectiva de estudiantes universitarios. Rev Iberoam sobre Calidad, Efic y Cambio en Educ [Internet]. 2013; 12 (1): 25-34. Available from: https://dialnet.unirioja.es/servlet/articulo?codigo=4654966

13. Hernández D., Vargas A., Almuiñas J. La importancia de la evaluación de la eficiencia académica en las universidades. Rev Cuba Educ Super [Internet]. 2020; 39 (1). Available from: http://scielo.sld.cu/scielo.php?script=sci_arttext&pid=S025743142020000100007&lng=es&tlng=es

14. Brenes Varela I. Deserción y repitencia en la educación superior universitaria de Costa Rica. San José, C.R. CONARE, OPES. https://hdl.handle.net/20.500.12337/2364

15. García Solórzano A. y Earl T. Eficiencia Terminal En Programas De Licenciatura, URACCAN Bilwi 1995-2005. Ciencia e Interculturalidad. 2012; 10 (1), 72-86. https://doi.org/https://doi.org/10.5377/rci.v10i1.814.

16. Legorreta L., Ortega A., Suárez R. y García S. Terminal Efficiency in Educational Programs of Economic-Administrative Sciences of the Technological Institute of Campeche. Journal-Republic of Colombia 2019; 5 (9), 8-14. Available from: https://www.ecorfan.org/republicofcolombia/journal/vol5num9/ECORFAN_Journal_Colombia_V5_N9_2.pdf.

17. Villanueva Echavarría J.R., Kantún Marín M.A., Rejón Lorenzo G.G., Villar Genesta G. Caracterización de la titulación de estudiantes universitarios del área de la salud. Un estudio de caso de México. Revista Universidad y Sociedad, 2022; 14 (3): 630-635. Epub 30 de junio de 2022.

18. Pérez González J.A. La eficiencia terminal en programas de licenciatura y su relación con la calidad educativa REICE. Revista Iberoamericana sobre Calidad, Eficacia y Cambio en Educación, vol. 4, núm. 1 2006, pp. 130-148

19. Domínguez, D., Sandoval, M., Cruz, F., y Pulido, A. Problemas relacionados con la eficiencia terminal desde la perspectiva de estudiantes universitarios. Revista Iberoamericana sobre Calidad, Eficacia y Cambio en Educación, 2014; 12 (1), 25-34. https://revistas.uam.es/reice/article/view/2862

20. Vanegas J., Sancho H. Análisis de cohorte: Deserción, rezago y eficiencia terminal, en la carrera de Licenciatura en Medicina y Cirugía de la Universidad de Ciencias Médicas. Rev Electrónica Educ. 2019; 23 (1): 203-24.

21. Coscarell N.Y., Seara S.E., Saporitti F., Medina MM. Orientación y nivelación de los ingresantes de la Facultad de Odontología de la UNLP. Sedici [Internet]. 2001; (2009): 12. Available from: http://sedici.unlp.edu.ar/bitstream/handle/10915/74220/Documento_completo.pdf?sequence=1

22. División Académica de Ciencias de la Salud. Reestructuración del Plan de Estudios de la Licenciatura en Cirujano Dentista. [Internet]. 2018. Available from: www.archivos.ujat.mx/2020/div-dacs/Cirujano-Dentista/PE-CIRUJANO-DENTISTA.pdf%0A

23. Collazo M., Seoane M., Hernández O. Perfil sociodemográfico y desempeños de los estudiantes de la carrera de Odontología (UdelaR). Odontoestomatología. 2011; XIII (18): 46-55.

24. Rodríguez M., Zamora J. Análisis de la deserción en la Universidad Nacional desde una perspectiva longitudinal [Internet]. 2014. Available from: repositorio.conare.ac.cr/handle/20.500.12337/829

25. Rodríguez-García C., Amador-Velásquez R., Mimbrera-Maturano A., Martínez-Ávila S., Santiago-Maturano M., Rodríguez-alarcón J. Problemáticas y consecuencias del embarazo y la maternidad en el rendimiento académico de estudiantes universitarias. Rev Enfermería del Inst Mex del Seguro Soc. 2021; 28 (3): 152-8.

26. García A., Adrogué C. Abandono de los estudios universitarios: dimensión, factores asociados y desafíos para la política pública. Rev Fuentes [Internet]. 2015; (16): 85-106 Available from: http://dx.doi.org/10.12795/revistafuentes.2015.i16.04 85

27. García C. Embarazo, maternidad y rendimiento de estudiantes de la Escuela Profesional de Trabajo Social,Universidad Nacional de Trujillo, 2019 [Internet]. 2019. Available from: http://dspace.unitru.edu.pe/bitstream/handle/UNITRU/3728/huaman_steven.pdf?sequence=1

28. Vega E., Laguna K., Amante L. Mujer, Estudiante y Madre: Desafíos De La Maternidad En Mujeres [Internet]. Vol. 1. 2017. Available from: http://dspace.unitru.edu.pe/bitstream/handle/UNITRU/3728/huaman_steven.pdf?sequence=1

29. Seara S., Medina M., Coscarrelli N., Conte C. Implementación de Estrategias para favorecer el ingreso y la permanencia de los estudiantes [Internet]. Vol. 1. 2018. Available from: http://sedici.unlp.edu.ar/handle/10915/72760

30. Chavarría D., Gómez A., Dittel C., Montero M. E-Learning in Dental Schools in the Times of COVID-19: A Review and Analysis of an Educational Resource in Times of the COVID-19 Pandemic. ODOVTOS. 2020; 22 (3): 69-86.

31. Heredia M., Andia M., Ocampo H., J. R.-C., Rodríguez A., Tenorio C., et al. Deserción estudiantil en las carreras de ciencias de la salud en el Perú. An Fac med. 2015; 76: 57-61.

32. Medina M., Gaytán C. Factores y significados de la deserción escolar en el nivel superior. Caso: Facultad de Odontología de la UACH. Rev Electrónica Cient Investig Educ. 2018; 4 (1): 515-25.

33. Abarca A., Sánchez M. La deserción estudiantil en la educación superior: el caso de la Universidad de Costa Rica. Rev Electrónica Actual Investig en Educ. 2005; 5: 1-22.

34. Salinas Quiroga M.D., González Salazar F. Factores asociados al rendimiento escolar en estudiantes de odontología Los estudiantes que trabajan. Univ Autónoma Nuevo León. 2019; 135-247.

35. Noriega Biggio M., Maris Vázquez S., Maris García, S. Deserción en Estudiantes de Nuevo Ingreso a Carreras de Diseño: El Caso de la Universidad de Buenos Aires, Argentina. Actualidades Investigativas en Educación, 2015; 15 (1), 341-364. http://www.scielo.sa.cr/scielo.php?script=sci_arttext&pid=S1409-47032015000100015&lng=en&tlng=es

36. Piratoba B., Barbosa O. Factores de deserción de los estudiantes en la Facultad de Enfermería de la Universidad de Ciencias Aplicadas y Ambientales U.D.C.A durante el período 2009-2010-I 2011. Rev UDCA Actual y Divulg Cient [Internet]. 2013; 16 (2): 553-62. Available from: http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0123-42262013000200031&lng=en&nrm=iso&tlng=

37. González-Ramírez T., Pedraza-Navarro I. Variables sociofamiliares asociadas al abandono de los estudios universitarios. Educ Siglo XXI. 2017; 35 (2 Julio): 365.

38. Lopera C. Determinantes de la deserción universitaria en la Facultad de Economía de la Universidad del Rosario. Borradores Investig [Internet]. 2008; 95: 1-41. Available from:http://www.urosario.edu.co/FASE1/economia/econ_inve_publicaciones_3.htm

39. Castaño E., Gallón S., Gómez K., Vásquez J. Análisis de los factores asociados a la deserción estudiantil en la Educación Superior: un estudio de caso. Rev Educ. 2008; 345 (345): 255-80.

40. Sánchez J. Modelos predictivos para el estudio del abandono en centros universitarios. 2014. https://oa.upm.es/31205/1/PFC_JESUS_SANCHEZ_SANTAMARIA.pdf

41. Fazio M. Incidencia de las Horas Trabajadas en el Rendimiento Académico de Estudiantes Universitarios Argentinos. Econstor [Internet]. 2004; 10. Available from:http://sedici.unlp.edu.ar/handle/10915/3543

42. Dittel Jiménez C. El reto de virtualizar contenidos en cursos clínicos en la enseñanza de la odontología: desafíos en tiempo de pandemia. La tecnología como eje del cambio metodológico. 2020; p. 107. Available from: https://hdl.handle.net/10630/19862