Research proposal writer

DETERMINANTS OF ACADEMIC ACHIEVEMENTS IN MATHEMATICS IN PRIMARY SCHOOLS A CASE STUDY OF MUKONO GOMA DIVISION

BY

MUHUMUZA RICHARD

ABSTRACT

Mathematics teachers have on several accounts been judged as the main determinant in the success or failure of students in mathematics, while other scholars indicate that poor achievement in mathematics has been attributed to two broad factors which include; Heredity and environmental factors. To be in position to understand the determinants in the performance of mathematics the researcher will use several theories. These theories will be systems theory and in an analysis of the systems theory, Bertalanffy (1920) indicates that no single factor can explain a specific phenomenon. Kisker, Lipka, Adams, Rickard, Andrew-Ihrke, Yanez, & Millard, (2012) indicate that many factors determine the academic achievement of students in mathematics and no single factor can explain that. Bandura theory of social learning indicates that much of the development in human  cognition  is  explained  by  the  interplay  of  internal  personal  factors  in  the  form  of cognitive,  affective  and  biological  events while Wahlberg’s theory of educational productivity; Walberg’s (1981) theory of educational productivity posits that psychological characteristics of individual students and their immediate environments influence students’ cognitive, behavioral, and attitudinal outcomes (Reynolds & Walberg, 1992) and Satish (2013).

Research attention has been given to academic achievement in mathematics in the scholarly world.  However, several gaps arise from such studies.  For example, most studies are in advanced countries, the sample size used was small and most of the studies use qualitative methods of research. After the identification of the theories, the past studies will be reviewed on academic performance in mathematics.

1.0 INTRODUCTION

According to Idowu, (2016) achievement in mathematics by students is a global challenge since most students view mathematics as difficult and they would rather not concentrate on. He further indicates that students’ achievement in mathematics is affected by the distance students’ move from home and the populations in the school all have a significant effect on the academic achievement of the students in mathematics. On the same note, Idowu (2015) indicates that Mathematics teachers have on several accounts been judged as the main determinant in the success or failure of students in the subject.

Dauda, Jambo & Umar, (2016) indicate that poor achievement in mathematics has been attributed to two broad factors which include; Heredity and environmental factors which can be subdivided into students home, teachers and school factors. These authors, therefore, believe hereditary factors influence a student’s achievement in mathematics, on the contrary Satish (2013) indicates that the causes of students’ mass failure in mathematics is mainly related to students social-economic background and lack of qualified trained mathematics teachers in some schools.

Gitaari, Nyaga, Muthaa, & Reche, (2013) notes that poor achievement in mathematics is linked to students’ absenteeism, poor entry marks, poor assessment techniques, and poor teaching methods while Suleiman& Araba, (2019)  indicated that there are numerous factors for poor achievement of students in school mathematics, among such factors mentioned include overpopulation of students in the classroom, poor content and context of instruction and lack of good textbooks.

In deriving the factors that determine achievement of students in mathematics, several theoretical frameworks are available, and of these, the researcher intends to; (i) to review some of the systems theory, (ii) Bandura’s Theory of Learning (iii) Walberg’s theory of educational productivity (iv) to review past studies on achievement in mathematics; and hence (iv) to develop hypotheses basing on determinants on the achievement in mathematics to guide further studies.

Traditional theories on academic achievement

The first objective is to review some of the traditional models which guide studies on academic achievement in mathematics.  These include the systems theory (subsection 2.1), the bandura theory of social learning (subsection 2.2), and Walberg’s theory of educational productivity (subsection 2.2.1).

2.1 Systems theory

Originating in biology, systems theory was developed in the 1950s against the backdrop of a need to have a set of systematical theoretical constructs to discuss the empirical world (Boulding, 1956; Bertalanffy, 1951). This is one of the frameworks which is essential for guiding studies on the factors related to academic achievement.  General systems theory is the skeleton of science in the sense that it aims to provide a framework or structure of systems on which to hang the flesh and blood of particular disciplines and particular subject matters in an orderly and coherent corpus of knowledge” (Boulding, 1956). Bertalanffy (1920) indicates that no single factor can explain a specific phenomenon. Kisker, Lipka, Adams, Rickard, Andrew-Ihrke, Yanez, & Millard, (2012) indicates that many factors determine academic achievement of students in mathematics and no single factor can explain that, Bertalanffy,(1951) emphasized that real systems are open to, and interact with their environments and that they can acquire qualitatively new properties through emergence, resulting in continual evolution. According to Hasz, & Lamport, (2012) the pupils are faced with a lot of environmental factors that affect their ability to perform in key subjects like mathematics.

Each student comes from a home that has its challenges and opportunities which they present to the child. Rather than reducing an entity to the properties of its parts or elements, systems theory focuses on the arrangement of and relations between the parts which connect them into a whole.  Particular organizations determine systems, which are independent of the concrete substance of the elements. Thus, the same concepts and principles of organization underlie the different disciplines, providing a basis for their unification. Systems concepts include system-environment boundary, input, output, process, state, hierarchy, goal-directedness, and information (Johnson, Kast, & Rosenzweig, 1964).

Systems analysis developed independently of systems theory, it applies systems principles to aid a decision-maker with problems of identifying, reconstructing, optimizing, and controlling a system, while taking into account multiple objectives, constraints, and resources. It aims to specify possible courses of action, together with their risks, costs, and benefits. Systems theory is closely connected to cybernetics, and also to system dynamics, which models change in a network of coupled variables (Johnson, Kast, & Rosenzweig, 1964).

This theory assumes that the systems are made of many factors, Mohd, Mahmood & Mohd (2011) assert that the academic achievement of students in mathematics cannot be explained by a single factor while Olarewaju (2010) indicates that teacher training and students attitudes towards mathematics is key towards explaining the achievement of pupils in mathematics.

Several studies like (Olarewaju (2010), Mohd, Mahmood & Mohd (2011), Johnson, Kast, & Rosenzweig, 1964), Hasz, & Lamport,. (2012), Kisker, Lipka, Adams, Rickard, Andrew-Ihrke, Yanez, & Millard, (2012), Boulding, 1956; von Bertalanffy, 1951), due to wide usage of systems theory by several scholars it is therefore evident that this theory is popular and therefore the researcher will use systems theory in explaining the determinants of academic achievement in mathematics.

2.2 Bandura theory of social learning

The study will use Bandura’s Social Learning Theory. According to social learning theory, behaviors can also be learned through observation and modeling. This theory believes that children learn by observing the actions of others, including parents and peers (Nabavi, 2012).

The social learning theory further indicates that children develop new skills and acquire new information. This theory indicates that children learn differently basing on their environment and surrounding. The environmental or societal aspect of social learning theory says that children learn in a social context. This reinforces the idea that when there is a change in the child’s environment, the child’s behavior may change and ultimately their attitude as stated by McLeod (2011) who further indicates that behaviors are learned from the environment through the process of observational learning.

Lou (2013), opined that Bandura proposed the concept of social cognitive theory. A general contention is that much of the development in human cognition is explained by the interplay of internal personal factors in the form of cognitive, affective and biological events; behavior;  and environmental events. In addition to that with a heavy emphasis on how the child’s environment affects him and directs his learning, this theory indicates that the child’s accountability for his actions is limited and the environment has an influence on the behaviors of the children.

Several studies like (Driscoll, 1994, Weinstein & Mayer (1986), Shuell (1986), Hoffman, (1993), Stokes, (1986), Pajares, (2004), used Bandura theory of social learning in explaining determinants of academic achievement. Edinyang & Sunday, (2016), Nabavi  (2014),  have reviewed the literature on determinants of academic achievement, this means bandura’s social learning theory is very popular and will be necessary to be used in this study.

According to Muro & Jeffrey (2008), Bandura believes that direct reinforcement could not account for all types of learning. For that reason, in his theory he added a social element, arguing that people can learn new information and behaviors by watching other people.

2.2.1 Walberg’s theory of educational productivity

Walberg’s (1981) theory of educational productivity posits that psychological characteristics of individual students and their immediate environments influence students’ cognitive, behavioral, and attitudinal outcomes (Reynolds & Walberg, 1992).

Satish (2013) indicates that the causes of students’ mass failure in high schools are mainly related to students’ poor socio-economic background and lack of qualified mathematics teachers in schools.

In another study, depoju, (2011) stated that there are numerous factors as the reasons for poor Achievement of students in school examination, among such factors mentioned include overpopulation of students in the classroom, poor content and context of instruction and lack of good textbooks. Apart from the fact that the mass failure of students in public examination constitutes wastage on investment in education,   Suleiman& Araba, (2019) indicated that poor Achievement in mathematics has been attributed to two broad factors which include: Heredity and environmental factors which can be subdivided into students, home, teachers, and school factors.

Walberg’s (1981) theory of educational productivity, which is one of the few empirically tested theories of school learning based on an extensive review and integration of over 3,000 studies (DiPerna,& Stephen, 2002).   Using a variety of methods, Wang, et al. (1977) identified different categories of learning that influence most domains of variables, Some of them involved social-emotional influences:  classroom management, parental support, student-teacher interactions, social-behavioral attributes, motivational- effective attributes, the peer group, school culture, and classroom climate (Greenberg et al., 2003).

Wang et al. (1997) indicated that direct intervention in the psychological determinants of learning, promises the most effective avenues for reform. Wang et al.’s research review targeted student learning characteristics (i.e., social, behavioral, motivational, affective, cognitive, and metacognitive) as the set of variables with the most potential for the modification that could, in turn, significantly and positively affect student outcomes (DiPerna et al., 2002).

Olarewaju (2010) notes that the lack of qualified mathematics teachers as one of the factors responsible for students’ dismal Achievement in mathematics in Nigerian senior secondary schools. He further indicated that there is a need for well-trained teachers in schools to enable the students to perform well in mathematics. in his research schools with well-trained teachers had better Achievement in mathematics than their counterparts.

According to Isabelo & Silao,(2018) indicated that the relationship between attitude and mathematics achievement has not been fully consented by most scholars.  Attitude is one of the most potent factors that relate to achievement. In general, attitudes, beliefs, and emotions are the major descriptors of the affective domain in mathematics education.

Zins, Weissberg, Wang, and Walberg, (2004) demonstrated the importance of the domains of motivational orientations, self-regulated learning strategies, and social/interpersonal abilities in facilitating academic achievement.  Zins et al., (2004) further reported that based on the large-scale implementation of a Social-Emotional Learning (SEL) program students who became more self-aware and confident regarding their learning abilities, who were more motivated, who set learning goals, and who were organized in their approach to work (self- regulated learning) performed better in mathematics at school.

Akey (2006) states motivation and attitude towards mathematics influences the efforts they put in understanding and practicing mathematical concepts and skills, this later affects their achievement in mathematics subject. Best, Miller, & Naglieri, (2011) also assert that students’ beliefs about their competence and their expectations for success in school have been directly linked to their levels of engagement, as well as to emotional states that promote or interfere with their ability to be academically successful in subjects like mathematics.

According to Greenberg, Weissberg, O’Brien, Zins, Fredericks, Resnick, & Elias, (2003), Zins et al. (2004), academic achievement in mathematics is affected by social, emotional, and academic factors in mathematics are sufficiently strong to advance the new term social, emotional, and academic learning (SEAL).

Walberg’s (1981) model specifies that; Classroom learning is a multiplicative, diminishing-returns function of four essential factors, student ability and motivation, and quality and quantity of instruction.

Several scholars have used Walberg’s theory in explaining determinants of academic achievement and some of the scholars include; DiPerna, Volpe & Stephen, (2002), Greenberg et al., (2003), DiPerna et al., (2002), Greenberg, Weissberg, O’Brien, Zins, Fredericks, Resnick, & Elias, (2003), Zins et al. (2004) and Haertel et al., (1983).

The consensus of such reviews is that Walberg’s theory of educational productivity has been greatly used to guide studies on the factors related to academic achievement.

3.1 Seminal Papers on academic achievement

The papers, Poorghorban, Jabbari, & Chamandar, (2018). Gersten, Jordan, & Flojo, (2005), Best, Miller, & Naglieri, (2011), Anaduaka, & Okafor, (2013), Roby, Maistry, Owens-Ibie, Ntseane, Nthomang, Segwabe, & Lekganyane, (2010), Suleiman, & Hammed, (2019), Suleiman, & Hammed, (2019), Etuk, Afangideh, & Uya, (2013), Popoola, & Olarewaju, (2010), JERRY, (2018) and Ker, (2013) that have made contributions on academic achievement of students in mathematics.  In this section, we hint on two scholars only Idowu, (2016) and Maganga, (2016). Academic achievement in mathematics by Idowu, (2016) indicates that in civilized and developed countries, schooling resources that cost money, including class size reduction, higher teacher salaries, modern school buildings, and equipment, are positively associated with student achievement in mathematics. Although money alone may not be the only solution, the more equitable and adequate allocation of financial inputs to schooling does provide opportunities for improving the equity and adequacy of outcomes of the students in subjects like mathematics.

Idowu, (2016) also indicates that Numerous factors were identified by some researchers for the inconsequential achievement by students, some of which included: the shortage of qualified mathematics teachers, poor facilities, equipment, and instructional materials for effective teaching. Idowu, (2016) further indicates that a shortage of qualified mathematics was judged to be the most contributing factor to poor achievement in mathematics.

3.2 Papers on achievement in mathematics

Researchers, like (Kisker, Lipka, Adams, Rickard, Andrew-Ihrke, Yanez,  Millard, (2012), Qiu, & Chung, (2017), Cupani, de Minzi, Pérez, & Pautassi, (2010), Close, S. (2013) have reviewed the literature on academic achievement. Maryam Poorghorban, Susan Jabbari & Fatemeh Chamandar, (2018) indicated that Students’ attitude towards mathematics influences the efforts they put in understanding and practicing mathematical concepts and skills. Students’ beliefs about their competence and their expectations for success in school have been directly linked to their levels of engagement, as well as to emotional states that promote or interfere with their ability to be academically successful, on the contrary, Best, Miller, & Naglieri, (2011) indicates that cognitive involvement is an effective factor in educational progress especially in areas of achievement in mathematics, They further note that students’ mass failure in high schools is mainly related to students social-economic background and poor socio-economic background and lack of qualified mathematics teachers. He concluded that there is a general impression that mathematics is difficult by its very nature.

3.3 Literature review on academic achievement in mathematics

Researchers (Azizah, & Hartono, (2018), Nicolaidou, & Philippou, (2003), Gomez-Chacon, (2000), Mensah, Okyere, & Kuranchie, (2013), Zan, & Di Martino, (2014), Manoah, Indoshi, & Othuon, (2011), Azizah, & Hartono, (2018), Mohd,  Mahmood, & Ismail, (2011), Visser, Juan, & Feza, (2015), Mohamed, & Waheed, (2011), Manoah, Indoshi, & Othuon, (2011), Mensah, Okyere, & Kuranchie, (2013), Gidena, & Gebeyehu, (2017), Katusiime, (2018), Yohannes, (2017), Berry, Bhaird, & O’Shea, (2015), in analyzing this further we shall look at, Kiplagat, Role, and Makewa, (2012), who indicates that Learners’ competency in numeracy and literacy in early grades affects their academic achievement more generally in later years and affects how they master other subjects.  Makewa, (2012) further indicates that a claim that a large part of bad achievement in national examinations in Kenya is contributed by poor achievement in mathematics apart, from that learning largely depends on the teacher. The job of a teacher is to impart knowledge, skills, attitudes, and mathematical concepts into the learner. To achieve this, teachers are advised to give assignments, projects, and tests to evaluate their pupils and discuss the results with them.

3.4 Hypothesis and paradigm shift on academic achievement in mathematics

Following the literature review, it becomes apparent that research attention has been given to academic achievement in mathematics in the scholarly world.  However, several gaps arise from such studies.  For example, the studies on academic achievement have delt more prominently on advanced countries and non has been there specifically for Mukono district schools, more to that most other studies on academic achievement in mathematics have been carried out for secondary schools students, Idowu (2015). This also presents a bias towards primary school pupils. The cited studies also suggest a bias against the developing world (Jordan & Dinh, 2012), the studies also used only one data analysis method mainly quantitative.  More to that Suleiman and Araba, (2019) study used a small sample size of 280. This study will have to use at least a large sample size of more than 350 respondents to be in a position to cover a large population and get more information regarding the study.

Therebefore basing on the above factors this study must be carried out on the determinants of academic achievement as it will be both quantitative and qualitative with large sample size and it will also be carried out in Mukono district, Goma, division.

3.5 Analysis of the literature

Table 1 below indicates that various scholars have researched academic performance in varying degrees for example Isabelo & Silao,(2018) carried out a study on factors affecting mathematics problem-solving skills. However, the study was carried out in the Philippines this therefore presents a gap to be filled with this study to carry out determinants of academic achievements in mathematics in primary schools a case study of the Mukono Goma Division.    Table 1 also further indicates that though scholars like Nicolaidou & Philippou (2003) have carried out a study in mathematics they specifically concentrated on attitudes towards mathematics this, therefore, leaves a gap to be filled by this study on determinants of academic achievement in mathematics while Popoola, F. R., & Olarewaju, R. R. (2010) carried out a research on academic performance in mathematics and on the same note Suleiman, Y., & Hammed, A. (2019) study was carried out in Nigeria all these present perfect gaps to the study and lastly Best, J. R., Miller, P. H., & Naglieri, J. A. (2011)  study doesn’t necessary point out to the topic.

Context of the studies

REFERENCES

Ali, H. O. (2013). Factors affecting students’ academic achievement in mathematical sciences department in tertiary institutions in Nigeria. US-China Education Review, 3(12), 905-913.

Abdulkarim, A., & Baba, M. M. (2019). TEACHERS PERCEPTION OF THE CAUSES OF POOR ACHIEVEMENT IN MATHEMATICS AMONG PUBLIC SECONDARY SCHOOLS STUDENTS IN GOMBE STATE, NIGERIA: IMPLICATIONS FOR COUNSELING FOR NATIONAL DEVELOPMENT. Journal of Information Technology Educators and Researchers (JITER), 1(2).

Idowu, O. O. (2016). An Investigation of Mathematics Achievement of High School Students in Lagos state, Nigeria: External Factors. Urban Education Research & Policy Annuals, 4(1).

Gitaari, E. M. E., Nyaga, G., Muthaa, G., & Reche, G. (2013). Factors contributing to students poor achievement in mathematics in public secondary schools in Tharaka South District, Kenya.

Maslow, A. H. (1943). A theory of human motivation. Psychological review, 50(4), 370.

Kasenene, A., Baidya, A., Shams, S., & Xu, H. B. Manuscript NO: 45768 Manuscript Type: META-ANALYSIS Evaluation of tumor response to antiangiogenic therapy in patients with recurrent gliomas using contrast-enhanced perfusion-weighted magnetic resonance imaging techniques: A meta-analysis.

sMonyane, T. G., & Okumbe, O. J. (2012). An evaluation of cost achievement of public sector projects in the Free State province of South Africa. Emuze, FA (Eds) 2nd NMMU Construction Management Conference, 11-197. Port Elizabeth, South Africa.

Poorghorban, M., Jabbari, S., & Chamandar, F. (2018). Mathematics Achievement of the Primary School Students: Attention and Shifting. Journal of Education and Learning, 7(3), 117-124.

Gersten, R., Jordan, N. C., & Flojo, J. R. (2005). Early identification and interventions for students with mathematics difficulties. Journal of learning disabilities, 38(4), 293-304.

Best, J. R., Miller, P. H., & Naglieri, J. A. (2011). Relations between executive function and academic achievement from ages 5 to 17 in a large, representative national sample. Learning and individual differences, 21(4), 327-336.

Anaduaka, U. S., & Okafor, C. F. (2013). The universal basic education (UBE) programme in Nigeria: Problems and prospects. Basic Research Journal of Education Research and Review, 2 (3): 42, 48.

Roby, J., Maistry, M., Owens-Ibie, N., Ntseane, D., Nthomang, K., Segwabe, M., … & Lekganyane, E. M. (2010). Social development and evidence-based practice Articles The spirituality of vulnerable children in South Africa: Implications for social development and welfare. Journal of Social Development in Africa, 25(2).

Suleiman, Y., & Hammed, A. (2019). Perceived Causes of Students’ Failure in Mathematics in Kwara State Junior Secondary Schools: Implication for Educational Managers. International Journal of Educational Studies in Mathematics, 6(1), 19-33.

Suleiman, Y., & Hammed, A. (2019). Perceived Causes of Students’ Failure in Mathematics in Kwara State Junior Secondary Schools: Implication for Educational Managers. International Journal of Educational Studies in Mathematics, 6(1), 19-33.

Udonsa, A. E. Strategies to Improve Nigerian Students’ Achievement in Mathematics.

Etuk, E. N., Afangideh, M. E., & Uya, A. O. (2013). Students’ Perception of Teachers’ Characteristics and Their Attitude towards Mathematics in Oron Education Zone, Nigeria. International Education Studies, 6(2), 197-204.

Popoola, F. R., & Olarewaju, R. R. (2010). Factors responsible for poor achievement of students in mathematics in Nigerian secondary schools. Journal of Research in Education and Society, 1(2), 55-65.

JERRY, O. K. (2018). FACTORS AFFECTING STUDENTS’ACHIEVEMENT IN MATHEMATICS AT KCSE LEVEL IN SELECTED MIXED SECONDARY SCHOOLS IN NJIRU SUBCOUNTY; NAIROBI (Doctoral dissertation, University of Nairobi).

Ker, H. W. (2013). Trend Analysis on Mathematics Achievements: A Comparative Study Using TIMSS Data. Universal Journal of Educational Research, 1(3), 200-203.

Azizah, F., & Hartono, H. (2018). Pemetaan Kemampuan Pemecahan Masalah dan Kecemasan Matematika. AKSIOMA: Jurnal Program Studi Pendidikan Matematika, 7(3), 334-344.

Nicolaidou, M., & Philippou, G. (2003). Attitudes towards mathematics, self-efficacy and achievement in problem solving. European Research in Mathematics Education III. Pisa: University of Pisa, 1-11.

Gomez-Chacon, I. M. (2000). Affective influences in the knowledge of mathematics. Educational Studies in Mathematics, 43(2), 149-168.

Mensah, J. K., Okyere, M., & Kuranchie, A. (2013). Student attitude towards mathematics and achievement: Does the teacher attitude matter. Journal of Education and Practice, 4(3), 132-139.

Zan, R., & Di Martino, P. (2014). Students’ attitude in mathematics education. Encyclopedia of mathematics education, 572-577.

Manoah, S. A., Indoshi, F. C., & Othuon, L. O. (2011). Influence of attitude on achievement of students in mathematics curriculum. Educational research, 2(3), 965-981.

Azizah, F., & Hartono, H. (2018). Pemetaan Kemampuan Pemecahan Masalah dan Kecemasan Matematika. AKSIOMA: Jurnal Program Studi Pendidikan Matematika, 7(3), 334-344.

Mohd, N., Mahmood, T. F. P. T., & Ismail, M. N. (2011). Factors that influence students in mathematics achievement. International Journal of Academic Research, 3(3), 49-54.

Visser, M., Juan, A., & Feza, N. (2015). Home and school resources as predictors of mathematics achievement in South Africa. South African Journal of Education, 35(1).

Mohamed, L., & Waheed, H. (2011). Secondary students’ attitude towards mathematics in a selected school of Maldives. International Journal of humanities and social science, 1(15), 277-281.

Ignacio, N. G., Nieto, L. J. B., & Barona, E. G. (2006). The affective domain in mathematics learning. International Electronic Journal of Mathematics Education, 1(1), 16-32.

Tella, A. (2007). The impact of motivation on student’s academic achievement and learning outcomes in mathematics among secondary school students in Nigeria. Eurasia Journal of Mathematics, Science & Technology Education, 3(2), 149-156.

Mohamed, L., & Waheed, H. (2011). Secondary students’ attitude towards mathematics in a selected school of Maldives. International Journal of humanities and social science, 1(15), 277-281.

Manoah, S. A., Indoshi, F. C., & Othuon, L. O. (2011). Influence of attitude on achievement of students in mathematics curriculum. Educational research, 2(3), 965-981.

Zan, R., & Di Martino, P. (2014). Students’ attitude in mathematics education. Encyclopedia of mathematics education, 572-577.

Mensah, J. K., Okyere, M., & Kuranchie, A. (2013). Student attitude towards mathematics and achievement: Does the teacher attitude matter. Journal of Education and Practice, 4(3), 132-139.

Nicolaidou, M., & Philippou, G. (2003). Attitudes towards mathematics, self-efficacy and achievement in problem solving. European Research in Mathematics Education III. Pisa: University of Pisa, 1-11.

Katusiime, B. (2018). Employee motivation, employee commitment and individual job achievement among AAR healthcare workers (Doctoral dissertation, Makerere University).

Close, S. (2013). Mathematics items: Context and curriculum. National schools, international contexts: Beyond the PIRLS and TIMSS results, 153-175.

Gidena, A., & Gebeyehu, D. (2017). The effectiveness of advance organiser model on students’ academic achievement in learning work and energy. International Journal of Science Education, 39(16), 2226-2242.

Bundy, D., Burbano, C., Grosh, M. E., Gelli, A., Juke, M., & Lesley, D. (2009). Rethinking school feeding: social safety nets, child development, and the education sector. The World Bank.

Yohannes, A. (2017). The effect of School Feeding Program on the school achievement of primary public school children in Arada Sub City, Addis Ababa (Doctoral dissertation, Addis Ababa University).

Berry, E., Mac An Bhaird, C., & O’Shea, A. (2015). Investigating relationships between the usage of Mathematics Learning Support and achievement of at-risk students. Teaching Mathematics and its Applications: An International Journal of the IMA, 34(4), 194-204.

Hasz, L. A., & Lamport, M. A. (2012). Breakfast and adolescent academic achievement: An analytical review of recent research. European Journal of Business and Social Sciences, 1(3), 61-79.

Ali, C. A., & Zuure, D. N. THE DIETARY RIGHT OF CHILDREN AND ITS EFFECT ON PUPILS’ACHIEVEMENT IN MATHEMATICS IN RURAL GHANA; THE VOICES OF STAKEHOLDERS IN NAAGA TRADITIONAL AREA.

Cupani, M., de Minzi, M. C. R., Pérez, E. R., & Pautassi, R. M. (2010). An assessment of a social–cognitive model of academic achievement in mathematics in Argentinean middle school students. Learning and Individual Differences, 20(6), 659-663.

Qiu, Z., & Chung, C. (2017). Effects of Food Assistance Programs, Demographic Characteristics, and Living Environments on Children’s Food Insecurity. Applied Economics and Finance, 4(4), 145-159.

Kisker, E. E., Lipka, J., Adams, B. L., Rickard, A., Andrew-Ihrke, D., Yanez, E. E., & Millard, A. (2012). The potential of a culturally based supplemental mathematics curriculum to improve the mathematics achievement of Alaska Native and other students. Journal for Research in Mathematics Education, 43(1), 75-113.