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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.

Eye-tracking (ET) method provides a promising channel for educational researchers to connect learning outcomes to cognitive processes. The main principle of ET is that our gaze and our focus of attention are connected. Due to the advent of digital technologies, eye tracking studies are increasingly growing in different fields and in mathematics education. We assume that the provided task is one of the ways to analyse deeply cognitive processes, and we wonder how ET studies are dealing with the integration of digital technology in task-design in geometry. Starting from Strohmaier et al. (2020) we found three studies, one focused on geometric proofs and two based on construction of geometric objects. We highlight the contributions of integrating digital technology in learning and instruction, and in research in geometry.

One of the central components of cognitive diagnostic assessment is the Q-matrix, which is an essential loading indicator matrix and is typically constructed by subject matter experts. Nonetheless, to a large extent, the construction of Q-matrix remains a subjective process and might lead to misspecifications. Many researchers have recognized the importance of estimating or validating the Q-matrix, but most of them focus on the conditions of relatively large sample sizes. This article aims to explore Q-matrix validation possibilities under small sample conditions and uses regularized methods to validate the Q-matrix based on the compensatory reparametrized unified model and generalized deterministic inputs, noisy "and" gate models. Simulation studies were conducted to evaluate the viability of the modified least absolute shrinkage and selection operator (Lasso) and modified smoothly clipped absolute deviation (SCAD) methods, comparing them with existing methods. Results show that the modified Lasso and the modified SCAD methods outperform the stepwise, Hull, and MLR-B methods in general, especially under the conditions of small sample sizes. While good recovery in all small sample size conditions is not guaranteed, the modified methods demonstrate advantages across various item quality conditions. Also, a real data set is analyzed to illustrate the application of the modified methods.

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.

Most existing solutions to the current replication crisis in science address only the factors stemming from specific poor research practices. We introduce a novel mechanism that leverages the experts' predictive abilities to analyze the root causes of replication failures. It is backed by the principle that the most accurate predictor is the most qualified expert. This mechanism can be seamlessly integrated into the existing replication prediction market framework with minimal implementation costs. It relies on an objective rather than subjective process and unstructured expert opinions to effectively identify various influences contributing to the replication crisis.

This study investigates the validity and reliability of generative large language models (LLMs), specifically ChatGPT and Google's Bard, in grading student essays in higher education based on an analytical grading rubric. A total of 15 experienced English as a foreign language (EFL) instructors and two LLMs were asked to evaluate three student essays of varying quality. The grading scale comprised five domains: grammar, content, organization, style & expression and mechanics. The results revealed that fine-tuned ChatGPT model demonstrated a very high level of reliability with an intraclass correlation (ICC) score of 0.972, Default ChatGPT model exhibited an ICC score of 0.947 and Bard showed a substantial level of reliability with an ICC score of 0.919. Additionally, a significant overlap was observed in certain domains when comparing the grades assigned by LLMs and human raters. In conclusion, the findings suggest that while LLMs demonstrated a notable consistency and potential for grading competency, further fine-tuning and adjustment are needed for a more nuanced understanding of non-objective essay criteria. The study not only offers insights into the potential use of LLMs in grading student essays but also highlights the need for continued development and research.

It is of critical importance to be aware of the historical discrimination embedded in the data and to consider a fairness measure to reduce bias throughout the predictive modeling pipeline. Given various notions of fairness defined in the literature, investigating the correlation and interaction among metrics is vital for addressing unfairness. Practitioners and data scientists should be able to comprehend each metric and examine their impact on one another given the context, use case, and regulations. Exploring the combinatorial space of different metrics for such examination is burdensome. To alleviate the burden of selecting fairness notions for consideration, we propose a framework that estimates the correlation among fairness notions. Our framework consequently identifies a set of diverse and semantically distinct metrics as representative of a given context. We propose a Monte Carlo sampling technique for computing the correlations between fairness metrics by indirect and efficient perturbation in the model space. Using the estimated correlations, we then find a subset of representative metrics. The paper proposes a generic method that can be generalized to any arbitrary set of fairness metrics. We showcase the validity of the proposal using comprehensive experiments on real-world benchmark datasets.

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.

In the shift to Emergency Remote Teaching and Learning (ERT&L) during the COVID-19 pandemic, remote assessment and feedback became a major source of discontent and challenge for students and staff. This paper is a reflection and analysis of assessment practices during ERT&L, and our theorisation of the possibilities for shifts towards sustainable and transformative approaches to assessment in the global south. We argue that the challenges experienced during the pandemic revealed a view of assessment as gatekeeping, and a conception of quality as exceptional. In the context of ERT&L, assessment strategies based on such views may have further marginalised and disadvantaged students faced with technological, economic, and socio-cultural access issues. We highlight that institutional responses and staff concerns regarding standards and the validity and reliability of remote assessments are evident of affirmative rather than transformative approaches to reimagining assessments for social justice.

Courses: This activity can be used in writing-based (communication) courses across various disciplines including, but not limited to, introduction to writing and rhetoric, business communication, and communication research methods. Objectives: On completion of this activity, students will develop critical reading, thinking, and writing skills as they both write their own summary and then compare it to AI-generated summaries on the same reading. Students will practice making decisions about the practical and ethical use of AI tools for communication, especially regarding inclusion in an academic research project and citation.

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.

Social realist theorising about curriculum and social justice in higher education has emphasised the importance of providing equity of epistemic access to powerful knowledge. However, there has been little discussion about what constitutes powerful knowledge and how students can use it for social good. In the science disciplines, the traditional undergraduate curriculum is shaped by economic agendas and by perceptions of its purpose to train future scientists. This has resulted in a curriculum focused on the learning of scientific facts rather than on how scientific knowledge is created, validated and critiqued, overshadowing the potential for the curriculum to simultaneously empower learners to develop critical scientific literacy to productively engage with urgent socio-scientific issues such as climate change. In this paper, I argue that social good can be better served by engaging students with powerful knowledge of the epistemology of science through including 'Nature of Science' (NOS) in the curriculum.

Research Findings: A growing number of stakeholders in early childhood education (ECE) rely on self-assessment to assess and improve the quality of ECE. In this systematic review, we investigated the reliability and validity of self-assessment in ECE, summarizing findings from 27 publications. We meta-analytically synthesized findings from 25 publications for 1,882 groups and 79,163 children aged 0-72 months in center-based childcare. Most studies reported high internal consistency, but one study reported a lower consistency. Inter-rater reliability was generally high. A three-level meta-analysis (k = 13, ES = 45) revealed a positive association between self-assessment ratings and ratings with validated measures of ECE quality (r = 0.38), indicating a moderate convergent validity. Studies with lower methodological quality and published "peer reviewed" studies reported somewhat higher correlations between self-assessment ratings and ratings with validated measures. The meta-analytic correlation remained significant after removal of studies with lower methodological quality (r = 0.33) or studies from the "grey" literature (r = 0.44). A second meta-analysis (k = 16, ES = 71) with a focus on the predictive validity of self-assessment ratings showed a small significant association between self-assessed ECE quality and child outcomes (r = 0.09); there were no significant moderators. Practice or Policy: Despite empirical evidence for the validity of self-assessment, further studies are needed to investigate potential bias in self-assessment. Future studies should further explore the validity and reliability of self-assessment measures in ECE, including countries outside the United States.

Although there is increased interest in social and emotional competence and mental health in Croatia, there are currently limited measurement options available for early childhood settings. Thus, the SSIS SEL Brief Scales (SSIS SELb), an efficient measure of social and emotional learning competencies developed in the United States, was translated to Croatian and used by 49 early childhood educators to rate a sample of 685 children (average age 4.3 years) from several counties in Croatia. Regarding measurement invariance, the final model cohered substantially with a CASEL-inspired framework. Overall reliability was also high especially for the SEL Composite ([alpha] = 0.94), with notably lower reliability for subscales. Regarding cross-group concurrent validity, concurrent coefficients were largely similar across age and gender, but there were regional differences in validity. Likewise, validity correlations were in line with expectations, with moderate relationships observed between the SSIS SEL Composite and Child and Youth Resilience Measure scores. In sum, the high level of reliability provided a foundation for applied and research usage of the Croatian SSIS SELb, although further validation research will continue to be necessary before widescale implementation. Limitations to the study are discussed and also point to needed additional research before utilizing the Croatian translated SSIS SELb for applied decisions with young children.

The article introduces triangulation to converge evidence from corpus and experimental data, by means of two case studies in second language (L2) learners of Greek. The first case study investigates the acquisition of gender agreement, while the second probes the development of relative clauses. In both studies, findings from the corpus are tested against online experimentation using eye-tracking and self-paced reading tasks, a combination that is scarce in research implementing triangulation. The findings suggest that methodological convergence yields both congruous and incongruous evidence. However, both types of evidence contribute to a nuanced understanding of the linguistic phenomena under study, as well as the different perspectives from which they are approached. The article concludes that such an approach to triangulation can significantly contribute to enhancing the reliability and validity of the findings, provided that methodological convergence has been achieved at the design level of the study.

Quantitative measures in mathematics education have informed policies and practices for over a century. Thus, it is critical that such measures in mathematics education have sufficient validity evidence to improve mathematics experiences for students. This article provides a systematic review of the validity evidence related to measures used in elementary mathematics education. The review includes measures that focus on elementary students as the unit of analyses and attends to validity as defined by current conceptions of measurement. Findings suggest that one in ten measures in mathematics education include rigorous evidence to support intended uses. Recommendations are made to support mathematics education researchers to continue to take steps to improve validity evidence in the design and use of quantitative measures.

A critical revisiting of research methods with multilingual learners raises issues of validity that are often unaddressed in current discussions of research quality. Though validity is conceptualized and assessed differently across research traditions, validity broadly describes the production of findings that are credible and trustworthy. The historically monolingual lens of research methodologies has led to conceptions of validity that are inadequate for ensuring that reported findings "fit the data" in research with multilingual learners. In this article, I describe a retrospective inquiry to critically reassess how current paradigms of validity might be reconceptualized in research with multilingual learners. Through a reexamination of research practices from two of my own studies, this article considers three ways that current monolingual paradigms of validity should be expanded in research with multilingual learners to work toward multilingual conceptualizations of research quality. This article then offers guidance to aid other researchers in taking up issues of validity in the design and reporting of research with multilingual learners.

In this study, the concept of social media parenting (SMP) was defined and a scale was developed to measure parents' perceptions of SMP. Although SMP is referred to as "sharenting" in the literature, given that it has a much broader definition, an attempt was made to define it as a new concept that includes the concept of sharenting. The SMP scale is a five-point Likert-type scale consisting of 28 items that can be grouped under six factors. The study group consisted of 430 parents from different provinces of Türkiye who volunteered to participate in the study. To ensure the scale's validity, exploratory and confirmatory factor analyses, item discrimination analyses, purpose levels, internal consistency levels, and stability analyses were conducted for reliability. It was concluded that the scale obtained from this research is a valid and reliable scale for measuring parents' perceptions of SMP.

The study aimed to develop a Likert-type measurement tool (Digital Literacy Scale, DLS) to determine the digital literacy levels of secondary school students. The validity and reliability of the developed measurement tool were verified using the Rasch model. The Rasch Model can estimate missing data and allow for small study groups (Rasch, Rasch, Probabilistic models for some intelligence and attainment tests, Danish Institute for Educational Research, 1960). Additionally, this model can verify the expected pattern of the measurement tool by calibrating it across participants and items. The content validity of DLS was ensured by expert opinion, and the construct validity was ensured by using the Rach model. In the content validity study, a 25-item pool was created for the draft DLS, and 5 items were removed from the draft DLS at this stage. Construct validity studies were carried out with the remaining 20 items using the classical test theory and item response theory (Rasch model). Exploratory Factor Analysis (EFA) and first-level Confirmatory Factor Analysis (CFA) were used within the scope of classical test theory. Then some Rasch assumptions such as dimensionlessness, local independence, monotonicity, and bias were tested for DLS. In the validity and reliability analysis of DLS, no items were eliminated, and the quantitative theoretical results were statistically confirmed. The analysis results showed that the minimum statistical values required for a good measurement tool were met. Accordingly, 20 valid and reliable compatible items that can be used to determine the digital literacy status of secondary school students were produced.

Eye-tracking procedures generate copious process data that could be valuable in establishing the response processes component of modern validity theory. However, there is a lack of tools for assessing and visualizing response processes using process data such as eye-tracking fixation sequences, especially those suitable for young children. This study, which explored student responses to a spatial reasoning task, employed eye tracking and social network analysis to model, examine, and visualize students' visual transition patterns while solving spatial problems to begin to elucidate these processes. Fifty students in Grades 2-8 completed a spatial reasoning task as eye movements were recorded. Areas of interest (AoIs) were defined within the task for each spatial reasoning question. Transition networks between AoIs were constructed and analyzed using selected network measures. Results revealed shared transition sequences across students as well as strategic differences between high and low performers. High performers demonstrated more integrated transitions between AoIs, while low performers considered information more in isolation. Additionally, age and the interaction of age and performance did not significantly impact these measures. The study demonstrates a novel modeling approach for investigating visual processing and provides initial evidence that high-performing students more deeply engage with visual information in solving these types of questions.

While there are many documented approaches to using technological tools to support collaboration in remote environments, studies related to proof-based courses are overwhelmingly situated in the context of geometry. This study uses instrumental genesis theory to study how students in an introduction to proofs course operationalize the technological tools, namely Google Docs and Zoom, available to them to engage in collaborative proof activity during small group work. Results from our analysis found that students coordinate uses of different tools to develop instruments that can be used to (1) engage in collective argumentation by coordinating visual mediators and verbal communication and (2) co-construct a group solution by refining shared text. In particular, Google Docs was found to be a versatile and rich tool that supported the students' collaborative activity and encouraged a more active approach to proof-related writing. We discuss implications of the students' tool use on their collective mathematical proof activity.

Active citizenship is core to social justice for both women and men. This paper explores how gender and active citizenship are addressed in teacher education training programmes in Tanzania. We applied qualitative methods in analysing two teacher education institutions' curricula documents and conducted thee focus group discussions with final year teacher student teachers. Our review of the curricula focused on (1) the course names, (2) course aims, (3) learning outcomes, (4) teaching/learning contents or (5) reading lists. This was supported by the findings from focus group discussions. The findings show that, although both gender and active citizenship were incorporated in the existing teacher's education curricula in Tanzania, the weight given to these topics were marginal. We argue that more content in combination with contextualised and gender-responsive teaching and learning resources or materials could give student teachers better competence necessary for linking knowledge they get with everyday gender and citizenship challenges in Tanzanian schools and their communities.

In this paper we develop a case for introducing a new teaching tool to undergraduate mathematics. Lean is an interactive theorem prover that instantly checks the correctness of every step and provides immediate feedback. Teaching with Lean might present a challenge, in that students must write their proofs in a formal way using a specific syntax. Accordingly, this paper addresses the issue of formalism from both a theoretical and a practical point of view. First, we examine the nature of proof, referring to historical and contemporary debates on formalization, and then show that in mathematical practice there is a growing rapprochement between strictly formal proof and proofs-in-practice. Next, we look at selections from the mathematics education literature that discuss how and when students advance through higher levels of mathematical maturity to reach a point at which they can cope with the demands of rigorous formalism. To probe the integration of Lean into teaching from an empirical point of view, we conducted an exploratory study that investigated how three undergraduate students approached the proof of double negation with Lean. The findings suggest that the rigorous nature of Lean is not an obstacle for students and does not stifle students' creativity in writing proofs. On the contrary, proving with Lean offers a great deal of flexibility, allowing students to follow different paths to creating a valid proof.

"Epistemological justification" is a way of thinking that manifests itself through perturbation-resolution cycles revolving around the question "why and how was a piece of mathematical knowledge conceived?" The paper offers a conceptual framework for constituent elements of epistemological justification. The framework provides: (a) a theoretical basis for epistemological justification, (b) criteria for its occurrence, and (c) analysis of its relation to "mathematical explanation." The criteria are illustrated by a series of learning-teaching events taken from teaching experiments aimed at investigating the learning and teaching in linear algebra. The contribution of the proposed framework is three-fold: (a) it addresses a critical aspect of proof understanding not explicitly addressed in the literature; (b) it goes beyond the traditional treatment of mathematical understanding and production into questions about learners' conceptualization of the origins of mathematical knowledge; and (c) it theorizes instructional approaches that can advance this conceptualization among students.

While proof has been studied from different perspectives in the mathematics education literature for decades, students continue to struggle to build proof comprehension. Complicating this, the manner in which proof comprehension is assessed largely remains to be the definition-theorem-proof format in which students are asked to reproduce proofs or similar proofs that are presented in class. This approach can encourage students to memorize proofs rather than develop tools for syllogistic reasoning. This paper reports on a seven-year collaboration among research mathematicians and mathematics educators. Following a model for proof comprehension, they implemented a cycle of planning assessments, implementing them and evaluating student responses in several courses each semester for three years at two universities. The model-based assessments were designed with probing questions about proofs or subproofs to point student attention to the relationships among definitions, statements and their relationships, as well as the logic used to help students to both develop proof knowledge and demonstrate their mathematical thinking. Discrepancies between the intention of assessments and student responses led to refinements as the team reviewed the results to inform its practice. Collaboration, experience and empirical data informed the development of the new "Promoting Reasoning in Undergraduate Mathematics (PRIUM) Qualitative Framework for Proof Comprehension." The paper discusses three main results: the Framework and how to use it, the Framework's utility at the individual, course and program levels of departmental evaluation, and a collaborative research process that may be utilized between research mathematics educators and mathematicians.

Recent research in university mathematics education has moved beyond the traditional focus on the transition from secondary to tertiary education and students' understanding of introductory courses such as pre-calculus and calculus. There is growing interest in the challenges students face as they move into more advanced mathematics courses that require a shift toward formal reasoning, proof, modeling, and problem-solving skills. This survey paper explores emerging trends and innovations in the field, focusing on three key areas: innovations in teaching and learning advanced mathematical topics, transitions between different levels and contexts of mathematics education, and the role of proof and proving in advanced university mathematics. The survey reflects the evolving landscape of mathematics education research and addresses the theoretical and practical challenges of teaching and learning advanced mathematics across various contexts.

The current study reviewed the practice and application of social validity assessments in single-case design (SCD) studies within the field of school psychology. Social validity refers to the acceptability of intervention or program goals, procedures, and outcomes to educators, families, and students. Understanding the ways social validity is assessed and analyzed in recent publications has the potential to improve both school psychology research and practice. Adopting similar procedures described in the (Snodgrass et al., Research in Developmental Disabilities 74:160-173, 2018) analysis, this review systematically investigated the extent to which social validity was evaluated in school psychology SCD studies, the characteristics of social validity assessments, the prevalence of assessing total construct social validity (i.e., goals, procedures, and outcomes), and the extent to which social validity findings were integrated with visual analyses to form conclusions about interventions. A total of 1371 articles were reviewed from six prominent school psychology journals between 2016 and 2020. Reviewed articles included 89 from the "Journal of Applied School Psychology," 227 from the "Journal of School Psychology," 471 from "Psychology in the Schools," 177 from "School Psychology International," 259 from "School Psychology (Quarterly)," and 148 from "School Psychology Review." Although the content analysis revealed several encouraging aspects of the current state of social validity assessment, the majority of the findings suggested that there was still much to be done to advance the rigor of social validity practice.

Research has increasingly focused on the intersection between gender diversity and autism. Understanding the foci, methods, and rigor of recent studies could help guide and maximize impact in this accelerating research area. We conducted a scoping review of peer-reviewed literature on this topic published between 2018 and 2023. The search generated 1432 records after deduplication. Included studies (N = 84) were of English language, featured original qualitative or quantitative findings, and examined a psychosocial connection between autism and gender spectra variables. Autism prevalence among gender-diverse people was the most-studied sub-topic. Methodological rigor was acceptable overall; however, we identified recurrent threats to generalizability and validity, including inconsistent conceptualization of constructs (e.g. gender dysphoria), weak participant sampling and characterization, and reliance on unvalidated measures. Addressing these limitations and meaningfully engaging with community shareholders will be critical to enhancing the replicability and clinical impact of future research.

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.

The integration of ICT in education in developing countries has become a significant focus in various ODA projects and educational research. With the increasing demand for teachers to incorporate ICT in their classrooms, the precise methods for effectively integrating ICT resources have not been thoroughly explored. Therefore, this research aimed to develop the most optimal instructional design principles that may systematically guide teachers in planning their lessons using ICT, specifically in the context of Bangladesh. By employing "the design and development research method," this research developed an initial set of instructional design principles based on literature review and field research, then elaborated on the principles through three sets of internal validation tests and a usability test by conducting in-depth interviews to confirm the applicability of the principles in real classroom settings in Bangladesh. The final version of instructional design principles is composed of five components, ten principles, and 22 specific guidelines. Two distinct features of the principles are discussed for further research. In discussion, this research underscores the necessity of providing practical instructional design principles to guide teachers in effectively utilizing ICT, particularly within a resource-limited learning environment like Bangladesh.

The Grit--short scale measures consistency and perseverance for long-term goals. In the present study, we translated and adapted the Grit--short scale into Hindi (Grit-SH) and examined its within-network and between-network construct validity among Indian adolescents. The participants were 534 senior secondary school students aged 14 - 18 years recruited from five schools across two samples. Grit-SH, along with the brief inventory of thriving and student satisfaction scale, was administered in sample 1 (N[subscript 1]= 310), whereas in sample 2 (N[subscript 2] = 224), the English version of the Grit--short scale was used. Regarding within-network construct validity, the two-dimensional structure of Grit-SH demonstrated an acceptable fit to the data, partially strict invariance against its English version, and good internal consistency reliability. In terms of between-network construct validity, grit demonstrated a significantly positive correlation with student satisfaction and well-being. Overall, findings indicated that the Grit-SH is a valid and reliable measure of grit that researchers and practitioners can use to assess grit among Indian adolescents.

The impact of teachers' beliefs on the implementation and effectiveness of Social and Emotional Learning (SEL) programs underscores the essential need for reliable measures of these beliefs. This study aims to explore and validate the psychometric properties of the Teacher Social and Emotional Learning Beliefs Scale (TSELBS) within the Chinese educational context, utilizing the Partial Credit Model of the Rasch family models. Through the analysis of responses from 893 Chinese teachers, our findings confirm the reliability, validity, and robust psychometric properties of the TSELBS, making it a valuable instrument for assessing educators' SEL beliefs. Additionally, our results indicate that the TSELBS demonstrates fairness across gender, educational levels, and areas. These outcomes emphasize the critical role of culturally sensitive methods in evaluating SEL beliefs and lay a foundational step for future cross-cultural research in this domain. This contribution advances the global conversation on SEL, facilitating further studies on similar validations across diverse cultural settings.

As technology advances, AI, like ChatGPT, has become a pivotal tool in improving educational practices, particularly in special education (SE). These tools support the fourth Sustainable Development Goal (SDG), which concerns quality education for all, and the tenth SDG addresses reducing disparities. The purpose of this study is to explore the ChatGPT's role in achieving Council for Exceptional Children (CEC) standards among preservice special education teachers (SET) and the challenges they confront while using this tool. The study employed a descriptive quantitative approach with purposive sampling. The data were collected through an online questionnaire, and the study sample comprised 166 preservice SETs. The data analysis was conducted using descriptive statistics of means and standard deviations to understand the participants' perceptions comprehensively. The results indicated that the preservice SET assessed ChatGPT as a valuable tool that assisted them in meeting the CEC standards (M=3.39). The highest benefit was observed in achieving CEC Standard 2 (M= 3.87), highlighting meeting individual learning and developmental needs. Additionally, they face moderate challenges (M=2.7), primarily regarding concerns about the validity of generated data and a tendency to over-rely on the tool. These insights posit the vitality of integrating ChatGPT with SE programs while guiding students on its effective use.

Automated writing evaluation feedback (AWE) has become popular in writing classrooms. However, few studies have conducted a comprehensive review of the employment of AWE in learning areas. This study aimed to provide a systematic review of the current research on AWE feedback, including its validity, effects, and students' engagement with AWE feedback. A total of 68 articles were collected from SSCI and A & HCL-indexed journals, which were published from 2008 to 2023. Concerning the validity of automated feedback, some research reported that the accuracy rate of AWE error flagging was inconclusive and students showed more preference for instructor feedback than AWE feedback. Regarding the effects of AWE feedback, most studies supported the positive evidence of AWE feedback on students' writing outcomes. Additionally, some research found less positive and mixed results, highlighting AWE feedback's shortcomings. Most students held positive feelings toward AWE feedback and perceived it as practical under the intervention of students' engagement. This review has made some implications and suggestions for the stakeholders in this field.

This study explores the DT and PjBL to enhance creative, collaborative, and critical writing skills among EFL learners· A post-test-only quasi-experimental design was employed, involving 65 students from an English Education Program, aged 20 to 22, divided into three groups: DT, PjBL, and a integration of both· The instruments used to evaluate creative, collaborative, and critical writing skills were thoroughly validated for reliability, demonstrating good convergent validity and internal consistency· Additionally, Cronbach's alpha confirmed high reliability across all constructs, ensuring an accurate assessment of the participants' writing proficiency· Data analysis was carried out using MANCOVA, with writing literacy as a covariate to control for variability in individual differences· The results indicate that integrating DT and PjBL significantly improves writing performance across all skill categories, with the combined approach yielding better outcomes than the individual application of each approach· This study highlights the effectiveness of integrating DT and PjBL in fostering deeper engagement, critical thinking, and innovation in writing, while preparing students for real-world challenges· These findings suggest that the integrated approach offers a comprehensive framework for improving EFL writing instruction, with the potential for broader implementation in various educational settings.

Comparative Judgement (CJ) is traditionally and primarily used to compare written texts. In this study we explored whether we could extend its use to comparing audio files. We used GCSE Music portfolios which contained a mix of audio recordings, musical scores and text documents. Fifteen judges completed two exercises: one comparing musical compositions and one comparing musical performances. For each exercise, each judge compared 80 pairs of portfolios. Once judges had finished both exercises, they completed a questionnaire about their views and experiences of the method. Here, we present the judges' perceptions of using CJ in this context with reference to the Dimensions of judge decision-making model (Leech & Chambers 2022). We also compare the findings to those from text-based CJ studies.

The study examines the validity of four commonly used early numeracy curriculum-based measurement (EN-CBM) tools in relation to math criterion measures. Additionally, the investigation examines the reporting quality of the included studies as related to important features of assessing CBM's technical adequacy. For inclusion in the meta-analysis, research had to investigate and report on the criterion validity of EN-CBM--oral counting, numeral identification, quantity discrimination, missing number--administered to students in preschool, kindergarten, or Grade 1. Twenty-two studies published between 1997 and 2023 met inclusion criteria, with 272 correlations and 4,130 total participants. A meta-analysis with robust variance estimates for correlated and hierarchical effects was conducted to estimate the average weighted correlations between the four EN-CBM tasks and math outcome measures and to identify potential moderating variables (grade level, CBM type, criterion measure type, correlation lag time). Results indicated the average weighted correlation across all EN-CBM was significantly correlated with criterion measures (r = 0.48; 95% CI [0.430, 0.528]). The average weighted correlation between EN-CBM and criterion measures was significantly smaller for ENCBM oral counting and state test criterion. Results indicated that grade level and administration lag time did not significantly predict relations between EN-CBM and criterion measures. The quality coding results revealed many opportunities for improving information reporting across all indicators (attrition [M = 0.63], EN-CBM reliability [M = 1.48], scoring reliability [M = 1.24], and administrator training [M = 1.60]). Results are discussed in terms of implications for practitioners who administer EN-CBM in school settings.

Despite a tremendous increase in the use of video for conducting research in classrooms as well as preparing and evaluating teachers, there remain notable challenges to using classroom videos at scale, including time and financial costs. Recent advances in artificial intelligence could make the process of analyzing, scoring, and cataloguing videos more efficient. These advances include natural language processing, automated speech recognition, and deep neural networks. To train artificial intelligence to accurately classify activities in classroom videos, humans must first annotate a set of videos in a consistent way. This paper describes our investigation of the degree of inter-annotator reliability regarding identification of and duration of activities among annotators with and without experience analyzing classroom videos. Validity of human annotations is crucial for research involving temporal analysis within classroom video research. The study reported here represents an important step towards applying methods developed in other fields to validate temporal analytics within learning analytics research for classifying time- and event-based activities in classroom videos.

In response to considerable critique of its rigour and relevance, the field of educational research has sought to prove its validity, both in terms of its scientific legitimacy and its relevance to policy and practice. One result of this has been a heightened concern with methodology, to the extent that a form of methodolatry has developed. In conjunction with wider changes in the governance of research, from disciplinary to thematic foci, educational research seems also prone to adisciplinarity. Critiques from philosophy of education of the privileging of gold-standard methodologies point to the empiricism that characterises the field and how this can overlook questions of value and meaning. It is arguably not the empiricism as such that is problematic, but its unmooring from the theoretical and the educational. The possibility of an anthropologically informed educational philosophy is explored as a way out of the impasse.

This study was undertaken to investigate the use and motivations behind teachers' engagement in social networks, while exploring their self-presentations and attitudes within these digital communities. The aim was to shed light on the relationship between real-life and digital communities by focusing on teachers as a specific demographic group. To address the research questions, namely the demographic characteristics of teachers using social networks, the reasons behind teachers' usage of social networks, the role of these platforms in shaping teachers' self-perception and professional identity, a mixed-method approach was employed. The findings of the study indicate that social networks provide an ideal platform for individuals to present themselves, and teachers exhibit distinct patterns of behavior compared to other groups. Teachers express themselves more openly and assertively when their identities are anonymous. They actively seek attention to expand their social network, yet refrain from making political posts to avoid jeopardizing their online presence. They strive to portray an idealized image of themselves and make efforts to distinguish themselves from others. Based on the study's conclusions, it is recommended to develop a digital platform that caters to the interests, needs, and inclinations of teachers.

This study investigates teachers' perspectives on the use of a mathematical argumentation teaching strategy in elementary mathematics in which students disprove mathematical statements they already know to be false. Mathematical argumentation is a process through which students develop an argument about a mathematical concept and rationalize its truth or untruth through mathematical reasoning but is if often underused in mathematics. In this study we focused on a argumentation tasks which involved providing students with number statements which they already knew to be false, and inviting them to argue, using visuals, numeric notation, and/or written explanations, why it was false. Through practical action research, seven teachers from two different schools implemented this approach in their mathematics programs to one hundred and thirty-one students over the course of five months. Findings indicate this approach was easy to implement, improved student engagement, supported learners who struggled and deepened students' mathematical knowledge. We believe that this approach can be used as a precursor to more formal proofs and provide more access for teachers and students in exploring mathematical proofs in elementary classrooms.

This paper presents a study focusing on the feasibility and validity of the SELFIEforTEACHERS self-assessment tool for student teachers, addressing three research questions. Using a mixed methods approach with a convergent parallel design. The study provides insights into quantitative and qualitative aspects of the self-assessment of student teachers' digital competences. Firstly, it is analyzed how student teachers assess their own media-related digital competences using SELFIEforTEACHERS. Secondly, uttered thought processes from student teachers were examined when using the self-assessment tool. Finally, the extent to which SELFIEforTEACHERS is suitable for the self-assessment of digital competences of student teachers was considered. The study was conducted at two German universities offering teacher training programmes to ensure a comprehensive survey of the target group. In the quantitative part, the SELFIEforTEACHERS instrument was used, comprising 32 items reflecting different digital competences based on the DigCompEdu framework. An overall sample of n = 127 student teachers who had completed more than three semesters of their studies was surveyed. Additionally, thoughts about the instrument were collected from the participants using the thinking aloud method (n[subscript think] = 9). The data analysis revealed that, on average, student teachers assign themselves at competence level B1. However, the validity of this assessment raises questions, particularly regarding the assumption of equidistant competence levels and their relevance for student teachers. The qualitative results revealed that student teachers encountered challenges using the self-assessment tool, including problems with the terminology used and the hierarchical structure of the competence levels. The integration of qualitative and quantitative data provided partial validation of the results and enabled a comprehensive discussion of the suitability of SELFIEforTEACHERS for student teachers' selfassessment of digital competences. The study concludes with recommendations for refining the self-assessment tool to better meet the needs of student teachers and increase its validity in the context of teacher education.

Advanced learning technologies have become a focal point in recent educational research, holding the promise of enhancing students' self-regulated learning (SRL) by facilitating various processes of planning, monitoring, performing, and reflecting upon learning experiences. However, concerns have arisen regarding the efficacy and design of technologies, the spectrum of possibilities for SRL support, and too ambiguous claims associated with these technologies. To address these uncertainties and to provide a platform for generating the more empirical evidence, Self-Regulated Learning Support (SRLS) rubric was developed to facilitate the assessment of SRL support in technologyenhanced learning environments. It is grounded in established educational theory and proven empirical research results. This article presents a study that extends the application of the rubric to establish its reliability and validity, filling a gap in prior research. First, content, criterion-related, and construct validation were performed through international and interdisciplinary experts' reviews. Subsequently, interrater and intra-rater reliability were assessed using Intraclass Correlation Coefficients and Cohens Kappa tests. The outcomes of these analysis demonstrated that the SRL-S is a reliable and valid instrument for assessing the levels of SRL support within learning environments. Additional implications for further research to support self-regulated learning are discussed.

Given the rapid adoption of machine learning methods by education researchers, and the growing acknowledgment of their inherent risks, there is an urgent need for tailored methodological guidance on how to improve and evaluate the validity of inferences drawn from these methods. Drawing on an integrative literature review and extending a well-known framework for theorizing validity in the social sciences, this article provides both an overview of threats to validity in supervised machine learning and plausible approaches for addressing such threats. It collates a list of current best practices, brings supervised learning challenges into a unified conceptual framework, and offers a straightforward reference guide on crucial validity considerations. Finally, it proposes a novel research protocol for researchers to use during project planning and for reviewers and scholars to use when evaluating the validity of supervised machine learning applications.

This article presents the first psychometric validation of the Culturally Responsive Assessment of Indigenous Schooling (CRAIS) tool, alongside a call for methodological complexity when engaged in research with and in Indigenous contexts. We examined the 23 culturally responsive schooling (CRS) principles underlying the newly created CRAIS tool in independent samples of curriculum units produced by teachers. Of these, 22 principles loaded into two factors. We further investigated the rationale for all 23 items through a review of the literature and robust discussions about the lived experiences of the authors and the Indigenous teachers with whom we work. We suggest that this both/and approach of quantitative and qualitative analysis results in a richer and more nuanced tool, as compared to what one single method would have rendered. Embracing this methodological complexity allows us to both center Indigenous lived experiences and maintain fidelity to the statistical implications of our work.

Learning a second language is a life-long process requiring acquaintance with a repertoire of language learning strategies (LLS). Despite copious research on LLS and their role in fostering autonomous learning, few studies have examined strategies employed when trying to master specific subsystems of the target language, especially grammar. Meaningful communication in a second language hinges on implicit or highly automatized grammar knowledge, which, given the limitations of classroom-based grammar instruction, must for the most part be developed by learners themselves outside the classroom and this can best be achieved through adept use of grammar learning strategies (GLS). Our knowledge of the GLS, however, is scant, an issue that can be addressed either by designing reliable GLS measurement instruments or revalidating the few existing ones. This study adopts the latter approach by investigating the psychometric properties of Pawlak's (2018) "Grammar Learning Strategy Inventory" (GLSI) in the Chinese context. The tool was administered to 923 English majors, and the responses were subjected to exploratory and confirmatory factor analyses. We found that all seven strategy categories included in the original instrument showed acceptable composite reliability and discriminant validity. The paper concludes by suggesting further revalidation of the GLSI and proposing avenues of research that employ methodological innovations to shed further light on GLS.