The School of Education at the University of Cape Town (UCT) investigated children’s learning through digital play. The aim of the study was to explore the intersection between child play, technology, creativity and learning among children aged between 3 and 11 years. The study also identified skills and dispositions children develop through both digital and non-digital play. The data shared emerged from a survey of parents of children in the stated age group, with particular reference to the parents views on children's play practices, including time parents spent playing with their children, concerns parents had on time children spend playing on various technologies, types of play children in South Africa engaged in and the concerns of parents when children played with some electronic devices. The following data files are shared:SA - Survey - Children, Technology and Play (CTAP) - Google Forms.pdfDescriptive Stats 2020.1.9 -Children Technology and Play SURVEY.xlsxParent Survey RAW PUBLIC DATA 2020.2.29 - Children Technology and Play Project.xlsxParent Survey RAW PUBLIC DATA 2020.2.29 - Children Technology and Play Project.csvParent Survey REPORT DATA 2020.2.29 - Children Technology and Play Project.xlsxParent Survey REPORT DATA 2020.2.29 - Children Technology and Play Project.csvParent Survey RAW and REPORT DATA SYNTAX 2020.2.29 - Children Technology and Play Project.spsNOTE: This survey was adapted from Marsh, J. Stjerne Thomsen, B., Parry, B., Scott, F. Bishop, J.C., Bannister, C., Driscoll, A., Margary, T., Woodgate, A., (2019) Children, Technology and Play. UK Survey Questions. LEGO Foundation.

Capturing variability in use of commercial technologies by children with autism can inform future learning and support technology design. Survey data were collected from parents (n = 388) in the UK, Spain, and Belgium, and includes information about individuals with a range of ages and ability levels. We found a comparable pattern of access and usage across age groups, though higher reading and language ability was linked to use of more devices and interfaces. Reported worries about technology correlated with longer time spent using technology. Autistic people use mainstream technologies for a broad range of recreational uses. The data suggest that technologies developed with therapeutic goals in mind may need to achieve a high standard of design to engage users.

The UK Survey Data forms part of Children, Technology and Play (2019-2020), an 8-month co-produced study by academics from the University of Sheffield and University of Cape Town, South Africa, the LEGO Foundation and Dubit.

The study explored the contemporary play environments of children to identify the ways in which their play is shaped by technology, examine the relationship between digital play, learning and creativity, and explore the role of adults in mediating digital play.

As part of the UK research, an online survey was conducted by Dubit of 2,429 families with children aged 3-11 years across the UK. This dataset comprises analysis of the statistical data from the survey. The analysis was carried out using SPSS (Statistical Package for the Social Sciences) version 26. The analysis involved the creation of tables using either customised tables by direct coding (CTABLES) or by using the CROSSTABS procedure which produced the chi-squared statistics which determined any statistical significance in relation to age/gender/social class/ethnicity.

The project received ethical approval from the University of Sheffield (no. 028701).

The research tools, including the survey questions, and other datasets from the study are deposited elsewhere in ORDA and have been brought together in the Children, Technology and Play collection.

DOI Abstract copyright UK Data Service and data collection copyright owner.The Kids' Life and Times Survey (KLT) began in 2008 and is conducted by Access Research Knowledge (ARK) which runs the Northern Ireland Life and Times Survey (NILT) and the Young Life and Times Survey (YLT). The KLT is a survey of Primary year 7 (P7) children in Northern Ireland which is carried out online and in school. (Note that NILT did not run in 2011, but resumed in 2012. The KLT and YLT both ran as normal in 2011.) The aims of the KLT are to:provide broad-based monitoring systems to examine children's views on policy issues on a regular basisensure that the information from the survey is fed back to policymakers and others engaged in the policy debates around children and their livesprovide a high profile endorsement of 'participation' by Northern Ireland's childrenFurther information about KLT, including the comic-style publication with key results especially designed for children, may be found on the ARK main Kids' Life and Times Survey web pages. Main Topics: In 2013, the following topics were included in the survey: background; bullying in school; parental involvement with education, childcare and nutrition (funded by Save the Children); use of technology (funded by Office of the First Minister and Deputy First Minister); children's rights (funded by Improving Children's Lives). No sampling (total universe) Self-completion Online survey

Abstract copyright UK Data Service and data collection copyright owner. The project aimed to enhance the knowledge base regarding children’s and parents’ experiences and practices of risk and safety in their use of the internet and new online technologies in Europe. The goal was to inform the promotion of a safer online environment for children. A comparable quantitative survey of children’s use of online technologies across European member states, matched with a survey of their parents’ experiences regarding their children’s internet use, was designed and conducted. The questionnaire design built on knowledge generated by the EU Kids Online network, on findings from comparable surveys of children and parents conducted elsewhere, and on the recommendations of the Safer Internet Forum 2007. Specific objectives were: (1) to design a thorough and robust survey instrument appropriate for identifying the nature of children’s access, use, risk, coping and safety awareness; (2) to design a thorough and robust survey instrument appropriate for identifying the nature of parental experiences, practices and concerns regarding their children’s internet use; (3) to administer the survey in a reliable and ethically-sensitive manner to national samples of internet users aged 9-16, and their parents, in member states; (4) to analyse the results systematically so as to identify both core findings and more complex patterns among findings on a national and comparative basis; (5) to disseminate the findings in a timely manner to a wide range of relevant stakeholders nationally, across Europe, and internationally; (6) to identify and disseminate key recommendations relevant to the development of safety awareness initiatives in Europe; (7) to identify any remaining knowledge gaps and methodological lessons learned, to inform future projects regarding the promotion of safer use of the internet and new online technologies; (8) to benefit from, sustain the visibility of, and further enhance the knowledge generated by, the EU Kids Online network. The mixed methods data collection United Kingdom Children Go Online, 2003-2005 (UKCGO) is also held at the UK Data Archive under study number 5475. The study conducted an investigation of 9-19 year olds' use of the internet between 2003 and 2005 in the United Kingdom. Work was conducted with girls and boys of different ages and socio-economic backgrounds across the UK in order to ask how the internet may be transforming, or may itself be shaped by, family life, peer networks and education. Further information can be obtained from the project's web site EU Kids Online. Main Topics: Specific topics focused on were: children’s experiences of the internet across locations and devices; similarities and differences by children’s age, gender and socio-economic status; a range of risks experienced by children online; children’s perception of the subjective harm associated with these risks; children’s roles as ‘victim’ and ‘perpetrator’ of risks; accounts of risks and safety practices reported by children and their parents; data across countries for analysis of national similarities and differences. Country-specific codes were standardised to obtain comparable variables for education and socio-economic status across countries. Psychological differences were measured on scales derived or adapted from existing measures for self-efficacy, the Strength and Difficulty Questionnaire (SDQ), sensation-seeking, and internet addiction. The dataset also contains paradata, metadata and auxiliary data. Multi-stage stratified random sample Quasi-random (eg random walk) sample Face-to-face interview Self-completion

README

Authors

César E. Corona-González, Claudia Rebeca De Stefano-Ramos, Juan Pablo Rosado-Aíza, Fabiola R Gómez-Velázquez, David I. Ibarra-Zarate, Luz María Alonso-Valerdi

Contact person

César E. Corona-González

https://orcid.org/0000-0002-7680-2953

a00833959@tec.mx

Project name

Psychophysiological data from Mexican children with learning difficulties who strengthen reading and math skills by assistive technology

Year that the project ran

2023

Brief overview of the tasks in the experiment

The current dataset consists of psychometric and electrophysiological data from children with reading or math learning difficulties. These data were collected to evaluate improvements in reading or math skills resulting from using an online learning method called Smartick.

The psychometric evaluations from children with reading difficulties encompassed: spelling tests, where 1) orthographic and 2) phonological errors were considered, 3) reading speed, expressed in words read per minute, and 4) reading comprehension, where multiple-choice questions were given to the children. The last 2 parameters were determined according to the standards from the Ministry of Public Education (Secretaría de Educación Pública in Spanish) in Mexico. On the other hand, group 2 assessments embraced: 1) an assessment of general mathematical knowledge, as well as 2) the hits percentage, and 3) reaction time from an arithmetical task. Additionally, selective attention and intelligence quotient (IQ) were also evaluated.

Then, individuals underwent an EEG experimental paradigm where two conditions were recorded: 1) a 3-minute eyes-open resting state and 2) performing either reading or mathematical activities. EEG recordings from the reading experiment consisted of reading a text aloud and then answering questions about the text. Alternatively, EEG recordings from the math experiment involved the solution of two blocks with 20 arithmetic operations (addition and subtraction). Subsequently, each child was randomly subcategorized as 1) the experimental group, who were asked to engage with Smartick for three months, and 2) the control group, who were not involved with the intervention. Once the 3-month period was over, every child was reassessed as described before.

Description of the contents of the dataset

The dataset contains a total of 76 subjects (sub-), where two study groups were assessed: 1) reading difficulties (R) and 2) math difficulties (M). Then, each individual was subcategorized as experimental subgroup (e), where children were compromised to engage with Smartick, or control subgroup (c), where they did not get involved with any intervention.

Every subject was followed up on for three months. During this period, each subject underwent two EEG sessions, representing the PRE-intervention (ses-1) and the POST-intervention (ses-2).

The EEG recordings from the reading difficulties group consisted of a resting state condition (run-1) and while performing active reading and reading comprehension activities (run-2). On the other hand, EEG data from the math difficulties group was collected from a resting state condition (run-1) and when solving two blocks of 20 arithmetic operations (run-2 and run-3). All EEG files were stored in .set format. The nomenclature and description from filenames are shown below:

Example: the file sub-Rc11_ses-1_task-SmartickDataset_run-2_eeg.set is related to: - The 11th subject from the reading difficulties group, control subgroup (sub-Rc11). - EEG recording from the PRE-intervention (ses-1) while performing the reading activity (run-2)

Independent variables

• Study groups:
  • Reading difficulties
    • Control: children did not follow any intervention
    • Experimental: Children used the reading program of Smartick for 3 months
  • Math difficulties
    • Control: children did not follow any intervention
    • Experimental: Children used the math program of Smartick for 3 months
• Condition:
  • PRE-intervention: first psychological and electroencephalographic evaluation
  • POST-intervention: second psychological and electroencephalographic evaluation

Dependent variables

• Psychometric data from the reading difficulties group:

  • Orthographic_ERR: number of orthographic errors.
  • Phonological_ERR: number of phonological errors.
  • Selective_Attention: score from the selective attention test.
  • Reading_Speed: reading speed in words per minute.
  • Comprehension: score on a reading comprehension task.
  • GROUP: C for the control group, E for the experimental group.
  • GENDER: M for male, F for Female.
  • AGE: age at the beginning of the study.
  • IQ: intelligence quotient.

• Psychometric data from the math difficulties group:

  • WRAT4: score from the WRAT-4 test.
  • hits: hits during the EEG acquisition [%].
  • RT: reaction time during the EEG acquisition [s].
  • Selective_Attention: score from the selective attention test.
  • GROUP: C for the control Group, E for the experimental group.
  • GENDER: M for male, F for female.
  • AGE: age at the beginning of the study.
  • IQ: intelligence quotient.

Psychometric data can be found in the 01_Psychometric_Data.xlsx file

• Engagement percentage within Smartick (only for experimental group)
  • These values represent the engagement percentage through Smartick.
  • Students were asked to get involved with the online method for learning for 3 months, 5 days a week.
  • Greater values than 100% denote participants who regularly logged in more than 5 days weekly.

Engagement percentage be found in the 05_SessionEngagement.xlsx file

Methods

Subjects

Seventy-six Mexican children between 7 and 13 years old were enrolled in this study.

Information about the recruitment procedure

The sample was recruited through non-profit foundations that support learning and foster care programs.

Apparatus

g.USBamp RESEARCH amplifier

Initial setup

1. Explain the task to the participant.
2. Sign informed consent.
3. Set up electrodes.

Task details

The stimuli nested folder contains all stimuli employed in the EEG experiments.

Level 1 - Math: Images used in the math experiment.​​​​​​​ - Reading: Images used in the reading experiment.

Level 2 - Math * POST_Operations: arithmetic operations from the POST-intervention.
* PRE_Operations: arithmetic operations from the PRE-intervention. - Reading * POST_Reading1: text 1 and text-related comprehension questions from the POST-intervention. * POST_Reading2: text 2 and text-related comprehension questions from the POST-intervention. * POST_Reading3: text 3 and text-related comprehension questions from the POST-intervention. * PRE_Reading1: text 1 and text-related comprehension questions from the PRE-intervention. * PRE_Reading2: text 2 and text-related comprehension questions from the PRE-intervention. * PRE_Reading3: text 3 and text-related comprehension questions from the PRE-intervention.

Level 3 - Math * Operation01.jpg to Operation20.jpg: arithmetical operations solved during the first block of the math

The Family Case Studies Images dataset forms part of Children, Technology and Play (2019-2020), an 8-month co-produced study by academics from the University of Sheffield and University of Cape Town, South Africa, the LEGO Foundation and Dubit.

The study explored the contemporary play environments of children to identify the ways in which their play is shaped by technology, examine the relationship between digital play, learning and creativity, and explore the role of adults in mediating digital play.

The UK research included case studies of 10 families in Sheffield with focus children aged 3-11. Each was visited 6 times at home and a range of qualitative data collection methods was employed.

This dataset comprises researcher photos, parent photos (shared with the research team), child photos (many on the GoPro cameras used in the project), and photographed copies of child drawings and play journals, plus a spreadsheet containing relevant metadata. Personal and school names have been pseudonymised.

The project received ethical approval from the University of Sheffield (no. 028701).

The research tools and other datasets from the study are deposited elsewhere in ORDA and have been brought together in the Children, Technology and Play collection.

Context

This data set contains the percentage of children in a school attendance age (approximately 3-17 years old depending on the country) that have an internet connection at home.

Acknowledgements

I'd like to thank UNICEF for aggregating this data!

The Telephone Interviews Data forms part of Children, Technology and Play (2019-2020), an 8-month co-produced study by academics from the University of Sheffield and University of Cape Town, South Africa, the LEGO Foundation and Dubit.

The study explored the contemporary play environments of children to identify the ways in which their play is shaped by technology, examine the relationship between digital play, learning and creativity, and explore the role of adults in mediating digital play.

The UK research included 31 telephone interviews with parents of children aged 3-11 years from a range of backgrounds across the UK.

This dataset comprises the anonymised transcriptions of the audio-recorded interviews, plus a spreadsheet containing relevant metadata.

The project received ethical approval from the University of Sheffield (no. 028701).

The research tools, including the question schedule for the telephone interviews, and other datasets from the study are deposited elsewhere in ORDA and have been brought together in the Children, Technology and Play collection.

This site is part of a network of digital infrastructure built by Code for Africa (CfA) as a free open source software for use by human rights defending organisations. Reuse it to empower your own communities. CfA is Africa's largest non-profit civic technology and open data catalyst, with labs across the continent. CfA content on this site is released under a Creative Commons 4.0 International License. Refer to our attributions page for attributions of other work on the site.

This 393-hour Korean Children Speech Dataset consists of scripted monologue recordings from young speakers, captured using smartphones. The speech content includes essays, storytelling, and numeric readings. Each audio file is transcribed and annotated with metadata such as speaker ID, gender, and age. Collected from a geographically diverse group of native Korean-speaking children, this dataset is designed to support training of automatic speech recognition (ASR), text-to-speech (TTS), pronunciation evaluation systems, and educational language models. The dataset has been quality-verified by multiple AI enterprises and is fully compliant with GDPR, CCPA, and PIPL privacy regulations.

Non-native children’s English speech (NNCES) corpus: There were a total of 50 children, 25 females and 25 males, ranging in age from 8 to 12. All of the children are native speakers of Telugu, an Indian regional language, who are learning English as a second language. All of the audio clips were acquired in a .wav file using the open source SurveyLex platform, which supports dual channel at 44.1 kHz and a data rate of 16 bits per sample. Every questionnaire is conducted 10 times per child to assess the variation in words and sentences. The data was recorded for a total around 20 hours. It incorporates both read speech, with a total of 5000 utterances, and spontaneous speech, with a total of 5000 utterances with word level transcription.

The goal of this study was to test specific hypotheses illustrating the relationships among serious victimization experiences, the mental health effects of victimization, substance abuse/use, and delinquent behavior in adolescents. The study assessed familial and nonfamilial types of violence. It was designed as a telephone survey of American youth aged 12-17 living in United States households and residing with a parent or guardian. One parent or guardian in each household was interviewed briefly to establish rapport, secure permission to interview the targeted adolescent, and to ensure the collection of comparative data to examine potential nonresponse bias from households without adolescent participation. All interviews with both parents and adolescents were conducted using Computer-Assisted Telephone Interviewing (CATI) technology. From the surveys of parents and adolescents, the principal investigators created one data file by attaching the data from the parents to the records of their respective adolescents. Adolescents were asked whether violence and drug abuse were problems in their schools and communities and what types of violence they had personally witnessed. They were also asked about other stressful events in their lives, such as the loss of a family member, divorce, unemployment, moving to a new home or school, serious illness or injury, and natural disaster. Questions regarding history of sexual assault, physical assault, and harsh physical discipline elicited a description of the event and perpetrator, extent of injuries, age at abuse, whether alcohol or drugs were involved, and who was informed of the incident. Information was also gathered on the delinquent behavior of respondents and their friends, including destruction of property, assault, theft, sexual assault, and gang activity. Other questions covered history of personal and family substance use and mental health indicators, such as major depression, post-traumatic stress disorders, weight changes, sleeping disorders, and problems concentrating. Demographic information was gathered from the adolescents on age, race, gender, number of people living in household, and grade in school. Parents were asked whether they were concerned about violent crime, affordable child care, drug abuse, educational quality, gangs, and the safety of their children at school. In addition, they were questioned about their own victimization experiences and whether they discussed personal safety issues with their children. Parents also supplied demographic information on gender, marital status, number of children, employment status, education, race, and income.

This repository contains data and information relating to a longitudinal project which investigated infants’ processing of causal events and its relationship with language learning. The same group of infants was tested at two time points, once at around 13-months-old, and again at 30-months. Experiments at each time point were designed to be independently as well as longitudinally informative.The International Centre for Language and Communicative Development (LuCiD) will bring about a transformation in our understanding of how children learn to communicate, and deliver the crucial information needed to design effective interventions in child healthcare, communicative development and early years education. Learning to use language to communicate is hugely important for society. Failure to develop language and communication skills at the right age is a major predictor of educational and social inequality in later life. To tackle this problem, we need to know the answers to a number of questions: How do children learn language from what they see and hear? What do measures of children's brain activity tell us about what they know? and How do differences between children and differences in their environments affect how children learn to talk? Answering these questions is a major challenge for researchers. LuCiD will bring together researchers from a wide range of different backgrounds to address this challenge. The LuCiD Centre will be based in the North West of England and will coordinate five streams of research in the UK and abroad. It will use multiple methods to address central issues, create new technology products, and communicate evidence-based information directly to other researchers and to parents, practitioners and policy-makers. LuCiD's RESEARCH AGENDA will address four key questions in language and communicative development: 1) ENVIRONMENT: How do children combine the different kinds of information that they see and hear to learn language? 2) KNOWLEDGE: How do children learn the word meanings and grammatical categories of their language? 3) COMMUNICATION: How do children learn to use their language to communicate effectively? 4) VARIATION: How do children learn languages with different structures and in different cultural environments? The fifth stream, the LANGUAGE 0-5 PROJECT, will connect the other four streams. It will follow 80 English learning children from 6 months to 5 years, studying how and why some children's language development is different from others. A key feature of this project is that the children will take part in studies within the other four streams. This will enable us to build a complete picture of language development from the very beginning through to school readiness. Applying different methods to study children's language development will constrain the types of explanations that can be proposed, helping us create much more accurate theories of language development. We will observe and record children in natural interaction as well as studying their language in more controlled experiments, using behavioural measures and correlations with brain activity (EEG). Transcripts of children's language and interaction will be analysed and used to model how these two are related using powerful computer algorithms. LuciD's TECHNOLOGY AGENDA will develop new multi-method approaches and create new technology products for researchers, healthcare and education professionals. We will build a 'big data' management and sharing system to make all our data freely available; create a toolkit of software (LANGUAGE RESEARCHER'S TOOLKIT) so that researchers can analyse speech more easily and more accurately; and develop a smartphone app (the BABYTALK APP) that will allow parents, researchers and practitioners to monitor, assess and promote children's language development. With the help of six IMPACT CHAMPIONS, LuCiD's COMMUNICATIONS AGENDA will ensure that parents know how they can best help their children learn to talk, and give healthcare and education professionals and policy-makers the information they need to create intervention programmes that are firmly rooted in the latest research findings. This repository contains data and information relating to a longitudinal project which investigated infants’ processing of causal events and its relationship with language learning. The same group of infants was tested at two time points, once at around 13-months-old, and again at 30-months. Experiments at each time point were designed to be independently as well as longitudinally informative. All data was collected in the Child Study Centre lab, at the University of Manchester site of The ESRC International Centre for Language and Communicative Development (LuCiD; Environment and Visual Preferences themes; ESRC Grant ref: ES/L008955/1). Eye tracking data was collected using an EyeLink 1000 Plus, using experiments created in Experiment Builder (SR Research). All data has been anonymised, and is organised in long, tidy format.

Educational StructuresThis feature layer, utilizing National Geospatial Data Asset (NGDA) data from the U.S. Geological Survey (USGS), displays schools, technical and trade schools, and colleges and universities in the U.S. Per the USGS, "Structures data are designed to be used in general mapping and in the analysis of structure related activities using geographic information system technology. The National Map structures data is commonly combined with other data themes, such as boundaries, elevation, hydrography, and transportation, to produce general reference base maps. The types of structures collected are largely determined by the needs of disaster planning and emergency response, and homeland security organizations."Kenmore West High SchoolData currency: This cached Esri federal service is checked weekly for updates from its enterprise federal source (Education) and will support mapping, analysis, data exports and OGC API – Feature access.NGDAID: 135 (USGS National Structures Dataset - USGS National Map Downloadable Data Collection)OGC API Features Link: (Educational Structures - OGC Features) copy this link to embed it in OGC Compliant viewersFor more information, please visit: The National MapFor feedback please contact: Esri_US_Federal_Data@esri.comNGDA Theme CommunityThis data set is part of the NGDA Real Property Theme Community. Per the Federal Geospatial Data Committee (FGDC), Real Property is defined as "the spatial representation (location) of real property entities, typically consisting of one or more of the following: unimproved land, a building, a structure, site improvements and the underlying land. Complex real property entities (that is "facilities") are used for a broad spectrum of functions or missions. This theme focuses on spatial representation of real property assets only and does not seek to describe special purpose functions of real property such as those found in the Cultural Resources, Transportation, or Utilities themes."For other NGDA Content: Esri Federal Datasets

The Nepal Multiple Indicator Cluster Survey (NMICS) 2010 is a subnational survey of 7,372 women aged 15–49 years and 3,574 children under five from 6,000 households in the Mid- and Far Western Regions (MFWR) of Nepal. NMICS 2010 was implemented as part of the fourth round of the global MICS household survey programme with technical and financial support from UNICEF Nepal in collaboration with the Government of Nepal. The main purpose of NMICS 2010 is to support the government to generate statistically sound and comparable data for monitoring the situation of children and women in the MFWR of the country. NMICS 2010 covers topics related to nutrition, child health, water and sanitation, reproductive health, child development, literacy and education, child protection, HIV and AIDS, mass media and the use of information and communication technology, attitude towards domestic violence, the use of tobacco and alcohol, and life satisfaction. In addition, NMICS 2010 is the first survey in Nepal to provide baseline information on the prevalence of chaupadi (women who live in a separate house or animal shed during menstruation) in the MFWR and evidence on women’s life satisfaction.

Context

This data was gathered as part of the web scraping project for the General Assembly Data Science Immersive course.

Content

noon is the lifestyle shopping destination for the region in Saudi Arabia, wwith the largest online selection of leading brands in categories such as electronics, fashion, health & beauty, fragrances, grocery, baby products, and homeware, noon is the one-stop-shopping destination for everyone. For this project, I choose the noon website, data was collected from the perfume section for female, male, and kids departments.

Acknowledgements

thanks to:

GA team

Misk academy

noon

Inspiration

Perfume notes: let the model predict perfume notes.

Department prediction: build a model to decide the perfume department based on the notes features

Price prediction: predict the prices of the products based on the num_seller_ratings and other features

Brand prediction: it seems that some brands have a favorite note, lets the machine guess the brand based on the notes features

Concentration prediction: it seems that some concentration has a common note, lets the machine guess the concentration based on the notes features

Feature Engineering: do magic and play around to create new features from this dataset

Dataset Description: This dataset contains materials from a parent study within the Smart Triage program of research. Materials include the parent study protocol and associated documents. See the Metadata section below for links to related publications and datasets. Background: Pediatric sepsis remains a leading cause of under-five mortality in low- and middle-income countries (LMICs), where delayed recognition and treatment contribute to high fatality rates. While early intervention with antibiotics and fluids improves outcomes, timely care depends on effective triage—yet many facilities lack standardized, validated tools suited to their context. Existing triage systems like WHO’s ETAT are widely used but face limitations in adaptability and evaluation due to inconsistent data and resource constraints. Quality of care—timely, safe, and efficient services—remains suboptimal in many LMICs, hindered by nonspecific clinical presentations, staffing shortages, and systemic barriers. To address these gaps, we developed Smart Triage, a digital triage platform incorporating predictive modeling, vital sign measurement, and treatment tracking to streamline pediatric sepsis management. Feasibility studies show it expedites treatment and improves clinician satisfaction. We are now expanding Smart Triage + QI to four sites in Uganda to enhance sepsis care through evidence-based quality improvement and optimize resource use for sustainable health system strengthening. Methods: This is a pre- (Phase I) and post- (Phase II) evaluation of Smart Triage + QI at 4 Ugandan hospitals. Phase I: Collect data on pre-selected clinical predictors and outcomes. This data provides baseline information to evaluate the effectiveness of the quality improvement system and potential target areas. Phase II: Collect data to evaluate the effectiveness of Smart Triage + QI based on the primary and secondary outcomes. This period is a component of the quality improvement program with the goal of optimizing care of children with severe infections/suspected sepsis. Ethics Declaration: This study was approved by the Makerere University School of Public Health Institutional Review Board in Uganda (SPH-2021-41) and the Uganda National Institute of Science and Technology (HS1745ES) . Associated datasets: Smart Triage: Clinical Data - QI NOTE for restricted files: If you are not yet a CoLab member, please complete our membership application survey to gain access to restricted files within 2 business days. Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator at sepsiscolab@bcchr.ca or visit our website.

We analysed both structural and functional aspects of sentences containing the four adverbials “after”, “before”, “because”, and “if” in two dense corpora of parent-child interactions from two British English-acquiring children (2;00–4;07). In comparing mothers’ and children's usage we separate out the effects of frequency, cognitive complexity and pragmatics in explaining the course of acquisition of adverbial sentences. We also compare these usage patterns to stimuli used in a range of experimental studies and show how differences may account for some of the difficulties that children have shown in experiments. In addition, we report descriptive data on various aspects of adverbial sentences that have not yet been studied as a resource for future investigations.The International Centre for Language and Communicative Development (LuCiD) will bring about a transformation in our understanding of how children learn to communicate, and deliver the crucial information needed to design effective interventions in child healthcare, communicative development and early years education. Learning to use language to communicate is hugely important for society. Failure to develop language and communication skills at the right age is a major predictor of educational and social inequality in later life. To tackle this problem, we need to know the answers to a number of questions: How do children learn language from what they see and hear? What do measures of children's brain activity tell us about what they know? and How do differences between children and differences in their environments affect how children learn to talk? Answering these questions is a major challenge for researchers. LuCiD will bring together researchers from a wide range of different backgrounds to address this challenge. The LuCiD Centre will be based in the North West of England and will coordinate five streams of research in the UK and abroad. It will use multiple methods to address central issues, create new technology products, and communicate evidence-based information directly to other researchers and to parents, practitioners and policy-makers. LuCiD's RESEARCH AGENDA will address four key questions in language and communicative development: 1) ENVIRONMENT: How do children combine the different kinds of information that they see and hear to learn language? 2) KNOWLEDGE: How do children learn the word meanings and grammatical categories of their language? 3) COMMUNICATION: How do children learn to use their language to communicate effectively? 4) VARIATION: How do children learn languages with different structures and in different cultural environments? The fifth stream, the LANGUAGE 0-5 PROJECT, will connect the other four streams. It will follow 80 English learning children from 6 months to 5 years, studying how and why some children's language development is different from others. A key feature of this project is that the children will take part in studies within the other four streams. This will enable us to build a complete picture of language development from the very beginning through to school readiness. Applying different methods to study children's language development will constrain the types of explanations that can be proposed, helping us create much more accurate theories of language development. We will observe and record children in natural interaction as well as studying their language in more controlled experiments, using behavioural measures and correlations with brain activity (EEG). Transcripts of children's language and interaction will be analysed and used to model how these two are related using powerful computer algorithms. LuciD's TECHNOLOGY AGENDA will develop new multi-method approaches and create new technology products for researchers, healthcare and education professionals. We will build a 'big data' management and sharing system to make all our data freely available; create a toolkit of software (LANGUAGE RESEARCHER'S TOOLKIT) so that researchers can analyse speech more easily and more accurately; and develop a smartphone app (the BABYTALK APP) that will allow parents, researchers and practitioners to monitor, assess and promote children's language development. With the help of six IMPACT CHAMPIONS, LuCiD's COMMUNICATIONS AGENDA will ensure that parents know how they can best help their children learn to talk, and give healthcare and education professionals and policy-makers the information they need to create intervention programmes that are firmly rooted in the latest research findings.