Academic Adaptation of Students with a History of Grade Repetition

Adaptação Acadêmica de Estudantes com Histórico de Repetência

Abstract

The study aimed to compare repeating and non-repeating students concerning the academic self-efficacy and academic adaptation variables and to verify how the social support and self-efficacy variables can predict the adaptation to Higher Education of students who have a history of reproval. Participants were 644 students, divided into those with a history of repetition or not. The Mann-Whitney test was used for group comparison and multiple regression analysis to investigate the prediction hypotheses. Higher scores in academic adaptation and self-efficacy in Higher Education were observed in non-repeating students. The study emphasizes the importance of providing resources aimed at the most vulnerable populations in the academic environment, including repeating students.

Keywords:
self-efficacy; social support; grade repetition; higher education

RESUMO

O estudo teve como objetivo comparar estudantes repetentes e não repetentes em relação às variáveis apoio social, autoeficácia acadêmica e adaptação acadêmica e verificar o quanto as variáveis apoio social e autoeficácia são capazes de predizer a adaptação ao ensino superior de estudantes que apresentam histórico de reprovação. Participaram 644 estudantes, divididos em estudantes com histórico de repetência ou não. Foi utilizado o teste de Mann-Whitney para comparação de grupos e análise de regressão múltipla para investigar as hipóteses de predição. Como resultados, foram observados maiores escores de adaptação acadêmica e a autoeficácia na formação superior em alunos não repetentes. Conclui-se enfatizando a importância de proporcionar recursos voltados para as populações mais vulneráveis no ambiente acadêmico, incluindo-se os alunos repetentes.

PALAVRAS-CHAVE:
autoeficácia; apoio social; fracasso escolar; ensino superior

The entrance into Higher Education is marked by the confrontation of challenging situations that provide personal and interpersonal development. The trajectory that precedes the beginning of the university experience requires investment of time, energy, and material resources, already demanding the dedication of students who aspire to pursue higher education. It has been affirmed that, upon entering university, adapting to the university context requires dedication and seriousness to achieve academic goals (Sahão & Kienen, 2021), continuing a path that requires effort from the student.

Considering that entering Higher Education requires specific skills from students, such as good performance or maturity for career choice, competition to occupy the university environment is a reality. Faria and Almeida (2021) stated that greater student involvement in academic tasks, greater autonomy, and responsibility for learning are expected. In this context, the authors consider that the democratization process has expanded access to Higher Education places and ensured the entry of students of different conditions and profiles. With the increase in the diversity of this population, the university public changed, characterizing a new profile of students from low-income families and first-generation students. However, the authors also indicate that many of these students enter without sufficient personal skills and resources to respond to the demands related to academic performance, organization of the university routine, and personal and professional development. Therefore, there is a need for greater attention by institutions, teachers, and support services in this moment of interaction with the new context.

It should also be considered that the democratization of admission to Higher Education does not guarantee the permanence of the student or even the quality of the learning processes. In addition to students arriving at the university with a diversity of prior experiences, needs, and expectations, it is understood that adapting and developing competencies to achieve personal and professional fulfillment is a process that encompasses skills such as autonomy in managing studies or the personal and social success of the student in the university environment (Casiraghi et al., 2020).

Given this configuration, challenges arise for institutions concerning the improvement of pedagogical projects and the importance of understanding the factors involved in adapting to the university (Almeida, 2007). In this context, Souza et al. (2016) emphasized that a greater commitment to the course and future career can be a reflection of the students’ greater confidence in their professional aspirations, provided by the investment and organization to achieve objectives. As a result, involvement in extracurricular activities allows for experience in different fields of work and a better understanding of the job market.

In an attempt to understand and explain the phenomenon of integration into the university and to promote healthier adaptation, some explanatory models have been proposed. Tinto (1975), when developing a model on academic and social integration, considered the academic domain to consist of the dynamics and characteristics existing in the new context. Among these, the regulation of performance, learning of curricular contents, understanding of the importance of these contents for professional formation, and knowledge of the guidelines of the chosen course were highlighted. The social domain included satisfaction with interpersonal relationships with peers and those who make up the university context and participation in curricular and extracurricular activities.

In the model proposed by Almeida (2007), the skills of the student and the teacher, and the specific characteristics of the academic context were highlighted. Among the skills valued by students, the author emphasized the knowledge and content acquired during High School Education, cognitive and intellectual skills, and the student’s perception of their abilities in terms of performance and self-regulation of behavior. These characteristics can promote motivation, learning, and academic and social integration.

In an attempt to understand the difficulties of students in Higher Education, Casanova et al. (2020) investigated those related to the academic adaptation of students in the first year of Higher Education. The results indicate a greater concern with the difficulties in adapting to the institution and the interpersonal relationships on the part of the students. After a few weeks, these difficulties seem to decrease in comparison to the self-assessment made soon after admission, revealing an overvaluation of the difficulties they will potentially face. Along with this, the students tended to identify more difficulties related to their learning, underestimating the difficulties in this domain or overestimating the resources and skills they had for the management of studying and academic preparation. The authors emphasized that the first weeks of class constitute a period of opportunity for highlighting the risk to performance and for academic adaptation. Accordingly, it becomes relevant to anticipate the need to provide differentiated tools and support to students.

Given the complexity of adapting to Higher Education the potential issues that arise from difficulties in adjustment and the heterogeneity of the student population, it is essential to investigate sets of variables that can contribute to understanding and developing intervention actions that consider the sociodemographic diversity of students. One of the relevant aspects of the student public is how cognitively and socially prepared they are to face the challenges that the university offers. In adolescence, school performance is an important indicator of adjustment and refers to the student’s ability to express the absorption of the content acquired during the teaching-learning process (Fernandes et al., 2018; Rosa et al., 2020).

According to D’Abreu and Marturano (2010), low school performance occurs when the student presents a result below the level expected for their age in grades or tasks, translated as the skills and potential of an individual. According to Almeida and Lopes (2020), personal, social, and cultural variables and their influences on academic performance have been scenarios of discussion in the scientific community at the national and international levels. With this in mind, the aim is to enable decision-making in education that focuses on planning and implementing interventions with students who have a history of academic “repetition”. According to Nunes et al. (2014), students with better school performance have less chance of grade repetition or dropping out. However, students with low school performance and low perception of support tend to be socially vulnerable and face more repetitions (Faria et al., 2020).

Considering this aspect, students who have a history of repetition need attention. These students are likely to arrive with deficits in acquired knowledge, study pace, perception of social support, and sense of self-efficacy, among other aspects, however, still manage to gain access to the university. They should be characterized in terms of their strengths and difficulties in academic adjustment. (Castillo-Sánchez et al., 2020). It should also be emphasized that students with low academic performance often experience motivational challenges along their learning path, as they face difficulties. However, they may not always be aware of their responsibility for their low performance and primarily attribute it to institutional factors. (Castillo-Sánchez et al., 2020).

Studies indicate that repetition during Fundamental Education is the result of multidetermined processes that include factors associated with the characteristics of students and their families, school practices, the community, and social, economic, and political aspects (Dazzani et al., 2014). Furthermore, it is a manifestation of grade repetition that culminates in adverse consequences for the socio-affective and academic development of students (Ingul et al., 2012). The study by Nunes et al. (2014) revealed that even when students have a positive perception of school, a significant number of them, particularly in public education, have experienced grade repetition at some point in their educational path. The conclusion is that low academic performance, due to difficulties in the educational process, can cause the student to have a lack of interest in studying, leading to repetition and even dropout. Consequently, this phenomenon may later constitute a risk to their human development (Ingul et al., 2012). Therefore, grade repetition can be a risk factor, as it affects students’ self-esteem, making them more fragile and prone to dropping out of school (Ingul et al., 2012).

With a history of grade repetition being considered a risk factor, the perception of social support and self-efficacy beliefs have been identified as protective factors for students (Achkar et al., 2017; Rock, 2020). These factors are linked to the perception of social support from the family, teachers, and the community as elements of protection in their contexts, as well as being associated with good school results (Juliano & Yunes, 2014). The perception of the ability to deal with academic requirements, called self-efficacy in Higher Education (Polydoro & Guerreiro-Casanova, 2010), also appears to be associated with better school performance, more motivation to learn, and better adaptation to Higher Education (Casiraghi et al., 2020; Rossi et al., 2020).

Social support is understood from the functions that a group of people performs in favor of an individual who is immersed in challenging and risky situations (Juliano & Yunes, 2014). They can be characterized by the presence of family members, friends, and/or neighbors, or even unknown people who play the role of help and support in moments considered critical (Squassioni & Matsukura, 2014). Antunes and Fontaine (2008) state that the perception of social support acts as a facilitator for the individual’s adaptation to changes during the transitions through the various levels of schooling. It results, therefore, in a sense of security and well-being in the academic context. Accordingly, the protective role played by family, friends, and teachers is crucial in helping students define and establish their goals and is an important predictor of good academic performance (Mishra, 2020; Tinajero et al., 2020).

The support network favors resilience processes in adolescents and young people by giving them greater confidence in themselves, generating protective factors perceived in their contexts (Santos et al., 2020). Social support operates by interacting with risk factors, enabling individuals to make different choices and providing a range of options to address daily social and emotional challenges, creating a situation of empowerment in individuals (Faria et al., 2020; Julian & Yunes, 2014).

Interpersonal and family problems and lack of help from the teaching body have also been identified as possible factors that influence reproval (Castillo-Sánchez et al., 2020). In the literature, the perception of social support from teachers is associated with higher self-esteem and better academic performance and with a lower chance of developing behavior problems (Fernandes et al., 2018). Social support from friends can also influence school performance by providing a sense of belonging to a group to which one can turn in times of difficulty, including problems that are not addressed by teachers (Dias et al., 2015). The low level of family support is presented as a factor associated with the history of school reproval and grade repetition, also relating to a lower level of autonomy of these students within the family (Batista et al., 2015).

In addition to the perception of social support, self-efficacy is another component that presents itself as a factor with a significant role in the academic experience and therefore should receive some attention. The concept refers to the individual’s beliefs in their ability to organize and perform actions required to achieve certain accomplishments (Bandura, 1997). In the academic context, it can be understood as the student’s reading of their abilities to acquire, apply and expand the content learned in the course, in addition to setting goals, planning the career, regulating actions in the learning process, and meeting deadlines, among other activities inherent to the academic environment (Polydoro & Guerreiro-Casanova, 2010). Self-efficacy plays an important role in academic adaptation, as it has been related to aspects such as greater academic satisfaction, the ability to regulate learning, greater academic motivation, and higher levels of academic performance (Lopes et al., 2020; Loricchio & Milk, 2012; Rossi et al., 2020; Santos et al., 2019).

The impact of social support is also present in academic performance (Menezes et al., 2020; Silva et al., 2014). Silva et al. (2014) stated that students with lower academic performance also have lower self-efficacy, which is an expected situation supported by the literature. This situation can be further exacerbated as a lack of belief in one’s academic potential can worsen performance and, consequently, weaken self-efficacy, creating a vicious circle. It should also be highlighted that the factors that can influence the reproval of university students can be diverse, however, some of the aspects most commonly identified by students are a lack of study time, effort, attention, organization, and previous knowledge, as well as difficulty in understanding new concepts, and poor attendance in classes (Castillo-Sánchez et al., 2020). Casiraghi et al. (2020) also associated many of these aspects with the ability to self-regulate learning, associated, in turn, with self-efficacy beliefs.

Self-efficacy beliefs are formed from four main sources: the subject’s experiences, vicarious experiences (observation), social persuasion, and physiological indicators, with effective behavior being the principal and strongest source of self-efficacy. That is, perceiving oneself as capable of performing a task or achieving a goal and achieving it is the best way for an individual to generate self-efficacy (Bandura, 1997; Pajares & Olaz, 2008). It is understood that students who perceive themselves as more self-effective are more susceptible to attempting more challenging tasks, setting more demanding goals, and maintaining higher levels of effort, focus, and persistence, even in times of difficulty (Santos et al., 2019). Conversely, it is worth considering the importance of these beliefs in individuals with histories of reproval and difficulty in school performance, understanding that these students accumulated negative experiences in their academic trajectory.

It can be conceived that both the perception of social support and the beliefs of self-efficacy are potentially significant protective factors in Higher Education. Both variables share the characteristic of the individual’s perception of their context (perception of support from close individuals or perception of their capabilities). It is important to note that students do not always recognize their weaknesses and, as a result, may struggle to seek support. This lack of self-awareness can further exacerbate their difficulties (Casiraghi et al., 2020). However, it is worth considering that students with a history of repetition may also present different perceptions compared to students who present better school performance.

Considering the negative impacts that a history of repetition can have on students’ lives, those who are in Higher Education and encounter this difficulty should be supported throughout their academic journey. Therefore, the present study aimed to compare university students with a history of repetition in the university considering the social support, academic self-efficacy, and academic adaptation variables and to verify the extent to which the social support and self-efficacy variables can predict the adaptation to Higher Education of students who have a history of reproval. The present study hypothesized that the social support and self-efficacy variables would be able to predict the adaptation to Higher Education and that non-repeating students would present higher scores in these variables compared to repeating students. Accordingly, it is expected that a better understanding of how significant the perception of social support and self-efficacy can be for access to Higher Education will contribute to healthier academic adaptation.

Method

Participants

The study included a sample of 644 students from public and private Higher Education Institutions (HEIs), from different undergraduate courses and periods, of both sexes, including 300 students with a history of repetition of at least one semester of the university course and 344 without a history of reproval. In the reproved students, the sample was composed of 34.66% male and 65.33% female students with a mean age of 26.17 (SD = 6.85) years. The students were mostly from public institutions (91.33%). Regarding the semester, 11.66% of the students were between the first and third semesters of the university, 31.66% were between the fourth and sixth semesters, and 56.55% were in the seventh semester or more. Among the non-repeating students, the sample was composed of 25.87% male and 74.12% female students. The mean age of these participants was 24.80 (SD = 7.54) years. Regarding the institution, 82.26% were from public institutions. Finally, 31.97% of the students were between the first and third semester of the university, 31.68% were between the fourth and sixth semester and 36.35% were in the seventh semester or more.

As inclusion criteria, participants had to be enrolled in a Higher Education Institution and be over 18 years of age. As the exclusion criterion, participants could not be students in the Distance Education format, due to the nature of the instruments used, which were constructed considering the face-to-face experience.

Instruments

The Sociodemographic Data questionnaire - aimed to collect information regarding gender, age, marital status, course enrolled, semester, and type of institution (public or private). At this time, students with a history of repetition were also identified.

The Higher Education Adaptation Questionnaire (Questionário de Adaptação ao Ensino Superior - QAES) (Araújo et al., 2014) has 40 items. It uses a five-point Likert-type scale, ranging from strongly disagree to agree strongly. The items are divided into five dimensions: Career Planning (F1 - eight items) - refers to the adaptation to the chosen course, such as satisfaction with the choice of course and competence for the course (α = 0.88), Social adaptation (F2 - eight items) - refers to the establishment of bonds, social support and friendship relationships (α = 0.86), Personal-Emotional Adaptation (F3 - eight items) - refers to feelings of physical and psychological well-being, and self-confidence linked to the university experience (α = 0.74), Adaptation to Studying (F4 - eight items) - refers to study habits, planning, perception of performance, and the learning process in the classroom (α = 0.75) and Adaptation to the Institution (F5 - eight items) - covers the institutional environment, including teachers, staff, services and living spaces, as well as the desire to remain until the conclusion of the course (α = 0.81).

The Higher Education Self-Efficacy Scale - (Escala de Autoeficácia na Formação Superior - AEFS) (Polydoro & Guerreiro-Casanova, 2010) is composed of 34 items in a 10-point Likert-type format, ranging from not very capable to very capable. The items are divided into five factors: Academic self-efficacy (F1 - nine items) - evaluates the student’s perception of their own ability to understand and demonstrate knowledge of the content provided in the course (α = 0.88), Self-efficacy in the regulation of training (F2 - seven items) - evaluates the student’s perception of their own competence to plan, make choices and build and achieve goals, self-regulating their behavior in the process of training and career development (α = 0.87), Self-efficacy in proactive actions (F3 - seven items) - covers recognition of the ability to take advantage of opportunities in training, promote institutional improvements and update knowledge (α = 0.85), Self-efficacy in social interaction (F4 - seven items) - assesses the student’s confidence in their own ability to establish relationships with teachers and colleagues, with academic and social purposes (α = 0.80) and Self-efficacy in academic management (F5 - four items) - assesses the student’s perception of their own ability to get involved, define and meet deadlines related to the university requirements (α = 0.80).

The Social Support Scale for University Students (Escala de Apoio Social para Estudantes Universitários, Soares, et al., in press) consists of 48 items in a five-point Likert-type format, ranging from strongly agree to strongly disagree. The items are divided into three factors: Academic Support (F1 - 31 items) - support perceived mainly in the experiences of the university, whether these include affective, study or material support (α = 0.98), Support for career decisions (F2 - nine items ) - perception of support directed toward the profession, career or more bureaucratic issues (α = 0.91) and family support (F3 - eight items) - perception of social support mainly from the family, about both affective and financial support (α = 0.97).

Data collection procedures

The Research Ethics Committee approved the research project. After its approval, the application of the Higher Education Adaptation Questionnaire (Araújo et al., 2014), the Social Support Scale for university students, and the Higher Education Self-Efficacy Scale (Polydoro & Guerreiro-Casanova, 2010) took place online through the Google Forms platform. The scales were disseminated, in a single form, to groups of university students from all over Brazil through social networks, in which they were asked to respond if they felt comfortable taking part in the research. Access to the instruments was preceded by an explanation of the study objectives and the risks involved. The application of the scales was preceded by the Sociodemographic Data Questionnaire to characterize the sample and identify which participants had been reproved. All procedures took place through the Google Forms platform.

Data analysis procedures

To verify the distribution of scores for each instrument, the mean and standard deviation for each group were calculated. Regarding the differences between the repeating and non-repeating groups, the Mann-Whitney test and biserial correlation were used to verify the effect size, since the Shapiro-Wilk normality test showed that it was a non-parametric sample (p < 0.001). The effect size was evaluated as follows: values of 0.8 or greater represent a large effect size; values between 0.8 and 0.2 are a medium effect size and values below 0.2 are a small effect size (Serdar et al., 2021). Besides, multiple regression analysis by the enter method was used to verify whether the history of reproval, social support, and self-efficacy variables could predict the adaptation to Higher Education of University students. The sample was used in its entirety, considering both sets of students. Data were analyzed using the JASP 0.14.1.0 software.

Ethical procedures

The research project was approved by the Research Ethics Committee of the university, under number 48512921.3.0000.5289 (CAAE). All participants agreed to participate and signed the informed consent form.

Results

The following are the comparisons between the repeating and non-repeating student groups concerning academic adaptation, perception of self-efficacy, and social support. The data are shown in Table 1.

Table 1
Comparison between repeating and non-repeating instruments in the instruments: Questionnaire of Adaptation to Higher Education (QAES), Scale of Self-Efficacy in Higher Education (EAES), and Scale of Social Support for University students and their respective factors. Comparison between repeating and non-repeating students using the instruments: Higher Education Adaptation Questionnaire (QAES), Higher Education Self-Efficacy Scale (EAES), and Scale of Social Support for University Students, and their respective factors.

	Repeated M (SD)	Never Repeated M (SD)	P	Effect size
QAES Total	123.1(21.3)	136.2(21.3)	< 0.001	-0.346
Career planning	28.3(6.5)	30.7(6.4)	< 0.001	-0.225
Social adjustment	25.6(7.8)	28.5(6.6)	< 0.001	-0.203
Personal-emotional adaptation	16.9(7.3)	19.3(7.7)	< 0.001	-0.201
Adaptation to Studying	25.0(5.2)	28.2(5.3)	< 0.001	-0.327
Adaptation to the Institution	27.2(5.8)	29.5(4.8)	< 0.001	-0.236
EAES Total	239.2(53.3)	262.5(45.1)	< 0.001	-0.259
SE¹ Academic	65.9(13.6)	72.8(10.5)	< 0.001	-0.314
SE in the Regulation of Training	49.1(13.4)	53.0(12.2)	< 0.001	-0.171
SE in Social Interaction	49.4(13.2)	52.8(11.4)	0.002	-0.145
SE in Proactive Actions	45.9(13.3)	50.5(12.3)	< 0.001	-0.201
SE at Academic Management	28.8(7.9)	33.3(5.9)	< 0.001	-0.354
Total Social Support	169.8(43.9)	185.2(35.3)	< 0.001	-0.195
Academic Support	104.9(30.9)	115.5(25.2)	< 0.001	-0.190
Support for Career Decisions	31.6(8.4)	34.5(7.0)	< 0.001	-0.195
Family Support	26.3(8.3)	27.5(7.3)	0.139	-0.067

• ¹ SE: Self-efficacy.

Table 1 shows that in most of the indicators, non-repeating students presented statistically significant means higher than the students with a history of repetition. That is, the academic adaptation, perception, and total self-efficacy, along with all their factors, were higher when the student had not repeated a semester, with effect sizes ranging from small to medium. Regarding social support, non-repeating students also had a higher perception of total social, academic, and career decision support with low magnitude compared to repeating students. In the family support factor, there was no difference between the groups.

The multiple linear regression analysis resulted in a statistically significant model, considering the total score of academic adaptation as the dependent variable [F (2,13) = 8.52; p < 0.01; R ² = 0.60]. All the variables studied were able to predict academic adaptation. Non-repetition (β = 0.0.11; t = 4.16; p < 0.001), total social support score (β = 0.33; t = 11.80; p < 0.001) and total self-efficacy score (β = 0.53; t = 18.52; p < 0.001) were predictors of academic adaptation. Additionally, the prediction met the requirements for multiple linear regression. That is, the total value of academic adaptation had a statistically significant and positive correlation with total social support (r = 0.58; p < 0.01) and with total self-efficacy (r = 0.70; p < 0.01). The Durbin-Watson value was 2.03, indicating that there was no correlation between the samples. In the multicollinearity test, the values were 1.06 for repetition, 1.26 for total social support, and 1.28 for total self-efficacy, indicating the absence of multicollinearity.

Discussion

The present study aimed to compare university students with a history of grade repetition to those without this history in the university considering the social support, academic self-efficacy, and academic adaptation variables and verifying the extent to which the social support and self-efficacy variables can predict the adaptation to Higher Education of students who had a history of repetition. The hypothesis that the social support and self-efficacy variables would be able to predict adaptation to Higher Education was confirmed, as well as the hypothesis that non-repeating students would present higher scores in the variables when compared to the others.

The results showed that academic adaptation and self-efficacy in Higher Education had statistically higher scores in non-repeating students, concerning both the total scores and the factors. In this context, the insights of Tinto (1975) are recalled, which highlighted performance regulation and content learning as prominent variables in his model of academic and social integration.

Faria and Almeida (2021) considered that, despite the democratization process that has expanded the access to university places, many of the students who enter Higher Education, enter without the skills and personal resources necessary to deal with the requirements, including in terms of curricular learning. Observing the results of the present study, one can consider the perception of greater adaptation on the part of students who had never repeated a semester as a possible factor associated with greater previous preparation for permanence in Higher Education, since they presented higher scores in academic adaptation.

In line with the understanding previously presented by Tinto (1975), the results found here also converge with those found by Nhachengo and Almeida (2021). The authors sought to investigate the relationship of academic adaptation with the performance of students at the end of the 1^st year of the undergraduate course, concluding that academic performance is correlated with the experiences of institutional adaptation, career projects, and study adaptation. It was also observed that during the second year, the correlation with personal-emotional adaptation increased. Therefore, it has been previously described by the authors that higher student mean scores are associated with greater academic adaptation. Therefore, it can be understood that repeating students have a greater tendency to not feel academically adapted, as observed in the present results. Also, regarding remaining in Higher Education, the perception of self-efficacy has previously been presented as a relevant factor in the adaptation to Higher Education (Rossi et al., 2020; Santos et al., 2019). If the nature of the variable is considered, which tends to strengthen with successful experiences (Bandura, 1997), the result presented is consistent with the previous theory, since students who perceive themselves as less self-effective maintain less focus and persistence in times of difficulty, which could lead them to being reproved. In addition, these students could also accumulate negative experiences when they are reproved, which may impact their performance in other subjects, their overall course progress, and their future development (Fior, 2022; Ingul et al., 2012, Santos et al., 2019).

Zuffiano et al. (2013) stated that support from family, peers, and teachers is an important predictor of academic performance. In the sample studied, no significant difference was obtained in the family support factor, however, the total score and the factors of academic support and career decisions were significantly higher in the students without a history of repetition. These results are in line with the literature that states that social support in an academic environment, from both teachers and peers, correlates positively with performance (Dias et al., 2015; Fernandes et al., 2018).

Finally, the results provide data for the understanding that self-efficacy, the perception of social support, and a history of repetition are relevant aspects of adaptation to Higher Education. As emphasized by Casiraghi et al. (2020), students must develop a greater capacity to perceive their context and their weaknesses so that they can seek support and ways to adjust to the university more healthily. Even considering the importance of factors such as teaching methodology and evaluation procedures, when focusing on the academic performance of university students (Casiraghi et al., 2020), the results presented converge with the understanding that it is possible and necessary to pay attention to the process of adaptation of university students who exhibit different functioning. Therefore, the importance of supporting university students who are faced with learning, personal, emotional, and social difficulties, is highlighted, particularly by creating adaptation strategies so that, mainly, those who have a history of repetition, remain and can complete their studies.

Final Considerations

The present study was able to fulfill the proposed objectives, indicating important differences when comparing the academic adaptation, self-efficacy, and social support of students with a history of grade repetition to those without this history. The results were relevant for the understanding of how these aspects can be facilitators or not for the adaptation to Higher Education.

It is understood that adaptation to Higher Education is an important variable in school dropout and that the experience of repetition can influence the adjustment of the subject to the academic environment. Considering that the perception of self-efficacy and social support are aspects that predict adaptation to Higher Education, it is important to pay attention to students with a history of repetition, since they may constitute a more vulnerable population compared to students who have never been reproved. With this, it is hoped that the contribution from this study will provide resources that target the most vulnerable populations in the academic environment, including repeating students.

It should be highlighted that the study was limited to investigating the academic adaptation, social support, and self-efficacy variables in students with a history of grade repetition within the university, however, it was not identified whether these students had a previous school history of reproval. Accordingly, it should be noted that in future studies the school experiences and the experience during High School and Elementary School should be considered as relevant factors for the adaptation of the student to the university.

From a future perspective, it is expected that new investigations can be carried out to expand knowledge about the experience and the academic adaptation of more specific audiences. Furthermore, new studies may seek to understand the role of other variables, in addition to delving into different courses or periods of the academic trajectory, as the present study focused solely on identifying repeating students without specifying their courses, semesters, or number of repetitions.

References

• Achkar, A. M. N. E., Leme, V. B. R., Soares, A. B., & Yunes, M. A. M. (2017). Risco e proteção de estudantes durante os anos finais do ensino fundamental.Psicologia Escolar e Educacional,21, 417-426. https://doi.org/10.1590/2175-35392017021311151
  » https://doi.org/10.1590/2175-35392017021311151
• Almeida, G. S., & Lopes, J. M. R. (2020). O que explica o desempenho dos estudantes? Um estudo de revisão. Revista de Instrumentos, Modelos e Políticas em Avaliação Educacional, 1(1), e020004. https://doi.org/10.51281/impa.e020004
  » https://doi.org/10.51281/impa.e020004
• Almeida, L. S. (2007). Transição, adaptação académica e êxito escolar no ensino superior. Revista Galego-Portuguesa de Psicoloxía e Educación, 14, 203-215. http://hdl.handle.net/2183/7078
  » http://hdl.handle.net/2183/7078
• Araújo, A. M., Almeida, L. S., Ferreira, J. A., Santos, A. A., Noronha, A. P., & Zanon, C. (2014). Questionário de Adaptação ao Ensino Superior (QAES): Construção e validação de um novo questionário. Psicologia, Educação e Cultura, 18(1), 131-145.
• Antunes, C. & Fontaine, A. M. (2008). Percepção de apoio social na adolescência: Análise fatorial confirmatória da escala Social Support Appraisal. Paidéia, 15(32), 355-366. https://doi.org/10.1590/S0103-863X2005000300005
  » https://doi.org/10.1590/S0103-863X2005000300005
• Bandura, A. (1997). Self-efficacy is the exercise of control Freeman and Company: New York.
• Batista, E. C., Mantovani, L. K. S., & Nascimento, A. B. (2015). Percepção de suporte familiar de alunos com histórico de reprovação escolar.Debates em Educação ,7(13), 50-70. https://doi.org/10.28998/2175-6600.2015v7n13p50
  » https://doi.org/10.28998/2175-6600.2015v7n13p50
• Brown, T. A. (2006). Confirmatory factor analysis for applied research. The Guilford Press.
• Casanova, J.R., Araújo, A.M., & Almeida, L.S. (2020). Dificuldades na adaptação académica dos estudantes do 1º ano do Ensino Superior. E-Psi, 9(1), 165-181. http://hdl.handle.net/11328/3576
  » http://hdl.handle.net/11328/3576
• Casiraghi, B., Boruchovitch, E., & Almeida, L.S. (2020). Crenças de autoeficácia, estratégias de aprendizagem e o sucesso acadêmico no Ensino Superior. E-Psi, 9(1), 27-38. https://revistaepsi.com/artigo/2020-ano9-volume1-artigo2/
  » https://revistaepsi.com/artigo/2020-ano9-volume1-artigo2/
• Castillo-Sánchez, M., Gamboa-Araya, R., & Hidalgo-Mora, R. (2020). Factores que influyen en la deserción y reprobación de estudiantes de un curso universitario de matemáticas.Uniciencia , 34(1), 219-245. https://doi.org/10.15359/ru.34-1.13
  » https://doi.org/10.15359/ru.34-1.13
• D’Abreu, L. C. F., & Marturano, E. M. (2010). Associação entre comportamentos externalizantes e baixo desempenho escolar: uma revisão de estudos prospectivos e longitudinais. Estudos de Psicologia (Natal), 15, 43-51. https://doi.org/10.1590/S1413-294X2010000100006
  » https://doi.org/10.1590/S1413-294X2010000100006
• Dazzani, M. V. M., Cunha, E. O., Luttigards, P. M., Zucoloto, P. C. S. V., & Santos G. L.. (2014). Queixa escolar: Uma revisão crítica da produção científica nacional. Revista Quadrimestral da Associação Brasileira de Psicologia Escolar e Educacional, 18(3), 421-428. https://doi.org/10.1590/2175-3539/2014/0183762
  » https://doi.org/10.1590/2175-3539/2014/0183762
• Dias, A., Oliveira, J. T., Moreira, P. A. S., & Rocha, L. (2015). Percepção dos alunos acerca das estratégias de promoção do sucesso educativo e envolvimento com a escola.Estudos de Psicologia (Campinas) , 32, 187-199. https://doi.org/10.1590/0103-166X2015000200004
  » https://doi.org/10.1590/0103-166X2015000200004
• Faria, A. A. G. B. T., & Almeida, L. S. (2021). Adaptação acadêmica de estudantes do 1º ano: promovendo o sucesso e a permanência na Universidade.Revista Internacional de Educação Superior, 7, e021024. https://doi.org/10.20396/riesup.v7i0.8659797
  » https://doi.org/10.20396/riesup.v7i0.8659797
• Faria, M. R. G. V. D., Zanini, D. S., & Pasian, S. R. (2020). Apoio social como fator de proteção para vitimizações e desempenho escolar. Avaliação Psicológica, 19(2), 152-158. http://dx.doi.org/10.15689/ap.2020.1902.05
  » http://dx.doi.org/10.15689/ap.2020.1902.05
• Fernandes, L. D. M., Leme, V. B. R., Elias, L. C. D. S., & Soares, A. B. (2018). Preditores do desempenho escolar ao final do ensino fundamental: histórico de reprovação, habilidades sociais e apoio social. Trends in Psychology , 26, 215-228. https://doi.org/10.9788/TP2018.1-09Pt
  » https://doi.org/10.9788/TP2018.1-09Pt
• Fior, C. (2022). Adaptação ao ensino superior e autoeficácia em universitários medalhistas em Olimpíadas Científicas: um estudo correlacional. Revista de Estudios e Investigación en Psicología y Educación, 9, 284-301. http://hdl.handle.net/2183/30627
  » http://hdl.handle.net/2183/30627
• Haukoos, J. S., & Lewis, R. J. (2005). Advanced statistics: Bootstrapping confidence intervals for statistics with “difficult” distributions. Academic Emergency Medicine, 12(4), 360-365. https://doi.org/10.1197/j.aem.2004.11.018
  » https://doi.org/10.1197/j.aem.2004.11.018
• Ingul, M. J., Klockner, C. A., Silverman, W. K., & Nordahl, H. M. (2012). Adolescent school absenteeism: Modelling social and individual risk factors. Child and Adolescent Mental Health, 17(2), 93-100. https://doi.org/10.1111/j.1475-3588.2011.00615.x
  » https://doi.org/10.1111/j.1475-3588.2011.00615.x
• Juliano, M. C. C. & Yunes, M. A. M. (2014). Reflexões sobre rede de apoio social como mecanismo de proteção e promoção de resiliência. Ambiente & Sociedade, 3(1), 135-154. https://doi.org/10.1590/S1414-753X2014000300009
  » https://doi.org/10.1590/S1414-753X2014000300009
• Lopes, J. M., Castro, J. G. F., Peixoto, J. M., & Moura, E. P. (2020). Autoeficácia de Estudantes de Medicina em Duas Escolas com Metodologias de Ensino Diferentes (Aprendizado Baseado em Problemas versus Tradicional).Revista Brasileira de Educação Médica,44(2), 1-7. https://doi.org/10.1590/1981-5271v44.2-20190187
  » https://doi.org/10.1590/1981-5271v44.2-20190187
• Loricchio, T. M. B., & Leite, J. R. (2012). Estresse, ansiedade, crenças de autoeficácia e o desempenho dos bacharéis em Direito.Avaliação Psicológica,11(1), 37-47. http://www.redalyc.org/articulo.oa?id=335027499005
  » http://www.redalyc.org/articulo.oa?id=335027499005
• Menezes, A. N. D., Alves, B. D. M., Barbosa, R. P. C., & Campos, P. C. (2020). A influência da crença de autoeficácia no desempenho dos alunos do IFMG-Bambuí.Psicologia Escolar e Educacional, 24, 1-9. https://doi.org/10.1590/2175-35392020202380
  » https://doi.org/10.1590/2175-35392020202380
• Mishra, S. (2020). Social networks, social capital, social support and academic success in higher education: A systematic review with a special focus on ‘underrepresented’ students. Educational Research Review, 29, 100307. https://doi.org/10.1016/j.edurev.2019.100307
  » https://doi.org/10.1016/j.edurev.2019.100307
• Nhachengo, M. V., & Almeida, L. S. (2021). Adaptação ao ensino superior e rendimento acadêmico em estudantes moçambicanos. Amazônica - Revista de Psicopedagogia, Psicologia escolar e Educação, 13(1), 56-72. https://periodicos.ufam.edu.br/index.php/amazonica/article/view/8310
  » https://periodicos.ufam.edu.br/index.php/amazonica/article/view/8310
• Nunes, T. G. R., Pontes, F. A. R., Silva, L. I. C., & Dell’Aglio, D. D. (2014). Fatores de risco e proteção na escola: Reprovação e expectativas de futuro de jovens paraenses. Psicologia Escolar e Educacional, 18(2), 203-210. https://doi.org/10.1590/2175-3539/2014/0182732
  » https://doi.org/10.1590/2175-3539/2014/0182732
• Organização de Cooperação e Desenvolvimento Econômico. (2012). OECD Higher Education Programme IMHE General Conference. Creative Connection.
• Pajares, F., & Olaz, F. (2008). Teoria social cognitiva e auto-eficácia: Uma visão geral, In A. Bandura, R. G. Azzi & S. Polydoro (Eds.),Teoria cognitiva: Conceitos básicos(Cap. 4, pp. 97-114). Artmed.
• Polydoro, S., & Guerreiro-Casanova, D. C. (2010). Escala de auto-eficácia na formação superior: construção e estudo de validação. Avaliação Psicológica: Interamerican Journal of Psychological Assessment, 9(2), 267-278. http://www.redalyc.org/articulo.oa?id=335027283011
  » http://www.redalyc.org/articulo.oa?id=335027283011
• Rocha, D. M. (2020). Crenças de autoeficácia e estratégias de aprendizagem: um estudo de caso dos ingressantes no curso de Licenciatura em Física.Pesquisa e Ensino em Ciências Exatas e da Natureza, 4, 01-16. http://dx.doi.org/10.29215/pecen.v4i0.1462
  » http://dx.doi.org/10.29215/pecen.v4i0.1462
• Rosa, A. R., Fernandes, G. N. A., & Lemos, S. M. A. (2020). Desempenho escolar e comportamentos sociais em adolescentes. Audiology-Communication Research, 25, e2287. https://doi.org/10.1590/2317-6431-2019-2287
  » https://doi.org/10.1590/2317-6431-2019-2287
• Rossi, T., Trevisol, A., Santos-Nunes, D. D., Dapieve-Patias, N., & Hohendorff, J. V. (2020). Autoeficácia geral percebida e motivação para aprender em adolescentes do Ensino Médio.Acta Colombiana de Psicología,23(1), 264-271. https://doi.org/10.14718/ACP.2020.23.1.12
  » https://doi.org/10.14718/ACP.2020.23.1.12
• Sahão, F. T., & Kienen, N. (2021). Adaptação e saúde mental do estudante universitário: revisão sistemática da literatura. Psicologia Escolar e Educacional, 25, e224238. https://doi.org/10.1590/2175-35392021224238
  » https://doi.org/10.1590/2175-35392021224238
• Santos, A. A. A. D., Zanon, C., & Ilha, V. D. (2019). Autoeficácia na formação superior: seu papel preditivo na satisfação com a experiência acadêmica.Estudos de Psicologia (Campinas) , 36, 1-9. https://doi.org/10.1590/1982-0275201936e160077
  » https://doi.org/10.1590/1982-0275201936e160077
• Santos, L. K. D. P. D., Santana, C. D. C., & Souza, M. V. O. D. (2020). Ações para o fortalecimento da resiliência em adolescentes. Ciência & Saúde Coletiva, 25, 3933-3943. https://doi.org/10.1590/1413-812320202510.22312018
  » https://doi.org/10.1590/1413-812320202510.22312018
• Serdar, C. C., Cihan, M., Yücel, D., & Serdar, M. A. (2021). Sample size, power and effect size revisited: simplified and practical approaches in pre-clinical, clinical and laboratory studies. Biochemia Medica, 31(1), 010502. https://doi.org/10.11613/BM.2021.010502
  » https://doi.org/10.11613/BM.2021.010502
• Silva, J. D., Beltrame, T. S., Viana, M. D. S., Capistrano, R., & Oliveira, A. D. V. P. D. (2014). Autoeficácia e desempenho escolar de alunos do ensino fundamental.Psicologia Escolar e Educacional , 18(3), 411-420. https://doi.org/10.1590/2175-3539/2014/0183760
  » https://doi.org/10.1590/2175-3539/2014/0183760
• Soares, A. B., Santos, A. A., Jardim, M. E. M., & Queluz, F. N. F. S. (no prelo). Evidências de validade da Escala de Apoio Social para Estudantes Univesitários.
• Souza, L. K. , Lourenço E., & Santos, M. R. G. (2016). Adaptação à universidade em estudantes ingressantes na graduação em psicologia. Psicologia da Educação, 42(1), 35-40. https://doi.org/10.5935/2175-3520.20150023
  » https://doi.org/10.5935/2175-3520.20150023
• Squassioni, C. E. & Matsukura, T. S. (2014). Adaptação transcultural da versão portuguesa do Social Support Appraisals para o Brasil. Psicologia: Reflexão & Crítica, 27(1), 71-80. https://doi.org/10.1590/S0102-79722014000100009
  » https://doi.org/10.1590/S0102-79722014000100009
• Tinajero, C., Martínez-López, Z., Rodríguez, M. S., & Páramo, M. F. (2020). El apoyo social percibido como predictor del éxito académico en estudiantes universitarios españoles. Anales de Psicología, 36(1), 134-142. https://doi.org/10.6018/analesps.344141
  » https://doi.org/10.6018/analesps.344141
• Tinto, V. (1975). Dropout from higher education: A theoretical synthesis of recent research. Review of Educational Research, 45, 89-125 https://doi.org/10.3102/00346543045001089
  » https://doi.org/10.3102/00346543045001089
• Zuffiano, A., Alessandri, G., Gerbino, M., Kanacri, B. P. L., Di Giunta, L., Milioni, M., & Caprara, G. V. (2013). Academic achievement: The unique contribution of self-efficacy beliefs in self-regulated learning beyond intelligence, personality traits, and self-esteem. Learning and Individual Differences, 23(1), 158-162. https://doi.org/10.1016/j.lindif.2012.07.010
  » https://doi.org/10.1016/j.lindif.2012.07.010

• Data availability statement

  The author does not authorize the disclosure of research data

Edited by

Responsible editor

Asdrubal Borges Formiga Sobrinho

Data availability

The author does not authorize the disclosure of research data

Publication Dates

• Publication in this collection
  29 July 2024
• Date of issue
  2024

History

• Received
  10 Feb 2023
• Accepted
  08 May 2023