Strategic-motivational profile and academic achievement in primary school students

Perfil estratégico-motivacional y rendimiento académico en alumnado de Educación Primaria

Marta Martínez Vicente

Universidad Isabel I, España

José Manuel Suárez Riveiro

Universidad Nacional de Educación a Distancia (UNED), España

Carlos Valiente Barroso

Universidad Europea Miguel de Cervantes (UEMC), España

Esta obra está bajo unaLicencia Creative Commons Atribución-NoComercial 4.0 Internacional.

A self-regulated student is one who participates actively in their own learning, a process where cognitive, metacognitive, motivational, and behavioral variables blend harmoniously. Consequently, a student’s profile or role depends on a broad range of variables pertaining to different dimensions, not only cognitive abilities, but also affective-motivational aspects, an area of great emphasis in recent years. Research that uses scientific evidence to support the dissemination and implementation of educational proposals that apply active, innovative methodologies in the teaching- learning process, in synergy with development of emotional competencies that favor teaching and learning, gives high priority to these variables (Muntaner et al., 2020). All this has taken shape in a new paradigm that blends the knowledge of neuroscience with contributions from education. Taking the name of neuroeducation or neurodidactics (Bullón-Gallego, 2017; Tapia et al., 2018), this paradigm focuses on the student as protagonist in the learning process (Muchiut et., 2018).

Some notable variables involved in learning are perceived stress, attitudes toward study, academic self-concept and learning strategies used by the student. Along with psychoemotional stability, these factors determine one’s success or failure in learning, as measured by academic achievement (Valiente-Barroso et al., 2020). Consequently, the role of each student is defined and outlined by a multiplicity of variables that converge in meaningful, pragmatic, functional learning, where cognitive processes determine appropriate application of different learning strategies (Rodríguez-Pérez & Madrigal-Arroyo, 2016). This has led to self-regulated learning as the object of systematic reviews analyzing the evidence produced by recent research on self-regulation (Dent & Koenka, 2016; Panadero, 2017; Puustinen & Pulkkinen, 2001; Rosário et al., 2014; Sáez et al., 2018), as well as many psychoeducational studies based on the interrelationship between cognitive and affective-motivational factors of learning, their influence on academic achievement (Ben-Eliyahu & Linnenbrink-García, 2015; Ellis et al., 2014; Gaeta et al., 2012; Karabenick & Zusho, 2015; Martínez-Vicente & Valiente-Barroso, 2019; Suárez-Valenzuela & Suárez-Riveiro, 2019), and consequently, on scholastic success or failure (Yan, 2020).

Self-regulation is a key factor that should be considered in all study plans. It involves a holistic view of learning that includes both cognitive and self-regulating strategies. The latter include metacognitive strategies, motivational strategies and strategies for managing and monitoring resources (Barca et al., 2013; Suárez & Fernández, 2013; Suárez et al., 2016; Suárez-Valenzuela & Suárez-Riveiro, 2019), all of which are essential to improved academic achievement. Students who use these types of strategies have been shown to practice better management of time and learning resources, key factors in school work. Consequently, they manifest greater security, confidence and persistence. This is reflected in their school grades (Barreto-Trujillo & Álvarez-Bermúdez, 2020; Barrios & Frías, 2015; Fernández et al., 2013; Panadero & Alonso-Tapia, 2014; Rodríguez et al., 2017). In all of this process, one of the ultimate purposes is the development of metacognition that will allow the student to be aware of their mental and psychological processes when performing a task. These are evident when the student is able to monitor, plan and reflect during all phases of learning (DiFrancesca et al., 2016). Thus, when this metacognitive knowledge is attained, students become the true protagonist in their process, exhibiting their skills as autonomous, strategic and, therefore, self-regulating learners (De la Fuente et al., 2018; García et al., 2016; Mejía-Rodríguez et al., 2018). Results from the meta-analysis by Dent and Koenka (2016) confirm the influence of cognitive and metacognitive processes which are part of self-regulated learning in academic achievement. Therefore, educational programs should address academic motivation, going beyond the strictly curricular content. By doing so, students improved self-efficacy beliefs and value expectations (Cerezo et al., 2019) will lead to improved effort regulation, interest, information processing, and overall, the use of learning strategies, which imply better academic achievement (Cueli et al., 2013; Rodríguez et al., 2014; Stoeger et al., 2015; Suárez et al., 2016; Zimmerman, 2011).

Certain intra-individual motivational variables that define the student’s psychological profile, including academic self-concept, have been shown to mediate scholastic and personal adjustment through direct relationships with academic achievement and engagement in learning. For some time, then, there has been a call to establish support networks at school that favor positive self-perception and that revolve around academic motivation and self-concept. In this way, the concept of student profile expands well beyond that of simply a learner (Inglés et al., 2015; Veiga et al., 2015). A students’ expectations of being competent and of successfully carrying out tasks with academic subject matter is called perceived self-efficacy; it has become established as one of the strongest variables in predicting academic performance (Cerezo et al., 2019; Schneider & Preckel, 2017). This variable has been explained through studies that show significant, positive relationships between perceived self-efficacy, persistence in academic work, and general achievement (Honicke & Broadbent, 2016; Multon et al., 1991; cited in Garzón et al., 2021), as well as other studies of the directional relationship between the two variables, finding significant, positive relationships in both directions, even if academic achievement’s influence on perceived self-efficacy is the stronger of the two (Talsma et al, 2018). In addition to the foregoing, one must consider the protective effect of certain variables on self-regulated learning. In the case of academic goals, as cognitive representations of future events, they guide students’ behavior in the academic context, thereby constituting a motivational support for performing scholastic tasks, where perceived academic and social support are present as protective variables for certain students (Gaeta et al., 2017; Gaxiola & González, 2019).

Academic achievement may constitute one of the most important dimensions in the teaching-learning process of students. It is a multi-factorial phenomenon influenced by many variables, which make it hard to properly conceptualize. It has been called scholastic achievement, academic achievement and scholastic aptitude, referring in any case to synonymous concepts; in the practice and experience of school, academics, and teaching, distinctions are a mere question of semantics. Beyond any such considerations, concern for the study of academic achievement has always aroused interest from various fields, which offer different lines of research whereby we can approach the complexity of the term by trying to understand its meaning both inside and outside the school context. Research in this regard has made it possible to develop theories with regard to learning and teaching methodologies; these in turn explain common, daily problems in the life of students (Castedo et al., 2016). From a didactic point of view, achievement has generally been measured by considering the outcomes of students’ tests and assignments, and assigning a number that represents the level of development attained in the different areas or subjects, thus representing their acquisition of knowledge in each subject according to previously formulated didactic objectives and evaluation criteria (Ramudo et al., 2017). It can be considered to be a student’s demonstrated level of knowledge in a given area of the curriculum, with reference to their age group and academic level; from this perspective, then, the corresponding assessment processes produce a measured value. But we must bear in mind other variables that intervene in academic achievement, among which are cognitive or intellectual level, aptitudes, motivation, personality, study techniques and habits, expectations and interests (Barreto-Trujillo & Álvarez-Bermúdez, 2020).

Previous studies have focused on the relationship between self-regulated learning and academic achievement to promote research in development of promotional, preventive, and compensational programs that improve students’ academic adaptation (Elvira-Valdés & Pujol, 2014; Gaxiola & González, 2019). Students with self-regulating strategies are thus confirmed to have an optimal level of academic achievement (DiFrancesca et al., 2016; Rodríguez et al., 2014; Yan, 2020). In this regard, statistically positive relationships have been demonstrated between self-regulated learning, motivation, self-efficacy and academic achievement (El-Adl & Alkharusi, 2020), and specifically in achievement in subjects like mathematics (Lawrence & Saileella, 2019). These students are characterized by an awareness that their intrinsic motivation when engaging in tasks determines academic success, they also show perseverance, interest and personal initiative outside the learning context (Álvarez-Bermúdez & Barreto-Trujillo, 2020; Rivera, 2017; Valle et al., 2010).

Continuing in this approach, the general aim of the present study was to examine how different variables of a student profile that are related to self-regulated learning, such as learning strategies and academic motivation, relate to academic achievement in Language Arts, Mathematics, English as a Foreign Language and overall academic achievement. Significant differences were expected in academic achievement (in Language Arts, Mathematics, EFL and overall), in accordance with low, medium, and high levels of learning strategies and academic motivation. We also expected to demonstrate the ability of these variables to predict academic achievement in upper primary education.

Continuing in the line of study initiated in the 1990s by researchers interested in demonstrating the relevance of a numerous, diverse set of variables in learning --including cognitive, metacognitive and affective-motivational strategies-- the present study seeks to reinforce these previous studies. Toward this end, the general objective of this study was to analyze the association between learning strategies, academic motivation and achievement in a convenience sample made up of students in upper primary school (5th and 6th grades), since this period represents a turning point and a transition between two stages of education, leading into significant changes in terms of student autonomy, and the demands and complexity of their studies.

In view of these results, there is a tendency that greater use of learning strategies, along with optimal motivation towards schoolwork, imply higher academic achievement in general. This has also been confirmed in previous studies that explain the direct relationship between students’ study habits and their overall academic achievement, and that explain the academic difficulties that stem from a lack or misuse of learning strategies, thereby hindering the development of deep, meaningful learning and of putting what has been learned to use. The information presented in this paper supports ideas about the effectiveness of training in learning strategies. Along with other variables such as previous knowledge, academic goals, beliefs, expectations, self-concept, effort, engagement, and demands of the tasks assigned, use of learning strategies is a determining factor in the achievement of satisfactory academic outcomes (Alvarado et al., 2014; Martín-Antón et al., 2012).

Findings from this study that indicate direct relations between attitude toward study and self-concept reinforce results from prior studies that explain the positive effects of these motivational variables on emotional control, and on information- seeking and effective problem-solving in the learning process (González-Cabanach et al., 2017; Panadero & Alonso-Tapia, 2014. Essential among these attitudes towards learning, intrinsic motivation, initiative, perseverance and effort all significantly improve students’ academic achievement at all stages of education, when students are able to adequately implement self-regulatory strategies in their learning (Cueli et al., 2013; Ellis et al., 2014; Suárez et al., 2016). In this study there were students with different levels of learning strategies and academic motivation, as evidenced by the cluster analysis where we were able to differentiate three types of students. The first group was characterized by a high level of learning strategies and academic motivation, the second group by medium levels, and the third group by a low level of learning strategies and academic motivation. In view of the obtained results, there were notable differences between the high-level group and the medium- and low-level groups in academic achievement in Language Arts, EFL, and general academic achievement; significant differences in the subject of Mathematics were also found between students with a high level of learning strategies and academic motivation and those with a low level. All these results stand in agreement with other previous results claiming that students with negative achievement outcomes show little knowledge of learning strategies (Barreto-Trujillo & Álvarez-Bermúdez, 2020; Barrios & Frías, 2016; Rodríguez et al., 2017), deficient affective-motivational conditions, and unorganized previous knowledge, and are unable to properly manage their time and the effort applied to tasks (Fernández et al., 2013; Panadero & Alonso-Tapia, 2014).

This study has confirmed that complementary learning strategies such as group work or extracurricular activities, as well as academic self-concept, are predictive of achievement in the subjects considered, as well as of academic achievement in general. These results follow the line of other researchers, where evidence shows that students with greater use of learning strategies, including the cognitive, metacognitive and motivational, obtain higher academic achievement (Cueli et al., 2013; Rodríguez et al., 2017; Stoeger et al., 2015). This reinforces previous studies where higher-achieving students are considered to have greater self-regulation strategies, applying reflection before, during and at the end of learning (Yan, 2020). All this comes as a consequence of the cognitive and metacognitive training they have gained by constantly taking actions to plan and monitor, while simultaneously controlling motivation and affect. This allows them to become self-regulated, autonomous, strategic learners who supervise their own learning process, thus ensuring optimal learning (De la Fuente et al., 2018; García et al., 2016; Mejía- Rodríguez et al., 2018; Valle et al., 2010). Regardless of the learning context, these students become experts when they are able to activate cognitions and behaviors to control comprehension, attention, and review, ultimately reaching the goals they have set (Ellis et al., 2014; Suárez et al., 2016). The result of this whole process can be seen in the attitudes of motivation, initiative, effort and perseverance that reveal how learning, motivation and achievement are directly related to attitudes towards schoolwork and study (Álvarez-Bermúdez & Barreto-Trujillo, 2020; Panadero & Alonso-Tapia, 2014; Rivera, 2017).

Limitations of this study include those typical of cross-sectional studies: Carried out at a specific moment in time, the study does not allow for comparison of the same students’ outcomes over time. Furthermore, since the study addresses a specific stage and level of education, results cannot be extrapolated or generalized to the entire student population. Longitudinal studies along these same lines, which allow the generalization of these exploratory results to the student population of all educational stages, would be of benefit. Another limitation is the use of a self-report instrument for data collection; this can lead to bias in the results --which are marked by a certain subjectivity-- although one must emphasize the characteristic frankness of students at these early ages. Regarding the instrument used, another limitation is its answer range of three options, unusual in the assessment of self-regulated learning, though we must note that this instrument was chosen for this investigation owing to the scarcity of instruments for measuring self-regulated learning, especially in primary education. One of the long-time challenges for researchers has been precisely that of constructing instruments to assess self-regulated learning (Rósario et al., 2014; Sáez-Delgado et al., 2021). As for measuring perceived self-efficacy, a very important motivational variable in explaining academic achievement, a very simplistic, one-item measure was used, which may suggest a limitation when we consider the lack of significance found when correlating these self-efficacy items with students’ grades in the same subjects. Additionally, another limitation is the use of school grades in certain subjects as the only variable to measure academic achievement; the competency approach should be taken into account, documenting its direct relationship with learning, since competency assessment is currently proposed as a short-term goal (Muntaner et al., 2020). It is important to recognize that greater competency development is a cognitive consequence of a student’s intrinsic motivation, and is fundamental for acquisition of the learning to learn competency, in increasingly competitive, globalized contexts (Godás-Otero et al., 2015). Finally, another study limitation to be added is the non-normality of most variables, which recommended the use of nonparametric tests.

In light of the foregoing analysis, the conclusions of this study center around the priority that should be given to learning strategies and academic motivation in the educational context, as a means and an end in themselves, for attaining meaningful, practical and functional learning with increased academic achievement, going beyond quantitative ratings to address competencies. In this way, gaps in the teaching-learning process can be bridged, where even today the process is still focused on outcomes, with less attention on the continuous progress that takes place from the moment a student begins their journey through the educational system.

How to reference this article: Martínez Vicente, M., Suárez Riveiro, J.M., & Valiente Barroso, C. (2023). Strategic-motivational profile and academic achievement in primary school students. Educación XX1, 26(1), 141-163. https://doi.org/10.5944/educxx1.31852