Development and validation of a competence measurement scale for digital experiential learning in child sexual abuse prevention education for student teachers

Abstract

Introduction:

This study aims to develop and validate a measurement scale for student teachers' competence in designing and implementing digital experiential learning activities on child abuse prevention education.

Methods:

Data were collected from 1,379 preservice teachers (from first- to fourth-year students) across four teacher education institutions in Vietnam between October and November 2025. Of these, 879 valid responses were used for statistical analyses using SPSS 26.0 and AMOS 24.0, including Exploratory Factor Analysis (EFA, n = 440) and Confirmatory Factor Analysis (CFA, n = 439).

Results:

The results confirmed a hierarchical model comprising one overarching competence and eight sub-competence domains: (1) Defining learning objectives and content; (2) Scenario design; (3) Developing digital learning materials; (4) Ensuring digital safety and ethics; (5) Preparing digital classrooms; (6) Managing and facilitating activities; (7) Organizing experience -reflection -application; and (8) Conducting assessment and feedback cycle. The measurement model comprised 47 observed variables, including 38 items representing eight competence domains and 9 indicators measuring the overarching competence, demonstrating high reliability, discriminant validity, and strong construct coherence.

Discussion:

Findings provide empirical evidence supporting the application of this scale in enhancing digital pedagogical competence among preservice teachers in Vietnam's educational digital transformation context.

1 Introduction

Child sexual abuse is a complex and persistent global issue that profoundly affects children's physical, emotional, and social development (Allen et al., 2020; Craig, 2022). Numerous studies have affirmed that preventive education within school settings is among the most effective measures to mitigate risks and enhance students' self-protection competencies (Del Campo and Fávero, 2019; McTavish et al., 2021; Wu et al., 2024). In-service teachers continue to encounter psychological barriers and practical difficulties when teaching this type of content, especially in digital and online settings (Cunnington and Clark, 2023; Dimitropoulos et al., 2022; Greenwood, 2025). These challenges are compounded by the rise of new forms of abuse, including image-based and online sexual exploitation, which have become increasingly common (Henry et al., 2023). There is an urgent need to strengthen teachers' and pre-service teachers' skills in developing and delivering educational activities to prevent child sexual abuse in digitally transforming learning environments.

Building on Kolb's (1984) experiential learning theory, knowledge is constructed through the cyclical process of “experience–reflection–conceptualization–application.” Digital technologies can amplify this cycle through simulation, interactivity, and feedback tools (Nam et al., 2025; Reyes et al., 2024). Empirical studies demonstrate that digitally mediated experiential models foster critical thinking, creativity, and problem-solving skills (Galeboe et al., 2025; Loia et al., 2025; Sotaquirá-Gutiérrez et al., 2025). Moreover, conceptualizing the classroom as an integrated experiential space for professional practice has proven effective (Cocieru et al., 2024). In teacher education, experiential learning bridges theory and practice for student teachers (Akarsu, 2025; Duchatelet et al., 2024; Ngo and Nguyen, 2021). The use of virtual learning environments strengthens pedagogical design capabilities among student teachers (Loia et al., 2025; Nam et al., 2025; Yordudom et al., 2025). Interactive VR/AR models similarly demonstrate significant potential for creating rich learning experiences (Yu, 2025).

In addition, contemporary teacher education programs emphasize the development of competencies in designing experiential learning activities and digital pedagogy (Li and Yu, 2025; Ordaz et al., 2021). Competency-based education is recognized as a foundational framework for teacher training in the 21st century (Frank et al., 2010; McMullen et al., 2023; Mulder, 2014; Ten Cate and Billett, 2023). Recent studies reaffirm the effectiveness of this approach, particularly within vocational and professional education contexts (McMullen et al., 2023).

In Vietnam, research has highlighted the need to strengthen teacher education competencies in experiential learning, child abuse prevention, and student psychological support (Bui et al., 2025; Tran et al., 2025; Tuyen and Oanh, 2025). Yet, empirical studies on integrating digital experiential activities into child sexual abuse prevention education remain limited (Diez-Ojeda et al., 2024; Uludağ et al., 2024). Existing frameworks and tools are often generic, lacking contextual validation for teacher education in Vietnam. Moreover, no standardized instrument currently measures pre-service teachers' competence in designing and implementing digital experiential activities for child sexual abuse prevention. To address this gap, this study develops and validates a reliable instrument to assess such competence, contributing to the improvement of teacher education quality and providing a foundation for future research on professional competence in digital and child protection contexts.

This study contributes to the existing literature in several important ways. First, it develops a context-specific competence measurement scale for pre-service teachers in designing and organizing digital experiential learning activities for child abuse prevention, an area that remains underexplored, particularly in the Vietnamese context. Second, unlike prior studies that address digital competence or experiential learning separately, this study integrates experiential learning theory, digital pedagogy, and child protection education into a unified competency framework. Third, the proposed scale is empirically validated using a large sample, providing a reliable and practical tool for teacher education in the context of digital transformation. To the best of our knowledge, this is among the first studies to systematically develop and validate such a scale in this domain.

2 Literature review

2.1 Experiential learning and educational activity design competence of student teachers

Research in this strand examines the theoretical and practical foundations of experiential learning (Kolb, 1984) and investigates methods for developing pre-service teachers' competence in designing pedagogical activities. The foundational premise is that competence in designing educational activities develops through the integration of theoretical knowledge with creative practice in real or simulated experiential environments. Empirical evidence across diverse educational contexts supports this premise. Chen et al. (2019) found that experiential education models are highly effective for developing professional skills at the university level. Similarly, Tan et al. (2022) demonstrated that well-structured research experience programs function as experiential learning environments that strengthen students' inquiry and problem-solving skills. Meanwhile, out-of-class experiential learning has been shown to cultivate reflective competence and systems thinking (Akarsu, 2025).

Additionally, Ortez et al. (2023) highlighted that experiential approaches combined with systems thinking significantly enhance students' adaptive learning capacity, reinforcing the multi-dimensional benefits of experiential models in higher education. These benefits extend across specializations: in early childhood education, Tuyen and Oanh (2025) documented improvements in assessment competence, and in foreign language teacher education, Kaygísız and Akar (2025) identified role-playing as an effective strategy for enhancing pedagogical communication skills and learner engagement. Broader meta-level studies conducted in Vietnam and internationally consistently confirm that experiential learning activities play a crucial role in enhancing overall professional competence. Beyond individual skill development, Cocieru et al. (2024) and Duchatelet et al. (2024) demonstrated that experiential environments effectively bridge theory-practice gaps and improve learning outcomes, suggesting that experiential learning operates at both individual and systemic levels.

However, the quality and sustainability of this learning depend on how learners engage with their own development. Butler et al. (2021) identified that supporting learners in identifying their own competence gaps is a key mechanism for fostering sustainable professional development within teacher education programs. This self-awareness becomes particularly important when teachers design experiential activities that integrate technological tools. The design and development of experiential activities incorporating digital tools enhances teachers' creativity and technological application while simultaneously expanding the scope of educational outcomes teachers can facilitate. Within reflective pedagogical frameworks, Lane and Grape (2023) and Fuchs et al. (2022) emphasized that experience-based learning cultivates essential competencies, including self-evaluation, collaboration, and reflection, that form the foundation of effective lesson design. This is especially evident in specialized contexts such as child abuse and violence prevention, where deliberate design of experiential activities creates safer and more humane school environments (Allen et al., 2020; Wu et al., 2024).

2.2 Studies on child sexual abuse prevention education and teachers' roles

Research in this domain examines child protection and sexual abuse prevention as specialized educational competencies, with particular attention to developing students' self-protection capacities. Foundational studies by Davis and Gidycz (2000) and Del Campo and Fávero (2019) synthesized empirical evidence demonstrating that effective prevention programs require three critical elements: student awareness, protective skills, and meaningful teacher involvement. However, implementing these programs presents significant challenges. Allen et al. (2020) and Craig (2022) analyzed teachers' experiences implementing the “Second Step Child Protection Unit,” identifying two primary barriers: limited pedagogical competence in prevention education and insufficient systemic professional support. Recent scholarship has shifted toward a more systematic approach, with researchers developing measurement scales to assess school and teacher readiness for child sexual abuse prevention education (Helpingstine et al., 2024; Wu et al., 2024), thereby establishing competence-based frameworks for program evaluation and improvement.

Beyond skill-based training, the sociocultural dimensions of prevention education have become increasingly important. Cunnington and Clark (2023) and Henry et al. (2023) examined how cultural beliefs, victim silence, and teachers' attitudes interact to influence prevention efforts, emphasizing the necessity of culturally responsive competencies in education design. This cultural sensitivity extends to diverse student populations: Bui et al. (2025) developed prevention education methods specifically tailored to primary school students, grounding these approaches in life skills education frameworks. The scope of teachers' roles extends further still to encompassing psychological support. Dimitropoulos et al. (2022) and Vostanis et al. (2025) connected prevention education to trauma-informed care and emotional support for affected children, linking these competencies directly to school counseling expertise that teachers must develop. Farrell et al. (2025) further emphasized that building interdisciplinary educator communities strengthens professional readiness in addressing sensitive issues such as exploitation and abuse, highlighting the need for collaborative capacity within prevention education.

Collectively, this evidence reconceptualizes teachers' professional identity: they function not merely as transmitters of child protection content but as designers of educational experiences that cultivate students' self-protection and resilience capacities. This expanded conception of the teaching role positions child protection pedagogy as a foundational professional competence that warrants systematic development in teacher education programs.

2.3 Digital transformation and experiential learning in virtual environments

In the era of digital education, designing experiential learning activities requires integrating simulation platforms, artificial intelligence (AI), virtual and augmented reality (VR/AR), and online learning systems. These technologies serve complementary functions in teacher preparation. Hu (2025) proposed the “Critical AI Literacy” framework to develop teachers' critical thinking and communication competencies in AI contexts, while Li and Yu (2025) identified collaboration and creative thinking as core competencies for digital learning environments. Immersive technologies offer distinct pedagogical advantages: Nam et al. (2025) and Loia et al. (2025) demonstrated that Metaverse-based and ZEPETO platforms enhance pre-service teachers' ability to design immersive instructional scenarios, while Reyes et al. (2024) and Yu (2025) confirmed that virtual experiments and 3D interactive models improve conceptual understanding and problem-solving. In addition, Shelar et al. (2024) showed that integrating instructional videos into weekly learning plans can enhance hands-on engagement, illustrating how simple digital tools can support experiential activity design.

Assessment frameworks must match these technological affordances. Heaney et al. (2025) and Borrego-Balsalobre et al. (2025) proposed digital badges and online platforms for comprehensive competence assessment. Miserandino (2025) argued that authentic assessment in the AI era requires teachers to integrate critical thinking, instructional design flexibility, and technological fluency. These findings align with Benita et al. (2021), who emphasized that data-driven, interactive environments foster creativity in STEM learning ecosystems. Notably, Srijuntrapun et al. (2025) highlighted how experiential technologies can support inclusive education for disadvantaged students, advancing equity alongside innovation.

These studies demonstrate the transformative potential of technology in reshaping experiential learning for child protection and abuse prevention, from simulation and role-playing to emotional response and reflection. When integrated with experiential learning theory, digital transformation provides a foundation for developing pre-service teachers' competence in digital lesson design and experiential activity implementation.

2.4 Research gaps and approaches of the project

Despite growing interest in digital experiential learning and child abuse prevention education, research specifically focusing on pre-service teachers' competence in designing digital experiential activities remains limited. The gap is evident in three main aspects: (1) the lack of an integrated competence model that combines pedagogy, experiential learning, and digital technology; (2) the absence of empirical research in Vietnam evaluating the impact of digital experiential design competence training model (3) the lack of measurement criteria and assessment tools for evaluating digital design competence aligned with the goals of child sexual abuse prevention education. Rajiah (2025) also underscored the importance of integrated curriculum design in developing competence-based professional training, aligning with the study's emphasis on constructing coherent competency frameworks.

The present study addresses this gap by integrating experiential learning theory (Kolb, 1984), digital pedagogy (Loia et al., 2025; Nam et al., 2025), and competence-based education frameworks (Li and Yu, 2025) to develop a model for fostering student teachers' competence to design experiential learning activities for child sexual abuse prevention.

The research contributes theoretically by clarifying the conceptual foundations of digital experiential design competence and practically by establishing assessment tools and training protocols for teacher education programs. This framework enables future applied research on digital transformation and child-safe education in teacher preparation contexts.

3 Method

3.1 Research design

This study employed a Research and Development (R&D) design guided by the ADDIE model (Analysis - Design - Development - Implementation - Evaluation) as the overarching framework for constructing and validating a competency development model. To ensure clarity and methodological rigor, the development and validation of the competence measurement scale followed a systematic multi-stage procedure. First, a theoretical framework was established through a comprehensive review of literature on experiential learning, digital pedagogy, teacher competence, and child sexual abuse prevention education. Second, an initial pool of items was generated and refined through expert consultation to ensure content relevance and contextual appropriateness. Third, content validity was assessed using expert evaluation and content validity indices (CVI). Fourth, a pilot study was conducted to improve item clarity and structure. Fifth, Exploratory Factor Analysis (EFA) was performed to identify the underlying factor structure of the scale. Sixth, Confirmatory Factor Analysis (CFA) was conducted on an independent sample to validate the measurement model and examine construct validity. Finally, multiple regression analysis was employed to examine the contribution of component competence domains to the overarching competence construct.

During the Analysis phase, international theories and models on child sexual abuse prevention education, experiential learning, digital competence, and teacher education in the context of digital transformation were synthesized. Nine experts in Education, School Psychology, and Educational Technology participated in in-depth interviews to identify one overarching competence (OC) and eight component competence domains essential for student teachers when designing and implementing digital experiential activities on child sexual abuse prevention. These domains included: (1) defining objectives and content design (DC); (2) scenario design (SD); (3) digital material and resource development (DL); (4) ensuring digital safety and ethics (ES); (5) preparing and initiating digital learning environments (PS); (6) facilitating and managing learning activities (NM); (7) organizing experiential–reflective–applicative cycles (OR); and (8) evaluation and feedback processes (RF).

In the Design phase, a comprehensive dependent variable (OC) comprising nine observable indicators was developed to represent the overall competence in designing and managing digital experiential activities. Initially, 40 items were developed based on theoretical and empirical foundations. Following expert validation and refinement, 38 items were retained across eight independent factors (DC, SD, DL, ES, PS, NM, OR, RF) to measure the respective sub-competence domains. All items were rated on a five-point Likert scale ranging from 1 (Not achieved) to 5 (Excellent).

During the Development phase, nine independent experts assessed the content validity of the measurement instrument. The results indicated that the item-level content validity index (I-CVI) was ≥ 0.79, while the scale-level average (S-CVI/Ave) reached ≥ 0.92, reflecting strong agreement among experts. The survey questionnaire was subsequently piloted with 68 students from first to fourth year and analyzed using descriptive statistics in SPSS, through which several items were identified as having response rates below 85%. These items were revised in terms of wording, structure, and semantics. After revision, all items achieved a clarity rating of 91% or higher.

In the Implementation and Evaluation phases, the finalized survey was distributed online via Google Forms. Data were collected from 1,379 pre-service teachers (first to fourth year), of which 879 valid responses were used for statistical analysis. Data processing was conducted using SPSS 26.0 and AMOS 24.0. Statistical procedures included Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) to examine the instrument's reliability, convergent and discriminant validity, and the overall model fit of the proposed competency framework (Hair et al., 2010).

3.2 Sampling

The study employed a combination of convenience and purposive sampling methods. Participants were selected based on the following criteria: (1) enrollment as student teachers from the first to fourth year; (2) attendance at teacher education institutions located in Northern Vietnam; and (3) participation in coursework related to experiential learning activities and educational technology. A total of 1,379 survey responses were collected. Among these, 500 responses were excluded due to incomplete information, invalid answers, or inconsistencies in responses. After screening, 879 valid responses were retained for subsequent quantitative analyses, including Exploratory Factor Analysis (EFA, n = 440) and Confirmatory Factor Analysis (CFA, n = 439), ensuring the reliability and representativeness of the research findings (Table 1).

Four teacher education institutions were sampled with Hanoi National University of Education (HNUE), A University (AU, anonymized for review), B University (BU, anonymized for review), and Tan Trao University (TTrU). These universities offer their student teachers courses about experiential learning, life skills education, and educational technology.

Female students accounted for a substantial majority (80.3%), while male students represented 19.7%. Participants were drawn from four universities with relatively even distribution (ranging from 19% to 24%).

The research sample was balanced across academic years, with second- and third-year students each comprising about 27%, aligning with the study's focus on competence development in professional and pedagogical training. In terms of majors, Primary Education (25.6%) and Early Childhood Education (16.5%) were the largest groups, followed by smaller proportions from other education-related fields such as Literature, Mathematics, Physics, History, English, and Educational Psychology.

3.3 Validation of the survey instrument and measurement scale

3.3.1 Scale design

The measurement scale included one overarching dependent variable (OC) with nine observed indicators, reflecting the overall competence in designing and organizing digital experiential learning activities, along with eight independent variables (DC, SD, DL, ES, PS, NM, OR, RF) representing the eight component competency criteria. The independent variables DC, SD, DL, PS, NM, and OR were constructed with four observed items each, while the ES and RF criteria were constructed with seven observed items. All items were measured using a five-point Likert scale. The interval value was calculated as (5–1)/5 = 0.8, with the following rating levels: Excellent from 4.20 to ≤ 5.0; Good from 3.4 to < 4.20; Fair from 2.6 to < 3.4; Minimum acceptable from 1.8 to < 2.6; and Not achieved from 1.0 to < 1.8.

Table 2 presents the theoretical foundations and reference competence frameworks utilized in this study. The eight competence domains (DC, SD, DL, ES, PS, NM, OR, RF) were constructed through the integration of well-established international models and validated frameworks.

DC domain was adapted from the TPACK Framework (Mishra and Koehler, 2006), Backward Design Model (Wiggins and McTighe, 2005), and the SMART learning objectives principle; the SD domain was based on Kolb's Experiential Learning Theory (1984), combined with the ADDIE and SAMR models for digital activity design; the DL domain referred to the Digital Competence Framework for Educators (DigCompEdu) (Redecker and Punie, 2017), Open Educational Resources (OER), and the Universal Design for Learning (UDL) principles; the ES domain was derived from the Digital Citizenship Framework (Ribble, 2015) and UNESCO's ICT Competency Framework for Teachers (2019); the NM domain incorporated key principles of Collaborative Learning and Adaptive Learning for effective coordination and management of online learning activities; the OR domain drew upon the Experiential Learning and Reflective Practice Models to foster learners' critical and creative thinking; and finally, the RF domain was developed from the Assessment Area of DigCompEdu, Learning Analytics Framework (Siemens and Long, 2011), and the Kirkpatrick Evaluation Model (1998).

Each competence domain was operationalized into four behavioral indicators to ensure structural consistency and contextual relevance to teacher education in digital learning environments. The aforementioned theoretical frameworks served as conceptual references, providing a sound foundation for developing a novel scale that captures student teachers’ competence in designing and organizing digital experiential learning activities for child abuse prevention education.

3.3.2 Content validity

Nine independent experts were invited to evaluate the survey items to determine their content relevance and appropriateness. The results revealed that the Item-level Content Validity Index (I-CVI) reached ≥ 0.79 for all items, while the Scale-level Content Validity Index (S-CVI/Ave) attained 0.92, indicating a high level of expert consensus.

Initially, the instrument consisted of 10 latent variables and 40 observed indicators representing student teachers' competence in designing and organizing digital experiential learning activities for child abuse prevention education. The initial instrument included 10 latent variables and 40 observed indicators reflecting student teachers' competence in designing and organizing digital experiential learning for child abuse prevention education. Expert validation revealed conceptual overlaps, leading to the merging of redundant items. The final version comprised eight latent variables and 38 indicators, maintaining theoretical comprehensiveness while improving clarity and analytical suitability.

The instrument was pilot-tested with 68 student teachers to assess item clarity. Pilot data were analyzed using descriptive statistics (percentage ratios) in SPSS. Three items under the DC, ES, and IE domains scored below 85% and were revised for linguistic precision. After revision, all items exceeded 92% clarity, confirming content validity and consistent respondent understanding.

3.3.3 Structural validity

The competence model comprised one overarching dependent variable (OC) with nine observed indicators reflecting general competence in designing and organizing digital experiential learning activities, alongside eight independent factors (DC, SD, DL, ES, PS, NM, OR, RF) representing specific competence domains. In total, 47 observed variables were included in the factor analysis to examine the scale's structural and construct validity. Exploratory Factor Analysis (EFA) was conducted on a subsample of 440 participants using Principal Component Analysis (PCA) with Varimax rotation. The results showed that the Kaiser–Meyer–Olkin (KMO) measure reached 0.961, and Bartlett's test of sphericity was statistically significant (p < 0.001), confirming that the data were suitable for factor analysis. All factor loadings were ≥ 0.40, indicating strong correlations between the observed variables and their respective latent constructs.

Confirmatory Factor Analysis (CFA) further validated the structure comprising one overarching dependent variable (OC) and eight independent latent factors (DC, SD, DL, ES, PS, NM, OR, RF), with goodness-of-fit indices demonstrating an excellent model fit (χ²/df = 1.067; CFI = 0.946; TLI = 0.943; RMSEA = 0.012). These results confirm the robustness of the scale's structural validity, showing high empirical consistency and reliability for use in subsequent research.

3.4 Data collection

Data were collected through an online Google Forms survey distributed via social media platforms such as Facebook and Zalo to reach a diverse population from HNUE, AU, BU, and TTrU. Participation in the survey was voluntary, and informed consent was obtained electronically prior to data submission. The survey was conducted from October 2 to November 1, 2025. Data collection, analysis, and report adhered to research ethics standards, ensuring participant anonymity, data confidentiality, and the exclusive use of responses for scientific research purposes.

3.5 Data analysis

The dataset consisted of 879 valid responses, randomly divided into two groups: Sample A for Exploratory Factor Analysis (EFA, n = 440) and Sample B for Confirmatory Factor Analysis (CFA, n = 439). For Sample A, the internal consistency of the initial 47 items was assessed using Cronbach's α, yielding α ≥ 0.82, which indicates strong reliability. Subsequently, EFA was performed, eliminating items with low factor loadings and retaining those with loadings ≥ 0.40 and KMO ≥ 0.80. For Sample B, CFA was applied to test the model comprising one dependent variable (OC) and eight independent factors (DC, SD, DL, ES, PS, NM, OR, RF), and the model fit was evaluated using indices such as χ²/df, GFI, AGFI, NFI, CFI, RMSEA, and PCLOSE.

Across the entire dataset (n = 879), multiple regression analysis was employed to determine the effects of the eight independent variables (DC, SD, DL, ES, PS, NM, OR, RF) on the dependent variable (OC), representing the overall level of professional competence in practice. The regression model was defined as follows: Y = β₀ + β₁X₁ + β₂X₂ + β₃X₃ + … + βₙXₙ where Y denotes the dependent variable (overall competence in classroom-based professional training), Xₙ represents the independent competence factors, and βₙ denotes the unstandardized regression coefficients. Y=β₀+β₁X₁+β₂X₂+β₃X₃+…+βₙXₙ.

The statistical criteria used in this study followed commonly accepted standards in scale development and validation research. Internal consistency was considered acceptable when Cronbach's alpha exceeded 0.70. For EFA, data adequacy was assessed using the Kaiser–Meyer–Olkin (KMO) measure and Bartlett's test of sphericity, with KMO values above 0.60 and a significant Bartlett's test indicating suitability for factor analysis. Observed variables were retained when factor loadings were at least 0.40.

For CFA, model fit was evaluated using multiple indices, including χ²/df, GFI, AGFI, NFI, CFI, TLI, RMSEA, and PCLOSE. A χ²/df value below 3.0, CFI and TLI values of 0.90 or higher, and RMSEA below 0.08 were considered indicators of acceptable model fit. Convergent validity was supported when composite reliability (CR) exceeded 0.70 and average variance extracted (AVE) exceeded 0.50.

4 Results

4.1 Exploratory factor analysis (EFA)

EFA was performed on a dataset comprising 440 valid responses, employing the Principal Component Analysis extraction method with Varimax rotation and Kaiser normalization to identify the latent structure of the competency scale for designing and organizing digital experiential learning activities in child sexual abuse prevention education.

The results indicated that the Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy was 0.961, and Bartlett's Test of Sphericity yielded a statistically significant result (χ² = 15,542.656; df = 1,081; p < 0.001), confirming that the dataset was suitable for factor analysis (Table 3).

The factor extraction results revealed nine factors (one OC and eight independent factors) with Eigenvalues greater than 1, accounting for 73.317% of the total variance, well above the 50% threshold recommended by Hair et al. (2010). The communality values of all observed variables exceeded 0.50, indicating satisfactory explanatory power for each indicator.

All observed variables demonstrated factor loadings above 0.60, confirming both the convergent validity and discriminant validity of the measurement scale. The extracted factors reflected a multidimensional structure consistent with the proposed theoretical model, consisting of one overarching dependent variable (OC) and eight independent variables corresponding to eight competence domains: (1) Defining Objectives and Content Design (DC), (2) Scenario Design (SD), (3) Digital Learning Material and Resource Development (DL), (4) Ensuring Digital Safety and Ethics (ES), (5) Preparing and Initiating Digital Learning Environments (PS), (6) Facilitating and Managing Learning Activities (NM), (7) Organizing Experiential–Reflective–Applicative Cycles (OR), and (8) Evaluation and Feedback Processes (RF).

These findings confirm that the nine constructs (OC, DC, SD, DL, ES, PS, NM, OR, RF) were highly interrelated, thereby validating both the theoretical foundation and the empirical reliability of the proposed competency model.

The Scree Plot (Figure 1) illustrates the variation in Eigenvalues and was employed to determine the optimal number of latent factors to retain in the model.

Figure 1

The Scree Plot indicated a steep decline in Eigenvalues across the initial components, followed by a gradual leveling thereafter. Although the plot suggested several components with relatively high Eigenvalues, the theoretical framework of this study was constructed upon a comprehensive competency structure encompassing one overarching competence and eight component domains, represented by 47 observed variables.

The EFA results, interpreted in conjunction with the theoretical framework and the total variance explained table, revealed that the eight extracted factors were both conceptually meaningful and statistically sound. Therefore, retaining eight component competence domains was deemed theoretically and empirically justified, accurately reflecting the proposed structure of homeroom teachers' professional competencies.

Table 4 presents the factor loadings of the observed variables across the eight latent components identified following Varimax rotation. The factor loadings ranged from 0.586 to 0.817. According to the guidelines of Hair et al. (2010), with a sample size exceeding 200, factor loadings above 0.40 are considered statistically significant and indicate convergent validity. These findings demonstrate strong correlations between the observed variables and their corresponding latent constructs, confirming the internal consistency of the measurement scale and providing a solid empirical foundation for subsequent Confirmatory Factor Analysis (CFA).

The results further reinforce the robustness of the measurement structure and highlight its applicability in teacher education practice. Each competence domain clearly delineates the specific requirements for developing pre-service teachers' ability to design and organize digital experiential learning activities aimed at child sexual abuse prevention.

Exploratory Factor Analysis (EFA) was conducted using the Principal Component Analysis extraction method with Varimax rotation and Kaiser normalization. The results revealed an eight-factor structure corresponding to the groups of variables with the highest factor loadings for each component. All observed variables exhibited factor loadings above 0.586. The rotation converged after eight iterations, indicating that the factor structure was stable and consistent with the empirical dataset. Specifically:

Factor 1 (DC – Defining Objectives and Content Design) reflects the competence to identify learning objectives, content, and the structural framework of experiential activities, ensuring logical consistency and learner-centered orientation.

Factor 2 (SD – Scenario Design) represents the ability to construct experiential activity scenarios aligned with educational goals, learners' age characteristics, and the digital learning environment.

Factor 3 (DL – Digital Learning Materials and Resource Design) denotes the competence to design, select, and utilize digital learning materials, tools, and resources to enhance learning effectiveness.

Factor 4 (ES – Ensuring Digital Safety and Ethics) demonstrates the competence to safeguard students' wellbeing in online learning environments, adhering to ethical standards, privacy protection, and digital citizenship principles.

Factor 5 (PS – Preparing and Initiating Digital Learning Environments) highlights the ability to prepare lessons, establish digital learning spaces, and stimulate students' engagement and motivation.

Factor 6 (NM – Facilitating and Managing Learning Activities) refers to the ability to organize, assign, guide, and monitor the implementation of digital experiential learning activities in a flexible and effective manner.

Factor 7 (OR – Organizing Experiential–Reflective–Applicative Cycles) captures the ability to facilitate student participation in experiential activities, promote reflection, and support knowledge and skill application in authentic contexts.

Factor 8 (RF – Evaluation and Feedback Process) reflects the competence to design assessment procedures, deliver constructive feedback, and improve experiential learning activities to enhance educational outcomes.

All factor loadings exceeded 0.70, indicating that the observed variables contributed strongly and consistently to their respective latent factors. These results confirm the scale's strong convergent and discriminant validity, while the eight-factor structure comprehensively represents the multidimensional nature of pre-service teachers' competence in designing and organizing digital experiential learning activities for child sexual abuse prevention education.

The Exploratory Factor Analysis was performed using the Principal Component Analysis extraction method and Varimax rotation with Kaiser normalization (Table 5). The rotation converged after nine iterations, further confirming the stability and adequacy of the factor structure.

The results of the EFA indicated that the observed variables were grouped into eight factors consistent with the proposed theoretical model. All factor loadings exceeded 0.6, ranging from 0.586 to 0.882, demonstrating satisfactory convergent validity among the variables. The Cronbach's Alpha coefficients of all factor groups surpassed the threshold of 0.7, confirming the high reliability of the measurement scales. The factor structure was clearly defined without any cross-loading issues, evidencing discriminant validity among variable groups. These findings confirm that the measurement model meets reliability and validity requirements, providing a solid foundation for subsequent Confirmatory Factor Analysis (CFA) and regression modeling.

4.2 Confirmatory factor analysis (CFA)

Following the completion of the exploratory analysis, the next step involved conducting a Confirmatory Factor Analysis (CFA) to evaluate the goodness of fit of the measurement model using an independent sample. The CFA results revealed that the model fit indices met the recommended thresholds: χ²/df = 1.149 (< 3), GFI = 0.921, AGFI = 0.908, NFI = 0.938, CFI = 0.991, TLI = 0.991, RMSEA = 0.018 (< 0.08), and PCLOSE = 1.000 (> 0.05). These values fall within the acceptable ranges suggested by Hu and Bentler (1999) and Hair et al. (2010), indicating an excellent model fit to the empirical data.

The measurement scales exhibited strong reliability and convergent validity, with Cronbach's Alpha coefficients ranging from 0.882 to 0.935, composite reliability (CR) values from 0.917 to 0.956, and average variance extracted (AVE) values from 0.705 to 0.751 (Table 6)—all exceeding the 0.50 benchmark (Fornell and Larcker, 1981). The CFA results affirm that the scale model assessing pre-service teachers' competence in designing experiential activities for child abuse prevention in the digital environment demonstrates high stability, robust theoretical and empirical validity, and potential applicability in evaluating, training, and developing professional competencies among pre-service teachers.

All reliability coefficients (Cronbach's Alpha, rho_A, and Composite Reliability) exceeded the recommended threshold of 0.70, indicating high internal reliability of the measurement scales (Hair et al., 2010). In addition, all Average Variance Extracted (AVE) values were greater than 0.50, confirming satisfactory convergent validity. This demonstrates that each independent latent variable explains more than 50% of the variance of its corresponding observed indicators. Therefore, the measurement model fully meets the required standards for reliability and convergent validity.

Overall, these indices demonstrate that the CFA model exhibits a high level of fit with the empirical data, confirming the stability and explanatory strength of the measurement structure. This provides a robust foundation for subsequent analyses in the study.

Table 7 demonstrates that both measurement models meet or exceed international standards of model fit. Specifically, the Comparative Fit Index (CFI) and Tucker–Lewis Index (TLI) both approximate 0.99, the Root Mean Square Error of Approximation (RMSEA) is less than or equal to 0.04, and the PCLOSE value exceeds 0.05. These results indicate that the models exhibit an excellent fit with the survey data. The independent variable model shows a particularly strong fit (RMSEA = 0.018, PCLOSE = 1.000), while the dependent variable model also demonstrates a very good fit (RMSEA = 0.040, PCLOSE = 0.776).

For the independent variable model, the Chi-square/df ratio is 1.149, whereas for the dependent variable model it is 1.714. Both values are below 3, and even under 2, suggesting that the discrepancy between the model and the data is minimal. Although the Chi-square statistic is known to be sensitive to sample size, these results nonetheless confirm a good model fit.

The Goodness-of-Fit Index (GFI) values are 0.921 for the independent variable model and 0.976 for the dependent variable model, both exceeding the 0.90 threshold. The Adjusted Goodness-of-Fit Index (AGFI) values are 0.908 and 0.961, respectively, reflecting a well-fitting and parsimonious model structure. Notably, the AGFI > 0.95 in the dependent variable model indicates a very high degree of congruence between the theoretical model and empirical data.

The Normed Fit Index (NFI), Comparative Fit Index (CFI), and Tucker–Lewis Index (TLI) all demonstrate excellent values. The NFI values for the independent and dependent variable models are 0.938 and 0.985, respectively. The CFI values reach 0.991 and 0.994, while the TLI remains consistent at 0.991 for both models. All indices surpass 0.95, indicating substantial improvement over the null model and confirming the balance between goodness of fit and model parsimony. These findings provide strong evidence that the measurement models accurately represent the proposed theoretical structure.

The RMSEA values are 0.018 for the independent variable model and 0.040 for the dependent variable model, both falling below 0.05—representing an excellent “close fit.” The PCLOSE values of 1.000 and 0.776 (both > 0.05) indicate failure to reject the null hypothesis of RMSEA ≤ 0.05, thereby confirming that both models fit the data closely. In particular, the independent variable model exhibits an almost perfect fit.

Overall, all model fit indices (CFI, TLI, RMSEA, PCLOSE, GFI, AGFI, NFI) fall within or exceed internationally recommended thresholds. Both measurement models demonstrate exceptionally high levels of fit, confirming the construct validity of the scale structure.

Figure 2 illustrates the complete measurement model, representing the eight-component structure of pre-service teachers' competence in designing and organizing digital experiential learning activities.

Figure 2

The analysis results confirm that the eight-factor measurement model demonstrates an excellent fit with the survey data (χ² = 732.131, df = 637, χ²/df = 1.149, p = 0.058; GFI = 0.921, CFI = 0.991, TLI = 0.991, RMSEA = 0.018, PCLOSE = 1.000). All indices fall within or exceed the recommended thresholds, indicating a very high level of congruence between the theoretical model and empirical data. This finding robustly validates the eight-factor structure (DC, SD, DL, ES, PS, NM, OR, RF). The exceptionally low RMSEA value (0.018), together with CFI and TLI values above 0.99, confirms that the measurement model possesses excellent stability, reliability, and fit, making it well-suited for subsequent Structural Equation Modeling (SEM) analyses.

All observed variables exhibit standardized factor loadings greater than 0.50, thereby affirming the model's convergent validity and stability (Hair et al., 2010). Although the GFI value of 0.921 falls within the acceptable range, the overall model demonstrates a strong fit, as other indices such as CFI, TLI, and RMSEA reach optimal levels. These results confirm that the eight-factor measurement model (DC, SD, DL, ES, PS, NM, OR, RF) accurately reflects the proposed theoretical structure of competence. Clearly defining these components provides critical guidance for teacher education institutions in designing curricula, organizing training activities, and assessing the professional competence of pre-service teachers in the current digital education context.

4.3 Regression analysis

Following the completion of CFA, one overall dependent variable (OC) and eight independent variables representing the components of competence in organizing digital experiential learning activities were included in a multiple regression model to determine the contribution of each component to the dependent variable—competence in organizing experiential learning activities (OC).

The results presented in Tables 8, 9 indicate that the linear regression model demonstrates a high explanatory power for the dependent variable. Specifically, the independent variables—RF, DL, DC, NM, OR, SD, PS, and ES—collectively account for 70.4% of the variance in the competency variable OC (R² = 0.704; adjusted R² = 0.701). According to the recommendations of Hair et al. (2010), an explanatory level exceeding 0.50 is considered satisfactory for studies in education and the social sciences. Moreover, the Durbin–Watson statistic of 2.148 suggests that the model's residuals do not exhibit autocorrelation, thereby confirming that the assumption of error independence is met.

The analysis of standardized regression coefficients (β) revealed that all eight factors exerted positive and statistically significant effects on the OC competency (p < 0.001). Among them, the competency in coordination and activity management (NM) demonstrated the strongest impact (β = 0.187), followed by the competency in activity design (DC) (β = 0.167) and scenario design competence (SD) (β = 0.166). Other components—organizational and reflective competency (OR) (β = 0.162), ensuring safe experiential conditions (ES) (β = 0.160), classroom preparation and initiation (PS) (β = 0.141), digital learning materials and resources (DL) (β = 0.142), and response–improvement competence (RF) (β = 0.105) also exert positive and statistically significant effects on organizational competence.

Beyond confirming statistical significance, the relative strength of the regression coefficients provides deeper insight into the structural hierarchy of competence in designing digital experiential learning activities for child sexual abuse prevention. The finding that coordination and activity management competence (NM) exerts the strongest influence suggests that the ability to orchestrate and manage complex learning processes plays a central role in integrating pedagogical, technological, and experiential elements in practice. This highlights that, particularly in sensitive and multifaceted educational contexts such as child protection, competence extends beyond instructional design to include dynamic implementation and real-time pedagogical decision-making.

In contrast, competencies such as feedback and improvement (RF), although statistically significant, demonstrate relatively weaker effects. This may reflect limited opportunities for pre-service teachers to engage in systematic reflective practice and iterative improvement cycles during their training. This finding indicates a potential gap in teacher education programs, where greater emphasis should be placed on developing reflective, evaluative, and feedback-oriented competencies alongside instructional design skills.

Furthermore, the relatively balanced contributions of the remaining domains (DC, SD, ES, OR, PS, DL) suggest that competence in digital experiential learning is inherently multidimensional, requiring the integration of multiple interrelated domains rather than reliance on a single dominant skill. This finding reinforces the conceptualization of competence as an integrated and holistic construct, consistent with contemporary competency-based education frameworks.

These findings are consistent with the study by Ngo and Nguyen (2021), which emphasized that pre-service teachers' competence in organizing and coordinating experiential learning activities constitutes a core element in the formation of professional competence.

5 Discussion

The results of the study confirmed the reliability, validity, and structural appropriateness of the scale measuring student teachers' competency in designing and implementing digital experiential learning activities for child sexual abuse prevention. The results of the EFA and CFA indicated that the model, comprising one overarching outcome construct (OC) and eight independent factors (DC, SD, DL, ES, PS, NM, OR, RF), exhibited an excellent model fit, explaining 73.317% of the total variance. The fit indices (χ²/df = 1.149, CFI = 0.991, RMSEA = 0.018) were all within the recommended thresholds suggested by Hair et al. (2010). These results affirm that the competency structure developed for pre-service teachers is stable and effectively captures the key components.

The measurement scale developed in this study aligns with the orientation toward comprehensive professional competency development in teacher education (Frank et al., 2010; Mulder, 2014). It not only describes technical competencies, such as activity design (DC) and the use of digital learning materials (DL), but also integrates soft competencies related to coordination, reflection, and digital ethics (SD, NM, OR, RF). This approach reflects contemporary trends in competency-based education, emphasizing the interconnectedness between disciplinary knowledge, technological skills, and ethical values in digital learning environments (Mishra and Koehler, 2006; Ten Cate and Billett, 2023).

The EFA results confirmed data suitability (KMO = 0.961, p < 0.001) and supported a clear factor structure consistent with the proposed model. The CFA results demonstrated an excellent model fit (χ²/df = 1.149; GFI = 0.921; AGFI = 0.908; NFI = 0.938; CFI = 0.991; TLI = 0.991; RMSEA = 0.018; PCLOSE = 1.000), confirming the reliability and validity of the measurement scale.

The analysis of standardized regression coefficients (β) indicates that all eight independent variables (DC, SD, DL, ES, PS, NM, OR, RF) exert positive and statistically significant effects on the dependent variable OC (p < 0.001). Among these, coordination and management competence (NM) shows the strongest influence (β = 0.187), followed by activity design competence (DC) (β = 0.167) and scenario design competence (SD) (β = 0.166). Other independent variables—including reflective–organizational competence (OR) (β = 0.162), experiential safety assurance (ES) (β = 0.160), class preparation and initiation (PS) (β = 0.141), digital learning materials and resources (DL) (β = 0.142), and feedback–improvement competence (RF) (β = 0.105)—also demonstrate positive and statistically significant effects on the dependent variable OC.

The regression results indicate that all eight independent variables exert positive and statistically significant effects on the overall competence (p < 0.001). The findings indicate that coordination and management competence (NM) exerts the strongest influence on overall competence, likely due to the complex nature of digital experiential learning environments requiring simultaneous management of pedagogy, technology, and learner interaction. The findings are also consistent with prior studies emphasizing the role of integrated digital and pedagogical competencies in teacher education (e.g., Cocieru et al., 2024; Redecker and Punie, 2017), further reinforcing the multidimensional nature of professional competence in digital learning environments. Competencies related to defining objectives (DC) and ensuring digital safety (ES) also show strong effects, aligning with prior studies emphasizing teacher preparedness in digital and ethical contexts (Allen et al., 2020; Wu et al., 2024).

The relatively weaker effect of feedback competence (RF) suggests limited experience in reflective practice among pre-service teachers, indicating an area for improvement in teacher training programs. Within this structure, the overarching competence (OC) reflects pre-service teachers' ability to synthesize, connect, and apply component competencies to create a safe, creative, and learner-centered digital learning environment. This finding is consistent with the DigCompEdu framework (Redecker and Punie, 2017) and Mulder's (2014) conceptualization of comprehensive professional competence.

In addition, the competencies of defining objectives and designing content (DC), as well as ensuring digital safety and ethics (ES), also exert significant influence, reflecting the emerging requirements in training pre-service teachers in child abuse prevention during the digital transformation era—namely, the integration of technical competence, pedagogical reasoning, and social responsibility. This finding is consistent with Allen et al. (2020) and Wu et al. (2024), who emphasize the importance of skills in identifying risks and managing abuse-related situations in online learning environments. Establishing clear objectives in designing and organizing child abuse prevention education for pre-service teachers helps ensure that experiential activities are well-oriented and easily assessed, aligning with the conclusions of Cocieru et al. (2024) and Duchatelet et al. (2024).

Moreover, reflective competence (OR) and response–improvement competence (RF) show positive effects, reinforcing the reciprocal–reflective learning model proposed by Lyons and Bandura (2025), in which the ability to self-evaluate and continuously improve serves as the foundation for sustainable professional development. The factors of classroom preparation (PS) and ensuring safe experiential conditions (ES) contribute to maintaining a stable learning flow, enabling pre-service teachers to develop flexible, learner-centered organizational capacities. These findings not only demonstrate the stability of the model but also strengthen the hypothesis that the competency to design and organize digital experiential activities is a multidimensional and integrated construct that harmoniously combines professional, technological, and educational reflective competencies (Li and Yu, 2025; Nam et al., 2025).

The validated scale not only contributes to strengthening the theoretical foundation for assessing student teachers’ competencies in designing and organizing digital experiential learning activities on child sexual abuse prevention but also lays the groundwork for future quantitative research aimed at standardizing assessment tools tailored to the specific context of Vietnamese higher education.

6 Conclusion

This study developed and validated a reliable measurement scale for assessing pre-service teachers' competencies in designing and organizing digital experiential learning activities for child sexual abuse prevention. Initially, 40 items were developed based on theoretical and empirical foundations. Following expert validation and refinement, 38 items were retained across eight competence domains (DC, SD, DL, ES, PS, NM, OR, RF). In addition, 9 observed indicators were used to measure the overarching competence (OC), resulting in a total of 47 observed variables included in the EFA and CFA analyses. This measurement structure reflects a comprehensive and coherent competency framework.

Theoretically, the findings validate a nine-component competency model that demonstrates strong fit and validity, advancing understanding of how experiential learning theory, the TPACK framework, and digital ethics education can be integrated to develop comprehensive professional competencies for future teachers. This integration addresses a theoretical gap in current teacher education research by providing a unified framework for digital experiential design competence.

Practically, the measurement scale developed in this study offers a direct application tool for teacher education programs to assess student teachers' development of competence in designing digital experiential learning activities for child sexual abuse prevention. The competency model provides a valuable reference framework for teacher education institutions designing curricula, modules, and practice-based activities related to child safety education. Educational policymakers can leverage these findings when building teaching workforces equipped with digital competence, professional ethics, and social responsibility for child protection in modern learning environments.

For future research, the proposed competency model serves as a foundation for extended studies in child abuse prevention education, curriculum design refinement, and development of validated digital pedagogical competence assessment criteria. The study reinforces experiential learning as a foundational theory in teacher education while establishing an empirical pathway for operationalizing digital pedagogical competence in teacher preparation programs.

This study has several limitations that should be acknowledged. First, the sample was drawn from pre-service teachers in four teacher education institutions in Northern Vietnam, which may limit the generalizability of the findings to other regions or educational contexts with different cultural and institutional characteristics.

Second, the study relied primarily on self-reported data, which may be subject to response bias and social desirability effects. Although measures were taken to ensure anonymity and encourage honest responses, such biases cannot be entirely ruled out.

Third, the study did not incorporate data triangulation methods, such as classroom observations, interviews, or qualitative approaches, which could provide deeper insights into the actual implementation of competencies in practice. Future research is encouraged to adopt mixed-methods designs to strengthen the robustness and validity of the findings.

Finally, the cross-sectional design limits the ability to examine changes in competence development over time. Longitudinal studies would provide a more comprehensive understanding of how these competencies evolve throughout teacher education.

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