FAMILY SUPPORT AS A POSSIBLE PREDICTOR OF STRATEGIES AND OF THE MOTIVATION TO LEARN

ABSTRACT

Students with good family support feel more connected to their family and studies, increasing the probability of being more motivated to learn and tend to be more strategic at the time of learning. This study aimed to investigate the correlation among family support, learning strategies and motivation to learn and to verify whether family support includes the use of these psychoeducational variables. In this research, 352 students enrolled in Elementary School II of a public school participated. We used the Perception of Family Support Inventory - IPSF, Children’s Continuum Questionnaire and the Assessment Scale of Learning Strategies for Elementary School - EVAP-EF. The descriptive research method was adopted, with survey and correlational designs. The results indicated that students who receive family support tend to make more use of learning strategies and they are more motivated to learn.

Keywords:
family; motivation; learning

RESUMO

O aluno com bom suporte familiar se sente mais vinculado à família e aos estudos, aumentando a probabilidade de apresentar maior motivação para aprender e tendência a ser mais estratégico no momento do aprendizado. Objetivou-se investigar a correlação entre o suporte familiar, as estratégias de aprendizagem e a motivação para aprender e verificar se o suporte familiar prevê o uso dessas variáveis psicoeducacionais. Participaram 352 alunos matriculados no Ensino fundamental II de uma escola pública. Utilizou-se o Inventário de Percepção de Suporte Familiar - IPSF, Questionário Continuum Infantil e a Escala de Avaliação das Estratégias de Aprendizagem para o Ensino Fundamental - EAVAP-EF. Adotou-se o método de pesquisa descritivo, com delineamentos de levantamento e correlacional. Os resultados indicaram que os alunos que recebem suporte familiar tendem a fazer mais uso de estratégias de aprendizagem e apresentam mais motivação para aprender.

Palavras-chave:
família; motivação; aprendizagem

RESUMEN

El alumno con buen soporte familiar se siente más vinculado a la familia y a los estudios, aumentando la probabilidad de presentar más motivación para aprender y tendencia a ser más estratégico en el momento del aprendizaje. Se tuvo por objetivo investigar la correlación entre el soporte familiar, las estrategias de aprendizaje y la motivación para aprender y averiguar si el soporte familiar previene el uso de esas variables psico educacionales. Participaron 352 alumnos matriculados en la Enseñanza Básica II de una escuela pública. Se utilizó el Inventario de Percepción de Soporte Familiar - IPSF, Cuestionario Continuun Infantil y la Escala de Evaluación de las Estrategias de Aprendizaje para la Enseñanza Básica - EAVAP-EF. Se adoptó el método de investigación descriptivo, con delineamentos de recopilación y correlacional. Los resultados indicaron que los alumnos que reciben soporte familiar tienden a hacer más uso de estrategias de aprendizaje y presentan más motivación para aprender.

Palabras clave:
familia; motivación; aprendizaje

INTRODUCTION

When it comes to education, families are typically believed to have the power to interfere positively or negatively in their children’s performance at school. However, regardless of structure, all families are responsible for satisfying basic necessities and nurturing social development, so that children are provided with the emotional and psychological foundation for the construction of their own identity. Many educators believe that students that present poor performance at school come from dysfunctional families. Nevertheless, although families are essential throughout the schooling process, not all students who fail necessarily come from family contexts with such characteristics (Ribeiro, Ciasca, & Capellato, 2016).

In addition, important changes in family routine can be observed in contemporary society. For example, we can point to the fact that parents work all day and, quite often, cannot provide continuous supervision to their children’s schooling. According to Barros and Santos (2015), many families face difficulties to follow the school trajectory of their children, which might turn out harmful to the family support that is supposed to be provided to students.

When students do not get family support for studying and will only find that kind of support in the school environment, they might present poorer performance or difficulties when it comes to the development of social, emotional, and cognitive skills, which are essential for students to reach self-regulation in their own learning process (Batista, Mantovani, & Nascimento, 2015). Thus, lack of support might lead students to have more difficulties to pay attention in class or display more skillful social behaviors. Therefore, it is important that families provide emotional stability and support for studies, so that students will be able to face personal and academic challenges successfully (Guidetti & Martinelli, 2017).

According to Baptista (2009), family support consists of the capacity by the family to provide essential elements such as protection, communication, autonomy, respect, interest, and safety to their children. Thus, family support might be considered an enhancing factor for education. It is capable of affecting the development of children, there learning context, and, consequently, their school performance. Such is the relevance of family support (Barros & Santos, 2015; Roksa & Kinsley, 2019).

In the search for connections between family support and psycho educational variables, it is possible to observe exploratory associations. Costa, Montiel and Bartholomeu (2016), for example, found connections between family support (autonomy and family adaptation) and the reading performance by children at the ages of 8 to 10 years, the regression analysis explained almost 10% of the variance (r ₂ = 0,098). The children who are helped by their parents in their reading tasks are the ones with better performance in reading tests. Also, Ribeiro et al. (2016) found associations between the resources in the family environment (family holidays, books and magazines, educational games, and so on) and writing performance at school by students in the fifth year of elementary school (r = 0,345).

In this sense, it is possible to establish that life at school, to a certain degree, can be influenced by family support, and that the connection formed by this kind of support allows students to feel, in addition, more motivated to learn. Motivated students are able to learn content in depth. In order to do that, students employ learning strategies that, when used in an adequate way, facilitate the acquisition, retention, and processing of information (Boruchovitch, 1999; Oliveira, Santos, & Inácio, 2017).

Concerning the motivation to learn, it refers to an inner construct or an acquired competence in accordance with an individual’s experience at school, which is determinant to quality school education (Brophy, 1987; Ryan & Deci, 2017). Among the diverse theories on the theme, the Self-determination Theory (SDT) classifies motivation into two types: intrinsic and extrinsic. In the first type, students tend to employ strategies that demand more effort and that allows them to process information more deeply and, in general, prefer more challenging tasks. On the other hand, students regulated by extrinsic motivation display a preference for activities with a lower level of difficulty (Bzuneck, Oliveira, Rufini, & Oliveira, 2015).

To Maieski, Oliveira, Beluce and Rufini (2017), the establishment of connections leads to the internalization of concepts and external regulation. Thus, internalization is essential for behavior regulation and the optimization of motivation in the school context. Once the student feels motivated and connected, this feeling is associated to family support, and can be the trigger for a motivational factor that is more present in the studies. Thus, there is the hypothesis that, by receiving family support, students will be able to establish greater connections with learning. These connections allow students to feel more motivated to learn, and to use more learning strategies and, consequently, do better academically (Castro, Miranda, & Leal, 2016).

When it comes to learning strategies, they can be a whole range of activities, behaviors, or plans with the aim to reach pre-established learning goals. Such strategies refer to a conscious, deliberate attitude revealed by the students’ decision-making skills. This attitude has been adjusted to the specific context and objectives that each student intends to reach, while guaranteeing good performance at school. Learning strategies can be considered cognitive, relating to behaviors of organization, storage, and elaboration of information. They can also be meta-cognitive, which are behaviors related to the regulation, monitoring, and planning of the students’ own thoughts during the learning process. (Boruchovitch, 1999; Dembo, 1994).

Students must diversify the ways to study and recover content, while benefitting from cognitive processes. Therefore, it is also possible to overcome school difficulties in order to develop attitudes of self-assessment and improvement in academic performance. To do that, students need to get acquainted with these strategies and learn the right time for each one (Boruchovitch, 1999; Oliveira et al., 2017).

Regarding the aforementioned conjectures, as well as the relevance of family support for school education, it is possible to hypothesize the existence of relation between this construct and the strategies employed at the moment of studying and the motivation to learn. Thus, it is possible that the students who feel connected to their families and are provided with satisfactory family support become more autonomous and motivated, consequently reaching better performance at school. In this perspective, the objective of the present study was to investigate the correlation between family support with learning strategies and with the motivation to learn. Additionally, there was the intention to verify whether family support is capable of predicting the use of these psychoeducational variables.

METHOD

Participants

355 students took part in the research. They were from the 6^th to the 9^th years of the second part of elementary school, with ages ranging from 10 to16 years (M = 12,6; DP = 1,2). 39% of these students were male (n = 139) and 60% were female (n = 213), while three participants did not answer the question. The students attended a public school in the countryside of Paraná and were selected by convenience. When it comes to the school year, the 6^th year represented 25.6% (n = 91) of the sample, the 7^th year represented 34.6% (n = 123), the 8^th year represented 25.1% (n = 89), and the 9^th year, 14,6% (n = 52).

Instruments

The Family Support Perception Inventory (IPSF): consists of a measurement instrument that was produced and validated for Brazil by Baptista (2005, 2009). The inventory is made up of 42 statements concerning family situations, in which one must choose the option that represents how often each one of those situations happen in the family. The items are subscribed into 3 subscales, they are: Affectionate-Consistent, Adaptation, and Autonomy.

The Child Education Continuum: elaborated by Rufini, Bzuneck and Oliveira (2011), the instrument is made up of 25 items, based on the Self-Determination Theory (SDT), which approach the reasons why students attend school. It is constituted by 5 subscales, they are: Demotivation, extrinsic motivation by external regulation, extrinsic motivation by introjected regulation, extrinsic motivation by identified regulation, and intrinsic motivation. In this instrument, the scale is presented by means of the drawing of geometric shapes in crescent sizes, followed by the numbers 1 to 5. The instrument was validated by means of Exploratory Factorial Analysis, realized by the authors.

The “Escala de Avaliação das Estratégias de Aprendizagem para o Ensino Fundamental - (EAVAP-EF), or Scale for Assessment of Learning Strategies for Elementary School: produced by Oliveira, Boruchovitch and Santos (2010), it includes 31 items, arranged into a Likert scale of three points (0 “never”, 1 “sometimes”, 2 “always”). There are three subscales: Absence of dysfunctional meta-cognitive strategies, cognitive strategies, and meta-cognitive strategies, in addition to the overall score. The instrument presents evidence of validity, as well as reliability.

Procedure

This research is supported by Resolution 466/2012 and by its complements by the National Health Council and approved by the Ethics Committee for Human Beings of a university in the north of Paraná. The instruments were applied by the researcher, after signature of a Free Informed Term of Consent - FITC by the students and by their legal guardians. Data was gathered collectively, in the classroom, at times and dates that had been previously set up by the institution, and the instruments were completed in approximately 50 minutes. For the students in the 6th year, the questions from the three instruments were read out loud, one by one, in order to facilitate the participants’ comprehension.

Data analysis

Descriptive and inferential statistics were realized by means of the SPSS program (Statistical Package for the Social Sciences) version 22.0. Initially, a frequency analysis was realized in order o check the averages, standard deviations, as well as minimal or maximal scores by the participants. Subsequently, researchers realized the Pearson correlation between the scores in the instruments, while estimating the magnitude of these relations based on the presuppositions by Cohen (1988). Finally, by means of Simple Linear Regression Analysis, the capacity for score prediction in the applied instruments was checked.

RESULTS

According to the initial objective, in the first part of the results, there was an assessment of the students’ skills in the employed instruments. After that, the sum of all the items was divided into the number of items, which made comparison possible. Thus, the results of the descriptive analysis can be visualized on Table 1.

Table 1
Descriptive statistics for the scores in the instruments.

Instrument	Score variation	average	Standard deviation	Maximum score	Minimum score
Affectionate-Consistent	0 - 42	26,2	7,5	42	6
Adaptation	0 - 26	18,8	4,7	26	4
Autonomy	0 - 16	8,9	2,9	16	0
Total	0 - 84	54,2	12,2	80	20
Absence L.S. Meta Dysf.	0 - 26	12,8	5,3	26	1,0
Cognitive L.S.	0 - 22	8,3	4,5	20	0
Meta-cognitive L.S. Meta-cognitive	0 - 14	9,9	2,2	14	3,0
Total	0 - 62	31,1	9,1	58	8
Demotivation	0 - 25	11,8	4,8	25	5,0
Ext. Reg. Mot	0 - 25	13,1	4,5	25	5,0
Introjected Reg. Mot	0 - 25	14,6	5,3	25	5,0
Identified Reg. Mot	0 - 25	21,5	3,9	25	5,0
Intrínsic Mot.	0 - 25	17,3	5,0	25	5,0

Concerning the perception of family support, it was possible to verify in the total scale that the average of right responses was 54,2, with standard deviation of 12,2. It was verified that the minimum number of right responses was 20 and the maximum number was 80, whiles the variation of possible points was between 0 and 84. Thus, it was possible to observe that the students obtained scores that were above average of half the possible score, that is, 42 points.

There was also an analysis of the employed learning strategies, the score of which might range from 0 to 62. The total average of the students was identified. It was 31.1 with 9.1 standard deviation. It is observed that the minimum score was 8 and the maximum score was 58. Therefore, it is perceived that the students obtained scores that were within the expected average, which should be 31 points, that is, half the possible right responses. Regarding the scale that assesses the motivation to learn, the score should range from 0 to 25 points in each one of the subscales, while the greatest average found concerning the Identified Regulation subscale.

With the objective to investigate the correlation between family support and the other constructs, learning strategies and the motivation to learn, Pearson’s call relation test was realized. Table 2 presents data referring to the correlation coefficients between the score in the family support perception inventory and the scale for assessment of learning strategies for elementary school and with the child education continuum.

Table 2
correlation indexes (r) and significance levels (p) between the IPSF and the EAVAP-EF and the child education continuum.

	ffectionate-consistent	Adaptation	Autonomy	Total
Absence L.S Meta. Dysf.	0,348***	0,432***	0,225	0,395***
Metacognitive L.S.	0,165*	0,373*	0,141*	0,159*
Cognitive L.S.	0,384***	0,224**	0,416**	0,345**
Total L.S.	0,447***	0,393**	0,109	0,460***
Demotivation	-0,379**	-0,388***	-0,091
External Reg. Mot.	-0,321**	-0,303**	0,367**
Introjected Reg. Mot.	-0,226**	-0,279**	-0,110*
Identified Reg Mot.	0,262**	0,251**	0,395**
Intrinsic Mot.	0,351**	0,294**	0,113*

• Note: Level of significance *=0,050; **=0,01; ***=0,001.

Positive and negative correlations were found for the Affectionate-Consistent subscale with all the subscales for Learning Strategies and Motivation to Learn, while magnitude ranged from small to medium (Cohen, 1988). The same result was found for the Adaptation subscales and the total scale for family support, and all results were significant. When it comes to the Autonomy subscale, the results were not significant only with Absence of Dysfunctional Meta-cognitive Strategies and with demotivation, both of the scale for Learning Strategies.

With the objective to verify whether family support can predict the use of psycho-educational variables in the present study, the Simple Linear Regression Analysis was realized. Table 3 presents the data regarding the analysis realized between the Family Support Perception Inventory and the Learning Strategies Assessment Scale, which presented significant correlation.

Table 3
Linear Regression for Family Support and Learning Strategies.

Independent Variable	R	R²adjusted	F	Betaz	t	Sig
Total Family Support and Learning Strategies
Absence of Meta Dysf L.S.	0,395	0,153	F(1,284)=52,401	0,395	7,239	0,001
Cognitive L.S.	0,345	0,116	F(1,287)=38,538	0,345	6,208	0,001
Total L.S.	0,460	0,208	F(1,270)=72,275	0,460	8,501	0,001
Affectionate-Consistent subscale and Learning Strategies
Absence Meta Dysf L.S.	0,348	0,118	F(1,299)=40,942	0,348	6,399	0,001
Cognitive L.S.	0,384	0,145	F(1,302)=52,136	0,384	7,221	0,001
Total L.S.	0,447	0,197	F(1,286)=71,139	0,447	8,434	0,001
Adaptation Subscale and Learning Strategies
Absence Meat Dysf. L.S.	0,432	0,184	F(1,313)=71,626	0,432	8,463	0,001
Total L.S.	0,393	0,152	F(1,297)=54,305	0,393	7,369	0,001

According to Table 3, it was verified that total Family support predicts the Absence of Dysfunctional Metacognitive Learning Strategies in 15%, the Cognitive Learning Strategies in 11%, and the Total Learning Strategies in 20%. This result indicates that these subscales of the

IPSF predict the use of learning strategies by the students in the researched sample, that is, the students that receive more family support use fewer Dysfunctional Metacognitive Strategies and more Cognitive Strategies at the moment of learning.

The Affectionate-Consistent subscale can predict the Absence of Dysfunctional Metacognitive Learning Strategies in 11%, the Cognitive Learning Strategies in 14%, and the Total Learning Strategies in 19%. Thus, the students that get more affection manifestations by members of their families use fewer Dysfunctional Meta-cognitive Learning Strategies and more Cognitive Learning Strategies, and more Learning Strategies, in general.

The Adaptation subscale predicted in 18% of the subscale for Absence of Dysfunctional Meta-cognitive Learning Strategies, and in 15% of the Total Learning Strategies. Therefore, the students that were better adapted within their own families use fewer Dysfunctional Meta-cognitive Learning Strategies and more Learning Strategies in general.

Based on the analysis of data from linear regression for family support and the child education continuum, Table 4 was structured. In table 4, data are presented concerning Total Family Support, and the subscales for Affectionate-Consistent and Adaptation.

Table 4
Linear Regression for Family Support and the Child Education Continuum.

Independent variable	R	R²ajusted	F	Betaz	T	Sig
Total Family Support and Motivation to Learn
Demotivation	0,419	0,173	F(1,288)=61,270	-0,419	-7,828	0,001
External Reg. Mot.	0,322	0,101	F(1,287)=33,084	0,322	-5,752	0,001
Intrinsic Mot.	0,360	0,127	F(1,284)=42,407	0,360	6,512	0,001
Affectionate-Consistent and Motivation to Learn Subscales
Demotivation	0,379	0,141	F(1,301)=50,462	-0,379	-7,104	0,001
External Reg. Mot.	0,321	0,100	F(1,302)=34,632	-0,321	5,885	0,001
Intrínsic Mot.	0,351	0,120	F(1,299)=42,063	0,351	6,486	0,001
Adaptation and Motivation to Learn Subscales
Demotivation	0,382	0,148	F(1,321)=56,676	-0,388	7,528	0,001

Table 4 presents Total Family Support predecting the Demotivation subscale in 17%, the Demotivation subscale in 17%, the Externally Regulated Motivation in 10%, and the Intrinsic Motivation in 12%. Thus, it is known that the students that receive family support in a way that they consider satisfactory, feel less demotivated to learn. In addition, they are driven to learn by external consequences but also find motivation in the activities for their own sake.

The Affectionate-Consistent subscale can predict the Demotivation subscale in 14%, the Externally Regulated Motivation in 10%, and the Intrinsic Motivation in 12%. Thus, the students that receive and perceive the affection of their family members present less demotivation for learning, and more motivation to learn for external causes as well as for the simple pleasure of learning new things. The Adaptation subscale might predict the Demotivation subscale in 14%, which means that the students who perceive themselves as better adapted within their own families, present less demotivation for learning.

DISCUSSION

One objective of the present study was to investigate the correlation between family support and the learning strategies and the motivation to learn. Another objective was to verify whether family support predicts the use of these psycho-educational variables. Considering the results, it was evident that the participating students had a good perception of family support, there was also relation between the perceived family support, the motivation, and the use of strategies, while a certain degree of dependence between the constructs was also verified. The data will be discussed in the following paragraphs based on the pertinent scientific literature.

Concerning the results of the IPSF, the students presented the highest average score in the Adaptation subscale. Thus, it has become evident that the sample participants present positive behaviors regarding their families, such as respect, dialogue, acceptance, and others. The second highest score occurred in the Affectionate-Consistent subscale, so it is possible that the students perceive the members of their families as affectionate and interested in their activities. This subscale also refers to the clarity of family rules, the consistency of behaviors, communication, interaction, respect, and others. The lowest manifested score was in Autonomy, however, with an average above half the possible points. Thus, it is possible that a perception of privacy and freedom among the members of families in this sample exists (Baptista, 2005, 2009).

Concerning the assessment of the learning strategies, the sample presented the highest score average for the Meta-cognitive Strategies subscale, which is a sign that the students are able to think over their own thoughts, and to pick and choose actions at the moment of learning. Regarding the absence o Dysfunctional Meta-cognitive Learning Strategies, the average was a little below half the number of right responses, which is possible evidence that students still resort to dysfunctional strategies, though not that much, at the moment of study (Boruchovitch, 1999; Dembo, 1994).

In the subscale for Cognitive Strategies, when it comes to the organization studies, and the elaboration of information, the students in the sample presented low scores. Such result can be seen as negative, since such strategies play an important role in the acquisition of knowledge and the consolidation of learning in the school context (Dembo, 1994; Oliveira et al., 2017).

Regarding the child education continuum, the students presented higher punctuation in the subscale for Extrinsic Motivation by Identified Regulation, which is characterized by the possibility that individuals will take over the task value and identify with it. Such fact might be considered positive, since the subscale in question is the closest one to intrinsic motivation (Bzuneck et al., 2015). The second highest scoring subscale was the one for Intrinsic Motivation, which allows us to say that the students are also driven to certain behaviors by the pleasure they experience simply by doing the school activities. Then, the Extrinsic Motivation by Introjected Regulation proved above half the possible score, which is evidence that the students are, occasionally, motivated by internal pressure, such as feelings of guilt, anxiety, or necessities connected to their self-esteem (Brophy, 1987; Rufini et al., 2011).

In the subscale for Extrinsic Motivation by External Regulation, the result is also above half the number of right responses, which can be considered negative because it consists of realizing an activity merely in order to gain external benefits, or even, avoid unpleasant consequences. The Demotivation subscale also got points in the score, although it was a little below half the number of possible points. This result shows that, in the school context of the assessed sample, there is no lack of intention or initiative. Quite the opposite, the students demonstrated motivation to learn (Bzuneck et al., 2015; Rufini et al., 2011; Ryan & Deci, 2017).

Regarding the correlations between the subscales of the IPSF with the Learning Strategies Inventory and with the Child Education Continuum, the magnitudes of the results were considered small and medium (Cohen, 1988), and most of the were significant. The subscales for Affectionate-Consistent, Adaptation and Total scale for the IPSF obtained correlation with all the subscales of the EAVAP-EF. Therefore, it is possible to infer that student who perceive the existence in the family of affection, positive behaviors, and freedom for its members, tend to use learning strategies, avoid the distraction strategies, and manifest more behaviors and thoughts capable of influencing the efficient acquisition and recovery of information (Dembo, 1994; Oliveira et al., 2017).

Concerning the Child Education Continuum, the correlations were also considered small and medium among all the subscales of the IPSF with the motivation questionnaire. The correlation was significant not only regarding Autonomy with the Demotivation subscale. Besides that, it is important to emphasize that Demotivation, Motivation by External Regulation and by Introjected Regulation correlated negatively with the subscale for Affectionate-Consistent and Adaptation, which is an indication that the more affection and positive behaviors are perceived by the students when it comes to their families, the less demotivated and/or regulated by external motivation they present themselves (Ryan & Deci, 2017).

Therefore, the results evidenced the positive and significant correlations between the Identified motivation and the Intrinsic motivation with the subscales for Affectionate-Constant, Adaptation, and Autonomy of the IPSF. The data provide evidence that the students who identify with the tasks and feel pleasure at executing them, perceive their family members as displayers of positive behaviors and affections, as well as with the existence of privacy and freedom for the member of the family. According to what was mentioned by Maieski et al. (2017), such factors are related to a greater connection with learning. Besides that, in the age group of Elementary School, there is a certain conditional autonomy, under which the more students behave positively regarding their own education, the more gratification from family they get, in other words, their external compensation is connected to more Autonomy, that is, privacy, freedom, and so on. (Baptista, 2005, 2009).

The realized regression analyses indicated relevant prediction rates. The Family Support Perception Inventory demonstrated a prediction, in approximately 20%, of the use of learning strategies. It means that, to a certain degree, the students who receive family support tend to employ these strategies at the school environment, which might contribute to a more facilitated, effective learning (Boruchovitch, 1999; Oliveira et al., 2017). The other prediction data for strategies indicated that the Affectionate-Consistent subscale also demonstrated being able to predict, to a certain degree, the Absence of Dysfunctional Meta-cognitive Strategies, Cognitive Strategies, and Total Strategies. In addition, the subscale for Adaptation evidenced prediction rates for the Absence of Dysfunctional Meta-cognitive Strategies and for Total Strategies. We emphasize that these data are debuting in the scientific literature and, despite their relevance, should be deemed with caution.

When it comes to the IPSF and the Child Education Continuum, there was a relation of prediction between the total scale for family support with the subscales for Demotivation, External Motivation, and Intrinsic Motivation. This means that family support can predict, to a certain degree, the demotivation of students, as well as their external demands. Similarly, family support was able to predict the realization of activities for the mere pleasure of doing them (intrinsic motivation), which indicates the importance of the support variable as an indicator of its strong influence on learning and, consequently, on academic support (Castro et al., 2016; Roksa & Kinsley, 2019).

Besides, the Affectionate-Consistent subscale of the IPSF was able to predict, to a certain degree, the subscales for Demotivation, Motivation by External Regulation, and Intrinsic Motivation. Thus, the students that feel embraced and protected by their family members, tend to display less demotivation, and realize tasks for external gains, but also for the mere pleasure of doing these activities. Finally, the Adaptation subscale was able to predict the one for Demotivation, toa certain degree, while evidencing the positive behaviors observed in their own families, such as respect, acceptance, etc., are related to the motivational characteristics of the students in the researched sample (Bzuneck, 2015; Ryan & Deci, 2017).

Considering the issues raised in this research, it is possible to come to the conclusion that there are psycho-educational challenges to overcome, such as the implementation of intervention programs with the students so that they will use more learning strategies at the moment of studying, the instrumentalization of teachers and also the orientation of parents and legal guardians. Although schools face problems such as learning difficulties, it should be possible to overcome these obstacles if educational institutions instructed the students on the best ways to study, and spent some time teaching them what strategies to use and how to use them at the moment of learning (Boruchovitch, 1999; Oliveira et al., 2017).

It is also necessary to problematize the fact that, according to the Base Nacional Comum Curricular - BNCC, or National Nucleus of Common Curricula (2019), which consists of the most updated document and of normative character that establishes the set of essential content to be learned by all students along the stages and modes of Basic Education, the general objectives of teaching refer to the promotion of skills related to cognitive, emotional, physical, ethical, esthetic, operational, and also social-insertion aspects, as a means to set up the basic formation that is necessary for the exercise of citizenship.

On the other hand, the perception of distance between the State and educational institutions is quite common, while the State very often attributes to parents roles that they are not professionally qualified to play. In this perspective, problematizing conceptions on such relation is necessary because, on the one hand, school frequently strays away from its functions. On the other hand, there are occasions when parents are denied their function of affection-social nature, which are also educational though not in the school sense. Thus, the complexity of the School/Family discussion becomes clear. It is something that needs to be better investigated.

The present study is not free from limitations. Therefore, it is important to highlight the fact that the sample was established by convenience and there is a necessity for fresh research works with the objective to investigate the issue of participants’ gender as a factor that interferes in possible differences between results. Another limitation might be connected to the fact that the students answered the inventory in classroom, which might interplay with the effect of social desirability. Thus, we expect that future research works realize assessments based on the student - family relation with a plan that includes interviews, so that researchers will be able to better understand this perception of support.

At last, we see it as an advance that the comprehension of family support, which is a socio-family variable, is in association with the learning variable, which is the case of motivation and learning strategies. When we demonstrate the relation that exists between these constructs, we promote an important discussion on the partnership of parents and educational institutions. The originality and the contribution of the data presented here is perceptible for the fact that, so far, researchers have not found studies approaching these themes with the objectives and the schooling stage portrayed here.

REFERÊNCIAS

• Baptista, M. N. (2005). Desenvolvimento do Inventário de Percepção de Suporte Familiar (IPSF): estudos psicométricos preliminares. Psico-US F, 10(1), 11-19. https://dx.doi.org/10.1590/S1413-82712005000100003
• Baptista, M. N. (2009). Inventário de percepção de suporte familiar (IPSF): estudo componencial São Paulo: Vetor.
• Barros, I. C. O.; Santos, J. (2015). O. A importância da parceria família-escola no processo de ensino aprendizagem. Revista brasileira de educação e saúde, 5(2), 39-45. Recuperado dehttps://www.gvaa.com.br/revista/index.php/REBES/article/download/4111/3641
  » https://www.gvaa.com.br/revista/index.php/REBES/article/download/4111/3641
• 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. http://dx.doi.org/10.28998/2175-6600.2015v7n13p50
  » https://doi.org/10.28998/2175-6600.2015v7n13p50
• Boruchovitch, E. (1999). Estratégias de aprendizagem e desempenho escolar: considerações para a prática educacional. Psicologia: Reflexão e Crítica, 12(2), 361-376. https://dx.doi.org/10.1590/S0102-79721999000200008
  » https://doi.org/10.1590/S0102-79721999000200008
• Ministério da Educação. Base Nacional Comum Curricular (2019). Recuperado dehttp://basenacionalcomum.mec.gov.br/abase/
  » http://basenacionalcomum.mec.gov.br/abase/
• Brophy, J. (1987). Synthesis of Research on Strategies for Motivating Students to Learn. Educational leadership, 45(2). 40-48. Recuperado dehttp://www.ascd.org/ASCD/pdf/journals/ed_lead/el_198710_brophy.pdf
  » http://www.ascd.org/ASCD/pdf/journals/ed_lead/el_198710_brophy.pdf
• Bzuneck, J. A.; Oliveira, M. F. C.; Rufini, S. E.; Oliveira, K. L. (2015). Estrutura fatorial de uma Escala de Motivação de Adolescentes para Leitura. Avaliação Psicológica, 14(3), 375-383. DOI: 10.15689/ap.2015.1403.09
  » https://doi.org/10.15689/ap.2015.1403.09
• Castro, J. X.; Miranda, G. J.; Leal, E. A. (2016). Estratégias de aprendizagem dos estudantes motivados. Advances in Scientific and Applied Accounting, 9(1), 80-97. Recuperado de https://asaa.anpcont.org.br/index.php/asaa/article/view/258
  » https://asaa.anpcont.org.br/index.php/asaa/article/view/258
• Cohen, J. (1988). Statistical power analysis for the behavioral sciences Hillsdale, NJ: Erlbaum.
• Costa, K.; Montiel, J. M.; Bartholomeu, C. S. M. (2016). Percepção do suporte familiar e desempenho em leitura e escrita de crianças do ensino fundamental. Revista Psicopedagogia, 33(101), 154-163. Recuperado dehttp://pepsic.bvsalud.org/scielo.php?script=sci_arttext&pid=S0103-84862016000200005&lng=pt&tlng=pt
  » http://pepsic.bvsalud.org/scielo.php?script=sci_arttext&pid=S0103-84862016000200005&lng=pt&tlng=pt
• Dembo, M. H. (1994). Applying educational psychology (5ª Ed). New York: Longman Publishing Group.
• Guidetti, A. A.; Martinelli, S. C. (2017). Percepções Infantis: Relações entre Motivação Escolar e Suporte Familiar. Psico-USF, 22(3), 515-525. https://dx.doi.org/10.1590/1413-82712017220311
  » https://doi.org/10.1590/1413-82712017220311
• Maieski, S.; Oliveira, K. L.; Beluce, A. C.; Rufini, S. E. (2017). Motivação de alunos do ensino fundamental: estudo de duas realidades culturais. Psicologia Escolar e Educacional, 21(3), 601-608. https://dx.doi.org/10.1590/2175-353920170213111129
  » https://doi.org/10.1590/2175-353920170213111129
• Oliveira, K. L.; Boruchovitch, E.; Santos, A. A. A. (2010). Escala de avaliação das estratégias de aprendizagem para o ensino fundamental - EAVAP-EF São Paulo: Casa do Psicólogo.
• Oliveira, K. L.; Santos, A. A. A.; Inácio, A. L. M. (2017). Estratégias de aprendizagem no ensino médio brasileiro: análise exploratória dos resultados. Revista de Estudios e Investigación en Psicología y Educación, Extra(01), 337-341. https://doi.org/10.17979/reipe.2017.0.01.3041
  » https://doi.org/10.17979/reipe.2017.0.01.3041
• Ribeiro, R.; Ciasca, S. M.; Capelatto, I. V. (2016). Relação entre recursos familiares e desempenho escolar de alunos do 5º ano do ensino fundamental de escola pública.Revista Psicopedagogia , 33(101), 164-174. Recuperado dehttp://pepsic.bvsalud.org/scielo.php?script=sci_arttext&pid=S0103-84862016000200006&lng=pt&tlng=pt
  » http://pepsic.bvsalud.org/scielo.php?script=sci_arttext&pid=S0103-84862016000200006&lng=pt&tlng=pt
• Roksa, J.; Kinsley, P. (2019). Correction to: The Role of Family Support in Facilitating Academic Success of Low-Income Students. Research in Higher Education, 60(437). https://dx.doi.org/10.1007/s11162-018-9525-z
  » https://doi.org/10.1007/s11162-018-9525-z
• Rufini, S. E.; Bzuneck, J. A.; Oliveira, K. L. (2011). Estudo de validação de uma medida de avaliação da motivação para alunos do ensino fundamental. Psico-USF, 16(1), 1-9. https://dx.doi.org/10.1590/S1413-82712011000100002
  » https://doi.org/10.1590/S1413-82712011000100002
• Ryan, R. M.; Deci, E. L. (2017). Self-determination theory: Basic psychological needs in motivation, development, and wellness. NewYork: Guilford Publications.

• This paper was translated from Portuguese by Régis Lima

Publication Dates

• Publication in this collection
  13 Dec 2021
• Date of issue
  2021

History

• Received
  09 Aug 2019
• Accepted
  29 May 2021