This policy outlines the framework that the MOE uses to assess and manage the risk to the children participating in all of its programs, including any donor-funded programs, and the measures and systems put in place to respond to concerns about their wellbeing.

This round of Eurobarometer surveys diverged from the standard trends questions, instead focusing on public opinion in the following major areas: consumer rights, personal data protection, education through sport, product safety, e-commerce, persons with disabilities, and national currency. Respondents were asked about opportunities to settle disputes with a seller or service provider including actions taken to settle dispute and type of product or service. A number of questions asked regarded the current justice system including the respondents' level of trust in the system, areas that need improvement, and what resources are available to protect consumer rights. Respondents were also asked about whether they were concerned with the privacy of their personal data. Questions sought the respondents' level of trust in national organizations, opinion of what data protection laws should entail, and whether they had used tools or technology to protect personal data. Respondents were also asked about their participation in sports activities. Questions included how often they perform recreational activities, where they exercise, what are the benefits and values of sports, and what are the anticipated outcomes due to the negative aspects of sports. Regarding safety instructions, respondents were asked if they purchase domestic electrical appliances. A number of questions focused on product safety information. Respondents were asked whether they read and obey the information provided on the product, whether the information impacted their purchase and/or use of the product, and the most effective way to provide product instructions. Several questions asked the respondent to recognize safety symbols labeled on the product, the symbol's effectiveness, and whether it impacted their purchase decision. Respondents were also asked whether they purchased products on the internet, how often, concerns regarding their internet transactions, why they purchased online, and from what Web sites they purchased. Other questions asked regarded the security of internet transactions including the respondents knowledge of consumer rights, internet security, protection laws concerning internet purchases, who they contacted if help was needed, and their past experience with complaints on internet transactions. Respondents were also asked questions about persons with disabilities including knowledge of European programs for persons with disabilities, their knowledge of various types of disabilities, and their view of persons with disabilities. Lastly, respondents in the euro-zone, were asked questions that pertained to national currency including how pleased they were with the establishment of the Euro as the universal currency. Demographic and other background information collected includes respondents' age, gender, marital status, nationality, left-right political self-placement, age at completion of education, occupation, household income group, type and size of locality, and region of residence.

From 2016 through 2020, Child Trends, in partnership with the D.C. Office of Human Rights and the D.C. Office of the State Superintendent of Education, and with funding from the National Institute of Justice's Comprehensive School Safety Initiative, implemented and evaluated the Safe School Certification (SSC) Program, a three-year technical assistance model to support schools in strengthening organizational capacity across eight elements key to improving school climate: leadership, data, buy-in, policy and policy enforcement, student engagement, family and community engagement, training, and programs and practices. To help support schools' efforts, and to evaluate SSC's effectiveness, survey data were collected annually from students, parents, instructional staff, and non-instructional staff at participating schools using the U.S. Department of Education's School Climate Survey (EDSCLS), which was adapted to include measures of sexual orientation and gender identity, grit, and personal experiences of bullying and fights. Additionally, observations using the Classroom Assessment Scoring System - Secondary (CLASS-S) were conducted in a random sample of five classrooms in each participating school each year. Finally, as part of the implementation evaluation, interviews were conducted with the technical assistance providers, points of contact or leadership at participating schools, the SSC developer, and the manager of the Certification Advisory Board (CAB), which provided feedback to schools over the course of implementation through reviews of compiled workbooks.

ABSTRACT This article consists of a case study that aimed to identify health and education professionals’ perceptions of the School Health Program (PSE) actions in a suburban territory of Baixada Santista, São Paulo. Three educational counselors from two schools, a PSE articulator, a therapeutic companion, a psychologist, two nurses, and a community health worker were interviewed. The transcribed interviews were submitted to lexographic analysis and descending hierarchical classification in the software IRaMuTeQ-R. They were later analyzed based on the theoretical references on the PSE, school health, and intersectoriality. The results showed that the PSE actions focus on the matrix support meeting, referrals, vaccination verification, oral health, and eye health. The inadequate continuing training, poor knowledge of the PSE policy, and overwork compromise the full consideration of the program’s objectives, which, traversed by the pandemic, escalated the challenges faced by professionals. There is potential to be explored by the meeting of health and education. However, challenges involving these sectors, the traditional management rationale, the biological approach, and social participation should be overcome to advance towards intersectoral proposals to promote health and well-being.

Users can view brief descriptions of laws and policies pertaining to the health of students Topics include: wellness policy, health education curriculum, school meal programs, physical activity, emergency response, bullying, and facility safety, among others. Background The State School Health Policy Database was developed by the National Association of State Boards of Education and is supported by the Division of Adolescent and School Health of the Centers (DASH) of the Centers for Disease Control and Prevention (CDC) and the Robert Wood Johnson Foundation. This database is useful for school policymakers interested in viewing strategies and policies across states and researchers and policy evaluators seeking to track changes in polici es across the United States. Topics include: wellness policies, health education curriculum; school meal programs, school food environment, physical activity, drug-free schools, bullying, emergency response, tobacco use, air quality, pesticide use, and facility safety. User Functionality Users can view brief descriptions of laws and policies pertaining to the health of students. When possible, hyperlinks to full written policies are included. Data Notes The data base is updated regularly with new and revised laws and policies from across the United States.

This is a multi-method study of school violence and victimization during the transition to high school. This study has two major data collection efforts. First, a full population survey of 7th through 10th grade students across 10 Flint Community Schools (fall 2016) -- which serve primarily African American and poor populations -- that will identify patterns of student victimization, including the location and seriousness of violent events, and examine the connections between school and community violence. This will be followed by a three-wave panel qualitative study of 100 students interviewed every 6 months beginning in the spring of their 8th grade year (spring 2017) and continuing through their 9th grade year. The goal of the interviews will be to further the research from the survey and develop a deeper understanding of how school safety impacts the transition experience, school violence, including how communities conflict impacts school safety, and what youth do to protect themselves from school-related victimization. Researchers integrated crime incident data from the Flint police department as a source for triangulation of findings. A community workgroup will provide guided translation of findings generated from mixed-methods analyses, and develop an action plan to help students successfully transition to high school. Results and policy implications will be given to practitioner, researcher, and public audiences through written, oral, and web-based forums. De-identified data will be archived at the National Archive of Criminal Justice Data.

Attitude to data protection.

Topics: Occupational contact with personal data; self-assessment of willingness to provide information about personal matters regarding authorities; detailed determination of type and frequency of contacts with authorities; perceived disturbances by the requests for personal data by authorities; personal determination of wrong decisions by authorities due to incorrect storage of personal data; attitude to a data protection law and assessment of a government demand for storage of personal data; detailed determinations of those authorities to whom one would provide information without hesitation; assessment of the danger of abuse of data; attitude to a personal identification and a computer network of authorities; attitude to innovations and computers; attitude to protection of the private sphere; classification of activities in the areas private sphere and public; receipt of social services; type of borrowing and taxes paid; completed insurance policies; last medical treatment and number of visits to the doctor in the last year; last hospital stay; membership in clubs or citizen initiatives; self-assessment of status in various roles, such as e.g. patient, borrower, citizen, insurance policy holder or in occupation; satisfaction with democracy and the political system in the FRG; attitude to reforms and more social justice; relationship with neighborhood; assessment of the size of personal circle of friends.

Scales: attitudes to democracy and the social system.

Demography: age; sex; marital status; school education; vocational training; occupation; employment; household income; size of household; composition of household; head of household; self-assessment of social class.

Please cite the following paper when using this dataset:

N. Thakur, “A Large-Scale Dataset of Twitter Chatter about Online Learning during the Current COVID-19 Omicron Wave,” Journal of Data, vol. 7, no. 8, p. 109, Aug. 2022, doi: 10.3390/data7080109

Abstract

The COVID-19 Omicron variant, reported to be the most immune evasive variant of COVID-19, is resulting in a surge of COVID-19 cases globally. This has caused schools, colleges, and universities in different parts of the world to transition to online learning. As a result, social media platforms such as Twitter are seeing an increase in conversations, centered around information seeking and sharing, related to online learning. Mining such conversations, such as Tweets, to develop a dataset can serve as a data resource for interdisciplinary research related to the analysis of interest, views, opinions, perspectives, attitudes, and feedback towards online learning during the current surge of COVID-19 cases caused by the Omicron variant. Therefore this work presents a large-scale public Twitter dataset of conversations about online learning since the first detected case of the COVID-19 Omicron variant in November 2021. The dataset is compliant with the privacy policy, developer agreement, and guidelines for content redistribution of Twitter and the FAIR principles (Findability, Accessibility, Interoperability, and Reusability) principles for scientific data management.

Data Description

The dataset comprises a total of 52,984 Tweet IDs (that correspond to the same number of Tweets) about online learning that were posted on Twitter from 9th November 2021 to 13th July 2022. The earliest date was selected as 9th November 2021, as the Omicron variant was detected for the first time in a sample that was collected on this date. 13th July 2022 was the most recent date as per the time of data collection and publication of this dataset.

The dataset consists of 9 .txt files. An overview of these dataset files along with the number of Tweet IDs and the date range of the associated tweets is as follows. Table 1 shows the list of all the synonyms or terms that were used for the dataset development.

Filename: TweetIDs_November_2021.txt (No. of Tweet IDs: 1283, Date Range of the associated Tweet IDs: November 1, 2021 to November 30, 2021)

Filename: TweetIDs_December_2021.txt (No. of Tweet IDs: 10545, Date Range of the associated Tweet IDs: December 1, 2021 to December 31, 2021)

Filename: TweetIDs_January_2022.txt (No. of Tweet IDs: 23078, Date Range of the associated Tweet IDs: January 1, 2022 to January 31, 2022)

Filename: TweetIDs_February_2022.txt (No. of Tweet IDs: 4751, Date Range of the associated Tweet IDs: February 1, 2022 to February 28, 2022)

Filename: TweetIDs_March_2022.txt (No. of Tweet IDs: 3434, Date Range of the associated Tweet IDs: March 1, 2022 to March 31, 2022)

Filename: TweetIDs_April_2022.txt (No. of Tweet IDs: 3355, Date Range of the associated Tweet IDs: April 1, 2022 to April 30, 2022)

Filename: TweetIDs_May_2022.txt (No. of Tweet IDs: 3120, Date Range of the associated Tweet IDs: May 1, 2022 to May 31, 2022)

Filename: TweetIDs_June_2022.txt (No. of Tweet IDs: 2361, Date Range of the associated Tweet IDs: June 1, 2022 to June 30, 2022)

Filename: TweetIDs_July_2022.txt (No. of Tweet IDs: 1057, Date Range of the associated Tweet IDs: July 1, 2022 to July 13, 2022)

The dataset contains only Tweet IDs in compliance with the terms and conditions mentioned in the privacy policy, developer agreement, and guidelines for content redistribution of Twitter. The Tweet IDs need to be hydrated to be used. For hydrating this dataset the Hydrator application (link to download and a step-by-step tutorial on how to use Hydrator) may be used.

Table 1. List of commonly used synonyms, terms, and phrases for online learning and COVID-19 that were used for the dataset development

Terminology

List of synonyms and terms

COVID-19

Omicron, COVID, COVID19, coronavirus, coronaviruspandemic, COVID-19, corona, coronaoutbreak, omicron variant, SARS CoV-2, corona virus

online learning

online education, online learning, remote education, remote learning, e-learning, elearning, distance learning, distance education, virtual learning, virtual education, online teaching, remote teaching, virtual teaching, online class, online classes, remote class, remote classes, distance class, distance classes, virtual class, virtual classes, online course, online courses, remote course, remote courses, distance course, distance courses, virtual course, virtual courses, online school, virtual school, remote school, online college, online university, virtual college, virtual university, remote college, remote university, online lecture, virtual lecture, remote lecture, online lectures, virtual lectures, remote lectures

Many schools have implemented programs to address bullying, such as the Olweus Bullying Prevention Program (OBPP), or broader school behavioral issues, such as School-wide Positive Behavioral Interventions and Supports (SWPBIS), but there have been calls to integrate school interventions in order to address the limits of each "stand alone" program. The purpose of this project was to develop an intervention combining OBPP and SWPBIS strategies into one integrated program, evaluate its effectiveness using a randomized controlled trial (RCT), analyze the program's cost effectiveness, and examine the use of school-based mental health services in elementary, middle, and high school settings. Implications for policy and strategy are also discussed. School-level data were presented including disciplinary incidents, student and teacher attendance, program costs, and the presence of mental health services. Students and teachers within intervention and control conditions were surveyed about their perceptions of bullying, school safety, and school climate. Teachers in intervention schools were asked about program satisfaction, self-efficacy, and fidelity. Students were asked numerous questions pertaining to physical and mental health, bullying perpetration and victimization, and substance abuse. Teachers and students were asked their grade, gender, and race.

The indicator measures the number who had previously been the subject of a child protection plan, or on the child protection register of that council, regardless of how long ago that was against the number of children subject to a child protection plan at any time during the Year, expressed as a percentage

Source: CPR3 statutory return form local authorities to Department for Children Schools and Families (DCSF).

Publisher: DCLG Floor Targets Interactive

Geographies: County/Unitary Authority, Government Office Region (GOR), National

Geographic coverage: England

Time coverage: 2006/07 to 2008/09

Type of data: Administrative data

Notes: This is a count of each occasion in the year, and may count the same child more than once.

Introduction

Online Privacy Statistics: We use many websites and online services every day, so it’s normal to feel worried about how our data is handled. Whether it’s personal information or data from work and school, there are real concerns about what could happen if it gets into the wrong hands. These worries have grown as technology has advanced. In 2025, data privacy will be very different from before, and it will continue to change.

Factors like artificial intelligence (AI) and a more connected business world are creating new challenges for companies trying to follow data privacy rules. Below, we’ve gathered some important Online Privacy Statistics that everyone should know. These numbers highlight how data privacy affects businesses and users, with updated information from 2025 and recent years to give a clear picture of today’s situation.

The indicator measures the number of children who had been the subject of a Child Protection Plan continuously for two years or longer against the number of children ceasing to be the subject of a Child Protection Plan during the year, expressed as percentage

Source: CPR3 statutory return form local authorities to Department for Children Schools and Families (DCSF).

Publisher: DCLG Floor Targets Interactive

Geographies: County/Unitary Authority, Government Office Region (GOR), National

Geographic coverage: England

Time coverage: 2006/07 to 2008/09

Type of data: Administrative data

This dataset provides detailed information about schools in California, including district names, school types, multilingual program availability, addresses, and administrative contacts. The dataset is ideal for geospatial analysis, educational research, and resource allocation studies.

Potential Use Cases

• Education Insights Analyze the distribution of public vs. private schools in California. Identify districts with high concentrations of multilingual programs. Study patterns in educational program types across urban and rural regions.

• Geospatial Studies Map the geographical distribution of schools by ZIP code or district. Highlight underserved areas or gaps in access to educational resources.

• Policy Research Provide insights for education policymakers on resource allocation. Identify trends or disparities in school operations.

• Public Resource Create a searchable directory for parents and educators to locate schools.

Source and Compliance Source: All data was collected from publicly available government resources and/or school directories. Privacy Compliance: To adhere to privacy standards and Kaggle's guidelines, fields containing personally identifiable information has removed.

School meals were introduced in the Brazilian political agenda by a group of scholars known as nutrition scientists' in the 1940s. In 1955, the Campanha de Merenda Escolar, the first official school food program, was stablished, and sixty years after its inception, school food in Brazil stands as a decentralised public policy, providing services to students enrolled in public schools, which involve the Brazilian federal government, twentyseven federative units, and their 5,570 municipalities. Throughout its history, school food has gone through many stages that reflect the social transformations in Brazil: from a campaign to implement school food focused on the problem of malnutrition and the ways to solve it, to the creation of a universal public policy relying on social participation and interface between other modern, democratic, and sustainable policies, establishing a strategy for promoting food and nutrition security, development, and social protection. In this article, the School Food Program is analyzed from the perspective of four basic structures that support it as public policy: the formal structure, consisting of legal milestones that regulated the program; substantive structure, referring to the public and private social actors involved; material structure, regarding the way in which Brazil sponsors the program; and finally, the symbolic structure, consisting of knowledge, values, interests, and rules that legitimatize the policy.

Snapshot img

Cloud Computing Market In K-12 Education Sector Size 2024-2028

The cloud computing market in K-12 education sector size is forecast to increase by USD 51.22 billion at a CAGR of 33.3% between 2023 and 2028.

In the K-12 education sector, cloud computing has emerged as a transformative technology, revolutionizing the way education is delivered. The integration of cloud computing in e-learning has facilitated easy access to educational content from anywhere, anytime. The trend towards IoT integration with cloud computing is further enhancing this accessibility, enabling the use of devices like tablets and glass for interactive learning experiences. However, this shift towards cloud-based solutions also brings about new challenges, particularly In the realm of security. Data security, network security, application security, endpoint security, and multi-factor authentication are key concerns for educators and administrators. Cloud security solutions are essential to mitigate these risks and ensure the safety of sensitive student information. As the adoption of cloud computing continues to grow In the education sector, addressing these security challenges will be crucial for successful implementation.

What will be the Size of the Market During the Forecast Period?

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The K-12 education sector's adoption of cloud computing continues to gain momentum as schools and districts seek to modernize their IT infrastructure and enhance the learning experience for students. Cloud computing offers numerous benefits, including scalability, cost savings, and access to a vast array of resources. However, this shift to cloud-first organizations also presents new challenges, particularly In the areas of security and user identity management. Traditional security measures, such as firewalls and VPNs, are being supplemented with cloud-based solutions, including network security, user authentication, and endpoint security. In the hybrid world of cloud and on-premises infrastructure, context-aware security policies and user identity management are essential to mitigating risks.
Furthermore, the cloud computing market in K-12 education is characterized by a growing attack surface, with network-based attacks, DDoS, ransomware, malware, and server scanning posing significant threats. Cloud security solutions, such as Zscaler, are increasingly being adopted to address these risks, with a focus on application infrastructure security and a need-to-know model. As the use of cloud computing in K-12 education continues to expand, business policies and user authentication protocols will become increasingly important to ensure data privacy and security. Cloud computing offers a VPN alternative, enabling secure access to resources from anywhere, while maintaining network security and user identity management.

How is this Market segmented and which is the largest segment?

The cloud computing in K-12 education sector industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Service

  Software-as-a-Service (SaaS)
  Infrastructure-as-a-Service (IaaS)
  Platform-as-a-Service (PaaS)


Geography

  North America

    US


  Europe

    Germany
    UK


  APAC

    China
    Japan


  South America



  Middle East and Africa

By Service Insights

The software-as-a-service (SaaS) segment is estimated to witness significant growth during the forecast period.

The market is primarily driven by the Software-as-a-Service (SaaS) segment due to its cost-effective and scalable benefits. SaaS enables schools to access cloud-based applications over the Internet, reducing expenses on installation, licensing, and maintenance. This model allows K-12 institutions to expand their data reach to larger audiences, fostering the exchange of innovative ideas among students. Security is a significant concern in cloud adoption for educational institutions. User identity, context, and business policy are crucial elements of a strong security model. Traditional security measures, such as VPNs, are being replaced by Cloud Security solutions that offer user authentication, resources protection, and access control policies.

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The Software-as-a-Service (SaaS) segment was valued at USD 5.74 billion in 2018 and showed a gradual increase during the forecast period.

Regional Analysis

North America is estimated to contribute 62% to the growth of the global market during the forecast period.

Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

For more insights on the market share o

This dataset shows all school level performance data used to create CPS School Report Cards for the 2011-2012 school year. Metrics are described as follows (also available for download at http://bit.ly/uhbzah): NDA indicates "No Data Available." SAFETY ICON: Student Perception/Safety category from 5 Essentials survey // SAFETY SCORE: Student Perception/Safety score from 5 Essentials survey // FAMILY INVOLVEMENT ICON: Involved Families category from 5 Essentials survey // FAMILY INVOLVEMENT SCORE: Involved Families score from 5 Essentials survey // ENVIRONMENT ICON: Supportive Environment category from 5 Essentials survey // ENVIRONMENT SCORE: Supportive Environment score from 5 Essentials survey // INSTRUCTION ICON: Ambitious Instruction category from 5 Essentials survey // INSTRUCTION SCORE: Ambitious Instruction score from 5 Essentials survey // LEADERS ICON: Effective Leaders category from 5 Essentials survey // LEADERS SCORE: Effective Leaders score from 5 Essentials survey // TEACHERS ICON: Collaborative Teachers category from 5 Essentials survey // TEACHERS SCORE: Collaborative Teachers score from 5 Essentials survey // PARENT ENGAGEMENT ICON: Parent Perception/Engagement category from parent survey // PARENT ENGAGEMENT SCORE: Parent Perception/Engagement score from parent survey // AVERAGE STUDENT ATTENDANCE: Average daily student attendance // RATE OF MISCONDUCTS (PER 100 STUDENTS): # of misconducts per 100 students//AVERAGE TEACHER ATTENDANCE: Average daily teacher attendance // INDIVIDUALIZED EDUCATION PROGRAM COMPLIANCE RATE: % of IEPs and 504 plans completed by due date // PK-2 LITERACY: % of students at benchmark on DIBELS or IDEL // PK-2 MATH: % of students at benchmark on mClass // GR3-5 GRADE LEVEL MATH: % of students at grade level, math, grades 3-5 // GR3-5 GRADE LEVEL READ: % of students at grade level, reading, grades 3-5 // GR3-5 KEEP PACE READ: % of students meeting growth targets, reading, grades 3-5 // GR3-5 KEEP PACE MATH: % of students meeting growth targets, math, grades 3-5 // GR6-8 GRADE LEVEL MATH: % of students at grade level, math, grades 6-8 // GR6-8 GRADE LEVEL READ: % of students at grade level, reading, grades 6-8 // GR6-8 KEEP PACE MATH: % of students meeting growth targets, math, grades 6-8 // GR6-8 KEEP PACE READ: % of students meeting growth targets, reading, grades 6-8 // GR-8 EXPLORE MATH: % of students at college readiness benchmark, math // GR-8 EXPLORE READ: % of students at college readiness benchmark, reading // ISAT EXCEEDING MATH: % of students exceeding on ISAT, math // ISAT EXCEEDING READ: % of students exceeding on ISAT, reading // ISAT VALUE ADD MATH: ISAT value-add value, math // ISAT VALUE ADD READ: ISAT value-add value, reading // ISAT VALUE ADD COLOR MATH: ISAT value-add color, math // ISAT VALUE ADD COLOR READ: ISAT value-add color, reading // STUDENTS TAKING ALGEBRA: % of students taking algebra // STUDENTS PASSING ALGEBRA: % of students passing algebra // 9TH GRADE EXPLORE (2009): Average EXPLORE score, 9th graders who tested in fall 2009 // 9TH GRADE EXPLORE (2010): Average EXPLORE score, 9th graders who tested in fall 2010 // 10TH GRADE PLAN (2009): Average PLAN score, 10th graders who tested in fall 2009 // 10TH GRADE PLAN (2010): Average PLAN score, 10th graders who tested in fall 2010 // NET CHANGE EXPLORE AND PLAN: Difference between Grade 9 Explore (2009) and Grade 10 Plan (2010) // 11TH GRADE AVERAGE ACT (2011): Average ACT score, 11th graders who tested in fall 2011 // NET CHANGE PLAN AND ACT: Difference between Grade 10 Plan (2009) and Grade 11 ACT (2011) // COLLEGE ELIGIBILITY: % of graduates eligible for a selective four-year college // GRADUATION RATE: % of students who have graduated within five years // COLLEGE/ ENROLLMENT RATE: % of students enrolled in college // COLLEGE ENROLLMENT (NUMBER OF STUDENTS): Total school enrollment // FRESHMAN ON TRACK RATE: Freshmen On-Track rate // RCDTS: Region County District Type Schools Code

Context

The World Bank is an international financial institution that provides loans to countries of the world for capital projects. The World Bank's stated goal is the reduction of poverty. Source: https://en.wikipedia.org/wiki/World_Bank

Content

This dataset combines key education statistics from a variety of sources to provide a look at global literacy, spending, and access.

For more information, see the World Bank website.

Fork this kernel to get started with this dataset.

Acknowledgements

https://bigquery.cloud.google.com/dataset/bigquery-public-data:world_bank_health_population

http://data.worldbank.org/data-catalog/ed-stats

https://cloud.google.com/bigquery/public-data/world-bank-education

Citation: The World Bank: Education Statistics

Dataset Source: World Bank. This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy - and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

Banner Photo by @till_indeman from Unplash.

Inspiration

Of total government spending, what percentage is spent on education?

This study examined safety and security in Finnish schools as well as preparedness for safety disturbances and detrimental behaviour in the school environment. The respondents of the survey were rectors and vice rectors in Finnish primary and upper secondary schools. The study was commissioned and funded by the Institute of Criminology and Legal Policy at the University of Helsinki. Three different questionnaires were used to collect the data depending on the type of the institution (primary school, upper secondary school, combined primary and upper secondary school). The data were processed according to the questionnaire for primary schools because primary schools constituted the majority of responses, but variables specific to a certain type of institution are indicated in the data. First, the study charted background information concerning e.g. class sizes in the school, how long the respondent had worked for the school, which grades were taught in the school, and how many times during a given day students had to switch from one classroom to another. It was also queried whether a school social worker, a school psychologist and a school nurse/doctor visited the school at least once per week. The next questions covered the school environment with questions regarding whether a variety of phenomena occurred near the school premises, e.g. panhandling, littering, drug use/sale or vandalism. It was also charted which services and locations were found within 500 metres of the school building as well as what sort of security personnel worked at the school during and outside school hours. The respondents were also asked whether syringes or other items relating to drug use had been found on school premises during the school year 2015-2016. The next questions pertained to whether the school had adopted specific security-increasing practices, such as camera surveillance, access control in school buildings, personal user accounts and passwords for computers, restricted access to internet sites, anti-bullying campaigns, and collaboration with the police. It was also queried what sort of punishments the school used for student misbehaviour (e.g. removing a student from class, teacher-parent discussion, detention or expulsion). Next, incidents of criminal behaviour against the school and the school building were examined (e.g. intentional damage to school or staff property, breaking and entering into school premises, arson or attempted arson, harm to information systems). It was also asked if any crimes had been reported to the police and what the monetary extent of intentional damage to school property had been during the school year 2015-2016. Cases of defamation, violence or threat of violence against personnel were charted, as well as how many days staff members had spent absent from work due to these crimes during the school year 2015-2016. Different crimes against students were also charted, such as bicycle and cellphone thefts and violence, as well as whether these cases were reported to the police. Further questions were asked about the perpetrators and victims of violent crimes, such as their gender and national background, and whether the crime was motivated by e.g. skin colour or sexual orientation. Next, the study surveyed whether students or other persons had brought dangerous items, such as knives or other weapons, into school premises during school hours and whether the school had reported these incidents to the police. Certain phenomena, such as racism among students and between students and teachers, were also charted. General threats of violence not against any particular person were also examined as well as whether there was any sign that the maker of the threat would have been preparing to carry out the act. The respondents were also asked if the school had carried out different surveillance and security measures during the school year 2015-2016 (e.g. searching students' bags, clothes or lockers; confiscating dangerous items, alcohol or drugs) and whether these measures had prevented an act or threat of violence or if they had caused a threatening situation. Finally, it was queried whether any students or their parents had threatened the respondent or teachers with legal action or reported a crime to the police where the respondent or teachers were accused. In addition, the respondents' preparedness to report a student's crime to the police in two hypothetical situations was examined (a student paints a graffiti on the school's wall; a student hits another student in the face, causing bruises and bleeding from the nose). The study finally surveyed some more background information on e.g. gender, age, and how many years the respondent had worked as rector or vice rector.

The School Survey on Crime and Safety (SSOCS) is managed by the National Center for Education Statistics (NCES) on behalf of the United States Department of Education (ED). SSOCS collects extensive crime and safety data from principals and school administrators of public schools in America. Data from this collection can be used to correlate school characteristics with violent and serious violent crimes in American schools. Furthermore, data from SSOCS can be used to assess what school programs, practices, and policies are used by schools in their efforts to prevent crime. SSOCS has been conducted three times, in school years 1999-2000, 2003-2004, and 2005-2006. The 2003-2004 School Survey on Crime and Safety (SSOCS:2004) was developed by the National Center for Education Statistics (NCES) and conducted by Abt Associates Inc. Questionnaire packets were mailed to 3,743 public primary, middle, high, and combined schools. A total of 2,772 public schools submitted usable questionnaires for a weighted response rate of 77.2 percent. Data were collected from March 1, 2004, to June 4, 2004.