From insight to measurement: A self-assessment tool development for entry-level teachers' instructional competence

This research addresses the critical need for assessing and enhancing instructional competence among entry-level teachers through the development of a quantitative self-assessment tool. The study follows best practices, employing Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and reliability testing with a sample of 1000 teachers. The resulting six-factor model includes effective lesson planning and development, alignment with educational and career goals, collaboration and stakeholder engagement, classroom management and leadership, well-being and stress management, and student engagement and passion, validated through CFA with a statistically significant fit. The scale development involves defining constructs, expert opinions, and rigorous statistical analyses, demonstrating high internal consistency in reliability testing. This study offers valuable insights into entry-level teachers' instructional competence, recommending the refinement of the scale, integration into training programs, and prioritization of ongoing professional development. Suggestions for longitudinal impact research and context-specific exploration will deepen understanding. Overall, this research lays a strong foundation for improving teacher induction programs and enhancing the effectiveness of entry-level educators in diverse educational settings.


Introduction
Educators, particularly those in the early stages of their careers, play a pivotal role in shaping the future of education (Asirit et al., 2022) because they can easily traverse the discernible shifts occurring within the educational landscape (Järvinen-Taubert, 2023).While Asirit et al. (2022) unveiled a significant gap that there exists no standardized measurement tool expressly crafted to assess the instructional competence of newly hired teachers, authorities in education suggest a selection process that yields the best results (Cranston, 2012), continuous evaluation to improve teaching (OECD, 2013), observation and self-evaluation (Nijveldt et al., 2005) and mentoring (Baker-Drayton, 2019).For new teachers, self-assessment and self-reflection are necessary for highlighting their strengths and weaknesses in teaching competencies (Quddus et al., 2019;Majzub, 2013;Manea et al., 2022;Huang, 2022).
The phenomenological study of Asirit et al. (2022) brought attention to the instructional competence of recently appointed public school teachers proposing a scale construction perceived to function as a dependable measurement tool, gauging the preparedness of entrylevel teachers in their instructional competence.In fact, previous studies also highlight the potential role of self-assessment tool for entry-level teachers towards augmenting teacher induction programs and enhancing the overall effectiveness of entry-level educators in public school settings (Pellerone, 2021;De Vera et al., 2021;Kotzebue et al., 2021;Lauermann & ten Hagen, 2021;Korir, 2022;Ohle-Peters & Shahat, 2023).
Through an in-depth exploration of the integral role played by self-assessment in shaping effective teaching methods, this research elucidates its significant impact on the cultivation of instructional competence in the context of newly hired teachers.Informed by foundational principles derived from the literature on scale development (DeVellis & Thorpe, 2022;Lamm et al., 2020;Zhou, 2019;Ellis, 2017), this study takes a pivotal turn, shifting from qualitative insights to the creation of a quantitative self-assessment tool.Embarking on this transformative journey, the research seeks to meticulously measure and validate the instructional readiness of entry-level teachers.The overarching objective is to furnish a reliable and empirically validated measurement tool, not only reinforcing qualitative discoveries but also enriching teacher induction programs.This concerted effort is geared towards facilitating the seamless integration of entry-level teachers into the intricate landscape of public school This study pursued two core goals.Firstly, it sought to examine and establish the foundational elements impacting the instructional competency of entry-level instructors through a thorough analysis of observable variables.Concurrently, the research evaluated the coherence of the proposed component structure, derived from Exploratory Factor Analysis (EFA), when applied to a specific group of novice educators.These dual objectives work in tandem, contributing to a profound understanding of the factors influencing instructional competency and validating the suggested factor structure through Confirmatory Factor Analysis (CFA).

Entry-level teachers' instructional competence
In exploring the instructional competence of entry-level teachers, a comprehensive examination of the existing literature reveals significant insights.Asirit et al. (2022), rooted in Bandura's Self-Efficacy Theory (1997), identified crucial attributes shaping instructional competence such as baseline instructional standards, drivers of instructional improvement, transition of instructional quality, strategizing for quality instruction, managing uncertainties, and health and well-being, which are necessary for well-equipped entry-level educators.While Pellerone (2021)  competence beliefs and students' academic outcomes while Korir (2022) emphasized the teachers' performance appraisal and development.These studies shed light on the critical role of teachers in building meaningful relationships and underscore the imperative for additional professional development centered on technology integration to equip teachers with the necessary skills for contemporary educational landscapes.

Scale development
Scale development stands as a pivotal component of empirical research, ensuring the acquisition of data that is both valid and reliable.According to Lamm et al. (2020), content validity, internal and external structure validation, and consequential validity are crucial to address the multifaceted process of scale development tailored to specific contexts.Lamm et al. (2020) suggest descriptive analysis, Cronbach's alpha calculations, and factor analysis for internal structure validation.The importance of external structure validity is underscored through data collection within the nomological network of related scales, with a conclusive emphasis on the broader implications of scale results.In terms of validation, Ellis (2017) accentuates the necessity of a validation study before the utilization of a test or scale, which include meticulous planning, expert involvement, and rigorous item analysis.
DeVellis and Thorpe (2022) emphasized the concept of internal consistency reliability using Cronbach's coefficient alpha (α) as a widely embraced metric.A scale attains internal consistency when its items exhibit high intercorrelations, indicative of strong connections to the latent variable.Scale reliability signifies internal consistency with coefficient alpha as an essential metrics in scale development.Moreover, Zhou (2019) integrated qualitative investigation, quantitative surveys, and validation techniques in scale development.By systematically integrating mixed methods, it ensures a nuanced understanding of the scale construct.

Theoretical framework
The theoretical framework of this study is informed by the principles outlined by DeVellis and Thorpe (2022) in the process of scale development.DeVellis and Thorpe provide a comprehensive guide that blends both theoretical and methodological considerations for creating reliable and valid measurement instruments.The second phase of scale validation unfolds through a series of analytical procedures.
EFA is employed to identify latent factors and unveil the underlying structure of the scale.
CFA follows, serving to validate and confirm the factor structure identified through EFA.This analytical process rigorously tests the consistency of the scale's structure and assesses how well the observed data aligns with the hypothesized model.Simultaneously, content validity is scrutinized to ensure the comprehensive coverage of intended constructs.Reliability tests, including measures like Cronbach's alpha, assess the internal consistency and stability of the scale over time.

Research design
This quantitative research employs a methodological approach influenced by Finch (2020).The construction and development of the scale utilized EFA to unveil the underlying structure of observed variables.Furthermore, CFA is introduced to validate a pre-defined factor structure, covering critical aspects like identification, model fit, and degrees of freedom.
The comprehensive methodological framework of the study as shown in figure 1 comprises two distinct yet interconnected phases: scale development and scale validation.
Guided by Ellis (2017), the scale development initiated with a meticulous definition of study constructs, followed by item generation and format determination.The initial construct list was scrutinized through the Delphi Technique.The final scale, determined by the Content Validity Index, marked the completion of the scale development phase.

Respondents
The scale validation phase involved randomly selected teachers in the Philippines, specifically targeting those newly appointed or with three years of teaching experience in either private or public schools.A total of 1000 respondents participated in the study, distributed as follows: 400 respondents for EFA, 400 for CFA, and 200 for reliability testing.
Respondents utilized an encrypted online form to answer the scale, ensuring data security, and received reminders for completion to maximize response rates.This comprehensive approach aligns with best practices in scale development and validation, ensuring the robustness of the study's findings.

Ethical considerations
This study prioritizes participant anonymity, informed consent, and confidentiality.
The study ensures participants are well-informed, free from coercion, and maintains transparency regarding sponsorship interests.Ethical considerations include secure data management, bias prevention, and transparent outcome sharing.The research employs the JotForm online survey platform, incorporating data encryption for enhanced participant data security.

Scale development
Defining the constructs.The process of identifying and generating scale items for assessing entry-level teachers' instructional competence involves a systematic review of literature.Asirit et al. (2022) serve as a valuable foundation for understanding the dimensions of instructional competence.Following a literature review, the study employed wellestablished scale construction criteria as outlined by DeVellis and Thorpe (2022).The study outlines a scale for entry-level teachers' instructional competence, consisting of ten indicators, each representing a unique facet.Initially, a list of 100 items corresponding to these indicators was developed to ensure comprehensive coverage of factors that influence instructional competence and enhancing the tool's robustness.Expert opinion.To enhance the content validity of the measurement tool for assessing entry-level teachers' instructional competence, a meticulous refinement process was performed guided by the Delphi Technique as recommended by Haughey (2021).This consensus-building method involved gathering insights from a panel of 13 subject experts to ensure the relevance and appropriateness of the items.Utilizing the Content Validity Index (CVI) as a quantitative measure, the study assessed the agreement among experts regarding item relevance, drawing on the methodology outlined by Yusoff (2019) and Israfilzade (2021).
The results presented in table 3 revealed an impressive CVI score of 0.87 following the evaluation of 100 items by experts, indicating a high level of agreement.Subsequently, 60 items, distributed across 10 dimensions, were identified as acceptable and retained for further investigation.(Shrestha, 2021).The robust KMO score of 0.862 attests to the substantial common variance among variables in the dataset, supporting their meaningful grouping into factors.This underscores the dataset's validity for factor analysis, indicating that the information encapsulated in the variables adequately identifies underlying factors.Additionally, the significant outcome in Bartlett's Test reinforces the dataset's appropriateness for EFA.Rejecting the null hypothesis implies nonzero correlations between variables, providing evidence of ample inter-variable correlations and affirming the dataset's suitability for factor analysis.In summary, the results of assumption checking decisively endorse the choice to undertake Exploratory Factor Exploratory factor analysis.as "Collaboration and stakeholder engagement," "Classroom management and leadership," "Well-being and stress management," and "Student engagement and passion," are aptly named, succinctly capturing core competencies reflected in factor loadings and providing a clear, meaningful representation of instructional dimensions.
The naming of components in this analysis shares parallels with the thematic focus observed in Asirit et al. (2022).A comparison between the two studies reveals common ground in supporting the notion that a range of abilities is necessary for successful teaching, emphasizing distinct instructional competencies for educators.Despite potential variations in individual competencies and factor names, this congruence points to a shared understanding of the multifaceted nature of instructional ability in the educational domain.In the context of this study, the objective is to assess the instructional competence of entry-level teachers and confirm the alignment of selected factors with the observed data.
Furthermore, emphasizing the importance of item loading magnitude, as highlighted by Perez (2023), proves crucial in accounting for significant unique variance.Following the guidelines of Tabachnick andFidell (2007, as cited in Perez, 2023), more stringent cut-offs are recommended, with values ranging from 0.32 (poor) to 0.71 (excellent), offering a nuanced evaluation of factor loadings.
The standardized CFA model depicted in figure 4 elucidates the relationships between latent factors and their respective observed items, providing insights into the instructional competence of entry-level teachers.The beta (β) values, representing standardized factor loadings, offer valuable information about the strength and direction of these relationships.

Effective lesson planning and development (Factor 1):
The latent factor exhibits substantial factor loadings, ranging from β = 0.66 to β = 0.88.Notably, item 9 demonstrates the highest loading at β = 0.88, signifying its significant contribution to this factor.These robust loadings suggest that the selected items effectively represent the latent construct, aligning with the notion that entry-level teachers proficiently plan and structure lessons, manage time, and update teaching skills.
Alignment with educational and career goals (Factor 2): Factor 2 manifests strong factor loadings ranging from β = 0.69 to β = 0.85.Items 12 and 11 exhibit notable loadings of β = 0.74 and 0.85, respectively, emphasizing the alignment of teaching goals with the educational system and the prioritization of continuous professional learning.This underscores the importance of these competencies in entry-level teachers.
Collaboration and stakeholder engagement (Factor 3): Factor 3 demonstrates robust factor loadings ranging from β = 0.67 to β = 0.87.Notably, item 23 shows the highest loading at 0.87, indicating the competency of collaborating with peers to enhance instructional practices.This factor highlights the significance of effective collaboration and stakeholder engagement for entry-level teachers.
Classroom management and leadership (Factor 4): Factor 4 presents factor loadings ranging from β = 0.70 to β = 0.89.Item 27 attains the highest loading at β = 0.89, emphasizing the competence in managing uncertainties in teaching.The high factor loadings across items underscore the critical role of classroom management and leadership skills for entry-level teachers.
Well-being and stress management (Factor 5): Factor 5 showcases factor loadings ranging from β = 0.65 to β = 0.84.These loadings suggest that preserving emotional wellbeing, utilizing socio-emotional learning programs, and prioritizing physical and mental health are integral aspects of entry-level teachers' competencies.
Student engagement and passion (Factor 6): Factor 6 demonstrates factor loadings ranging from β = 0.68 to β = 0.88.Notably, item 32 shows the highest loading at 0.88, emphasizing competence in maintaining a passion for the teaching profession.These loadings highlight the importance of fostering positive engagement and passion in entry-level teachers.
Goodness of fit of the conceptual model.The evaluation of the fit of the conceptual model is a pivotal step in CFA, assessing the alignment of the proposed model with observed data (Ben-Shachar et al., 2022).This section interprets various commonly used fit indices in CFA, including the chi-squared statistic, adjusted goodness of fit index (AGFI), goodness of fit index (GFI), normed fit index (NFI), non-normed fit index (NNFI), comparative fit index (CFI), relative fit index (RFI), incremental fit index (IFI), parsimony-adjusted measures index, root mean square error of approximation (RMSEA), and (standardized) root mean square residual (SRMR).These fit indices serve as benchmarks for evaluating model adequacy, with recommended cutoffs for each index.For instance, GFI and AGFI should be > .95 and > .90,respectively, while NFI and NNFI are advised to be > .95 and > .90(or > .95for NNFI in smaller samples).Similarly, CFI is suggested to be > .96,IFI > 0.90, and RMSEA < .08 (or < .05 for more stringent criteria).The RFI, although not strictly bound between 0 and 1, closer to 1 indicates a good fit.The SRMR should be < .08.
These indices collectively provide a comprehensive assessment of the model fit, allowing researchers to draw meaningful conclusions about the alignment of the proposed model with the observed data in the context of instructional competence evaluation for entrylevel teachers.The assessment of the derived six-factor model of the entry-level teacher's instructional competence scale is crucial for determining its parsimonious fit.Considering the reliability of the instrument's total score, which combines all factors, a Cronbach's alpha of 0.920 reinforces the overall robustness and internal consistency of the entire instrument.

Conclusion and Recommendation
This study has yielded valuable insights into the instructional competence of entrylevel teachers, utilizing a comprehensive research design that integrates both EFA and CFA.Longitudinal impact research: Explore the longitudinal impact of instructional competence factors on teacher performance and student outcomes for valuable insights into long-term success in the teaching profession.
Context-specific exploration: Investigate context-specific factors, including school culture, community dynamics, and regional variations, to better understand their influence on entry-level teachers' instructional capabilities.
constituting a crucial stride towards the perpetual refinement of educational practices.
emphasized the influence of self-perceived instructional competence and selfefficacy on teaching effectiveness, De Vera et al. (2021) addressed novice teachers' competence in integrating educational technology within the context of the new normal in education.Furthermore, Kotzebue et al. (2021) highlighted subject-specific competencies for pre-service science teachers within the DiKoLAN framework.Several studies revealed underscored the importance of aligning training structures with authentic classroom scenarios.For example, Ohle-Peters and Shahat (2023) illuminated on the role of technical pedagogical content knowledge (TPACK) in enhancing instructional quality.Lauermann and ten Hagen (2021) synthesized the relationship between teachers'

Figure 1
Figure 1 Figure 3 The pattern matrix showcases factor loadings for each item across six identified factors, with notable loadings surpassing the 0.7 threshold, indicating strong relationships.Guided by Finch's (2020) systematic evaluation, 26 items were excluded due to low factor loadings, ensuring the final construct retains variables with substantial relationships to underlying factors.Observed factor loadings, ranging from 0.310 to 0.949, predominantly surpass the 0.3 threshold, indicating substantial correlations between variables and identified factors.Factors 1 to 6 exhibit distinct competencies contributing to entry-level instructional competence, providing a comprehensive view of crucial skills and knowledge for effective teaching at the career's outset.Finch (2020) underscores the importance of determining the optimal number of components to retain in exploratory factor analysis.The present study utilizes the pattern matrix to conduct a comprehensive analysis of the identified components, emphasizing their critical role in articulating the underlying constructs.Naming of factors.The process of naming factors in EFA serves as a crucial link between statistical abstraction and meaningful interpretation.Drawing insights from Shrestha (2021) and Fein et al. (2022), factors are typically labeled based on the characteristics of variables with prominent loadings, signifying their substantial contribution to the factor's variance.This naming strategy ensures that the assigned label encapsulates the core features of the variables within a factor, thereby enhancing the interpretability and relevance of the analysis.Fein et al. (2022) highlight the combination of art and science in factor naming, emphasizing the importance of labels that are not only statistically accurate but also contextually meaningful.Ultimately, the strategic naming of factors aims to transform abstract statistical results into comprehensible and actionable insights, facilitating a more insightful and nuanced understanding of the underlying constructs.In the factor analysis of entry-level teachers' instructional competence, the naming of factors aligns meticulously with the characteristics of variables showing significant factor loadings.Each factor receives a name based on the thematic coherence of encompassed items, reflecting the underlying competencies measured.For example, Factor 1, termed "Effective lesson planning and development," incorporates items related to lesson planning, time management, assessment design, and skill updates, emphasizing a cohesive theme around effective instructional preparation.Factor 2, labeled "Alignment with educational and career goals," includes items addressing the alignment of teaching goals with broader educational objectives, emphasizing a strategic and goal-oriented dimension.The remaining factors, such

Figure 4 CFA
Figure 4 The default model reveals a commendable fit, with NFI (0.756), RFI 0.733), IFI (0.922), TLI (0.913), and CFI (0.920), collectively suggesting strong alignment with the observed data.The Δ1 (Delta1) and ρ1 (rho1) values further highlight improved fit indices compared to the Independence model, affirming the default model's efficacy in capturing and explaining observed patterns.In contrast, the saturated model, serving as an ideal benchmark, boasts perfect fit indices (1 for NFI, IFI and CFI).While representing an optimal fit, it's crucial to acknowledge the rarity or impracticality of achieving such perfection in real-world scenarios.Conversely, the independence model demonstrates a lack of fit, with all indices registering values of 0, aligning with its assumption of treating variables as independent.This underscores the significance of considering relationships among variables for a meaningful and accurate representation of data.The assessment of default, saturated, and independence models provides key insights into the entry-level teacher's instructional competence scale.The default model, aligning well with observed data, suggests a strong fit for the six-factor model, as emphasized by Δ1 and ρ1.While the saturated model is an ideal fit, acknowledging practical limitations makes the default model a more realistic representation.The lack of fit in the independence model underscores the need for a sophisticated model considering variable relationships, crucial for accurate instructional competence representation.This comprehensive assessment informs model refinement for enhanced teacher competence assessment among researchers and practitioners.
The identification of six factors-effective lesson planning and development, alignment with educational and career goals, collaboration and stakeholder engagement, classroom management and leadership, well-being and stress management, and student engagement and passion-contributes to a nuanced understanding of the multifaceted dimensions shaping instructional competence.The CFA affirms the robustness of the proposed model, showcasing a statistically significant and reasonably good fit.Factor loadings underscore the strength and direction of relationships, validating the effectiveness of these factors in capturing observed data.The detailed assessment of model fit, encompassing relative fit indices and root mean square error ISSN 2719-0633 (Print) 2719-0641 (Online) | 49 of approximation, provides a comprehensive perspective on the entry-level teacher's instructional competence scale.In light of the insights gleaned from this study on entry-level teachers' instructional competence, the following recommendations are proposed; Refinement of instructional competence scale.Enhance the instructional competence scale by incorporating the factors identified in this study for improved accuracy and applicability in assessing entry-level teachers.Integration into teacher training programs.Integrate identified factors into teacher training curricula to comprehensively prepare entry-level teachers.Develop targeted interventions to enhance specific competencies.Ongoing professional development: Prioritize continuous professional development for entry-level teachers, focusing on factors like collaboration, classroom management, and alignment with educational goals for sustained improvement.

Table 1 34 | International Journal of Educational Management and Development Studies, Volume 5 Issue 1
Initial items for the entry-level teacher's instructional competence scale Ellis (2017)format.The measurement format in assessing entry-level teachers' instructional competence utilizes a 5-point Likert scale, as recommended byEllis (2017)for factor and item analysis.Respondents use this scale to indicate their perceived competence in each skill area as illustrated in table 2. Crafted for reliability and validity, the format ensures a comprehensive representation by formulating items aligned with the chosen domain, allowing for varied responses through the Likert scale's five categories.

Table 2
Likert scale for entry-level teacher's instructional competence

Table 3
Items from the Delphi techniqueOlkin Measure of Sampling Adequacy (KMO) and Bartlett's Test of Sphericity, are detailed in table 4.These statistical metrics are pivotal in assessing the dataset's suitability for factor analysis of 60 questions, validated through expert panel feedback, covering ten distinct factors.These questions were then administered in an online survey during October 2023, marking the initial phase of the study.The assumption-checking results for EFA, encapsulating the Kaiser-Meyer-

International Journal of Educational Management and Development Studies, Volume 5 Issue 1 instructional
(McNeish, 2023)izing Promax rotation with Kaiser Normalization in 5 iterations(McNeish, 2023), the SEM approach deems factor loading critical for assessing variable relevance and strength of identified factors.Factor loadings exceeding 0.7 signify sufficient variance extraction, ensuring construct robustness.
Table 5 displays the factor loadings of the pattern matrix resulting from a Principal Axis EFA on a 34-item construct measuring entry-level teacher's |

Table 6
Pattern matrix of 34 -item construct of the entry-level teacher's instructional competence

Factor 2: Alignment with Educational and Career Goals
particularly valuable when a predefined theoretical framework exists or when the dimensionality of an instrument has been established through a prior EFA study.
Table 7 presents the Likelihood Ratio Chi-Square test results, evaluating the goodness of fit for three models: the default model, the saturated model, and the independence model.

Table 9
Baseline comparison of the relative fit indices

Table 9
presents a baseline comparison of relative fit indices for three different models: the default model, the saturated model, and the independence model.These indices include normed fit index (NFI), relative fit index (RFI), incremental fit index (IFI), Tucker-Lewis

Table 10
RMSEA results contribute to a nuanced assessment of the entry-level teacher's instructional competence scale, offering valuable insights for model refinement.Reliability test.The reliability of the instrument was assessed to gauge the internal consistency of its items.As presented in table 7, the overall reliability is notably high, with a While collaboration and stakeholder engagement (α=0.857) and classroom management and leadership (α=0.854)exhibit slightly lower Cronbach's alpha values, they still surpass the .70threshold, suggesting satisfactory internal consistency within these factors.

Table 11
Reliability analysis of variables