Carmela García-Marigómez
Vanessa Ortega-Quevedo
Cristina Gil-Puente3- 1Departamento de Didáctica de las Ciencias Experimentales, Sociales y de la Matemática, University of Valladolid, Valladolid, Spain
- 2Universidad Complutense de Madrid, Madrid, Spain
- 3Universidad de Valladolid, Valladolid, Spain
Introduction: Neglecting the role of attitudes in didactic change is a serious obstacle to progressing toward the inclusion of the Nature of Science and Technology (NoST) in the classroom and achieving a scientific culture that enables the development of a critical and socially engaged citizenship capable of addressing contemporary societal challenges.
Method: For this reason, this study presents the design and validation of an assessment tool that allows attitudes to be collected in a holistic way, taking into account the cognitive, affective and conative components of trainee and practicing Primary School (PS) teachers toward the teaching of NoST. For this purpose, an instrumental-psychometric study was carried out. A sample of 210 subjects participated in the validation of the questionnaire.
Results: The statistical analyses of the scale show that it has an adequate content validity, an appropriate construct validity with a good fit to the theoretical model, and a high level of reliability. Furthermore, a first approximation to the description of the attitudinal profile indicates that thereis, in general, a positive attitude toward NoST teaching.
Discussion: It is concluded, on the one hand, that the instrument is optimal and adequate for assessing attitudes and, on the other hand, that teacher training should consider both the cognitive and affective factors that hinder the transformation of educational practices in the field of science teaching.
1 Introduction
In today’s society, citizens needs to be prepared to make informed decisions about their environment (Wagner, 2014). This is because both public and private spheres need to act on socio-scientific issues (Vázquez Alonso and Manassero Mas, 2018; García-Marigómez et al., 2023).
For this reason, scientific and technological literacy (STL) has become a fundamental pillar of Global Citizenship Education (GCE) (Fueyo et al., 2015; Thompson, 2016), as it is directly linked to the Sustainable Development Goals (ONU, 2015) and, more specifically, to Education for Sustainable Development (ESD). Through STL, it is possible to foster critical thinking, creativity, communication, and collaboration (Tenreiro-Vieira and Vieira, 2021)—competences essential for imagining and building a fairer and more sustainable world.
STL is therefore a key element in integral development. However, the propaedeutic model of science that has been and is still being transmitted from educational institutions (Vázquez Alonso and Manassero Mas, 2018) has caused multiple generations to acquire a negative (unattainable knowledge) and simplistic (little understanding) view of science, distancing and excluding them from scientific training, and from critical and active participation in socio-scientific issues and, by extension, from engagement with the challenges of global citizenship (Pérez-Foguet and Lazzarini, 2019; Yemini et al., 2019).
Given this situation, a shift in educational processes is needed one that promotes a form of scientific literacy accessible to all, understood not merely as the acquisition of content but as an interactive and participatory educational process that encourages critical awareness, civic engagement, and the construction of alternatives in favor of social justice and sustainable development.
To address the errors arising from transmissive teaching, a meta-knowledge about science based on interdisciplinary reflections emerges: the Nature of Science and Technology (NoST) (Acevedo et al., 2016). It emphasizes that science transcends content, as it is intrinsically linked to historical, philosophical and sociological circumstances.
There are currently different proposals on what to consider in the teaching and learning of the Nature of Science (NoS), such as the proposal by Lederman et al. (2002), Matthews (2012), McComas (2002), Osborne et al. (2003), the Similar Family Approach by Irzik and Nola (2014), Erduran and Dagher (2014), and the Science-Technology-Society (STS) Tradition updated by Manassero-Mas and Vázquez (2019). Although all offer important perspectives that should be taken into account, in the present research a greater affinity toward the STS Tradition can be observed, given that it incorporates aspects related to epistemology, external sociology, internal sociology and triadic influence.
The inclusion of NoS stimulates the acquisition of a more humanistic scientific-technological culture (which takes into account values and attitudes). This is crucial if we bear in mind that emotions influence and determine new learning (Mayer et al., 2000). Therefore, it is essential to consider knowing how to be (attitudes and values) so as not to fall into the error of teaching and learning exclusively cognitive content.
2 Theoretical framework
2.1 Scientific and technological literacy in primary school teacher
If we take into consideration the social and educational characteristics described above, we can argue that science education (SE) is still dominated by technical rationality. These ideas reveal the importance of approaching SE from a transformative vision.
Therefore, teacher development must be understood as a continuous process of theoretical-practical integration in which the teacher is conceived as a learner, innovator and researcher who participates in the construction of the science of teaching science (Furió and Carnicer, 2002).
In this line, the studies initiated by Shulman (1986) on the professional knowledge of teachers stand out. Specifically, from this research we focus on the ability to transform an object of knowledge into an object of teaching (Chevallard, 1985), in other words, in the pedagogical content knowledge (PCK).
The concept of PCK has been studied by various authors and teams. In the case of SE, PCK has been considered a useful theoretical framework since its origin and, therefore, we can find various proposals, such as Magnusson et al. (1999) and Gess-Newsome (2015) or the Refined Consensus (Carlson and Daehler, 2019). These models, given that they are based on advances in cognitive psychology, do not include aspects linked to affective variables, such as attitudes, in the components to be considered in teacher training and development. Other models, such as the hexagonal model (Acevedo and García-Carmona, 2016) or the ReCo model (Loughran et al., 2004), consider affective variables, but from an exclusively cognitive perspective, and the conative or emotional component of attitude is overlooked. In this sense, it is necessary to reflect on the role of these affective variables in the teaching of NoST in order to address the factors that prevent the implementation of these contents in the classroom, given their relevance in the creation of an authentic STL.
2.2 Attitudes in didactic change
Taking the previous ideas into account, it becomes clear that teacher education must be based on a process that fosters didactic change (Mellado, 2003). This change involves not only professional transformation but also personal development. Teaching is not merely a cognitive process; it requires emotional commitment, engaging both the head and the heart, as it tests personal emotional and cognitive competencies as well as professional practice (Day, 1999). Therefore, learning changes who we are and what we are capable of doing—it is an experience of identity (Wenger, 1998). Identity is particularly relevant as it highlights the need for teacher learning and development to go beyond knowledge and skills (Avraamidou, 2014).
“Emotions influence the goals that teachers set and indicate the intensity of their relationships with ideas, their beliefs about science, others, and science teaching” (Rivera Maulucci, 2013, p. 137). This idea underscores that the development of Pedagogical Content Knowledge (PCK) cannot be limited to cognitive aspects alone if it is to contribute meaningfully to the construction of professional teaching identity.
It is important to note that evidence shows changes are more likely to become embedded when they incorporate attitudes and values (Sanmartí, 2001). Therefore, the focus on attitudes must be twofold: they should be seen both as a tool to achieve positive learning outcomes, given their influence on learning and behavior, and as essential and valuable content in science education. However, at present, emotional aspects remain largely absent from teacher education programs and, consequently, from student training plans (Bisquerra and Pérez, 2007).
With regard to knowing how to be, it is important to pay attention to the concept of attitude as a construct. Attitudes can be positive and negative, i.e., they are evaluative predispositions with a motivational component that implies affectivity and a tendency to action (Sarabia, 1992). Moreover, they have a learned character (Morales, 2000) which makes them a fundamental factor to take into account in the educational field due to their influence on behavior and learning.
There are multiple models that study the structure of attitudes. Following the three-dimensional model (Martín-Baró, 1983; Hogg and Vaughan, 1995), we can identify a clear parallelism with the structure of competences and, therefore, with educational objectives. These three components are: the cognitive component, which refers to the subject’s knowledge, beliefs and opinions about the object, taking a position in favor or against; the affective component, which refers to feelings, to the emotions of acceptance or rejection, liking or disliking, that are activated when faced with a stimulus; and the conative component, which refers to the declarations of intentions before the object of attitude. These components differ from one another, but converge intensely in that they share a common basis (the representation of the same attitude).
If we transfer this construct to Science Education, the literature reveals that there are problems derived from the lack of precision of the attitude, the attitude object and the absence of a single construct (Bogdan and Meneses, 2021; Manassero Mas and Vázquez, 2002; Vázquez and Manassero, 1995; Vázquez and Manassero Mas, 1997).
In this sense, the literature puts together taxonomies to organize and support the study of this construct and to define more accurately and precisely the attitudinal objects. One of the widely accepted classifications is the one proposed by Gardner (1975): attitudes toward science (a more affective and evaluative approach toward the elements involved in learning science) and scientific attitudes (with a cognitive character and linked to scientific thinking). However, the objects of attitude in science education cannot be limited to the attitude toward learning science. Hodson (1988) reveals that school is a key element in the shaping of a balanced attitude and, for this reason, he includes the attitude toward SE in his taxonomy. This category is the focus of the present study.
In summary, taking into account the ideas gathered, the manuscript is based on multiple theoretical perspectives that complement each other to support, contextualize, and operationalize the attitudinal approach (which constitutes the central construct).
3 Literature review
In recent decades, there has been an increase in interest in the study of attitudes within the theoretical framework provided by social psychology (Vázquez and Manassero, 1995). If we focus on teachers’ attitudes toward SE, the systematic literature review conducted by García-Marigómez et al. (2026) reveals that, from 2015 onwards, new areas of interest have emerged, such as critical thinking, the role of ICT and media, and the influence of attitudes. Regarding the latter, the documentary analysis indicates that, within the emphasis on knowing how to be, there is a predominant focus on the cognitive component of attitudes, while the affective and conative components are largely overlooked.
The most frequently investigated attitudinal objects are beliefs or opinions about STS issues (Barnes et al., 2015; Ozturk-Akar and Dogan, 2013), self-efficacy beliefs (Clerici, 2008; Murphy and Smith, 2012), and beliefs about teaching (Aragón Núñez, et al., 2021; Mansour, 2013). Less frequently, studies on liking or interest in scientific areas (Aguirregabiria and García-Olalla, 2022; Mateos Núñez and Martínez Borreguero, 2021; Martínez-Borreguero et al., 2022) and on beliefs about pseudoscience (Cadena-Nogales et al., 2022) are encountered.
In short, although existing instruments have contributed to the assessment of teachers’ views on the Nature of Science, several limitations remain, particularly when applied to Primary Education contexts. Many tools prioritize cognitive dimensions, are designed for secondary or higher education teachers, or do not explicitly integrate affective and conative components. As a result, they provide a partial view of teachers’ attitudes and offer limited guidance for professional development in primary science education. The instrument developed in this study addresses these gaps through a multidimensional and context-sensitive approach.
As has been noted, numerous studies have focused on teachers’ self-efficacy beliefs. However, self-efficacy represents only one dimension of the attitudinal framework of teachers, being primarily associated with the cognitive component of attitude. Therefore, this approach, limited to the cognitive dimension, fails to address the affective and conative aspects that also influence teachers’ stance toward science teaching.
This issue becomes particularly relevant when considered in light of the Theory of Planned Behavior (Ajzen and Fishbein, 1980). Attitude constitutes a determining factor in the formation of intentions and behaviors. A favorable attitude may strengthen intention even when self-efficacy is low, whereas an unfavorable attitude may weaken it despite a high perception of competence. Consequently, focusing on attitudes allows for a deeper understanding of the evaluative and motivational factors that shape teachers’ actions.
Furthermore, when the behavior has not yet been performed, attitude serves as a more accessible and stable indicator than self-efficacy, whose validity may be limited in the absence of prior experience. In this regard, examining teachers’ attitudes toward science education offers a more comprehensive perspective for analyzing the processes of teaching and learning in science.
Ultimately, it is essential to overcome the limited attention given to teachers’ attitudes, considering the influence they exert on teaching practices and, consequently, on students’ scientific competence (Talavera et al., 2018).
4 Purpose of the study
In an attempt to fill this gap, this study develops and validates an instrument to measure attitudes toward teaching NoST in trainee teachers (who have experience in classroom teaching because they have taken the Practicum course) and practicing primary school teachers. We examine teachers’ beliefs and emotions, and relate them to behavioral intentions when assessing different situations linked to epistemological content and the internal and external sociology of science. The instrument is conceived as a tool to assess attitudinal change after the training process. With the data collected to carry out the validation of the instrument, a first description and assessment of the attitudinal profile is also attempted.
5 Materials and methods
This study analyses the psychometric properties (Ato et al., 2013) of the scale: Attitudes toward teaching NoST in PS aimed at pre-service and in-service teachers. The objectives of this study are, therefore, to test the content and construct validity, and the reliability of the questionnaire, as well as to obtain a first description of the attitudinal profile of the participants.
5.1 Procedure
To achieve the objective of designing and validating the proposed tool, a process comprising five stages was established, as summarized in Figure 1 and detailed below. Firstly, a review of existing instruments was conducted, and an initial draft of the tool was developed based on the reviewed literature. Secondly, content validity was assessed through expert judgment. Thirdly, the length of the scale was reduced by means of item correlation analysis and a second round of expert review. Fourthly, construct validity was examined through confirmatory factor analysis and goodness-of-fit indices. Finally, the internal consistency (reliability) of the questionnaire was evaluated using McDonald’s Omega coefficient. For the psychometric analysis, items related to sociodemographic variables were excluded, and the software programs Microsoft Excel, SPSS v.29, and Jamovi v.24 were used.
Figure 1. Scale design and validation process.
6 Results
This section presents the results of the different stages of the psychometric study and, in addition, the preliminary results on the attitudinal profile of the participants.
6.1 Literature review of instruments and design of the first version of the questionnaire
Initially, a series of scales were reviewed in order to analyze whether they could be applied according to the needs of the study or used as a reference. Those scales intended for students were discarded.
After the selection and review of scales aimed at teachers, several instruments were identified (Aikenhead and Ryan, 1992; Manassero et al., 2003; Rubba et al., 1996; Tyler-Wood et al., 2010; Vázquez and Manassero Mas, 1997; Villafañe and Lewis, 2016; etc.), but these were few in number and had limitations, such as the language in which they were written (predominantly English) and the non-holistic approach to the attitude object and construct (opinions toward science, attitudes toward scientific research, interest in science, etc.).
Therefore, as they did not respond to the characteristics of the study itself and the context in which it is carried out, a four-point Likert scale was designed (totally disagree, disagree, agree, strongly agree). The different items were written using the traditional method, with the criteria compiled by Morales (2000): Relevance, clarity, discrimination and bipolarity, and taking into account the three attitudinal components. The cognitive component was constructed by focusing on measuring the value, usefulness or importance that teachers attach to the discipline. These were formulated as cognitive judgments centered on the views of NoST as a discipline with value for the present and future of students. In the affective component, a series of adjectives (emotions) with a strong connotative meaning were selected to focus the measurement on the direction of emotions (positive/pleased or negative/unpleased) and their intensity (high or low polarization of the score). Emotions were selected from the Atlas de significados afectivos del español-mexicano by Urbán (1980), the taxonomy proposed by Fernández-Abascal et al. (2001), and the work of Goleman (1996). The conative component was constructed using verbal formulas that denoted intention or predisposition to perform the behaviors linked to the construct. In summary, the wording of the items was carefully designed to avoid expressions related to perceived ability or teaching competence (e.g., “I am able to…”) and instead emphasized evaluative judgements, affective responses, and intentional orientations toward teaching NoST.
For the drafting of the items, reference was also made to the educational models previously analyzed: the questions of NoST according to the STS Tradition (Acevedo and García-Carmona, 2016), Project 2061 (American Association for the Advancement of Science [AAAS], 2009) and the National Research Council (1996), as they contain the appropriate topics to characterize NoST in detail. This process led to a scale of 37 items that were then submitted to expert judgment.
6.2 Content validation
For the content validity of the questionnaire, a procedure was carried out based on the judgment of three experts with recognized expertise in science education, NoST and attitudes. This number is consistent with methodological literature indicating that a small panel of highly qualified experts can provide robust qualitative validation in the early stages of scale development (Hernández-Sampieri et al., 2010). For the evaluation of the instrument, a descriptive scale was developed with four criteria (Escobar-Pérez and Cuervo-Martínez, 2008): clarity, coherence, relevance and sufficiency and four levels (with indicators) plus a section for “other comments.”
Based on the experts’ evaluation, the Content Validity Coefficient (CVC) of Hernández-Nieto (2002), which indicates the degree of agreement between the judges’ evaluations for each item, was calculated using Microsoft Excel.
The results obtained regarding the degree of agreement and content validity (Table 1) for the scale items indicate a predominantly excellent (>0.90) and good (>0.80 and < 0.90) level.
Table 1. Results of CVC.
The feedback provided by the experts highlighted items that could be improved. Specifically, modifications were made to items 1, 4, 5, 6, 7, 11, 14, 20, 21, 22, 24, 25, 26, 31, 32, and 34 related to the clarity criterion, i.e., to improve understanding.
6.3 Scale reduction
Once the necessary modifications had been made following the expert judgment validation, the instrument was administered using two types of sampling. On the one hand, a non-probabilistic snowball sampling method was employed, given that the target population was small and specialized. On the other hand, an accidental/convenience non-probabilistic sampling approach was used, as the selected sample consisted of student groups to which the researchers had access. In total, the instrument was administered to 219 Spanish-speaking participants.
Based on the results obtained from this pilot test, the scale was reduced through a Spearman correlation analysis between items. Items that did not show significant correlations with the others were submitted to a second round of expert judgment in order to assess the relevance of their removal. This decision was based on both the statistical outcome (which indicates whether the items are measuring the same dimension or diverging into unrelated aspects) and relevant literature in the field. As a result of this process, the scale was reduced from 37 to 27 items (Table 2). The Spanish version can be found in Table A1.
Table 2. Questionnaire items and dimensions in brackets.
6.4 Construct validity
To assess the construct validity of the questionnaires, a Confirmatory Factor Analysis (CFA) was performed using the SEM (Structural Equation Modeling) package (Gallucci and Jentschke, 2021; Rosseel et al., 2019) in Jamovi v.24. This type of analysis was chosen because, as previously mentioned, the scales were developed based on a theoretically pre-established structure derived from the literature on the attitude construct. Consequently, the resulting path diagram (Figure 2) reflects a hierarchical model in which a second-order factor represents the overall attitude, expressed through its three components: cognitive, affective, and conative. These components, although distinct, converge strongly due to a shared foundation (i.e., the representation of the same underlying attitude) among individuals with consistent attitudinal profiles.
Figure 2. Path diagram.
The factor loadings reveal that, in general, the relationship between observed variables and latent factors is both statistically significant and consistent, with most loadings being moderate (≥0.50) or strong (≥0.70). This suggests that the model’s structure is appropriate. For those items with lower factor loadings, their inclusion was deemed conceptually relevant by the experts involved in the second round of expert judgment. These items provide meaningful insights into the construct and help maintain balance across the different aspects represented (epistemology, internal sociology, and external sociology). For example, removing item 15 would result in a loss of valuable information concerning the affective dimension of teaching’s external sociology.
Model fit indices were analyzed (Table 3) to determine whether the proposed models fit the data satisfactorily. The Robust Weighted Least Squares estimator (WLSMV) was used, as it does not assume normality of variables and is especially suitable for CFAs with dichotomous or ordinal data (Xia, 2016). This estimator corresponds to a robust correction of DWLS. The interpretation of the results was based on scaled indices. First, absolute fit indices were considered: root mean square error of approximation (RMSEA), standardized root mean square residual (SRMR), and chi-square (χ2). Second, incremental fit indices were examined: comparative fit index (CFI), normed fit index (NFI), and Tucker–Lewis index (TLI). Third, parsimonious fit was assessed using the parsimonious normed fit index (PNFI).
Table 3. Results of the maximum likelihood parameters.
Analysis of the data indicates that the proposed models, after certain modifications (removal of non-significant paths and addition of correlations between residuals), display an adequate fit. Absolute fit indices show acceptable values for this type of model, with RMSEA ≤ 0.08, SRMR < 0.08, and a χ2/df ratio close to 3 (Browne and Cudeck, 1993; Cho et al., 2020; West et al., 2012).
Similarly, the incremental fit indices (CFI, TLI, NFI, and GFI) yielded values considered acceptable (≥0.90) and optimal (≥0.95), according to specialized literature (Bentler, 1990; Hu and Bentler, 1999; Cho et al., 2020; Lai, 2020; Xia and Yang, 2019).
Finally, in terms of parsimony, the PNFI showed appropriate values, approaching 0.80 (Byrne, 2001; Hu and Bentler, 1999).
In summary, after making adjustments to the model, the results indicate a good fit to the data. Model modifications were implemented following a theory-informed approach. Modification indices were considered only when they were conceptually coherent with the multidimensional attitudinal framework and with established interpretations of NoST-related dimensions. No modifications were introduced that altered the underlying theoretical structure of the model. The various indices used to assess model quality support the consistency and stability of the proposed relationships, thereby confirming the validity of the scale’s underlying structure.
6.5 Internal consistency
To assess the internal consistency of the questionnaire, reliability was analyzed using McDonald’s Omega coefficient (McDonald, 1999), in order to overcome the limitations associated with Cronbach’s alpha and to obtain more stable estimates (Ventura-León and Caycho-Rodríguez, 2017). The McDonald’s Omega value calculated for the scale was 0.96. The conclusion from this result is that the scale demonstrates high reliability (Campo-Arias and Oviedo, 2008).
6.6 Preliminary results
As previously indicated, the analysis of the scale was complemented by an examination of the preliminary results obtained through its application. For this purpose, SPSS v.29 was used. This software was employed to compute descriptive statistics for the attitudinal components and for the overall scale. Additionally, comparisons were made based on selected sociodemographic variables (gender, academic/employment status, age, and experience).
Since the Kolmogorov–Smirnov test yielded a p-value of 0.003, indicating that the data did not follow a normal (Gaussian) distribution, and given the ordinal nature of the variables, non-parametric statistical tests were applied: the Mann–Whitney U test for comparisons between two independent groups, and the Kruskal–Wallis H test for comparisons among several independent groups. Effect size (r) was also calculated to assess the strength of the relationships. Furthermore, Spearman’s rank correlation coefficient was used to analyze the relationship between attitudinal components and to assess the external criterion validity of the scale.
6.6.1 Results of the attitude scale toward teaching NoST in Primary Education
The overall attitude toward teaching NoST in the primary classroom can be considered to be positive, given that the mean score was 92.21 points (SE = 0.166), with 27 and 108 being the minimum and maximum possible scores, respectively.
Measures of position identify three distinct profiles. 50% of the sample expressed positive opinions or beliefs, scoring between 28 and 34 points. 25% showed highly positive attitudes, with scores above 34, while the remaining 25% exhibited negative opinions, scoring below 28.
With regard to the attitudinal components, these were found to behave similarly. As the minimum and maximum values for the cognitive, affective, and conative components ranged from 9 to 36 points, the mean scores indicate that participants considered the subject matter to be highly important or useful (M = 31.03; SE = 3.743), generally expressed positive affect toward teaching NoST (M = 30.43; SE = 4.125), and demonstrated a high behavioral intention to include NoST content in their classrooms (M = 30.75; SE = 3.927).
6.6.2 Results of the relational analysis between attitude components
The results compiled in Table 4 regarding Spearman’s correlation reveal that there is a systematic relationship between the attitude components. They are linearly, directly and highly significantly related. Positive affect is linked to high behavioral intention and favorable beliefs toward the object.
Table 4. Results of the correlational factor analysis.
6.6.3 Results of attitudes toward teaching NoST according to gender, academic/employment status, age, and teaching experience
In order to explore potential significant differences in the study results based on the sociodemographic variables considered (gender, age, teaching experience, and academic/employment status), a comparative analysis was conducted across the different groups defined by these variables. As shown in Table 5, statistically significant differences were found only in relation to age.
Table 5. Results of the hypothesis testing.
7 Discussion and conclusion
From a practical perspective, the validated instrument presented in this study can be used in both initial and in-service teacher education to diagnose attitudinal profiles, monitor changes following professional development or training programs, and identify specific dimensions that require targeted support. Conceived as a diagnostic and evaluative tool, the scale allows for the assessment of attitudinal change and the effectiveness of educational and classroom interventions. This focus is especially relevant in teacher education, as attitudes play a key role not only in teachers’ personal and professional development, but also in shaping future teaching practices and influencing students’ own attitudes toward science.
The construction of the scale took into account several psychometric challenges in attitude measurement within science education, as identified in the literature. To avoid deficiencies in reliability and validity stemming from poor definitions of the constructs involved (science and attitudes) (Vázquez and Manassero, 1995), a theoretical framework was developed that considers attitudes from the perspective of Social Psychology—providing an appropriate foundation of basic theories (Vázquez and Manassero, 1995)—and science from the metacognitive perspective of NoST. This approach addresses key innovations in science teaching and learning, clarifies the object of the attitude (Bogdan and Meneses, 2021), makes its multidimensionality explicit (Manassero Mas and Vázquez, 2002), and promotes affective aspects not merely as a means to improve learning but as educational content in their own right (Vázquez and Manassero Mas, 1997).
The structure of the tool includes three factors, which add value given that existing literature does not treat the construct holistically, with a prevailing emphasis on the cognitive component (García-Marigómez et al., 2026).
First, one subdimension gathers evidence regarding beliefs and opinions on the relevance of teaching NoST in Primary Education. Literature has predominantly focused on evaluating the correctness of opinions on scientific issues (Barnes et al., 2015; Ozturk-Akar and Dogan, 2013; Yalvac et al., 2007), but has largely ignored perspectives on the importance of including these topics in the classroom.
Second, the emotional component related to such teaching is addressed, given the relevance and impact of emotions in teaching practice. While studies focusing on affectivity toward teaching NoST are lacking, existing research by Aguirregabiria and García-Olalla (2022), Clerici (2008), Kaya et al. (2009), Mateos Núñez and Martínez Borreguero (2021), and Martínez-Borreguero et al. (2022) shows a predominance of negative emotions toward science topics, highlighting the need to strengthen affective connections to achieve genuine commitment to meaningful science teaching.
Lastly, the predisposition toward teaching is included as a factor, recognizing the potential of attitudes to predict behavior (Ajzen and Fishbein, 1980; Hogg and Vaughan, 1995) and to better understand the attitude-behavior relationship. This component represents a significant contribution, as no previous studies were found addressing this variable. In existing literature, behavioral intention has been primarily explored in the context of students’ intentions to pursue science-related careers (Roberts, 2014).
The scale therefore helps fill a gap in the literature regarding tools that assess attitudes comprehensively. It also addresses other gaps, such as the limited focus on teachers, teaching, and NoST as central elements in the educational process.
Additionally, the scale’s structure allows for a global understanding of attitudes and how the different components interrelate, supporting the search for strategies that promote attitudinal—and therefore pedagogical—change. A more detailed item-by-item analysis may reveal which science topics are associated with more positive or negative attitudes.
After the favorable results from the content validity assessment by expert judges it was possible to proceed with construct validity and internal consistency analysis. Again, positive results from the CFA and McDonald’s omega supported the instrument’s alignment with the theoretical model and its high reliability. The scale’s psychometric consistency enables robust evaluation of an essential but often overlooked competence: knowing how to be in science teacher education. No comparison was made with other instruments due to the lack of similar or comparable characteristics, as the study addresses a previously identified gap in the literature.
Given the original and novel nature of this study, no direct comparison can be made with previous work. However, connections with literature on other attitudinal aspects related to teachers provide valuable considerations.
Results regarding attitudes toward teaching NoST indicate a generally positive trend. However, this conclusion is based on descriptive statistics reflecting general patterns. Future studies should apply more detailed analyses to identify attitude profiles, enabling more targeted and effective educational interventions. Moreover, while the results indicate generally positive attitudes toward teaching NoST, the present study does not allow direct conclusions to be drawn regarding actual classroom implementation. Any potential discrepancy between attitudes and practice should therefore be interpreted with caution and constitutes an important avenue for future research rather than a conclusion derived from the current data.
At the cognitive level, the findings suggest that teachers value NoST as important and useful for Primary Education, despite existing studies showing their views on these topics are often naive or inadequate (Barnes et al., 2015; Ozturk-Akar and Dogan, 2013; Yalvac et al., 2007).
On the emotional level, the emotions reported are predominantly positive, in contrast to earlier studies (Aguirregabiria and García-Olalla, 2022; Clerici, 2008; Kaya et al., 2009; Mateos Núñez and Martínez Borreguero, 2021; Martínez-Borreguero et al., 2022; Murphy and Smith, 2012), which reported negative feelings toward science content.
Regarding the conative component, reported scores show a high predisposition. As mentioned before, no previous studies have focused specifically on this construct.
These findings underscore the need to explore why a predominantly positive attitude toward teaching NoST does not translate into its actual inclusion in the classroom (Acevedo, 2009; De Pro et al., 2022; García-Marigómez et al., 2026). Links must be established between this gap and obstacles identified in the literature, such as limited knowledge (Walag et al., 2022), low self-efficacy (Clerici, 2008; Murphy and Smith, 2012), and the persistence of traditional teaching practices (Aragón Núñez, et al., 2021; Kim and Tan, 2011; Mansour, 2013). Understanding these connections will help design training approaches that address both cognitive and affective factors hindering educational transformation in science teaching.
7.1 Limitations and future directions
Among the main limitations identified is, firstly, the sample size and its non-probabilistic nature. A larger and more diverse sample (both in terms of participants and schools) would yield more robust results across the different phases of statistical analysis. Regarding its non-random nature, it is worth noting that such sampling is common—and often the only feasible option—in educational research, due to practical and contextual constraints.
Secondly, since the instruments were self-administered, there is an increased risk of response bias, which may affect the accuracy of the data collected.
Thirdly, the instrument was designed and adapted for Spanish-speaking contexts, meaning its applicability in other settings cannot be guaranteed without prior translation and cultural adaptation to ensure validity and reliability.
Fourthly, although reducing the length of the questionnaire was necessary to avoid excessive burden, this limited the ability to explore the construct in greater depth and detail.
Finally, it is important to note that this instrument is not used in isolation but forms part of a broader methodological framework involving multiple tools aimed at gaining a deeper understanding of the complex nature of attitudes and avoiding the limitations of a purely positivist perspective in educational research.
Looking ahead, future research could involve expanding the sample size once the scale is fully validated, in order to obtain more conclusive results.
Applying the instrument in various educational programs could help analyze its potential and support further research based on educational interventions. This research should include longitudinal designs to examine attitude change over time, studies exploring the relationship between attitudinal components, and studies investigating the connection between teachers’ attitudes and actual classroom practices.
In addition, cross-cultural validation of the instrument in different educational contexts may be of interest.
Data availability statement
The datasets presented in this article are not readily available due to confidentiality restrictions and data embargo, as the research is still in progress. Requests to access the datasets should be directed to Y2FybWVsYS5nYXJjaWFAdXZhLmVz.
Ethics statement
The study involving human participants was approved by the Ethics Committee of the University of Valladolid. Furthermore, the study guaranteed the confidentiality and anonymity of the research participants. The management and processing of the data were carried out in accordance with Organic Law 3/2018, of December 5, on the Protection of Personal Data and Guarantee of Digital Rights, and Regulation (EU) 2016/679 of the European Parliament and of the Council of April 27, 2016, on the protection of natural persons with regard to the processing of personal data and the free movement of such data, repealing Directive 95/46/EC (General Data Protection Regulation). The participants gave their express consent and were also informed of the study’s objective and their right to withdraw at any time. Their participation was voluntary. The study was conducted in accordance with local legislation and institutional requirements. The participants provided their written informed consent to participate.
Author contributions
CG-M: Writing – original draft, Formal analysis, Funding acquisition, Methodology, Data curation, Investigation, Writing – review & editing, Conceptualization, Software. VO-Q: Investigation, Writing – review & editing, Supervision, Methodology, Writing – original draft, Resources, Visualization, Software. CG-P: Supervision, Conceptualization, Funding acquisition, Project administration, Writing – review & editing, Validation, Writing – original draft.
Funding
The author(s) declared that financial support was received for this work and/or its publication. This research was funded by the Ministry of Education and Vocational Training of the Government of Spain through a grant contract for University Teacher Training (FPU 21/04817).
Acknowledgments
We would like to thank the support and collaboration.
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declared that generative AI was not used in the creation of this manuscript.
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References
Acevedo, J. A. (2009). Conocimiento didáctico del contenido para la enseñanza de la naturaleza de la ciencia (I): El marco teórico. [Pedagogical content knowledge for teaching the nature of science (I): The theoretical framework]. Rev. Eureka Sobre Enseñanza Divulgación Ciencias 6, 21–46. doi: 10.25267/Rev_Eureka_ensen_divulg_cienc.2009.v6.i1.02 Spanish
Acevedo, J. A., and García-Carmona, A. (2016). Algo antiguo, algo nuevo, algo prestado’: Tendencias sobre la naturaleza de la ciencia en la educación científica. [’Something old, something new, something borrowed’: Trends on the nature of science in science education]. Revista Eureka Sobre Enseñanza Divulgación Ciencias 13, 3–19. doi: 10.25267/Rev_Eureka_ensen_divulg_cienc.2016.v13.i1.02 Spanish
Acevedo, J. A., García-Carmona, A., and Aragón-Méndez, M. M. (2016). Un caso de historia de la ciencia para aprender naturaleza de la ciencia: Semmelweis y la fiebre puerperal. [A case study in the history of science to learn about the nature of science: Semmelweis and puerperal fever]. Rev. Eureka Sobre Enseñanza Divulgación Ciencias 13, 408–422. doi: 10.25267/Rev_Eureka_ensen_divulg_cienc.2016.v13.i1.02 Spanish
Aguirregabiria, F., and García-Olalla, A. (2022). Primary school teacher in training and the natural sciences: Previous experience, self-perception and training needs. Góndola 17, 268–285. doi: 10.14483/23464712.17374
Aikenhead, G., and Ryan, A. G. (1992). The development of a new instrument: ‘Views on Science—Technology—Society’ (VOSTS). Sci. Educ. 76, 477–491. doi: 10.1002/sce.3730760503
Ajzen, I., and Fishbein, M. (1980). Understanding Attitudes and Predicting Social Behaviour. Englewood Cliffs, NJ: Prentice Hall.
American Association for the Advancement of Science [AAAS] (2009). Benchmarks—project 2061. Washington, DC: AAAS.
Aragón Núñez, L., Jiménez Tenorio, N., Vicente Martorell, J. J., and Eugenio, M. (2021). >Progresan las concepciones sobre la ciencia de futuros maestros/as tras la implementación de propuestas constructivistas para la alfabetización científica?. [Do future teachers’ conceptions of science improve after the implementation of constructivist proposals for scientific literacy?] Góndola 16, 78–95. doi: 10.14483/23464712.15589 Spanish
Ato, M., López, J. J., and Benavente, A. (2013). Un sistema de clasificación de los diseños de investigación en psicología. [A classification system for research designs in psychology]. Anal. Psicol. 29, 1038–1059. doi: 10.6018/analesps.29.3.178511 Spanish
Avraamidou, L. (2014). Studying science teacher identity: Current insights and future research directions. Stud. Sci. Educ. 50, 145–179. doi: 10.1080/03057267.2014.937171
Barnes, C., Angle, J., and Montgomery, D. (2015). Teachers describe epistemologies of science instruction through Q methodology. School Sci. Mathemat. 115, 141–150. doi: 10.1111/ssm.12111
Bentler, P. M. (1990). Comparative fit indices in structural models. Psychol. Bull. 107, 238–246. doi: 10.1037/0033-2909.107.2.238
Bisquerra, R., and Pérez, N. (2007). Las competencias emocionales. [Emotional skills]. Educ. XXI 10, 61–82. doi: 10.5944/educxx1.1.10.297 Spanish
Bogdan, R., and Meneses, J. A. (2021). “>Cómo se conceptualiza las actitudes hacia la ciencia en los instrumentos de la última década?. [How are attitudes towards science conceptualized in the instruments of the last decade?],” en Proceedings of the 29 Encuentros de Didáctica de las Ciencias Experimentales, (Córdoba: Universidad de Córdoba y APICE), 632–638. Spanish
Browne, M. W., and Cudeck, R. (1993). “Alternative ways of assessing model fit,” en Testing Structural Equation Models, editado por K. A. Bollen and J. S. Long (Newbury Park, CA: Sage), 136–162.
Byrne, B. M. (2001). Structural equation modeling with AMOS, EQS, and LISREL: Comparative approaches to testing for the factorial validity of a measuring instrument. Intern. J. Testing 1, 55–86. doi: 10.1207/s15327574ijt0101_4
Cadena-Nogales, P., Solaz-Portolés, J., Echegoyen-Sanz, Y., and Sanjose-López, V. (2022). Level of acceptance of epistemically unwarranted beliefs in pre-service primary school teachers: Influence of cognitive style, academic level and gender. J. Baltic Sci. Educ. 21, 398–407. doi: 10.33225/jbse/22.21.398
Campo-Arias, A., and Oviedo, H. C. (2008). Propiedades psicométricas de una escala: La consistencia interna. [Psychometric properties of a scale: Internal consistency]. Rev. Salud Pública 10, 831–839. doi: 10.1590/S0124-00642008000500015 Spanish
Carlson, J., and Daehler, K. R. (2019). “The refine consensus model of pedagogical content knowledge in science education,” en Repositioning pedagogical content knowledge in teachers’ knowledge for teaching science, editado por A. Hume, R. Cooper, and A. Borowski (Cham: Springer), 77–92.
Chevallard, Y. (1985). Le transposition didactique: Du savoir savant au savoir enseigné. París: La Pensée Sauvage. Traducción castellana (1991). La transposición didáctica. Del saber sabio al saber enseñado. [The didactic transposition: From scholarly knowledge to taught knowledge. Paris: The Wild Thought. Spanish translation (1991). The didactic transposition. From wise knowledge to taught knowledge]. Buenos Aires: Aique. Spanish
Cho, G., Hwang, H., Sarstedt, M., and Ringle, ChM. (2020). Cutoff criteria for overall model fit indexes in generalized structured component analysis. J. Market. Anal. 8, 189–202. doi: 10.1057/s41270-020-00089-1
Clerici, R. (2008). Knowledge and attitudes of future schoolteachers in the scientific-mathematical sphere: Some evidences for Italy. Educ. Stud. 34, 277–287. doi: 10.1080/03055690802034369
Day, C. (1999). Teachers as inquirer. En developing teachers: The challenges of lifelong learning. London: Falmer Press, 22–47.
De Pro, A., de Pro, C., and Cantó, J. (2022). Cinco problemas en la formación de maestros y maestras para enseñar ciencias en Educación Primaria. Rev. Int. Formación Prof. 97, 185–202. doi: 10.47553/rifop.v97i36.1.92510
Erduran, S., and Dagher, R. F. (2014). Reconceptualizing the nature of science for science education. Dordrecht: Springer.
Escobar-Pérez, J., and Cuervo-Martínez, A. (2008). Validez de contenido y juicio de expertos: Una aproximación a su utilización. [Content validity and expert judgment: An approach to its use]. Avances Med. 6, 27–36. Spanish
Fernández-Abascal, E., Martín, M., and Domínguez, J. (2001). Procesos psicológicos. [psychological processes]. Madrid: Ediciones Pirámide. Spanish
Fueyo, A., Hevia, I., and García, S. (2015). Haciendo educación para el desarrollo: Guía didáctica. [Doing education for development: A teaching guide]. Oviedo: Universidad de Oviedo. Spanish
Furió, C., and Carnicer, J. (2002). El desarrollo profesional del profesor de ciencias mediante tutorías de grupos cooperativos. Estudio de ocho casos. [The professional development of science teachers through cooperative group tutoring: A study of eight cases]. Enseñanza Ciencias 20, 47–73. doi: 10.5565/rev/ensciencias.3979 Spanish
García-Marigómez, C., Ortega-Quevedo, V., and Gil Puente, C. (2023). Teaching and learning geology as a way to develop thinking and encourage positive attitudes towards science. Reidocrea 12, 242–260. doi: 10.30827/Digibug.82318
García-Marigómez, C., Ortega-Quevedo, V., and Gil Puente, C. (2026). Systematised review of know-how in teacher training: Science–Technology–Society teaching in the primary school classroom. Educ. Sci. 16:112. doi: 10.3390/educsci16010112
Gardner, P. L. (1975). Attitudes to science: A review. Stud. Sci. Educ. 2, 1–41. doi: 10.1080/03057267508559818
Gess-Newsome, J. (2015). “A model of teacher professional knowledge and growth: Reconceptualizing pedagogical content knowledge,” in Reconceptualizing Pedagogical Content Knowledge in Science Education, ed. A. F. Orange (New York, NY: Routledge), 28–42.
Goleman, D. (1996). La práctica de la inteligencia emocional. [The practice of emotional intelligence]. Barcelona: Paidós. Spanish
Hernández-Sampieri, R., Fernández-Collado, C., and Baptista-Lucio, P. (2010). Metodología de la Investigación. [Research Methodology]. México: McGraw-Hill Interamericana. Spanish
Hernández-Nieto, R. A. (2002). Contributions to statistical analysis. Mérida: Universidad de Los Andes.
Hodson, D. (1988). Toward a philosophically more valid science curriculum. Sci. Educ. 72, 19–40. doi: 10.1002/sce.3730720103
Hogg, M. A., and Vaughan, G. M. (1995). Psicología social. [Social psychology]. Madrid: Editorial Médica Panamericana. [Spanish]
Hu, L. T., and Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Struct. Equat. Model. A Multidiscipl. J. 6, 1–55. doi: 10.1080/10705519909540118
Irzik, G., and Nola, R. (2014). “New directions for nature of science research,” en International handbook of research in history, philosophy and science teaching, editado por M. Matthews (Dordrecht: Springer), 999–1021.
Kaya, O., Yager, R., and Dogan, A. (2009). Changes in attitudes towards science-technology-society of pre-service science teachers. Res. Sci. Educ. 39, 257–279. doi: 10.1007/s11165-008-9084-y
Kim, M., and Tan, A. (2011). Rethinking difficulties of teaching inquiry-based practical work: Stories from elementary pre-service teachers. Intern. J. Sci. Educ. 33, 465–486. doi: 10.1080/09500691003639913
Lai, K. (2020). Fit difference between nonnested models given categorical data: Measures and estimation. Struct. Equat. Model. A Multidiscipl. J. 28, 99–120. doi: 10.1080/10705511.2020.1763802
Lederman, N. G., Abd-El-Khalick, F., Bell, R. L., and Schwartz, R. S. (2002). Views of nature of science questionnaire: Towards valid and meaningful assessment of learners’ conceptions of nature of science. J. Res. Sci. Teach. 39, 497–521. doi: 10.1002/tea.10034
Loughran, J., Mulhall, P., and Berry, A. (2004). In search of pedagogical content knowledge in science: Developing ways of articulating and documenting professional practice. J. Res. Sci. Teach. 41, 370–391. doi: 10.1002/tea.20007
Magnusson, S., Krajcik, J., and Borko, H. (1999). “Nature, sources, and development of pedagogical content knowledge for science teaching,” in Examining Pedagogical Content Knowledge: The Construct and its Implications for Science Education, eds J. Gess-Newsome and N. G. Lederman (Dordrecht: Springer), 95–132.
Manassero Mas, M. A., and Vázquez, A. (2002). Instrumentos y métodos para la evaluación de las actitudes relacionadas con la ciencia, la tecnología y la sociedad. [Instruments and methods for the assessment of attitudes related to science, technology and society]. Enseñanza Ciencias: Rev. Invest. Exp. Didácticas 20, 15–27. doi: 10.5565/rev/ensciencias.3977 Spanish
Manassero, M. A., Vázquez, A., and Acevedo, J. A. (2003). Cuestionario de opiniones sobre ciencia, tecnología y sociedad (COCTS). [Science, Technology and Society Opinions Questionnaire (COCTS)]. Princeton, NJ: Educational Testing Service. Spanish
Manassero-Mas, M. A., and Vázquez, A. (2019). Conceptualización y taxonomía para estructurar los conocimientos acerca de la ciencia [Conceptualization and taxonomy to structure the knowledge about science]. Rev. Eureka Sobre Enseñanza Divulgación Ciencias 16, 3104–3117. doi: 10.25267/Rev_Eureka_ensen_divulg_cienc.2019.v16.i3.3104 Spanish
Mansour, N. (2013). Consistencies and inconsistencies between science teachers’ beliefs and practices. Intern. J. Sci. Educ. 35, 1230–1275. doi: 10.1080/09500693.2012.743196
Martín-Baró, I. (1983). Acción e ideología: Psicología social desde Centroamérica [Action and ideology. Social psychology from Central America]. San Salvador: UCA Editores. Spanish
Martínez-Borreguero, G., Naranjo-Correa, F., and Mateos-Núñez, M. (2022). Cognitive and emotional development of STEM skills in primary school teacher training through practical work. Educ. Sci. 12:470. doi: 10.3390/educsci12070470
Mateos Núñez, M., and Martínez Borreguero, M. G. (2021). Diseño y validación de metodologías didácticas aplicadas en el aula de educación primaria para mejorar el dominio cognitivo y emocional en la enseñanza/aprendizaje de competencias STEM. [Design and validation of teaching methodologies applied in the primary education classroom to improve cognitive and emotional mastery in the teaching/learning of STEM skills]. Tesis doctoral, Extremadura: Universidad de Extremadura. Spanish
Matthews, M. (2012). “Changing the focus: From nature of science (NOS) to features of science (FOS),” en Advances in nature of science research, ed. M. S. Khine (Dordrecht: Springer), 3–26.
Mayer, J. D., Salovey, P., and Caruso, D. (2000). Models of emotional intelligence. Cambridge, MA: Cambridge University Press.
McComas, W. F. (2002). The nature of science in science education: Rationales and strategies. Dordrecht: Kluwer Academic Publishers.
Mellado, V. (2003). Cambio didáctico del profesorado de ciencias experimentales y filosofía de la ciencia. [Didactic change of the teaching staff of experimental sciences and philosophy of science]. Enseñanza Ciencias 21, 343–358. doi: 10.5565/rev/ensciencias.3913 Spanish
Morales, P. (2000). Medición de actitudes en psicología y educación. [Measuring attitudes in psychology and education]. Madrid: Universidad Pontificia de Comillas. Spanish
Murphy, C., and Smith, G. (2012). The impact of a curriculum course on pre-service primary teachers’ science content knowledge and attitudes towards teaching science. Irish Educ. Stud. 31, 77–95. doi: 10.1080/03323315.2011.634061
National Research Council (1996). National science education standards. Washington, DC: National Academy Press.
ONU (2015). Transformar nuestro mundo: La Agenda 2030 para el desarrollo sostenible. [Transforming our world: The 2030 Agenda for Sustainable Development]. New York, NY: ONU. Spanish
Osborne, J., Collins, S., Ratcliffe, M., Millar, R., and Duschl, R. (2003). What ‘ideas-about science’ should be taught in school science? A Delphi study of the expert community. J. Res. Sci. Teach. 40, 692–720. doi: 10.1002/tea.10105
Ozturk-Akar, E., and Dogan, D. (2013). Turkish pre-service teachers’ views of Science-Technology-Society: Influence of a history of science course. J. Baltic Sci. Educ. 12, 793–802. doi: 10.33225/jbse/13.12.793
Pérez-Foguet, A., and Lazzarini, B. (2019). Continuing professional education in engineering faculties: Transversal integration of sustainable human development in basic engineering sciences courses. J. Cleaner Product. 218, 772–781. doi: 10.1016/j.jclepro.2019.02.054
Rivera Maulucci, M. S. (2013). Emotions and positional identity in becoming a social justice science teacher: Nicole’s story. J. Res. Sci. Teach. 50, 453–478. doi: 10.1002/tea.21081
Roberts, S. J. (2014). ENGage: The use of space and pixel art for increasing primary school children’s interest in science, technology, engineering and mathematics. Acta Astronautica 93, 34–44. doi: 10.1016/j.actaastro.2013.06.013
Rosseel, L., Speelman, D., and Geeraerts, D. (2019). Measuring language attitudes in context: Exploring the potential of the personalized implicit association test. Lang. Soc. 48, 429–461. doi: 10.1017/S0047404519000198
Rubba, P. A., Schoneweg-Bradford, C. S., and Harkness, W. L. (1996). A new scoring procedure for the views on science-technology-society instrument. Intern. J. Sci. Educ. 18, 387–400. doi: 10.1080/0950069960180401
Sanmartí, N. (2001). Enseñar a enseñar ciencias en secundaria: Un reto muy completo. [Teaching how to teach science in secondary school: A very comprehensive challenge]. Rev. Interuniversitaria Formación Profesorado 40, 31–48. Spanish
Sarabia, B. (1992). “El aprendizaje y la enseñanza de las actitudes. [Learning and teaching attitudes],” en Los contenidos de la reforma. Enseñanza y aprendizaje de conceptos, procedimientos y actitudes, editado por C. Coll, J. I. Pozo, B. Sarabia, and E. Valls (Madrid: Aula XXI y Santillana), 133–198. Spanish
Shulman, L. S. (1986). Those who understand: Knowledge growth in teaching. Educ. Res. 15, 4–14. doi: 10.3102/0013189X015002004
Talavera, M., Mayoral, O., Hurtado, A., and Martín-Baena, D. (2018). Motivación docente y actitud hacia las ciencias: Influencia de las emociones y factores de género. [Teacher motivation and attitude towards science: Influence of emotions and gender factors]. Rev. Electrón. Enseñanza Ciencias 17, 461–475. Spanish
Tenreiro-Vieira, C., and Vieira, R. M. (2021). Promover o pensamento crítico e criativo no ensino das ciências: Propostas didáticas e seus contributos em alunos portugueses. [Promoting critical and creative thinking in science education: Teaching proposals and their contributions to Portuguese students.]. IENCI 26, 70–84. doi: 10.22600/1518-8795.ienci2021v26n1p70 Spanish
Thompson, K. (2016). Developing education v. education for development. Ann. Am. Acad. Political Soc. Sci. 424, 16–28. doi: 10.1177/000271627642400104
Tyler-Wood, T., Knezek, G., and Christensen, R. (2010). Instruments for assessing interest in STEM content and careers. J. Technol. Teach. Educ. 18, 341–363.
Urbán, F. (1980). Un método de investigación de origen psicolingüístico: El diferencial semántico. [A research method of psycholinguistic origin: The semantic differential]. Cauce: Rev. Intern. Filología Comun. Didácticas 3, 47–70. Spanish
Vázquez, A., and Manassero, M. A. (1995). Actitudes relacionadas con la ciencia: Una revisión conceptual. Enseñanza de las Cienc. Rev. Invest. Exp. Didácticas 13, 337–346. doi: 10.5565/rev/ensciencias.4254
Vázquez, A., and Manassero Mas, M. A. (1997). Una evaluación de las actitudes relacionadas con la ciencia. [An assessment of attitudes related to science]. Enseñanza Ciencias 15, 199–213. doi: 10.5565/rev/ensciencias.4176 Spanish
Vázquez Alonso, Á, and Manassero Mas, M. A. (2018). El conocimiento epistémico en la evaluación de la competencia científica en PISA 2015. [Epistemic knowledge in the assessment of scientific competence in PISA 2015]. Rev. Educ. 380, 103–128. doi: 10.4438/1988-592X-RE-2017-380-374 Spanish
Ventura-León, J. L., and Caycho-Rodríguez, T. (2017). El coeficiente Omega: Un método alternativo para la estimación de la confiabilidad. [The Omega coefficient: An alternative method for estimating reliability]. Rev. Latinoamericana Ciencias Soc. Niñez Juventud 15, 625–627. Spanish
Villafañe, S. M., and Lewis, J. E. (2016). Exploring a measure of science attitude for different groups of students enrolled in introductory college chemistry. Chem. Educ. Res. Practice 17, 731–742. doi: 10.1039/c5rp00185d
Wagner, T. (2014). The global achievement gap: Why even our best schools don’t teach the new survival skills our children need—and what we can do about it. New York, NY: Basic Books.
Walag, A., Fajardo, M., Bacarrisas, P., and Guimary, F. (2022). A canonical correlation analysis of filipino science teachers’ scientific literacy and science teaching efficacy. Intern. J. Instruct. 15, 249–266. doi: 10.29333/iji.2022.15314a
Wenger, E. (1998). Communities of Practice: Learning, Meaning, and Identity. Cambridge, MA: Cambridge University Press.
West, S. G., Taylor, A. B., and Wu, W. (2012). “Model fit and model selection in structural equation modeling,” in Handbook of Structural Equation Modeling, ed. R. H. Hoyle (New York, NY: Guilford), 209–231.
Xia, Y. (2016). Investigating the Chi-square Based Model-Fit Indexes for WLSMV and ULSMV Estimators. Dissertation, Tallahassee, FL: Florida State University.
Xia, Y., and Yang, Y. (2019). RMSEA, CFI, and TLI in structural equation modeling with ordered categorical data: The story they tell depends on the estimation methods. Behav. Res. Methods 51, 409–428. doi: 10.3758/s13428-018-1055-2
Yalvac, B., Tekkaya, C., Cakiroglu, J., and Kahyaoglu, E. (2007). Turkish pre-service science teachers’ views on science-technology-society issues. Intern. J. Sci. Educ. 29, 331–348. doi: 10.1080/095006906007086
Yemini, M., Tibbitts, F., and Goren, H. (2019). Trends and caveats: Review of literature on global citizenship education in teacher training. Teach. Teach. Educ. 77, 77–89. doi: 10.1016/j.tate.2018.09.014
Appendix
Table A1. Ítems del cuestionario y dimensiones entre paréntesis.
Keywords: attitude, in-service teachers, Nature of Science and Technology, Primary Education, trainee teachers, validation of scales
Citation: García-Marigómez C, Ortega-Quevedo V and Gil-Puente C (2026) Attitudes in didactic change: design and validation of a questionnaire of Primary Education teachers’ attitudes toward the teaching of the Nature of Science and Technology. Front. Educ. 11:1748194. doi: 10.3389/feduc.2026.1748194
Received: 02 December 2025; Revised: 30 December 2025; Accepted: 02 January 2026;
Published: 29 January 2026.
Edited by:
Ana María Pinto-Llorente, University of Salamanca, SpainReviewed by:
Yu Zhao, University of Salamanca, SpainWati Sukmawati, Universitas Muhammadiyah Prof. Dr. Hamka, Indonesia
Copyright © 2026 García-Marigómez, Ortega-Quevedo and Gil-Puente. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Carmela García-Marigómez, Y2FybWVsYS5nYXJjaWFAdXZhLmVz