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A diagnosis of gender dysphoria remains the primary requirement for transgender people to receive medical and legal gender affirmation services. Three focus groups conducted in 2018 with transgender and gender diverse (TGD) adolescents were assessed to understand how they define and use the term dysphoria and how the clinical discourse of gender dysphoria relates to their sense of self and overall wellness. The 21 participants (age 12-18) were primarily White (n = 19, 90%; Hispanic n = 2, 10%). Thirteen adolescents had a masculine identity, 2 feminine, and 6 genderqueer/nonbinary. TGD youth understood the clinical definition of gender dysphoria but expanded its use; reported stigma as the cause of some of their dysphoria; and used their conceptualization of dysphoria to find self-acceptance. This study highlights the perceived harm and potential limitations of using diagnostic language to define identity. However, through rescripting and self-definition, TGD youth exercise personal agency and reject stigma.

Sex trafficking of minors is a significant problem across North America, with sizeable numbers of youth being directly or indirectly manipulated into being exploited or trafficked. Identification of these youth remains difficult, in part because of a lack of knowledge about common characteristics and in part because of victims' reluctance engaging with and trusting law enforcement enough to disclose their experiences. Given that many youth are trafficked during school-aged years, school settings may represent an ideal location to target prevention and identification efforts, especially by health-related school professionals, whose training, professional duties, and often positive relationships with youth may make the professionals trustworthy disclosure recipients. Whether such professionals are effective, though, depends on their knowledge of who is at risk for trafficking, characteristics that distinguish trafficking from other forms of harm, and effective questioning approaches to elicit disclosures from victimized youth. To document whether this knowledge exists, we surveyed 361 school-based professionals concerning their ability to identify trafficking and knowledge of trafficking, adolescent development, and interviewing youth. Although nearly all (97%) school professionals recognized general student risk in the vignettes, only 18% identified that risk as trafficking. Professionals who had prior experience with trafficked youth were more likely to recognize trafficking than those without such experience. Finally, professionals evidenced some general knowledge about the existence of trafficking, adolescent development, and interviewing, but demonstrated more limited knowledge in the most common characteristics of trafficked minors and nuanced aspects of best-practice questioning approaches. Results highlight important directions for training of school-based professionals to improve prevention and identification of a highly vulnerable and often overlooked population of victims, namely trafficked minors.

In this brief we shift the current academic integrity conversation from "detecting and preventing plagiarism" to "examining how plagiarized contents can be corrected with an objective knowledge of the number of words to modify and properly acknowledged". We proposed a simple, yet useful and powerful mathematical model that is useful for both students, authors, and technology-enabled plagiarism detection firms. We discussed the model, its relevance to students and authors, and firms.

Early warning systems (EWS) using analytical tools that have been trained against prior years' data, can reliably predict dropout risk in individual students so that educators may intervene early to help avert this from happening. Risk profiles for dropouts aren't always useful since students often do not conform to the profiles. Researchers with the Montana Office of Public Instruction developed objective, evidence-based indicators that respond to student context. These indicators show when a student may be at risk and provide signs of when to intervene.

Purpose: Early detection of language delays is essential, as language is key for academic outcomes, well-being, and societal participation. Previous studies have focused on undetected delays in young children. Much less is known about referrals at older ages. In this study, we aimed to (a) establish how many children are referred at toddler age (2-3 years) and how many at lower elementary (4-7 years), upper elementary (8-12 years), and high school (13-16 years) age; (b) evaluate characteristics of the referred children and adolescents across age groups; and (c) assess whether the ensuing classification (no language disorder [LD], developmental LD, LD + additional problems) differed across age groups. Method: We used the 2010-2014 database of the Dutch federation of speech and hearing centers, containing 18,894 cases with target ages. We established the number of referrals in each age group (Q1) and assessed the composition of the age groups in terms of speech, language, behavioral, and cognitive outcomes (Q2), as well as in terms of classification (Q3). To answer Q2 and Q3, we conducted chi-squared analyses with the toddler group as reference group. Results: Late-identified LDs exist: There were new referrals in all age groups. Compared to older age groups, the toddler group contained fewer girls and multilingual children. The toddler group also contained fewer children without an LD and more children with LD + additional problems. Conclusions: Reassuringly, children with multiple language problems are referred earliest. However, late-identified LDs exist, even at high school age. Girls and multilingual children tend to be missed at younger ages. More work on awareness and identification of language delays is needed, requiring awareness, knowledge, and tools for educational professionals.

A psychoeducation program that was originally developed by the Dutch Association for Autism was adjusted for older adults to enhance its feasibility and efficacy in later life. In this study, we explored the effects of this adapted psychoeducation program for older autistic adults in a pre-test -- post-test 6-month follow-up design. A total of 61 patients (55-78 years) and 44 proxies (a person close to them) participated in the study; attrition rate was high for the follow-up assessment. As hypothesized, an increase in knowledge and acceptance of the diagnosis was observed, with a strong and positive correlation between patients and proxies for knowledge. Furthermore, ambiguous results were observed on coping with the diagnosis and no positive effects on psychological distress were found. The feedback of participants and proxies about the psychoeducation program was largely positive. Future research with larger group samples and larger time scales is necessary to gain more insight into the effectiveness of the psychoeducation program. It seems worthwhile to further adjust the program to the needs and requirements of older adults, and to help older autistic adults to construct a new narrative of themselves, and the life they have lived, in the light of the recent autism diagnosis.

Since the learning disability (LD) population comprises the largest group receiving special education services, there is a need for research to examine the self-concept of this population at a global level. This systematic literature review synthesized 20 years of quantitative research (k = 16) about the self-concept of students with LD. The overarching theme was that the diagnosis of LD relies on divergent criteria among the studies reviewed. While the academic self-concept was the center of the research, regardless of its domains, results indicated that students with LD had a lower level of self-concept. To have a deeper understanding of the phenomenon, an instrument specifically designed for assessing self-concept of students with LD is needed. Limitations of the study and implications for research and practice are discussed.

Before adopting a scale for a new culture, researchers should conduct systematic translation procedures and evaluations to ensure its psychometric quality. The Pediatric Symptom Checklist-17 (PSC-17) is a brief and valid scale developed by U.S. researchers to evaluate children's emotional, attentional, and behavioral problems. This study aimed to adapt the PSC-17 to a Chinese version for use in elementary school settings. In this process, 74 teachers rated 666 students using the PSC-17. These students were also assessed using the Strengths and Difficulties Questionnaire (SDQ) and additional questions (e.g., teachers' referral status and demographic information). The scale was successfully translated into simplified Chinese using a standard procedure. Factor analysis supported a general factor model for the PSC-17. Furthermore, decent criterion validity and internal consistency were verified. Finally, a cut-off score of 17 was established, slightly higher than the original cut-off score of 15. We concluded that the PSC-17 is a high-quality screening tool in Chinese elementary schools. The findings are particularly relevant to researchers investigating children's emotional, attentional, and behavioral development within the Chinese cultural context.

The pervasive issue of cheating in educational tests has emerged as a paramount concern within the realm of education, prompting scholars to explore diverse methodologies for identifying potential transgressors. While machine learning models have been extensively investigated for this purpose, the untapped potential of TabNet, an intricate deep neural network model, remains uncharted territory. Within this study, a comprehensive evaluation and comparison of 12 base models (naive Bayes, linear discriminant analysis, Gaussian process, support vector machine, decision tree, random forest, Extreme Gradient Boosting (XGBoost), AdaBoost, logistic regression, k-nearest neighbors, multilayer perceptron, and TabNet) was undertaken to scrutinize their predictive capabilities. The area under the receiver operating characteristic curve (AUC) was employed as the performance metric for evaluation. Impressively, the findings underscored the supremacy of TabNet (AUC = 0.85) over its counterparts, signifying the profound aptitude of deep neural network models in tackling tabular tasks, such as the detection of academic dishonesty. Encouraged by these outcomes, we proceeded to synergistically amalgamate the two most efficacious models, TabNet (AUC = 0.85) and AdaBoost (AUC = 0.81), resulting in the creation of an ensemble model christened TabNet-AdaBoost (AUC = 0.92). The emergence of this novel hybrid approach exhibited considerable potential in research endeavors within this domain. Importantly, our investigation has unveiled fresh insights into the utilization of deep neural network models for the purpose of identifying cheating in educational tests.

Background: Peer assessment has played an important role in large-scale online learning, as it helps promote the effectiveness of learners' online learning. However, with the emergence of numerical grades and textual feedback generated by peers, it is necessary to detect the reliability of the large amount of peer assessment data, and then develop an effective automated grading model to analyse the data and predict learners' learning results. Objectives: The present study aimed to propose an automated grading model with reliability detection. Methods: A total of 109,327 instances of peer assessment from a large-scale teacher online learning program were tested in the experiments. The reliability detection approach included three steps: recurrent convolutional neural networks (RCNN) was used to detect grade consistency, bidirectional encoder representations from transformers (BERT) was used to detect text originality, and long short-term memory (LSTM) was used to detect grade-text consistency. Furthermore, the automated grading was designed with the BERT-RCNN model. Results and Conclusions: The effectiveness of the automated grading model with reliability detection was shown. For reliability detection, RCNN performed best in detecting grade consistency with an accuracy rate of 0.889, BERT performed best in detecting text originality with an improvement of 4.47% compared to the benchmark model, and LSTM performed best with an accuracy rate of 0.883. Moreover, the automated grading model with reliability detection achieved good performance, with an accuracy rate of 0.89. Compared to the absence of reliability detection, it increased by 12.1%. Implications: The results strongly suggest that the automated grading model with reliability detection for large-scale peer assessment is effective, with the following implications: (1) The introduction of reliability detection is necessary to help filter out low reliability data in peer assessment, thus promoting effective automated grading results. (2) This solution could assist assessors in adjusting the exclusion threshold of peer assessment reliability, providing a controllable automated grading tool to reducing manual workload with high quality. (3) This solution could shift educational institutions from labour-intensive grading procedures to a more efficient educational assessment pattern, allowing for more investment in supporting instructors and learners to improve the quality of peer feedback.

Background: In example-based learning, examples are often combined with generative activities, such as comparative self-explanations of example cases. Comparisons induce heavy demands on working memory, especially in complex domains. Hence, only stronger learners may benefit from comparative self-explanations. While static text-based examples can be compared easily, this is challenging for transient video-based modelling examples used in complex domains because simultaneous processing of two videos is not feasible. Objectives: To allow for such comparisons, we combined video-based modelling examples with static representations (i.e., summarizing tables) of the observed optimal and a suboptimal solution of the problem-solving process. A comparative self-explanation prompt asked learners to compare the different solution approaches. Our study investigated the impact of video-based modelling examples versus independent problem-solving on cognitive load and problem-solving skill development. Moreover, we investigated the effects of comparative versus sequential self-explanation prompts, depending on learners' prior knowledge. Methods: In an experiment, 118 automotive apprentices learned a car malfunction diagnosis strategy. Apprentices were divided into three groups: (1) modelling examples with comparative self-explanation prompts, (2) modelling examples with sequential prompts, and (3) no examples or prompts. Diagnostic knowledge and skills were assessed before and after the intervention. Cognitive load was measured retrospectively. Results and conclusions: Despite no observed effects on cognitive load, modelling examples enhanced diagnostic knowledge and diagnostic skills with scaffolds, though not independent diagnostic skills without scaffolds. The need for more practice opportunities to foster independent diagnostic skills is assumed. Additionally, comparative prompts seem promising for learners with higher prior knowledge. Takeaways: Video-based modelling examples were more beneficial for learning than practising to apply the diagnostic strategy. Static representations allow for comparisons of video examples and comparative prompts are promising for learners with higher prior knowledge (cf. expertise-reversal effect). Further research, especially on the effects on cognitive load, is necessary.

Hyper-realistic silicone masks provide a viable route to identity fraud. Over the last decade, more than 40 known criminal acts have been committed by perpetrators using this type of disguise. With the increasing availability and bespoke sophistication of these masks, research must now focus on ways to enhance their detection. In this study, we investigate whether super-recognisers (SRs), people who excel at identity recognition, are more likely to detect this type of fraud, in comparison to typical-recogniser controls. Across three tasks, we examined mask detection rates in the absence of a pre-task prompt (covert task), and again after making participants aware of their use in criminal settings (explicit task). Finally, participants were asked to indicate which aspects of the masks could support their detection (regions of interest task). The findings show an SR advantage for the detection of hyper-realistic masks across the covert and explicit mask detection tasks. In addition, the eye, mouth, and nose regions appear to be particularly indicative of the presence of a mask. The lack of natural skin texture, proportional features, expressiveness, and asymmetry are also salient cues. The theoretical and applied implications of these findings are discussed.

Students' talent and potential cannot be served until they are recognized by schools or caregivers. While the field of gifted education has had success in identifying many students with talents in reading and mathematics, those with spatial talents are often overlooked. This article reviews how we might identify spatial talent using traditional tests as well as observations during planned activities. Identifying spatial talent is an area in need of further research and assessment development.

The problem of propagating disinformation (a.k.a. "fake news") on social media has increased significantly in the last few years. There are several initiatives around the world to combat this serious problem. Maybe the most promising ones involve training people to identify "fake news." The use of digital educational games (DEG) to implement such initiatives has presented significant results. Nevertheless, to the best of our knowledge, most of the existing DEG applied to this purpose are designed for English-written News articles, leaving an important gap for news written in other languages, such as Portuguese, for example. Faced with this scenario, this article presents JEDi, a DEG that trains students to identify "fake news" written in Portuguese. JEDi is a version of the known "Trail Game" where the players must traverse the board by correctly distinguishing real from false news. We raise the hypothesis that as the students play JEDi, they develop the ability to recognize disinformation. It is also important to highlight that JEDi collects detailed data from every match in order to provide longitudinal analyses of each player's performance. This paper reports the application of JEDi in three case studies. While the first study involved 43 students from high school, the second and the third were developed with 29 undergraduate and 33 graduate students, respectively. Quantitative and qualitative results obtained in the three studies point to JEDi's effectiveness as a "fake news" detection training instrument. Mining techniques such as association rule mining were employed in data analysis and revealed frequent information that occurred simultaneously in JEDi's database (e.g. some mined association rules showed that even students who considered themselves experts in identifying "fake news" could improve their skills by playing successive rounds of the game).

Purpose: We investigated and compared the outcomes from two standardized, norm-referenced screening assessments of language (i.e., Clinical Evaluation of Language Fundamentals Preschool--Second Edition [CELFP-2], Diagnostic Evaluation of Language Variation--Screening Test [DELV-ST]) with African American preschoolers whose spoken dialect differed from that of General American English (GAE). We (a) described preschoolers' performance on the CELFP-2 Core Language Index (CLI) and its subtests with consideration of degree of dialect variation (DVAR) observed, (b) investigated how the application of dialect-sensitive scoring modifications to the expressive morphology and syntax Word Structure (WS) subtest affected CELFP-2 CLI scores, and (c) evaluated the screening classification agreement rates between the DELV-ST and the CELFP-2 CLI. Method: African American preschoolers (N = 284) completed the CELFP-2 CLI subtests (i.e., Sentence Structure, WS, Expressive Vocabulary) and the DELV-ST. Density of spoken dialect use was estimated with the DELV-ST Part I Language Variation Status, and percentage of DVAR was calculated. The CELFP-2 WS subtest was scored with and without dialect-sensitive scoring modifications. Results: Planned comparisons of CELFP-2 CLI performance indicated statistically significant differences in performance based on DELV-ST--determined degree of language variation groupings. Scoring modifications applied to the WS subtest increased subtest scaled scores and CLI composite standard scores. However, preschoolers who demonstrated strong variation from GAE continued to demonstrate significantly lower performance than preschoolers who demonstrated little to no language variation. Affected-status agreement rates between assessments (modified and unmodified CELFP-2 CLI scores and DELV-ST Part II Diagnostic Risk Status) were extremely low. Conclusions: The application of dialect-specific scoring modifications to standardized, norm-referenced assessments of language must be simultaneously viewed through the lenses of equity, practicality, and psychometry. The results of our multistage study reiterate the need for reliable methods of identifying risk for developmental language disorder within children who speak American English dialects other than GAE.

Prevalence estimates of autism spectrum disorder (ASD) point to geographic and socioeconomic disparities in identification and diagnosis. Estimating national prevalence rates can limit understanding of local disparities, especially in rural areas where disproportionately higher rates of poverty and decreased healthcare access exist. Using a small area estimation approach from the 2016-2018 National Survey of Children's Health (N = 70,913), we identified geographic differences in ASD prevalence, ranging from 4.38% in the Mid-Atlantic to 2.71% in the West South-Central region. Cluster analyses revealed "hot spots" in parts of the Southeast, East coast, and Northeast. This geographic clustering of prevalence estimates suggests that local or state-level differences in policies, service accessibility, and sociodemographics may play an important role in identification and diagnosis of ASD.County-Level Prevalence Estimates of Autism Spectrum Disorder in Children in the United States.

What are the key challenges facing the field of gifted education? In this qualitative study, we posed this question to some of the field's eminent leaders and scholars. Overwhelmingly, our respondents mentioned problems of diversity, equity, inclusion, and accessibility (DEIA). Respondents also discussed problems concerning identification, the limited use of research-based practices, and insufficient support from outside the field; they also touched upon larger theoretical issues like the lack of clarity surrounding our conceptions of giftedness and the purposes of gifted education. In this article, we trace a brief history of the problems and paradigms of our field, share our study's results, some theoretical and practical connections among the most pressing issues, and implications for moving our field forward.

I discuss White American students' experiences of reading racism-themed young adult literature (YAL), addressing the issue of police brutality, and using the concept of intersectionality to promote social justice awareness. Based on analysis of their written reflections and classroom discussions, I argue reading racism-themed YAL with an intersectionality lens helped White American students complicate their understanding of the struggles and the resistance of youths of color at the present time. I share my instructional strategy for helping White students identify, analyze, and critique the work of power upon American youths.

Reading proficiency is important because it has life-long consequences and influences success in other academic areas. Many students with behavior problems are poor readers and many students with learning disabilities have more behavior problems than their typical peers. We conducted a correlational meta-analysis to examine the association between reading and externalizing behavior in students ages 5-12. We identified 33 studies that reported 88 effect sizes. Using a random-effects linear regression model with robust variance estimation, we found a significant, negative correlation (r= -0.1698, SE = 0.01, p < 0.0001) between reading and externalizing behavior. We tested several moderators related to measurement and sample characteristics. We found that rater type, behavior dimension (e.g., aggression), time between longitudinal measurement points, age of the sample, and percentage male of the sample moderated the relation between reading and behavior. Whether the reading assessment measured comprehension or word reading and socioeconomic status of the sample did not moderate the relation. Understanding the association between reading and externalizing behavior has implications for disability identification and intervention practices for children in elementary school. Future research should examine shared cognitive factors and environmental influences that explain the relation between the constructs.

It could be argued that autistic females, attending high school, have a distinct set of needs when compared to their male counterparts. The purpose of this review is to synthesise reported findings on what could be considered as effective for supporting the needs of autistic females in high school settings. The review adhered to PRISMA guidelines. Searches identified 12 papers that included direct perspectives of autistic females, their families and the professionals supporting them. Data were analysed using thematic synthesis. The findings indicate seven main themes for support related to: mental health; identification of specific needs and post-diagnostic support; friendship interventions and skills development; tiered support; relationships between home and school; transitions between levels of education; self, peer and staff advocacy, and sense of belonging. Social and emotional experiences of autistic females in high school are key areas to target in ensuring successful education. Findings are discussed in relation to integrated, inclusive practices that high schools may adopt to support this cohort of students. Implications for professional practice, policy and research are discussed, which will be of interest to educators and helping professionals alike.

Paganism, despite growing as a religious affiliation over recent decades, has rarely been the subject of study within higher education. Due to the general lack of cohesive organizations, a persistent social stigma, and a number of ill-defined identity labels, they have proven difficult to study even within the general population. This chapter will provide a descriptive snapshot of the population of Pagan college students in the United States and offer guidance for higher education practitioners working with this often-invisible religious demographic group on their campuses.

Purpose: Telemedicine approaches to autism (ASD) assessment have become increasingly common, yet few validated tools exist for this purpose. This study presents results from a clinical trial investigating two approaches to tele-assessment for ASD in toddlers. Methods: 144 children (29% female) between 17 and 36 months of age (mean = 2.5 years, SD = 0.33 years) completed tele-assessment using either the TELE-ASD-PEDS (TAP) or an experimental remote administration of the Screening Tool for Autism in Toddlers (STAT). All children then completed traditional in-person assessment with a blinded clinician, using the Mullen Scales of Early Learning (MSEL), Vineland Adaptive Behavior Scales, 3rd Edition (VABS-3), and Autism Diagnostic Observation Schedule (ADOS-2). Both tele-assessment and in-person assessment included a clinical interview with caregivers. Results: Results indicated diagnostic agreement for 92% of participants. Children diagnosed with ASD following in-person assessment who were missed by tele-assessment (n = 8) had lower scores on tele- and in-person ASD assessment tools. Children inaccurately identified as having ASD by tele-assessment (n = 3) were younger than other children and had higher developmental and adaptive behavior scores than children accurately diagnosed with ASD by tele-assessment. Diagnostic certainty was highest for children correctly identified as having ASD via tele-assessment. Clinicians and caregivers reported satisfaction with tele-assessment procedures. Conclusion: This work provides additional support for the use of tele-assessment for identification of ASD in toddlers, with both clinicians and families reporting broad acceptability. Continued development and refinement of tele-assessment procedures is recommended to optimize this approach for the needs of varying clinicians, families, and circumstances.

We aimed to identify unique constellations of sensory phenotypes for genetic etiologies associated with diagnoses of autism spectrum disorder (ASD) and intellectual disability (ID). Caregivers reported on sensory behaviors via the Sensory Profile for 290 participants (younger than 25 years of age) with ASD and/or ID diagnoses, of which [approximately] 70% have a known pathogenic genetic etiology. Caregivers endorsed poor registration (i.e., high sensory threshold, passive behaviors) for all genetic subgroups relative to an "idiopathic" comparison group with an ASD diagnosis and without a known genetic etiology. Genetic profiles indicated prominent sensory seeking in "ADNP," "CHD8," and "DYRK1A," prominent sensory sensitivities in "SCN2A," and fewer sensation avoidance behaviors in "GRIN2B" (relative to the idiopathic ASD comparison group).

There are many well-developed screening tools for both intellectual disabilities and autism, but they may not be culturally appropriate for use within Africa. Our specific aims were to complete a systematic review to (1) describe and critically appraise short screening tools for the detection of intellectual disabilities and autism for older children and young adults, (2) consider the psychometric properties of these tools, and (3) judge the cultural appropriateness of these tools for use within Africa. Six screening tools for intellectual disabilities and twelve for autism were identified and appraised using the Consensus-based Standards for the Selection of Health Measurement Instruments (COSMIN) guidelines. We identified two screening tools which appeared appropriate for validation for use within African nations.

A Monte Carlo simulation study was conducted to compare fit indices used for detecting the correct latent class in three dichotomous mixture item response theory (IRT) models. Ten indices were considered: Akaike's information criterion (AIC), the corrected AIC (AICc), Bayesian information criterion (BIC), consistent AIC (CAIC), Draper's information criterion (DIC), sample size adjusted BIC (SABIC), relative entropy, the integrated classification likelihood criterion (ICL-BIC), the adjusted Lo-Mendell-Rubin (LMR), and Vuong-Lo-Mendell-Rubin (VLMR). The accuracy of the fit indices was assessed for correct detection of the number of latent classes for different simulation conditions including sample size (2,500 and 5,000), test length (15, 30, and 45), mixture proportions (equal and unequal), number of latent classes (2, 3, and 4), and latent class separation (no-separation and small separation). Simulation study results indicated that as the number of examinees or number of items increased, correct identification rates also increased for most of the indices. Correct identification rates by the different fit indices, however, decreased as the number of estimated latent classes or parameters (i.e., model complexity) increased. Results were good for BIC, CAIC, DIC, SABIC, ICL-BIC, LMR, and VLMR, and the relative entropy index tended to select correct models most of the time. Consistent with previous studies, AIC and AICc showed poor performance. Most of these indices had limited utility for three-class and four-class mixture 3PL model conditions.

Background: This study explores the impact of the pandemic on children's mental health. It examined the understanding of parents regarding their children's mental condition and their ability to identify issues, 2 years post the outbreak of the COVID-19 pandemic. Methods: Using a cross-sectional design, 507 Italian parents reported on their youngest child aged between 2 and 17, totaling 507 children. The outcomes focused on were parental perception of children's mental health deterioration, scores on the Strengths and Difficulties Questionnaire (SDQ) above the clinical cut-off, and parental under-recognition of mental health issues. Descriptive analyses and multivariable logistic regression models were executed (significance at p < 0.05). Results: Parents were 88.1% women (median age 41 years, interquartile range [IQR] = 36-47). Their children were 50.3% female [median age 6 years (IQR = 4-11)]. The data revealed 21.1% of parents perceived a deterioration in their children's mental health, while 44.2% had SDQ scores above the cut-off. Parental under-recognition of mental issues was found in 20.1% of cases. Significant correlations were found between parental perception of deterioration, SDQ scores, and factors like parental mental distress and children's sleep issues. Implications: The findings suggest that schools and verified websites can serve as critical conduits for providing parents with reliable information. By promoting early identification and intervention, such mechanisms can help ensure mental health equity for children. Conclusions: The research highlights the effect of the pandemic on children's mental health and the issue of parental under-recognition. The results underscore the importance of public health initiatives that enhance mental health information accessibility and reliability for parents.

As marginalized graduate students and faculty, we have stories to tell about our experiences within school psychology. Many of these stories center our oppression, trauma, and exclusion but some of them also center our joy and resistance. The purpose of this collaborative autoethnographic project was to create a counterspace in which we, BIWOC faculty and graduate students, could come together to engage in storytelling and build community amongst one another as a way to survive and thrive in academia. As a result of the counterspace, we are able to provide critical feedback and recommendations for school psychology programs to better support marginalized students and faculty. And we also offer critical hope and knowledge to marginalized graduate students and faculty who are currently in the field.

As colleges and universities seek to invigorate ethics education, they need methods to identify where and describe how ethics is already present across their curricula. Meeting this need is complicated by the fact that much ethics education occurs in courses not explicitly focused on ethics or morality. In this paper, we review recent methodological advances before presenting a new Ethics Course Identification Tool (ECIT) that combines application of an expert-derived weighted dictionary and natural language processing methods to identify ethics-related courses based on their titles and course catalog descriptions, even when the terms "ethic" or "moral" are not present. Two studies, the second a pre-registered replication, revealed considerable interrater reliability among experts in ethics education regarding the ethical relevance of courses. Critically, both studies revealed strong correlations between expert judgments and ECIT scores. This empirical evidence points to a shared understanding of ethics education among experts, and it supports the valid use of the ECIT to rapidly and reliably identify ethics-related courses. Based on these findings, we propose that the ECIT can be used both to advance research on trends in ethics education and to help target interventions to improve ethics education at colleges and universities.

Danish schools offering "preparatory basic education and training" (FGU schools) have students that are characterized by having different academic, social, or personal problems. In addition, many FGU students are at high risk of suicidal behavior. Many young people with suicide behavior do not seek help and early identification is important for suicide prevention. Teachers are in a position where it could be relevant to implement a gatekeeper intervention. To ensure successful implementation of an intervention, it is important to establish organizational readiness for change, including its innovation-specific capacity, which are the facilitating requirements in the organization specific to the intervention. We aimed to explore the innovation-specific capacity to implement a gatekeeper intervention at FGU schools in Denmark. This study is based on an online survey completed by teaching staff (n = 251) at FGU schools to explore their overall knowledge about and experience with students' suicidal behavior. Limited knowledge of suicide prevention was found among teaching staff. Most knowledge was from personal experience. There is a need for teaching staff to be educated about suicidal behavior. There is a lack of innovation-specific capacity to implement a gatekeeper intervention.

The main aim of this paper is to assess the level of knowledge, attitude and practice of university teachers regarding plagiarism in Bangladesh. An online questionnaire consisted of 20 knowledge questions, 23 attitude items, and 18 practice questions was created using Google Forms. The link to the questionnaire was sent via email to university teachers. The total correct answers for knowledge and practice questions, and the total attitude score were converted to percentile scores and categorized accordingly as poor (< mean -- 1 SD), average (mean ± 1 SD), and good (> mean + 1 SD). Bivariate analyses were conducted to compare the total knowledge, attitude and practice scores based on demographic and academic variables. Multiple linear regressions were used to identify the association between knowledge, attitude and practice scores, and other covariates. The findings revealed an average level of knowledge, attitude and practice regarding plagiarism among the majority of university teachers. The knowledge, attitude and practice scores were significantly higher for teachers who attended academic writing workshops compared to those who did not attend such events. Demographic and academic variables did not impact knowledge and attitude scores. However, the number of papers published in the last two years and their indexing in Web of Science (WoS) or Scopus significantly impacted attitude and knowledge scores. The multiple regression analyses showed that the practice score was significantly associated with age, highest education, and knowledge.

Bias-based (also called identity-based) harassment refers specifically to a subset of peer victimization that targets a person's identity, such as their gender identity, religion, immigration status, sexual orientation, race, or ethnicity. Research indicates that bias-based harassment is a particularly devastating form of victimization that has an even stronger association with poor mental health and school functioning than general forms of bullying and harassment that do not target identity characteristics. In the current study, we used the AmeriSpeak Teen Panel, a US nationally representative panel of youth ages 13-17, to examine the prevalence and predictors of bias-based harassment. Youth (N = 639) completed a self-report survey about their experiences with victimization and perpetration of bias-based harassment. A series of regression models tested the association of individual youth demographic characteristics with reports of bias-based harassment victimization and perpetration. Overall, 28.2% of youth reported experiences of bias-based victimization, and 12.4% reported bias-based perpetration. Bias-based harassment most often targeted students' race, sexual orientation, and gender identity. Results have implications for school-based prevention and intervention planning to address bias-based harassment.

The purpose of this provincial cross-sectional survey (N = 254) was to explore the mental health literacy (MHL) of educators, and particularly, if training and experience explains differences in MHL. There were meaningful differences based on MHL training and between educators of different division levels. Those who completed graduate degrees or took Learn or Teach MHL training modules clearly had stronger MHL knowledge and abilities to accurately discriminate mental health needs on a vignette measure. Pre-primary educators had the lowest MHL knowledge and ability to discriminate mental health needs on a vignette measure. Our findings evidence current disparities in, as well pathways towards, improving MHL training for pre- and in-service educators, including pre-primary educators. Significant relationships observed between measures of MHL, and vignette discrimination accuracy suggest MHL training for educators may strengthen help-seeking pathways through the timely identification of students experiencing mental disorders and the judicious provision of mental health resources for these students.

Identity matters in science, technology, engineering, mathematics, and medicine (STEMM) because it can affect an individual's long-term sense of belonging, which may in turn affect their persistence in STEMM. Early K-12 science classes often teach students about the foundational discoveries of the field, which have been predominately made, or at least published, by White men. This homogeneity can leave underrepresented individuals in STEMM feeling isolated, and underrepresented K-12 students may feel as though they cannot enter STEMM fields. This study aimed to examine these feelings of inclusivity in STEMM through an interactive workshop that asked middle schoolers to identify scientists from images of individuals with various racial and gender identities. We found that a plurality of students had a positive experience discussing diversity in science and recognizing underrepresented individuals as scientists.

This case asks information systems analysts to assess the cybersecurity posture of a manufacturing company. The exercise works well as a group activity in an information systems course that addresses cybersecurity controls. The case introduces guidance from the National Institute of Standards and Technology, and learners develop work products consistent with the standards. The narrative provides high-level summaries of relevant cybersecurity standards. The case is based on a real company and actual projects, but the company name and specific details have been fictionalized and made more abstract to make this case relevant even when specific technologies evolve. Through this experience, students will learn the importance of a defense-in-depth strategy for securing information systems.

This study focuses on the analysis of school exclusion, which underlies and causes early school leaving, in 20 schools around Porto, Portugal. It is based on the qualitative and documental study of the personal school files of 25 youth, born between 1996 and 2003, who have left school and are now in a situation of social exclusion. We created a characterization grid for these "at-risk" students, and we have picked the following categories for the analysis of their schooling paths: early detection of misalignment processes between students and school; disruptive behaviour and corrective and punitive actions by schools; individual academic paths; main pedagogical recommendations devised by schools; and the articulation mode for these measures leading up to the exclusion from school. The study allows us to understand how these educational practices, through processes marked by humiliation and disqualification, create unteachable students, as well as make them solely accountable--together with their families--for their own academic failure, thus hiding the role of the schools as promoters of silent exclusion.

Homelessness among college students is an increasing concern on campuses across the U.S. Homelessness during college is associated with food insecurity, mental health concerns, and academic challenges including dropped classes, low GRE, and delayed degree completion. Homeless education liaisons--a role often filled by financial aid officers--are tasked with assisting students experiencing homelessness as the students navigate systems of support for basic needs while pursuing their degrees. Little is known about the perspectives or experiences of these professionals in terms of their role as a liaison. Our aim was to inform efforts to support these professionals by gaining an understanding of the knowledge and experiences of liaisons and their professional development preferences and needs. Based on survey data collected from 49 liaisons in four states, we identified gaps in understanding of college student homelessness, such as underestimates of the rate of student homelessness. We pinpointed areas of potential professional development including methods to identify and reach all students at risk for or experiencing homelessness and approaches for collaboration with community partners. We found that liaisons welcomed professional development and preferred online training and peer support as approaches to gain knowledge and skills to fulfill their critical roles. [Note: The publication date (Feb 2022) shown on the PDF is incorrect. The correct publication date for v52 n1 is Mar 2023.]

This research utilizes a unique, validated, multiple-choice exam design that allows researchers to observe and measure the degree to which students copy answers from their peers. Using data collected from the exam, this study investigates whether asking students to sign an honor code at the start of the exam reduced instances of cheating relative to a control group. Empirical results demonstrate that the classroom of students who signed the honor code had less overall copying of answers and also fewer individual students who engaged in cheating. This study contributes to the literature by conducting analysis on a sample that measures actual cheating frequency, as opposed to relying on reported cheating in surveys, and by demonstrating that a positive intervention can effectively discourage unethical behavior.

Screening for autism spectrum disorder (ASD) is an essential early step in the identification process and inaccurate screening may lead to significant delays in the onset of treatment. Past research has highlighted discrepancies in the performance of ASD screening tools such as the Social Communication Questionnaire (SCQ) among certain racial and ethnic groups. The current study explored the functioning of the SCQ among African American/Black and White respondents based on item level performance on the measure. Differential Item Functioning (DIF) analyses showed that 16 (41%) items of the SCQ functioned differently for African American/Black respondents when compared to White respondents. Implications, such as the potential for delayed diagnosis and treatment, and the influence on downstream outcomes, are discussed.

We explored reading comprehension development in children on the spectrum from pre-school to the first (YOS1) and third year of schooling (YOS3). Children were first assessed on meaning-related skills in pre-school. Forty-one children completed follow-up assessments of reading comprehension, reading accuracy, and listening comprehension in YOS1. Nineteen returned for assessments of reading accuracy, reading comprehension, and listening comprehension in YOS3. Children showed poorer reading comprehension than reading accuracy at both timepoints. Reading comprehension, reading accuracy, and listening comprehension were significantly concurrently correlated. Pre-school receptive vocabulary was a significant predictor of YOS3 reading comprehension. Results from this preliminary investigation highlight the potential for early identification of children on the spectrum at risk for reading comprehension difficulties.