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This study aims to examine the potential differences between teacher evaluations and artificial intelligence (AI) tool-based assessment systems in university examinations. The research has evaluated a wide spectrum of exams including numerical and verbal course exams, exams with different assessment styles (project, test exam, traditional exam), and both theoretical and practical course exams. These exams were selected using a criterion sampling method and were analyzed using Bland-Altman Analysis and Intraclass Correlation Coefficient (ICC) analyses to assess how AI and teacher evaluations performed across a broad range. The research findings indicate that while there is a high level of proficiency between the total exam scores assessed by artificial intelligence and teacher evaluations; medium consistency was found in the evaluation of visually based exams, low consistency in video exams, high consistency in test exams, and low consistency in traditional exams. This research is crucial as it helps to identify specific areas where artificial intelligence can either complement or needs improvement in educational assessment, guiding the development of more accurate and fair evaluation tools.

The advent of digital technology has enabled the development of alternative learning methods that enable personalized education to meet the demands of the modern era. Regardless of geographical location and time, online education facilitates the provision of personalized learning opportunities through asynchronous or synchronous recording. Thanks to COVID-19, the rapid adaptation of formal education to digital environments promoted individualization and self-directed learning. The increasing use of design software in architectural education due to digitalization promotes integrating synchronous or asynchronous extracurricular training into the individual learning process. By exploring the diversity of informal online education programs in design software, this study aims to identify the contributions and limitations of informal learning in personalization. Examining the context of a five-day online workshop and a 21-day course can provide new perspectives through a multidisciplinary environment of discussion and practice, even in a short period of time. These programs provide education and training for skilled designers who have their own unique perspectives and techniques on design. Participants' economic situation regarding course fees introduces a competitive medium, which restricts learning accessibility in any scenario. Moreover, excluding these educational programs from transcripts due to imprecise evaluation conditions results in unfairness. With equal access and fair and accurate evaluation mechanisms, informal online education can help professionals develop unique, global, and harmonious perspectives.

Personalized learning, a pedagogical approach tailored to individual needs and capacities, has garnered considerable attention in the era of artificial intelligence (AI) and the fourth industrial revolution. This systematic literature review aims to identify key drivers of personalized learning and critically assess the role of AI in reinforcing these drivers. Following PRISMA guidelines, a thorough search was conducted across major peer-reviewed journal databases, resulting in the inclusion of 102 relevant studies published between 2013 and 2022. A combination of qualitative and quantitative analyses, employing categorization and frequency analysis techniques, was performed to discern patterns and insights from the literature. The findings of this review highlight several critical drivers that contribute to the effectiveness of personalized learning, both from a broad view of education and in the specific context of e-learning. Firstly, recognizing and accounting for individual student characteristics is foundational to tailoring educational experiences. Secondly, personalizing content delivery and instructional methods ensures that learning materials resonate with learners' preferences and aptitudes. Thirdly, customizing assessment and feedback mechanisms enables educators to provide timely and relevant guidance to learners. Additionally, tailoring user interfaces and learning environments fosters engagement and accessibility, catering to diverse learning styles and needs. Moreover, the integration of AI presents significant opportunities to enhance personalized learning. AI-driven solutions offer capabilities such as automated learner profiling, adaptive content recommendation, real-time assessment, and the development of intelligent user interfaces, thereby augmenting the personalization of learning experiences. However, the successful adoption of AI in personalized learning requires addressing various challenges, including the need to develop educators' competencies, refine theoretical frameworks, and navigate ethical considerations surrounding data privacy and bias. By providing a comprehensive understanding of the drivers and implications of AI-driven personalized learning, this review offers valuable insights for educators, researchers, and policymakers in the Education 4.0 era. Leveraging the transformative potential of AI while upholding robust pedagogical principles, personalized learning holds the promise of unlocking tailored educational experiences that maximize individual potential and relevance in the digital economy.

This study draws on the perceptions of students who have completed authentic project-based and work-integrated assessments and explores their perception of authenticity of the assessments in terms of real work projects. In response to industry and government expectations for work-ready graduates three authentic assessments, were developed in collaboration with industry partners, covering different business program subjects. Drawing on the literature, a three-dimensional framework for authentic assessment in workplace learning was developed. These dimensions -- realism, producing an authentic product, and workplace-based judgment criteria -- formed the basis for thematic analysis of students' perceptions. A case study approach was used with three authentic assessment cases. Qualitative data was gathered via focus groups and surveys guided by the three-dimensional framework. Findings suggest that factors such as social environments created by engaging with industry, realistic tasks that replicated industry activities, and working in teams contributed to the perception of an authentic project-based and work-integrated assessment.

Finite complement clauses (FCCs) are an understudied syntactic structure of L2 advanced academic writing. The present study cross-investigated FCCs in qualitative (QUALI) and quantitative (QUANTI) research articles written by Filipino academic writers (FAWs) in Applied Linguistics (APPLING), Communication (COMM), and Measurement and Evaluation (MEEV). Specifically, it determined the FCCs with the most occurrences across five disciplinary research article sub-registers and identified whether these FCCs differ significantly in terms of frequencies of use. With Hernandez's (2021) framework adapted from Biber and Gray's (2016) study, this research analyzed five FCCs in 42 disciplinary research articles. Major results revealed that verb-controlled that-clauses (with 33.69 as normalized frequency count) outnumbered other FCCs in research article sub-registers across disciplines. They were more recurrent in QUALI and QUANTI APPLING research articles (7.91 and 7.54, respectively) and QUANTI and QUALI COMM research articles (7.34 and 6.96, respectively) than in QUANTI MEEV research articles (3.94). In addition, a significant difference exists between them and other FCCs at the p<0.05 level in terms of frequencies of use. In view of these findings, it can be concluded that verb-controlled that-clauses are the most useful FCCs in APPLING, COMM, and MEEV research articles. Likewise, FAWs across the three disciplines write more informally as signposted by their repeated use of that complementizer with these FCCs controlled by verbs. The study draws its implications for academic writing instruction.

An objective structured clinical examination (OSCE) has been recognised as a reliable but workload-intensive assessment method across health sciences studies. Though a variety of digital marking tools have been employed to improve marking and feedback provision for OSCEs, many of these require specialist software or maintenance. This pilot study examines the development and trialling of Microsoft Forms as a marking and feedback instrument for an OSCE within a Sport and Exercise Therapy module. This study aims to assess whether the use of a non-specialist digital tool, such as Microsoft Forms, might be able overcome limitations in current assessment procedures and ultimately provide a more effective method for marking and feedback provision for an OSCE. Results from OSCE examiners (N = 8) and students (N = 30) who participated in the pilot indicate that Microsoft Forms does have the potential to provide a more effective experience for examiners and ultimately improve upon feedback provision for students when compared with a paper-based marking tool. However, concerns around the form's ease-of-use may ultimately influence its adoption as a marking instrument above current paper-based methods.

In November 2022, ChatGPT, an Artificial Intelligence (AI) large language model (LLM) capable of generating human-like responses, was launched. ChatGPT has a variety of promising applications in education, such as using it as thought-partner in generating curricular resources. However, scholars also recognize that the use of ChatGPT raises concerns, such as outputs that are inaccurate, nonsensical, or vague. We, two mathematics teacher educators, engaged in a collaborative self-study using qualitative descriptive approaches to investigate the procedures, concepts, and cognitive demand of ChatGPT-generated mathematical tasks focused on fraction multiplication using the area model approach. We found that the ChatGPT-generated tasks were mostly procedural and not cognitively demanding. Moreover, despite ten variations of input prompts, ChatGPT did not produce any tasks that used the area model approach for fraction multiplication. Rather, it generated tasks focused on procedural approaches. Alarmingly, some tasks were conceptually and/or procedurally inaccurate and vague. We suggest that educators cannot fully rely on ChatGPT to generate cognitively demanding fraction multiplication tasks using the area model. We offer recommendations for educators' strategic use of ChatGPT to generate cognitively demanding mathematical tasks.

Learning analytics (LA) adoption is a challenging task for higher education institutions (HEIs) since it involves different aspects of the academic environment, such as information technology infrastructure, human resource management, ethics, and pedagogical issues. Therefore, it is necessary to provide institutions with supporting instruments to deal with these challenges. Although there has been much research on factors that are associated with the adoption of LA in HEIs, there has been much less research on specific models that can be used to guide actual adoption. In this sense, we developed MMALA, a Maturity Model for Adopting Learning Analytics. It is a guide that describes the necessary practices for taking the first steps in this area and enables institutions to reach higher levels of maturity in LA use, culminating in an organized and systematic adoption. In this paper, we describe the development process of MMALA, focusing on the model evaluation, which used both the questionnaire and the expert opinion method. MMALA can also give institutions an overview of their current situation regarding LA adoption. In this sense, we present the results of the maturity evaluation of three Brazilian HEIs using MMALA.

This paper discusses engineering praxis ethos (EPE), a proposed framework for constructing a STEM learning environment embedding interrelated components of learner experience and design activity, which can support curriculum and instructional design and evaluation in STEM education. The authors propose that STEM is a meta-discipline that relies on the design life cycle, the intellectual root of engineering disciplinary knowledge. The nature of design and design activity calls attention to domain-specific needs of STEM teachers and focuses discussions and critiques about the epistemological adequacy of integrated STEM content knowledge. Given the urgent need for learners to develop 21st century skills in STEM, the authors argue for the feasibility of incorporating both mathematical and simulation models using new technologies when designing experiences for learners. An example of teaching and learning systems thinking in undergraduate engineering education highlights how EPE can be a viable theory of action for STEM educators.

The present study aimed to analyze the views of pre-service teachers, expressed through metaphors, about the adequacy of mentors and teaching practice schools and their recommendations for effective mentoring. A phenomenological design was adopted, and participants included 105 mentees. The current mentors and teaching practice schools had attributes that were not adequate for active mentoring. The mentor should be selected based on criteria such as professional competence, ability to perform mentoring roles, and positive interpersonal relationships. The teaching practice schools should be selected based on human relations, educational activities, the quality of education and instruction, and the physical conditions of the school.

The use of digital media in education has already been addressed in numerous technology acceptance models, but there is very little research on establishing a link between acceptance and assessment using mobile devices, a reality in educational institutions. This work aims to extend research by developing the TAM model and studying teachers' perceived usefulness of mobile devices in terms of how they understand assessment: generically, as a summative and a formative assessment, or as the complementarity of these. This study proposes a comparison between three models using the partial least squares structural equation modeling (PLS-SEM) on a sample of 262 master's degree students (pre-service teachers). The results show the validity of the three proposals and confirm the advantages to specifically consider assessment in acceptance models, as well as the importance of addressing its modalities differently after obtaining better results in the two models that do so. The study also confirms the importance of self-efficacy in the use of mobile devices as a predictor of usefulness and intention to use in the three models. The use of a comparative approach and the development of the perceived usefulness construct in assessment represents a new contribution to the field of acceptance studies.

Studies found that the mastery of Level-4 Science Process Skills (L4SPS) among secondary school students is still relatively weak. Thus, the purpose of this research was to determine the effects of 5E Inquiry-based Learning and Group Investigation (I5E-GI) model on the five constructs of L4SPS, namely Identifying Manipulated, Responding, and Constant Variables, Forming Hypotheses, Making Observations, Making Inferences, and Defining Operationally. A teaching and learning (TL) module was developed to guide teachers in implementing the I5E-GI method for the five L4SPS constructs. The L4SPS Test Instrument was constructed to measure the level of L4SPS mastery at the end of intervention. The quasi-experimental research design was conducted on 180 Form Four students taking Core Science subjects. A total of three groups were assigned, namely i) 5E Inquiry-based Learning and Group Investigation method (I5E-GI, n = 60), ii) 5E Inquiry-based Learning method (5E, n= 60), and iii) Traditional Learning (TR, n = 60) in an urban secondary school in Sarawak, Malaysia. Data were analyzed using the inferential statistical tests of MANOVA, MANCOVA, ANCOVA, and effect size. The results showed that there was a statistically significant effect across the three groups of TL methods. There is a statistically significant effect of the I5E-GI method compared to the 5E and TR methods on the five L4SPS constructs. As for the effect size, the I5E-GI method provides a more significant effect size than the 5E and TR learning methods. Overall, the findings prove that the I5E-GI method has positive implications for the mastery of L4SPS among Form Four students.

This paper reports a mixed-methods study at a public university in Colombia. It describes the classroom assessment practices and challenges of 75 novice foreign language teachers. To gather the quantitative data, the participants completed an online survey. For the qualitative data, 11 key informants participated in one-on-one online interviews. Findings revealed that novice teachers predominantly used summative assessment in the classroom and aligned their assessment instruments to large-scale tests. Moreover, novice teachers faced many challenges with classroom assessment, including determining how to assess their students, developing assessment instruments, and interpreting and using assessment scores to inform teaching and learning. In conclusion, novice teachers need more knowledge, skills, and support to handle daily assessment-related tasks.

Artificial intelligence is a popular technology that affects many fields today. Its impact is noticeable daily, especially in education, design, and other essential areas. This technology, which stands out with the convenience it creates for users and its help in organizing the workflow, will play a critical role in our lives in the future. This study is aimed to touch upon the innovations provided by artificial intelligence in the field of education and some of its basic features. Some software, especially ChatGPT, is included based on the potential of language models and their essential usage areas. In addition, in the study, it is mentioned how artificial intelligence can be evaluated as a material in text and visual form, the essential functions of artificial intelligence technologies, which are rapidly changing today, are explained in this article, and stimulating points about the current situation are mentioned for those who will work in the field.

This paper presents the findings of a qualitative study about the inclusion of arts-based assessment strategies in a 12th grade Israel education classroom. Students were tasked with producing a political cartoon that demonstrated their understandings of contemporary Israeli society. Data was collected from interviews and students' original artwork. The findings revealed that learning through the arts provided students with opportunities to think about and express their feelings about Israel in aesthetically complex and personal ways. The findings also demonstrated the importance of pre-assessment strategies like frequent exposure to the genre of political cartoons and conferencing before submission.

Transnational online education has become an emerging trend in promoting academic collaboration and exchange in higher education during and after the pandemic. Guided by the learning ecology framework, we conducted concurrent mixed methods research by distributing an online survey to Chinese students (N=51) to collect quantitative and qualitative data. This helped us deeply understand their experiences and perceptions of a cross-cultural online learning environment in the United States. We applied multiple regression and thematic analysis to analyze the data. The merging of both types of data analysis indicated the confirmation of the importance of discipline-based English learning environments, the transformation of online learning practices, the insufficiency of student-to-instructor interactions, discordance of technological self-efficacy and the disadvantages of technology-assisted instruction, and discordance between the usefulness and difficulties of learning activities and assessments. We further discussed appropriate strategies and techniques to promote online teaching and learning excellence in transnational distance education.

This research aimed to: 1) investigate the components and performance indicators for organizing experiential activities that foster life skills among early childhood students, particularly those taught by teachers under the Office of the Basic Education Commission of Thailand; 2) examine the current state, desired state, and the needs of supervision models for teachers to develop experiential competency that promotes life skills in early childhood students; and 3) enhance the supervision models for developing experiential competency, specifically focusing on promoting life skills among early childhood students taught by teachers under the Office of the Basic Education Commission of Thailand. The research is divided into 3 phrases. Phase 1: examine the components and indicators, targeting a qualified group of 9 experts selected through purposive sampling. This selection is based on the appropriateness assessment using the components and indicators evaluation form. Phase 2: investigate the needs of the supervision models. The sample group comprises 320 early childhood teachers, selected through multi-stage random sampling using a questionnaire with a 5-level Likert scale. Phase 3: developing the supervision models. Nine qualified experts selected through purposive sampling examined the appropriateness of the supervision models. The data were collected through questionnaires, interviews, assessments, and observations. Average, standard deviation and Priority Needs Index (PNImodified) were used to analyze the data. The findings of the study revealed the following: (1) The components and indicators of life skills serve as standards for teachers in organizing experiences that promote life skills for early childhood students. There are 5 components and 23 indicators, categorized as follows: 1) Decision-making with 5 indicators, 2) Problem-solving with 5 indicators, 3) Analytical thinking with 4 indicators, 4) Empathy with 4 indicators, and 5) Communication with 5 indicators. Overall, the proficiency level is rated as the highest. (2) The current state is rated as the highest, and the desired state is also at a high level. When assessing the needs of the supervision models, it is found that the component with the highest need is Component 3--Analytical Thinking. This is followed by Component 2--Problem-Solving, Component 4--Empathy, Component 1--Decision Making, and Component 5--Communication, with the lowest index of essential needs respectively. (3) The results of enhancing the supervision models for teachers to develop experiential competency that promotes life skills in early childhood students reveal that the supervision models encompasses five formats: 1) Preparation: Planning and development, 2) Strengthen Relationships and Increase Knowledge: Building relationships and expanding knowledge, 3) Knowledge into Practice: Applying knowledge into practice, 4) Reflection: Reflecting on outcomes for understanding, and 5) Evaluation: Quality measurement and assessment. These formats are deemed highly suitable, appropriate, and effective.

Instructor leadership is widely recognized as essential for facilitating meaningful online learning in higher education. While previous studies have applied organizational leadership theories to the study of instructor leadership, fewer studies have investigated online instructor leadership. This predictive correlational study detailed the associations between the Community of Inquiry (CoI) framework and servant leadership (SL) theory and employed multiple regression analyses to investigate the predictive relationships of seven SL dimensions on the three CoI presences. Survey data were gathered from 148 graduate students enrolled in online courses in education, communication, and engineering master's degree programs using the CoI Survey (Arbaugh et al., 2008) and the SL-28 (Liden et al., 2008). The findings revealed a significant positive correlation between the instruments. The predictive model as a whole explained 66% of the variance in students' perceptions of a CoI. Three SL predictor variables demonstrated the most influence: helping subordinates grow and succeed, conceptual skills, and creating value for the community. Additional analyses at the CoI subscale level revealed that the SL variables accounted for 73% of the variance in teaching presence, 55% of the variance in cognitive presence, and 31% of the variance in social presence. Implications and limitations are discussed and recommendations are proposed to implement online instructor SL.

The cybersecurity threat landscape evolves quickly, continually, and consequentially. This means that the "transfer" of cybersecurity learning is crucial. We compared how different recognized "cognitive" transfer theories might help explain and synergize three aspects of cybersecurity education. These include "teaching and training" in diverse settings, "assessing learning" formatively & summatively, and "testing & measuring" achievement, proficiency, & readiness. We excluded newer sociocultural theories and their implications for inclusion as we explore those theories elsewhere. We first summarized the history of cybersecurity education and proficiency standards considering transfer theories. We then explored each theory and reviewed the most relevant cybersecurity education research; in some cases, we broadened our search to computing education. We concluded that (a) archaic "differential" transfer theories are still influential but have negative implications to be avoided, (b) "constructionist" theories are popular in K-12 settings but raise issues for assessment and transfer, (c) many embrace a "general cognitive science perspective" that can resolve tensions between modern "cognitive-associationist" and "cognitive-constructivist" theories that are popular with innovators, and (d) new "perceptual" and "coordinative" theories have potential worth exploring. These insights should support "generative" cybersecurity learning that transfers readily and widely to future classes, tests, and workplaces. These insights should be beneficial when designing and using cyber "ranges" and other hyper-realistic simulations, where transfer assumptions inform costly design decisions and undergird the validity of performance as evidence of proficiency.

The terminology of "Chinese characteristics" (zhongguo tese) is ubiquitous in China's political language, but its precise definition remains elusive. This study focuses specifically on the mobilising of the idea of Chinese characteristics of China's science evaluation programme: the China Discipline Evaluation (CDE). Implemented as an instrument of the higher education reform since 1978, it still plays a vital role in China today. This paper is structured into three parts. It begins by laying out the broad landscape of the science evaluation systems across several countries including China, to distil the distinctiveness of the CDE. Then, it moves to focus on the CDE and locates it in its historical and social-political context. Finally, it investigates the origin and use of Chinese characteristics, suggesting that this terminology functions as a rhetoric modality which describes, labels, and legitimates seemingly self-contradictory phenomena exclusive to China. It also emphasises the idea of Chinese exceptionalism that is touted as irreducible to other cultural forms. Based on these considerations, it proposes three dimensions of the Chinese characteristics of the CDE: (i) the paradoxical status of the evaluation agency, (ii) the co-existence of contradictory values embedded in the objectives and criteria of the evaluation, and (iii) the promotion of the visibility of the idea of China at the international stage. Overall, it shows that while the CDE may appear to be a decentralisation instrument, it is in essence a "hegemonic project" and "hegemonic apparatus" to fulfil the party-state's ambition in securing domestic stability and pursuing international competitiveness.

Background: Stepping Stones Triple P (SSTP) is a complex parent-mediated intervention aimed to reduce behaviours that challenge in children with moderate to severe intellectual disabilities, aged 30-59 months. Methods: To formulate a comprehensive understanding of SSTP implementation in the UK, we conducted a process evaluation collecting stakeholder views and considering intervention fidelity, dose, reach, delivery adaptations, and acceptability. Results: Fidelity and quality of delivery ratings were high. Parents perceived SSTP as valuable, reporting increased parental confidence and understanding of the child's behaviours. However, only 30% of families received an adequate dose of the intervention. Parents who only received treatment as usual described feeling abandoned by current services. Service managers emphasised the importance of availability of resources and therapist training for successful intervention delivery. Conclusions: SSTP supports effective management of early-onset behaviours that challenge. Further work is needed to ensure equitable access to the intervention across health and social care services.

A survey completed by 22 literacy clinic directors indicated that clinics share beliefs and instructional practices. Literacy clinics provide a context in which children are taught to read and write by clinicians who are training to be literacy teachers. As best practices in reading instruction are debated, effective clinical assessment and instructional practices have endured. Using a student-centered approach, literacy clinics help students become engaged, confident, and capable readers. Research results identified four themes: "multiple literacy components, affective factors, a cyclical assessment and instruction process, and clinician and student agency." The article connects these themes and gives examples of the application of the themes for classroom instruction and assessment practices.

Accurate assessment and effective feedback are crucial for cultivating learners' abilities of collaborative problem-solving and critical thinking in online inquiry-based discussions. Based on quantitative content analysis (QCA), there has been a methodological evolvement from descriptive statistics to sequential mining and to network analysis for mining coded discourse data. Epistemic network analysis (ENA) has recently gained increasing recognition for modelling and visualizing the temporal characteristics of online discussions. However, due to methodological restraints, some valuable information regarding online discussion dynamics remains unexplained, including the directionality of connections between theoretical indicators and the trajectory of thinking development. Guided by the community of inquiry (CoI) model, this study extended generic ENA by incorporating directional connections and stanza-based trajectory tracking. By examining the proposed extensions with discussion data of an online learning course, this study first verified that the extensions are comparable with QCA, indicating acceptable assessment validity. Then, the directional ENA revealed that two-way connections between CoI indicators could vary over time and across groups, reflecting different discussion strategies. Furthermore, trajectory tracking effectively detected and visualized the fine-grained progression of thinking. At the end, we summarize several research and practical implications of the ENA extensions for assessing the learning process.

With the introduction and implementation of core literacy, scientific thinking (ST) has become an essential goal and key dimension of science teaching. At present, there is no agreement on how to cultivate students' ST. This study took 238 sixth grade students from a public primary school in urban China as research sample, built a theoretical model of scientific thinking development based on the theory of the Bronfenbrenner' ecological systems theory, and used multiple data to explore and analyze the impact path of ST development of primary school students using the fuzzy sets of qualitative comparative analysis method (fsQCA). The development of urban primary school students' ST is the result of multiple factors at the level of individual drive, family environment, school teaching, and social resources. The result of data analysis showed that the influence path of ST development of urban primary school students driven by multiple factors includes three paths: parent participation leading, scientific practice leading, and home-school-community integration. We have interpreted the influence mechanism of each path in detail and put forward the enlightenment for science education policy and practice.

Classroom research has demonstrated the capacity for significantly influencing student learning by engaging students in evaluation of previously submitted work as an intentional priming exercise for learning; we call this experience "Learning by Evaluating" (LbE). Expanding on current LbE research, we set forth to investigate the impact on student learning by intentionally differing the quality of examples evaluated by the students using adaptive comparative judgement. In this research, university design students (N = 468 students) were randomly assigned to one of three treatment groups; while each group evaluated previously collected student work as an LbE priming activity, the work evaluated by each group differed in quality. Using a three-group experimental design, one group of students only evaluated high quality examples, the second only evaluated low quality examples, and the third group of students evaluated a set of mixed-quality examples of the assignment they were about to work on. Following these LbE priming evaluations, students completed the assigned work and then their projects were evaluated to determine if there was a difference between student performance by treatment condition. Additional qualitative analysis was completed on student LbE rationales to explore similarities and differences in student cognitive judgments based on intervention grouping. No significant difference was found between the groups in terms of achievement, but several differences in group judgement approach were identified and future areas needing investigation were highlighted.

Although there is a plethora of tools available to assess children's movement competence (MC), the literature suggests that many have significant limitations (e.g. not being practical for use in many 'real-world' settings). The FMS[superscript 2] assessment tool has recently been developed as a targeted solution to many of the existing barriers preventing practitioners from utilising MC assessments. The aim of this study was to investigate the structural and convergent validity of this new tool among 8- to 12-year-old Irish primary school children. As part of this study, 102 children (56.8% female, mean = 9.8 years) were assessed using the FMS[superscript 2], the Test of Gross Motor Development (3rd edition) (TGMD-3) (short version) and the Functional Movement Screen™ (FMS™). Structural validity was assessed using confirmatory factor analysis (CFA). The convergent validity between the FMS[superscript 2], the TGMD-3 (short version) and the FMS™ was investigated using the Pearson product-moment correlation coefficient. Results of CFA for the FMS[superscript 2] indicate a good fit model, supporting a three-factor structure (locomotor, object manipulation, and stability). Additional findings indicate a moderate, positive correlation between the FMS[superscript 2] and the TGMD-3 (short version) (r = 0.66), with a low, positive correlation between the FMS[superscript 2] and the FMS™ (r = 0.48). This study presents the first preliminary findings to suggest that the FMS[superscript 2] may be a versatile, time-efficient, and ecologically valid tool to measure children's MC in multiple settings (e.g. research, education, sport, athletic therapy, and physiotherapy). Future research should also seek to continue to implement this solution, consolidate the existing validity findings with a larger and more diverse sample, and further explore the feasibility of the tool in 'real-world' settings.

In England the 2014 Children and Families Act introduced wide ranging changes to the assessment of and provision for children and young people with special educational needs and disabilities (SEND). Guidance underpinning implementation was then published in the Code of Practice. Our study focuses on a key component of that legislation, known as the 'local offer', which requires local authorities to establish and maintain, clear, comprehensive, accessible and up to date information for children and young people with SEND, and their families, about available SEND provision. Local authorities are expected to involve children and young people and their families in co-designing and reviewing their local offer, alongside other key stakeholders, to ensure provision is responsive to local needs and aspirations. To support our assessment of local offers we first established six categories based on the criteria in the Code of Practice about expected availability of SEND-related information (e.g. financial support, health service information, accessibility information). We used these categories to evaluate the relevant local offer websites of all 151 English local authorities with legal responsibilities for SEND assessment and provision. We further assessed whether each local offer website included three common website accessibility functions. Our findings demonstrate variation in the availability of information at local authority level, therefore limiting the ability of some young people and families to make informed decisions about the support available to them. This provides further evidence to support growing concerns about 'postcode lottery' inequities for families and their children with SEND.

Sensory Over-Responsivity (SOR) is an increasingly recognized challenge among children with neurodevelopmental concerns (NDC). To investigate, we characterized the incidence of auditory and tactile over-responsivity (AOR, TOR) among 82 children with NDC. We found that 70% of caregivers reported concern for their child's sensory reactions. Direct assessment further revealed that 54% of the NDC population expressed AOR, TOR, or both -- which persisted regardless of autism spectrum disorder (ASD) diagnosis. These findings support the high prevalence of SOR as well as its lack of specificity to ASD. Additionally, AOR is revealed to be over twice as prevalent as TOR. These conclusions present several avenues for further exploration, including deeper analysis of the neural mechanisms and genetic contributors to sensory processing challenges.

Access to online career information increases the complexity of career decisions (choosing a major or job). When the number of alternatives is large, the first step is to compile a list of promising career alternatives for further exploration, often by using interest inventories (e.g., the Self-Directed Search). But what makes such a list useful? The judgments of 20 career counselors and 103 graduate students supported the hypothesis that higher list quality is associated with a greater similarity between the occupations on the list, fewer occupational fields represented by the occupations on the list, and a list length approximating seven occupations.

This article discusses the knowledge, skills, and mindsets necessary for careers in assessment. The authors outline strategies and techniques to rapidly transition and be successful in assessment roles. Finally, they prepare readers of this work to consider a succession plan for sustained excellence in assessment within their organization.

This systematic review examines the role and efficacy of gamification in leadership education, addressing a significant void in contemporary literature. Recognizing the universally acknowledged significance of leadership in diverse sectors, this study highlights the pervasive challenges in post-secondary leadership curricula, such as unclear objectives, student motivation, lack of access and practical applications. This review dissects gamification's effectiveness, identifies key outcome determinants, and discusses the hurdles to classroom implementation, suggesting potential solutions or interventions by examining 23 peer-reviewed journal articles that are published in various locations and disciplines from 2012-2022. The results cover the roles of digital tools in facilitating gamification, recurring obstacles such as resource limitations, evaluation difficulties, and identifies the challenges in formulating a consensus of an operational definition between scholars. The paper suggests the need for future research focusing on refining gamification's definition, extending its scope, and crafting robust evaluation strategies, thereby catalyzing a transformation in pedagogical practices and should prioritize the development and implementation of robust evaluation strategies for gamified leadership training programs.

The allocation of financial resources in higher education has always been a hot topic of concern in academia and society. The measurement and evaluation of the allocation efficiency of higher education financial resources from the perspective of 'Double first-class' construction is the most important initiative to improve the quality of higher education development and promote the construction of a community with a shared future for mankind. The author constructs a resource allocation efficiency evaluation index system, including two input factors: basic expenditure and project expenditure, and four primary indicators: personnel cultivation, scientific research, international repercussions and social contribution, in addition, ten secondary culture results, results Awarded, education of students abroad, achievement transformation, etc., are considered as output factors. The three-stage Global Super Slacks-Based Measure (SBM) model is applied to accurately measure and scientifically evaluate the allocation efficiency of financial resources in China's higher education. Results show that: first, the true efficiency level can be revealed by eliminating the influence of external environmental factors and random noise. Only 2.82% of universities are located on the effective frontier, indicating that there is significant room for improvement in universities' financial resource allocation capacity and fund utilization efficiency. Second, influenced by factors such as external dependence, R&D intensity, industrial structure and fiscal decentralization, the financial resources allocation efficiency is significantly overestimated, many universities rely heavily on external policy environments for financial resource allocation, and the support from the external environment for efficiency improvement in a few universities still needs to be strengthened. The third, promoting the classification evaluation of universities can meet the needs of 'Double first-class' construction and guarantee the development of university characteristics and diversification. The research shows that first-class universities, comprehensive universities, eastern universities have relatively mature management capabilities, and first-class universities, comprehensive universities and central universities are the most suitable for operation scale; while first-class disciplines, liberal arts universities and western universities have the most significant improvement in the efficiency. Additionally, in view of the research questions and empirical analysis results, this paper also discusses the construction of evaluation index system, the impact of environmental factors and efficiency measurement, classification evaluation, and the effectiveness and promotion of the three-stage Global Super-SBM model, presenting the supporting literature, the uniqueness of this study and the areas for further research. Finally, conclusions are summarized, and suggestions are proposed to provide theoretical guidance and methodological references for dynamic adjustments in the allocation of resources in the new round of 'Double first-class' construction and the strategic planning of higher education resource allocation.

Purpose: Dialogic reading (DR) is an evidence-based method for reading with young children that is associated with improvements in children's oral language skills. There is, however, a lack of consensus on (a) how to train educators to deliver the intervention and (b) methods for assessing implementation fidelity. We designed this study to provide preliminary data about the viability of online video modules as an initial training option within a future tiered training model. Method: We employed a within-subject repeated-measures group design to evaluate educators' (N = 20) implementation of DR after viewing training videos. Educators filmed themselves reading three storybooks with a child "as they would typically" to establish pretest reading behaviors. After being given access to a series of DR training videos, the educators recorded themselves reading three storybooks with the child using DR strategies as a posttest measure. Results: Educators improved their use of individual strategies included in the DR instructional sequence at posttest; however, most participants did not consistently follow the entire instructional sequence as designed. Only one educator delivered the complete DR instructional sequence in > 80% of opportunities at posttest. Conclusion: Modifications to video training modules and additional coaching support may be warranted for many educators to achieve the level of implementation fidelity needed to improve the child's oral language skills from the intervention.

This study explored the nature, prevalence, and developmental profiles of sensory processing disorders among children with autism spectrum disorder (ASD). The participants comprised 119 children with ASD and 30 typically developing children and their parents. The Child Sensory Profile-2 was used to assess the children's sensory processing characteristics. The children with ASD exhibited elevated sensory processing difficulties. Deficits were observed in all the sensory modalities among the children with ASD, except the visual processing modality. Age-related improvements were observed in most sensory processing domains, although non-significant differences were noted in three domains. These findings should enhance understanding of the sensory challenges faced by children with ASD and contribute to the development of individually tailored, targeted, and age-specific therapeutic interventions.

There is a need to investigate the diagnostic utility of autism diagnostic questionnaires in school-age children, who are increasingly being referred for autism assessment. Aside from the standardization sample, little research has been conducted on the Autism Spectrum Rating Scales, particularly regarding teacher reports. This study investigated the criterion validity of the Autism Spectrum Rating Scales-Teacher report for ages 6-18 (ASRS-T[subscript 6-18]) in a well-characterized community sample of 409 children (autism [AUT] n = 122; non-autism [NOT] n = 287; [x-bar]age = 9.91) evaluated with the Autism Diagnostic Observation Schedule-2, a well-validated autism diagnostic measure. Significant mean differences with small to moderate effect sizes (d = 0.28-0.56) were observed for all scores except Self-Regulation, Adult interaction, and Attention. Logistic Regression and Receiver Operating Characteristic analyses conducted for the Summary, ASRS, and two Treatment scales (Peer and Social-Emotional Reciprocity) indicated low ORs (<|1.08|) and AUCs in the poor range ([less than or equal to]0.67). Total and Unusual Behavior emerged as comparatively stronger scales with covariates (age and IQ); other scales were generally similar with/without control variables. Sensitivity and specificity could not be optimized. The suggested 60t-cutpoint had fair or good sensitivity (76.23-83.61) for all examined scales except Unusual Behavior (68.03). However, specificity was poor (46.93-54.36), with high false positive rates (45.64%-63.07%). In complex community samples, the ASRS-T[subscript 6-18]behaves more like a screener as opposed to a diagnostic measure.

How do teachers learn about what learners already know? How do learners aid teachers by providing them with information about their background knowledge and what they find confusing? We formalize this collaborative reasoning process using a hierarchical Bayesian model of pedagogy. We then evaluate this model in two online behavioral experiments (N = 312 adults). In Experiment 1, we show that teachers select examples that account for learners' background knowledge, and adjust their examples based on learners' feedback. In Experiment 2, we show that learners strategically provide more feedback when teachers' examples deviate from their background knowledge. These findings provide a foundation for extending computational accounts of pedagogy to richer interactive settings.

Population-adjusted indirect comparison (PAIC) is an increasingly used technique for estimating the comparative effectiveness of different treatments for the health technology assessments when head-to-head trials are unavailable. Three commonly used PAIC methods include matching-adjusted indirect comparison (MAIC), simulated treatment comparison (STC), and multilevel network meta-regression (ML-NMR). MAIC enables researchers to achieve balanced covariate distribution across two independent trials when individual participant data are only available in one trial. In this article, we provide a comprehensive review of the MAIC methods, including their theoretical derivation, implicit assumptions, and connection to calibration estimation in survey sampling. We discuss the nuances between anchored and unanchored MAIC, as well as their required assumptions. Furthermore, we implement various MAIC methods in a user-friendly R Shiny application Shiny-MAIC. To our knowledge, it is the first Shiny application that implements various MAIC methods. The Shiny-MAIC application offers choice between anchored or unanchored MAIC, choice among different types of covariates and outcomes, and two variance estimators including bootstrap and robust standard errors. An example with simulated data is provided to demonstrate the utility of the Shiny-MAIC application, enabling a user-friendly approach conducting MAIC for healthcare decision-making. The Shiny-MAIC is freely available through the link: https://ziren.shinyapps.io/Shiny_MAIC/.

To meet the diverse needs of school-aged children, school psychologists often must collaborate with other professionals within and outside the school setting. Despite potential benefits, challenges exist related to interprofessional collaboration, including ethical challenges. This article explores some of the most salient ethical dilemmas that school psychologists are likely to face when collaborating with other professionals. Specifically, ethical issues related to competence, multiple relationships, informed consent/assent, privacy/confidentiality, assessment, and therapy are examined. Using vignettes, recommendations for navigating common ethical issues that may arise when engaging in interprofessional collaboration are offered. Suggestions are contextualized within the ethical principles and standards outlined in the American Psychological Association's "Ethical Principles of Psychologists and Code of Conduct" (2017) and the National Association of School Psychologists Professional Standards (2020), which includes the Principles for Professional Ethics.