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Boosting underrepresented student persistence in STEM majors has been of interest for several years. Prior research has explored various factors that may influence student success and persistence in STEM majors. Specifically, some of these studies have employed Yosso's community cultural wealth framework to explore how a student's cultural wealth may link to certain outcomes. Most of these studies have taken a qualitative approach when exploring cultural wealth and less adopt a quantitative approach. Using biology students in an introductory biology class during the fall (n = 303) and spring semesters (n = 215) at a large Hispanic-serving institution in the southeastern United States, this study seeks to contribute to the literature by validating a previously constructed instrument with a new population. An exploratory factor analysis (EFA) was conducted using principal axis factoring and an oblique rotation. EFA results revealed 10 dimensions of cultural wealth. Additionally, confirmatory factor analysis confirmed that the model produced properly measures the constructs as intended. Overall, the final 56-item instrument used in this study was validated and can be used for measuring cultural wealth in similar populations.

The aim of this study is to develop a valid and reliable instrument to measure the performance of schools in relation to corporate social responsibility based on teachers' perceptions. To this end, content and construct validity and reliability studies were conducted with the participation of 521 teachers from four different study groups. As part of the related studies, a comprehensive literature review on the phenomenon was conducted and the theoretical structure was revealed through open-ended questions to the first study group of thirty teachers. An item pool was then created in accordance with the existing scope and the type of scale was determined. Eight experts were consulted for the item pool and the item pool was finalised and a draft scale form consisting of thirty-one items was produced. The draft scale, with the addition of the administration instructions, was administered to the second study group, a group of forty teachers, and thus the pre-application was realised. The scale that emerged after the pre-test was applied to a total of 451 teachers from two different study groups for exploratory and confirmatory factor analyses, and validity and reliability analyses were conducted on the data obtained from the study groups. These analyses showed that the total variance explained by the nine-item, one-factor structure that emerged from EFA was 81.8%, and the construct validity of the scale was supported by confirming the emerging structure with CFA. Reliability analyses revealed that Cronbach's [alpha] and McDonald's [omega] values were 0.975 and 0.976 respectively, and these values, which were quite high, proved that the scale was a reliable scale. As a result, a valid and reliable scale capable of measuring teachers' perceptions of the CSR performance of the schools where they work has been introduced to the literature.

In this study, a valid and reliable scale was developed to measure parents' perceptions of their children's social development in physical education classes. In the first part of the research, the relevant literature reviewed and student-parent interviews were held. As a result of the data obtained from the interviews, a 30-item draft scale was created. The draft scale was applied to 30 parents of students, and as a result of the feedback received, 5 items were removed from the pool. The remaining draft scale items were submitted to expert opinion and the number of items was reduced to 22. The 22-item scale was applied to 240 volunteer parents for Exploratory Factor Analysis (EFA) and to 216 different volunteer parents for Confirmatory Factor Analysis (CFA). As a result of the analyses, the final scale consisting of 15 items and four sub-dimensions was obtained. The Cronbach's Alpha values of the sub-dimensions were found to be between 0.74-0.79. In the final part, the 15-item scale was applied to 540 volunteer parents. Accordingly, while it was observed that parents' PSDSPEL scores were higher in the sub-dimension of showing positive behavior, it was determined that male parents' perception levels were higher than female parents. As a result of the study, it was found that the validity, reliability and internal consistency coefficients of the scale were at acceptable levels.

This study aims to develop a valid and reliable scale for determining the self-efficacy of teachers toward context-based science education. This study employed a survey design. The sample has formed 433 science teachers working in Kayseri province in the 2020-2021 spring semester. Firstly, an item pool of 85 items was developed by reviewing the literature. Secondly, a five-point Likert-type draft scale consisting of 67 items was developed. Required arrangements have been performed according to expert opinions to provide content validity. Explanatory and confirmatory factor analyses have been run to provide construct validity. As a result of explanatory factor analysis, a structure with four factors as "Learning/Teaching Process", "Self-efficacy Resources", "Academic Self-efficacy" and "Planning Instruction" consisting of 47 items has been reached. Factors have been confirmed by confirmatory factor analysis. Cronbach Alpha internal consistency coefficient has been calculated as 0.98. To provide criterion validity, the Pearson correlation coefficient has been found as 0.86 between the draft and criteria scales. Based on the findings, researchers have determined that the scale was valid and reliable, and they recommended that this scale should be used to determine self-efficacy beliefs towards context-based learning of science teachers.

Simon Fraser University in Vancouver, Canada offers two introductory calculus courses designed for students enrolled in science and engineering programs. Students identified as needing additional support based on their admission grades take the version of the course where students meet weekly for four hours instead of three. A new approach for the fourth hour was introduced in Fall 2019 splitting the class into smaller sections of 20-40 students to work in small groups on vertical whiteboards under the supervision of the instructor, complemented by peer tutors. This format introduces an active learning element that improves student performance and attitude. The project was first implemented in Fall 2019, although interrupted due to COVID-19. After returning to the in-person classroom, the whiteboard seminar program was reinstated. In Fall 2022 and Spring 2023, survey feedback was collected from both students and peer tutors for a more holistic perspective on the program. In this study, the results of these surveys are analyzed, focussing on four areas of measurement: students' satisfaction, learning calculus concepts and problem-solving techniques, the contribution of the instructor, and the contribution of the peer tutors. Exploratory factor analysis revealed three latent variables underlying student survey responses. The survey results suggest that interactions with the instructor, peer tutors, and active learning activities all contributed to students' enjoyment of the course and their perceptions of their own learning. We compared students' final course grades from Fall 2018, where the fourth hour was devoted to lecture before the program was implemented, to Fall 2019 and 2022. The data shows a decrease in the percentage of students failing the course and an increase in those earning A's and B's since the program's implementation. Additionally, survey results show that replacing a typical lecture-style hour with a whiteboard seminar improved students' attitudes and perceptions of the course.

The process of decision-making is a multifaceted cognitive endeavor encompassing various cognitive, emotional, psychological, and social processes. It empowers individuals to select from a range of alternatives. Its significance spans across age groups, impacting both adults and children, and the relevance of which goes beyond aiding learners in choosing their educational or professional paths; it also pertains to preparing them to navigate the diverse situations they will encounter throughout their lives. To approach this ability, we developed a scale comprising 20 items, assessing five distinct decision-making factors. This scale was administered to a sample of 303 learners in the first and second years of the baccalaureate course (pre-final and final years of secondary education), representing both genders, and studying in four high schools. The participants' ages ranged between 16 and 20 years. The results of this study revealed positive psychometric properties of the scale after its apparent validity was verified. Additionally, principal component analysis, using a latent root criterion greater than one (Eigenvalue > 1), and performing Varimax rotation, resulted in five factors that represent decision-making styles (dependent, avoidant, confident, rational, intuitive) that explain 53.67% of the total variance. Through the application of confirmatory factor analysis (CFA), the outcomes showcased favorable conformity indicators. The ratio of chi-square value to degrees of freedom was recorded at less than 5 (X[superscript 2]/df = 1.531). The RMSEA index, at 0.041, remained below the accepted threshold of 0.08. The metrics (CFI, TLI, GFI, IFI) all surpassed 0.90, falling within acceptable ranges. Strong internal consistency between item scores and their respective factors was established by Pearson coefficients. The correlation coefficients between each factor's score and the total scale score were robust, ranging from 0.483 to 0.727. The Cronbach's alpha coefficient for the scale's factors ranged from 0.788 (highest) to 0.723 (lowest), with an overall scale stability coefficient of 0.748. These high coefficients collectively confirm the scale's validity, reliability, and appropriateness for implementation within the Middle East and North Africa (MENA) region.

Background: Adolescent-specific ADHD self-report screening measures can greatly increase the likelihood of correct diagnosis and timely treatment of ADHD in adolescents. This study provides preliminary evidence for evaluating the reliability and validity of the Adult ADHD Self-Report Scale-Revised (ASRS-R) in a school-based sample of Chinese adolescents. Methods: The ASRS-R and the Strengths and Difficulties Questionnaire (SDQ) were administered to 867 adolescents aged 12 to 16 years (M[subscript age] = 13.08 years). Construct validity was assessed using correlation analysis of the ASRS-R with the SDQ. Moreover, confirmatory factor analysis (CFA), internal consistency, retest reliability, and measurement invariance of the scales were examined by gender. Results: CFA showed a two-dimensional factor structure of the ASRS-R, and the model fitted the data well ([chi-squared]/df = 4.370, RMSEA = 0.062, TLI = 0.932, CFI = 0.940, GFI = 0.927, AGFI = 0.907, and SRMR = 0.038). The ASRS-R scale was invariant across gender and had satisfactory internal consistency (Cronbach's alpha = 0.934) and test-retest reliability (intraclass correlation coefficient = 0.874). The construct validity, as calculated using the SDQ, was also acceptable. Conclusion: The ASRS-R can be a psychometrically reliable self-report instrument and provide preliminary support as a simple tool for identifying ADHD symptoms in Chinese adolescents. The findings provide evidence for extending the application of the ASRS, previously limited to adults, to the adolescent populations.

Measurement invariance (MI) is an essential part of validity evidence concerned with ensuring that tests function similarly across groups, contexts, and time. Most evaluations of MI involve multigroup confirmatory factor analyses (MGCFA) that assume simple structure. However, recent research has shown that constraining non-target indicators to zero when cross-loadings are present results in biased estimates of latent variable associations. Using Monte Carlo simulation, we investigate the behavior of fit statistics for identifying non-invariance when the target measurement model is the same for both groups, and the source of non-invariance is the presence and magnitude of non-zero cross-loadings in one group, but not in another. We consider differences between MGCFA and multigroup ESEM (MGESEM), and combined and separate group tests of configural invariance. Implications for applied researchers are provided.

Multilevel factor mixture modeling (FMM) is a hybrid of multilevel confirmatory factor analysis (CFA) and multilevel latent class analysis (LCA). It allows researchers to examine population heterogeneity at the within level, between level, or both levels. This tutorial focuses on explicating the model specification of multilevel FMM that considers the conceptualization of multilevel constructs. Empirical data sets are used to demonstrate the applications of multilevel FMM for within-level constructs, between-level constructs, and within- and between-level constructs. Detailed model specifications of integrating latent classes into multilevel constructs are provided. For modeling the heterogeneity at the between level, parametric and nonparametric approaches are compared both conceptually and substantively using demonstration data. The interpretations of results using multilevel FMM are also provided. The tutorial is concluded with a discussion of some important aspects of applying multilevel FMM.

The replication crisis in social and behavioral sciences has raised concerns about the reliability and validity of empirical studies. While research in the literature has explored contributing factors to this crisis, the issues related to analytical tools have received less attention. This study focuses on a widely used analytical tool - confirmatory factor analysis (CFA) - and investigates one issue that is typically overlooked in practice: accurately estimating factor-loading signs. Incorrect loading signs can distort the relationship between observed variables and latent factors, leading to unreliable or invalid results in subsequent analyses. Our study aims to investigate and address the estimation problem of factor-loading signs in CFA models. Based on an empirical demonstration and Monte Carlo simulation studies, we found current methods have drawbacks in estimating loading signs. To address this problem, three solutions are proposed and proven to work effectively. The applications of these solutions are discussed and elaborated.

When comparing relations and means of latent variables, it is important to establish measurement invariance (MI). Most methods to assess MI are based on confirmatory factor analysis (CFA). Recently, new methods have been developed based on exploratory factor analysis (EFA); most notably, as extensions of multi-group EFA, researchers introduced mixture multi-group EFA, multi-group exploratory factor alignment, EFA trees, and multi-group factor rotation to resolve rotational indeterminacy in EFA. The main advantage of EFA-based (compared to CFA-based) assessment of MI is that no potentially too restrictive measurement model has to be specified. This allows for a more thorough investigation because violations of MI due to cross-loadings can be considered, too. For each method, we address the model specification and recommendations for application, detailing their strengths and weaknesses. We demonstrate each method in combination with multi-group factor rotation in an empirical example. Differences to and possible combinations with CFA-based methods are discussed.

There is increasing interest in using factor scores in structural equation models and there have been numerous methodological papers on the topic. Nevertheless, sum scores, which are computed from adding up item responses, continue to be ubiquitous in practice. It is therefore important to compare simulation results involving factor scores to those of sum scores so that applied researchers can understand the advantages. Yet, researchers seldom compare sum scores and factor scores in terms of bias, a common simulation outcome. A reason for this is that sum scores are on a different scale and it has been unclear how to compare sum scores to other types of scores. This paper provides guidance on computing bias for sum scores by deriving the expected values of model parameters in a sum score model.

We propose new ways of robustifying goodness-of-fit tests for structural equation modeling under non-normality. These test statistics have limit distributions characterized by eigenvalues whose estimates are highly unstable and biased in known directions. To take this into account, we design model-based trend predictions to approximate the population eigenvalues. We evaluate the new procedures in a large-scale simulation study with three confirmatory factor models of varying size (10, 20, or 40 manifest variables) and six non-normal data conditions. The eigenvalues in each simulated dataset are available in a database. Some of the new procedures markedly outperform presently available methods. We demonstrate how the new tests are calculated with a new R package and provide practical recommendations.

This paper describes the design and evaluation of the Organic chemistry Representational Competence Assessment (ORCA). Grounded in Kozma and Russell's representational competence framework, the ORCA measures the learner's ability to "interpret," "translate," and "use" six commonly used representations of molecular structure (condensed structures, Lewis structures, skeletal structures, wedge-dash diagrams, Newman projections, and chair conformations). Semi-structured interviews with 38 first-semester organic chemistry learners informed the development of the ORCA items. The ORCA was developed and refined through three pilot administrations involving a total of 3477 first-semester organic chemistry students from multiple institutions. The final version of the ORCA was completed by 1494 students across five institutions. Various analyses provided evidence for the validity and reliability of the data generated by the assessment. Both one-factor and three-factor correlated structures were explored via confirmatory factor analysis. The one-factor model better captured the underlying structure of the data, which suggests that representational competence is better evaluated as a unified construct rather than as distinct, separate skills. The ORCA data reveal that the representational competence skills are interconnected and should consistently be reinforced throughout the organic chemistry course.

The Servant Leadership Scale has been developed in the context of the university. This scale has seven dimensions: behaving ethically, development, emotional healing, empowerment, pioneering, relationship building, and wisdom. Furthermore, this scale was modified into six dimensions: authenticity, behaving ethically, development, emotional healing, humility, and wisdom. To date, this scale has only been tested in universities and the public sector, while it has never been studied in Indonesian Christian higher education. This study aimed to validate the scale of servant leadership of Christian education leaders in Indonesia. The method is quantitative, with second-order confirmatory factor analysis. This study used a survey of 180 lecturers in Christian higher education in East Java, Indonesia. The analysis was carried out with the help of SmartPLS 4. The analysis employing pretest, first and second-order (post-test) indicates that all indicators of servant leadership are valid, reliable, and constitute a multidimensional construct with nine dimensions. These dimensions include behaving ethically, development, emotional healing, empowerment, pioneering, relationship building, wisdom, transcendental spirituality, and motivation to serve. This study concludes that the Servant Leadership Scale suits Indonesian culture and can be used for research in religious universities.

The mental health of college students in the United States has been a longstanding national concern, which has only been exacerbated by the ongoing COVID-19 pandemic. The Journey to Wellness Scale (JWS) is a newly developed instrument grounded in empirical research in prevention, positive psychology, resilience, and social-emotional learning, designed to measure psychological wellbeing in adults, including college students, across 10 dimensions: Adaptability, Initiative, Conscientiousness, Connectedness, Social Competence, Empathy, Optimism, Emotional Self-Regulation, Mindfulness, and Self-Efficacy. The JWS, a 60-item self-report instrument, requires participants to rate their endorsement of the items on a Likert-type scale. The current study explored the adequacy of the JWS in measuring psychological wellness by confirmatory factor analysis with a sample of 722 college students. Results indicated that the JWS reliably captured the 10 dimensions and effectively measured overall psychological wellness. These findings support the JWS as a valid tool for assessing psychological wellness in the college student population. Future research directions and implications of the study were discussed.

Teaching is a stressful profession with a high turnover rate. Schools and related institutions need to take more action to support teachers and keep teacher stress at a manageable level. The continued research and practical effort require measures to examine teachers' stress in a briefer and accurate manner. The Teacher Stress Scale is a recently developed brief measure to examine teacher stress with promising psychometric characteristics. The present study aims to further validate TSS scores with a large sample of teachers ranging from pre-kindergarten to the 12th grade from the United States and United Kingdom. Findings of the internal structure validity, convergent validity, and the internal consistency reliability of TSS scores were examined. Specifically, the confirmatory factor analysis of the unidimensional model and the two-dimensional model showed poor fit, but the bi-factor model evidenced a strong fit. Factorial invariance testing yielded strong invariance between early education and secondary education teachers as well as satisfactory invariance between teachers from the United States and the United Kingdoms. The Inadequate School-Based Support TSS subscale demonstrated convergent validity with other support measures, and the overall TSS showed acceptable internal consistency reliability evidence of scores. Limitations and implications of the TSS, as well as future research directions were discussed.

Given the crucial role of feedback in supporting learning in higher education, understanding the factors influencing feedback effectiveness is imperative. Student feedback literacy, that is, the set of attitudes and abilities to make sense of and utilize feedback is therefore considered a key concept. Rigorous investigations of feedback literacy require psychometrically sound measurement. To this end, the present paper reports on the development and initial validation (N = 221) of a self-report instrument. Grounded in the conceptual literature and building on previous scale validation efforts, an initial overinclusive item pool is generated. Exploratory factor analysis and the Rasch measurement model yield adequate psychometric properties of an initial scale measuring two dimensions: feedback attitudes and feedback practices with a total of 21 items. We further provide evidence for criterion-related validity. Findings are discussed in light of the emerging feedback literacy literature and avenues for further improvement of the scale are reported.

Purpose: Given that the current sustainability assessment in higher education institutions primarily relies on qualitative methods with relatively limited quantitative tools, the purpose of this study is to design a tool that could be used to comprehensively assess the overall state of higher education institutions' sustainability. Design/methodology/approach: The authors based the "Model to Assess the Sustainability of Higher Education Institutions" on the Triple Bottom Line (TBL) framework of economic, environmental and social factors, and established its primary dimensions as educational level, research capacity, community outreach, campus operations, campus experience and assessment reports. They designed the College Organisational Sustainability Scale (CO-SS) based on this research model, drawing their inspiration from the qualitative research tool, the Sustainability Assessment Questionnaire, and taking the following validation steps: expert review (n = 10), pilot testing (n = 150) and formal experiments (n = 1108). These steps were taken to optimise the scale items, test the model's validity and assess its reliability. Findings: After undergoing rigorous scientific validation, CO-SS was unequivocally confirmed as an effective and reliable tool, demonstrating its accurate reflection of the level of sustainability in higher education institutions. Originality/value: The authors took an industry-specific approach by relying on the TBL and the Sustainability Assessment Questionnaire to construct and validate the CO-SS. Furthermore, the CO-SS has the potential to evolve into a self-assessment tool for higher education institutions, and a reliable foundation for data-driven decision-making in the realm of organisational sustainability at universities.

It is well documented that literacy coaches engage in a wide variety of tasks related and unrelated to their role. However, little is known about their efficacy beliefs related to performing these tasks. In this article we describe the development and initial testing of the Literacy Coaching Self-Efficacy Scale that was designed and created to assess K-12 literacy coaches' self-efficacy beliefs for coaching tasks. The items on the scale reflect our review of the International Literacy Association's 2017 standards for literacy coaches. Evidence of test content was examined based on review from experts in the fields of literacy coaching and self-efficacy. Validity evidence was explored through correlations with other previously established instruments. Exploratory factor analysis yielded three distinct factors and results indicated a high level of internal consistency. A summary of participant efficacy beliefs regarding coaching tasks are discussed, n = 100. The results of this study will support school districts, teacher preparation programs, and individual coaches to monitor beliefs related to performing literacy coaching tasks and provide insights into the tasks that a coach may need additional support to perform.

The aim of this research is to adapt the 24-item "Learner Autonomy Scale" developed by Sereti and Giossos (2018) in higher education samples into Turkish by examining the psychometric properties of high school and secondary school samples, and to determine whether these groups are equivalent in terms of measurement invariance. The scale was applied in high school (n = 475) and secondary school (n = 395) samples consisting of 870 students. Different from the original four-factor scale form, EFA applied to both groups revealed a two-factor (factor load range: 0.308-0.775) and 21-item. Correlation values (r = 0.209-0.392, p?0.001) indicate that the factors are not strongly related. The factors produced adequate internal consistency coefficients ([alpha] = 0.706-0.866; [omega] = 0.708-0.871) and were validated by meeting the fit indices accepted in the literature for CFA. Measurement invariance tests revealed strong invariance for the structural and metric tests and partial invariance for the scalar test in high school and secondary school samples. More research is needed to determine why the intersections of items 19, 20, and 21 are not invariant. The main contribution to "learner autonomy" in this study is the adaptation and justification of a valid and reliable measurement tool for determining autonomy in the adolescent age group. The use of the adapted scale in different educational environments and in the examination of "autonomy" by adapting it specific to the field (science, mathematics, etc.) will provide important implications for further theoretical studies.

The learning environment for students is affected by factors inside and outside of the classroom. Research denotes the relationship between students' learning environment and teachers' satisfaction with their job. Job satisfaction for teachers consists of several interpersonal, classroom, and school factors known as teacher working conditions (TWCs). Few studies attempt to understand TWCs and job satisfaction for teachers in an urban school district; which is of particular importance as approximately 20% of teachers in the U.S. instruct in urban environments. This study analyzes teacher responses from an annual TWCs survey through a principal component analysis and hierarchical multiple regression. Results indicate that teachers' satisfaction with campus school culture and ratings of campus behavioral response were positively associated with job satisfaction. As learning environments across the U.S. continue to require highly qualified teachers, this research underscores how one urban school district was able to retain teachers and keep their teachers satisfied with their job. This study contributes an initial conceptualization of urban TWCs and the importance of school administrators' addressing of these to maintain high job satisfaction.

With the increasing usage of digital technologies, online collaborative learning is becoming popular in institutions. However, comprehensive factors (e.g. technological factors, collaboration factors and psychological factors) affecting the effectiveness of online collaborative learning are understudied. Thus, both the online collaboration learning theory and technology acceptance model were employed to propose a conceptual framework to explain the effectiveness of online collaborative learning on student learning outcomes. A cross-sectional survey was conducted using a reliable online platform in China. We have collected 368 valid responses from Sojump (http://www.sojump.com) using judgmental sampling method. Participants from China who had used online collaborative tools for learning in the past three months were invited to complete an online survey, and data were analyzed by using Partial Least Square Structural Equation Modelling. The results revealed that technological factors (i.e. perceived usefulness and perceived ease of use) predict positive attitudes towards using technology. In addition, collaborative factors (i.e. collaboration with peers and teacher-student interactions) enable students to be emotionally engaged. When psychological factors (i.e. emotional engagement and attitudes) are in place, better student learning outcomes can be achieved. The theoretical contribution of this study includes extending the theoretical framework of technology acceptance model to examine factors affecting student learning outcomes by integrating online collaborative learning theory. The study also offers practical implications to institutes for promoting online collaborative learning to achieve greater academic success by ensuring technology support, fostering teacher-student interactions, encouraging peer collaborations and emotional engagement, as well as developing a positive attitude towards students.

Grounded in the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), this study investigates the interplay between key UTAUT2 constructs and motivation modeled by Self-Determination Theory (SDT) in shaping English as a Foreign Language (EFL) learners' behavioral intention and actual use of generative AI tools. Accordingly, three research questions were devised, including (1) What are the structural relationships between the UTAUT2 constructs for EFL learners to accept and use generative AI for English learning? (2) Does EFL learners' SDT motivation influence their behavioral intention toward and actual use of generative AI? and (3) What are the moderating effects of EFL learners' SDT motivation toward their acceptance and use of generative AI? A comprehensive survey involving 620 Chinese undergraduates assessed their technology acceptance and SDT motivation of generative AI tools in the EFL learning context. Confirmatory factor analysis and structural equation modeling were employed to analyze the data. Results indicate robust model fit indices, both with and without considering moderating effects. Performance expectancy, effort expectancy, social influence, hedonic motivation, habit, and SDT motivation serve as significant predictors of EFL learners' behavioral intention towards generative AI tools, while price value does not demonstrate a significant impact on behavioral intention. Additionally, behavioral intention and SDT motivation jointly and significantly predict EFL learners' actual use of the technology. Importantly, introducing SDT motivation as a moderator unveils additional insights. Facilitating conditions exerts a significant influence on both behavioral intention and actual use, indicating a significant moderating effect of SDT moderation on these two pathways. Moreover, SDT motivation also significantly moderates the relationships between facilitating conditions and behavioral intention as well as between facilitating conditions and actual use, adding depth to our understanding of the nuanced interplay between motivation and technology acceptance of generative AI tools. The study concludes with insightful discussions on the findings, acknowledging the robust contributions and highlighting areas for future research to further enrich our understanding of EFL learners' adoption of generative AI tools in the context of UTAUT2 with SDT moderation.

Research Purpose and Contribution: The study aimed to construct an evaluation framework for assessing pupils' computational thinking (CT) during classroom learning problem solving. As a self-report evaluation scale for pupils, this evaluation framework further enriched the CT assessment instruments for pupils and provided a specialized instrument for experts to evaluate pupils' CT in problem-solving situations during classroom learning. Background: CT cultivation and assessment methods are hot topics in the field of education. CT assessment can effectively test the effect of CT cultivation. There are many CT assessment methods, of which evaluation frameworks are an effective self-reporting assessment method. Existing studies on self-reported CT evaluation frameworks are commonly applicable to students at different stages. However, few studies have focused on the specific context from the perspective of practice for pupils. Thus, the evaluation framework of pupils' CT is worth exploring. Intended Outcomes: A CT evaluation framework for evaluating pupils' CT in problem-solving situations in classroom learning was constructed to facilitate researchers' understanding of pupils' CT levels and problem-solving skills. Application Design: In this study, data from 897 pupils in the fifth and sixth grades were collected using an online questionnaire that included 27 items about CT. Exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and item analysis were conducted to analyze the data in this study, with 17 items remaining in the final evaluation framework. Findings: The fitting validity, convergence validity, and discriminant validity all met the recommended criteria, which showed that the evaluation framework was effective. The total reliability of CT was 0.911, indicating that the consistency and reliability of the evaluation framework constructed in this study were satisfied.

We conducted a component analysis of skill acquisition consequences for correct and incorrect responses. In the learn unit (LU) condition, researchers praised correct responses and implemented a correction procedure contingent on incorrect responses. In the praise-only-for-correct-responses (PC) condition, researchers delivered contingent praise for correct responses and ignored incorrect responses. In the correction-only-for-incorrect-responses (CI) condition, researchers ignored correct responses and implemented the correction procedure contingent on incorrect responses. We manipulated this independent variable across educational and abstract stimuli and measured acquisition rate, duration, and maintenance of responses. The results showed that the LU and the CI conditions were both effective in teaching listener responses and were more effective than the PC procedure. Furthermore, the LU instruction was not necessarily more efficient than the CI condition on acquisition of listener responses. The results suggested that the correction procedure may be necessary and sufficient for skill acquisition and maintenance.

This study aimed to develop and evaluate the psychometric properties of the Educational Leadership Scale for Faculty Members (ELSF) in Arabic. The scale was rigorously tested using both traditional methods--exploratory factor analysis (EFA) and confirmatory factor analysis (CFA)--as well as advanced network techniques, including exploratory graph analysis (EGA) and centrality measures. The study sample consisted of 350 faculty members (56% male, 44% female) from various universities, with a mean age of 42.3 years (SD = 7.8). Participants represented a range of academic disciplines, and all were involved in educational leadership roles within their respective institutions. EFA revealed a five-factor structure that explained 68.4% of the total variance. CFA further confirmed the model's adequacy, with fit indices showing a good model fit (CFI = 0.95, TLI = 0.94, RMSEA = 0.06). The ELSF, comprising 22 items across these five dimensions, demonstrated strong internal consistency, with a Cronbach's alpha coefficient of 0.89. Additionally, EGA supported the factor structure identified by traditional methods, reinforcing the stability and consistency of the scale. Centrality measures highlighted Item 18 as the most influential, with betweenness, closeness and strength centrality scores of 0.45, 0.78 and 0.62, respectively, within the 'Research-Ethical Leadership' subscale. These findings affirm the ELSF's credibility as a robust tool for assessing educational leadership among faculty members. The scale's strong psychometric properties suggest it is well-suited for application in diverse academic settings, including potential use across Arabic-speaking countries such as Saudi Arabia, Qatar, the United Arab Emirates, Egypt, Oman and Kuwait.

This report presents a new parent-rated outcome measure of insomnia for children with autism spectrum disorder. Parents of 1185 children with autism spectrum disorder (aged 3-12; 80.3% male) completed the first draft of the measure online. Factor and item response theory analyses reduced the set of 40 items to the final 21-item Pediatric Insomnia Autism Rating Scale. In this online sample, Pediatric Insomnia Autism Rating Scale mean was 21.8 ± 15.0 (range 0-63; coefficient alpha = 0.94). Item response theory results indicated excellent reliability across a range of scores. Next, we conducted a telehealth assessment of 134 children with autism spectrum disorder (aged 3-12; 73% male). In this clinical sample, Pediatric Insomnia Autism Rating Scale mean was 28.9 + 14.62 (range 0-61; coefficient alpha = 0.93). Pearson correlations of Pediatric Insomnia Autism Rating Scale with the PROMIS Sleep Disturbance and the modified Children's Sleep Habits Questionnaire was 0.74 for each. This was significantly higher than correlations of parent-rated disruptive behavior, hyperactivity, repetitive behavior, and anxiety measures (range 0.29-0.59)--supporting convergent and divergent validity. Parents of 63 children completed the Pediatric Insomnia Autism Rating Scale three times over 4 weeks. Intraclass correlation was excellent (0.88) over three time points. Pediatric Insomnia Autism Rating Scale is a valid dimensional measure of insomnia in autistic children that produces reliable scores.

There are many approaches used to deliver social and emotional learning (SEL) in schools. These include both explicit skills-based curricula and more micro strategies, such as behavioral modeling by teachers, incorporating concepts into academic lessons, and creating opportunities for students to apply skills throughout the school day. However, in most SEL studies, implementation "dosage" is measured only as the number of lessons delivered from a curriculum, failing to account for the various approaches to SEL delivery. Currently, there is a lack of measurement approaches that capture SEL implementation dosage across diverse "dose forms." To fill this gap, this study proposes a measure of "Multiform Dosage," which captures four different dose forms: delivering lessons, modeling, incorporating, and applying intervention concepts. We tested a measurement model of Multiform Dosage with data collected during the implementation of TOOLBOX, a school-based SEL program. Multiple forms of implementation dosage were measured through self-report surveys of K-5 classroom teachers (n = 94) in October, December, and May. The four-factor measurement model with one cross-loading showed a good fit to the data with acceptable loadings at each occasion. Measurement weights were equivalent between K-2 and 3-5 grade subgroups except one loading of the Incorporation factor in October. Implications of these findings are discussed.

School-based universal well-being screening is proposed within the Multi-tiered Systems of Support approach to collect data on school and individual well-being. Universal screening allows for data-based informed decision, allocating each pupil or set of pupils in universal, selective and/or indicated structured interventions and supports. However, schools require adequate and validated measures of both positive well-being and indicators of psychological health problems. This study focused on the adaptation and validation of the Student Subjective Wellbeing Questionnaire (SSWQ) in Portugal, a tool directed to positive well-being screening. After a translation process, data was collected in 10 schools. A sample of 942 school pupils in the 3rd cycle was randomly split into two subsamples. First was conducted on one subsample, and then, CFA was conducted in the other. Gender and school year invariance were also conducted with the CFA subsample. Internal consistency was likewise analysed. The analysis finished with convergent and discriminant validity. Overall, results supported a second-order factor model (subjective well-being), including four first-order factors, with the elimination of one item and changing one item to another subscale. Results showed good reliability of each factor (all above 0.70). Full measurement invariance was reached for gender (male and female) and school year (7th, 8th and 9th grades). Convergent validity was found with measures of satisfaction with school, group identification with peers and school social support, and divergent validity was found with BPM-Y. Altogether, results support that SSWQ-PG can be used to screen for subjective well-being in schools, helping schools in identifying and addressing pupils' mental health needs more effectively.

Testing for differential item functioning (DIF) has undergone rapid statistical developments recently. Moderated nonlinear factor analysis (MNLFA) allows for simultaneous testing of DIF among multiple categorical and continuous covariates (e.g., sex, age, ethnicity, etc.), and regularization has shown promising results for identifying DIF among many covariates. However, computationally inefficient estimation methods have hampered practical use of the regularized MNFLA method. We develop a penalized expectation-maximization (EM) algorithm with soft- and firm-thresholding to more efficiently estimate regularized MNLFA parameters. Simulation and empirical results show that, compared to previous implementations of regularized MNFLA, the penalized EM algorithm is faster, more flexible, and more statistically principled. This method also yields similar recovery of DIF relative to previous implementations, suggesting that regularized DIF detection remains a preferred approach over traditional methods of identifying DIF.

The current study examined the psychometric properties and correlates of three measures assessing individual differences in mattering among people from Palestine assessed in January, 2024. This study uniquely considers mattering as a resource and feelings of not mattering as a risk factor among people experiencing traumatizing life circumstances. Our sample consisted of 950 Palestinian adults (305 men and 645 women). They completed the General Mattering Scale, the Anti-Mattering Scale, the Fear of Not Mattering Inventory, and the Depression Anxiety Stress Scales-21 (DASS-21). Extensive psychometric tests supported these measures as each having one factor with adequate reliability and validity. Examination of means indicated significantly elevated levels of fear of not mattering, anxiety, depression, and stress. Regression analyses further established that each measure predicted significant unique variance in anxiety, depression, and stress. The findings attest to the further use of these measures and how feelings of mattering can be vital resource as the need for resilience and adaptability escalates due to traumatizing events.

We developed and provided initial validation for a 15-item scale for use with academics. In Phase 1, we utilized a review of the literature, focus groups, and expert feedback to generate 36 items. In Phase 2, we conducted item and exploratory factor analyses to reduce the number of items and assess the factor structure (N = 212; 51.4% female; mean age 48.93 years, SD = 9.45). In Phase 3, we conducted confirmatory factor analyses to verify the initial structure (hold-out sample: N = 210; 56.7% female; mean age 49.20 years, SD = 9.98). In Phase 4, we provided construct validity.

This study developed the Speaking Strategies for Self-Regulated Learning Questionnaire based on Oxford's (2017) strategic self-regulation model of language learning to cross-validate the multifaceted structure of speaking strategies in English as a foreign language (EFL) learners. 963 undergraduate students from a university in Southeast China voluntarily participated in the investigation. Confirmatory factor analyses were conducted to verify three hypothesized models. Through model comparisons, the results indicate that the 10-factor correlated multidimensional structure is the most informative and robust model. The model sheds light on the relationships between the cognitive, affective, sociocultural-interactive strategies, and metastrategies of the ten lower-order speaking strategies. Through multiple linear regression analysis, it was found that three of the ten SRL strategies were predictive of EFL learners' speaking competence. The findings imply that Oxford's (2017) theory can be extended to the field of EFL speaking. The study concludes with implications for fostering strategic awareness among EFL learners.

Determining the number of factors in exploratory factor analysis (EFA) is crucial because it affects the rest of the analysis and the conclusions of the study. Researchers have developed various methods for deciding the number of factors to retain in EFA, but this remains one of the most difficult decisions in the EFA. The purpose of this study is to compare the parallel analysis with the performance of fit indices that researchers have started using as another strategy for determining the optimal number of factors in EFA. The Monte Carlo simulation was conducted with ordered categorical items because there are mixed results in previous simulation studies, and ordered categorical items are common in behavioral science. The results of this study indicate that the parallel analysis and the root mean square error of approximation (RMSEA) performed well in most conditions, followed by the Tucker-Lewis index (TLI) and then by the comparative fit index (CFI). The robust corrections of CFI, TLI, and RMSEA performed better in detecting misfit underfactored models than the original fit indices. However, they did not produce satisfactory results in dichotomous data with a small sample size. Implications, limitations of this study, and future research directions are discussed.

We conducted an extensive Monte Carlo study of factor-rotation local solutions (LS) in multidimensional, two-parameter logistic (M2PL) item response models. In this study, we simulated more than 19,200 data sets that were drawn from 96 model conditions and performed more than 7.6 million rotations to examine the influence of (a) slope parameter sizes, (b) number of indicators per factor (trait), (c) probabilities of cross-loadings, (d) factor correlation sizes, (e) model approximation error, and (f) sample sizes on the local solution rates of the oblimin and (oblique) geomin rotation algorithms. To accommodate these design variables, we extended the standard M2PL model to include correlated major factors and uncorrelated minor factors (to represent model error). Our results showed that both rotation methods converged to LS under some conditions with geomin producing the highest local solution rates across many models. Our results also showed that, for identical item response patterns, rotation LS can produce different latent trait estimates with different levels of measurement precision (as indexed by the conditional standard error of measurement). Follow-up analyses revealed that when rotation algorithms converged to multiple solutions, quantitative indices of structural fit, such as numerical measures of simple structure, will often misidentify the rotation that is closest in mean-squared error to the factor pattern (or item-slope pattern) of the data-generating model.

We develop a "latent variable forest" (LV Forest) algorithm for the estimation of latent variable scores with one or more latent variables. LV Forest estimates unbiased latent variable scores based on "confirmatory factor analysis" (CFA) models with ordinal and/or numerical response variables. Through parametric model restrictions paired with a nonparametric tree-based machine learning approach, LV Forest estimates latent variable scores using models that are unbiased with respect to relevant subgroups in the population. This way, estimated latent variable scores are interpretable with respect to systematic influences of covariates without being biased by these variables. By building a tree ensemble, LV Forest takes parameter heterogeneity in latent variable modeling into account to capture subgroups with both good model fit and stable parameter estimates. We apply LV Forest to simulated data with heterogeneous model parameters as well as to real large-scale survey data. We show that LV Forest improves the accuracy of score estimation if parameter heterogeneity is present.

This mixed methods study examined how a National Professional Development Grant project's first cohort (2018-2020) in the Midwest impacted mostly White and monolingual inservice teachers who work with emergent bilingual learners (EBLs). Two research questions (RQs) guided this study: RQ1: What were the inservice teachers English language ideologies and their confidence in teaching EBLs after they completed professional development on racially, linguistically, and culturally (RLC) responsive teaching mindsets and pedagogies? and RQ2: How did the inservice teachers respond to prompts about raciolinguistic ideologies and EBLs' use of Standard American English? Quantitative t-tests and factor analyses on pre-post teacher surveys were conducted to investigate RQ1. Qualitative open and axial analyses on teachers' reflections to prompts about language ideologies were completed for RQ2. Quantitative results revealed that a majority of the participating teachers reported improved confidence in developing RLC responsive teaching strategies for EBLs. At the same time, their reflections showed that they persisted in their deeply-rooted raciolinguistic ideologies about English, even though they intended to acknowledge and appreciate EBLs' use of language varieties.

The purpose of this study was to validate the Spanish version of the Family Involvement Questionnaire-Short Form (FIQ-SF) for use with Spanish-speaking families of children enrolled in early childhood education programs. This study examined the factor structure of the FIQ-SF and established criterion validity for the resulting FIQ-SF dimension scores. Results from exploratory and confirmatory factor analyses replicated the three dimensions of the English FIQ: Home Engagement, School Engagement, and home-school Conferencing. Mean differences across family demographics were examined. Criterion-related validity for the three FIQ-SF dimensions was established by examining correlations with scores on measures of parent-reported satisfaction with educational experiences, program records of family engagement, direct assessments of child language skills and teacher-reported approaches to learning. Future directions and practice implications for the use of the Spanish FIQ-SF to inform program policy and interventions are discussed.

Intercultural communication research has highlighted the significance of intercultural communication apprehension/anxiety measurement and instrument development in diverse sociocultural contexts. This study embarked on developing and validating a scale, the Perceived Intercultural Communication Anxiety/Apprehension Scale (PICAS) in the English as a foreign language (EFL) context. By drawing upon the review of the literature and expert judgment, a Likert scale with 52 items was developed for assessing the construct of intercultural communication anxiety/apprehension, which was subjected to exploratory and confirmatory factor analysis (CFA) with 760 Iranian EFL learners. The ultimate results of exploratory factor analysis evidenced 17 items with a stable five-factor solution, comprising L2 proficiency, prejudice and stereotypes, significant others' attitudes, status, and context familiarity factors. The subsequent CFA confirmed the five-factor model. The five-factor PICAS was found to be psychometrically reliable and valid. Potential applications, future directions, and limitations are finally addressed.

This study diverges from conventional psychological perspectives that often concentrate on language learning deficiencies necessitating remedial interventions. Instead, it emphasizes the pivotal role of positive psychological constructs in facilitating optimal language development, particularly in contexts characterized by limited exposure to English. Through an exploration of positive psychology dimensions among Thai EFL secondary school students, the research examined the nuanced interplay of positive psychological factors shaping language learning in such contexts. Employing an Exploratory Factor Analysis (EFA) with the inventory and interviews, this study examined the underlying psychological determinants guiding the language learning experiences of 255 Thai EFL secondary school students from diverse regions. Factor analysis, complemented by Kaiser-Meyer-Olkin (KMO) statistics, contributes to refining the inventory and reveals four crucial positive psychology factors that collectively explain 61.158% of the variance in positive psychology levels. The resultant 18-item, 4factor model encompasses processes within four categories of positive psychology constructs--"Engagement and Enjoyment," "Grit and Perseverance," "Interest and Focus," and "Future Intentions." This model culminates in the development of the EFL Positive Psychology Inventory (EFLPP), which exhibits commendable validity and reliability. Additionally, insights gleaned from semi-structured interviews elucidate three sources of L2 positive psychology constructs: "learning environment," "predetermined goals," and "personal interests." This study emphasizes the significance of these positive psychology constructs in informing pedagogical strategies aimed at cultivating efficacious language learning experiences. By elucidating learners' positive psychology constructs, the research attempts to equip English educators in EFL contexts with tailored instructional methodologies that align with learners' positive aspirations, thereby augmenting English language learning outcomes.

The study aimed to translate, culturally adapt and validate the Spanish version of the "Assessing Reasons for School Non-attendance" (ARSNA) originally developed by Havik, Bru and Ertesvåg in 2015 to assess the reasons for school absence in adolescents. We used the back-translation method to translate and adapt the instrument without substantially altering it. A total of 1168 Spanish adolescents (M = 15.03, SD = 2.40) enrolled in 6 secondary education institutes participated in the study. The confirmatory factor analysis establishes a four-dimensional model (FI: Somatic symptoms; FII: Subjective health complaints; FIII: Unjustified absences; FIV: School refusal) with 16 items and invariant depending on gender. The results obtained provide the Spanish version of the ARSNA with good understandability, internal consistency, and reliability for measuring the causes of lack of school attendance. This research makes a new instrument available to the Spanish population that evaluates reasons for school absenteeism.

In this study, an assessment tool was developed to measure the reasoning skills (RS) of preservice science teachers on socio-scientific issues (SSI). As a result of the literature review, the scale was developed based on five dimensions. These dimensions are complexity, questioning, having different perspectives, skeptical approach and the limitations and adequacy of science. The developed scale consists of a total of 18 items. 577 preservice science teachers participated in the study voluntarily. First-level confirmatory factor analysis (CFA) was conducted to evaluate the construct validity of the items created in line with the theoretical framework. In addition, second-level CFA was applied to test whether the dimensions represented the students' perceptions of socio-scientific reasoning (SSR) skills. When the literature was examined, it was decided that the values of the fit indices were appropriate for model verification. The findings reveal that the developed scale can be used for valid and reliable measurements in determining the perceptions of preservice teachers regarding their SSR skills.

This article reports the development and validation of the new Process and Outcomes from Service-Learning (POSL) questionnaire, a self-report measure that assesses students' service-learning experiences as well as their attainment of a comprehensive set of intended service-learning outcomes. The study involved three phases: (a) construct identification and item generation, (b) content and face validation of the draft items through expert judgment and cognitive interviews, and (c) construct validation through exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and reliability analysis. The final instrument consists of two parts. Part 1 comprises 18 items that measure students' service-learning experiences on six dimensions. Part 2 contains 14 items to assess students' learning outcomes from service-learning grouped under four dimensions. Results show that POSL is a highly reliable and reasonably valid measure of students' experiences of and outcomes from service-learning with good psychometric properties. Limitations and implications of the study are also discussed.

In this paper, we examined the relationship between social networking sites (SNSs) and the coping strategies international students adopt amidst cultural shocks in India, particularly in the vibrant locale of Chandigarh. The study scrutinizes pivotal factors that influence international students' SNS use and creates and validates an instrument that measures this relationship. Grounded in the uses and gratifications theory (UGT), this research introduces an instrument -- the Social Capital Assessment Scale and Inventory (SCASI), which was developed via exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). The research concludes that SNSs play a pivotal role in the globalization of information, encompassing education, knowledge dissemination, interactivity, and cultural exchange in geographically diverse countries such as India.

Exploratory structural equation (ESEM) has received increased attention in the methodological literature as a promising tool for evaluating latent variable measurement models. It overcomes many of the limitations attached to exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), while capitalizing on the benefits of each. Given that the recent introduction of ESEM in statistical software has made its use more accessible to applied researchers, we describe the differences between these three approaches to evaluating measurement models and provide an illustration of their differences through an applied example. Syntax for running these models is also provided that can be modified for application by others.

The Fourth Industrial Revolution Chemistry Teachers Effectiveness Scale (4IRCTES) was evaluated in secondary schools in Southwest Nigeria to determine its item discrimination, item parameters, and model-data fit. This study utilised a descriptive survey research design and included 4,986 Chemistry teachers in the southwestern region of Nigeria, with a sample of 35 Chemistry teachers. The 4IRCTES instrument was used to collect data. Research question one focused on item discrimination using the Multidimensional Graded Response Model (MGRM) of the Item Response Theory (IRT). Research question two examined the overall model-data fit, or M2 statistic. Results indicated that the 4IRCTES items effectively discriminated between teachers with low and high effectiveness. Also, result showed that the MGRM of the IRT is the substantial model-data fit for the 4IRCTES. The study concluded that the MGRM of the IRT provided a strong model-data fit for the 4IRCTES, and that the scale effectively distinguished between ineffective and effective teachers.

This article delineates the development of a measure to assess teachers' reported engagement in practices that center on issues of racial equity as part of their SEL instruction. An iterative mixed-method approach included theoretical grounding, literature reviews, content expert evaluation, focus groups, cognitive interviews, and multiple survey administrations. Exploratory and confirmatory factor analyses were conducted using data from three independent samples of fifth- to eighth-grade teachers (N range = 240-260; White = 67-89%; Black = 3-7%; Latinx = 5-23%). Test-retest reliability was assessed in a fourth national sample from the RAND American Education Panels (N = 482; Black/African American = 19.9%, Latino/Hispanic = 16.2%, Asian/Asian American = 2.7%, American Indian/Native American = 1.9%, White = 66.0%, Middle Eastern/North African = 0.6%, and Other = 2.7%). Results suggest (1) evidence of strong internal consistency for the 41-item Racial Equity-oriented Social Emotional Learning (REQSEL) measure; (2) REQSEL scores correlated with multiple relevant measures of teachers' beliefs and behaviors regarding race, ethnicity, culture, and social justice; and (3) REQSEL scores correlated with teachers' own ethnic-racial identity beliefs.

Interdisciplinarity has the potential to lead to more innovation and advances in knowledge than are possible from a single discipline. Yet, little is known about interdisciplinary collaborations and the perceptions of those involved. This quantitative study investigated the perceptions of U.S. faculty, staff, postdocs, and graduate students involved in education and science/engineering collaborations. Exploratory factor analysis was conducted for two modified scales, Collaboration Perceptions (CP; n = 117; 17 items; [alpha] = 0.923) and Interdisciplinarity Perceptions (IP; n = 119; 11 items; [alpha] = 0.852). Participants' perceptions of collaboration and interdisciplinarity were strongly positive and did not significantly differ based on demographic factors (e.g., gender, discipline, role). Perceptions were influenced by collectivist orientation; the high collectivism group had significantly more positive perceptions of collaboration and interdisciplinarity, and collectivist orientation was positively and significantly correlated with CP and IP scores. Implications and recommendations for interdisciplinary collaborations will be discussed. [Note: The volume number (9) shown on the PDF is incorrect. The correct volume number is 10.]