Next Article in Journal
Scratch as an Environment for Learning the Coordinate System by Elementary School Students
Previous Article in Journal
Microlearning for the Development of Teachers’ Digital Competence Related to Feedback and Decision Making
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Management Discourse Analysis of High- and Low-Efficacy Schools: A Comparative Study of Factors Influencing School Performance

by
Jesús García-Jiménez
1,*,
Inés Lucas-Oliva
2,3,
Javier Rodríguez-Santero
1 and
Juan-Jesús Torres-Gordillo
1
1
Department of Educational Research Methods and Diagnostics, University of Seville, 41013 Seville, Spain
2
Department of Language and Literature Teaching, University of Seville, 41013 Seville, Spain
3
Department of Philology and Translation, Spanish Language Studies, University Pablo de Olavide, 41013 Seville, Spain
*
Author to whom correspondence should be addressed.
Educ. Sci. 2023, 13(7), 723; https://doi.org/10.3390/educsci13070723
Submission received: 15 May 2023 / Revised: 10 July 2023 / Accepted: 13 July 2023 / Published: 15 July 2023
(This article belongs to the Section Curriculum and Instruction)

Abstract

:
Offering an efficient, egalitarian, and quality education is an agreed-upon goal in society that aims to guarantee upwards social mobility. For this reason, the objectives of this article are to determine how Andalusian primary schools with high and low efficiency rate their own performance, and to study in depth the factors that favour or hinder academic performance in these schools. To this end, 50 interviews were conducted with school management teams based on the ESCALA test scores. Analysis of the informants’ discourse on educational performance shows that high-performing schools are evaluated in terms of learning standards, while low-performing schools are compared with other schools that are considered similar. It is concluded that low-performing schools perform much more poorly than high-performing schools, failing to provide quality and equal education to the whole school population and perpetuating social divides. Additionally, both types of schools overlook intrinsic factors that have a negative impact on academic performance. It is necessary for them to adopt a self-critical attitude that allows them to identify room for improvement and demand necessary support.

1. Introduction

Education is one of the state issues that receives the most attention in any society. Quality education that reaches everyone equally is a concern and an objective in any territory that seeks sustainable growth and development [1,2], as it is the basis for a thoughtful society prepared for the challenges of a world in constant and dizzying evolution [3,4,5]. This is reflected in the Sustainable Development Goals (SDGs) developed by the United Nations (UN) in its 2030 Agenda [6]. Goal number 4—quality education—proposes to improve the quality of the education system in terms of equity [6]. Education, therefore, is a fundamental right of human beings to improve their emotional and social situation.
For this reason, it is essential to delve into research that sheds light on the functioning of schools from within them. It is necessary to listen to the voices of those in school systems to understand their strengths and deficiencies [7,8,9,10,11,12,13,14]. Only in this way will it be possible to form a complete picture of the situation in schools that will allow politicians and educational managers to make the right decisions and implement the necessary proposals for improvement [5,15].
In light of the above, this article has a twofold objective: (1) to determine how Andalusian schools with high and low efficiency rate their own performance, and (2) to study in depth the factors that favour or hinder the academic performance of Andalusian primary schools with high and low efficiencies.

1.1. Educational Assessment

One of the tools available to public institutions to learn about school performance and assess school effectiveness, strengths, and weaknesses are large-scale diagnostic tests for educational assessment [16,17]. These are administered centrally in schools at a given time and year, and exist both at the international level, such as the renowned PISA (Programme for International Student Assessment) report [17], and at the national or regional level. In Spain, in the Autonomous Community of Andalusia, ESCALA tests (EScritura, CÁlculo y Lectura en Andalucía [Writing, Calculating, and Reading in Andalusia]) were implemented between 2011 and 2019 [18]. These were administered in the second year of primary education (students aged 7–8 years) by the now defunct AGAEVE (Andalusian Agency for Educational Assessment) until 2019, when its functions were assumed by the Directorate General for Educational Planning and Evaluation [19]. Its main objective was to assess the Andalusian educational system, promoting the value of school evaluation itself to achieve constant improvements in the academic performance of students [19].
The administration of diagnostic tests for educational assessment has many advocates and detractors [20,21]. On the one hand, there are studies that argue that large-scale assessments are a fundamental tool in the study of school effectiveness [16], serving politicians and decision-makers in updates to the curriculum and the promotion of improved teaching practices [7,22]. For this reason, their results have a great impact on educational policies and society, fostering debate on the quality and effectiveness of educational systems and their schools [23]. In fact, there are countries such as Spain that establish among their legislative objectives the improvement of results on these large-scale assessment tests [24]. On the other hand, there are studies that agree that the objective of these large-scale tests is to promote curricular and educational improvements, but at the same time hold that their real impact on schools is minimal or null. These studies claim that standardised tests are based on results obtained in a very superficial manner that overlook important factors such as the school and sociocultural context of the students [22,25]. In line with this perspective, certain studies [21,22] criticize the use of these tests as definitive evidence to justify any decision-making related to educational reforms and plans in favour of the quality of education. Regardless of the assessment of large-scale diagnostic tests, by always taking into consideration their limitations, there is evidence that associates this research on school effectiveness—based on standardised tests—with the improvement of educational systems, especially studies focused on identifying the factors that influence school effectiveness and academic achievement [26,27].

1.2. School Effectiveness and Academic Achievement

One of the permanent objectives of society and its public administrations related to education is the constant improvement of the quality of education, which is directly linked to the efficiency of schools [2,28,29]. Some of the variables linked to greater school effectiveness that have received the most attention in the scientific literature have been attention to diversity; the systematization and adaptation of curricula to optimise available resources [30]; leadership of the management team through democratic and shared management practices based on good communication with the rest of the school community [30,31,32,33]; ongoing teacher training, leading to updated teaching practices [34,35]; and the emotional involvement of the school community, ensuring that faculty, students, and families feel a sense of belonging to the educational community [36,37,38].
The standardised way for administrations to assess school effectiveness, and thus the quality of education and educational systems, is through students’ academic performance as measured by large-scale assessment tests [20,39,40]. Academic achievement establishes the level of attainment that a given student community (a school, a school grade, a class, a student, etc.) achieves with respect to the objectives and content established in the curriculum. The administration of a context questionnaire, annexed to large-scale assessment tests, has allowed the advancement of studies on school effectiveness and academic achievement [13]. One result of this progressive work highlights the detection of schools with very high and very low efficacy based on four criteria [11,41]: high or low raw scores, growth or decrease in raw scores, high residual scores, and growth or decrease in residual scores. The residual scores are calculated by the difference between the obtained scores and the expected scores [11].
Research on the factors that positively or negatively influence academic performance is extensive [41,42,43,44,45,46,47,48,49,50]. These factors can be differentiated between those that are directly related to the educational context and those that refer to extracurricular variables [13,51]. Among the former are aspects such as the methodology implemented [52], teacher training and motivation [35,38,53], the management of the school and its management team [32], or the classroom climate [53,54,55,56,57,58]. Among the latter, gender [59,60,61]; previous academic performance; self-perception, psychological, and emotional factors [62,63]; mother tongue or immigrant status [64,65,66]; extracurricular support [36,67]; or economic, social, and cultural status (ESCS), measured by the ESCS index, stand out. The ESCS is undoubtedly one of the most studied factors, given the scientific evidence supporting its influence on academic performance [7,49,52,68,69,70,71,72,73].
Large-scale assessments provide insight into variables associated with educational performance and the equity of education systems [7]. However, it is necessary to complement these studies with qualitative research that makes it possible to detect educational processes and practices [52]. A qualitative study on the discourse of management teams in selected schools will provide first-hand knowledge of the reality experienced in these schools, and an understanding of the factors that influence school effectiveness and academic performance [14,52]. In this way, it will be possible to propose and implement improvements in educational systems that favour equity in education and reduce the existing inequality gap in schools [1,2,17,74]. This will allow administrations to offer quality education to all students, thus fulfilling those institutional educational objectives that are still a pending task in many educational systems [1,2,17,28,75].

2. Methods

To respond to the research objectives, a qualitative methodology has been developed from a descriptive perspective [76]. Based on the perceptions of members of the educational staff of primary schools in Andalusia, content analysis [77] was carried out to assess educational performance and its explanatory factors. The schools were divided into CAEF (Centros de muy alta eficacia/very highly effective schools) and CBEF (Centros de muy baja eficacia/very ineffective schools) to compare the schools’ views on the phenomenon under study.
To ensure the quality of the work being carried out, it was checked against the COREQ checklist for qualitative research [78]. Study participants were informed of the study objectives and the scope of the intervention. All participants were adults, their participation was voluntary, and it included signing in advance an informed consent form accepting the necessary conditions. The research followed the rules of the Ethics Committee for Experimentation in the Social Sciences of the University of Seville.

2.1. Participant Selection

Theoretical sampling [79] was used to select participants in select CAEFs and CBEFs. For this purpose, the criteria of residual scores set out by García-Jiménez et al. [41] and of growth or decrease of scores and residuals [8,80] were followed. These scores were calculated from the hierarchical multilevel analysis of the ESCALA tests. These tests assess the linguistic competence and mathematical reasoning of all pupils in the second year of primary school (7–8-year-old students) in Andalusia. These tests are accompanied by a context questionnaire which allows variables such as ISEC to be controlled. The results of the tests carried out in the 2010–2011 to 2016–2017 school years were used, excluding 2015–2016, due to the fact that the context questionnaire was not administered. A total of 410,030 pupils and a maximum of 2138 schools participated in these tests. The schools that participated in the 5 assessments were used for the study, totalling 1786. Following the above-mentioned criteria, a list of 100 schools was drawn up, of which 50 were CAEFs and 50 were CBEFs.
From these 100 selected schools, the objective was to reach a sample of 50 schools. After contacting 74 of the 100 selected schools, 24 declined to participate in the study due to the workload caused by COVID-19, yielding a final sample size of 50 schools to participate in the study. An appointment was arranged between the research team and the management team to conduct the interviews, guaranteeing the anonymity of the schools and the confidentiality of the information shared through the interview. An agreement was signed that allowed the audio of the interview to be recorded for later transcription, in which anonymity would be guaranteed.
Each interviewee acts as a representative of a school. The gender and years of management experience shown in Table 1 correspond to the individuals interviewed from different management teams (principal, head of studies or secretary).

2.2. Data Collection

For the study, semistructured interviews were used as a data collection strategy. This strategy is one of the most suitable means of conducting qualitative studies in the socioeducational field [81]. The aim of these interviews was to get to know the point of view of the management team on the daily work of the schools. The interview script was developed based on one used in a similar project developed in the autonomous community of the Basque Country [9,34,82]. Of the 8 dimensions used in that study, the present research focuses on the dimension “general perception, context, and evolution of the school”, whose categories and subcategories are presented in Table 2:
The interviews were conducted over 13 months (from December 2019 to February 2021) by experienced researchers from the research team, and lasted between 60 and 90 min in total. At the beginning of the fieldwork, interviews were conducted face-to-face. Due to the disruption caused by COVID-19 and to follow health recommendations, the rest of the interviews were conducted remotely, using only the audio recording as a record of the information. During interviews, only the interviewee and interviewer were present. Subsequently, the interviews were transcribed for analysis.

2.3. Data Analysis

The content analysis of the transcription of the interviews allowed the information in the interviewees’ discourse to be divided and catalogued to give it meaning [83]. The paragraph was used as the unit of analysis since the oral nature of the information prevented a precise definition of sentences. The following steps were followed to create the categories [84,85]:
  • The system used categories present in the scientific literature on the topic of interest.
  • The analysis of the information led inductively to the inclusion of new categories and the modification of existing categories.
  • The categories are complete when information saturation is reached. In other words, all collected information was reflected in the developed system of categories and subcategories.
A descriptive analysis used frequencies (F) to estimate the weight of each category, and it included a description of the categories and subcategories. To facilitate the process, the Atlas.Ti 8 computer program was used. The resulting value for all the categories was 0.81, which allows us to conclude that a good level of agreement was reached [86], and therefore, the system of categories had more than acceptable reliability.

3. Results

This section presents the analysis of the weighted categories and their content analysis. Table 3 shows the weight analysis (Frequency of interventions) of the categories for academic performance and explanatory factors of performance.
The high-performance subcategory had the highest weight (54.1%). CAEFs have a greater weight in this subcategory than CBEFs. However, it is noteworthy that more CBEFs rated their performance as high (F = 19.7%) than low (F = 83.3%). The benchmarks used to assess high or positive performance were different for CAEFs and CBEFs. CAEFs assessed their performance by reference to assessment standards, external standardised tests such as ESCALA, or educational inspection:
Emmm The educational performance I think it is mmm medium-high I think it is a bit above the average of Andalusian schools.
[School 24]
I always refer to the data we have from the AGAEVE and the sociocultural index. If we are above the Andalusian average, then we are not doing so badly.
[School 10]
There are also CAEFs that assessed their performance on the basis of the final rating system, measured by quantitative grades:
Eh, if I put it in numerical ratings as we usually do, more-or-less to be able to put a scale of value, I would put more or less the average of my school would be between 7 and 8 or so, which could be at a general level, at a global level.
[School 50]
In contrast, with the CBEFs, the influence of the context is used as a reference for assessing performance without referring, for example, to the aforementioned ESCALA tests. In other words, the assessment of high performance in the CBEFs is made in comparison with schools that they consider to be of the same level or equally problematic, not with the Andalusian schools as a whole or the reference standards pursued in the legislation in force:
But the fact is that we are not a normal school, so within the schools that are located in marginal areas, we work very well. It’s an ugly thing to say, but that’s how it is and the performance of our students is very good and they work well and the progress we have made since we started with the learning community so far has been great.
[School 19]
The subcategory with the lowest weight was low performance. In this case, the majority of the weight is provided by CBEFs (83.3%). For the subcategory of low academic performance, the CAEFs do not specify a reference standard. However, in the CBEFs, the school is again identified with schools within the same cohort as a matter of distorted logic; although in this case, to assess performance, they are compared with what would be desirable:
The academic performance of our school is very low, we are in a disadvantaged area of… So surely our data is going to bring down all the possible statistics you might have from other types of schools, right? Bear in mind that 90% of our school is of Romani ethnicity and therefore the academic performance is low.
[School 18]
Finally, the subcategory in the middle, which brings together teachers’ assessments of school performance that are neither positive nor negative, had a weight of 26.2%. In this case, the same number of CAEFs and CBEFs are used. Both CAEF and CBEF usually refer to schools with the same characteristics, either by socioeconomic index, compensatory, or rural (CPR):
Well, average, average…, it depends on the years. Bear in mind that we are CPR and so there are years when the performance is very, very favourable and other years when it is more reduced.
[School 36]
In regard to the category of explanatory factors of performance (see Table 4), the subcategory of factors contributing to performance had a weight of 40%, with a greater presence in CAEFs (70%). On the other hand, the subcategory factors hindering performance had a higher weight. In this case, its presence was higher in CBEFs (78.3%). Although the evaluations of performance tend to be positive when we delve deeper into the day-to-day work of the schools, the difficulties or potential of the CAEFs and CBEFs that condition their educational performance are mentioned.
To facilitate the interpretation of the results, a double-entry table has been constructed. In the columns, we differentiate between the factors that contribute to and hinder performance by CAEF and CBEF, and in the rows, extrinsic causes (i.e., contextual factors) —attributed to factors outside the school—and intrinsic causes (i.e., school factors)—attributed to internal factors and teaching activity—are shown (see Table 5). This extrinsic-intrinsic differentiation, supported by the scientific literature and common in studies on school effectiveness [9,10,13], helps to understand the factors in which the teaching team has the capacity to act to implement improvements, as opposed to those that are beyond its reach.
Regarding the extrinsic factors that contribute to achievement, both CBEF and CAEF refer to having a positive socioeconomic context, which values education and inculcates these values in the students:
(…) First of all, as is normal, it is the environment we are in, the involvement of the family. Well, I always say that our school is an environment of working families. In which we are used to having hard and tough work schedules where children are taught that they have to work. (…).
[School 50]
Additionally, in the case of CAEFs, they point out that having a smaller ratio allows for closer and more familiar attention. However, both CAEF and CBEF identify more intrinsic factors, i.e., factors specific to the school, which are also similar. They highlight the use of active or cooperative methodologies, good relations between teachers and families, and the positive atmosphere of coexistence:
Yes, performance was good. We made a change in the school’s methodology, to work… cooperative work, in a cooperative way, by groups, so that students who had more difficulty would also get involved, and the truth is that there was a fairly positive evolution in the courses… quite positive (…).
[School 29]
That we maintain… first, the attention to diversity that we have in the school, which is very oriented to the different educational and cognitive levels of the pupils, and second, that the entities that collaborate with us in the school work inside the classroom, so we have support inside the classroom, which improves performance.
[School 4]
The extrinsic factors that hinder performance are similar for both CAEFs and CBEFs. They refer to the conflictive social climate in which the school is located, the language barriers they face due to ethnic diversity, the low level of family involvement in education, and even in the care and hygiene of pupils:
Mainly the family does not respond in the same way as in the school where the families are structured and where the resources of the families are resources…. they are not the resources we normally have, we are talking about families that live on unemployment or in the majority of cases in the underground economy, therefore, the resource is not the same, the school is not conceived of as an institution for learning, but as an institution or a means to survive, because there they eat, there they are looked after and fundamentally they do not see it as a teaching-learning school.
[School 7]
Well, the factors that justify the performance are that the context in which we are teaching is a context with a socioeconomic and cultural index of −1.02, we are below the average for practically all of Andalusia. The Andalusian evaluation agency that used to send us reports and we have this index, we are far below the social and family context, which does not help. Families are not very aware of the importance of their children’s education, and it is not their priority.
[School 34]
To a lesser extent, schools identify causes specific to educational practice as factors hindering performance. In the case of the CAEFs, none of the schools identified factors of their own that conditioned performance. In the case of the CBEFs, although this is not reflected in the results, the work they carry out with families, in teacher training, and in the use of methodologies such as learning communities stands out. Therefore, the context itself limits the improvement of performance and results, despite the efforts of the educational community:
Of course, that’s why the curricular level is low. Even if they could have a good curricular base and have skills and so on, it is limited because they are not accompanied by their social or family environment, or often by resources. They are not the same as other pupils who go to school in another area. So, this limits them, and their level is almost always below average.
[School 14]
Well, the performance of our school, apart from the fact that the training of the teaching staff is excellent and that we work in an innovative way and in learning communities, the performance does not exactly reflect the results that are obtained because we have secondary schools here, we take in children from other schools with a high rate of school failure and absenteeism, which makes it difficult to have continuity. (…).
[School 13]

4. Discussion

The results have made it possible to meet the objectives proposed in this study. In the first objective, the aim was to determine how high- and low-efficiency schools in Andalusia assess their own performance. The results allow us to acquire in-depth knowledge of the standards used as a reference by both types of schools and the different perspectives that CAEFs and CBEFs adopt to carry out this assessment. While CAEFs assess their performance by taking external standardised assessment tests such as the ESCALA as a reference or establish comparisons with all Andalusian schools, CBEFs make their assessment by taking only schools with similar sociocultural and economic realities and contexts as a reference. Using the problems and difficulties of the economic, social, and cultural context as a defence can lead to complacency and imply a lack of honesty on the part of the school staff, leading them to ignore the educational shortcomings of the school itself. Although the ESCS is one of the factors with a strong impact on academic performance [7,71,87,88], justifying poor performance by this factor and ignoring the rest of the variables related to the educational context (other than extracurricular factors beyond their control) may imply the avoidance of responsibilities as an educational centre. The reflections, as well as the individual and collective self-criticism, of the teaching staff, the management team, and the educational community in general should be a constant that identifies the factors that are within the reach of this community to improve and that have a positive impact on student performance.
Similarly, in regard to the first objective, this study also allows us to affirm that CBEFs have insufficient academic performance and have a much lower performance than CAEFs. This implies a perversion of the system, which does not offer quality education equally among the student population. A system that does not guarantee equal quality educational opportunities among its citizens, especially among the most disadvantaged, is a system that aggravates social inequalities, failing to comply with the SDGs contained in the 2030 Agenda of the United Nations.
To reduce this gap and democratize the education system, it may be necessary to offer support to those schools with the greatest difficulties in achieving satisfactory academic performance; however, it is essential to offer the right kind of support. Understanding what type of aid could improve their performance and make their opportunities for quality educational development equitable implies a recognition of the factors that positively or negatively influence academic performance in high- and low-efficiency schools.
This is directly linked to the second objective proposed in this work, which has also been resolved. It was proposed to delve into the factors that favour or hinder academic performance in Andalusian primary schools of high and low efficacy. It should be noted that in the discourse of high-efficiency schools, the factors that contribute to school performance have a greater weight (70%), while in those of low efficiency, the weight is inverted, with the factors that hinder school performance having the greatest presence (78.3%). It may be significant that while CAEFs are more aware of what helps them to achieve good performance, CBEFs are more focused on what prevents them from improving. Perhaps it would be positive for the latter to shift their focus and pay more attention to those factors that could improve their performance. It is important to be aware of—and very clear about—the factors that enhance performance so that they can focus on implementing them and/or requesting appropriate support.
The factors mentioned by the interviewees could be classified into two categories: extrinsic factors—outside the school—and intrinsic factors—related to the educational reality within the school and to teaching practices. For the former, both types of schools alluded to very similar factors, in line with scientific evidence. Among them, as factors that hinder performance, both CAEF and CBEF refer to the conflictive social climate in the school environment [89], language barriers in the cases of migrant children and families [36,64,65,73], and mainly the low sociocultural and economic index of the family environment [71,90,91]. With respect to extrinsic factors that favour academic achievement, the most relevant factor for the management teams of both types of schools continues to be the economic and sociocultural index of the family environment. The schools believe that a family with better resources and a higher sociocultural level that also values education naturally instils certain values and work routines in the students that promote their performance. In addition, the CAEFs mention the low ratios in the classrooms and the family environment of the school, which allow closer and more personalized attention to the students, as a factor favouring academic performance [38,53].
Regarding intrinsic factors, it should be noted that both CAEFs and CBEFs mention positive aspects of their educational work that improve academic performance; however, they make no mention of intrinsic factors that hinder it. In the case of CAEFs, no mention is made of this type of factor, while CBEFs mention positive aspects of their work, explaining that, despite their efforts, these are not reflected in improved performance due to limitations and difficulties resulting from negative extrinsic factors. Among the intrinsic factors that improve performance, both types of schools refer to similar factors. These include the implementation of active and/or cooperative methodologies, good relations with families, and a good climate of coexistence, which is consistent with the scientific literature [35,36,56,58,92].
This demonstrates a good intuition or understanding about the intrinsic factors that positively influence performance and for which there is scientific evidence. However, the discourse of the management teams lacks an awareness of the importance of identifying which intrinsic factors also hinder academic performance, with a view to seeking solutions and proposals for improvement.
Two issues should be mentioned in this regard. First, there are studies that show that the implementation of active methodologies, attention to diversity, or the promotion of a good classroom climate [35,36,56,58,92] favour academic performance, compensating for the limitations caused by a disadvantaged sociocultural and economic context. Second, the fact that neither CAEF nor CBEF identify nor recognize intrinsic shortcomings that limit or hinder quality education has an impact on the conclusions drawn about the first objective of the study. This lack of reflection and self-criticism implies a refusal of responsibility by the schools themselves for the educational performance of their students. Perhaps this is due to excessive pressure exerted on the teaching staff and their management teams by educational systems and society in general, which holds teachers totally or mostly responsible for poor or not good enough performance. This could lead the teaching staff to take a defensive stance and to ignore—wilfully or unconsciously—the shortcomings of their daily work. However, it is necessary to make this effort, both individually and collectively, to identify where there is room for improvement and to highlight these shortcomings. Only through critical introspection will teachers become aware of the aspects that they can improve, and thus, demand from the systems and their administrations the resources or tools of any kind that will allow them to work towards improvements in the academic performance of their students.
This study has certain limitations, and its results must be considered in context. The data collected correspond to primary schools in Andalusia, so they cannot be generalized to any other educational reality. Future research could replicate the present study in other geographical areas and compare the results. Similarly, mixed and/or quantitative model studies (some of which have already been published or are about to be published) could be implemented to provide a complementary perspective to these results obtained through qualitative techniques. Likewise, triangulating the information drawn from school management’s discourse with zone inspectors’ perspectives would provide an external view of the reality of the selected schools.

5. Conclusions

The present study allows us to identify differences in the assessment that high- and low-efficacy Andalusian primary schools make of their own academic performance and similarities in the recognition of intrinsic and extrinsic factors with a positive or negative influence on such performance. While high-efficacy schools evaluate their performance in global and quantitative terms, that is, comparing the results obtained in external evaluation tests such as ESCALA with all other schools, low-efficacy schools evaluate their performance according to their contextual situation, comparing themselves only with schools immersed in disadvantaged socioeconomic and cultural realities similar to their own. With respect to the factors influencing academic performance, both types of schools identify similar variables, both extrinsic and intrinsic. Among them, it is worth highlighting the importance given to the socioeconomic and cultural factors of the students’ family environment as an extrinsic factor, and the fact that no intrinsic factors with a negative influence on their performance were mentioned.
Two fundamental conclusions can be drawn from this. First, low-performing schools have a much lower performance than high-performing schools, which results in the failure of educational systems to meet their objective of offering quality and equal education to the entire school population, and consequently, in the perpetuation or even increase of the social gap that leads to more unequal and less democratic societies. Second, both types of schools evade their responsibility by ignoring the intrinsic factors (related to the educational reality and their teaching practices) that have a negative impact on academic performance.
In short, it is necessary for teaching teams to adopt a self-critical attitude that allows them to identify and recognize their internal margin for improvement, their shortcomings, and opportunities to act as faculty and as an institution to demand necessary help. At the same time, only when administrations pay attention to these concerns, listen to schools, and meet their demands will it be possible to create educational systems that offer a quality and egalitarian education that generates fairer, more democratic, and sustainable societies.

Author Contributions

Conceptualization, J.G.-J., I.L.-O., J.R.-S. and J.-J.T.-G.; methodology, J.G.-J., I.L.-O., J.R.-S. and J.-J.T.-G.; software, J.G.-J., I.L.-O., J.R.-S. and J.-J.T.-G.; validation, J.R.-S. and J.-J.T.-G.; formal analysis, J.G.-J., I.L.-O., J.R.-S. and J.-J.T.-G.; investigation, J.G.-J., I.L.-O., J.R.-S. and J.-J.T.-G.; resources, J.G.-J., I.L.-O., J.R.-S. and J.-J.T.-G.; data curation, J.R.-S. and J.-J.T.-G.; writing—original draft preparation, J.G.-J., I.L.-O., J.R.-S. and J.-J.T.-G.; writing—review and editing, J.G.-J., I.L.-O., J.R.-S. and J.-J.T.-G.; project administration, J.R.-S. and J.-J.T.-G.; funding acquisition, J.R.-S. and J.-J.T.-G. All authors have read and agreed to the published version of the manuscript.

Funding

Grant EDU2017-84649-P funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe”.

Institutional Review Board Statement

This research was adhered to the standards of the Social Sciences of the Ethical Committee of Experimentation of the University of Seville (Spain).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Not available.

Acknowledgments

The European Union “NextGenerationEU”, by the Recovery, Transformation and Resilience Plan and by the Ministry of Universities, within the framework of the Margarita Salas grants for the Requalification of the Spanish University System 2021–2023 called by the Pablo de Olavide University, Seville, in collaboration with the University of Seville from the State Project PID2019-104557GB-I00.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. OECD. Equity in Education; OECD Publishing: Paris, France, 2018; ISBN 9789264056732. [Google Scholar]
  2. OECD. Educational Opportunity for All: Overcoming Inequality throughout the Life Course; OECD Publishing: Paris, France, 2017; ISBN 9789264287440. [Google Scholar]
  3. OECD. Youth in the Education Sustainable Development Goal. In Education at a Glance 2021; OECD Publishing: Paris, France, 2021. [Google Scholar]
  4. General Asembly of United Nations Work of the Statistical Commission Pertaining to the 2030 Agenda for Sustainable Development; United Nations: New York, NY, USA, 2017; Volume Seventy-Fifth.
  5. Soares Carvalho, A.P.; Bignami, F. Social Development through (Global) Citizenship Education: The Brazilian Case. Intercult. Educ. 2021, 32, 464–475. [Google Scholar] [CrossRef]
  6. United Nation. The Sustainable Development Goals Report 2020; United Nations: New York, NY, USA, 2020.
  7. Lucas-Oliva, I.; García-Jiménez, J.; Torres-Gordillo, J.J.; Rodríguez-Santero, J. Equity and Parity in Primary Education: A Study on Performance in Language and Mathematics Using Hierarchical Linear Models. Sustainability 2022, 14, 12404. [Google Scholar] [CrossRef]
  8. López-González, E.; Navarro-Asencio, E.; Pedro, M.J.G.S.; Lizasoain, L.; Tourón, J. A Study of School Effectiveness in Primary Schools Using Hierarchical Linear Models. Bordon 2021, 73, 59–80. [Google Scholar] [CrossRef]
  9. Joaristi, L.; Lizasoain, L.; Azpillaga, V. Detección y Caracterización de Los Centros Escolares de Alta Eficacia de La Comunidad Autónoma Del País Vasco Mediante Modelos Transversales Contextualizados y Modelos Jerárquicos Lineales. Estud. Sobre Educ. 2014, 27, 37–61. [Google Scholar] [CrossRef] [Green Version]
  10. OECD. La Medición Del Aprendizaje de Los Alumnos; OECD: Paris, France, 2011; ISBN 9789264090163. [Google Scholar]
  11. Lizasoain, L. Criterios y Modelos Estadísticos de Eficacia Escolar. Rev. Investig. Educ. 2020, 38, 311–327. [Google Scholar] [CrossRef]
  12. Aguilar-Mediavilla, E.; Salvà-Mut, F.; Imbernon, F.; Oliver-Trobat, M.F.M. Influence of Qualifications in Initial Training on the Professional Development and Motivation of Primary Teachers in the Balearic Islands. Eur. J. Teach. Educ. 2021, 46, 308–330. [Google Scholar] [CrossRef]
  13. García-Jiménez, J.; Rodríguez-Santero, J.; Torres-Gordillo, J.-J. Influence of Contextual Variables on Educational Performance: A Study Using Hierarchical Segmentation Trees. Sustainability 2020, 12, 9933. [Google Scholar] [CrossRef]
  14. Martínez-Abad, F.; Lizasoain-Hernández, L.; Castro-Morera, M.; Joaristi-Olariaga, L.M. Selección de Escuelas de Alta y Baja Eficacia En Baja California (México). Rev. Electron. Investig. Educ. 2017, 19, 38–53. [Google Scholar] [CrossRef] [Green Version]
  15. Maxwell, J.A. The Value of Qualitative Inquiry for Public Policy. Qual. Inq. 2020, 26, 177–186. [Google Scholar] [CrossRef]
  16. OECD. Synergies for Better Learning; OECD Publishing: Paris, France, 2013; ISBN 9789264190641. [Google Scholar]
  17. OECD. Balancing School Choice and Equity: An International Perspective Based on PISA; OECD Publishing: Paris, France, 2019; ISBN 978-92-64-69571-9. [Google Scholar]
  18. Boletín Oficial de la Junta de Andalucía Resolución de 14 de Marzo de 2019, de La Dirección General de Ordenación y Evaluación Educativa, Por La Que Se Acuerda El Procedimiento de Aplicación de La Prueba de Evaluación ESCALA, En El Curso Escolar 2018–2019 En Los Centros Docentes de Andalucía, En Virtud de Lo Establecido En La Orden de 18 de Mayo de 2011 Que La Regula; Junta de Andalucía: Sevilla, Spain, 2019.
  19. Boletín Oficial de la Junta de Andalucía Decreto 525/2019, de 30 de Julio, Por El Que Se Extingue La Agencia Andaluza de Evaluación Educativa; Junta de Andalucía: Sevilla, Spain, 2019.
  20. Johansson, S. International Large-Scale Assessments: What Uses, What Consequences? Educ. Res. 2016, 58, 139–148. [Google Scholar] [CrossRef]
  21. Penuel, W.R. Reimagining American Education: Possible Futures for Equitable Educational Assessment. Phi. Delta Kappan 2021, 103, 54–57. [Google Scholar] [CrossRef]
  22. Martínez-Rizo, F.; Silva-Guerrero, J.E. Impact of Large-Scale Assessment on Mexico’s Education Policies. Res. Pap. Educ. 2016, 31, 556–566. [Google Scholar] [CrossRef]
  23. OECD. Low-Performing Students; PISA, OECD Publishing: Paris, France, 2016; ISBN 9789264250239. [Google Scholar]
  24. Ley Orgánica 3/2020, de 29 de Diciembre, Por La Que Se Modifica La Ley Orgánica 2/2006, de 3 de Mayo, de Educación; Junta de Andalucía: Sevilla, Spain, 2020.
  25. Reynolds, D.; Neeleman, A. School Improvement Capacity—A Review and a Reconceptualization from the Perspectives of Educational Effectiveness and Educational Policy. In Concept and Design Developments in School Improvement Research. Accountability and Educational Improvement; Oude Groote Beverborg, A., Feldhoff, T., Maag Merki, K., Radisch, F., Eds.; Springer: Cham, Switzerland, 2021; pp. 27–40. [Google Scholar]
  26. Reynolds, D.; Teddlie, C. The International Handbook of School Effectiveness Research; Routledge: London, UK, 2002. [Google Scholar]
  27. Townsend, T. 20 Years of ICSEI: The Impact of School Effectiveness and School Improvement on School Reform. In International Handbook of School Effectiveness and Improvement; Springer: Dordrecht, The Netherlands, 2007. [Google Scholar]
  28. OECD. Education at a Glance: Transition from School to Work; OECD Publishing: Paris, France, 2021. [Google Scholar]
  29. Antoniou, P.; Kyriakides, L.; Charalambous, E. How and under Which Conditions Can We Best Combine Research on School Effectiveness with Research on School Improvement? Establishing Connections Using the Dynamic Approach to School Improvement. Educ. Sci. 2022, 12, 537. [Google Scholar] [CrossRef]
  30. Intxausti, N.; Etxeberria, F.; Bartau, I. Effective and Inclusive Schools? Attention to Diversity in Highly Effective Schools in the Autonomous Region of the Basque Country. Int. J. Incl. Educ. 2017, 21, 14–30. [Google Scholar] [CrossRef]
  31. Day, C.; Gu, Q.; Sammons, P. The Impact of Leadership on Student Outcomes: How Successful School Leaders Use Transformational and Instructional Strategies to Make a Difference. Educ. Adm. Q. 2016, 52, 221–258. [Google Scholar] [CrossRef]
  32. Prasertcharoensuk, T.; Tang, K.N. The Effect of Strategic Leadership Factors of Administrators on School Effectiveness under the Office of Maha Sarakham Primary Educational Service Area 3. Kasetsart J. Soc. Sci. 2017, 38, 316–323. [Google Scholar] [CrossRef]
  33. Tichnor-Wagner, A.; Harrison, C.; Cohen-Vogel, L. Cultures of Learning in Effective High Schools. Educ. Adm. Q. 2016, 52, 602–642. [Google Scholar] [CrossRef]
  34. Lizasoain, L.; Bereziartua, J.; Bartau, I. La Formación Permanente Del Profesorado En Centros Educativos de Alta Eficacia. Bordon 2016, 68, 199–218. [Google Scholar] [CrossRef] [Green Version]
  35. Azpillaga Larrea, V.; Bartau Rojas, I.; Aierbe Barandiaran, A.; Intxausti Intxausti, N. Teacher Training and Professional Development in Accordance with Level of School Effectiveness. Rev. Educ. 2021, 2021, 155–179. [Google Scholar] [CrossRef]
  36. Azpillaga, V.; Intxausti, N.; Joaristi, L. Implicación de Las Familias En Los Centros Escolares de Alta Eficacia En La Comunidad Autónoma Vasca. Bordon 2014, 66, 27–38. [Google Scholar] [CrossRef] [Green Version]
  37. Rutledge, S.A.; Cohen-Vogel, L.; Osborne-Lampkin, L.; Roberts, R.L. Understanding Effective High Schools: Evidence for Personalization for Academic and Social Emotional Learning. Am. Educ. Res. J. 2015, 52, 1060–1092. [Google Scholar] [CrossRef] [Green Version]
  38. Khun-Inkeeree, H.; Yusof, M.R.; Maruf, I.R.; Mat, T.R.T.; Sofian, F.N.R.M. Enhancing School Effectiveness by Implementing Identified and Intrinsic Motivation Among Primary School Teachers. Front. Educ. 2022, 7, 852378. [Google Scholar] [CrossRef]
  39. Fischman, G.E.; Topper, A.M.; Silova, I.; Goebel, J.; Holloway, J.L. Examining the Influence of International Large-Scale Assessments on National Education Policies. J. Educ. Policy 2019, 34, 470–499. [Google Scholar] [CrossRef]
  40. Kauko, J.; Centeno, V.G.; Candido, H.; Shiroma, E.; Klutas, A. The Emergence of Quality Assessment in Brazilian Basic Education. Eur. Educ. Res. J. 2016, 15, 558–579. [Google Scholar] [CrossRef] [Green Version]
  41. García-Jiménez, J.; Torres-Gordillo, J.J.; Rodríguez-Santero, J. Factors Associated with School Effectiveness: Detection of High-and Low-Efficiency Schools through Hierarchical Linear Models. Educ. Sci. 2022, 12, 59. [Google Scholar] [CrossRef]
  42. Nagy, G.; Nagengast, B.; Frey, A.; Becker, M.; Rose, N. A Multilevel Study of Position Effects in PISA Achievement Tests: Student- and School-Level Predictors in the German Tracked School System. Assess Educ. 2019, 26, 422–443. [Google Scholar] [CrossRef] [Green Version]
  43. Karakolidis, A.; Pitsia, V.; Emvalotis, A. Examining Students’ Achievement in Mathematics: A Multilevel Analysis of the Programme for International Student Assessment (PISA) 2012 Data for Greece. Int. J. Educ. Res. 2016, 79, 106–115. [Google Scholar] [CrossRef]
  44. Wu, H.; Gao, X.; Shen, J. Principal Leadership Effects on Student Achievement: A Multilevel Analysis Using Programme for International Student Assessment 2015 Data. Educ. Stud. 2020, 46, 1584853. [Google Scholar] [CrossRef]
  45. Gamazo, A.; Martínez-Abad, F.; Olmos-Migueláñez, S.; Rodríguez-Conde, M.J. Evaluación de Factores Relacionados Con La Eficacia Escolar En PISA 2015. Un Análisis Multinivel. Rev. Educ. 2017, 2017, 56–84. [Google Scholar] [CrossRef]
  46. Abad, F.M.; López, A.A.C.C. Data-Mining Techniques in Detecting Factors Linked to Academic Achievement. Sch. Eff. Sch. Improv. 2017, 28, 39–55. [Google Scholar] [CrossRef]
  47. Cordero, J.M.; Manchón, C. Explanatory Factors for Achievement in Primary Education: An Analysis Using TIMSS 2011. Estud. Sobre Educ. 2014, 27, 9–35. [Google Scholar] [CrossRef]
  48. Kauffman, H. A Review of Predictive Factors of Student Success in and Satisfaction with Online Learning. Res. Learn. Technol. 2015, 23, 26507. [Google Scholar] [CrossRef] [Green Version]
  49. Gamboa, C.; Vanderhoven, C.; Maturana, E.P. Perceived Success Factors in an Outstanding School Serving Vulnerable Students: Case-Study of a Chilean Public School. Multidiscip. J. Educ. Res. 2022, 12, 1–37. [Google Scholar]
  50. Atchia, S.M.C.; Chinapah, V. Factors Influencing the Academic Achievement of Secondary School Students: A Structural Equation Model. Int. J. Instr. 2023, 16, 999–1020. [Google Scholar] [CrossRef]
  51. Holzberger, D.; Reinhold, S.; Lüdtke, O.; Seidel, T. A Meta-Analysis on the Relationship between School Characteristics and Student Outcomes in Science and Maths–Evidence from Large-Scale Studies. Stud. Sci. Educ. 2020, 56, 1–34. [Google Scholar] [CrossRef]
  52. Steinmann, I.; Olsen, R.V. Equal Opportunities for All? Analyzing within-Country Variation in School Effectiveness. Large Scale Assess Educ. 2022, 10, 2. [Google Scholar] [CrossRef]
  53. Holzberger, D.; Prestele, E. Teacher Self-Efficacy and Self-Reported Cognitive Activation and Classroom Management: A Multilevel Perspective on the Role of School Characteristics. Learn Instr. 2021, 76, 101513. [Google Scholar] [CrossRef]
  54. Yang, G.; Badri, M.; Al Rashedi, A.; Almazroui, K.; Qalyoubi, R.; Nai, P. The Effects of Classroom and School Environments on Student Engagement: The Case of High School Students in Abu Dhabi Public Schools. Compare 2017, 47, 223–239. [Google Scholar] [CrossRef]
  55. Sortkær, B.; Reimer, D. Classroom Disciplinary Climate of Schools and Gender–Evidence from the Nordic Countries. Sch. Eff. Sch. Improv. 2018, 29, 511–528. [Google Scholar] [CrossRef] [Green Version]
  56. Wang, F.; Liu, Y.; Leung, S.O. Disciplinary Climate, Opportunity to Learn, and Mathematics Achievement: An Analysis Using Doubly Latent Multilevel Structural Equation Modeling. Sch. Eff. Sch. Improv. 2022, 33, 479–496. [Google Scholar] [CrossRef]
  57. Ning, B.; van Damme, J.; van den Noortgate, W.; Yang, X.; Gielen, S. The Influence of Classroom Disciplinary Climate of Schools on Reading Achievement: A Cross-Country Comparative Study. Sch. Eff. Sch. Improv. 2015, 26, 586–611. [Google Scholar] [CrossRef]
  58. Holzberger, D.; Schiepe-Tiska, A. Is the School Context Associated with Instructional Quality? The Effects of Social Composition, Leadership, Teacher Collaboration, and School Climate. Sch. Eff. Sch. Improv. 2021, 32, 465–485. [Google Scholar] [CrossRef]
  59. Campbell, J.A.; McIntyre, J.; Kucirkova, N. Gender Equality, Human Development, and Pisa Results over Time. Soc. Sci. 2021, 10, 480. [Google Scholar] [CrossRef]
  60. Hill, A.C.; Laird, A.R.; Robinson, J.L. Gender Differences in Working Memory Networks: A BrainMap Meta-Analysis. Biol. Psychol. 2014, 102, 18–29. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  61. Muñoz-Chereau, B. Exploring Gender Gap and School Differential Effects in Mathematics in Chilean Primary Schools. Sch. Eff. Sch. Improv. 2019, 30, 83–103. [Google Scholar] [CrossRef]
  62. Lucas-Oliva, I.; Toledo-Vega, G.; Núñez-Román, F. From Neurodidactics to Language Teaching and Learning: The Emotional Approach. Theory Pract. Lang. Stud. 2022, 12, 1457–1467. [Google Scholar] [CrossRef]
  63. Wach, F.S.; Spengler, M.; Gottschling, J.; Spinath, F.M. Sex Differences in Secondary School Achievement—The Contribution of Self-Perceived Abilities and Fear of Failure. Learn Instr. 2015, 36, 104–112. [Google Scholar] [CrossRef]
  64. Elosua, P. Performance Factors and Immigration. Impact of Individual and School Variables/Factores de Rendimiento e Inmigración. Impacto de Variables Individuales y Escolares. Cult. Educ. 2019, 31, 1–30. [Google Scholar] [CrossRef]
  65. Kirss, L.; Säälik, Ü.; Leijen, Ä.; Pedaste, M. School Effectiveness in Multilingual Education: A Review of Success Factors. Educ. Sci. 2021, 11, 193. [Google Scholar] [CrossRef]
  66. Murillo, F.J.; Belavi, G. Differential Impact of School Segregation in the Performance of Native and Non-Native Students in Spain. J. New Approaches Educ. Res. 2021, 10, 85–100. [Google Scholar] [CrossRef]
  67. Wiseman, A.W. Does Inequality Stay in the Shadow? The Cross-National Effects of Educational Equity on Private Tutoring and Student Achievement. Int. J. Educ. Res. 2021, 109, 101808. [Google Scholar] [CrossRef]
  68. Mahuteau, S.; Mavromaras, K. An Analysis of the Impact of Socio-Economic Disadvantage and School Quality on the Probability of School Dropout. Educ. Econ. 2014, 22, 389–411. [Google Scholar] [CrossRef] [Green Version]
  69. Kluczniok, K.; Schmidt, T. Socio-Cultural Disparities in the Quality of Children’s Interactions in Preschools. Eur. Early Child Educ. Res. J. 2020, 28, 519–533. [Google Scholar] [CrossRef]
  70. Sciffer, M.G.; Perry, L.B.; McConney, A. Does School Socioeconomic Composition Matter More in Some Countries than Others, and If so, Why? Comp. Educ. 2021, 58, 37–51. [Google Scholar] [CrossRef]
  71. Zhao, D.; Liu, S.; Li, Q. Effects of Socioeconomic Status and Its Components on Academic Achievement: Evidence from Beijing-Shanghai-Jiangsu-Zhejiang (China). Asia Pacific. J. Educ. 2022, 1–16. [Google Scholar] [CrossRef]
  72. Murillo, F.J.; Graña, R. Incidencia de La Segregación Escolar Por Nivel Socioeconómico En El Rendimiento Académico: El Caso de Uruguay. Páginas Educ. 2021, 14, 96–120. [Google Scholar] [CrossRef]
  73. Tsai, S.L.; Smith, M.L.; Hauser, R.M. Families, Schools, and Student Achievement Inequality: A Multilevel MIMIC Model Approach. Sociol. Educ. 2017, 90, 64–88. [Google Scholar] [CrossRef] [Green Version]
  74. Schmidt, W.H.; Burroughs, N.A.; Zoido, P.; Houang, R.T. The Role of Schooling in Perpetuating Educational Inequality: An International Perspective. Educ. Res. 2015, 44, 371–386. [Google Scholar] [CrossRef] [Green Version]
  75. Costa, P.; Araújo, L. Skilled Students and Effective Schools: Reading Achievement in Denmark, Sweden, and France. Scand. J. Educ. Res. 2018, 62, 850–864. [Google Scholar] [CrossRef] [Green Version]
  76. Elo, S.; Kyngäs, H. The Qualitative Content Analysis Process. J. Adv. Nurs. 2008, 62, 107–115. [Google Scholar] [CrossRef]
  77. Bardin, L. El Análisis de Contenido; Akal Ediciones: Madrid, Spain, 1991; ISBN 978-84-7600-093-9. [Google Scholar]
  78. Tong, A.; Sainsbury, P.; Craig, J. Consolidated Criteria for Reporting Qualitative Research (COREQ): A 32-Item Checklist for Interviews and Focus Groups. Int. J. Qual. Health Care 2007, 19, 349–357. [Google Scholar] [CrossRef] [Green Version]
  79. Speziale, H.S.; Streubert, H.J.; Carpenter, D.R. Qualitative Research in Nursing: Advancing the Humanistic Imperative; Lippincott Williams & Wilkins: Hong Kong, China, 2011; ISBN 978-0-7817-9600-2. [Google Scholar]
  80. García-Jiménez, J.; Lucas-Oliva, I.; Torres-Gordillo, J.-J.; Rodríguez-Santero, J. Equidad y Paridad En Centros Educativos Andaluces: Un Análisis a Través de La Competencia Lingüística de Las Pruebas ESCALA. In Desafíos de la Investigación y la Innovación Educativa Ante la Sociedad Inclusiva; Aznar Díaz, I., Rodríguez Jiménez, C., Ramos Navas-Parejo, M., Gómez García, G., Eds.; Dykinson: Madrid, Spain, 2021; pp. 371–380. [Google Scholar]
  81. Taylor, S.J.; Bogdan, R. Introducción a Los Métodos Cualitativos de Investigación; Paidós: Barcelona, Spain, 1992; ISBN 84-7509-816-9. [Google Scholar]
  82. Lizasoain Hernández, L.; Angulo Vargas, A. Buenas Prácticas de Escuelas Eficaces Del País Vasco: Metodología y Primeros Resultados. Particip. Educ 2014, 3, 17–27. [Google Scholar]
  83. Díaz Herrera, C. Investigación Cualitativa y Análisis de Contenido Temático. Orientación Intelectual de Revista Universum. Rev. Gen Inf. Doc. 2018, 28, 119–142. [Google Scholar] [CrossRef] [Green Version]
  84. Corbeta, P. Metodología y Tecnicas de Investigación Social. Acta Univ. Agric. Silvic. Mendel. Brun 2010, 53, 3–419. [Google Scholar]
  85. McMillan, J.; Schumacher, S. Investigación Educativa; Pearson: Upper Saddle River, NJ, USA, 2005. [Google Scholar]
  86. Krippendorff, K. Reliability in Content Analysis: Some Common Misconceptions and Recommendations. Hum. Commun. Res. 2004, 30, 411–433. [Google Scholar] [CrossRef]
  87. Finch, H.; Finch, M.E.H. The Relationship of National, School, and Student Socioeconomic Status with Academic Achievement: A Model for Programme for International Student Assessment Reading and Mathematics Scores. Front. Educ. 2022, 7, 857451. [Google Scholar] [CrossRef]
  88. Willms, J.D.; Tramonte, L. The Measurement and Use of Socioeconomic Status in Educational Research. In The SAGE Handbook of Comparative Studies in Education; SAGE Publications Ltd.: London, UK, 2019. [Google Scholar]
  89. Murillo, F.J.; Carrillo, S. Desigualdad Socioespacial y Segregación Escolar En La Ciudad de Lima. Rev. Peru. Investig. Educ. 2021, 13, 55–88. [Google Scholar] [CrossRef]
  90. Murillo, F.J.; Martínez-Garrido, C. Perfiles de Segregación Escolar Por Nivel Socioeconómico En España y Sus Comunidades Autónomas. Rev. Electron. Investig. Eval. Educ. 2019, 25, 12917. [Google Scholar] [CrossRef] [Green Version]
  91. Shi, J.; Zhang, Y.; Liu, F.; Li, Y.; Wang, J.; Flint, J.; Gao, J.; Li, Y.; Tao, M.; Zhang, K.; et al. Associations of Educational Attainment, Occupation, Social Class and Major Depressive Disorder among Han Chinese Women. PLoS ONE 2014, 9, e86674. [Google Scholar] [CrossRef]
  92. Rojas, I.B.; Larrea, V.A.; Olariaga, L.M.J. Metodología de Enseñanza En Centros Eficaces de La Comunidad Autónoma Del País Vasco. Rev. Investig. Educ. 2017, 35, 93–112. [Google Scholar] [CrossRef] [Green Version]
Table 1. Demographic data of participants.
Table 1. Demographic data of participants.
DimensionVariablesN
GenderMale26
Female24
Type schoolCAEF27
CBEF23
FundingPublic43
Private7
Years of management experience0–423
5–88
9<19
Table 2. Categorical system used in the analysis.
Table 2. Categorical system used in the analysis.
DimensionCategoriesSubcategories
General perception, context, and evolution of the schoolAcademic Performance(1) High performance/Positive assessment
(2) Underperformance/Negative assessment
(3) Average/Neutral evaluation
Explanatory factors for performance(1) Factors contributing to performance
(2) Factors hindering performance
Table 3. Analysis of the weight of the academic performance category.
Table 3. Analysis of the weight of the academic performance category.
CategoryFSubcategoryTotalCAEFCBEF
Academic performance37.9%(1) High performance/Positive assessment54.1%63.6%36.4%
(2) Underperformance/Negative assessment19.7%16.7%83.3%
(3) Average/Neutral rating26.2%50%50%
Table 4. Analysis of the weight of the explanatory factors of performance.
Table 4. Analysis of the weight of the explanatory factors of performance.
CategoryFSubcategoryTotalCAEFCBEF
Explanatory factors of performance62.1%(1) Factors contributing to performance40%70%30%
(2) Factors hindering performance60%21.7%78.3%
Table 5. Factors favouring or hindering performance, mentioned in the discourse of management teams.
Table 5. Factors favouring or hindering performance, mentioned in the discourse of management teams.
Factors Contributing to PerformanceFactors Hindering Performance
CAEFCBEFCAEFCBEF
Extrinsic factors
(contextual factors)
-
Positive economic and sociocultural context.
-
Disadvantaged economic and sociocultural context.
-
Little family involvement in the education and care of pupils.
-
Ethnic diversity with language barriers.
-
Low classroom ratios.
-
Conflictual social climate.
-
School absenteeism.
-
Irregular enrolment of pupils (throughout the school year).
-
Difficulties caused by COVID-19.
Intrinsic factors
(school factors)
-
Implementation of active and cooperative methodologies.
-
Collaboration and good communication with families.
-
High motivation and involvement of teachers and students.
(-)1 Good relations with families.
(-)1 Good teacher training.
(-)1 Work by learning community.
-
Positive and friendly atmosphere among teachers and pupils.
-
Attention to diversity.
-
Concern for motivating students.
(-)1 Factors that are rated positively but do not have an impact on performance due to extrinsic causes.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

García-Jiménez, J.; Lucas-Oliva, I.; Rodríguez-Santero, J.; Torres-Gordillo, J.-J. Management Discourse Analysis of High- and Low-Efficacy Schools: A Comparative Study of Factors Influencing School Performance. Educ. Sci. 2023, 13, 723. https://doi.org/10.3390/educsci13070723

AMA Style

García-Jiménez J, Lucas-Oliva I, Rodríguez-Santero J, Torres-Gordillo J-J. Management Discourse Analysis of High- and Low-Efficacy Schools: A Comparative Study of Factors Influencing School Performance. Education Sciences. 2023; 13(7):723. https://doi.org/10.3390/educsci13070723

Chicago/Turabian Style

García-Jiménez, Jesús, Inés Lucas-Oliva, Javier Rodríguez-Santero, and Juan-Jesús Torres-Gordillo. 2023. "Management Discourse Analysis of High- and Low-Efficacy Schools: A Comparative Study of Factors Influencing School Performance" Education Sciences 13, no. 7: 723. https://doi.org/10.3390/educsci13070723

APA Style

García-Jiménez, J., Lucas-Oliva, I., Rodríguez-Santero, J., & Torres-Gordillo, J. -J. (2023). Management Discourse Analysis of High- and Low-Efficacy Schools: A Comparative Study of Factors Influencing School Performance. Education Sciences, 13(7), 723. https://doi.org/10.3390/educsci13070723

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop