Enhancement of private schools for collaboration to address gender equity gap of STEM education: Case study in Mbeya city of Tanzania

Isack Ephraim Kibona

doi:10.12688/f1000research.137430.1

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Enhancement of private schools for collaboration to address gender equity gap of STEM education: Case study in Mbeya city of Tanzania

[version 1; peer review: 1 approved with reservations]

Isack Ephraim Kibona

PUBLISHED 31 Oct 2023

Author details Author details

Department of Mathematics and Statistics, Mbeya University of Science and Technology, Mbeya, Mbeya Region, 00255, Tanzania

Isack Ephraim Kibona
Roles: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Project Administration, Writing – Original Draft Preparation, Writing – Review & Editing

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Abstract

Investment in education to guarantee gender equity in most developing countries has focused on modern teaching pedagogy, teaching and learning facilities, cultural issues and the likes. However, performance in private schools do set learnable examples of which if not ignored, a nation in question may take lessons and improve gender equity in science, technology, engineering and mathematics (STEM) education. Private secondary schools may serve as on way to enrich girls' enrolment in STEM for future career opportunities by scoring qualifiable grades in STEM subjects, provided that education investment environment not only favors public schools but also be in favor of private schools. In the study conducted in Mbeya city of Tanzania, the author investigated 58 secondary schools of which 32 were private schools. From these schools 7936 candidates sat for Certificate of Secondary Education Examination (CSEE) of 2022 in Mbeya city. 2232 candidates were from private schools. The analysis indicated that more girls with a potential to enter into STEM education came from private schools, and it is about twice the number of girls from public schools regardless of more girls candidates from public schools.

Chi-square testing of pass in STEM subjects between boys and girls verified that performance in private schools had no gender equity gap between boys and girls. On the other hand, boys outperformed girls in public schools.

Moreover, an estimation of 2202 candidates of which 999 were girls had at least a minimum pass in basic mathematics. Private schools contributed 626 (63%) of passes in basic mathematics.

Thus, appropriate collaboration with private schools might revamp not only girls’ enrolment but also clear gender equity gap in performance of STEM subjects if policy makers in education investment can do more improvement in the environment for education investment through private schools.

Keywords

STEM education, gender equity, Mbeya city of Tanzania, Private schools

Corresponding author: Isack Ephraim Kibona

Competing interests: No competing interests were disclosed.

Grant information: The author(s) declared that no grants were involved in supporting this work.

Copyright: © 2023 Kibona IE. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite: Kibona IE. Enhancement of private schools for collaboration to address gender equity gap of STEM education: Case study in Mbeya city of Tanzania [version 1; peer review: 1 approved with reservations]. F1000Research 2023, 12:1423 (https://doi.org/10.12688/f1000research.137430.1) First published: 31 Oct 2023, 12:1423 (https://doi.org/10.12688/f1000research.137430.1) Latest published: 31 Oct 2023, 12:1423 (https://doi.org/10.12688/f1000research.137430.1)

Introduction

Establishment of Sustainable Development Goals (SDGs) by the United Nations (UN) in September 2015 placed the world to ensure gender equity in science, technology, engineering and mathematics (STEM) education (Koehler, 2016; Leal Filho et al., 2022; Zorzano, 2020). Gender is commonly representing female or male, however, in this study, added to that describes the socio-cultural characters of masculinity and femininity according to practices by individual based on their culture, while sex describes the biological characteristics of women and men (Unicef & others, 2020). In this regard, gender may change with time and place depending on roles taken by women and men, whereas sex never change. Before 2016, sub-Saharan Africa had a substantial number of secondary schools whose quality of education was questionable according to United Nations, this being one of the reasons to launch SDG4 (Unterhalter, 2019).

Some regions of the world are closing gender equity gaps in STEM education like USA, and Europe (Kamberidou & Pascall, 2019), but gender inequity in STEM education is substantial in sub-Saharan Africa, the Arab states, and south and west Asia (Ismail, 2018; Loyalka et al., 2021). Emphasis to enhance STEM education in literature has centered resolution on pedagogical skills, low teacher student ratio, incompetent teachers, and education facility availability (Allen et al., 2016; Huang et al., 2022; Teo & Ke, 2014). Moreover, girls' poor participation in STEM subjects in secondary schools especially in sub-Saharan Africa are more associated with cultural practices and other reasons associated with masculinity (Adams & Baddianaah, 2023; Lewin, 2009).

Education policy makers in Tanzania engaged private sectors to run private schools along with public schools (Komba, 2017). This lead to contribution in containing not only enrolment issues in STEM education but also great improvement of gender equity (Weaver, 2011). Evaluation of private schools’ contribution is indispensable, this fact holds following the reality that graduates from private education sectors become part of the nation decent and future human resource capital (Achoui, 2009; Budhwar & Sparrow, 2002; Sebola, 2023). Table 1 presents the performance of students from 32 private schools in Mbeya city. Majority of students in privates’ schools passed in first and second division. Unlike in private schools, candidates in public schools' majority were in the fourth division Table 2.

Table 1. CSEE results of the 32 private schools in Mbeya city.

Divisions	Total	Girls	Boys
Div I	715	359	356
Div II	569	270	299
Div III	406	206	200
Div IV	480	267	213
Div 0	62	34	28
All Students	2232	1136	1096

Table 2. CSEE results of the 26 public schools in Mbeya city.

Divisions	Total	Girls	Boys
Div I	280	83	197
Div II	775	372	403
Div III	926	457	117
Div IV	2896	1711	1185
Div 0	827	370	457
All students	5704	2993	2711

In Tanzania, efforts to solve gender issues in STEM education is historical (Samoff, 1987). Several bodies like United States Agency for International Development (USAID) have supported to ease the tension of gender inequity in STEM education (Stromquist, 2006; Swainson, 2000).

This report unleashes aspects of private schools’ contributions in gender equity in STEM education following credible educational policies by the Tanzanian government and promotes improvement in education investment for harmonization of public and private schools. This study illustrated by concrete examples the contribution of private schools in STEM education. Contribution is not only an increase in number of students specializing in STEM subjects but also significant improvement in diminishing of gender equity gap of STEM education.

Figure 1 depicts performance in STEM subjects of biology, chemistry, physics and basic mathematics of 2232 candidates from 32 private secondary schools in Mbeya city. Comparable performance of 5704 candidates from 26 public schools Figure 1 indicated deprived performance in STEM subjects. In parallel to more girls’ enrolment over boys, more girls passed every STEM subject in private schools except for physics. However, regardless of more girl’s enrolment in public schools, boys outperformed girls in every STEM subject except for biology.

Figure 1. CSEE 2022 results of STEM subjects in private schools.

Objective

The study is for enhancing education investment policies along with engaging private school investments for collaboration to address challenges of gender equity in STEM education.

Specific objectives

i. Stimulate harmony and more collaboration between education policy makers and private schools investors to enrich gender equity in STEM education.
ii. Compare private schools and public schools’ performance of girls and boys in STEM subjects.

Methods

Methodologies in this study undertook over form four secondary school examination results for Mbeya city, Tanzania. In this regard, this study dealt with secondary data, already processed for student placement to the next education level, in this situation, analysis of sex or gender was not applicable from the raw data. That is study design, data collection and data analysis carried out free of considerations due to sex or gender. Thus, this study is about what is observed in the examination results and not how teachers reach these results. On the other hand, this study calls for more insights as to how these results are reached, which is not the scope of this study. Therefore, the scope of study is to examine whether gender has influence in the examination performance.

Study design

The author collected secondary schools’ performance data from National Examination Council of Tanzania. The data involved 58 secondary schools of which 32 were private and 26 public schools. The data tabulated in separation of private and public schools as in Table 3 and Table 4 respectively, indicating number of girls and boys in every STEM subject. The researcher processed the data, analyzed by employing chi-square test for interpretation, and eventually reported the finding.

Table 3. CSEE 2022 results of the STEM subjects in 32 private secondary schools. (Source: NECTA 2022).

Gender	Pass in Biology	Pass in Chemistry	Pass in Physics	Pass in Mathematics	Total
Girls	1020 (1032)	549 (544)	393 (412)	626 (601)	1136
Boys	1008 (996)	520 (525)	417 (398)	555 (580)	1096
Total	2028	1069	810	1181	2232

Table 4. CSEE Students performance of 26 public schools in STEM subjects.

Gender	Pass in Biology	Pass in Chemistry	Pass in Physics	Pass in Mathematics	Total
Girls	1616 (1737)	560 (697)	234 (396)	373 (536)	2993
Boys	1695 (1574)	768 (631)	520 (358)	648 (485)	2711
Total	3311	1328	754	1021	5704

Data collection

The Author conducted data collection by reading and recording from the report by NECTA of CSEE for the year 2022, particularly, selecting all Mbeya city secondary schools participated in the form four national examinations of year 2022. In addition to division-wise performance as organized by NECTA, the author went further by listing overall performance of every STEM subject and eventually bar charts plotted as in Figure 1 and Figure 2.

Figure 2. CSEE 2022 results of STEM subjects of public school in Mbeya city.

Data analysis

The author used the chi-square approach to determine whether there was a significant difference in the passing of STEM subjects between boys and girls. The focus of the STEM subjects was biology, chemistry, physics and basic mathematics. The degree of freedom evaluated leads to a critical value (p) from statistical tables, a test statistic computed for each group of students separately, and the decision made based 95% confidence interval. Records of number of passes in STEM subject are as listed in Table 3 and Table 4. No software were involved and all computations conducted manually, aided by Casio scientific calculator.

Calculation of Chi – square, $(χ^{2})$ :

Numbers in parentheses of Table 3 are theoretical expectations of gender equity. The author went through five steps to justify whether gender has an effect in the performance of STEM subjects.

Step 1: Define Null ( $H_{0}$ ) and Alternative Hypotheses ( $H_{1}$ ):

$H_{0}$ : For the students in Mbeya city from private secondary schools, gender has no effect to pass in STEM subjects.

$H_{1}$ : For the students in Mbeya city private secondary schools, gender has effect to pass in STEM subjects.

Step 2: State the confidence interval: $α = 0.05$

Step 3: Calculate degree of freedom (df) and state the critical value (p):

$df = (rows - 1) (columns - 1) = (2 - 1) (4 - 1) = 3$ , so critical value, p = 7.81473.

That is if chi-square ( $χ^{2}$ ) is greater than 7.81473, reject $H_{0}$ .

Step 4: Calculation of test statistic $χ^{2} = \sum \frac{{(f_{o} - f_{e})}^{2}}{f_{e}}$ , where $f_{e} = \frac{f_{c} f_{r}}{n}$ and $f_{0} = observed frequence,$ $f_{e} = expected frequence$ , $f_{c} = frequence of the column, f_{r} = frequence of the row$ , $n = total number of subjects .$

Step 5: Calculation of theoretical pass expectations: Girls expected to pass biology in first cell of Table 3,

{(Girls, biology)}_{11} = (2028 * 1136) / 2232 = 1032

χ_{pr}^{2} = \sum \frac{{(f_{o} - f_{e})}^{2}}{f_{e}}

χ_{pr}^{2} = \frac{{(1020 - 1032)}^{2}}{1032} + \frac{{(1008 - 996)}^{2}}{996} + \frac{{(549 - 544)}^{2}}{544} + \frac{{(520 - 525)}^{2}}{525} + \frac{{(393 - 412)}^{2}}{412} + \frac{{(417 - 398)}^{2}}{398} + \frac{{(626 - 601)}^{2}}{601} + \frac{{(555 - 580)}^{2}}{580} = 4.28

$χ_{pr}^{2} = 4.28 < 7.81473 = p$ . Therefore, the null hypothesis is true.

The author applied a similar testing to candidates of public schools.

With similar calculations as Table 3 of private schools, $χ_{p}^{2} = \sum \frac{{(f_{o} - f_{e})}^{2}}{f_{e}} = 318.33425$ for Table 4. However, $χ_{p}^{2} = 318.334 > 7.81473 = p$ . Therefore, we reject the null hypothesis.

Analysis of STEM prospects

The author went further to ascertain every student with a pass of at least D grade (minimum pass) in both physics and basic mathematics and classified this group as minimum pass in STEM. Moreover, students with at least two C grades and one D pass grade in any of three subjects: physics, chemistry and biology (PCB) or same passes in any of three: physics, chemistry and mathematics (PCM) classified as potential PCM or PCB candidates. A collection of students with minimum passes in STEM and/or potential PCM or PCB candidates grouped as potential STEM candidates.

Results

The degree of freedom for each group is three with α =0.05 of which the collected critical value, p =7.81473. Computed chi-squares were $χ_{pr}^{2} = 4.28$ for private schools $χ_{p}^{2} = 318.334$ for public schools. In addition to chi-square testing of the data, student performance in STEM subjects were listed in tabular (Table 3, Table 4) form along with plotting the bar charts (Figure 1, Figure 2).

Impact of performance of STEM subjects in STEM education prospects

Performance in STEM subjects determines number of candidate placements in high school PCB or PCM combinations and prospects of STEM career candidates in higher education institutions. Out of 2232 candidates, private schools contributed 783 (35%) candidates of which 380 were girls able to further studies in STEM education (Table 5). On the other hand, out of 5704 candidates, public schools contributed 699 (12%) candidates of which 206 were girls with potential to advance in STEM careers in higher education (Table 6).

Table 5. Estimated CSEE 2022 candidates to enter STEM career or major science from 32 private schools.

Gender	Pass in mathematics	Pass in physics and mathematics	Potential PCM or PCB	Potential STEM candidates	Total
Girls	626	380	379	380	1136
Boys	555	396	403	403	1096
Total	1181	776	782	783	2232

PCM: physics, chemistry and mathematics; PCB: physics, chemistry and biology; STEM: science, technology, engineering and mathematics.

Table 6. Estimated CSEE 2022 candidates to enter STEM career or major science from 26 public schools.

Gender	Pass in mathematics	Pass in physics and mathematics	Potential PCM or PCB	Potential STEM candidates	Total
Girls	373	206	205	206	2993
Boys	648	493	375	493	2711
Total	1021	699	580	699	5704

PCM: physics, chemistry and mathematics; PCB: physics, chemistry and biology; STEM: science, technology, engineering and mathematics.

Discussion

Based on the data analysis, we calculated critical value, p = 7.81473 and a test statistic computed $χ_{pr}^{2} = 4.209$ for all students’ performance in STEM subjects for private schools and $χ_{p}^{2} = 318.33425$ for public schools. It is clear that $χ_{pr}^{2} = 4.28 < 7.81473 = p$ , and $χ_{p}^{2} = 318.33425 > p .$ Recall the null and alternative hypothesis:

Null ( $H_{0}$ ) and Alternative Hypotheses ( $H_{1}$ ):

$H_{0}$ : For the students in Mbeya city from private/public secondary schools, gender has no influence to pass in STEM subjects.

$H_{1}$ : For the students in Mbeya city from private/public secondary schools, gender has influence to pass in STEM subjects.

In this regard, we do accept the null hypothesis for private schools and reject the null hypothesis for public schools. Therefore, private schools in Mbeya city resolved the gender equity gap in performance of STEM subjects. On the other hand, gender equity gaps are unresolved between girls and boys in STEM subjects’ performance for public schools. That implies that the gender equity gap shall extend to the future STEM careers of graduates from public schools, and therefore, spread to the whole nation and worldwide at large.

We suppose education policy had had recognized private sectors contribution and further promote teamwork along with private schools then more output that is stunning would surface. Thus, in so speaking, this study saves to encourage education policy makers to enrich policy mechanism for collaboration and possible embolden of private schools for more enrolment in STEM education. This is in parallel with the implementation of SDG4 realization in 2030. It is also clear that passing in both physics and basic mathematics determines the potential of STEM career prospects from secondary schools (Table 5, Table 6).

Conclusion and recommendations

Private schools’ reflection of balancing gender in STEM education in the case of Mbeya city offers a great step toward achieving SDG4 of the United Nations. The author recommends policy makers to engage private schools to address the challenges of gender equity in STEM education in a collaborative manner rather than existing in with public schools. STEM education stakeholders need to stress not only STEM careers position in the 21st century of job placements but also the importance of passing both basic mathematics and physics as determinants of STEM career for secondary school students. Basic mathematics alone is not enough.

This study is calling for further investigation as to why in the same nation with likely the same environment, private schools outperformed public schools to such great extent. The researcher will explore both parties separately to acquire reliable information to share experiences to avert the situation in public schools.

Data availability

Data used in this study are available and accessible for reproducibility. Information about public and private schools involved are all associated to Mbeya city CSEE results of 2022. Specifically, the Author used the data published by the National Examination Council of Tanzania (NECTA) from all test centers of the year 2022 (NECTA of CSEE for the year 2022).

Acknowledgements

First, I do appreciate Mbeya University of Science and Technology leadership for their strength and determination. Secondly, I do acknowledge the support in ideas by all colleagues in the Department of mathematics and statistics, to mention a few are; Mr. Justin Kisakali, Mr. Paulo Ngayekamwe and Ms. Tatu S. Irunde, who as well offered their time to work on behalf for some of the office routine activities. That gave a room for me to concentrate on writing. The whole members of the Department were willing to teach more classes, this boosted ending in small teaching load and therefore ability to write. Finally, my family support is indispensable in this task. They have been patient to all my late coming at home to ensure I am okay with this task. I must point out my youngest son, David.

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Version 1

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Author details Author details

Department of Mathematics and Statistics, Mbeya University of Science and Technology, Mbeya, Mbeya Region, 00255, Tanzania

Isack Ephraim Kibona
Roles: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Project Administration, Writing – Original Draft Preparation, Writing – Review & Editing

Competing interests

No competing interests were disclosed.

Grant information

The author(s) declared that no grants were involved in supporting this work.

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Published: 31 Oct 2023, 12:1423

https://doi.org/10.12688/f1000research.137430.1

© 2023 Kibona IE. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Kibona IE. Enhancement of private schools for collaboration to address gender equity gap of STEM education: Case study in Mbeya city of Tanzania [version 1; peer review: 1 approved with reservations]. F1000Research 2023, 12:1423 (https://doi.org/10.12688/f1000research.137430.1)

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Reviewer Report 22 Feb 2024

María Goretti Alonso de Castro, Regional Council of Education, Alcalá de Henares, Madrid, Spain

Approved with Reservations

https://doi.org/10.5256/f1000research.150590.r242769

While the study's objectives are clearly delineated and the methodologies are thoroughly explained, there remains a need for a clearer rationale behind the chosen analysis method. Furthermore, the study lacks an explicit discussion of its limitations and fails to address the variables that could potentially impact the observed differences between public and private educational centers. It is essential to delve into the analysis of contextual variables such as methodologies utilized, available resources, family support systems, socioeconomic status, and cultural influences to better comprehend the disparities in outcomes between these educational settings. A more comprehensive examination of the study's limitations and the myriad factors influencing the differences outlined in the article is warranted. This would significantly enhance the depth and rigor of the research, providing a more nuanced understanding of the observed discrepancies.
Regarding replicability, the text references the state test database; however, it lacks clarity on the selection process, sample criteria, and the variables considered in the presented tables. A more detailed explanation of the methodology behind selecting the state test database, the criteria for sample inclusion, and the specific variables incorporated into the tables would significantly enhance the transparency and replicability of the study.

Is the work clearly and accurately presented and does it cite the current literature?

Yes
Is the study design appropriate and is the work technically sound?

Partly
Are sufficient details of methods and analysis provided to allow replication by others?

Partly
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Partly
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Education, Technology, ICT, Educational European projects; Educational Inspection

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

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Author Response 13 Apr 2024

Isack Ephraim Kibona, Department of Mathematics and Statistics, Mbeya University of Science and Technology, Mbeya, 00255, Tanzania

13 Apr 2024

Author Response

The Author has responded by including a section informing limitations of the study, see an attachment. Moreover, the data involved (CSEE 2022) in the study enabled the study to reveal ... Continue reading The Author has responded by including a section informing limitations of the study, see an attachment. Moreover, the data involved (CSEE 2022) in the study enabled the study to reveal unfair prevailing situation in secondary schools but on the other hand situation about contextual variables such as methodologies utilized, available resources, family support systems, socioeconomic status, and cultural influences shall need more data pertaining to tools such as questionnaire and interview.

On selection criteria, all schools in the city in the given year of study went into participation in this study, therefore, the study involved city school population. Thus, for reproducibility of the study, one shall need to study all secondary schools in the city that participated in the CSEE 2022.
The Author has responded by including a section informing limitations of the study, see an attachment. Moreover, the data involved (CSEE 2022) in the study enabled the study to reveal unfair prevailing situation in secondary schools but on the other hand situation about contextual variables such as methodologies utilized, available resources, family support systems, socioeconomic status, and cultural influences shall need more data pertaining to tools such as questionnaire and interview.

On selection criteria, all schools in the city in the given year of study went into participation in this study, therefore, the study involved city school population. Thus, for reproducibility of the study, one shall need to study all secondary schools in the city that participated in the CSEE 2022.
Competing Interests: No competing interests available to this review process. Close
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Author Response 13 Apr 2024

Isack Ephraim Kibona, Department of Mathematics and Statistics, Mbeya University of Science and Technology, Mbeya, 00255, Tanzania

13 Apr 2024

Author Response

The Author has responded by including a section informing limitations of the study, see an attachment. Moreover, the data involved (CSEE 2022) in the study enabled the study to reveal ... Continue reading The Author has responded by including a section informing limitations of the study, see an attachment. Moreover, the data involved (CSEE 2022) in the study enabled the study to reveal unfair prevailing situation in secondary schools but on the other hand situation about contextual variables such as methodologies utilized, available resources, family support systems, socioeconomic status, and cultural influences shall need more data pertaining to tools such as questionnaire and interview.

On selection criteria, all schools in the city in the given year of study went into participation in this study, therefore, the study involved city school population. Thus, for reproducibility of the study, one shall need to study all secondary schools in the city that participated in the CSEE 2022.
The Author has responded by including a section informing limitations of the study, see an attachment. Moreover, the data involved (CSEE 2022) in the study enabled the study to reveal unfair prevailing situation in secondary schools but on the other hand situation about contextual variables such as methodologies utilized, available resources, family support systems, socioeconomic status, and cultural influences shall need more data pertaining to tools such as questionnaire and interview.

On selection criteria, all schools in the city in the given year of study went into participation in this study, therefore, the study involved city school population. Thus, for reproducibility of the study, one shall need to study all secondary schools in the city that participated in the CSEE 2022.
Competing Interests: No competing interests available to this review process. Close
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María Goretti Alonso de Castro, Regional Council of Education, Alcalá de Henares, Spain

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María Goretti Alonso de Castro, Regional Council of Education, Alcalá de Henares, Madrid, Spain

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Approved With Reservations

Is the work clearly and accurately presented and does it cite the current literature?

Yes
Is the study design appropriate and is the work technically sound?

Partly
Are sufficient details of methods and analysis provided to allow replication by others?

Partly
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Partly
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Education, Technology, ICT, Educational European projects; Educational Inspection

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Author Response

13 Apr 2024

Isack Ephraim Kibona, Department of Mathematics and Statistics, Mbeya University of Science and Technology, Mbeya, 00255, Tanzania

The Author has responded by including a section informing limitations of the study, see an attachment. Moreover, the data involved (CSEE 2022) in the study enabled the study to reveal unfair prevailing situation in secondary schools but on the other hand situation about contextual variables such as methodologies utilized, available resources, family support systems, socioeconomic status, and cultural influences shall need more data pertaining to tools such as questionnaire and interview.

On selection criteria, all schools in the city in the given year of study went into participation in this study, therefore, the study involved city school population. Thus, for reproducibility of the study, one shall need to study all secondary schools in the city that participated in the CSEE 2022.

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Alongside their report, reviewers assign a status to the article:

Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested

Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.

Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions

[1] Achoui MM: Human resource development in Gulf countries: An analysis of the trends and challenges facing Saudi Arabia. Hum. Resour. Dev. Int. 2009; 12(1): 35–46. Publisher Full Text

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Enhancement of private schools for collaboration to address gender equity gap of STEM education: Case study in Mbeya city of Tanzania

Abstract

Keywords

Introduction

Table 1. CSEE results of the 32 private schools in Mbeya city.

Table 2. CSEE results of the 26 public schools in Mbeya city.

Figure 1. CSEE 2022 results of STEM subjects in private schools.

Objective

Methods

Study design

Table 3. CSEE 2022 results of the STEM subjects in 32 private secondary schools. (Source: NECTA 2022).

Table 4. CSEE Students performance of 26 public schools in STEM subjects.

Data collection

Figure 2. CSEE 2022 results of STEM subjects of public school in Mbeya city.

Data analysis

Analysis of STEM prospects

Results

Impact of performance of STEM subjects in STEM education prospects

Table 5. Estimated CSEE 2022 candidates to enter STEM career or major science from 32 private schools.

Table 6. Estimated CSEE 2022 candidates to enter STEM career or major science from 26 public schools.

Discussion

Conclusion and recommendations

Data availability

Acknowledgements

References

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