Tanzania Commission for Science and Technology
(COSTECH)
RESEARCH PROPOSAL
TITLE: Causes and Solutions for Dismal Performance of Science Subjects in Secondary Schools of Tanzania
Submitted by:
Task Force appointed by the R&D Advisory Committee on Basic Sciences
(COSTECH)
1 Introduction
1.1 Background
Tanzania Commission for Science and Technology (COSTECH) was established under the act of parliament of 1986. It is the principal advisory organ of government on all matters related to scientific research and technology development.
COSTECH has 12 R&D advisory committees, and these are the principal organs of the commission, responsible for coordinating all scientific/technological issues carried out in the country in respective fields. One of the R&D advisory committees deals with Basic Sciences.
During the 21st meeting of the R&D advisory committee on Basic Sciences, held on 21st December 2007, a paper was presented by Ms. Anastazia Martin from the Christian Social Services Commission on the “Trends of Performance in Science Subjects at Form Four Level in some selected Secondary Schools of Tanzania”. In this study, she revealed that the 200 schools under study between 1998-2005 showed dismal performance in Basic Science subjects. In particular, girls performance was poorer than boys and that Mathematics featured very badly by all sexes.
The Committee suggested therefore that the trends of performance in science subjects should be a theme of research and agreed to from a task force to look into reasons for such dismal performance, as it is a national problem.
The task force was therefore formed comprising of the following members;
1. Dr Allen R. Mushi Mathematics Department, UDSM
2. Mr. John Massawe TIE
3. Ms Anastazia Martin CSSC
4. Mr. Charles Philemon MoEVT
The team was required to deliberate on the problem and come up with a research proposal on causes and solutions for the dismal performance in Science subjects in Tanzania.
1.2 Terms of Reference:
1. To collect performance data for secondary schools over the years
2. To analyze collected data so as to verify the claim on dismal performance and their characteristics
3. Using analyzed data, find out the source(s) of the problem
4. Propose solutions which will help to solve the problem
1.3 Statement of the Problem
The performance of Science subjects for secondary schools in Tanzania has been very poor for many years. The situation has become worse over the years compared to non-science subjects. Impact of this state of affair is obvious, since Science and Technology plays major role in any country’s development.
1.4 Rationale
Tanzania is committed to serving her people through a framework which focuses on reduction of poverty, the National Strategy of Growth and Reduction of Poverty (NSGRP) or MKUKUTA. Tanzania is also committed to the Millennium Development Goals (MDGs) which are internationally agreed targets for reducing poverty, hunger, diseases, illiteracy, environmental degradation and discrimination against women by 2015.
The quality of education will determine the kind of science and technological development that the society will achieve. Science and Technology is no doubt, one of the most important components in the fight against poverty. It is quite obvious that science subjects are absolutely necessary for development of Science and Technology, which is an important component, if we have to achieve our national goals and targets in alleviating poverty.
1.5 Objectives
The main objective of this research is to investigate the causes of poor performance in Science subjects and to propose the sustainable solutions to reduce or to eradicate the situation.
The specific objectives are: -
(i) To determine the trend of Science subject performances in secondary schools in Tanzania.
(ii) To establish the causes of the observed trend.
(iii) To identify the factors that lead to poor performance in general and across the schools.
(iv) To propose the sustainable solution to the observed problem.
1.6 Project significance
This research will help to identify some main factors that lead to poor performance of Science subjects in schools using secondary level as a case study. The findings of the study will give light on how the real situation is and give valuable recommendations accordingly.
Several research works have been reported and proposed recommendations. However, the situation is getting even worse over the years, indicating that the best, sustainable and feasible solutions are yet to be found.
2 Research questions
1. What is the status of science subjects’ performance for secondary schools in Tanzania?
2. Are the mathematics teachers in secondary schools competent enough?
3. Are the teaching methods used science appropriately done?
4. How does the examination set correspond to the needs in science syllabi?
5. Do we have sufficient resources to make pupils understand science content?
6. Are other subjects negatively affected by science poor performances in schools?
7. What is the effect of marking procedures in performance of science?
8. Does science have unique features that require special attention compared to other subjects?
9. Is the curriculum well designed to cater for the needs of science learning?
10. Does society’s attitude towards science affect performance?
11. What type of environment and parental support that pupils get from the society?
12. What is the effect of the language used in teaching and learning in sciences?
13. Are students well motivated by society when it comes to science subjects learning?
14. What is the future of a science student after graduation?
15. Are there any special best practices that we can learn from?
3 Literature Review
Several projects have been working in trying to solve this problem, including the work by Female Education in Mathematics and Science (FEMSA) in Africa. FEMSA was a project under the Forum for African Women Educationalists (FAWE). The project was designed to attract more women into Science, Mathematics and Technology (SMT) and targeted girls schools in special pilot areas. Secondary Schools: 12 schools were selected from Bagamoyo, Karagwe, Bukoba, Ilala, Morogoro and Muleba districts. A number of publications have been produced including ([B2000]), ([F2000]), ([M2001]). They have presented success stories and various recommendations. Some of these include; Government should; improve the equity of distribution of educational facilities throughout the country; Design subject and examination syllabuses taking into account the resources and facilities available in the country, so that no one school is unduly disadvantaged by struggling to follow set syllabuses that call for use of materials and resources that are unavailable in their school. The drawbacks of the projects stems from the fact that it only concentrated on Girls performance, hence conclusions are not necessarily applicable to all cases.
The TEAMS project in Tanzania was established at the University of Dar es Salaam (UDSM) in the mid nineties of the last century as a response to a study which showed the poor state of science and mathematics in the country. The project, a cooperation between science and mathematics educators at UDSM and Dutch counterparts and funded by the Dutch government, was aimed at assisting with the production of more and better-qualified science and mathematics teachers. Specifically the project sought to help in setting up more productive and effective teacher education programs, to build capacity at UDSM via formal Masters and PhD studies of staff, to develop postgraduate programs for leadership development for stakeholders in the education system and to break the isolation of science teacher educators through international exposure. Successes have been reported in establishing new degree programmes and in-service training. The project involved several research studies and have been reported in a paper by Osaki et al ([O2005]). Unfortunately, performance in mathematics is still dropping over the years. It seems their effort is not adequate and some additional factors need to be established and worked on.
There have been complaints by the public that the students are performing badly in science and worse in mathematics. The Prime Minister acknowledged this fact in the 25th April 2008 speech to the Members of Parliament ([i]Pinda2008). He categorically pointed out that the overall performance at primary level has been rising, while the performance in mathematics has been declining. For instance, the overall PSLE pass rate in 2004 was 48.7%, 2005 was 61.8% and 2006 was 70.5%. In mathematics pass rate in 2003 was 63.6%, 2004 was 33.4%, 2005 was 47.6% in 2007 was 17.4%. The mathematics pass rate for girls in 2003 was 57.3% and 2007 was 11.1%. The mathematics pass rate for boys in 2003 was 69.9% and 2007 was 23.3%. At secondary school ordinary level he pointed out that performance in CSEE mathematics in 2003 was 26.9%, Physics 56.8%, Chemistry 65.1% and Biology 57.9%. The performance in mathematics was 29.9% in 2004, 23.4% in 2005 and 31.3% in 2006. The Prime Minister concluded that in the past three years, there has been a decrease in performance in science subjects with worse drop in mathematics performance.
Specifically, a number of reasons have been cited as sources of poor performance in Mathematics ([ii]Sumra2008; [iii]Masanja2002; Pinda2008, [iv]Kitta2008). The following are some of the listed sources of the problem;
1. Shortage of mathematics teachers.
2. The increase of students over the years is not proportional to number of teachers.
3. The inherited attitude that mathematics is a very difficult subject and therefore some students tends to hate it.
4. In primary schools, mathematics exams are structured in such a way that only final answers are marked.
5. Low motivation to teachers and students.
6. Nature of the examinations which do not correspond to the syllabus content.
7. Some of the mathematics teachers are weak due to their poor background.
8. Use of untrained teachers
9. Lack of basic and quality facilities such as books, and desks
10. More effort being directed to tuitions with low effort in ordinary classes.
Most of these reasons have not been properly investigated and tend to be rather speculations than evidenced research results. Furthermore, most of the reasons pointed out can easily apply to all other subjects and may not necessarily address the uniqueness of mathematics and science.
4 Methodology
The following components will be covered during the project activities;
4.1 Literature review
As observed in the initial literature review, a number of organizations have been working on this problem and have written report papers. We would like to know their findings in details and drawbacks so as to learn from their work. There is no point re-inventing the wheel and therefore our interest is to come up with concrete set of recommendations that will be practical and will yield short-term and long-term results. We expect to spend some time going through literature and build a strong base for our research work.
4.2 Fieldwork
During the course of investigation, the team will need to collect data from various sources including the National Examinations Council of Tanzania (NECTA), Ministry of Education and Vocational Training (MoEVT) offices, NGOs, higher learning institutions and most importantly visit schools around the country.
Since there are thousands of schools in Tanzania, it would not be possible to visit each and every school; instead sampling techniques have to be applied so as to come up with representative sample which will give us into credible conclusions without the need to cover all schools.
Here is the proposed sampling of schools to be visited by the team.
4.2.1 Distribution of Number of Secondary Schools in Tanzania (Mainland)
Table 1: Total number of Secondary Schools in Tanzania mainland (2007)
S/N / Education Level / Number of schools/colleges1 / O-LEVEL / 2,074
2 / A-LEVEL / 319
Totals / 2,393
Source: The United Rep. of Tz, BEST 2003-2007: National Data – MoEVT (Primary and Colleges), NECTA Results, A-level 2008,
4.2.2 The proposed Sample
Table 2: Proposed sample size for each region (21 regions of Tanzania mainland)
S/N / Education Level / Sample size (No. of Schools) / % / Sample size for each region / Sample size with Performance1 / O-LEVEL / 338 / 16.3 / 13 / Low / 6
Medium / 3
High / 4
2 / A-LEVEL / 78 / 24.5 / 4 / Low / 2
Medium / 1
High / 1
Totals / 416 / 20.4 / 17
Some regions will be given more priority as indicated depending on concentration of schools.
From Table 2, the proposed sample is 20.4% of the population. We need for each region to consider performance as Low, Medium and High as shown for comparison purposes. Again the proportion indicated is for fulfillment of the research need.
In A-level schools we need only those with Mathematics in their combination (PCM, EGM and PGM). Samples composition:
In the proposed samples in Table 2, the following groups will be considered as composition of the proposed sample
o Government, Non –Government
o Girls, Boys, Coed Schools
o Day, Boarding
o Urban, Rural
o Inspectorate zones/Regions representation
o Special needs schools
o English-medium, non-English medium primary schools
4.2.3 Time period for data analysis
For NECTA results, we propose to analyze data for a period of 15 years i.e. from 1992 to 2007. This period will give sufficient data to observe the trend in performance over the years. Furthermore, many have taken place between this period, including Diploma teachers who went through 2 years training instead of 3, and ‘Vodafasta’ teachers who went through 4 months of training, and explosion of Secondary schools (ward secondary schools).
4.2.4 Questionnaire design
Apart from physical data collection, a questionnaire will be prepared to ensure all variables are well captured. The questionnaire is an extremely important instrument in collecting data, both qualitative and quantitative. Stakeholders, including parents, students in all levels and organizations associated with Tanzanian education system will be interviewed. The instrument will be developed carefully so as to cater for all necessary details.
4.3 Data Analysis
After data collection, we will be in a position to probe sources of the problem. A set of hypothesis as developed over the data collection session will be put into test. Therefore, data analysis will be done using statistical software including SPSS and spreadsheet tools to confirm or discard some of the hypotheses.