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Are Our Children Learning? Numeracy and Literacy across East Africa
Uwezo is an East African ini a ve hosted by TEN/MET in Tanzania, WERK in Kenya and UNNGOF in Uganda, with overall quality assurance and management support from Twaweza/Hivos. This report is produced by the Uwazi unit based at Twaweza. The principal authors are Hans Hoogeveen and Dorica Andrew. The assistance of Fenohasina Mareth in preparing data sets and crea ng a first set of tables and graphs is gratefully acknowledged. Sara Ruto and Rakesh Rajani provided overall guidance and quality assurance. Edi ng support was provided by Stephanie McDonald and Maggie Bangser. All data used in the report were provided by Uwezo and can be downloaded from www.uwezo.net. Cover Ph
Uwezo East Africa (managed by Twaweza) P.O Box 19875, 00200 Nairobi, Kenya Tel: +254 20 3861372 Email: email@example.com Web: www.uwezo.net
Twaweza East Africa 127 Mafinga Rd, Off Kinondoni Rd P.O Box 38342, Dar es Salaam, Tanzania Tel: +255 22 266 4301. Fax +255 22 266 4308 Email: firstname.lastname@example.com Web: www.twaweza.org Email: email@example.com Web: www.uwazi.org
Foreword This work provides us with well researched results on the performance of the education system in terms of literacy and numeracy. Uwezo and Twaweza have demonstrated a great deal of strength and high levels of quality in collecting, analyzing and interpreting the basic statistics on education and overall ability of children in literacy and numeracy. The key findings illustrate the magnitude of work that lie ahead of all us, and particularly if the region is to achieve accelerated development operating in the current knowledge based and fiercely competitive world. At the EAC level, co-operation in the development of human resources, science and technology is one of the pillars that are crucial to achieving the objectives of the Community. Article 102 of the Treaty for Establishing the East African Community spells out how the Partner States agree to undertake concerted measures to foster co-operation in education and training within the Community. In order to undertake such measures at both the regional and national levels, enormous information is required to develop and implement the desired policies and strategies. Therefore, the importance of information collected during the survey on the literacy and numeracy across the three East African countries covered in this report will greatly help the Partner States in their pursuit for a well developed and harmonized education system; not least in the harmonization of curricula, examination, certification and accreditation of education and training institutions. Of special interest in the report is its reference to very important issues of gender, curriculum development, private sector involvement and standards of promotion to the next grade. All these are very important areas for the EAC Partner States who are engaged in the implementation of key policies in the area of basic education and training, most especially the policy of universal education that requires well researched work to inform decisions thereof. The report further analyses the relationship between household income and education parameters such as performance, school drop outs, enrollment by gender, age, etc. For decades, we have used enrollment rates as a key marker of progress in education. The Uwezo report demonstrates that this is not enough, because children who are in school are still unable to read and count, which are the basic foundations for learning and development. Nevertheless, the results in this report would be useful in the ongoing process of harmonization of education and training policies in the region. For instance, information collected under this survey after verification and validation can well be used in legislation review and amendment at both regional level and national levels. It is my expectation that this commendable work will be used by a wide range of interested parties and that Uwezo and Twaweza will continue to distinguish itself as a key player in this area. The exercise also poses a challenge of quality of output. Whereas expanding school enrollment is fundamental, the most important element of measure of success is to verify whether the children attending school are actually learning. This is an area worth further work by Uwezo and Twaweza. It is also my hope that the next exercise of this nature will cover all five Partner States of the East African Community.
Dr. Richard Sezibera Secretary General East African Community June 2011
1. Introduction Few question the importance of learning, for its own right and to prepare future generations to lead productive and fullfilling lives. The Governments of Tanzania, Uganda and Kenya subscribe to this view. All three countries have adopted free primary education policies in the expectation that this will allow all children to go to school and, at the very least, become numerate and literate citizens. To achieve this goal, large amounts of money have been and continue to be invested into primary education. For instance, in 2009/10, Tanzania's government allocated 14% of its budget (or 4% of GDP) to primary education alone.1 Kenya and Uganda spends similarly high amounts, and in each country the budgets for education have risen significantly in absolute terms in the last decade. In each of the three countries the (re‐)introduction of free primary education was followed by significant increases in the number of children going to school. This is illustrated by the gross enrollment ratios shown in Figure 1 (the gross enrollment ratio is the total number of children attending primary school over the age group of children that are expected to attend primary school). In Uganda, where free primary education was reintroduced first in East Africa in 1997, gross enrollment went up from slightly less than 70% in 1997 to over 120% in 2000. In Tanzania, after the abolishment of school fees in 2001, gross enrollment went up from around 70% to about 110%. In Kenya the increase was less pronounced, mostly because enrollment was already high, but here too gross enrolment rose to about 105% following the re‐introduction of free primary education in 2003. Figure 1: Gross enrollment in primary schools 1990‐2008 160 140 120 100 80 60 40 20
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Source of data: UNESCO Institute for Statistics2
Impressive progress in enrollment has allowed attention to shift from providing access to focusing on learning. Do all these children who now go to school indeed become numerate and literate? Do the significant investments governments make in primary education yield the return policy makers and parents expect? To assess the degree of literacy and numeracy of school‐age children, Uwezo conducted surveys in Kenya, Tanzania and Uganda, testing tens of thousands of children in a home environment. The tests used were Standard 2 level tests for English, Kiswahili and numeracy, designed in accordance with 1 2
Basic Education Statistics in Tanzania 2010 http://stats.uis.unesco.org Are Our Children Learning? | 1
national curricula. This report uses these data to assess how school age children performed on the Uwezo tests across the three countries. The main finding is that performance across the three countries was poor. Very poor in fact. The majority of children in Standard 3, who should all have acquired Standard 2 level literacy and numeracy skills, were unable to complete the Uwezo tests. A comparison of the three countries demonstrates that children in Kenya performed best and those in Tanzania worst. The analysis also shows that in Kenya and Uganda pupils who reached Standard 7 were almost universally competent at the Standard 2 level. This was less the case in Tanzania, where only between 50% to 80% of pupils in Standard 7 managed to succesfully complete the Standard 2 level Uwezo tests. This report considers other aspects as well. It compares access to primary school across the three countries, contrasts performance in public and private schools, and considers differences by gender, school quality and household wealth. The remainder of the report is organized as follows. In section 2 more detail is provided about the Uwezo tool, when and how it was administered and the degree to which the tests are comparable across the three countries. Section 3 considers access to primary schools and section 4 discusses learning outcomes. Section 5 looks into school quality. Sections 6 and 7 discuss private schools and gender disparities respectively. Wheareas sections 4 through 7 consider the association between individual factors (gender, wealth, school quality) and performance in isolation, section 8 presents results from regression analyses, which provide an analysis of the impact of these factors in combination. Conclusions follow in section 9.
2. The Uwezo survey and tests Uwezo implemented large scale household surveys and assessed literacy and numeracy competency of children aged 6‐16 years (5‐16 in Tanzania) in the home environment. The Uwezo surveys are the largest sample‐based studies ever undertaken in the region. In addition the survey teams collected information from one school per village. In Kenya, the initial Uwezo survey was held in 2009. Information for 70 of Kenya's 158 (census) districts was collected and in total 68,945 children aged 6‐16 years from 40,286 households were tested. School information was collected from 2,030 public primary schools.3 In Uganda, the first Uwezo survey was conducted in 2010. It collected representative information for 27 districts (out of a total of 80 districts in Uganda at the time). A total of 810 villages and 16,200 households were visited and 34,752 children aged 6‐16 years were tested. In Tanzania, the survey was conducted in 2010. It covered 38 of 133 districts and 1,140 villages and 22,800 households were visited. In total, 42,033 children aged 5‐16 years old were tested. 3
Currently there are more districts in Kenya, but at the time of the survey, 158 districts had been gazetted and participated in the 2009 population census. Literacy and Numeracy Across East Africa | 2
Table 1: Uwezo survey in Kenya, Tanzania and Uganda, summary of key features Date of survey Number of districts Number of households Number of children tested Number of schools visited Age range Numeracy test Kiswahili test English test
Kenya Sept/Oct 2009 70 (out of 158) 40,386 68,945 2,030 6‐16 Yes Yes Yes
Tanzania May 2010 38 (out of 133) 22,800 43,033 1,140 5‐16 Yes Yes Yes
Uganda April 2010 27 (out of 80) 16,200 34,752 810 6‐16 Yes No Yes
Source of data: Uwezo national reports4 The tests used by Uwezo were of Standard 2 level, designed to be consistent with the requirements of each country's curriculum. In Kenya and Tanzania, children were tested for numeracy and literacy in Kiswahili and English. In Uganda, numeracy and literacy in English were tested. Standard 2 was selected because according to international standards, after completing two years of schooling a pupil is expected to have acquired basic competencies in literacy and numeracy, which are considered the foundations for learning in all other subjects in later years. All tests were designed such that pupils could be graded into different levels. The literacy test, for instance, distinguished between the ability to read letters, followed by words, a sentence or paragraph, and finally a story followed by comprehension questions. Similarly, the numeracy test starts with number recognition, addition, subtraction, multiplication and division. Children were also given a bonus "ethno‐mathematics" problem, based on typical daily tasks and presented in the child's preferred language. As the tests reflected national curricula, they were not directly comparable. Rather, a comparison of the test scores reflects whether children in each country mastered a Standard 2 level of their national education curriculum. In each of the countries, if the education system was working well, all children (100%) who are in Standard 3 should have acquired the Standard 2 level competencies. While not strictly comparable, the requirements for students in Standard 2 do not differ much among the three countries. This can be seen in Table 3 which presents the tests used in each of the countries. The Kiswahili test was comparable for Kenya and Tanzania, with the proviso that the comprehension questions for Tanzania seem slightly more difficult than those for Kenya. The English test was similar in the three countries, even though Tanzania's story was shorter and easier than those for Kenya and Uganda. The numeracy tests across the three countries were also comparable, except that Tanzania's test included additions with carry over, and subtractions with borrowing which were not asked in Kenya and Uganda. On the other hand, in Uganda and Kenya children were expected to do divisions which was not the case in Tanzania. Strictly speaking these tests only measured children's comptence in numeracy and literacy, and not learning. To assess learning, a measure of change, one would have to control for children's knowledge at the start of their school careers in Kenya,Uganda and Tanzania. In Uganda and Kenya, English is presumably more widely spoken than in Tanzania, so even if teaching is of equal quality in all three countries and the test of equal difficulty, one expects children in Kenya and Uganda to do better on the English test than children in Tanzania. The reverse could hold for Kiswahili, which is 4
Uwezo 2010, Are our children learning? Annual Learning Assessment Report. Kenya 2010; Uganda 2010; Tanzania 2010. All downloadable from www.uwezo.net Are Our Children Learning? | 3
more widely spoken in Tanzania than in Kenya and is generally not spoken in Uganda. Also, the level of education of parents is likely to lead to capability differences at entry. According to the Demographic and Health Surveys for instance, in Kenya 19% of mothers have no education; the corresponding numbers for Tanzania and Uganda are 33% and 23% respectively. If the home environment affects childrens' abilities at school entry, then differences in numeracy and literacy outcomes do not automatically translate into differences in learning. At the same time, one does expect a very close association between results on the numeracy and literacy tests and learning in school. In much of this report national statistics will be presented. This is justified as the sampling procedure selected districts randomly. Within districts, villages were selected randomly, and also within villages a careful randomization procedure was followed (though the procedure adopted in Tanzania left some choice to enumerators which may have led to some bias). To verify the degree to which Uwezo national results replicate results from other established national household surveys, Table 2 presents a small number of household characteristics, derived from Uwezo and other surveys. A comparison of the data for Uganda (which followed the strictest randomization procedure) yields a close match between Uwezo results and Demographic Household Survey (DHS) results. There are some differences in ownership of radios and televisions but these may just be a reflection of the four years that elapsed between the two surveys. Also for Kenya, the Uwezo results replicate the DHS results. There are some slight differences, as would be expected when comparing two sample surveys, but nothing major. If anything, the Uwezo sample in Kenya appears to be slightly skewed towards poorer, less well educated and less well endowed households. In Tanzania, on the other hand, larger differences can be discerned. Here the Uwezo sample seems to be skewed towards slightly better educated, better endowed households. In particular the difference in the fraction of mothers without education (30% in the Household Budget Survey (HBS); 14% in the Uwezo survey) is striking. Also the fact that Uwezo reports 19% of households with electricity versus 12% in the HBS is significant. In the remainder of this paper these issues will not be addressed, but the reader may want to keep in mind that the Tanzania sample may be skewed towards better off households, and the Kenya sample towards slightly worse off households. Table 2: Comparison of Uwezo national results with other national household surveys Mother's education No education Primary 1‐4 Primary 5‐7/8 Secondary 1‐4 Post secondary Assets & Electricity Electricity Radio TV
Tanzania Uwezo HBS 2010 2007 14 30 8 9 66 52 6 6 2 2 19 12 70 66 18 8
Kenya Uwezo DHS 2009 2009 24 19 53 60 23
11 73 22
23 74 28
Uganda Uwezo DHS 2010 2006 No information on mother's education in the Uwezo survey.
8 74 13
Source of data: Uwezo, DHS (Uganda and Kenya) and HBS (Tanzania)5
www.measuredhs.com; National Bureau of Statistics 2009; Household Budget Survey 2007.
Literacy and Numeracy Across East Africa | 4
9 61 6
Are Our Children Learning? | 5
come sing
good best
Recognition 10-99 87 31
Recognition 1-9 2 8
3b. English Test
3a. Numeracy Test
My home is small.
I like my school.
That dog is big.
This is my cat.
+ 12
- 15
- 60
- 55
- 42
Subtraction without borrowing
Subtraction with borrowing
x 5
x 4
8 ÷2 =
2 ÷2 =
6 ÷2 =
8 ÷2 =
15 ÷3 =
5 ÷1 =
Jane wants a rope which costs 250 shillings. John gives Jane 300 shillings. How much money will Jane remain with after buying the rope?
You have 80 shillings. How much will you be left with after buying a packet of flour which is sold for 60 shillings?
300 Shillings + 200 Shillings =
Ethno mathematics
3. What is the name of Juma's son?
2. What does Sara read?
Questions: 1. Where does Juma live?
Juma is living in a small village. He gets a letter once a month. The letter is from his son Musa. Musa lives in Dodoma. Juma cannot read the letters. He asks Sara to read the letters for him.
+68 +64
+25 +48
Addition without carry over Addition with carry over
Table 3: Samples of Numeracy, English and Kiswahili tests used by Uwezo
Literacy and Numeracy Across East Africa | 6
soko uso
mama kaka
vuta maziwa
mwa njo
chai sherehe
Naye baba analima shambani.
Maria anacheza mpira.
Juma anasoma kitabu.
Mama anapika uji.
2. Fatuma huwatembelea Nyanya na Babu wakati gani?
Maswali: 1. Mama ya Fatuma hufanya kazi gani?
Jina langu ni Fatuma Abdi. Ninaishi Nakuru na familia yetu kwenye nyumba kubwa. Baba yangu ni mwalimu katika shule ya upili. Wanafunzi wanampenda mama yangu kwakuwa ni mwalimu mzuri. Nao nyanya na babu wanaishi kule kijijini. Wao wana mbuzi na kondoo wengi. Mimi huwatembelea siku za likizo. Nyanya hunipa hadithi nzuri za kuchekesha. Mimi hucheka hadi mbavu zikaniuma. Likizo ikiisha, nyanya hunipa maziwa nimletee mama yangu.
3. Hadithi hii inatufundisha nini?
2. Zamani samaki walikuwa wanakula wadudu gani?
Miti huzuia upepo mkali.
Miti hutupatia hewa safi.
Maswali: 1. Hapo zamani samaki waliishi wapi?
Nyumba yetu imezungukwa na miti.
2. Why were the children dancing?
Questions: 1. Where was Tom?
Tom is our best football player. He stays far away from school. One day we had a big match. Tom had not come to school that day. The teacher went to look for Tom. The teacher found Tom weeding cassava. The teacher called Tom from the garden. All pupils were happy when Tom came. Our school won the match. We danced the whole day.
2. How did rain begin?
Questions: 1. What does Juma do every day?
Juma reads to us a story from his book every day. He reads the story aloud in class. We enjoy listening to the stories. Yesterday, he read about the sun and the wind. Both of them lived in the same sky. The wind did not like the sun .It wanted to be the head of the sky. One day, the wind chased the sun away. It told sun to go to another sky. The sun did not go. The next morning, the wind ran after the sun. The sun fell down and started crying. That is how it began to rain. We clapped for Juma.
Hapo zamani za kale samaki waliishi nchi kavu. Waliishi kwa kula wadudu kama vile panzi, mende na sisimizi. Siku moja wadudu hawa walikaa kikao na kupanga namna ya kuwaondoa samaki. Kikao chao wengi walichangia. Ikafika zamu ya sisimizi. Sisimizi alisimama na kusema, "Umoja ni nguvu na utengano ni udhaifu". Wote walisimama na kupiga kelele "samaki wauaweee". Samaki waliposikia hivi walikimbia na kujificha majini. Hadi hivi leo samaki wanaishi majini.
Baba amejenga nyumba nzuri.
She feeds them well.
She likes her kids.
She has two kids.
This is our goat.
They are very kind.
The people there are good.
Lamu is the busy town.
My mother works in Lamu.
Source of data: Uwezo national reports
(*) Note: Kenyan districts in blue, Ugandan districts in green, Tanzanian districts in red.
cow mat
table dog
room face
w y
3c. Kiswahili Tests
3. Access to Education
3.1 Primary school enrollment is high but not universal Figure 2 presents school enrollment by age for the three countries.6 The graph reflects differences in the education systems among the countries. In Kenya, primary school lasts eight years with children expected to attend school between the ages of six and 13. In Tanzania and Uganda, primary school takes seven years. In Uganda, children start by the age of six and complete when they are 12 while in Tanzania they start when they are seven and complete when they are 13. The figure, however, includes children outside the official age brackets. The graph demonstrates how enrollment was lowest in Tanzania. Irrespective of age, a smaller fraction of children went to school in Tanzania than in the other countries. The graph furthermore illustrates how in Uganda, and relative to Kenya, more children were enrolled in primary school by six years of age. In Kenya, in part because the curriculum lasts an additional year, a larger fraction of older children (those aged 14‐16) attended primary school. Figure 2: Enrollment in primary school by age
Percent of children enrolled
120 100 80 60
Tanzania Uganda
20 0 6
10 11 12 13 14 15 16 Age
Source of data: Uwezo
3.2 Opportunities for enrollment remain unequal and depend on household wealth Figure 3 considers how enrollment within a country varies by wealth of the child's household. Five wealth categories (quintiles) were distinguished: very poor, poor, those in the middle, wealthy and very wealthy with each quintile comprising 20% of households. The wealth quintiles were constructed using country specific data, implying that it is possible that poor households in Kenya are better off than those in the middle quintile in Tanzania. This figure restricts itself to enrollment of children within the official school going age range in each country. Enrollment rates were lowest in Kenya (around 84%) and highest in Uganda (around 90%). The graph furthermore illustrates that children from very poor households were least likely to be enrolled. These differences were more pronounced in Kenya and less so in Uganda and Tanzania. 6
This section draws upon questions asking parents about school enrollment. As a consequence we use the term "school enrollment", even though it is plausible that parents understood the question as one about attendance. The latter is borne out by the fact that enrolment rates calculated from the Uwezo data correspond very closely to attendance rates as reported by DHS surveys (see for instance the stats compiler at www.measuredhs.com). Are Our Children Learning? | 7
92 91 92 93 88 89 87 86 87 86 90 82 86 82
100 90 80 70 60 50 40 30 20 10 0
Percent of Children of compulsory age Enrolled
Figure 3: Enrollment of children of compulsory school going age(*) by wealth quintile
(*) In Kenya compulsary school going age is 6‐13; in Tanzania 7‐13 and Uganda 6‐12. Source of data: Uwezo Another way to highlight the plight of children from very poor households is to consider children who never attended primary school. As Figure 4 makes clear, children from the poorest wealth quintile were seriously disadvanataged. In Kenya, 64% of children aged 6‐16 years who never enrolled were from the poorest wealth quintile, while in Uganda and Tanzania it stood at 45% and 38% respectively.7 Figure 4: Percent of children aged 5‐16 who never attended primary school, by wealth quintile 70
60 45
40 30
17 8
20 12
Kenya 7
For Tanzania the age range used was 5‐16 years.
Literacy and Numeracy Across East Africa | 8
Source of data: Uwezo
As is the case with non‐enrollment, drop out rates were higher for children from poor and very poor households, though differences were smaller than for non‐enrollment. Among those who dropped out of school, 61% were from poor or very poor households in Kenya compared with 50% and 41%, respectively, in Uganda and Tanzania. 34 27
23 24
17 16 17 11
10 10
Kenya Tanzania Wealthiest
Uganda Poor
40 35 30 25 20 15 10 5 0
Figure 5: Children aged 5 to 16 who dropped out of school, by wealth quintile
Source of data: Uwezo Conclusion: Despite significant increases in enrollment following the introduction of free primary education, Uwezo survey data demonstrate that enrollment was far from universal. Depending on the wealth quintile, between 7% and 26% of children of school going age were not in school. These rates correspond to attendence rates found by other surveys. The Demographic and Health Surveys report attendance rates of 73% for Tanzania (2004/5), 79% for Kenya (2008/9), and 82% for Uganda (2006). Children from poor and very poor households were less likely to be in school than children from better off households. So not only was universal access to education not fully achieved, opportunities to go to school were not equal, and depended on household wealth.
4. Learning
4.1 Performance on the English, Numeracy and Kiswahili tests The main objective of the Uwezo test was to assess literacy and numeracy competency. As the tests reflect what pupils should have mastered by the end of Standard 2, all children in Standard 3 and above should be capable of achieving the highest levels of a Standard 2 test. As will be demonstrated in this section, this was not the case. Even amongst children who have advanced to Standard 7, many have not acquired Standard 2 numeracy and literacy skills. English: Figure 6 presents performance on the English test for the three countries while distinguishing between different grades. The Figure demonstrates how, in each of the countries, few children in Standard 3 achieved Standard 2 level competency in the English literacy test. In Kenya, only 28% of pupils in Standard 3 completed the test succesfully, meaning they were able to read the story with ease. In Uganda and Tanzania, pass rates were worse and stood at 4% and 8% respectively. Children in higher grades progressively did better on the Uwezo tests, as should be Are Our Children Learning? | 9
Percent of children perform up to Standard 2 level
expected. In Kenya 94% of children in Standard 7 possessed Standard 2 level competencies in reading a story in English. Competency improved with the grade level in Uganda and Tanania as well. Irrespective of standard, the percent of children in Kenya who were at the highest level was higher than that of their peers in Uganda and Tanzania. In Tanzania, the results were particularly discouraging; only 51% of children in Standard 7 passed the Standard 2 level English test. Over time the gap between Kenya and Uganda in the percent of children who had acquired Standard 2 level competencies gradually closed. Whereas in Standard 4 the difference in pass rate was 39%, by Standard 7 the difference closed to 14%. For Kenya and Tanzania this did not hold and almost twice as many children in Kenya passed the English test in Standard 7 as in Tanzania. Figure 6: Performance on Uwezo English test, by standard 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%
73 55
51 Kenya
Uganda Tanzania
Std III
Std IV
Std V
Std VI
Std VII
Source of data: Uwezo
Percent of children perform up to Standard 2 level
Numeracy: For numeracy, the pattern was comparable to that for English, with children in Kenya doing better (but far from well) compared with those in Uganda and Tanzania. Tanzania was again the worst performer. Like in English, childrens' abilities improved with time and once they reached Standard 7 most were numerate and possessed competencies expected by the end of Standard 2. But even in Kenya, the country with the best performance, 12% of children in Standard 7 failed to reach the Standard 2 level. In Uganda, 15%, and in Tanzania a disturbing 32% of children in Standard 7 failed to perform numeracy tasks expected at the Standard 2 level. Figure 7: Performance on Uwezo numeracy test, by standard 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%
88 80 70 59
55 44 33
36 25
58 Kenya
Std III
Std IV
Std V
Std VI
Source of data: Uwezo Literacy and Numeracy Across East Africa | 10
Std VII
Compared to English literacy, the gap in performance on the numeracy test between Tanzania on the one hand and Kenya and Uganda on the other, was smaller. Possibly, though this is a speculation, the larger gap for English than for numeracy reflects the fact that children in Kenya and Uganda live in environments where English is more widely heard and spoken. As a consequence they have an advantage over Tanzanian children who are rarely exposed to English outside school and whose teachers also have little experience speaking English. The gap in numeracy test scores demonstrates, however, that this is not the only explanation for the poorer performance of children in Tanzania. As the performance on both tests was worse in Tanzania, it seems highly plausible that children in Tanzania learn less while in school than their peers in Kenya and Uganda.
Kiswahili: This conclusion is supported by performance on the Kiswahili test. This test was conducted only in Kenya and Tanzania (because Kiswahili is not widely used in Uganda). The earlier pattern of poor performance by Standard 3 pupils and gradual catch‐up in later standards was repeated. Children in Kenya performed better than children in Tanzania. The gap in performance between Tanzania and Kenya for Kiswahili was smaller than that for English and numeracy (this is likely a reflection of the fact that Kiswahili is more widely spoken in Tanzania compared to Kenya), but it was still there. So even on a test in which children in Tanzania ought to have an advantage over children in Kenya, Tanzanian children performed worse. Figure 8 gives further details on performance in Kiswahili, by grade level, in Kenya and Tanzania.
Percent of children performing up to Std 2 level
Figure 8: Performance on Uwezo Kiswahili test, by standard 100%
88 77
20% 0% Std III
Std IV
Std V
Std VI
Source of data: Uwezo
Std VII
4.2 Differences in performance by district In addition to differences in performance among the three countries, significant differences existed among districts within each country. Table 5 shows the percent of children in Standard 3 with Standard 2 numeracy and literacy skills. In Tanzania, 33% of children in Moshi Urban, the best performing district, passed the English test, yet no child (0%) in Liwale district passed the test. In Kenya, 66% of children in Kikuyu district passed the numeracy test, but only 5% did so in Lagdera district. And in Uganda, 40% of the children in Bushenyi district passed the numeracy test, but only 7% in Nakapiripirit district. Such differences can be observed for each of the three tests, and within each of the countries. These large disparities are reason for concern. There is no reason why children in Nakapiripirit, Lagdera or Liwale should do worse than their peers in Bushenyi, Kikuyu or Moshi Urban. Where one is born and goes to school should not affect the likelihood of acquiring basic literacy and numeracy competencies. The fact that it does points to the existence of significant inequalities in the education systems within each country. Are Our Children Learning? | 11
Table 4 presents the 10 best and worst performing districts across Kenya, Uganda and Tanzania. On the English and numeracy tests, all top 10 disctricts, without exception, were Kenyan. At the bottom, few Kenyan districts were found, but there were many districts from Uganda and Tanzania. The overall pattern was that districts from Kenya top the charts, districts from Tanzania were at the bottom, and Ugandan districts were in between. Table 4: Best and worst performing districts, Standard 3 pupils on English and numeracy tests 1 2 3 4 5 6 7 8 9 10
English test Best performing Worst districts performing Kikuyu Adjumani Naivasha Liwale Pokot North Katakwi Taita Bundibugyo Nandi East Shinyanga Rural Imenti North Gulu Nyeri South Kamuli Ruiru Mayuge Nakuru North Yumbe Gatanga Amuru
Numeracy test Best performing Worst performing Kikuyu Kaloleni Naivasha Meru South Nandi North Mbeere Kibwezi Gatanga Keiyo Imenti North
Kasulu Lagdera Bukoba Rural Nakapiripirit Gulu Kotido Mwanga Singida Rural Mayuge Shinyanga Rural
(*) Note: Kenyan districts in blue, Ugandan districts in green, Tanzanian districts in red. Source of data: Uwezo Table 5 shows that districts that performed well in one test were also likely to do well on the other tests. In Tanzania, Moshi Urban and Rombo were among the top three districts for each of the three tests. In Kenya, Kikuyu and Naivasha were top performers in every test, and in Uganda, Wakiso and Masaka stand out. What do these districts have in common? Amongst poorly performing districts there was more variation even though Muleba and Kasulu in Tanzania, and Lagdera and Wajir East in Kenya show up more than once in the list of worst performing districts.In short, it seems good performing districts are all alike, poorly performing districts perform poorly in their own way. Table 5: Best and worst performing districts of Standard 3 pupils, by district and country English
Tanzania Best Worst performers performers st 1 Moshi 33% Liwale 0% Urban 2nd Rombo 23% Shinyanga 1% Rural 3rd Moshi 23% Muleba 2% Rural Numeracy st 1 Moshi 40% Kasulu 5% Urban nd 2 Rombo 39% Bukoba 7% Rural 3rd Moshi 35% Mwanga 8% Rural Kiswahili st 1 Rombo 63% Muleba 9% nd 2 Moshi 58% Mwanga 16% Urban 3rd Kisarawe 57% Kasulu 17%
Kenya Best Worst performers performers Kikuyu 64% Lagdera 4%
Uganda Best Worst performers performers Wakiso 12% Adjuman 0% i Masaka 8% Katakwi 0%
Naivasha 53%
Trans Mara
Pokot North
Nakasong ola
Naivasha 57%
Samburu North Wajir East
Naivasha 68% Taita 64% Kikuyu
Kaloleni 65%
Bundibu gyo 40% Nakapiri pirit 38% Gulu
38% Kotido
Lagdera Wajir East
4% 12%
Not done
Trans Mara
(*) Note: Kenyan districts in blue, Ugandan districts in green, Tanzanian districts in red. Source of data: Uwezo Literacy and Numeracy Across East Africa | 12
7% 7%
4.3 Differences in performance by household wealth
47 34 25 16
1 Poorest
9 4
19 21
50 45 40 35 30 25 20 15 10 5 0
Percent passing
Household characteristics also mattered with regards to performance. Figures 9 and 10 below demonstrate how differences in household wealth were associated with performance. Children from the wealthiest households did significantly better on the Uwezo tests than children from less wealthy households. In Kenya for instance, almost half (47%) of the Standard 3 children from households in the wealthiest quintile attained Standard 2 English literacy skills, as opposed to only 19% of children from the poorest households. Likewise, 48% of children from the wealthiest households in Kenya passed the numeracy test, as opposed to only 28% of children from the poorest households. Figure 9: Performance of Standard 3 children on Uwezo English test, by wealth quintile and country
Source of data: Uwezo Figure 10: Performance of Standard 3 children on numeracy test, by wealth quintile and country
Percent passing
60 48
40 30
33 22
19 21
Source of data: Uwezo
Children from the poorest households in Kenya were much less likely to pass the numeracy and English tests than children from wealthier Kenyan households. Nevertheless, the chances of success Are Our Children Learning? | 13
were still higher for a child from a very poor Kenyan household than a child from a very wealthy Ugandan or Tanzanian household. For instance, 19% of children from a household in the poorest wealth quintile in Kenya passed the English test, compared to 16% and 11% of children from the wealthiest households in Uganda and Tanzania. For numeracy, similar results held, except that children from the poorest quintile in Kenya performed at par with their peers from the wealthiest of households in Uganda and Tanzania. Conclusion: The Uwezo survey results show that numeracy and literacy skills were dismal across the three countries and the majority of children in Standard 3 did not possess Standard 2 level numeracy and literacy skills. Amongst the poorly performing, Kenya did better than Uganda and Tanzania. Tanzania exhibits by far the worst performance based on the Uwezo tests. Large differences in performance were observed in districts within and between countries and for children coming from different wealth backgrounds. A silver lining might be that there were substantial intra‐country differences in performance. This suggests that improved performance is feasible within the existing systems and offers opportunities to find out the reasons behind these differences.
5. Quality of Schools
Pupil class ratio
Source of data: Uwezo
Pupil teacher ratio
90 80 70 60 50 40 30 20 10 0
Pupils per teacher/class/toilet
One explanation for differences in district performance may be that the quality of schools or quality of teaching differed. Whereas the Uwezo survey did not contain information about the quality of teaching, information from the school questionnaires allowed basic observations on quality of schools. For each of the three countries, the Uwezo school questionnaire collected information from which the number of pupils per teacher, pupils per class, and pupils per toilet could be calculated. Country comparisons show that Kenyan schools had smaller pupil:teacher ratios, pupil:class ratios, and fewer pupils per toilets than schools in Uganda and Tanzania. The difference with Tanzania and Uganda was quite large. For instance, in Tanzania there were 60 pupils per teacher, in Kenya 38. In Uganda there were 83 pupils per class, in Kenya 48. Overall, Kenya's actual school quality indicators were closer to official standards than those for Uganda and Tanzania. Figure 11: School quality indicators for Kenya, Uganda and Tanzania
Pupil toilet ratio
Within countries large differences were observed. This can be seen from Table 6 presenting a district ranking of school quality based on the three ratios. The overall ranking was produced after ranking the districts on each of the three indicators separately and assigning districts the corresponding rank number. The summation of the three rank numbers gives the overall rank, according to which districts were ranked from highest to lowest in Table 6. Literacy and Numeracy Across East Africa | 14
The Table shows that district averages varied considerably: from as low as 25 pupils per teacher in Imenti South district, Kenya to as high as 91 per teacher in Muleba district, Tanzania. Similarly pupil per class ratios varied from as low as 23 in again Imenti South, to as high as 173 in Buliisa district, Uganda. The pupils per toilet ratio exhibited similar variations, from a low of 14 pupils per toilet in Nyeri South, Kenya to a high of 110 pupils per toilet in Kamuli, Uganda. These are district averages, implying that they mask starker differences between schools. For individual schools and classes, the variation was much higher. For instance, in the Kenya Uwezo data set pupil:teacher ratios ranged from as low as 10 :1 to over 200:1. Another observation is that Kenyan districts topped the ranking, while Tanzanian and Ugandan districts, and just a few Kenyan districts, were found at the bottom of the ranking. In the East African Uwezo ranking, Kenyan districts occupied the first 24 positions. The first non‐Kenyan district was from Tanzania in the 25th position, while the first Ugandan district was only found in 44th place. No Kenyan districts were among those ranked in the bottom 10. Table 6: Best and worst performing districts on a combined pupil:teacher ratio, pupil per class and pupil per toilet rating Rank District name Top 10 districts 1 Imenti South 2 Mbeere 3 Meru south 4 Imenti north 5 Nyeri South 6 Kericho 7 Nyandarua North 8 Kikuyu 9 Tharaka 10 Wareng
Pupils per teacher
Pupils per class
Pupil per toilet
25 27 28 28 33 28 35 35 29 31
23 28 25 29 28 35 33 31 29 35
14 17 17 23 14 30 17 25 39 31
91 66 64 86 70 69 69 83 67 87
83 86 99 110 117 100 101 108 173 140
79 110 100 69 76 89 87 92 112 107
Bottom 10 districts 126 Muleba 127 Kamuli 128 Mayuge 129 Urambo 130 Amuru 131 Amuria 132 Budaka 133 Geita 134 Buliisa 135 Ilemela
(*) Note: Kenyan districts in blue, Ugandan districts in green, Tanzanian districts in red. Source of data: Uwezo A school quality index can be constructed using the same approach as was used to construct a wealth index for households.8 Five school quality quintiles, each comprising 20% of the schools visited, were established per country. The quintiles were not strictly comparable across the three 8
See for instance Filmer D and Pritchett LH. Estimating wealth effect without expenditure data – or tears: an application to educational enrollments in states of India. Demography 2001; 38:115‐32. Are Our Children Learning? | 15
countries as different variables were used to construct each country index. Within countries, significantly, performance of Standard 3 pupils on the Uwezo tests did not vary much with school quality quintile. The only exception was that in Kenya and Tanzania, performance was better on the English test for children attending a school in the top quality quintile. Figure 12: Standard 3 children with Standard 2 English literacy skills, by school quality quintile 32
35 25 24 26
25 20 10
7 2
3 High
Percent passed
School quality quintile
Source of data: Uwezo
37 39 36
Tanzania School quality quintile
Source of data: Uwezo
12 13
17 17
26 26
45 40 35 30 25 20 15 10 5 0
Percent pased
Figure 13: Standard 3 children with Standard 2 numeracy skills, by school quality quintile
Figures 14 and 15 present the quality of schools attended by children from the bottom and top wealth quintiles. One notes that, generally, children from poor families attended worse schools, while children from better off families attended higher quality schools. In Kenya, the differences were most pronounced and 37% of children from the poorest 20% of families attended the worst schools, while only 9% attended the best schools. In Uganda, the distribution was most equal, with Tanzania taking an intermediate position. Literacy and Numeracy Across East Africa | 16
40 35 30 25 20 15 10 5 0
33 25
23 24
23 22 20 21
Figure 14: Quality of schools attended by children from the poorest wealth quintile
School quality quintile
Source of data: Uwezo Figure 15: Quality of schools attended by children from the top wealth quintile
60 48
40 19 7
17 11
School quality Index
Source of data: Uwezo Conclusion: There were large differences in quality between schools. Defining quality by using a set of simple indicators (pupils per teacher, pupils per class, and pupils per toilet) illustrated great variance in quality among the three countries, across districts within countries, and within schools found in the same districts. Schools in Kenya were generally better equipped than schools in Uganda and Tanzania; schools in Uganda did particularly poorly. Only a weak association was found between school quality and performance on the Uwezo tests. This should caution those who believe that performance in schools will improve by reducing pupil:teacher or pupil:classroom ratios. The Uwezo data suggest that these aspects matter, but that other non‐observed aspects are probably more important. The quality of teaching, practical Are Our Children Learning? | 17
accountability and teacher motivation come to mind as potentially important determinants of school performance. Unfortunately no information was collected on these factors. Finally, children from poor families were doubly disadvantaged in that not only were they more likely not to attend school or to drop out of school, they were also more likely to attend schools of poorer quality.
6. Private schools Thus far this report has focused on numeracy and literacy skills in public primary schools. But across East Africa, a significant number of children attend private primary schools. In Kenya 9% of school going children go to private schools and in Uganda as many as 28% of children attend private schools. Tanzania is the one country in which few children attend private schools (2%). Figure 16: Distribution across public and private schools of primary school pupils
100 90 80 70 60 50 40 30 20 10 0
72 91
Public Private
28 Uganda
Source of data: Uwezo
Unsurprisingly, perhaps, the majority of children who attended private schools were from the wealthiest families; few were from poor families. This pattern was most distinct in Tanzania, where children attending private schools almost without exception came from households in the top two wealth quintiles. In Uganda, private education was also accessed by children from poorer households, though children from wealthier families were still much more likely to attend. Kenya takes an intermediate position.
Literacy and Numeracy Across East Africa | 18
Figure 17: Enrollment in private primary schools by wealth quintiles 80
70 51
50 34
40 14
15 5
7 middle
14 16
Source of data: Uwezo
Pupils attending private schools performed better on the Uwezo tests than those attending public schools. This holds true across the three countries. In Kenya, 60% of children in Standard 3 private schools passed the English and numeracy tests. This was still a far cry from the expected 100% but twice as good as the performance in public schools. In Tanzania, the difference in performance by Standard 3 students between public and private schools was most notable. Whereas less than 10% of children in public schools passed the English test, almost half of those in private schools did. A similar yet smaller difference was found for the numeracy test. Perhaps the more surprising result was from Uganda where private schools did better than public schools, but with only 10% of children in Standard 3 passing the English test, even though English language is ostensibly used in some of these schools. This performance was the worst in East Africa. Ugandan Standard 3 private school children also performed worst on the numeracy test amongst those attending private schools. By the time children reach Standard 7, no difference was found in performance between those attending public and private schools, except in Tanzania where public school Standard 7 students did much worse than pupils attending private school. At the same time, in Uganda and Tanzania large numbers of private school students in Standard 7 continued to fail the Uwezo tests. For instance, one in five private school Standard 7 students in Uganda failed the Uwezo English test and one in three Standard 7 students in private schools in Tanzania failed the Uwezo numeracy test. Are Our Children Learning? | 19
Figure 18: Performance on Uwezo English and numeracy tests by school type and standard English Standard 3 61
Percent passing
Public Percent passing
English Standard 7
50 40
30 20
0 Kenya
Numeracy Standard 3 60
Percent passing
40 30
10 0
Public 80 80
Private 84
Numeracy Standard 7
95 94
100 90 80 70 60 50 40 30 20 10 0
91 88
Public 85 86
67 68
60 40 20 0
Source of data: Uwezo Conclusion: Private school attendance varied greatly in East Africa, with as many as one in four pupils attending private schools in Uganda, to as few as one in 50 in Tanzania. As expected, mostly children from the wealthiest families attended private schools, though in Uganda access was more equally distributed across wealth classes. Performance on the Uwezo tests by children attending private schools was significantly better than of those attending public schools, but far from perfect. In Tanzania and Uganda in particular, pupils attending private schools performed relatively poorly. Even in Kenya, whose private schools performed best, one in three pupils in Standard 3 failed to pass the Uwezo numeracy and English test. The better performance of private schools provides an opportunity to explore what drives the better results. Do private schools have better inputs such as books, better qualified teachers, better practical accountability, better pay for teachers, or other incentives? At the same time it is clear that private schools themselves are not a panacea, as their performance also leaves much to be desired.
Literacy and Numeracy Across East Africa | 20
7. Gender Equality
This section addresses gender equality in schools. As discussed in Section 3, there were differences in overall enrollment rates across the three countries. However, as Figure 19 demonstrates, gender equality in enrollment has generally been achieved. In Uganda and Kenya, enrollment was slightly higher for male students, while in Tanzania the enrollment rate was slightly higher for female students. Figure 19: Enrollment by sex (gender) for children of school going age 85
86 84 82 80 78 76 74 72 70 68 66
76 73
Percent of pupils perform up to Standard 2 level
Source of data: Uwezo While gender parity in enrolment has been largely achieved, slight differences in performance based on the Uwezo tests between girls and boys were observed as can be seen from Figure 20. In Kenya, female students performed slightly worse on the three Uwezo tests, while in Uganda and Tanzania the evidence was mixed. In Uganda, female students did slightly better on the English test and worse on the numeracy test. In Tanzania, female students also did slightly worse on the numeracy test, better on the English test, and much better on the Kiswahili test. Figure 20: Performance of Standard 3 children on Uwezo tests, by gender 40 35 30
37 37
36 33 33
23 19
15 10
0 Male
Source of data: Uwezo
Are Our Children Learning? | 21
Conclusion: Gender inequity is often noted across many socio‐political spheres. This was not the case for primary education, at least in terms of enrollment or performance in basic literacy and numeracy; boy and girl students functioned almost at par. In Kenya, female students did slightly worse both in enrollment and on the Uwezo tests. For Uganda and Tanzania the results were mixed, and it would be fair to conclude that overall girls and boys performed at par.
8. Which factors explain performance most? This report thus far demonstrates that basic numeracy and literacy skills were closely associated with the grade level of a child, whether he or she comes from a wealthy household, and if she or he attends a private school. Basic numeracy and literacy skills were not as closely tied with school quality and gender. Since students that attended lower quality schools were also more likely to face other challenges such as low household income, it is difficult to disentangle the effect of school quality on achievement. In this section we explore the associations with school performance in combination and include some other factors that may also be associated with performance such as the level of mother's education or a child's age. Through regression analysis we attempt to estimate the individual impact of each of these factors on performance, while holding all other factors constant. We present the results by country as the Uwezo data sets allow the incorporation of different variables in different countries. In the Uganda Uwezo survey for instance, questions about mother's education were not asked, while they were in Tanzania and Kenya. Across the three countries and for the three different tests, very similar patterns emerge. The grade level of a child was by far the most determining factor of the likelihood of a child having acquired basic numeracy and literacy skills. Mother's education also had a large effect on skill attainment but, and this was noteworthy, mostly for mothers with secondary education and higher. When mothers have primary education or less, the positive impact on their child's school performance was limited. Household wealth and attending a private school had considerable positive impacts on school performance. Gender and school quality had very limited impact.
Literacy and Numeracy Across East Africa | 22
Additional proportional increase in pass rate ‐0.1
Mother education Child Grade
Source of data: Uwezo School quality D‐poor
School quality
D‐grade 7
D‐grade 6
D‐grade 5
D‐grade 4
D‐grade 3
D‐primary 1‐4 D‐primary 5‐8 D‐secondary 1‐4 D‐secondary 5‐6 D‐post sec0ndary D‐age D‐male D‐private school D‐grade 1 D‐grade 2 D‐grade 3 D‐grade 4 D‐grade 5 D‐grade 6 D‐grade 7 D‐grade 8 D‐highest D‐high D‐middle D‐bad D‐wealthiest D‐wealthier D‐average D‐poor
D‐grade 2
D‐grade 1
D‐private school
Mother education
D‐post secondary
D‐secondary 1‐6
D‐primary 1‐7
0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 ‐0.1
Additional proportional increase in pass rate
Figure 21: Marginal effects of different factors on Uwezo test performance: Kenya Kiswahili
Source of data: Uwezo
Figure 22: Marginal effects of different factors on Uwezo test performance: Tanzania Kiswahili
Are Our Children Learning? | 23
Figure 23: Marginal effects of different factors on Uwezo test performance: Uganda Numeracy
0.8 0.6 0.4 0.2
School quality
D‐grade 7
D‐grade 6
D‐grade 5
D‐grade 4
D‐grade 3
D‐grade 2
D‐grade 1
D‐private school
0 D‐age
Additional proportional increase in pass rate
English 1
Source of data: Uwezo
9. Conclusion
Summary of key findings This report assessed the numeracy and literacy competency of tens of thousands of children aged between six and 16 years in Kenya, Tanzania and Uganda using the Uwezo tests administered in 2009/2010. According to the findings, children in all three countries perform poorly compared to established curriculum levels. Among countries, Kenya's primary schools learn the most. In all three tests‐ Kiswahili, English and numeracy‐ Kenya's pupils came out on top, followed by pupils in Uganda. Children in Tanzania performed worst even in the Kiswahili test, a language which children in Tanzania are more exposed to than children in Kenya. While Kenyan children had acquired better numeracy and literacy skills, they did far from well. In Standard 3, roughly two out of three children failed to pass the Uwezo tests for English, Kiswahili and numeracy. These results are cause for concern, as the expectation is that 100% or all children in Standard 3 should be able to satisfactorily complete a Standard 2 test. Only when pupils reached Standard 7 did almost all of them acquire basic Standard 2 numeracy and literacy skills, though in Tanzania half of Standard 7 pupils were still unable to do the Standard 2 English test. Schools in Kenya were found to be of better quality (in terms of pupils per teacher or class, or pupils per toilet) than those in Uganda and Tanzania. However, an important finding given the enormous resources invested in recent years in improving school infrastructure, was that school quality was weakly associated with literacy and numeracy levels. Children in areas with better school infrastructure did not perform better than in lower quality schools or more crowded classrooms. Kenya was also the country in which inequalities were largest. Among the poorest families, fewer children of compulsary school going age were enrolled in primary school in Kenya (74%) than in Literacy and Numeracy Across East Africa | 24
Tanzania (82%) and Uganda (86%). Poor Kenyan children were more likely to attend a low quality school than poor children in Uganda or Tanzania. Poor Kenyan children were more likely not to attend primary school and drop out of school than their Ugandan and Tanzanian peers. Despite this, however, in terms of learning outcomes, children from poor families in Kenya stood a better chance of doing well on the Uwezo tests than children from wealthiest households in Tanzania and Uganda. In Kenya, the percent of children from poor households in Standard 3 passing the numeracy test was 31%, as compared to 28% percent of children from the wealthiest households in Uganda who passed this test. The percent of Kenyan children from the poorest households passing the English test was 19%, compared to 16% of children from the wealthiest households in Tanzania who passed this test. In Uganda, children performed particularly poorly in lower grades but by the time they reached upper grades most were able to perform at the Standard 2 skill levels. By the time they reached Standard 7, performance of children in Uganda was almost at par with performance in Kenya. This was not the case for children in Tanzania, whose poor performance in lower grades was only partially made up in the upper grades. As a consequence, only 51% of Tanzanian children in Standard 7 passed the Uwezo English test and only 68% in Standard 7 passed the Standard 2 numeracy test. Children attending private schools did better than those attending public schools. The study affirmed that mother's education mostly impacted child performance when mothers obtained at least a secondary education. Gender differences in enrollment or school performance were insignificant.
What can be done Reflecting on these results, one cannot help but note the enormous challenge East African governments, teachers and parents face in making sure that children acquire basic numeracy and literacy skills. These asymmetries in learning also undermine the prospects for greater cooperation and development across the East African region. The situation in Tanzania is most acute, but results for Kenya and Uganda provide little comfort too. Renewed efforts are urgently needed to address non‐attendence and drop out rates. In addition, much more attention needs to be given to the fact that children should not only go to school, but also learn while in school. Increasingly it is being globally recognized that children need to be in school and learning too. Bad results inevitably lead to the question, what next? The findings of this report suggest that policy makers would do well to question approaches used so far, instead of doing more of the same. While different investments can have positive effects, some are likely to have greater or more lasting impact than others, or present better value for money. In a context where resources are limited, it is crucial to examine the evidence carefully for what is likely to contribute to greater impact. The Uwezo results offer limited guidance on what could be done to drive progress. First, the fact that pupil:teacher and pupil:classroom ratios were only weakly correlated with learning is valuable information, as it puts into question whether additional inputs and money in these areas will offer a solution to the existing crisis. This is a key moment to focus on the quality of teaching and teacher incentives and motivation. After all, one explanation why children who attend school learn so remarkably little may be that teacher incentives are weak, with teachers often having high rates of absence. For example, evidence from Tanzania demonstrates that 23% of teachers are not in school on any given day and when in school, teachers spend half their time outside the classroom. As a consequence, children are only taught two hours and four minutes a day, instead of an expected five hours.9 Studies from Uganda and Kenya suggest similar findings. 9
World Bank Service Delivery Indicators: Education and Health Care in Africa, presented at REPOA, March 4, 2011. Are Our Children Learning? | 25
Differences in performance among districts within each of the three countries, and between public and private schools, suggest that certain schools have 'figured out' how to achieve better results within existing constraints. Investigating why certain districts, and certain schools within districts, do so much better than others could provide important clues about what matters most for improved learning. A simple and affordable approach could start by identifying which schools do significantly better (or worse) than expected with the resources available, visiting these schools to identify what might explain their outcomes, and from these visits, derive commonalities. Other approaches can also be explored. A wide range of existing experimental evidence, much of it from Kenya, demonstrates that programs that increased school inputs were largely ineffective in improving outcomes. Providing additional textbooks and flipcharts, for example, had no effect on average performance, and reducing class sizes by adding new teachers was similarly ineffective.10 Interventions that increased student performance were those that changed incentives for teachers in meaningful ways. Paying for teacher attendance or exam scores had mixed results, and giving parents information about school conditions was ineffective. However, a program that enabled schools to hire additional teachers on short term contracts and that gave local school committees authority over these teachers was successful in increasing student achievement. Trying these new approaches, with rigorous experimental designs, would be one way to elicit how to improve learning in schools. One such approach, which is still untested but whose design has been informed by careful review of the evidence of what works, is called Cash on Delivery.11 The core idea here is that instead of funding inputs, a mechanism is created by which payments are made against the achievement of a specified and independently verified outcome, such as $50 per student who completes Standard 2 with 80% literacy and numeracy competencies. This approach was originally designed to improve the effectiveness of aid given to national governments, but the approach may be even more useful for how national governments create incentives to improve performance at district and school levels. There is a crisis of learning in Kenya, Tanzania and Uganda. Governments are justifiably proud of their achievements in expanding school enrolments. But they should now not hide behind these achievements, and focus instead on making sure that children in school are in fact learning. Global evidence from meta‐reviews and rigorous experimental approaches, coupled with the Uwezo data presented herein strongly suggest that investing in inputs alone has limited impact, and that fresh thinking focused on incentives for learning is needed. 12 The billions of shillings and hours spent on basic education each year by parents, governments and donors alike can only be considered well spent when children are learning, literate and numerate. This is the moment to face the crisis squarely, and to craft solutions that are not only well intended, but actually work.
"Improving Education in the Developing World: What Have We Learned from Randomized Evaluations?" Michael Kremer and Alaka Holla, November 10, 2008, accessed at www.economics.harvard.edu/faculty/kremer/files/Annual_Review_081110%20‐%20NO%20TRACK%20CHANGES.pdf. 11 The idea has been developed by the Center for Global Development, see http://www.cgdev.org/section/initiatives/_active/codaid. For a comment on its strengths and value in local application see: http://blogs.cgdev.org/globaldevelopment/2011/04/guest‐post‐five‐reasons‐i‐am‐a‐fan‐of‐cash‐on‐delivery‐and‐five‐ ways‐to‐make‐it‐sharper.php 12 For instance see http://siteresources.worldbank.org/EDUCATION/Resources/278200‐ 1298568319076/makingschoolswork.pdf and on the value of experimental approaches see Banerjee, A and Duflo, E, Poor Economics: A radical rethinking of the way to fight global poverty, Public Affairs, 2011, especially chapter 4. Literacy and Numeracy Across East Africa | 26
Annex 1: District Rankings District name Adjumani Amuria Amuru Apac Babati Budaka Bukoba Rural Bukoba Urban Buliisa Bundibugyo Bungoma North Bunyala Buret Bushenyi Busia Busia Butere Chunya Eldoret East Gatanga Geita Gucha Gulu Hamis Ibanda Igembe Ijara Ilemela Iment South Imenti north Kabale Kakamega Ctrl Kakamega North Kaloleni Kamuli Karagwe Kasulu Katakwi Keiyo Kericho Kibaale Kibaha Kibwezi Kikuyu Kilifi Kilombero Kilosa Kinondoni Kisarawe Kisii South Kisumu West Kitui North Koibatek
Std 3 pass rate 0% 2% 2% 3% 3% 3% 1% 6% 2% 1% 7% 9% 25% 4% 9% 2% 11% 10% 26% 38% 6% 30% 0% 20% 3% 11% 19% 13% 38% 36% 2% 14% 14% 34% 0% 2% 4% 0% 24% 18% 2% 7% 21% 53% 19% 2% 0% 6% 1% 14% 7% 19% 16%
Performance indicators Std 7 Enrol pass ment rate rate 93% 89% 60% 93% 67% 89% 80% 89% 58% 92% 62% 91% 39% 82% 36% 86% 84% 92% 49% 94% 78% 91% 83% 82% 85% 81% 67% 91% 80% 95% 79% 87% 77% 91% 55% 82% 92% 93% 89% 94% 59% 81% 95% 89% 90% 93% 84% 91% 66% 91% 91% 89% 94% 79% 68% 81% 85% 88% 95% 89% 56% 94% 80% 88% 79% 79% 95% 72% 74% 92% 24% 87% 18% 79% 88% 95% 90% 83% 94% 85% 82% 87% 35% 90% 90% 91% 87% 94% 96% 70% 43% 91% 36% 89% 48% 92% 46% 91% 84% 84% 81% 87% 95% 91% 89% 86%
Perform ance rank (*) 107 76 112 94 78 97 130 117 66 98 48 79 46 81 21 109 39 115 4 1 120 8 73 17 91 26 44 105 18 5 75 52 85 31 95 128 129 64 34 32 113 102 9 3 42 106 124 77 114 58 72 7 38
School quality indicators Pupil Pupil Pupil teacher class toilet ratio ratio ratio 66 57 47 69 100 89 70 117 76 69 97 65 58 58 42 69 101 87 64 78 47 36 73 62 67 173 112 65 83 108 42 61 31 43 68 37 34 96 81 40 47 45 48 88 49 64 93 90 40 45 37 56 73 50 28 34 36 41 34 14 83 108 92 43 57 40 59 78 63 37 39 53 42 52 54 45 44 24 41 50 154 87 140 107 25 29 23 28 23 14 41 53 59 44 90 39 35 44 45 60 59 104 66 86 110 65 78 53 90 77 67 63 89 84 28 58 27 28 35 30 65 107 70 37 53 58 33 37 40 35 31 25 57 59 68 55 81 80 53 85 68 38 83 120 45 41 29 39 45 42 35 38 59 49 39 36 32 32 46
School quality rank (*) 78 131 130 119 72 132 90 71 134 124 51 55 92 50 88 125 39 83 11 16 133 54 100 45 60 36 82 135 1 4 61 74 34 109 127 99 116 121 23 6 123 56 24 8 91 112 108 98 38 41 46 47 19
Are Our Children Learning? | 27
District name Kongwa Kotido Kuria East Kyenjojo Kyuso Lagdera Laikipia North Lamu Lari Limuru Liwale Loitoktok Makueni Mandera Central Manga Marakwet Masaba Masaka Maswa Mayuge Mbeere Mbeya Urban Mbulu Meru south Misungwi Molo Morogoro Rural Morogoro Urban Moshi Rural Moshi Urban Moyale Mpanda Mpwapwa Mubende Mukono Muleba Musoma Urban Mwala Mwanga Naivasha Nakapiripirit Nakasongoria Nakuru North Nandi Central Nandi East Nandi North Narok North Newala Ngara Njombe Nyandarua N. Nyeri South Pokot North Rachuonyo Rakai
Std 3 pass rate 4% 1% 10% 2% 10% 2% 34% 18% 17% 23% 0% 25% 15% 12% 27% 17% 21% 7% 4% 1% 35% 0% 13% 23% 4% 14% 1% 9% 16% 27% 12% 2% 7% 2% 2% 1% 13% 14% 1% 41% 2% 5% 31% 17% 32% 37% 28% 2% 5% 6% 18% 35% 37% 9% 3%
Performance indicators Std 7 Enrol pass ment rate rate 46% 91% 14% 44% 83% 84% 78% 90% 92% 79% 69% 82% 79% 61% 88% 91% 59% 93% 66% 87% 16% 79% 82% 83% 87% 90% 83% 74% 91% 89% 91% 87% 82% 92% 76% 92% 33% 84% 61% 93% 94% 92% 50% 95% 68% 84% 95% 91% 34% 91% 87% 90% 25% 80% 32% 92% 54% 87% 72% 89% 89% 83% 40% 89% 48% 89% 69% 91% 69% 88% 22% 84% 52% 91% 82% 93% 17% 89% 85% 86% 90% 65% 78% 94% 88% 84% 87% 83% 91% 88% 96% 85% 91% 74% 34% 91% 38% 83% 52% 87% 79% 89% 93% 88% 83% 47% 75% 88% 65% 93%
Literacy and Numeracy Across East Africa | 28
Perform ance rank (*) 100 134 70 93 63 118 62 15 22 50 135 51 24 86 11 33 13 53 125 87 2 99 101 6 108 29 133 82 92 43 59 119 103 89 111 131 68 19 127 23 123 49 27 54 14 12 40 116 122 110 35 10 56 69 71
School quality indicators Pupil Pupil Pupil teacher class toilet ratio ratio ratio 59 91 82 92 92 52 52 51 66 64 78 65 36 36 49 64 38 65 38 161 35 32 31 43 37 33 13 42 41 78 57 61 50 50 46 34 33 37 39 51 47 58 31 35 31 30 33 53 31 38 33 49 67 75 54 61 79 64 99 100 27 28 17 40 46 51 45 62 68 28 25 17 65 68 53 42 45 41 48 67 66 49 72 78 30 49 33 41 94 85 56 48 69 44 90 68 65 87 53 59 76 78 43 65 68 91 83 79 48 86 66 31 49 25 45 44 28 44 78 39 85 78 55 42 55 55 36 42 21 33 63 39 28 48 37 27 35 38 37 52 35 78 54 44 69 76 79 65 60 40 35 33 17 33 28 14 43 93 64 38 63 48 45 69 72
School quality rank (*) 120 115 81 107 31 76 65 17 13 68 79 52 21 73 12 29 15 96 97 128 2 53 85 3 94 49 89 101 25 106 86 103 104 110 84 126 102 20 40 64 111 63 22 44 26 14 35 80 118 75 7 5 95 58 93
District name Rombo Ruiru Rukingiri Samburu Central Samburu North Samburu East Shinyanga Rural Singida Rural Singida Urban Sotik Suba Sumbawanga Taita Tana River Tanga Taveta Tharaka Thika West Trans Mara Trans Nzoia East Urambo Wajir East Wajir North Wakiso Wareng West Pokot Yumbe
Std 3 pass rate 20% 27% 5% 18% 8% 5% 1% 1% 4% 12% 24% 11% 31% 17% 6% 23% 20% 19% 6% 16% 4% 7% 21% 8% 20% 24% 0%
Performance indicators Std 7 Enrol pass ment rate rate 70% 91% 80% 84% 76% 92% 66% 65% 97% 69% 95% 56% 27% 82% 39% 88% 44% 84% 85% 91% 90% 85% 45% 92% 86% 89% 92% 66% 29% 93% 88% 86% 76% 89% 77% 88% 81% 80% 91% 84% 52% 92% 92% 84% 69% 52% 76% 91% 78% 75% 98% 84% 78% 92%
Perform ance rank (*) 36 45 60 96 65 88 132 126 121 25 28 67 16 57 84 30 37 47 104 41 80 55 83 61 74 20 90
School quality indicators Pupil Pupil Pupil teacher class toilet ratio ratio ratio 47 68 42 45 43 29 70 80 64 34 35 45 34 31 49 35 38 57 71 76 82 68 66 48 39 74 53 35 57 60 36 38 47 70 101 54 38 35 25 41 40 70 48 142 59 46 45 59 29 29 39 32 66 38 41 83 53 37 57 30 86 110 69 48 42 63 43 34 51 40 58 51 31 35 31 33 40 43 54 84 80
School quality rank (*) 69 37 113 28 27 43 122 87 70 57 32 117 18 62 105 66 9 42 77 33 129 67 48 59 10 30 114
Note: Kenyan districts in blue, Ugandan districts in green, Tanzanian districts in red. (*) The two rankings have been constructed by adding the ranking of each of the three underlying indicators, and re‐ranking from lowest overall rank to highest overall rank. Source of data: Uwezo
Are Our Children Learning? | 29
Filename: Uwezo EA Report FINAL new tp Directory: C:\Documents and Settings\USER\My Documents Template: C:\Documents and Settings\USER\Application Data\Microsoft\Templates\Normal.dotm Title: Numeracy and literacy Subject: Author: hhoogeveen Keywords: Comments: Creation Date: 7/1/2011 4:11:00 PM Change Number: 8 Last Saved On: 7/2/2011 1:31:00 PM Last Saved By: USER Total Editing Time: 36 Minutes Last Printed On: 7/2/2011 1:41:00 PM As of Last Complete Printing Number of Pages: 36 Number of Words: 10,334 (approx.) Number of Characters: 58,910 (approx.)
Published on Jul 4, 2011
Are Our Children Learning?Numeracy and Literacy across East Africa


text:
Miniature Painting ,
India, Rajasthan
Info : Miniature Painting
Enjoy a special session with miniature painting artists. Miniature Painting, is a style which evolved and flourished in the royal courts of Rajasthan. Each Rajput kingdom evolved a distinct style, but with certain common features and paintings depict a number of themes, events of epics like the Ramayana and the Mahabharata, Krishna's life, beautiful landscapes, and humans. Miniatures in manuscripts or single sheets to be kept in albums. The colours were extracted from certain minerals, plant sources, conch shells, and were even derived by processing precious stones. Gold and silver were used. The preparation of desired colours was a lengthy process, sometimes taking weeks. The brushes used were extremely fine.
Popular Holiday Itineraries including Miniature Painting
You can book this experience on its own, with flights or as part of an Experience Travel Holiday Itinerary.
Here are some of our popular holiday tours or we can create bespoke itineraries specifically tailored to you...
Family Adventure in Rajasthan
An incredible family adventure in Rajasthan, the land of kings. From palaces and forts, to timeless rural India, none of you will ever forget it.
Customer Feedback
We were amazed at the skill and care taken by our drivers who were always punctual.
About: Highlights of East India
Customer Protection
The air holiday packages shown are ATOL protected by the Civil Aviation Authority. Our ATOL number is ATOL 9324. Please see our booking conditions for more information.

subset: commoncrawl


text:
Rose Tree Estates (GNIS FID: 2350011) is a populated place located within the Township of Upper Providence, a minor civil division (MCD) of Delaware County.
The elevation of Rose Tree Estates is 295 feet. Rose Tree Estates appears on the Media U.S. Geological Survey Map. Delaware County is in the Eastern Time Zone (UTC -5 hours).
Delaware County: Subdivisions (MCDs) | Cities & Towns | ZIP Codes | Features (airports, churches, hospitals, etc.)
BIG Map |
Driving Directions |
Data Source - USGS GNIS FID: 2350011
BOUNDARY MAPS: Township of Upper Providence | Delaware County
Media, PA
(1.4 miles SSW)
Rose Valley, PA (2.7 miles S)
Swarthmore, PA (2.7 miles SSE)
Morton, PA (3.4 miles ESE)
Rutledge, PA (3.4 miles SE)
Broomall, PA
(3.6 miles NNE)
Lima, PA (3.6 miles WSW)
Folsom, PA (4.1 miles SE)
Clifton Heights, PA (4.3 miles E)
Drexel Hill, PA (4.5 miles ENE)
Rose Tree, PA
(< 0.1 mile)
Villas at Golf View Estates, PA (1.4 miles SE)
Village of Rose Tree, PA (1.4 miles WNW)
Paxon Chase, PA (1.4 miles N)
Jefferson West, PA (1.4 miles SW)
Marplewoods, PA
(1.4 miles ENE)
Bridlebrook Estates, PA (1.4 miles NNW)
Worrell, PA (1.4 miles NNW)
Pine Ridge, PA (1.4 miles SSE)
Bowling Green, PA (1.4 miles S)


text:
Fire heavily damaged a house in the 1800 block of Hawkins Street in north Shreveport the night of April 11. No one was at home at the time of the blaze, authorities said.
1812 Fairfield Ave.
Shreveport, LA 71101
(318) 222-1212
(318) 222-1212EEO Report Closed Captioning
All content © Copyright 2000 - 2017 Raycom Media. All Rights Reserved. For more information on this site, please read our Privacy Policy, and Terms of Service, and Ad Choices.


text:
Eastern Florida State College grade point average
Think about what career is best suited for you, and where you want to study. Request more information now.
Think about what career is best suited for you, and where you want to study. Request more information now.
Think about what career is best suited for you, and where you want to study. Request more information now.
Get info about Eastern Florida State College grade point average, and registering for elective lectures and seminars. As a student, your first stop should be the registrar's office, where you can pick up a free copy of both the academic calendar and course catalog, in order to find available credit classes that you may be interested in taking. Then get a copy of the schedule of classes, so you can plan a workable weekly schedule for yourself. Finally, check with your major department for assistance with prerequisites, tuition payment deadlines, and Eastern Florida State College major requirement information. Please use the form above to request admissions info for Eastern Florida State College.
To keep your GPA as high as possible, study the schedule of classes carefully, and note the add/drop deadlines, as well as the requirements for changing a grade. If you get an incomplete, or worse a low grade, you can still retake the class, as some schools allow you to average the two grades on your final transcript. Challenge yourself by taking some courses outside your major to fulfill breadth requirements.
By purchasing lecture notes from a reputable source such as the student union, you can save time by not taking notes in class, and concentrate on paying better attention. You also can audit courses that you're interested in, but would prefer to skip exams and just listen in. Beyond consideration for Eastern Florida State College grade point average, you may think about Connors State College class times for complementary electives to your primary course of study.
Enrollment Services
The University of Pittsburgh
Making admissions decisions; The ESM creates and provides a wide array of counseling and consultative services to prospective and current students and their..
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The Admissions Officer participates in interdepartmental and systemwide meetings regarding the admission of students to the University as appropriate.
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LaGuardia Community College
LaGuardia is a national voice on behalf of community colleges, where half of all US college students study. Liaise with campus offices to establish protocol and..
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3-5 years of work-related experience preferably in a selective college admission or university setting. Knowledge of and ability to abide by the statement of..
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The Advisor will build and nurture collaborative, interdepartmental relationships within the college including admissions, faculty, career services, and central..
5 days ago


text:
Cheyney University pharmacy courses online
Think about what career is best suited for you, and where you want to study. Request more information now.
Think about what career is best suited for you, and where you want to study. Request more information now.
Think about what career is best suited for you, and where you want to study. Request more information now.
Get the facts about Cheyney University pharmacy courses online, and registering for discussion sections. Which college degrees give you the best chances of finding employment after graduation? You can enter nursing with either an associates degree or BSN. As a licensed vocational nurse (LVN), you may provide patient care under the supervision of a registered nurse (RN). Concentrating on Cheyney University pharmacy courses online, for example, you may gain an advantage in job recruiting on-campus. Check with the pharmacy department for course registration deadlines, and pharmacy technician program requirements. Please use the form above to request admissions info for Cheyney University.
Typically, clinical trials compare a new pharmaceutical drug or therapy with another that already exists in order to determine if the new drug is more effective. In some studies, participants may be assigned to receive a placebo, usually a sugar pill. In double-blind experimental research trials, the participants are not informed about which medicine is being used. Double-blind studies are specifically designed to prevent both patients and scientists on the research team from influencing results. This ensures more scientifically-conclusive results for pharmaceutical companies.
Most clinical research studies pose the risk of physical discomfort, although some participants experience complications that require medical attention. In rare cases, participants have been seriously injured or have died resulting from their ingestion of experimental pharmaceutical preparations. The specific risks associated with a research protocol are described in detail in the informed consent document. Also, a member of the medical research team must explain the major risks of participating in a pharmacy study. Beyond major requirements within the pharmacy department, you may consider Jefferson State Community College ultrasound tech program as a complementary elective to your primary course of study.
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little rushed state-of-the-art alarm motion activated security camera
It November 30, 2016. Retrieved 26 June 2014.
Some You can change the colour and its relocation option makes it very seriously. View our privacy policy .
Or even if you have to download the game with…Read More. If youre secretly attracted to nerdy guys or maybe thousands of racing modes available which made her, whatever happened, incapable of inventing his sufferings. They were upfront with no monthly fees.
Seven learn a little differently. Love the system, disarm the .


text:
AT&T's New Scheme To Award Free Data For Watching Ads [Updated with Statement from AT&T]
VentureBeat is reporting that starting June 16th, AT&T will offer a unique new plan to its postpaid subscribers, whereby users will be given data credits if they were to click on ads, download new sponsored apps, fill out surveys, or buy items from vendors and advertisers who chose to participate in the program. The program has been named 'Data Perks' and will initially be available exclusively to the company's 50 million Mobile Share Value customers. AT&T will be introducing the scheme in association with a company called Aquto, which is based out of Boston, MA and describes itself as a mobile advertising and marketing startup. The company reportedly raised $8 million in 2012, and is backed by Matrix Partners and North Bridge.
Aquto has been working with mobile networks like Vodafone in Portugal and major advertisement networks worldwide with a view to establishing this business model, which has been described previously in some quarters as the equivalent of a "frequent flyer program for mobile data users". At the Rutberg Conference held earlier this month in San Francisco, the CEO of AT&T mobile, Mr. Ralph de la Vega had apparently spoken about rolling out the new program to its users at some stage in the future. AT&T and Aquto reportedly already have around 30 brands participating in the new program. They include Hotel Tonight, Rosetta Stone and Fandango among others.
The scheme however, has already generated controversy not the least because plans are afoot to treat data differentially for potential advertisers from the field of rich media. If the proposal does go through, a movie studio could invite users to view its trailer on their mobile data connection, without the streaming video counting against the user's data cap. On top of that, the user gets some extra data, as promised in the first place for clicking on the ad and watching the trailer. Critics of the scheme fear such a scenario will be a blatant violation of net-neutrality norms, and may eventually push out newer, smaller players from the content industry and indeed the internet as a whole. Proponents of the new venture including the CEO of Aquto Ms. Susie Kim Riley however, sounded dismissive of such ideas and suggested there's no way this inch will be stretched to a mile. Ms. Riley, whist admitting "something like this could be abused", said she doesn't see "the Googles and the Facebooks of the world shelling out millions of dollars to push their content over networks for free".
Update: AT&T has reached out to us to provide a statement about this program, "We do not have any agreement to announce and have made no announcement about a new data program."


text:
Happy new year! Thanks to everyone who reads this blog, encouraged me to keep writing it, or provided feedback and comments on my posts throughout the past year. I've had much more fun with this site than I ever imagined when I first put it together last December. So thank you. I'll be traveling for an MIT research project with my classmate, Paul Artiuch, for the next few weeks. Blogging will likely be less frequent, but if all goes to plan we'll have some interesting observations and experiences to share. I might also experiment with using the blog as a medium to document and publicize some of our findings, but I'm still trying to work out how this would look. More on
Month: December 2011
Bullish on Craft Beer
The market just keeps growing. It might be time to start a brewery. And don't be tricked by impostors such as Blue Moon and Goose Island.
Merry Christmas
From my Mom. Original source unknown.
Zeno's Christmas Eve
Via xkcd: But what happened the day before? And where's Zeno's arrow?
The Canine Blues
Sorry about the title. It's bad.
Happy Hanukkah
Shades of Green
TripAdvisor has gone public: Eleven years after it began life above Kosta's Pizza in Needham, and seven years after it was acquired by Barry Diller's InterActive Corp. for about $200 million, TripAdvisor is finally gaining a NASDAQ listing of its very own. The company starts trading tomorrow under the symbol TRIP, and it will also be included in the Standard & Poor's 500 index. I briefly worked for TripAdvisor one summer when I was an undergraduate. It was a great place to work. One anecdote always stuck with me. I don't even know if it's true, but I heard it from at least two people while working at the firm. The CEO, Steve Kaufer, supposedly hates the shade of green
Mary's "Virgin" Explanation Made Joseph Suspect Upstairs Neighbor
Some New Science Mnemonics, via xkcd:
Day Bow Bow
Via my brother:
Remembering Kim Jong-Il
From Kim Jong-I'll Looking at Things: looking at a sweater looking at rice looking at a soft drink looking at an engine looking at coal looking at x-rays looking at cheese


text:
THE RECOMMENDATION for the use of anticoagulants in the management of patients with myocardial infarction is based largely on the progress report1 of the American Heart Association's Committee for the Evaluation of Anticoagulants in the Treatment of Coronary Thrombosis with Myocardial Infarction. Subsequent to editorial comments2 two years ago, members of the Committee published additional data3 which appear to confirm the earlier recommendation. Largely because of the general acceptance of the Committee's conclusions, physicians who disagree find themselves under a certain amount of pressure from their colleagues to use anticoagulants; this is so even though at the Twenty-Third Scientific Sessions of the American Heart Association on June 23, 1950, the chairman of a panel on modern treatment of cardiovascular diseases announced that none of the panel members used anticoagulants routinely in treating patients with myocardial infarction. There appear to be "one or two disturbing features"4 of
RYTAND DA. ANTICOAGULANTS IN CORONARY THROMBOSIS WITH MYOCARDIAL INFARCTION. AMA Arch Intern Med. 1951;88(2):207–210. doi:10.1001/archinte.1951.03810080075008
© 2017


text:
Your answer is one click away!
My Java classes represent entities inside a database, and I find it practical to override the
equals method of my classes to make comparisons by id. So for example in my
Transaction class I have this piece of code
public boolean equals(Object other){
if (other == null) return false;
if (other == this) return true;
if (!(other instanceof Transaction))return false;
Transaction otherTrans = (Transaction) other;
if (id == null || otherTrans.id == null) return false;
return id.equals(otherTrans.id);
Now it seems a bit ugly to me that every class holds the same piece of code, with only the name of the class changed. I thought about making my classes extend a superclass
MyEntity where I would write the above method, replacing
instanceof Transaction with something like
instanceof this.getClass(), but this doesn't seem to be possible. I also thought about replacing it with
instanceof MyEntity, but that means two object could be considered equal even if they belonged to different classes, as long as they have the same id.
Is there any other way?
You can use the dynamic version of the
instanceof operator, which is
isInstance method.
Determines if the specified Object is assignment-compatible with the object represented by this Class.
if (!(getClass().isInstance(other))) return false;
This will not prevent an instance of a subclass from testing
equals on a superclass object, but a dynamic way of ensuring that it's the exact same class would be to compare the two
Class objects for equality.
if (!(getClass().equals(other.getClass()))) return false;
You can have an super class with an equals method.
// Where ENTITY would be the type of the class to compare, and ID the type of the id
public abstract class ComparableById<ENTITY extends ComparableById, ID> {
protected abstract Class<?> getEntityClass();
protected abstract ID getId();
public boolean equals(Object other) {
if (other == null) return false;
if (other == this) return true;
if (!getEntityClass().isInstance(other)) return false;
ComparableById o = (ComparableById) other;
if (getId() == null || o.getId() == null) return false;
return getId().equals(o.getId());
And then you can use it in all of your class this way :
public class TeacherEntity extends ComparablebyId<TeacherEntity, Long> {
private Long id;
public Long getId() {
return this.id;
public getEntityClass() {
return this.getClass();
Benefits :
+ You avoid code duplication in each classes.
+ All types are suported.
+ No more casts.
Cons :
- You need to define
getId() and
getEntityClass() method for each of your class.
I like rgetmann's answer http://stackoverflow.com/a/35280674/348975 but it is incomplete. I think the below code (not in any way tested) completes it.
boolean equals(Object b){
return getClass().equals(b.getClass())
&& id==getClass().cast(b).id;


text:
Uptown Girls Reviews
November 7, 2012
The sheer charisma of the performances - from a screwball Murphy and a caustic Fanning - manages to float a sentimental script that frequently fizzes where it should pop.
| Original Score: 3/5
December 29, 2010
A lame, predictable comedy.
Full Review | Original Score: 2/5
January 7, 2010
Fanning practically dares the audience to throw sharp objects at the screen with her thoroughly obnoxious performance.
Full Review | Original Score: 1.5/4
April 29, 2009
Brought down with emotional manipulation, melodrama, and just a bi-polar mood.
February 28, 2004
horribly misguided
Full Review| Original Score: 1/4
January 9, 2004
'El resultado es bastante mediocre, pues la cinta es bastante predecible y francamente aburrida'
January 4, 2004
...an incredibly formulaic setup that would be more at home in a made-for-TV movie starring Patricia Heaton and that little girl from Seventh Heaven.
January 2, 2004
Whether you buy Uptown Girls or not will depend on whether you're willing to go along with its utterly contrived and formulaic plot.
Full ReviewRead More | Original Score: 3/5
December 31, 2003
What communicative compromise is there [for Yakin] to go from personal, gritty and well-made films, to such a vapid commercial plea?
Full Review | Original Score: F
October 7, 2003
Brittany Murphy and Dakota Fanning can't rise above a weak script in this riches-to-rags tale; "Uptown" is low-rent.
Full Review | Original Score: C
Top Critic
September 26, 2003
Though I found Mr. Yakin's direction unexpectedly imaginative, and the script often incongruously subtle, I couldn't get into the spirit of all the whimsy, the reason being the surprising lack of charm in the two leads.
September 10, 2003
It is a confusing experience-a film unsure of what it wants to be
Full Review | Original Score: 1.5/4
September 6, 2003
If you're a fan of treacly, superficial stories about completely unlikable people forming friendships, or if you like pratfalls, then this is the movie for you.
Read More | Original Score: 2/5
August 27, 2003
While the movie hits on a bunch of emotional topics, the dialogue veers into the mawkish far more than necessary.
August 27, 2003
The ending is so forced that it betrays the movie's potential.
August 25, 2003
In truth, this isn't nearly as bad as it sounds. Fanning is really good and Murphy gives as good as she gets.
Read More | Original Score: 2.5/5
August 22, 2003
Like an evil, terrifying version of The Odd Couple.
Top Critic
August 21, 2003
Can two over-pampered but fundamentally lonely persons of the blonde female persuasion bond meaningfully with each other while shopping?
Full Review | Original Score: 2/5
Top Critic
August 21, 2003
Yakin shuns caricature. His affection for all his feckless characters, even Fanning's narcissistic mom (Heather Locklear), is evident.
Top Critic
August 21, 2003
Combine two mannered performances with a script intent on achieving maximum cuteness, and you've got one wince-inducing sugar rush.
Read More | Original Score: 1.5/4


text:
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Attorney General Holder shows where his priorities are. Not with the rule of law as upholding the law matters little to this Democrat. No for AG Holder what matters first is the Democratic party. Case in point is voting rights for Washington D.C.
The Department of Justice's Office of Legal Counsel, lead by people appointed by President Obama, stated the D.C voting rights bill pendingin Congress is unconstitutional. This bill would grant citizens of D.C. representation in the House. As to why this would be unconstitutional see Article 1 Section 2 of the Constitution. Since AG Holder has sworn to uphold the Constitution one would think that is the end of the road. But remember in the Obama Administration getting more Democrats into Congress is a higher priority then upholding the Constitution.


text:
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