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Effective integration of technology is critical for online, blended, hybrid, and face-to-face learning. The purpose of this paper is to introduce the SETI (Socio-Ecological Technology Integration) framework and explain what it adds to the scholarly research regarding effective technology integration. The SETI framework goes beyond previous frameworks and applies a holistic systems approach to understanding effective technology integration. This takes into account all aspects of technology integration including new findings uncovered during the COVID-19 lockdown. TPACK and SAMR were analyzed identifying their benefits and limitations and then the SETI framework was explained providing insight into the value of a whole systems approach to technology integration.

Geometry and spatial reasoning form the foundations of learning in mathematics. However, geometry is a subject often ignored by curriculum writers and teachers until high school, leading to students lacking in critical skills in geometric reasoning. As the United States moves into a new curriculum epoch, heralding the commencement of the national common core standards (CCS), one could question if CCS in geometry align with the essential understandings children need to be successful geometric thinkers. This paper begins with an examination of the essential understandings of geometric reasoning leading to an interpretation and critique of the elementary geometry CCS. Finally, the instructional implications are discussed, considering the common core progression through what we know about how children learn geometry.

English is one of the most used languages for jobs, markets, tourism, discourse and international connectivity. However, English learners face many challenges in gaining English language skills. Extant studies show that AI has affordances to support in English language teaching and learning ELT/L. This study answers the call to examine specific challenges and affordances for using AI in ELT/L. A systematic review method was used with PRISMA principles to identify 42 studies. Findings reveal the geographical locations of studies, learner ages and years of study. Grounded coding was then used to identify affordances of the use of AI in ELT/L in the areas of speaking, writing, reading, pedagogy and self-regulation. AI in ELT/L challenges uncovered were technology breakdowns, limited capabilities, fear and standardising language. Policymakers, funders, practitioners and educational leaders can use the information provided in this study to gain a holistic understanding of the current trend in the use of AI in ELT/L, and practical implications are provided to guide future use of AI.

Studies investigating autistic community research priorities indicate a mismatch between what autism research focuses on and what autistic people want to see researched. Furthermore, there has not been a research priority-setting exercise specifically with autistic people in Scotland, where there are unique cultural, political and social contexts. Using a community-based participatory design, we aimed to identify the research priorities of autistic adults living in Scotland. Autistic and non-autistic researchers designed and conducted a survey where 225 autistic adults rated and ranked research topics in order of importance and provided qualitative feedback on issues and questions important to them. The top five research priorities were mental health/well-being, identification and diagnosis of autistic people, support services, knowledge and attitudes towards autistic people and issues impacting autistic women. There were differences in priorities according to different intersections of identity, and qualitative responses indicated a desire for research to focus on support and understanding. The bottom three priorities concerned genetics, treatments and interventions and causes. These findings emphasise the need to address the gap between what autism research focuses on and the everyday lives of autistic people.

Technology has become commonplace in K-12 classrooms with students actively using digital technology to support learning. The purpose of this study was to investigate whether there is empirical support that implementing the ISTE Standards for Students can result in learning gains. A scoping review methodology was used to map extant literature to evidence of learning gains. To ensure transparency in the selection of the articles and the evidence gathering procedure, an a priori method was used. This study is unique in that it provides the first examination of a set of student standards for technology use to learning gains within empirical articles. The findings reveal that there is evidence that all seven of the standards can lead to learning gains. This study is helpful in providing direction and guidance for all, such as educational leaders, teachers, administrators, researchers and policy makers who are looking for a roadmap for effective technology integration that leads to student success.

ChatGPT, an AI chatbot developed by OpenAI, was released in November 2022, sparking a significant surge in global awareness and utilization of generative AI across various domains. Although recent studies have acknowledged the significance of ChatGPT in the education sector, they have yet to focus on exploring faculty attitudes toward ChatGPT. We gathered a comprehensive corpus of tweets containing "#ChatGPT" and "#highered" between November 30th, 2022, and April 30th, 2023. We analyzed data by triangulating VADER, NRC lexicon, and ground coding. Findings suggest that 40% of the expressed sentiments were positive, 51% were neutral, and 9% were negative. The study also revealed the diverse range of emotions held by higher education faculty regarding ChatGPT, with trust and joy being the most prevalent positive sentiments and fear and anger being the most prevalent negative sentiments. This study shed light on faculty members' perceptions of ChatGPT, contributing to a better understanding of the impact, emotions, and incorporation of ChatGPT in the higher education sector.

While ChatGPT has recently become very popular, AI has a long history and philosophy. This paper intends to explore the promises and pitfalls of the Generative Pre-trained Transformer (GPT) AI and potentially future technologies by adopting a speculative methodology. Speculative future narratives with a specific focus on educational contexts are provided in an attempt to identify emerging themes and discuss their implications for education in the 21st century. Affordances of (using) AI in Education (AIEd) and possible adverse effects are identified and discussed which emerge from the narratives. It is argued that now is the best of times to define human vs AI contribution to education because AI can accomplish more and more educational activities that used to be the prerogative of human educators. Therefore, it is imperative to rethink the respective roles of technology and human educators in education with a future-oriented mindset.

Abstract Malaria is a major public health problem, but many of the factors underlying the pathogenesis of this disease are not well understood, including protection from the development of febrile symptoms, which is observed in individuals residing in areas with moderate-to-high transmission by early adolescence. Here, we demonstrate that susceptibility to febrile malaria following Plasmodium falciparum infection is associated with the composition of the gut microbiome prior to the malaria season in 10-year-old Malian children, but not in younger children. Gnotobiotic mice colonized with the fecal samples of malaria-susceptible children were shown to have a significantly higher parasite burden following Plasmodium infection compared to gnotobiotic mice colonized with the fecal samples of malaria-resistant children. The fecal microbiome of the susceptible children was determined to be enriched for bacteria associated with inflammation, mucin degradation and gut permeability, and to have increased levels of nitric oxide-derived DNA adducts and lower levels of mucus phospholipids compared to the resistant children. Overall, these results indicate that the composition of the gut microbiome is associated with the prospective risk of febrile malaria in Malian children and suggest that modulation of the gut microbiome could decrease malaria morbidity in endemic areas.

Abstract Persistence of malaria parasites in asymptomatic hosts is crucial in areas of seasonally-interrupted transmission, where P. falciparum bridges wet seasons months apart. During the dry season, infected erythrocytes exhibit extended circulation with reduced cytoadherence, increasing the risk of splenic clearance of infected cells and hindering parasitaemia increase. However, what determines parasite persistence for long periods of time remains unknown. Here, we investigated whether seasonality affects plasma composition so that P. falciparum can detect and adjust to changing serological cues; or if alternatively, parasite infection length dictates clinical presentation and persistency. Data from Malian children exposed to alternating ~6-month wet and dry seasons show that plasma composition is unrelated to time of year in non-infected children, and that carrying P. falciparum only minimally affects plasma constitution in asymptomatic hosts. Parasites persisting in the blood of asymptomatic children from the dry into the ensuing wet season rarely if ever appeared to cause malaria in their hosts as seasons changed. In vitro culture in the presence of plasma collected in the dry or the wet seasons did not affect parasite development, replication or host-cell remodelling. The absence of a parasite-encoded sensing mechanism was further supported by the observation of similar features in P. falciparum persisting asymptomatically in the dry season and parasites in age- and sex-matched asymptomatic children in the wet season. Conversely, we show that P. falciparum clones transmitted early in the wet season had lower chance of surviving until the end of the following dry season, contrasting with a higher likelihood of survival of clones transmitted towards the end of the wet season, allowing for the re-initiation of transmission. We propose that the decreased virulence observed in persisting parasites during the dry season is not due to the parasites sensing ability, nor is it linked to a decreased capacity for parasite replication but rather a consequence decreased cytoadhesion associated with infection length.

ABSTRACT: Automated measurements of the ratio of concentrations of methane and carbon dioxide, [CH4]:[CO2], in breath from individual animals (the so-called “sniffer technique”) and estimated CO2 production can be used to estimate CH4 production, provided that CO2 production can be reliably calculated. This would allow CH4 production from individual cows to be estimated in large cohorts of cows, whereby ranking of cows according to their CH4 production might become possible and their values could be used for breeding of low CH4-emitting animals. Estimates of CO2 production are typically based on predictions of heat production, which can be calculated from body weight (BW), energy-corrected milk yield, and days of pregnancy. The objectives of the present study were to develop predictions of CO2 production directly from milk production, dietary, and animal variables, and furthermore to develop different models to be used for different scenarios, depending on available data. An international dataset with 2,244 records from individual lactating cows including CO2 production and associated traits, as dry matter intake (DMI), diet composition, BW, milk production and composition, days in milk, and days pregnant, was compiled to constitute the training dataset. Research location and experiment nested within research location were included as random intercepts. The method of CO2 production measurement (respiration chamber [RC] or GreenFeed [GF]) was confounded with research location, and therefore excluded from the model. In total, 3 models were developed based on the current training dataset: model 1 (“best model”), where all significant traits were included; model 2 (“on-farm model”), where DMI was excluded; and model 3 (“reduced on-farm model”), where both DMI and BW were excluded. Evaluation on test dat sets with either RC data (n = 103), GF data without additives (n = 478), or GF data only including observations where nitrate, 3-nitrooxypropanol (3-NOP), or a combination of nitrate and 3-NOP were fed to the cows (GF+: n = 295), showed good precision of the 3 models, illustrated by low slope bias both in absolute values (−0.22 to 0.097) and in percentage (0.049 to 4.89) of mean square error (MSE). However, the mean bias (MB) indicated systematic overprediction and underprediction of CO2 production when the models were evaluated on the GF and the RC test datasets, respectively. To address this bias, the 3 models were evaluated on a modified test dataset, where the CO2 production (g/d) was adjusted by subtracting (where measurements were obtained by RC) or adding absolute MB (where measurements were obtained by GF) from evaluation of the specific model on RC, GF, and GF+ test datasets. With this modification, the absolute values of MB and MB as percentage of MSE became negligible. In conclusion, the 3 models were precise in predicting CO2 production from lactating dairy cows.

Artificial Intelligence in Education (AIEd) has experienced a rapid rise in the past decade. This systematic review is the first examining the use of AIEd in K-12 including 169 extant studies from 2011 to 2021. This study provides contextual information from the research, such as the educational disciplines, educational levels, research purposes, methodologies, year published and who the AI was intended to support. The grounded coding revealed affordances fit into three main themes of AIEd connecting to pedagogies (e.g., gaming, personalization), administration (e.g., diagnostic tools), and subject content. Challenges in AIEd K-12 included issues toward negative perceptions, lack of student and teacher technology skills, ethical concerns, and issues directly with the ease of use and design of the AI tools.

Purpose: This systematic review paper aims to examine extant empirical research involving educational technology during COVID-19 to provide an aggregated analysis of how the pandemic has influenced educational technology research. Design/methodology/approach: Using a Preferred Reporting Items for Systematic Reviews and Meta-Analysis systematic review and an integrative review methodology, 50 primary research studies were selected from ten top-ranked educational research journals. These studies were reviewed regarding research purposes, methodologies, instruments, educational level, geographical distribution, and findings of the studies. Findings: The findings reveal four emerging themes--influencing factors, effectiveness, challenges and teachers. The majority of the studies focused on higher education. Quantitative research design based on a questionnaire was the most adopted method of investigation by researchers. Research limitations/implications: Search parameters focused on the top 10 journals in the field of educational technology. Although this provides a level of quality, it narrowed the search. Practical implications: For practitioners and researchers, this study provides a summary of the field to better understand what knowledge we have gained on the use of educational technology to enable a more agile, knowledgeable response to education in future emergencies. Originality/value: This systematic review is unique in examining how the pandemic has influenced educational technology research. It also provides insight into gaps in the research that future researchers can use as a springboard to enable a more knowledge and a more agile approach to future emergencies.

The implementation of virtual reality (VR) has gained popularity in the organizational settings in responding to the digital transformation in the era of Industry 4.0. VR offers immersive and authentic experiences for learners through simulated real-life scenarios during training. While the affordances have been widely discussed, there is a need to take a systems thinking approach and look at the challenges and side effects associated with the implementation. This systematic review is an effort to comprehensively understand the challenges and side effects along with the exploration of contexts, affordances, and attitudes toward VR applications of the VR initiative for training in organizational contexts. Following a ground theory approach, we analyzed 50 articles published since 2011 that covered a wide range of industries and locations worldwide. The findings from our analysis revealed multiple affordances, challenges, and side effects of applying VR in training. We hope to promote a discussion on VR integration, especially to caution researchers and practitioners the challenges and side effects of this initiative in the design and implementation process, to derive maximum value of the immersive technologies in learning. The results contribute to a comprehensive understanding of applying VR in organizational settings and informs design considerations for successful VR implementation in training programs.

ChatGPT was released to the public in November 30, 2022. This study examines how ChatGPT can be used by educators and students to promote learning and what are the challenges and limitations. This study is unique in providing one of the first systematic reviews using peer review studies to provide an early examination of the field. Using PRISMA principles, 44 articles were selected for review. Grounded coding was then used to reveal trends in the data. The findings show that educators can use ChatGPT for teaching support, task automation, and professional development. These were further delineated further by axial sub codes. Eight student uses were 24/7 support, explain difficult concepts, conversational partner, personalized feedback and materials, provide writing support, offer self-assessment, facilitate engagement, and self-determination. In addition to be affordances of the AI, the data from the articles also showed limitations to ChatGPT and misuses, specifically, inaccuracies and hallucinations, potential bias, and tool limitations. Misuses are plagiarism and cheating, privacy issues and spread of false information. This study is a springboard for researchers, practitioners, policy makers and funders in understanding the emerging state of the field of ChatGPT.

As online learners are increasingly diverse, making online learning more inclusive becomes an urgent need. Universal design has been perceived as a viable framework to reach the widest possible range of learners. However, applying universal design to online education has been a challenge to instructors due to different barriers. It is also unclear what evidence-based strategies can be infused into online education. In this systematic review, we selected and analyzed relevant studies and synthesized their designs and findings to explore the trends, strategies, impacts, challenges, and instructors' and students' attitudes toward applying universal design in online environments. We discuss implications for research and practice.

Those experiencing high rapport or strong social connection are more likely to copy each other, or emulate each other's ideas, either consciously or sub-consciously. In this study, we use this phenomenon to examine whether neurotype match or mismatch impacts degree of imitation in a creative task. We asked 71 participants in neurodiverse pairs (including both autistic and non-autistic participants) and single-neurotype pairs (both autistic or both non-autistic), where one participant builds and one observes, to build the tallest possible tower from dried spaghetti and plasticine. We measured the height of each tower and photographed them to create a stimulus set. We then asked independent raters (n = 351, 62 autistic) to rate towers for degree of similarity. We hypothesised that lower similarity scores would be generated for towers created by people in neurodiverse pairs, showing positive innovation. Results showed towers built in the neurodiverse condition had least similarity, whereas towers built in the autistic and non-autistic conditions were significantly more similar. There was no difference in performance (height of tower) based on condition. Our results are the first to examine creativity within single-neurotype and neurodiverse pairs; they indicate that neurological diversity may be beneficial within a group setting. Subsequent research is required to examine how this interacts with divergent communication styles.

Technology has shaped people's lifestyles globally. Today, the majority of the world's population seeks help through technology as a portal to learning with the wide variety of learning materials available. Women in both developed and developing countries can access learning through technology, yet the scholarly community do not have an up-to-date collective view of how technology is being used to provide learning materials to empower women around the world. Therefore, this systematic review included an aggregated and qualitative synthesis to investigate extant empirical work over five years, 2017-2021. Following a rigorous PRISMA selection process, 40 articles were included in the final analysis from 80 countries. The findings reveal that the majority (60%) of studies took place in Sub-Saharan Africa. From the grounded coding, five industries emerged as areas providing empowerment through the learning materials: health, agriculture, environment, entrepreneurship, and communication. Women were empowered by learning in three main areas: health, communication, and entrepreneurship. This study provides information for funders, policymakers, advocates, and women. This study revealed areas in need of future research, including additional systematic reviews to explore gray literature not published in scholarly outlets and academic publications published in non-English language journals.

Abstract Deep brain stimulation (DBS) of the subthalamic nucleus (STN) produces an electrophysiological signature called evoked resonant neural activity (ERNA); a high-frequency oscillation that has been linked to treatment efficacy. However, the single-neuron and synaptic bases of ERNA are unsubstantiated. This study proposes that ERNA is a subcortical neuronal circuit signature of DBS-mediated engagement of the basal ganglia indirect pathway network. In people with Parkinson’s disease, we: (i) showed that each peak of the ERNA waveform is associated with temporally-locked neuronal inhibition in the STN; (ii) characterized the temporal dynamics of ERNA; (iii) identified a putative mesocircuit architecture, embedded with empirically-derived synaptic dynamics, that is necessary for the emergence of ERNA in silico; (iv) localized ERNA to the dorsal STN in electrophysiological and normative anatomical space; (v) used patient-wise hotspot locations to assess spatial relevance of ERNA with respect to DBS outcome; and (vi) characterized the local fiber activation profile associated with the derived group-level ERNA hotspot.

Abstract Wilms tumor (WT) is the most common renal malignancy of childhood. Despite improvements in the overall survival, relapse occurs in ~15% of patients with favorable histology WT (FHWT). Half of these patients will succumb to their disease. Identifying novel targeted therapies remains challenging in part due to the lack of faithful preclinical in vitro models. Here we establish twelve patient-derived WT cell lines and demonstrate that these models faithfully recapitulate WT biology using genomic and transcriptomic techniques. We then perform loss-of-function screens to identify the nuclear export gene, XPO1, as a vulnerability. We find that the FDA approved XPO1 inhibitor, KPT-330, suppresses TRIP13 expression, which is required for survival. We further identify synergy between KPT-330 and doxorubicin, a chemotherapy used in high-risk FHWT. Taken together, we identify XPO1 inhibition with KPT-330 as a potential therapeutic option to treat FHWTs and in combination with doxorubicin, leads to durable remissions in vivo.

IntroductionDans le cadre de l’approche en santé publique en matière de protection de l’enfance, il est essentiel de recueillir des données sur les enfants placés hors de leur foyer familial afin d’évaluer les tendances à l’échelle de la population, de comprendre les facteurs à l’origine des inégalités sociales et de santé et d’analyser les conséquences pour les enfants et les familles. Nous avons analysé des données administratives provenant de l’ensemble du Canada pour décrire la population des enfants placés hors de leur foyer familial, estimer et comparer les taux de placement hors du foyer familial par province ou territoire, année, sexe ou genre, groupe d’âge et type de placement. MéthodologieNous avons effectué une analyse transversale des données basées sur des dénombrements ponctuels dans toutes les provinces et tous les territoires pour la période 2013-2014 à 2021-2022. Nous avons utilisé des fréquences et des pourcentages pour décrire la population d’enfants (et de jeunes jusqu’à 21 ans) placés hors de leur foyer familial et nous avons estimé les taux globaux et les ratios de taux. RésultatsNous estimons qu’au Canada, 61 104 enfants étaient placés hors de leur foyer familial au 31 mars 2022. Le taux national de placement des enfants hors de leur foyer familial était de 8,24 enfants pour 1 000. Les variations de taux par province et territoire étaient importantes et ont changé au fil du temps. Les taux les plus élevés ont été relevés chez les garçons ainsi que chez les enfants de 1 à 3 ans et chez les jeunes de 16 et 17 ans. Si les familles d’accueil sont restées le type de placement le plus courant, le placement dans la parenté a représenté une part croissante des placements. ConclusionCette analyse a montré que les données administratives sont utilisables pour produire des indicateurs nationaux sur les enfants encadrés par le système de protection de l’enfance au Canada. Ces données sont utilisables aussi pour mesurer les progrès en matière d’équité sociale et de santé pour les enfants et les jeunes du Canada.

IntroductionAs a part of the public health approach to child welfare, data about children placed in out-of-home care are needed to assess population trends, understand drivers of social and health inequities, and examine outcomes for children and families. We analyzed administrative data from Canada to describe the population of children in out-of-home care, and estimate and compare rates of out-of-home care by province/territory, year, sex/gender, age group and placement type. MethodsWe conducted a cross-sectional analysis of point-in-time data from all provinces and territories for the period 2013/2014 to 2021/2022. We used frequencies and percentages to describe the population of children (and youth up to age 21 years) in out-of-home care and estimated overall and stratified rates and rate ratios. ResultsAn estimated 61 104 children in Canada were in out-of-home care on 31 March 2022. The national rate of out-of-home care was 8.24 children per 1000 population. Rate variations by province/territory were substantial and changed over time. Rates were highest among males and children aged 1 to 3 and 16 to 17 years. Foster homes were the most common type of placement, although kinship homes accounted for an increasing share. ConclusionThis analysis demonstrated that administrative data can be used to generate national indicators about children involved in the child welfare system. These data can be used for tracking progress towards health and social equity for children and youth in Canada.

Rabies is a contagious viral disease that can be easily transmitted by the saliva and brain/nervous system tissues of the infected animals, causing severe and fatal encephalitis in both animals and humans. Vaccination campaigns are crucial to combat and prevent rabies's spread in dogs and humans. The Modified Fuenzalida & Palicios vaccines have been widely used since the 70s and have proven effective in producing a solid serological response. Since 2008, the Brazilian Ministry of Health has introduced a Cell Culture Rabies Vaccine (CCRV) for all dog mass vaccination campaigns in Brazil. However, to date, there is limited evidence on the immunologic response of dogs to this type of vaccine in field conditions. The present study evaluated the serological response in dogs vaccinated with CCRV from blood samples of 724 dogs using the Simplified Fluorescence Inhibition Microtest – SFIMT. Dogs with a titer equal to 0.5 IU/mL or above were considered seropositive. The results revealed that 59.12% (428/724) of all dogs tested and 48.49% (32/66) of primo-vaccinated animals were seropositive. The percentage of seronegative animals was higher than seropositive for animals that received a single dose during their life (p

This study investigates the link between household welfare and solar electricity demand in sub-Saharan Africa for the period between 2010 and 2019. Welfare was proxied by HDI, inequality in income, infant mortality, education, mobile phone subscriptions, internet users and unemployment rate. The study employed a Quantile regression with nonadditive fixed effects and the adaptive Markov Chain Monte Carlo optimisation method. The findings show that HDI has a negative and significant effect on solar electricity consumption at all quantiles except for the 30th quantile where the effect is positive. This implies that as welfare improves, consumers’ demand for solar electricity declines due to a shift to other fuels or stacking of multiple fuels. Moreover, the findings show varying effects of inequality in income, education, mobile phone subscriptions, internet connectivity and unemployment rate on solar electricity demand at different quantiles. Lastly, the findings reveal that infant mortality has a negative effect on solar electricity demand across all quantiles. In overall, the findings imply that policy makers should develop strategies that will promote and incentivise solar electricity consumption across all income groups.

Mobile learning has become the potential for innovation and disruption in the last decade. This study reviewed Chinese scholarly publications related to mobile learning research and published related to teaching and learning English in China's higher education. Its purpose is to enrich systematic reviews for digital education with the provision of mobile learning research in China's context with academic findings inaccessible to those who do not speak Chinese. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) principles are used to provide a transparent synthesis of extant studies. Major findings include that English learning has made progress in teaching strategy, pedagogical practice, and teaching model related to mobile technology, but a concern emerges in how teachers integrate technology into pedagogy appropriately to achieve the outcome beyond traditional teaching. The findings suggest further studies to analyse teachers' needs in disruptive education in China.