Open Educational Resources: Teachers’ Perception and Impact on Students’ Motivation and Meaningful Learning

Abstract

Open Educational Resources (OER) are increasingly recognized as key tools for promoting quality, inclusive, and equitable education. Their ease of access and the possibility of free adaptation to different contexts contribute to continuous improvement in teaching and learning. Drawing on data collected from teachers and students, this study looks at teachers’ perceptions of OER, how they influence collaboration and educational practices, and the impact of OER on students’ learning and motivation. The findings reveal both enabling and constraining factors and highlight how OER foster teacher collaboration and self-reflection on pedagogical practices. Moreover, the use of OER is associated with active and constructive teaching approaches, positively influencing student engagement. These results are triangulated with data from Likert-scale responses, indicating that students who engage with OER demonstrate significantly higher levels of motivation and deep learning compared to those who do not. Based on these findings, the study recommends implementing strategies to encourage broader integration of OER in classroom settings, alongside ongoing professional development to address existing barriers. In this context, institutional support and community-building initiatives emerge as critical levers to scale the adoption of OER. Finally, the importance of further investigation is emphasized to explore long-term impacts on teaching practices and student outcomes across diverse educational settings

1. Introduction

Education is one of the most powerful tools for transforming the world. It enables personal and professional development while fostering culturally and socio-economically flourishing societies. Promoting quality education for all is essential to unlocking human potential and improving overall well-being.

Open Educational Resources (OER) are widely recognized as key instruments in achieving the United Nations Sustainable Development Goal 4 (Romero-Ariza et al., 2023), which advocates for inclusive and equitable quality education. Their open access nature and adaptability to diverse educational contexts and objectives make them valuable resources that support continuous improvement in teaching and learning.

The United Nations Educational, Scientific and Cultural Organization (UNESCO) has widely recognized the educational potential and strategic value of OER. The last OER World Congress held in 2024 emphasized the importance to enhance global cooperation and innovation in this respect and to implement UNESCO recommendations. These recommendations address the needs to (i) build the capacities of stakeholders to create, access, reuse, adapt and redistribute OER; (ii) develop and implement policies to support OER implementation; (iii) foster the development of inclusive, equitable, and quality OER; (iv) promote the creation of sustainability models for the implementation and exploitation of OER; and (v) facilitate international cooperation focused on innovation and educational improvement based on OER.

There are various initiatives, both nationally and internationally, for the development and exploitation of OER, as catalysts for inclusive and quality education (Weller et al., 2015). Some of these initiatives have led to the creation of OER repositories and the vindication of the need to have evaluation instruments and strategies that guarantee their quality. In this sense, in the specialized literature we find works focused on the rigorous evaluation of the psychopedagogical and didactic quality of OER (Romero-Ariza et al., 2023). However, despite numerous national and international initiatives aimed at promoting the development and adoption of OER, there is a growing need for rigorous research that evaluates their quality and assesses their impact on educational practices.

In the following section, we will discuss the literature review performed in order to identify the main research gaps and to make a significant contribution to the state of the art. We will track the origin of the term OER according to experts (Tlili et al., 2025) and the fundamental characteristics of these resources (Tlili et al., 2023), as well as the key dimensions of the pedagogical practices aligned with the OER philosophy (Bozkurt et al., 2023; Huang et al., 2020). In addition, we will refer to the importance of OER metadata and metadata frameworks for OER exploitation (Schuwer & Janssen, 2024) and how artificial intelligence can assist educational practices in this respect (Z. Li et al., 2024).

Secondly, we will revise the specialized literature about teachers and OER, discussing studies that report on teachers’ views (Tosun & Altintas, 2024), how OER can support equitable teaching practices (Jensen & Kimmons, 2022), the factor affecting teaching adoption of these resources (Tang et al., 2020) and the importance of providing specific teacher professional development (Arispe et al., 2023) and organizational support (Scott & Smith, 2024).

Thirdly, we will discuss the literature concerning OER and students, referring to students’ perceptions of these resources (Hilton, 2020), the factors affecting students’ educational choices (Angelopoulou et al., 2022), students’ adoption of OER (Glasserman-Morales et al., 2024) and some recent reviews about the impact of OER on students (Tlili et al., 2023, 2025). In these latter reviews, Tlili et al. (2023, 2025), showed how the impact of OER on students depend on the circumstances in which these resources are applied to teaching and learning processes. These authors highlight the need to conduct studies that triangulate qualitative and quantitative data and couple students’ performance with the underlying pedagogies, as well as with teachers’ experiences with the use of these resources and how they influence students’ engagement and achievement. The present study directly addresses this need, presenting data from both teachers and students in order to develop a better understanding of the impact of OER on students’ motivation and learning, as a result of the resources and pedagogies applied.

In response to these needs, this paper presents the results of a collaborative project between the “Anonymized” and the “Anonymized” research teams. The study focuses on addressing these key concerns, through empirical evidence gathered from a representative sample of teachers and students who use OER from a national repository developed through the EDIA project (Educational, Digital, Innovative, and Open). This project has been developed by the Spanish Ministry of Education to support the creation of digital and methodological transformation processes in schools, with the aim of improving student learning and promoting new school models (CEDEC, 2025). In addition to the study of teachers’ perceptions and experiences about OER, we evaluate the impact of EDIA OER on the motivation and learning of students, comparing two groups of students—one exposed to EDIA OER and one not.

Within this context, the present research seeks to explore, on a national level, aspects that remain underexplored in the scholarly literature on teaching and learning with OER. Specifically, it aims to contribute to a deeper understanding of the factors that influence teachers’ decisions to adopt or avoid OER, as well as their related needs and concerns. Additionally, the study includes a comparative analysis of student motivation and learning approaches depending on whether instruction follows a more traditional model or leverages the OER developed through the EDIA project.

More precisely, this study aims to answer the following research questions:

• What are teachers’ perceptions and experiences related to the use of EDIA OER?
• What are the effects of EDIA OER on students?

2. Theoretical Background

Within this section, we will build on the specialized literature to provide theoretical foundation to the fundamental elements of this paper. Firstly, we will briefly revise how the OER movement originated, what are the precedents, philosophical and pedagogical principles and key research contributions. Secondly, we will discuss previous research about OER from the perspective of teachers and students. Finally, we will provide some theoretical foundation for the main constructs measured in the students’ questionnaire, namely motivation and learning. The following table summarizes the main aspects discussed:

2.1. Open Educational Resources (OER): Origin and Main Features

The philosophy behind the OER movement lies in the belief that everyone has the same right to receive high-quality education, regardless of socio-economic background and culture. This assumption is aligned with the democratization of knowledge, the open access movement to digital content and the current attempt to ensure open science.

The first efforts to provide open access content took place in the 1980s, with important events such as the GNU project to develop free software, the launch of the MIT OpenCourseWare in 2002 or the creation of creative common licenses in 2007. The term Open Educational Resources (OER) spread significantly after the MIT project launched in 2001, although the fundamental idea leads us to consider OER as successors to those initially called, in the Anglo-Saxon sphere, as Learning Objects (Ariza & Quesada, 2011; Weller, 2014). However, it was at the Forum on Open Courseware in 2002 where the term “Open Educational Resource” was first coined by UNESCO (Tlili et al., 2025).

Multiple definitions of the OER term have been offered (Weller et al., 2015). A review of the different definitions offered over time reveals that the key concepts associated with this term are free access to such resources, which requires their availability on the web and the absence of conflicts related to restricted authorship licenses, as well as the possibility of sharing, re-using and modifying them freely to improve them or adapt them to new contexts and educational needs.

UNESCO (2019) defines them as “learning, teaching and research materials in any format and support that exist in the public domain or are under copyright and were released under an open license, which allow their access at no cost, their reuse, reorientation, adaptation and redistribution by third parties”.

To fully understand the potential of OER as strategic tools to promote inclusive and high-quality education, it is important to highlight five key characteristics of these type of resources named as the 5R by Wiley (2014, cited in Tlili et al., 2023): (1) Retain (anyone has the right to make own copies); (2) Reuse (OER can be used in many different ways and for different purposes by anyone); (3) Revise (anyone has the right to modify and adapt OER to any particular context or need); (4) Remix (anyone has de the right to partly used, or combine any OER with other ones according to their needs and motivations); (5) Redistribute (OER can be freely shared with others, either as original copies or as derivatives of previous versions partly modified or adapt).

These key characteristics significantly expand the potential of these resources to be continuously improved after successive cycles of implementation and modification and successfully be tailored to many different educational needs.

However, a mere change in the content from proprietary to open does not lead to improvement, especially if it is integrated into traditional teaching practices. In 2007, the Open e-Learning Content Observatory Services created a roadmap for the exploitation of OER emphasizing the key role of the teaching approach applied and setting the offset for the idea of Open Education Practice (OEP).

Ehlers (2011) defined OEP as innovative teaching approaches supporting the use of OER and placing learners at the center of the learning process and as co-producer of knowledge. Huang et al. (2020) propose five dimensions for OEP that should be consequently aligned to provide a coherent approach: technology, resources, teaching practices, assessment and open collaboration.

The joint editorial effort, driven by Bozkurt et al. (2023), offers a privileged forum to discuss why openness in education is important nowadays and why it is critically needed. This Special Issue illustrates and justifies open education and the OER movement through a rich collection of experiences and cases. The data and the narratives discussed allow readers to recognize the fundamental values behind. “These range from aspects such as sharing, access, flexibility, affordability, enlightenment, barrier-removal, empowerment, care, individual agency, trust, innovation, sustainability, collaboration, co-creation, social justice, equity, transparency, inclusivity, decolonization, democratization, participation, liberty, and respect for diversity” (Bozkurt et al., 2023, p. 77).

2.2. Open Digital Resources: The Vision from the Teacher’s Perspective

Teachers play a pivotal role in the adoption and integration of Open Educational Resources (OER) into educational practice. Consequently, numerous studies have explored the key factors that either facilitate or hinder teachers’ engagement with these resources.

Baas et al. (2019) aimed to characterize the use of OER in teaching through a pyramid model. Their findings suggest that the foundational level of the pyramid includes factors related to awareness and access to OER, along with essential technical competencies and digital literacy. The data show that teachers often discover OER through interactions with colleagues, social media, or participation in professional networks. In terms of practical use, some educators employ OER directly in the classroom as primary or supplementary materials, while others use them as inspiration or references to create their own teaching resources. However, the authors concluded that the pyramid model inadequately captures the complexity of the data and emphasized the need for qualitative studies to better understand teachers’ perceptions, experiences, needs, and expectations.

Similarly, Tang et al. (2020) conducted a mixed-methods study to identify the factors influencing teachers’ use of OER and how their adoption can be promoted. Drawing on Davis’s Technology Acceptance Model (Davis, 1989), the study found that perceived usefulness and ease of access were strong predictors of teachers’ willingness to implement OER. Teachers’ attitudes acted as mediating variables in the adoption process.

Time constraints also emerged as a significant barrier. Teachers often cite a “lack of time” as a reason for not engaging more fully with OER (Tosun & Altintas, 2024). In that study, educators expressed a need for greater institutional support and called for official mechanisms to ensure the quality of both OER repositories and the resources themselves.

A fundamental requirement for promoting OER use among educators is the ability to locate and identify relevant materials, often made possible using metadata. Schuwer and Janssen (2024) proposed two categorization systems to facilitate this process. The first categorizes OER based on resource type and its accessibility and adaptability. The second focuses on the value and applicability of the resource, including information about the subject area, educational level, pedagogical approach, and curricular alignment. Recent advances in artificial intelligence have further expanded the potential for OER by enabling the automatic generation of metadata tags to support classification and retrieval (Z. Li et al., 2024).

Regarding the impact of OER on teaching methodologies, Wiley et al. (2017) demonstrated that their use can significantly influence classroom practices. This impact is more pronounced when OER adoption is supported by long-term professional development programs and opportunities for practical application (Arispe et al., 2023).

In terms of professional development, Jensen and Kimmons (2022) highlighted the benefits of a collaborative model designed to transform teaching practices. Their model promoted more inclusive learning experiences, in line with the principles and values underpinning OER. It provided opportunities for co-creation, joint planning, discussion, and shared reflection. Classroom observations further enabled constructive feedback and professional growth, grounded in student outcomes and teaching practices.

In addition to professional development initiatives, Scott and Smith (2024) proposed a three-tiered framework for OER-driven educational transformation. At the individual level, teachers are encouraged to cultivate originality, creativity, and autonomy. At the professional network level, collaboration fosters broader impact and resource sharing. Finally, at the systemic level, structural change can be achieved to scale the educational benefits of OER adoption.

2.3. Impact of OER on Students

The study conducted by Delimont et al. (2016) identified highly positive attitudes toward the use of Open Educational Resources (OER) compared to traditional textbooks. These attitudes were associated with the perceived quality of OER, along with greater accessibility and lower costs for students. Similarly, instructors perceived that these resources enhanced and facilitated learning, and they expressed an intention to continue using them beyond the scope of specific courses.

Angelopoulou et al. (2022) examined the influence of several variables—such as gender, academic performance, socioeconomic status, and motivation to learn—on students’ perceptions of OER. Among these, only two variables showed a significant impact: preference for digital formats and motivation to learn. More positive attitudes toward OER were associated with higher levels of learning motivation.

Hilton (2020), in turn, reviewed research conducted between 2015 and 2018 on the use of OER in higher education. The review revealed a predominance of positive attitudes and outcomes among both instructors and students, who particularly valued the ease of access and cost reduction associated with OER. More recently, Glasserman-Morales et al. (2024) validated a questionnaire designed to assess OER adoption among university students. This instrument includes the following dimensions: ease of use, perceived usefulness, attitude toward digital resources, subjective norms, and sense of control.

Most studies identified focus primarily on attitudes and perceptions, while significantly fewer examine the actual impact of OER on learning outcomes. One of the most notable exceptions is the meta-analysis conducted by Tlili et al. (2023), which synthesized findings from 25 studies and demonstrated a positive effect on academic performance. Nevertheless, there remains a pressing need for rigorous research to evaluate the impact of OER on learning quality, in order to support evidence-based education and guide classroom practices and educational policy.

Following the previously commented study, Tlili et al. (2025) conducted a two-level analysis in two stages. Firstly, they conducted a systematic literature review, purposely selecting 32 papers and applying a meta-analysis to calculate the impact of OER and OEP on students’ performance. Then, Authors conducted a meta-synthesis according to the Activity Theory, to identify the factors leading to this impact. They found out that the overall effect is negligible although significant. A detailed look to explain these results show that almost half of the works reported a negative impact on students’ performance, leading to an overall small effect as a consequence of this fact. The effect reported depended on the subject, the educational level, the duration of the intervention and especially on the pedagogy behind the application of OER. Authors argued that very often OER were used as alternative resources integrated in a traditional transmissive teaching, not necessarily leading to learning improvement. Therefore, one of the main conclusions is the need to support OEP and OER-driven pedagogical innovation for student-centered meaningful and competence-based learning (Tlili et al., 2025).

2.4. A Theoretical Framework to Measure Motivational Aspects and Types of Learning

After revising the key aspects of the OER movement and discussing previous research on the effect of these resources on teachers and students and how they experience them, we will provide some theoretical foundation for the main constructs measured in this study. In particular, we will look at motivational aspects and how they influence students’ engagement and learning.

Motivation has been defined as the processes involved in the activation, orientation and persistence of behavioral in a particular direction. Pintrich’s work provides an interesting framework to relate motivation and learning (Panadero, 2017). One of his main contributions is the Motivated Strategies for Learning Questionnaire (MSLQ) which according to different reviews in the field, is still widely used (Honicke & Broadbent, 2016; Roth et al., 2016). The MSLQ is a complex instrument entailing 5 scales and a total of 81 items (Pintrich et al., 1993). Building on the theoretical model supporting the MSLQ, we intend to provide foundation to a simplified instrument better adapted to the sample and context of this study. To this end, we will discuss the main constructs underlining the instrument developed to evaluate the impact of OER on students’ motivation and learning.

One of the strengths of Pintrich’s model is that it is supported with robust theory and empirical data (Panadero, 2017). This model explains and predicts the relationship between motivational aspects and self-regulated learning, considering different aspects such as achievement goals, cognition, control, emotions and contextual factors.

When explaining students’ learning and engagement, Pintrich distinguishes between mastery goals and performance goals. Each of these achievement goals entails important differences concerning the type of driving motivation, the referent points (either self-set or external) and the sense of control and self-efficacy. For instance, mastery goals are associated with intrinsic motivation, enjoyment and interest in the activity per se, self-efficacy, deep learning strategies, low boredom, and greater persistence and effort (Hall et al., 2016). On the contrary, performance goals are associated with extrinsic motivation (e.g., passing an exam, achieving high marks, receiving external recognition, graduating or securing a job). In addition, performance goals tend to use external standards as referent points for success and usually entail a low sense of control and learning strategies related to memorization or repetition.

Other aspects having a strong relationship with motivation and learning are emotions. The control-value theory (Pekrun, 2006) states that students with mastery goals perceive the activity of personal value and focus their attention on improving their own understanding and competence and therefore, use self-referent standards (own learning), developing a sense of control on the process. These cases usually bring positive emotions related to one’s achievement such as pride and satisfaction. Conversely, performance goals take external referents as indicators of success (e.g., achieving high marks or outperforming others) and produce emotions such as anxiety.

Finally, another key element influencing motivation and learning orientation is self-efficacy. Building on Bandura’s model (Bandura, 1977), self-efficacy refers to an individual’s belief in their own capabilities to conduct a particular activity with success and usually bring positive emotions related to feeling competent and in control. Individuals usually exhibit intrinsic motivation and enjoyment in relation to those tasks that make them feel competent. Therefore, self-efficacy is usually associated with intrinsic motivation and with learning strategies orientated to understanding, mastery and deep learning.

The concept of deep learning is primarily rooted in constructivism and self-determination theory (Zhou & Zhang, 2025). Constructivism emphasizes learning as a process of actively re-structuring knowledge to incorporate new one in a meaningful and consistent way. These kinds of processes favor long-term learning and the capacity to apply and transfer previous learning to new situations, better preparing individuals to tackle and solve complex problems. Nevertheless, the terms “deep learning” and “surface learning” were firstly used by Marton and Säljö (1976) in a study looking at how different ways of engagement with information led to distinctive learning outcomes. Marton and Säljö (1976) defined deep learning as an active form of learning based on understanding, comprehension, critique, connection, construction, transfer, and application of knowledge. In contrast, surface learning was characterized by memorization rather than understanding. Surface learning is often associated with quick exam preparation and low cognitive engagement or reflection on the inherent meaning of knowledge (Zhou & Zhang, 2025).

As previously discussed, learning is closely connected to motivational aspects. From a psychological perspective, the self-determination theory highlights the importance of intrinsic motivation and autonomy in enhancing learning outcomes (Ryan & Deci, 2000). Ekwue and colleagues note that learners with high autonomy and intrinsic motivation are more likely to adopt deep learning strategies, focusing on the deeper meanings of knowledge. This autonomous approach aids learners in achieving sustained and profound mastery of knowledge (Ekwue, 2015).

Based on this theoretical framework, within this work, we have developed a questionnaire to evaluate the impact of EDIA OER on students that allow us to consider the key aspects influencing motivational aspects and students’ learning profile: intrinsic motivation, task-value (as indicator of external motivation considering the task as a means to attain an external goal), self-efficacy, surface learning and deep learning).

3. Materials and Methods

3.1. Context of Study: The EDIA Project

This study stems from a collaboration with “Anonymized,” an organization whose political and educational goals include the development and promotion of high-quality OER. This objective has been pursued through the EDIA project, which supports the creation of digital and methodological transformation processes in schools with the aim of improving student learning and promoting new school models (CEDEC, 2025).

EDIA offers an OER repository that includes learning situations for Early Childhood Education, Primary, Secondary, Baccalaureate, and Vocational Training. All OERs are aligned with national curricula and are structured as didactic sequences that promote the use of active methodologies. These resources aim to foster digital competence among both teachers and students. Each OER package includes all the necessary materials to implement the proposal in the classroom and assess student learning, including rubrics aligned with the official curricula.

Since EDIA OERs are developed using an open authoring tool, any teacher can freely download and use the materials or adapt them to their specific classroom context. To modify an OER, it is only necessary to install the open authoring tool on the device being used. Both the tool and the source files are available on the project website, which also hosts infographics, videos, and news updates, facilitating participation in a dynamic and continuously evolving initiative. The website highlights this community of practice by providing dialog spaces focused on the classroom implementation of OER. The teaching network fostered around these resources encourages experimentation and the sharing of teaching practices, while also promoting the discussion and analysis of new educational content models that aim to enhance learning, accessibility, gender equity, and digital citizenship. Within this context, a research collaboration was established to study teachers’ perceptions of EDIS OER, and how they influence collaboration and educational practices and the effect of EDIA OER on students’ learning and motivation.

3.2. Research Design

The study focused on teachers was based on the data collected from a sample of participants, purposely selected to represent the teacher population of EDIA OER users. The teacher sample is described later, along with the structure and characteristics of the questionnaire specifically developed and validated for the purpose of this study.

The study about the impact of the EDIA OER on students applies a correlational/non-experimental comparative design. These designs do not involve manipulation of the independent variable or group assignment by the researcher, but rather observe and compare characteristics or outcomes between groups already differentiated by a variable, in this case, learning through EDIA OER (Starbuck, 2023).

3.3. Instruments

3.3.1. Teacher Questionnaire

The investigation into teachers’ beliefs and perceptions of OER in general and EDIA OER, in particular, followed a methodology, aiming to capture their perspectives and experiences with those resources. Teachers were questioned about the reasons that motivated them to adopt or develop OER, the criteria they applied in doing so, and the main barriers and opportunities they identified. Additionally, they were asked about the perceived influence of EDIA OER on classroom processes, student learning, and collaboration with colleagues.

Specifically, the teacher questionnaire included an initial section designed to collect demographic and professional information about the participants (gender, teaching experience, and knowledge and experience with OER); this information was used to describe the sample, as presented in the following paragraphs. Below, there is a set of items with response options derived from the relevant literature. These options aimed to reflect the most commonly cited, significant, and representative aspects of teachers’ beliefs and attitudes in this field. These items were related to the study’s key areas of interest: (i) perceptions of OER; (ii) motivation and criteria for generating, using, and selecting OER; (iii) main barriers to the creation and use of OER; and (iv) perceived benefits and opportunities.

Questions related to these key areas were included in the questionnaire in three sections: the first focused on the impact on students, the second on professional development, and the third focused on the actions of creating and sharing OERs:

The first section, with questions about the possible impact on students, includes items such as in which level teachers used OERs, in which subject, for what purpose, possible support from their school in this type of professional actions, what criteria they usually consider when choosing OERs, the most valuable aspects of OERs, and the negative aspects of these resources. In this section, some questions required teachers to select possible answers (e.g., If you had to describe OER EDIA to a colleague who was not familiar with these digital resources, which of the following statements would you include in said description? (a) they are free, (b) they can be edited and reused, (c) they have a Creative Commons license, (d) they are easy to combine with other digital educational resources… and so on, up to 14 possible answers) and in others, to explain their degree of agreement or disagreement on a 5-point scale (e.g., Please indicate your degree of agreement or disagreement with the following statements: Using OER EDIA improves my students’ motivation).

The second section, which focused on teacher professional development, included questions asking teachers to indicate their level of agreement or disagreement with different statements on a 5-point scale (e.g., Please indicate your level of agreement or disagreement with the following statements: To obtain optimal benefits from working with OERs, we should use OERs to practice what we have learned).

Finally, the third section, focused on questions about the options for creating and sharing OERs, included questions in which teachers had to choose options (e.g., If you have created your own open educational materials, what motivates you to create OERs? (a) To help other teachers, (b) To improve the quality of my materials, … and so on, up to a total of 9 different options in this case).

3.3.2. Student Questionnaire

The student questionnaire was developed based on a review of the specialized literature in order to identify the key aspects of the constructs under investigation—namely, motivation and learning approach. The resulting scales were statistically validated to assess their internal consistency and reliability.

The questionnaire comprised two main sections. The first section gathered demographic data including gender, age, academic year, educational institution, and subject area. The second section included a series of statements aimed at measuring students’ levels of motivation, perceived self-efficacy, task value, and learning approach (deep vs. surface learning). Although it is an original instrument, it draws on previously validated tools and aligns with contemporary psychometric theory related to the constructs studied, such as intrinsic motivation, task value, self-efficacy, and learning depth. The theoretical framework underpinning the student questionnaire has been extensively discussed in the theoretical background.

The instrument was piloted in various phases with different cohorts of secondary education students (overall N = 230). The questionnaire was initially designed using a pool of 38 items elaborated from the theoretical and conceptual review of the dimensions of motivation, self-efficacy and learning approaches mentioned above. However, after the Principal Component Analysis (PCA, varimax), it was decided to discard 18 items that did not meet the established psychometric criteria. The items were eliminated for one or more of the following reasons: (a) they had factor loads less than 0.40, indicating a low contribution to the corresponding theoretical dimension; (b) exhibited significant cross-loads in two or more factors, which made their interpretation difficult and compromised discriminant validity; or (c) they showed very low commonalities, suggesting that the item might be inadequately represented by the underlying factor structure. A second EFA (method: minimum residuals; rotation: obliming; number of factors: parallel analysis; Revelle, 2024; Jamovi Project, 2023) finally yield a 20 items (

Table 1. Recent contributions from the specialized literature discussed as part of the theoretical background.

Main Aspects Discussed in the Theoretical Background	Authors and Year of Publication	Published in
Origin of the term OER	Tlili et al. (2025)	Humanities and Social Sciences Communications
Key characteristics of OER	Tlili et al. (2023)	International Journal of Educational Technology in Higher Education
Collection of cases illustrating the fundamental values underlying the OER philosophy	Bozkurt et al. (2023)	Open Praxis
The key dimensions of Open Educational Practices (OEP)	Huang et al. (2020)	Smart Learning Environments
The role of metadata in the identification and exploitation of OER	Schuwer and Janssen (2024)	Open Praxis
Artificial Intelligence application to enhance the use of OER	Z. Li et al. (2024)	Computers & Education
Teachers’ views on OER	Tosun and Altintas (2024)	Turkish Online Journal of Distance Education
Factors influencing teachers’ use of OER	Tang et al. (2020)	British Journal of Educational Technology
Teacher Professional Development and OER	Arispe et al. (2023)	Open Praxis
How OER can support teacher collaborative learning to enact equitable teaching practices	Jensen and Kimmons (2022)	Journal for Multicultural Education
Digital technologies, teacher development and reciprocity with organizational innovation	Scott and Smith (2024).	Open Learning: The Journal of Open, Distance and e-Learning
Factors affecting student educational choices regarding OER.	Angelopoulou et al. (2022).	Journal of Computers in Education
OER adoption among university students	Glasserman-Morales et al. (2024).	Journal of Social Studies Education Research
OER, student efficacy, and user perceptions: A synthesis of research published between 2015 and 2018.	Hilton (2020).	Educational Technology Research and Development
Findings from 25 studies about the impact of OER on students’ performance	Tlili et al. (2023).	International Journal of Educational Technology in Higher Education.
Factors affecting the impact of OER on students.	Tlili et al. (2025).	Humanities and Social Sciences Communications.
Students’ superficial and deep learning	Zhou and Zhang (2025).	Education Sciences.

) structure of the questionnaire, coherent with the pretended construct. The sample adequacy was confirmed with a KMO index of 0.91 and a significant Bartlett’s sphericity test (χ² = 3888.45, df = 190, p < 001), which supports the appropriateness of the analysis explaining 57.6% of covariance. Overall, these results support the structural validity of the instrument and its suitability for use in educational contexts. The analysis was complemented and reinforce using a matrix of polychoric correlation (C. H. Li, 2019) yielding similar results in terms of questionnaire internal validity (more information in Section 2.2 and in Appendix A).

Validation yield reliability indicators (Viladrich et al., 2019) consistent with findings in the existing literature (see

Table 2. Validated Student Questionnaire. Retained items, dimensions and reliability indices.

Dimension (Cronbach α) (ω MacDonalds)	Items (Retained)
Intrinsic motivation (.881) (.881)	I like this subject. I enjoy the classes of this subject. I love doing activities related to this subject. I don’t like this subject” (inverted punctuation).
Task Value (.845) (.848)	What I learn is useful. This subject provides me with important knowledge for life. This subject helps me understand the world around me. What I learn in this subject helps me make good decisions in my life.
Self-efficacy (.904) (.905)	I am good at exams in this subject. I can understand difficult concepts of this subject. This subject is easy for me. I understand this subject.
Deep Learning (.808) (.811)	I need to understand what I learn. I try to relate what I learn to what I already know. I tend to relate ideas by looking for common ground. I like to understand where the ideas I have to learn come from.
Surface learning (.806) (.806)	I memorize even if I don’t understand it. I don’t usually ask myself questions about what I study. I study thinking about what they will ask me in the exam.

) for social sciences studies and coherent with previous version of the questionnaire. In addition, the Factor Loadings and Dimensional Structure from EFA is displayed in Appendix A.

3.4. Validation and Analysis

The teacher questionnaire was based on the specialized literature about teachers and OER and was subjected to external validation by experts from different fields: 3 experts in OER-based research; 2 experts in OER teacher professional development and 7 experts in OER development and use. After the feedback received from all experts, a new, revised version was agreed. The revision entailed re-phrasing some of the items, eliminating others and formulating new ones, according to the suggestions received.

The analysis of teacher survey responses was carried out by calculating response frequencies for each of the predefined analytical categories. Open-ended responses were analyzed through content analysis conducted independently by two researchers using MAXQDA 2020 (VERBI Software, 2020). Iterative coding cycles were employed to ensure inter-rater reliability, reaching an agreement level of 90.0% or higher before resolving remaining discrepancies by consensus.

Internal validation of the student’s questionnaire was carried out using the statistical packages SPSS (IBM Corp., 2022), R (R Core Team, 2025) and RStudio Team (2025), through Principal Component Analysis (PCA) and Exploratory factor analysis (EFA). In the initial phase of validation of the internal structure of the questionnaire used for this study of students’ motivation and learning approach, a classic exploratory factor analysis (EFA) was initially conducted in the SPSS statistical package, based on the analysis of the Pearson correlation matrix. However, given that the questionnaire items were of the ordinal Likert type and traditional factor analysis assumes continuous and normally distributed variables, it was considered necessary to reinforce and complement the procedure using a matrix of polychoric correlations (C. H. Li, 2019). When working with ordinal variables, this type of analysis offers a more adequate estimate of latent relationships and is especially useful in the psychometric validation of educational instruments. As SPSS does not directly allow the calculation of polychoric correlations and thus for this phase of the analysis we used R studio (version 2.4) to generate the polychoric matrix and package psych (Revelle, 2024).

Data processing and statistical analyses were primarily conducted using Jamovi software (version 2.4; Jamovi Project, 2023). The scores in the different scales analyzed (Table 2) come from the sum of Likert-type items. The non-parametric Mann–Whitney U test has been applied to determine significant differences in the measurements. This decision is based on a conservative position, on the ordinal nature of the original answers (although the sum could be considered somehow in some extension as scale) and on the methodological precaution of not assuming a normal distribution, added to an unequal number of individuals in the control and experiment group. This test allows two independent groups to be robustly compared without making assumptions about the distribution although there is sufficient evidence to indicate that it does not follow a normal distribution (Shaphiro–Wilk test W = [range .973–.974], p < .001). The whole teacher questionnaire is available in Appendix B.

3.5. Procedure and Ethical Considerations

The research protocols, data collection instruments, informed consent procedures, and data handling methods received a favorable review from the Human Research Ethics Committee of the University of “Anonymized.”

3.6. Sample

The characteristics of the participants corresponding to the samples of teachers and students, respectively, are described below.

3.6.1. Teachers

For the teacher sample, a purposive sampling strategy was employed, based on teaching profiles and experience with OER in general and EDIA OER in particular. A total of 40 teachers were selected, all with more than 10 years of teaching experience at the Secondary and Baccalaureate levels. Among them, 85.0% reported over 11 years of teaching experience, and 45.0% had more than 20 years of experience. Additionally, 87.5% indicated that they had been familiar with OER for at least three years, and 60.0% had been using these resources in their classrooms for over three years. Moreover, 70.0% of the sample reported familiarity with OER from other repositories.

3.6.2. Students

To investigate the influence of EDIA OER on student motivation and learning approaches, a student sample provided by the teachers participating in the study was organized into two independent groups, distinguished by the variable “use of OER. The student sample intended to be representative of the students having experienced EDIA OER. The comparison group was selected by the participant teachers as representative of students in similar contextual conditions but not having used EDIA OER. The group of students who used OER as part of their learning experience constituted the OER-group (N = 219, 43.6% female), while the students who had not used OER (“Non-OER”) formed the comparison group (N = 136, and 51.2% female). The questionnaires were electronically distributed by teachers at the beginning of the second semester in 2022 and students were voluntarily invited to fill it. Both groups consisted of students in Compulsory Secondary Education in Spain aged 12–17 years with an average age of 14 years.

4. Results

4.1. Results About Teachers’ Perceptions and Experiences with EDIA OER

A total of 75.0% of the teachers in this study reported using OER as the main instructional material in their classes, and 65.0% also indicated using them as complementary resources. Regarding their experience in the creation of OER, 70.0% of the sample stated that they had developed their own open digital resources at some point. The most frequently mentioned types of resources included full or partial didactic sequences, presentations, images or infographics, and assessment tools.

The data also show that teachers primarily share their OER through cloud storage platforms, personal websites, or the Spanish Ministry platform. However, 40.0% of the teachers reported creating digital resources without sharing them, mainly due to a lack of training or uncertainty about copyright and open licensing options.

When asked about the motivations for creating and using OER, 81.0% cited improving the quality of their instructional materials as their main motivation for resource creation, and 82.1% expressed a willingness to share their materials. The main motivations for using OER were to improve student learning (82.0%) and to better adapt to students’ needs and preferences (75.1%).

In terms of criteria used to select EDIA OER, 47.5% of the teachers valued the inclusion of all necessary materials and resources for classroom implementation. Additionally, 45.0% considered alignment with the official curriculum to be essential. The ability to adapt and edit resources was considered important by 42.5% of respondents, while 40.0% highlighted resource quality and content accuracy as primary selection criteria. Furthermore, 35.0% positively valued the presence of user feedback and evaluations from other teachers who had implemented the resources.

Regarding the perceived impact of EDIA OER on classroom practices, 67.5% of teachers reported that these resources promote active teaching methodologies, 65.0% believed they foster skill development, and 57.5% pointed to their potential to enhance collaborative learning. Moreover, teachers noted that EDIA OER supports the use of varied assessment tools, offers reusable and editable materials (50.0%), and can be easily integrated with other resources (45.0%).

Notably, teachers’ responses emphasized features such as reusability and granularity—key principles of the OER paradigm—indicating that the evaluated resources align with this model and are valued as such by users. This supports the notion that teachers appreciate OER not only for their pedagogical utility but also for their adaptability and potential for collaborative refinement. Recent reports, such as the Commonwealth of Learning Global Report (COL, 2017), and academic literature (e.g., Beaven, 2018), underscore that while collaboration is encouraged, many efforts still occur in isolation. Furthermore, most initiatives focus on the creation of new resources, while insufficient attention is given to improving or adapting existing ones through iterative cycles of use. Similar conclusions are echoed in reports from the International Council for Open and Distance Education (Orr et al., 2018) and the UNESCO Institute for Information Technologies in Education (Hoosen & Butcher, 2019).

With respect to institutional support, 68.0% of the teachers indicated that their schools promote technological innovation in teaching and recognize the use of digital resources in the classroom. However, they also expressed a need for more training opportunities and clearer institutional guidance regarding intellectual property and open licensing.

Finally, the main barrier to OER creation identified by teachers was a lack of time, often linked to school structures that do not account for the time required to develop new educational resources.

Teachers’ perceptions of the type of learning promoted by OER are consistent with the learning profiles of students who use them (see below). More than 52.0% of teachers reported that, in contrast to traditional approaches based on teacher-led explanations and textbooks, the use of OER encourages active methodologies, discourages rote learning, and promotes more meaningful and competency-based learning.

4.2. Rusults About Effects of EDIA OER on Students

Regarding the learning outcomes associated with the use of EDIA OER, more than 75% of the surveyed teachers reported observing various positive effects. These included increased positive attitudes toward learning, the development of self-directed learning and motivational skills, and meaningful acquisition of disciplinary knowledge with clear applicability to everyday contexts and across different subjects. Additionally, they noted improvements in transversal skills such as cooperation, critical thinking, creative learning, digital competence, communication skills, and the ability to express ideas and emotions.

The analysis of the student questionnaire data was conducted using a construct scale with the following dimensions (Table 2), that is, motivation, self-efficacy, task value, deep learning, and surface learning.

Table 3. Descriptive Statistics, Mann–Whitney U Test Results, and Effect Sizes (Rank-Biserial Correlation) Between OER and Non-OER Groups.

Scale	Group	Students (N)	Mean (M)	Median (MED)	U	p	Effect Size
Motivation a	Non-OER	136	3.22 (1.10)	3.38
	OER	219	3.62 (0.84)	3.75	11,879	.001	.202
Task value b	Non-OER	136	3.29 (0.93)	3.40
	OER	219	3.76 (0.77)	3.80	10,277	<.001	.310
Self-Efficacy a	Non-OER	136	3.29 (1.04)	3.50
	OER	219	3.56 (0.91)	3.75	12,795	.025	.141
Meaningful Learning a	Non-OER	136	3.63 (0.93)	3.75
	OER	219	3.87 (0.72)	4.00	12,729	.021	.145
Surface learning	Non-OER	136	2.95 (0.96)	3.00
	OER	219	2.97 (0.91)	3.00	14,855	.969	.002

Ha: U-Mann–Whitney test. ^a Differences at significant level p < .05; ^b Differences at significant level p < .001. Effect sizes were computed as rank-biserial correlations (r_sb). Source: Authors.

presents the mean scores (and their corresponding standard deviations) for the comparison group (Non-OER) and the OER-group, across the analyzed dimensions.

The results of the Mann–Whitney U tests revealed statistically significant differences between students in the OER and Non-OER groups across most of the analyzed scales (see Table 2). Specifically, significant differences were found in motivation (U = 11,879, p = .001), task value (U = 10,277, p < .001), self-efficacy (U = 12,795, p = .025), and deep learning (U = 12,729, p = .021). No significant differences were observed in surface learning (U = 14,855, p = .969). To enrich and complement the analysis, effect sizes were calculated using rank-biserial correlation (r_sb). The largest effect was observed for self-efficacy (r_sb = .310), indicating a moderate association between the use of OER and students’ perceived self-efficacy. Motivation also showed a meaningful effect size (r_sb = .202), suggesting that students in the OER group reported higher motivation levels compared to their peers in the Non-OER group. Task value (r_sb = .141) and deep learning (r_sb = .145) exhibited small effect sizes, yet still association within the OER group. The effect size for surface learning was very small value (r_sb = .002), reinforcing the absence of a statistically significant differences between groups. With regard to learning patterns, the average score for surface learning is close to 3 (on a normalized 5-point scale) for both groups, with no statistically significant differences (U = 14,268, p = .505): 2.95 (SD = 0.96) for the Non-OER group and 2.97 (SD = 00.91) for the OER group. This suggests that surface learning is reported to a similar extent in both groups. However, statistically significant differences were observed in deep learning, with higher scores in the OER group. These findings could indicate that while surface learning coexists with deep learning in both groups, the latter is more prominent among students using OER. However, these two types of learning show weak and not significant correlations within the group.

The statistical tests to compare intergroup scores for the scales between men and women did not show statistically significant differences (e.g., for self-efficacy U = 14,509, p = .966), suggesting that the distribution of scores on the scales studied is similar between both genders in intragroup. However, the p-value for the deep learning dimension (p = .064) is close to the conventional threshold (p = .05), which could indicate a potentially relevant aspect from the educational point of view for the analysis of this dimension and gender differences.

The Spearman correlation analysis was conducted to examine the relationship between the dimensions of motivation, task value, and self-efficacy, types of learning strategies, and demographic variables (age and course), differentiating between the two groups studied. This analysis shows that in the group that did not use OER, a strong correlation was observed between motivation and task value (ρ = .77, p < .001), as well as between motivation and self-efficacy (ρ = .71, p < .001). Additionally, deep learning positively correlated with motivation (ρ = .50, p < .001), self-efficacy (ρ = .55, p < .001) and task-value (ρ = .54, p < .001). In contrast, surface learning showed weak, negative and no significant correlation with other scales (e.g., motivation ρ = −.06, p = .46).

For the group that did use OER, positive and significant correlations were observed between motivation and self-efficacy (ρ = .57, p < .001), as well as between motivation and deep learning (ρ = .44, p < .001). The correlation between motivation and task value was moderate but significant (ρ = .45, p < .001), while the relationship between self-efficacy and surface learning was negative but significant (ρ = −.25, p < .001).

Importantly, in both groups, meaningful learning was positively and significantly correlated with motivation, self-efficacy, and task value, which also exhibited positive intercorrelations with each other.

The variables age and course show weak correlations in both groups, although some associations reached statistical significance (e.g., motivation*age ρ = .19, p = .006), an aspect that can be taken into account for the disaggregation of data in future analyses.

Although it is not the object of this work, the preliminary results obtained through de Multiple linear regression analysis revealed that the group of OER students was significantly associated with higher scores on the dimensions of motivation (R² = .08, p < .001), task value (R² = .121, p < .001), and deep learning (R² = .04, p = .035), after controlling for sex, age, and course. Self-efficacy and surface learning did not show significant effects in the models (p > .05), suggesting that these dimensions are not modulated by the predictors considered.

5. Discussion and Conclusions

Within this section, we will further discuss the results previously presented, considering the research questions and the context of study. In addition, we will discuss those results in the light of previous research in the field, identifying key contributions, limitations and future lines of work. We will especially focus on those aspects directly related to the research gap identified in the specialized literature, responding to the need to conduct studies that triangulate data from both teachers and students in order to develop a better understanding of the impact of OER on students’ motivation and learning, as a result of the resources and pedagogies applied.

5.1. Discussing Teachers’ Perceptions and Experiences with EDIA OER

EDIA OER are characterized by open-ended activities that promote inquiry, problem-solving through multiple strategies, discussion and argumentation, feedback, error correction, and ultimately, the development of more autonomous, competency-based, and meaningful learning. The emphasis on inquiry-based and open-ended learning aligns with recent OER-oriented research (Grimaldi et al., 2019), that argue that while OER can support student success, their greatest impact really emerges when pedagogical strategies are parallel to resource use, especially for students who might otherwise lack access to quality and adapted materials. In this regard, the findings of this study indicate that teachers who use EDIA OER value the ability to adapt and modify these resources to meet the specific needs of their classrooms. They report that these resources support the implementation of active methodologies, cater to diverse learning styles, and help engage students who might otherwise remain disengaged with more traditional approaches. Teachers also highlight the potential of EDIA OER to enhance student motivation and involvement, support inclusion and attention to diversity, and improve learning outcomes. In this sense, OER are perceived by teachers as well-aligned with one of the core priorities of the European Education Area: enhancing quality and equity in education and training (European Commission, 2023). In addition, these results are consistent with recent findings from STEM education research, where the integration of OER with active methodologies has been shown to enhance creativity, problem-solving skills, and engagement, particularly in primary education settings (Arabit-García et al., 2023). The use of open platforms and hands-on strategies in that context further supported learners’ motivation and their connection between scientific content and real-world applications.

Apart from their open access nature, the methodological pillars underlying the OER conceptualization, that teachers noticed, could therefore be considered suitable pathways toward inclusive education, as suggested by Ossiannilsson (2019) discussing specifically about OER and equity or by Milanovic et al. (2023) reporting on inclusive classroom practices, who highlight the importance of flexible, student-centered practices for addressing diverse educational needs in real classroom contexts.

However, teachers frequently reported the need for training in order to implement them effectively in the classroom (Fränkel et al., 2023), an area in which OER, due to their intrinsic features, could provide valuable support and opportunities for professional development. In line with this, Baas et al. (2023) emphasize that participation in inter-institutional OER communities can serve not only as a source of pedagogical resources, but also as a powerful context for informal and sustained professional development, especially when value creation is explicitly addressed and supported by institutions. Nevertheless, despite institutional recognition of the value of OER and digital competence, teachers reported in the present study that the effort required to design and implement these resources is not adequately acknowledged. A lack of time emerges as the main barrier to the creation and sustained use of OER. This tension reflects a broader challenge noted by Grimaldi et al. (2019): while OER can reduce barriers to access, their impact on teaching effectiveness is limited when structural conditions—such as time, training, or recognition—remain insufficiently addressed.

Furthermore, based on the above findings showing that teachers also act as developers of their own OER, training programs should consider the role of teachers as designers, but also as critical analysts of existing OER, enabling them to enrich and adapt them to their own classroom needs. This approach, facilitated by the OER context, may improve teachers’ professional development. Teachers that participate in the adaptation and design of OER are exposed to new ways of conceptualizing their own classroom practice. In fact, adopting a designer profile may represent one of the final steps in teachers’ engagement with the OER lifecycle, typically occurring once they feel confident enough to share their resources with the teaching community (Beaven, 2018). Teachers draw on their cognitive, effective and systemic knowledge throughout the entire OER lifecycle (selecting, creating, adapting, using and sharing resources) which enables them to make complex pedagogical decisions and adapt their teaching to unforeseen situations promoting self-reflection and flexibility (Beaven, 2021), both key skills for professional growth. These competencies are also reflected in the “applied” and “realized” value dimensions described by Baas et al. (2023), where teachers who engage with OER communities report changes in their teaching practices, improved collaboration with peers, and deeper reflection on their pedagogical roles. However, although 70% of teachers participating in the present study reported creating OER, 40% actually do not share them with others but around 82% of respondents would like to do so.

Despite these limited resource-sharing practices that teachers reported in the present research, and also in others (Flowers et al., 2024), they particularly appreciate peer feedback on shared resources, which encourages critical reflection on their own instructional practices and fosters collaboration and the formation of professional learning communities. This contrast between teachers’ positive perceptions and their actual practices may reflect a need for facilitated mechanisms and training that empower teachers to share their resources more effectively. The work by Flowers et al. (2024) identifies both institutional and cultural barriers (lack of recognition, uncertainty about quality, and absence of collaborative infrastructure) as key factors limiting open sharing despite positive attitudes toward OER. Thus, the mentioned mechanisms could include structured community-building strategies, mediator roles, and recognition systems, as proposed by Baas et al. (2023), who document how supportive structures within OER communities increase both the frequency and quality of teacher collaboration and sharing practices.

Among the various community-building strategies in education, one of the most well-established is the formation of teacher communities of practice. These communities are defined as groups of individuals who share a common interest or concern and come together to learn from one another, develop skills, and deepen their conceptual understanding (Patton & Parker, 2017). Nevertheless, fostering genuine and fruitful collaborative practices within these communities should not be assumed as a given, but rather approached as a deliberate and sustained effort (Quesada et al., 2023).

There is substantial evidence showing how OER can foster sustainable teachers’ communities of practices and, at the same time, engagement in a community of practice has been shown to be the most significant driver for OER sharing (Baas et al., 2023; Flowers et al., 2024). This dual effect is grounded in the OER lifecycle, a process that not only improves the resources themselves but also transforms their creators by encouraging critical reflection on their teaching practices (Beaven, 2021). In this line, Kleinschmit et al. (2023) propose a framework of linked communities of practice, which includes resource incubators for the creation, improvement, and quality assurance of OER; teacher mentoring networks to facilitate the adoption, adaptation, and classroom implementation of OER providing ongoing training and support; and educational research communities to evaluate OER effectiveness and refine assessment tools. This framework aims to overcome barriers to educational reform, develop high-quality OER, and empower educators, with a strong emphasis on peer interaction and community support. These communities help teachers transform private drafts into publishable, community-validated OER, thereby addressing one of the key barriers to sharing identified by Flowers et al. (2024): teachers’ low confidence in the quality of their resources when they have not undergone peer or expert review or design support. This also highlights the importance of involving instructional designers as supportive agents in these communities of practice (Wiley, 2020).

As the driving force behind the EDIA project, the CEDEC actively follows this mindset and fosters the development of a community of practice around the OER concerning this research by organizing regular in-person meetings that encourage dialog and the exchange of experiences related to the implementation of EDIA OER in all educational settings. This approach could have been a factor behind the percentage of participating teachers who share OER reported in this study; just 40% of them do not share their resources, a promising mark compared with the results reported by Senn et al. (2022) who found that 28% of the explored instructor sample actually share these resources or the low figures for sharing dynamics discussed by Beaven (2021) or Flowers et al. (2024). Furthermore, the impact of this community of practice lies not only in its engagement with the OER lifecycle, but also in its role as a transformative driver of teachers’ pedagogical practices towards those envisioned by the EDIA OER instructional model (Romero-Ariza et al., 2023). Building on this idea, changes in teachers’ classroom practice can also be driven by learners’ outcomes (de Barros et al., 2024) and students’ performance can be largely explained by the effect of the teachers (Rivkin et al., 2005). In this context, the effect of EDIA OER on students’ motivation and learning observed in this study, when compared to a control group not exposed to these resources, may be attributed not only to the mere introduction of the OER in the classroom, but also to the pedagogical design principles underlying the OER and the resulting methodological transformation of teachers’ practices.

5.2. Discussing the Effects of EDIA OER on Students

Teachers’ perceptions of the positive effects of EDIA OER on student motivation and learning are supported in this study by the comparative analysis of students whose teachers use EDIA OER versus those who do not. While the magnitude of the differences varies across grade levels, students exposed to EDIA OER consistently report higher levels of motivation, perceived self-efficacy, and task value, as well as a greater prevalence of meaningful (deep) learning. Interestingly, surface learning appears equally present in both groups, but the level of deep learning is significantly higher among students who use EDIA OER. These findings align with previous literature that acknowledges the coexistence of both learning styles (González-Cabanach, 1997).

The correlation analyses further reveal that motivation is positively associated with task value and self-efficacy, which, in turn, are linked to the dominant type of reported learning. These results are consistent with the notion that individuals are more likely to be motivated by tasks they value or feel competent performing. High levels of involvement are associated with meaningful learning, which itself correlates positively with motivation, task value, and self-efficacy, and negatively with surface learning. In contrast, students who engage in surface or rote learning tend to report lower levels of motivation and self-efficacy, likely due to the lack of meaningful engagement and conceptual mastery.

These findings are coherent with established research on student motivation and learning, as well as the theoretical model underpinning the design of the measurement instrument used in this study. Previous research shows important differences in motivational and learning profiles depending on students’ orientation (either to mastery or performance). Mastery goals are usually associated with deep learning strategies and high-self-efficacy, alongside greater persistence and effort. This orientation is also related to intrinsic motivation and positive emotions such as interest in the activity per se, enjoyment and, low boredom (Hall et al., 2016; Panadero, 2017; Pekrun, 2006; Zhou & Zhang, 2025).

Teachers using EDIA OER describe how the pedagogical design underlining these resources engages students in active learning, increasing their sense of control and the perceived value of the learning task. The classic self-determination theory in Psychology highlights the importance of autonomy in enhancing intrinsic motivation and relevant learning outcomes (Ryan & Deci, 2000). In addition, Ekwue and colleagues showed that learners with high autonomy and intrinsic motivation were more likely to adopt deep learning strategies, which in turn bring meaning and mastery (Ekwue, 2015).

These results are again triangulated with those obtained from the student questionnaire, showing that students using EDIA OER exhibit higher levels of deep learning, intrinsic motivation, task value and self-efficacy. According to the specialized literature in the field, self-efficacy makes students perceive their own capabilities to conduct a particular activity with success, feeling competent and in control. Individuals usually exhibit intrinsic motivation and enjoyment in relation to those tasks that make them feel competent and in control. Therefore, self-efficacy is usually associated with intrinsic motivation and with learning strategies orientated to understanding, mastery and deep learning (Bandura, 1977; Hall et al., 2016; Panadero, 2017).

Finally, results show how students using EDIA OER exhibit significantly higher levels of deep learning than those learning through traditional resources. Some authors discuss how surface learning related to transmissive teaching is usually characterized by memorization rather than understanding and often associated with quick exam preparation and low cognitive engagement or reflection. On the contrary, deep learning is associated with long-term learning and the capacity to apply and transfer previous learning to new situations, better preparing individuals to tackle and solve complex problems (Zhou & Zhang, 2025). These results are very relevant considering the easy access to information and current advances in artificial intelligence, which require more than ever individuals capable of developing deep learning and problem-solving skills.

5.3. Final Remarks, Limitations and Future Lines of Work

In conclusion, this study provides empirical evidence for the benefits of implementing EDIA OER in terms of promoting teacher collaboration and professional development, facilitating the creation of communities of practice, and enhancing student-centered pedagogical practices. These, in turn, contribute to improved classroom instruction and higher student motivation, as learners perceive greater task value and engage in deeper learning experiences that reinforce their sense of competence and self-efficacy. Similar outcomes were observed in STEM-focused classrooms where OER and active learning strategies were co-deployed. Arabit-García et al. (2023) report increases in students’ problem-solving capacities and motivation when these elements are combined with real-world, context-rich activities.

Beyond the relevance of the specific findings, this research also addresses ongoing criticisms regarding the lack of valid and reliable instruments for systematically assessing the quality and impact of OER on teaching and learning processes. A key contribution has been the design and validation of an original student questionnaire carefully developed based on an extensive review of the specialized literature. Our instrument effectively captures the theoretical constructs of motivation and learning approach, demonstrating strong psychometric properties in terms of internal consistency and reliability. Its structure includes scales measuring intrinsic motivation, task value, perceived self-efficacy, and learning style (deep vs. surface). While inspired by well-established tools such as the well-known MSLQ by Pintrich et al. (1993), this questionnaire stands out for being both robust and theoretically grounded, while also remaining simple and concise. Nevertheless, the conclusions presented here must be understood within the limitations of the study, as discussed below.

The comparison of student motivation and learning patterns is based on whether or not teachers used EDIA OER, without accounting for other potentially influential variables such as prior academic achievement, teachers’ pedagogical styles or the broader institutional context. Additionally, while the student questionnaire was piloted and statistically validated, the quasi-experimental design did not include random assignment, which limits the ability to establish causal relationships. Differences between the control and experimental groups may be influenced by factors beyond the presence or absence of OER-based instruction, including teacher experience, school culture, or curricular emphasis. Future studies should further investigate how contextual and pedagogical variables mediate the relationship between OER use and its impact on teaching practices, student learning, and classroom dynamics.

Regarding the teacher data, the purposive sampling strategy—although appropriate for exploratory research—limits generalizability. The participating teachers already had significant experience with OER, which may have resulted in more favorable perceptions and higher engagement levels than those of the broader teaching population. This is consistent with concerns raised in prior studies (Flowers et al., 2024) about selection bias in OER-related research, particularly when participation is voluntary and based on familiarity with open practices. However, it must be taken into account that the results presented stem from the evaluation of OERs within the EDIA project, which necessarily entails an inherent constraint in the sampling method.

Our study provides valuable insights into teachers’ reflective processes and their role as resource designers; however, it does not examine how these practices evolve over time. Longitudinal studies would be useful to capture how sustained involvement with OER communities affects teacher identity, collaboration, and innovation, including their capacity to adapt, reuse and share OER—core practices of OER-based pedagogy.

Finally, although student learning outcomes were assessed through validated self-report instruments, future research could consider triangulating these data with objective performance measures and classroom observations to further capture the possible nuances of engagement and deep learning.