{"type":"survey","doc_desc":{"title":"KEN_2007_SACMEQ-III_v01_M","idno":"DDI_KEN_2007_SACMEQ-III_v01_M_WB","producers":[{"name":"Development Economics Data Group","abbreviation":"DECDG","affiliation":"The World Bank","role":"Documentation of the DDI"}],"prod_date":"2014-06-03","version_statement":{"version":"Version 01 (June 2014)"}},"study_desc":{"title_statement":{"idno":"KEN_2007_SACMEQ-III_v01_M","title":"Southern Africa Consortium for Monitoring Educational Quality 2007","sub_title":"SACMEQ-III Project","alt_title":"SACMEQ-III 2007"},"authoring_entity":[{"name":"Southern and Eastern Africa Consortium for Monitoring Educational Quality (SACMEQ)","affiliation":""}],"production_statement":{"copyright":"Copyright, Southern and Eastern Africa Consortium for Monitoring Educational Policy","funding_agencies":[{"name":"United Nations Educational, Scientific and Cultural Organization","abbreviation":"UNESCO","role":"Funding the project"},{"name":"Netherlands Government","abbreviation":"","role":"Funding and Technical Support"},{"name":"Ministries of Education","abbreviation":"","role":"Funding the project"}]},"distribution_statement":{"contact":[{"name":"Director- Southern Africa Consortium for Monitoring Educational Quality","affiliation":"International Institute for Educational Planning - UNESCO","email":"info@sacmeq.org","uri":"http:\/\/www.sacmeq.org"},{"name":"International Institute for Educational Planning","affiliation":"United Nations Educational, Scientific and Cultural Organization (UNESCO)","email":"info@iiep.unesco.org ","uri":"http:\/\/www.iiep.unesco.org"}]},"series_statement":{"series_name":"Socio-Economic\/Monitoring Survey [hh\/sems]","series_info":"The origins of the Southern and Eastern Africa Consortium for Monitoring Educational Quality (SACMEQ) date back to 1991, the year when several Ministries of Education in Eastern and Southern Africa started working closely with UNESCO's International Institute for Educational Planning (IIEP) on the implementation of integrated educational policy research and training programmes.\n\nIn 1995 these Ministries of Education formalized their collaboration by establishing a network that is widely known as SACMEQ. Fifteen Ministries are now members of SACMEQ: Botswana, Kenya, Lesotho, Malawi, Mauritius, Mozambique, Namibia, Seychelles, South Africa, Swaziland, Tanzania (Mainland), Tanzania (Zanzibar), Uganda, Zambia, and Zimbabwe.\n\nThe Southern and Eastern Africa Consortium for Monitoring Educational Quality (SACMEQ) undertook three large-scale, cross-national studies of the quality of education: SACMEQ I (1995-1999, reading) with seven ministries; SACMEQ II (2000-2004, reading and mathematics) with 14 ministries; and SACMEQ III (2006-2010, reading, mathematics, and pupil and teacher knowledge about HIV and AIDS) with 15 ministries."},"version_statement":{"version":"- v2.1: Edited, anonymous dataset for public distribution.","version_date":"2007"},"study_info":{"topics":[{"topic":"basic skills education [6.1]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"}],"abstract":"The SACMEQ III Project commenced in 2006 and was completed during 2011. The SACMEQ III data collection was implemented in fifteen SACMEQ Ministries of Education (Botswana, Kenya, Lesotho, Mauritius, Malawi, Mozambique, Namibia, Seychelles, South Africa, Swaziland, Tanzania (Mainland), Tanzania (Zanzibar), Uganda, Zambia, and Zimbabwe). The SACMEQ III Project followed the general research direction of the first two SACMEQ Projects by focusing on an examination of the conditions of schooling in relation to achievement levels of learners and their teachers in reading, and mathematics. The focus was expanded to cover the learners\u2019 levels of basic knowledge about HIV and AIDS. The SACMEQ III Project involved data collections from around 61,000 learners, 8,000 teachers, and 2,800 school principals.","coll_dates":[{"start":"2007-09","end":"2007-12","cycle":""}],"nation":[{"name":"Kenya","abbreviation":"KEN"}],"geog_coverage":"National Coverage","geog_unit":"The lowest level of geographic aggregation covered by the data is province, and in some cases, metropolitan area.","analysis_unit":"- Pupils\n- Schools\n- Teachers","universe":"The desired target population for the SACMEQ III study was defined as \"All pupils at Grade 6 level in 2007 (at the first week of the eighth month of the school year) who were attending registered mainstream primary schools\". This definition used a grade-based description (and not an age-based description) of pupils because an age-based description would have required the collection of data across many grade levels due to the high incidences of \"late starters\" and grade repetition in SACMEQ school systems.\n\nExcluded and Defined Target Populations\nThe use of the word \"mainstream\" in the definition of the desired target population automatically indicated that special schools for the handicapped should be excluded from the SACMEQ II data collection. In addition, a decision was taken to exclude small schools - based on the definition of having less than either 15 or 20 pupils in the desired target population. Small schools were excluded because it was known that they represented a very small component of the total population of pupils, and were known to be mostly located in very isolated areas that were associated with high data collection costs. That is, it was understood that the allocation\nof these small schools to the excluded population had the potential to reduce data collection costs - without the risk of leading to major distortions in the study population. The exclusion rule that was applied in Kenya was schools with less than 15 Standard 6 pupils and Special Schools. The \"defined target population\" was constructed by removing the \"excluded target population\" from the \"desired target population\".","data_kind":"Sample survey data [ssd]","notes":"Data was collected on pupils\u2019 home backgrounds and their school life; classrooms, teaching practices, teachers' working conditions, and teacher housing; enrolments, school buildings and facilities, and school management.","study_scope":"Data was collected on pupils\u2019 home backgrounds and their school life; classrooms, teaching practices, teachers' working conditions, and teacher housing; enrolments, school buildings and facilities, and school management."},"method":{"data_collection":{"data_collectors":[{"name":"Ministry of Education","abbreviation":"","affiliation":""}],"sampling_procedure":"The desired target population definition for the SACMEQ III Project was exactly the same (except for the year) as was employed for the SACMEQ I and II Projects. This consistency was maintained in order to make valid cross-national and cross-time estimates of \"change\" in the conditions of schooling and the quality of education.\n\nThe SACMEQ III data were selected using a stratified two-stage cluster sample design based on the technique of a lottery method of sampling proportional to size, with the assistance of SAMDEM software (Sylla et al., 2003). At the first stage, schools were selected in each region (province) in proportion to the number of pupils in that region in the defined target population. The main reason for choosing Region as the explicit stratification variable was that the SACMEQ Ministries of Education wanted to have education administration regions as \"domains\" for the study. That is, the Ministries wanted to have a reasonably accurate sample estimates of population characteristics for each region. At the second stage, a simple random sample of 25 pupils was taken within each selected school (in the Seychelles, all Grade 6 pupils in all 25 schools in the island country were tested).\n\nIn educational survey research the primary sampling units that are most often employed (schools) are rarely equal in size. This variation causes difficulties with respect to the control of the total sample size when schools are selected with equal probability at the first stage of a multi-stage sample design. One method of obtaining greater control over the total sample size is to stratify the schools accorging to size and then select samples of schools within each stratum. A more widely applied alternative is to employ probability proportional to size (PPS) sampling of schools within strata followed by the selection of a simple random sample size and results in epsem sampling of pupils within strata. The lottery method of PPS selection was implemented for the SACMEQ Projects with the assistance of the SAMDEM software (Sylla et al, 2003).\n\nIn order to avoid selection bias, precautions were taken to ensure that school heads and teachers did not have any influence over the sampling procedures within schools. This is because school heads and teachers might have felt they had a vested interest in selecting particular kinds of pupils, and this could have resulted in major distortions of sample estimates (Brickell, 1974). \n\nThe Stratification Procedures (Kenya)\ni) The Province\nThe explicit stratification variable, \"Province\", was applied by separating each sampling frame into separate regional lists of schools prior to undertaking the sampling. The main reason for choosing Province as the explicit stratification variable was that the Ministry of Education wanted to have education administration regions as \"domains\" for the study so as to have reasonably accurate sample estimates of population characteristics for each province. At the time of conducting of this study, the Province was the second tier of the administrative structure and thus sufficient data differentiation was possible to allow specific actions and follow-up in the respective regions.\n\nii) The Selection of Schools\nIn order to obtain greater control over the total sample size, stratification of the schools according to size was done, after which samples of schools were selected within each stratum. This technique is known as Probability Proportional to Size (PPS) sampling which also involved the selection of a simple random sample of a fixed number of pupils within selected schools.\n\niii) The Selection of Pupils within Schools\nA critical component of the sample design for the SACMEQ III Project was concerned with the selection of pupils within selected schools. It was decided that these selections should be placed under the control of trained data collectors - after they were provided with materials that would ensure that a simple random sample of pupils was selected in each school. Class registers for all Standard 6 pupils that attended regular classes were obtained by the data collectors. In the register, each pupil would be assigned a number after which the numbers were selected using a random number table that had been prepared for this purpose. The names of sampled pupils who totalled 20 in each school were written. The sampled pupils were thus called out to participate in the data collection process.","coll_mode":"Face-to-face [f2f]","research_instrument":"- Apart from pupil achievement scores, SACMEQ studies are renowned for collecting a wide range of information about pupils, teachers, classrooms, school heads, schools, and school communities. For the SACMEQ III study, four main questionnaires (pupil, teacher, school head, and school information) were used. \n- It is important to note that SACMEQ questionnaires were subjected to careful thought, thorough examination, and stringent refinement before they were administered. For example, for the SACMEQ III study, the questionnaires were developed by a committee of experts consisting of members drawn from all SACMEQ countries, SCC staff, IIEP staff, and private consultants, following \n(a) Field experiences gained from the SACMEQ II study, \n(b) Recommendations arising from analyses of SACMEQ II data, and (c) policy questions raised by SACMEQ country ministries of education. These questionnaires were refined by the SACMEQ scientific committee, then piloted in each SACMEQ country and refined further before they were administered.\n- One important innovation in the development of questionnaires for the SACMEQ III study was introduction of a \u201cHomework form\u201d for pupils to take home. This consisted of questions to which the pupil might not know the answers (for example, parental education, estimates of travel distance to school, home possessions, whether or not their biological parents were alive) that parents, family members, or guardians could help in filling in. This considerably reduced the number of missing values in the SACMEQ III study compared with previous SACMEQ studies.\n- Materials were translated into Kiswahili (Tanzania Mainland and Zanzibar) and Portuguese (Mozambique).","coll_situation":"According to the National Research Coordinators (NRC) manual, The training of Data Collectors could either be conducted centrally by the NRCs (in the case of small states) or had to be conducted in several sites in the country. After the training, these Data Collectors would be deployed as Data Collectors in the sampled schools.\n\n- The main SACMEQ III data collection occurred for most SACMEQ Ministries of Education in the period September to December 2007. In Kenya, data was collected in September 2007 in 193 sample schools that were involved. \n- Two days of data collection were required for each sample school. On the first day the data collectors had to sample learners from all the Standard 6 classes in the sampled schools, using a list of provided random numbers. The sampled learners were then given the learner questionnaire, the HAKT and the Reading test. On the second day they were given the Mathematics test. Part of the learner questionnaire required learners to get confirmation of the accuracy of the information from their parents and so the questionnaire was taken home and returned the following day.","weight":"The calculation of sampling weights could only be conducted after all files had been cleaned and merged. Sampling weights were used to adjust for missing data and for variations in probabilities of selection that arose from the application of stratified multi-stage sample designs. There were also certain country-specific aspects of the sampling procedures, and these had to be reflected in the calculation of sampling weights.\n\nTwo forms of sampling weights were prepared for the SACMEQ III Project. \nThe first sampling weight (RF2) was the inverse of the probability of selecting a learner into the sample. These \u201craising factors\u201d were equal to the number of learners in the defined target population that were \u201crepresented by a single learner\u201d in the sample. The second sampling weight (pweight2) was obtained by multiplying the raising factors by a constant so that the sum of the sampling weights was equal to the achieved sample size. A detailed account of weighting procedures can be found in Ross et al (2003).","cleaning_operations":"Data Entry was done using WinDEM (Windows Data Entry Manager) Software. Preliminary data cleaning involved checks on data to ensure it was clean before it was sent to the SACMEQ Coordinating Centre (SCC) for further checks an analysis and calculation of sampling weights. (See p12 of the NRC Manual - provided as external resources - for more detail on the process.)\n\nThe Kenyan NRT received the completed materials from the provincial coordinators and kept these safely while they were being checked, entered into computers, and then \u201ccleaned\u201d to remove errors prior to data analysis. Data- checking involved the \u201chand editing\u201d of data collection instruments by a team of trained staff. The staff checked that: \n(i) All expected questionnaires, tests, and forms had been received, \n(ii) The identification numbers on all instruments were complete and accurate, and \n(iii) Certain logical linkages between questions made sense (for example, they had to verify if the two questions to School Heads concerning \u201cDo you have a school library?\u201d and \u201cHow many books do you have in your school library?\u201d were answered consistently).\n\nTrained data capturers, supervised by the NRT, entered data into computers using the WINDEM software that was supplied by the SACMEQ Coordinating Centre. Data was \u201cdouble entered\u201d in order to monitor accuracy. Individual data capturers worked for a maximum of six hours per day, and the whole data entry operation for Kenya was estimated to involve around 75 person days of data entry.","method_notes":"During December 2007 the SACMEQ Coordinating Centre organized a training programme for all NRTs. The teams were led step-by-step through the required data cleaning procedures that they were to follow in their respective countries. At individual country level, NRTs followed a \u201ccyclical\u201d process whereby data files were cleaned by the NRT and then emailed to the Coordinating Centre for checking and then emailed back to the NRC for further cleaning. The entire data cleaning process in Kenya lasted ten months, from May 2008 to February 2009.\n\nTo clean the data, using the WINDEM software, the NRTs followed specific directions to \n(i) Identify major errors in the sequence of identification numbers, \n(ii) Cross-check identification numbers across files (for example, to ensure that all learners were linked with their own Life Skills, Reading and Mathematics teachers), \n(iii) Ensure that all schools listed on the original sampling frame also had valid data collection instruments and vice-versa,\n(iv)Check for \u201cwild codes\u201d that occurred when some variables had values that fell outside pre-specified reasonable limits, and \n(v) Validate that variables used as linkage devices in later file merges were available and accurate.\n\nMerging of data files\nWhen data cleaning was complete, the NRT merged the data from all the sources. The merging process required the construction of a single data file in which learners were the units of analysis and the rest of the data from the other respondents and linked to the learner data. That is, each record of the final data file for the country consisted of the following four components: \n(a)The questionnaire and test data for an individual learner, \n(b)The questionnaire and test data for his\/her Life Skills, Mathematics and Reading teacher, \n(c)The questionnaire data for his\/her School Head, and \n(d) School and learner \"tracking forms\" that were required for data cleaning purposes.\n\nTo illustrate, with the merged file it was possible to examine questions of the following kind: \"What are the average Reading and Mathematics test scores (based on information taken from the learner tests) for groups of learners who attend urban or rural schools (based on information taken from the School Head questionnaire), and who are taught by male or female teachers (based on information taken from the teacher questionnaire)?\" ."},"analysis_info":{"response_rate":"The technical requirement for the SACMEQ research programme was that all countries should seek to achieve overall response rates of 90 percent for schools and 80 percent for pupils. The SACMEQ III response rates presented in Table 2.2 of the Kenya National Report (provided as an external resource) indicates\nthat Kenya satisfied the required response rate for schools and pupils, at 98 and 91 percent, respectively.","sampling_error_estimates":"Design effect is a proportion (ratio) which indicates the amount of \u201csampling error\u201d that is introduced by the use of a clustered (two-stage) sampling method in relation to the \u201csampling error\u201d that would result if a simple random sample of the same size had been used. Alternatively, the \u201cdesign effect\u201d is the ratio of the variance (of the sample mean) for a multi-stage sample to the variance for a simple random sample of the same size. Applied to SACMEQ III, this means that for Reading the achieved two-stage sample of 4,436 had a variance (of the sample mean) which was 11.5 times the variance that would be realized if a simple random sample of the same size was used. For Mathematics this ratio was 9.4 while for HAKT it was 10.2. Generally, the inaccuracy associated with a multi-stage sample was many times greater than the inaccuracy associated with a simple random sample of the same size.","data_appraisal":"The quality of the data provided by the school heads, teachers, and pupils was examined in the following ways. \nFirst, at the time of data collection, the data collectors who visited the schools verified, for example, \n(a) the actual existence and conditions of the school resources such as library, school head office, and staff room, and \n(b) the official school records about the information provided by pupils such as their gender, age, days absent, and whether or not their parents were alive. \nSecond, similar questions were included in the school head, pupil, and teacher questionnaires, and these helped to verify the responses given by the respondents during data cleaning. For example, a question on the existence of a class library was included in both the teacher and pupil questionnaires. Any inconsistencies between the responses of the school heads, teachers, and pupils were followed up by the national research coordinators (NRCs) and corrected during data cleaning.\nThe processes of generating pupil scores, competency levels, measure of school location, socioeconomic status and tabulations are outlined in the SACMEQ-III Project Results Working Document Number 1 available as external resources."}},"data_access":{"dataset_use":{"conf_dec":[{"txt":"Before being granted access to the dataset, all users have to formally agree: \n1. To make no copies of any files or portions of files to which s\/he is granted access except those authorized by the data depositor. \n2. Not to use any technique in an attempt to learn the identity of any person, establishment, or sampling unit not identified on public use data files. \n3. To hold in strictest confidence the identification of any establishment or individual that may be inadvertently revealed in any documents or discussion, or analysis. Such inadvertent identification revealed in her\/his analysis will be immediately brought to the attention of the data depositor.","required":"yes","form_no":"","uri":""}],"contact":[{"name":"Director- Southern Africa Consortium for Monitoring Educational Quality (SACMEQ)","affiliation":"International Institute for Educational Planning - UNESCO","email":"info@sacmeq.org","uri":"http:\/\/www.sacmeq.org"}],"cit_req":"Citation requirement is the way that the dataset should be referenced when cited in any publication. Every dataset should have a citation requirement. This will guarantee that the data producer gets proper credit, and that analytical results can be linked to the proper version of the dataset. The Access Policy should explicitly mention the obligation to comply with the citation requirement. The citation should include at least the primary investigator, the name and abbreviation of the dataset, the reference year, and the version number. Include also a website where the data or information on the data is made available by the official data depositor.\n\nExample:\n\nSouthern and Eastern Africa Consortium for Monitoring Educational Quality. SACMEQ Project III 2007 [dataset]. Harare: SACMEQ [producer], 2007. Paris: International Institute for Educational Planning, UNESCO [distributor], 2007. Ref. KEN_2007_SACMEQ-III_v01_M. Dataset downloaded from [URL] on [date].","conditions":"TERMS AND CONDITIONS FOR USE OF THE SACMEQ DATA ARCHIVE\n \n1.0 Introduction \n \nThe Southern and Eastern Africa Consortium for Monitoring Educational Quality (SACMEQ) Co-ordinating Centre (SCC ) has produced a data archive containing all information collected for SACMEQ's first three educational policy research projects (SACMEQ I, SACMEQ II, and SACMEQ III). This archive is now available online on the SACMEQ website so as to give bona fide researchers and students online access to SACMEQ data and documents.\n \nThe SACMEQ data sets have been developed at great cost and with the application of stringent quality controls. It is being made available to eligible users because it has a great potential to contribute to educational policy development beyond what has already been achieved in this respect through the reports written by the National Research Co-ordinators (NRC s) and Deputy National Research Coordinators (NRC s). It is expected that many researchers and students will wish to use the Data Archive for research, publications, and\/or training purposes. \n \nThe Terms and Conditions serve two purposes. Firstly, they provide interested applicants with guidelines on how to access this valuable information resource. Secondly, they are intended to safeguard against the danger of users being unaware of the complexities of the data collection process and consequently arriving at misinterpretations that could lead to incorrect conclusions.\n \n2.0 How can the user gain such access? \n\nIn order to obtain SACMEQ Data Archive for any of the SACMEQ school systems, the applicant should follow these steps:\n \n2.1 Read and Agree to these \"Terms and Conditions for the Use of the SACMEQ Data Archive.\"\n \n2.2 Complete an online application form.\n3.0 What rules govern the use of the SACMEQ data archive? \n \n3.1 The Data Archive is the outcome of expensive and time-consuming activities of the staff of the represented Ministries of Education spread over many years. For this reason, the SACMEQ Ministries of Education described in the Data Archive should: \n \n3.1.1 be notified by the SACMEQ SCC of any request for data; \n \n3.1.2 have an opportunity to review reports based on the data archive so as to correct any gross errors before they are published; and \n \n3.1.3 satisfy themselves that the data have been used in such a manner that they contribute positively to the development of relevant education policies in relevant SACMEQ member countries. \n \n3.2 It is the National Research Coordinators (NRC s) and Deputy National Research\nCoordinators (DNRCs) who have spearheaded the collection and compilation of SACMEQ data. In acknowledgment of their efforts, the applicant(s) will be required to invite the relevant country's National Research Coordinator to participate in the study associated with the use of the data. Where an individual other than the NRC or DNRC is co-opted, the relevant NRC and DNRC shall be given the first right of refusal. \n \n3.3 This provision does not apply in situations where the SACMEQ Data Archive is used purely for purposes of individual academic research by a student, and where the results are not intended for publication. \n \n3.4 All relevant NRC s and DNRCs will be informed by the SCC about the recipients of the Data Archive. \n \n3.5 SACMEQ provides the SACMEQ Data Archive to applicants on the basis of the intended use stated in the application. The applicant, therefore, should not use the data for any purpose other than the one stated in the application. Should the applicant(s) wish to use the data for a purpose other than that stated in the agreement, then he\/she\/they must first secure the written approval of SACMEQ before he\/she\/they proceed to do so. \n \n3.6 SACMEQ data are provided for the sole and exclusive use of the applicant specified in the agreement. The successful applicant should, therefore, not share the SACMEQ Data Archive with, or pass it on to, any other unauthorized person(s). \n \n3.7 The authorized user shall take responsibility for the safe custody of the SACMEQ Data Archive and also take reasonable steps to ensure that no unauthorized persons gain access to it. \n \n3.8 The authorized user shall give due credit to SACMEQ for providing the Data Archive by providing written acknowledgement of this in any publication emanating from their use. \n \n3.9 As the Data Archive remains the property of the SACMEQ, no other person(s), including the successful applicants or the member Ministry, shall re-distribute or offer for sale the SACMEQ Data Archive. \n \n3.10 All reports based on the SACMEQ Data Archive have to secure the written approval of the SCC prior to the publication in order to confirm compliance to our terms and conditions, and also to ensure that there is no misunderstanding or misinterpretation of the data.\n \n3.11 Once authorization has been granted to access the archive, you will see a link on the website which will take you to the Data Archive.\n \n3.12 All relevant NRC s will be informed by the SCC about the recipients of the SACMEQ Data Archive.\n \n3.13 Full acknowledgement of the source of the data (including reference to the SACMEQ Data Archive) must be given whenever the data are used.\n \n3.14 A copy of any published article or report based on the SACMEQ Data Archive must be provided free of charge to (a) the SACMEQ Co-ordinating Centre, and (b) the Ministry(ies) of Education from whose data the report has been generated.","disclaimer":"The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses."}}},"data_files":[{"file_id":"F1","file_name":"sacmeq15_final_ken","description":"SACMEQ-III Data for Kenya\n- Kenya data extracted from sacmeq15_final.sav","case_count":"4436","var_count":"2317","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null}],"variables":[{"vid":"V1","name":"country","file_id":"F1","var_intrvl":"discrete","var_start_pos":"1","var_end_pos":"3","var_width":"3","var_rec_seg_no":"1","labl":"COUNTRY 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