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Abstract

The Young Lives survey is an innovative long-term project investigating the changing nature of childhood poverty in four developing countries. The purpose of the project is to improve understanding of the causes and consequences of childhood poverty and examine how policies affect children's well-being, in order to inform the development of future policy and to target child welfare interventions more effectively. The study is being conducted in Ethiopia, India (in Andhra Pradesh), Peru and Vietnam. These countries were selected because they reflect a range of cultural, geographical and social contexts and experience differing issues facing the developing world; high debt burden, emergence from conflict, and vulnerability to environmental conditions such as drought and flood.

The Young Lives study aims to track the lives of 12,000 children over a 15-year period, surveyed once every 3-4 years. Round 1 of Young Lives surveyed two groups of children in each country, at 1 year old and 5 years old. Round 2 returned to the same children who were then aged 5 and 12 years old. Round 3 surveyed the same children again at aged 7-8 years and 14-15 years, and Round 4 surveyed them at 12 and 19 years old. Thus the younger children are being tracked from infancy to their mid-teens and the older children through into adulthood, when some will become parents themselves.

The survey consists of three main elements: a child questionnaire, a household questionnaire and a community questionnaire. The household data gathered is similar to other cross-sectional datasets (such as the World Bank's Living Standards Measurement Study). It covers a range of topics such as household composition, livelihood and assets, household expenditure, child health and access to basic services, and education. This is supplemented with additional questions that cover caregiver perceptions, attitudes, and aspirations for their child and the family. Young Lives also collects detailed time-use data for all family members, information about the child's weight and height (and that of caregivers), and tests the children for school outcomes (language comprehension and mathematics). An important element of the survey asks the children about their daily activities, their experiences and attitudes to work and school, their likes and dislikes, how they feel they are treated by other people, and their hopes and aspirations for the future. The community questionnaire provides background information about the social, economic and environmental context of each community. It covers topics such as ethnicity, religion, economic activity and employment, infrastructure and services, political representation and community networks, crime and environmental changes. The Young Lives survey is carried out by teams of local researchers, supported by the Principal Investigator and Data Manager in each country.

Further information about the survey, including publications, can be downloaded from the Young Lives website.

School surveys were introduced into Young Lives in 2010 in order to capture detailed information about children’s experiences of schooling, and to improve our understanding of: - the relationships between learning outcomes, and children's home backgrounds, gender, work, schools, teachers and class and school peer-groups. - school effectiveness, by analysing factors explaining the development of cognitive and non-cognitive skills in school, including value-added analysis of schooling and comparative analysis of school-systems. - equity issues (including gender) in relation to learning outcomes and the evolution of inequalities within education

The survey allows us to link longitudinal information on household and child characteristics from the household survey with data on the schools attended by the Young Lives children and children's achievements inside and outside the school. It provides policy-relevant information on the relationship between child development (and its determinants) and children’s experience of school, including access, quality and progression. This combination of household, child and school-level data over time constitutes the comparative advantage of Young Lives. Findings are all available on our Education theme pages and our publications page. Further information is available from the Young Lives http://www.younglives.org.uk/content/school-survey-0" title="School Survey">School Survey webpages.

Geographic coverage

The Young Lives study traced the lives of 3,000 children in 20 sentinel sites located in five regions of the country (Addis Ababa, Amhara, Oromia, SNNP and Tigray). The second school survey extended beyond the 20 Young Lives sites to include ten newly selected sites in the developing regions of Somali and Afar, where historically poor access to and participation in services, including education, is of particular concern to government, donors and NGOs.

Analysis unit

Individuals Institutions/organisations

Kind of data

Sample survey data [ssd]

Sampling procedure

Multi-stage stratified random sample

The final sample included 94 ‘schools’ and 280 classes (142 Grade 4 and 134 Grade 5) making a sample size of 13,724. The majority of surveyed schools are government-owned (75 out of 94), but 19 nongovernment-owned schools were also surveyed in sites in Addis Ababa, SNNP and Somali regions.

The second school survey in Ethiopia sampled all pupils (including both Young Lives Younger Cohort children and non-Young Lives children) studying in all Grade 4 and Grade 5 classes in all schools located within the geographic boundaries of each survey sentinel site. The survey therefore constitutes a site-level census of all Grade 4 and 5 pupils attending school within the geographic boundaries of the 30 sentinel sites.

The survey was conducted at both the beginning (Wave 1) and end (Wave 2) of the school year. At Wave 1, the pupil-level sample included all pupils present on the first day of the survey visit to the school. These pupils were then followed up at Wave 2, without replacement of absent pupils.

The twenty main Young Lives sites (in the regions of Addis Ababa, Amhara, Oromia, SNNP and Tigray) were selected purposely in 2001 to ensure that the household survey reflected the cultural and geographic diversity of the country, including urban-rural differences, but with a pro-poor bias and a focus on areas with food insecurity (see Outes-Leon and Sanchez 2008 for further details). Between three and five sites were selected in each region to represent diversity across zones and ethnicities. The ten new sites in Somali and Afar were selected according to the same criteria as in the household survey, but with additional considerations for fieldworker safety and security.

While not statistically representative at the national or regional levels, the survey includes a range of community settings illustrative of the diversity of the country. Appendix 1 of the survey report (provided under related materials) provides a description of the 30 school-survey sites.

Mode of data collection

Face-to-face interview; Self-completion; Educational measurements; Observation

Research instrument

The instruments included in the survey are:

• Principal questionnaire: Administered individually by fieldworkers to principals.
• School site observation: Fieldworker completed through observation of school site during their time in the school.
• Teacher questionnaire: Administered individually by fieldworkers to teacher of YL child's class.
• Pupil questionnaire: Administered to the whole class. Fieldworker led and directed. Collected background data on the Pupil, as well as information on attitudes to school.
• Pupil assessments in Maths and Amharic: Administered to the whole class. Fieldworker led and directed.

Survey documentation and questionnaires are provided as related materials, and can also be downloaded from http://www.younglives.org.uk/content/ethiopia-school-survey

Abstract copyright UK Data Service and data collection copyright owner.

The Young Lives survey is an innovative long-term project investigating the changing nature of childhood poverty in four developing countries. The study is being conducted in Ethiopia, India, Peru and Vietnam and has tracked the lives of 12,000 children over a 20-year period, through 5 (in-person) survey rounds (Round 1-5) and, with the latest survey round (Round 6) conducted over the phone in 2020 and 2021 as part of the Listening to Young Lives at Work: COVID-19 Phone Survey.
Round 1 of Young Lives surveyed two groups of children in each country, at 1 year old and 5 years old. Round 2 returned to the same children who were then aged 5 and 12 years old. Round 3 surveyed the same children again at aged 7-8 years and 14-15 years, Round 4 surveyed them at 12 and 19 years old, and Round 5 surveyed them at 15 and 22 years old. Thus the younger children are being tracked from infancy to their mid-teens and the older children through into adulthood, when some will become parents themselves.

The 2020 phone survey consists of three phone calls (Call 1 administered in June-July 2020; Call 2 in August-October 2020 and Call 3 in November-December 2020) and the 2021 phone survey consists of two additional phone calls (Call 4 in August 2021 and Call 5 in October-December 2021) The calls took place with each Young Lives respondent, across both the younger and older cohort, and in all four study countries (reaching an estimated total of around 11,000 young people).
The Young Lives survey is carried out by teams of local researchers, supported by the Principal Investigator and Data Manager in each country.

Further information about the survey, including publications, can be downloaded from the Young Lives website.

School Survey:
A school survey was introduced into Young Lives in 2010, following the third round of the household survey, in order to capture detailed information about children’s experiences of schooling. It addressed two main research questions:

• how do the relationships between poverty and child development manifest themselves and impact upon children's educational experiences and outcomes?
• to what extent does children’s experience of school reinforce or compensate for disadvantage in terms of child development and poverty?

The survey allows researchers to link longitudinal information on household and child characteristics from the household survey with data on the schools attended by the Young Lives children and children's achievements inside and outside the school. A wide range of stakeholders, including government representatives at national and sub-national levels, NGOs and donor organisations were involved in the design of the school survey, so the researchers could be sure that the ‘right questions’ were being asked to address major policy concerns. This consultation process means that policymakers already understand the context and potential of the Young Lives research and are interested to utilise the data and analysis to inform their policy decisions. The survey provides policy-relevant information on the relationship between child development (and its determinants) and children’s experience of school, including access, quality and progression. This combination of household, child and school-level data over time constitutes the comparative advantage of the Young Lives study.

The School Survey data are held separately for each country. The India data are available from the UK Data Archive under SN 7478, the Peru data have been archived under SN 7479, and the Vietnam data are available from SN 7663.

A further round of school surveys took place during the 2016-2017 school year. The Ethiopia survey is available under SN 8358, the India survey under SN 8359 and the Vietnam survey under SN 8360.

Further information is available from the Young Lives School Survey webpages.


Main Topics:

The survey included data collection at the school, class and pupil level, and involved the Principal, the teacher of Grade 4 and 5 class, and pupil. The instruments included in the survey are:

• Principal questionnaire. Administered individually by fieldworkers to principals.
• School site observation. Fieldworker completed through observation of school site during their time in the school.
• Teacher questionnaire. Administered individually by fieldworkers to teacher of YL child's class.
• Pupil questionnaire. Administered to the whole class. Fieldworker led and directed. Collected background data on the Pupil, as well as information on attitudes to school.
• Pupil assessments in Maths and Amharic. Administered to the whole class. Fieldworker led and directed.

These data were generated as part of a two-and-a-half-year ESRC-funded research project examining the digitalisation of higher education (HE) and the educational technology (Edtech) industry in HE. Building on a theoretical lens of assetisation, it focused on forms of value in the sector, and governance challenges of digital data. It followed three groups of actors: UK universities, Edtech companies, and investors in Edtech. The researchers first sought to develop an overview of the Edtech industry in HE by building three databases on Edtech companies, investors in Edtech, and investment deals, using data downloaded from Crunchbase, a proprietary platform. Due to Crunchbase’s Terms of Service, only parts of one database are allowed to be submitted to this repository, i.e. a list of companies with the project’s classification. A report offering descriptive analysis of all three databases was produced and is submitted as well. A qualitative discursive analysis was conducted by analysing seven documents in depth. In the second phase, researchers conducted interviews with participants representing three groups of actors (n=43) and collected documents on their organisations. Moreover, a list of documents collected from Big Tech (Microsoft, Amazon, and Salesforce) were collected to contextualise the role of global digital infrastructure in HE. Due to commercial sensitivity, only lists of documents collected about investors and Big Tech are submitted to the repository. Researchers then conducted focus groups (n=6) with representatives of universities (n=19). The dataset includes transcripts of focus groups and outputs of writing by participants during the focus group. Finally, a public consultation was held via a survey, and 15 participants offered qualitative answers.

The higher education (HE) sector has been marketised for decades; but the speed, scope, and extent of marketisation has led key education scholars to conceptualise it as a global industry (Verger, Lubienski, & Steiner-Khamsi, 2016). Further, the use of technology to transform teaching and learning, as well as the profound digitalisation of universities more broadly, has led universities to collect and process an unprecedented amount of digital data. Education technology (EdTech) companies have become one of the key players in the HE industry and the UK has made EdTech one of its key pillars in its recent international education strategy (HM Government, 2019). EdTech companies are reporting unprecedented growth. In 2019, Coursera became a 'unicorn' (i.e. a company worth over $1 billion), while British-based FutureLearn secured £50 million investment by selling 50% shares of the company. Investment in EdTech is growing at an impressive rate and reached $16.3bn in 2018 (ET, 2019). While EdTech start-up companies strive to become 'unicorns' and profit from HE, so too might universities increasingly look for new ways of profiting from the wealth of digital data they produce.

The study of HE markets has so far focused on service-commodities. However, data and data products do not act like commodities. Commodities are consumed once used, but data is reproducible at almost zero marginal cost. New products and services can be created from data and monetised through subscription fees, an app, or a platform that does not transfer ownership, control, or reproduction rights to the user. Furthermore, data use creates yet more data, and the network effects increase the value of these platforms. Therefore, there is a new quality at play in the monetisation and marketisation of these digital HE products and services: 'assetization'. We are witnessing a widespread change from creating value via market exchange towards extracting value via the ownership and control of assets.

This research project aims to investigate these new processes of value creation and extraction in an HE sector that is digitalising its operations and introducing new digital solutions premised on the expansion of service fees. By introducing a focus on assets, and economic rents, this project offers a theoretically and empirically transformative approach to understand emerging HE markets and their implications for the HE sector. The assetization of HE is consequential because of the legal and technical implications for its regulation. It is also crucial to examine in any discussion about the legitimate and socially just arrangement and distribution of assets, their ownership, and their uses. The project employs an innovative, comparative, and participatory mixed-methods research design. It combines digital methods, interviews, observation, document analysis, deliberative focus groups, knowledge exchange and co-production with stakeholders, and public consultation. Data analysis will include quantitative and qualitative analysis of investment trends, comparative case studies of investors, EdTech companies and universities, and social network analysis.

The application of this...

This dataset classifies statistical areas (lower super output areas or LSOAs) in Cheshire East on either a two level classification - rural or urban - or a six level classification; rural, predominantly rural, more rural than urban, more urban than rural, predominantly urban and urban. A methodology document explains how the classifications were created. A map of the classifications is also available.Six variables are used to create the classification, four of these come from the census:1. Proportion (aged 16-74) of employment in agriculture 2. Average number of cars per household 3. Population density - people per hectare 4. Proportion (aged 16-74) self-employed of those economically active 5. Access to services – this includes road distances to; a GP surgery, a supermarket or convenience store, a primary school and distance to a Post Office6. Buildings as a proportion of all land useThe classification will be updated following the release of the 2021 Census in 2022-23.There are many definitions of areas within Cheshire East classifying them into varying degrees of rural or urban. Organisations such as the Countryside Agency, DEFRA, the Office for National Statistics and central government each produced their own classification. The indicators used and available geographies are different. Several local definitions also existed. To remedy this, a local classification was developed.

Siyakha Nentsha (SN) was a randomised experiment that targets young people in KwaZulu-Natal province, South Africa. The program addressed the real-life economic, social and health challenges young people encounter on a daily basis. The educational programme developed for the intervention was accredited by the South African Qualifications Authority (SAQA, the national government body that accredits education and training curricula) meaning that not only will young people who complete the program have received valuable skills, but that they have documentation of these skills that can be used in future job searches. Siyakha Nentsha was delivered in secondary schools during school hours. It was led by young adult mentors who were chosen from the local community and received extensive training. Sessions with students occurred 2-3 times per week and each was approximately one hour in length. The long-term objective of the programme is to improve lifelong functional capabilities and well-being of adolescent females and males who face high risks for HIV, teenage pregnancy, school dropout, and unemployment, coupled with the actual or potential loss of one or both parents. The skills are geared to help offer protective strategies against HIV and mechanisms for coping with and mitigating the impacts of AIDS, with the long-term goal of building economic, social and health assets.

The study has three intervention arms: control, partial intervention and full intervention. These arms were randomised at the classroom level for 10th and 11th graders in Round 1 in seven secondary schools. One school that received a delayed intervention served as the control sample. The two versions of the intervention differ in that the full version includes HIV/AIDS education, social capital building, and financial capabilities, whereas the partial version omits the financial capabilities component. The study began in January 2008 and lasted for 36 months, with measures on individual students at baseline and post-intervention. The number of individuals who were part of at least Round 1 or Round 2 is 1,307. Individuals can be uniquely identified with the variables qnum (round 1) and IDNUM (round 2).

Further information may be found on the ESRC Enhancing the economic, health and social capabilities of highly vulnerable youth award webpage.