Multiple Determinants Of Academic Achievement Education Essay

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Abstract

In Ethiopian, multiple factors affecting academic achievement of preparatory school atudents have not yet been systematically investigated. This situation calls for an empirical study which will examine the relationship between students' academic achievement and multiple factors (student, family and school related factors). Therefore, this study will focus on looking for answers for questions: what are the roles of multiple determinant factors in influencing the level of preparatory students' academic achievement in the Northern Gondar Administrative Zone? In addressing this question the researchers, on the basis of a postpositivist knowledge base, will design a sample survey that will consist of 377 students selected randomly from 4 (20 percent) sample schools out or the 19 preparatory schools in the zone. The dependent variable of the research is the educational achievement which is a continuous variable whilst the independent variables are those students, family and school level variables. The measures of both the independent and dependent variables will be gathered through the application of a self-administered structured questionnaire developed by the researchers. A multiple regression model will be used to analyze the data with the help of statistical software called Predictive Analysis Software (PASW) version 18.0.

Key words: academic achievement, multiple determinants, multiple regression

Background

Academic achievement is a well researched issue in different parts of the world. Different researchers have addressed different aspects of the issue at different time and place. Some focused on school based factors while others emphasized family level determinants. Still another major group of scholars has given immense attention to individual as well as background factors that determine the level of academic achievement. Social and behavioral, ecological factors and health factors as well as factors related to intelligence and personality were also addressed as determinant factors for the level of academic achievement considering other socioeconomic and environmental settings.

Those researchers who have addressed the school level factors of academic achievement have focused on different issues. For instance, Milesi and Gomoran (2006) addressed the effects of class size (Borland, Howsen & Trawick, 2005; Opdenakker & Damme, 2000) and instruction (Alkharusi, 2008) while Yan and Lin (2005) concentrated on class size and the length of days as factors determining education achievement at different levels of schools (Opdenakker, Damme, De Frain, Landoghem & Onghena, 2002). Others reported the role of factors related with teachers in determining students academic achievement (for example, Chong, Klassen, Huan, Wong & Kates, 2000; Park, 2005; Gill & Reynolds, 1999; Jacobs and Harvey, 2010; Opdenakker & Damme, 2000). Some others have tried to see the effects of school disorder on the academic achievement of students (for instance, Chen, 2007; Chen & Weikart, 2008, Shann, 2010). Still others have dealt with other school level factors for academic achievement (Papansfasiou, 2008; Nguyen, 2006; Lynn, Hampson & Magee, 1983; Zhang; 2006; Jimenez-Castellanos, 2010; Scott, 2009).

The relationship between family level factors and student's academic achievement have addressed by a significant number of scholars worldwide. Some of them have studied the effects of parents' expectations of academic achievement on their children's academic success (Gill & Reynolds, 1999; Jacobs & Harvey, 2006; Phillipson; 2009). Similarly, family support to and involvement in their children academic effort were also studies as factors that determine academic achievement of children (Jones & White, 2000; Chen, 2005; Moon & Lee, 2009; Kristjansson & Sigfusdottir, 2009; Chen & Ho, 2012). Family structure and other family backgrounds, as factors for academic achievement, were also the target for educational researchers, for example, Jeynes (2000) addressed family structure, Jones & White (2000) family composition, and Moon and Lee (2009) family structure with other variables. Some of the remaining researchers have dealt with the other family level socioeconomic and demographic factors for the academic achievement of students at different levels of schools (Lee & Kushner, 2008; Chowdhury & Pati, 1997; Al-mehklafi, Mohdy, Sallan, Ariffin, Al-mekllafi, Amran, et. al., 2011; Ogunkola & Olatoye, 2010).

Another group of scholars have been interested in addressing some of social and behavioral factors that have some contribution in determining students' academic achievement. In this regard, Becker and Luther (2004) have addressed those social-emotional variables relating to the issue under discussion whereas DiPrete and Jonnings (2012) concentrated on the influence of social and behavioral skills on students' academic achievement. Social class inequality was also studied as the factor for educational success (Socker, Schoon & Bartley, 2002) whereas the importance of community services and social support in determining academic achievement was studied by Powell and Arriola (2003) in relation to other variables. Social inclusion as a factor for academic achievement was also an agenda for some educational researchers (for example, Farrell, Dyson, Polat, Hutscheson & Gallannaugh, 2007) while Jeynes (1999) has dealt with analyzing the effect of residential mobility on the academic success of students with a special focus on children from custodial parents.

Still other handful of researchers have attempted to examine the relationship between several backgrounds of students and their academic achievement at different levels of schools. To mention some of them, Chen and Weikkart (2008) and Hason, Adam, Mustopha and Midi (2010) have shown us the effects of students' background in determining their educational success along with other selected variables (Lynn, Hampson & Magee, 1983; Casanova, Garcia-Linares, de la Torro & Caprio, 2005). Similarly, Nguyen (2006) examined the relationship between social classes of students and their academic achievement whereas Jakinova (2010) studied cultural milieu, lifestyle and customs and their relationship with students' success or failure in their education.

Individual differences have also been the focus of educational scholars in investigating students' academic achievement worldwide. Students' self-beliefs were seen as main and mediating factor in determining educational success (Valentine, DeBois & Cooper, 2004; Valentine, Cooper & Bettencourt, 2002). The association and relative influence of cognitive/motivational and demographic factors of academic success, on the other hand, were studied (Cassidy, 2011). In the meantime, Lowis and Castley (2008) reported their finding on the relationship between academic achievement and their early and actual expectations. Likewise, academic motivation and students' methods of handling, which can be seen as individual level factors, were also investigated (Powell & Arriola, 2003).

Although it is possible to categorize some previous researches into some of the categories we have so far discussed earlier, I have tried to identify some researches to be classified into those researches which focused on ecological factors for students' academic achievement. In this regard, Moon and Ando (2009) studied the extent to which students' closeness to family, peers, and school in relation with academic achievement. Likewise, family and school level determinants of academic achievement along with demographic factors were investigated as some important ecological factors (Dincer & Uysal, 2010) whereas Stolz, Barber, Olsen, Erickson, Bradford, Maughan, et. al (2004) have investigated the socialization conditions of connection, regulation and respect of psychosocial autonomy within the family and school context as factors determining academic achievement. Furthermore, multilevel examination of students' school and district level effects on academic achievement (Caldes & Bankston lll, 1999) while others tried to evaluate the significance of rural urban differences in determining students' academic achievement (Young, 1998). Single-parent families were also seen as ecological variables that related with the academic success or failure of students (Lee & Kushner, 2008).

In addition, among those researchers who have studied the determinant factors of students' academic achievement, there are some who attempted to deal with the relationship between health conditions and educational achievement. Here, malnutrition, as a health factor, was seen as factors having a significant relationship with students' academic achievement (Themane, Mondyeki, Nthangeni, Kemper & Twisk, 2003; Al-Mekhlaf, Mohdy, Sallan, Ariffin, Al-Makhlaf, Amran, et. al., 2011) while others attempted to examine the effect of disability, as a health related factor, on academic achievement (Roth, Punch & Backman, 2001; McConnell, 1981). Others have addressed the relation of substance use, both as main and mediating factor, with academic achievement although this does not necessarily directly related with health factors, (for instance, Kalyu, Andualem & Yeshigeta, 2009; Moon & Ando, 2009).

As far as determinants of academic achievement has been concerned, there still there are researchers who have tried to examine the relationship between academic achievement and intelligence and personality (for instance, Deary, Strand, Smith & Fernandes, 2007; Lynn, Hompson & Magee, 1983; Diseth, 2002). However, currently the relationship between intelligence and academic achievement gets less attention among scholars from different disciplines.

Finally, the remaining few studies tried to relate academic achievement with different other factors than the aforementioned ones. To list some of them, Mpofu (2010) studied the effect of students' social acceptance on their academic achievement whilst Ogunkola and Olatoye (2010) have dealt with the joint and relative effects of inherent characteristics relating with family level factors on academic achievement. Besides, self-assessment skills and student achievement were related (McDoland, 2009) whereas Chambers and Schreiber (2004) have tried to investigate the relation of academic achievement of girls with extra-curricular activities.

To sum up, even though the issue of academic achievement has been investigated immensely, the determinant factors and the issue itself are dynamic that vary across time, place, socioeconomic and cultural settings. Factors which are important today may not be important sometimes in the future. Similarly, those determinant factors of academic achievement in one part of the world may not be important in another area since the immediate social, economic, cultural and ecological environments can affect them (Apfelthaler, Hansen, Keuchel, Mueller, Neubauer, Ong, et.al., 2007). Furthermore, any social phenomenon, like the problem of poor academic achievement, always cannot be affected by one or some variables rather it is the product of many factors which directly or indirectly affect it (Tarling, 2009). These multiple determinant factors of the issue under discussion will also interact one another. Hence, the researchers believe that identifying the effects of multiple factors for academic achievement is the best approach to understand the issue fully in this integrated and globalized world which is missed by almost all of the literatures we have reviewed earlier.

Statement of the problem

Education, as one of the basic social institutions of a society, has several purposes. It gives people more and better life and career opportunities; develops peoples knowledge and understanding of themselves and the world; gives youngsters a broader perspective on life and the world; and helps make the nation more competitive and prosperous (Moore, 2000). Education should allow students to reach their fullest potential in the area of their cognitive, emotional and creative capacity (EFA, 2005). Whether these purposes of education have been functioning up to the expectations and standards or not, is mostly measured in terms of the level of students' academic achievement which can be defined, according to McDonald (2009), as a 'task-oriented behavior that allows the individual's performance to be evaluated according to some internally or externally imposed criterion that involves the individual in competing with others, or that otherwise involves some standards of excellence.' (P: 146). Taking the importance of academic achievement into account, the United Nations Children Fund (UNCF) has argued that academic achievement is mostly used as an indicator of quality of school as it is easily measurable with the application of some standardized tests while other outcomes may be more complex and less tangible (UNCF, 2000).

Similarly, the government of Ethiopia has given much emphasis to education in its Five Year Growth and Transformation Plan. In this document, the government has mentioned the second objective as 'expand and ensure the qualities of education and health services thereby achieving the millennium development goals in the social sectors' (FDRE, 2010) which is intended to be realized by increasing efforts of the government in human resource development through improving access and quality of education during the plan years. More specifically, the government showed its intention to expand quality secondary education that will serve as a basis and bridge to produce a middle and higher level workforce in line with the demand of the national labor market, and intake capacity of higher education institutions. Regardless of the zeal the nation has in bringing about a positive change in the education sector, there are only few insufficient empirical investigations in the area, particularly on the academic achievement of secondary education which can usually be helpful to the government's policy formulation, implementation and evaluation.

As it has been tried to show in the background section of this proposal, the issue of academic achievement is a well-researched social phenomenon worldwide. Many researchers from different parts of the world have studied academic achievement at all levels of the education institution concentrating on factors affecting its extent. However, the vast majority of these studies did not try to see the cumulative effects of multiple factors on students' academic achievement other than examining the relationship between some selected factors and academic achievement. This situation is ubiquitous in Ethiopia in general and in the study area in particular. So far, as my humble effort is concerned, I have failed to get previous efforts which have dealt simultaneously with investigating the effects of multiple factors related to students, family and school on the academic achievement of high school students in the country. Therefore, the main aim of this research is to divulge the multiple determinant factors (factors related with student, family and school) of high school students' academic achievement in northern Gondar Zone Administration.

Research objectives

12.1. General objective

The main intention of this research is to see the significance of multiple factors that determine academic achievement of students among preparatory schools of the Northern Gondar Administrative zone, including Gondar town.

12.2. Specific objectives

To examine the relationship between student-related characteristics and their academic achievement;

To make clear the effects of family-related factors on students' academic achievement;

To examine the extent to which school-related variables and students' academic achievement are related, and

To examine the cumulative effects of the multiple factors (student, family, and school related factors) on students' academic achievement.

Methodology of the Study

13.1. Paradigm

Researchers have claimed the post-positivist knowledge base which depends of a philosophy called critical realism which believes that there is a reality independent on the person's thinking about it that can science study (Corbetta, 2003). In other words, Corbetta stated that critical realism believes that reality is only imperfectly knowledgeable due to the fact that human knowledge is inevitably imperfect and the very nature of its laws is probabilistic. Generally, postpositivism relies mostly on such assumptions as (1) knowledge is conjectural or anti-foundational - absolute truth can never be found, but truth is hypothetical (Corbetta, 2003); (2) research is the process of making claims and then refining or abandoning some of the themes for other claims more warranted; (3) data, evidence, and rational considerations shape knowledge (Creswell, 2007); (4) research seeks to develop relative true statement ones that can serve to explain the situation that of concern the causal relationships of the interest (Corbetta, 2003); and (5) being objective is an essential aspect of competent inquiry; and for this reason, researchers must examine methods and conclusions for bias (Creswell, 2003; Corbetta, 2003).

These assumptions are relevant to the examination of the cause-and-effect relationships between academic achievement and the multiple factors (that is, factors related to students, family and school) identified. As a result, we believe that we will remain being objective during the whole process of the research in our searching for a relative truth about the relationships between multiple factors and students' academic achievement depending on the data that will be gathered from the participants.

13.2. Research design

In Ethiopian, multiple factors affecting students' academic achievement at preparatory schools have not yet been systematically investigated. This situation calls for an empirical study which will attempt to evaluate the relationship between students' academic achievement and multiple factors (student, family and school related factors). In addressing this problem, the researchers have intended to search answers for the questions: what are the contributions of students, family and school related factors in determining students' academic achievement at the preparatory school of the Northern Gondar Administrative Zone? In searching for the answer for this research question, we claim a post-positivist knowledge base that helped us formulate a quantitative research design based upon a unilateral survey design that aims to examine the causal relationship between the independent variables, namely, student, family and school level factors, and the dependent variable - academic achievement - which is the main focus of this research.

Subsequently, the nature of the research question and the knowledge base we have depended upon demand for the application of a sample survey research design. The survey will be built upon some 377 sample students which will be interviewed with a structured, self-administered questionnaire designed to gather the necessary data regarding the determinant factors of preparatory students' academic achievement. A multiple regression model with the help of the Predictive Analysis Software (PASW) will help to analyze the collected data.

13.3. Population and sampling design

The target population of the study is grade 11 students in 19 preparatory schools of Northern Gondar Administrative Zone of Amhara National Regional State among which 4 (20 percent) are included in the sample being randomly selected. The schools included in the sample are Chilga, Tikldingay, Worgera, and Fasiledes. According to the Educational Office of the Zone, in 2004 E. C., there were a total of 6234 (N) grade 11 students (3121 males and 3113 females) distributed across 19 preparatory schools. Therefore, the sample size (n) for the study will be determined using the formula discussed in the following paragraph.

A statistical formula will be used to determine the size of the sample (n) when the total population (N) is known (that is, 6234) (Kothari., 2004), where z is equal to 1.96 as we have assumed to be 95 percent confident; e is the sampling error which is equal to 0.05; p is the chance of being successful in academic achievement which is supposed to be 50 percent and q is the chance of not to be successful which equals to or 50 percent, too, where N is the total number of grade 11 students in the Zone. Hence, based on the above formula the sample size of the research will be 377 (203 females and 174 males) grade 11 students which is consisted of 293 students from the natural sciences and 84 from social sciences.

Table 1: sample schools and students

Schools in the sample

Total number of students

Number of students in the sample

Male

Female

Total

Male

Female

Total

NS

SS

T

NS

SS

T

NS

SS

T

NS

SS

T

NS

SS

Chilga

275

79

354

344

174

518

872

38

11

49

48

24

72

86

35

Tikildingay

148

24

172

140

71

211

383

20

3

23

19

10

29

39

13

Wogera

128

33

161

145

79

224

385

18

4

22

20

11

31

38

15

Fasiledes

524

65

589

434

92

526

1115

71

9

80

59

12

71

130

21

Total

1075

201

1276

1063

416

1479

2755

147

27

174

146

57

203

293

84

Note: NS = natural sciences; SS = social sciences; and T = total

Here, it should be noticed that we believe that the chance of occurrence (p) and nonoccurrence (q) are equal depending on the assumption that when several variables are involved in a research, like ours. The variability of the proportion is measured by and this index is always the highest when p and q are equal; and this is happened when p is equal to 50 percent (Corbetta, 2003) because we have assumed that the population is normally distributed. Thus, it was on the basis of this assumption that the final sample size is calculated for the least favorable case, that is to say, when p is equal to q: both are equal to 50 percent. The sample size is the highest when p and q are equal (Corbetta, 2003). This condition has something to do with the proportion of cases to variables in the survey that will be discussed at the beginning of the analysis section of the research report.

A simple random sampling technique (lottery method) has been used in the selection of the four schools among the nineteen total preparatory schools in the zone including the three schools from Gondar city administration while a multistage stratified random sampling will be used to select sample students. In the first stage, the survey population will be stratified based on the field of education as natural sciences and social sciences. Then, in the next stage, students from each of the disciplines will be stratified into two based on the sex of students. Finally, a simple random method of sampling will be used in selecting the actual sample size in line with the number of students assigned to each sample schools in table 1 above.

13.5. The model

The research will fit a multiple regression model in analyzing the data gathered and entered the statistical software (PASW). The rationale behind the application of multiple regression model is that it enables the researchers to clearly evaluate the effects of groups of independent variables (multiple variables categorized into student, family and school related factors) which are both continuous and categorical ones on a continuous response variable (academic achievement measured in average score of the students). The multiple regression model is based on the principles of the general linear regression equation which is constructed upon (1) the explanatory variables, (2) response variable, (3) error term and (4) regression coefficients, that is, where, y is the dependent variable, are the parameters or the coefficients which indicate the magnitude by which y changes as changes, are the explanatory variables related to student, family and school, and is the error term or residuals which represents those values which cannot not be explained by group of explanatory variables in the model.

This model is built upon two important assumptions. The first assumption is the assumption of linearity which assumes a linear relationship between the predictor variables and students' academic achievement. This assumption will be proven by examining scatterplots of the model. The second assumption, on the other hand, is the assumption of residuals which deals with the idea that residuals are distributed normally in the model. Residuals are the amount by which the fitted line of the model deviates from the data points. This assumption of the model will be tested using the F-test that is fairly robust with respect to minor violation of the assumption.

13.6. Variables

The target variable of the study is students' academic achievement (a continuous variable) which is to be measured in terms of annual average score of the students achieved in all subjects of the academic year. This variable is supposed to be influenced by many predictive variables which are grouped into three: student related variables, family related variables, and school related variables. Student related explanatory variables consist of student's gender, age, place of origin, disability status, and health status whereas family related variables include all the variables related with parents' socioeconomic and demographic statuses, namely, home possessions (books, computers, and cell phone), parents' annual financial income, parents' highest occupation status, age of parents, parents' highest education status, parents' marital status, family type, and parent type.

Table 2: variable in the model and their measurements

Variables

Measurements

Dependent variable

Academic achievement

Annual average score of a student

Independent Variables

Student-related variables

Gender

Age

Place of origin

Study time

Disability status

Health status

Prior achievement

Family-related variables

Parents' socio-economic &demographic statuses

Home possessions;

Books

Computer

Cell phone

Parents' annual income

Parents' highest occupation status

Father's highest occupation status

Mother's highest occupation status

Parents' age

Father's age

Mother's age

Parents' highest education status

Father's highest education status

Mother's highest education status

Parents' marital status

Family structure

Parent type

Family size

Parental expectations for A. achievement

Parental involvement

School-related variables

Class size

Student-teacher ratio

Percentage of girls

Gender of teachers

Male

Female

Library accessibility

Learning-teaching type

Elementary school type

Access to internet services

Field of study

Length of class

Attendance

School climate

Teachers commitment to students

Cooperation among students

Teachers' support to students

Teachers' attitude

Antisocial behaviors of students

Lesser infractions

Major transgressions

Prosocial behaviours

Help others directly

Help with tasks

Friendship/harmony

Show respect

Gender of the student (Male = 1; female = 0)

Age of the student in year

Origin of the student (rural = 0; urban = 1)

Amount of time spent for study in hour

Student's disability status (disabled = 1; nondisabled = 0)

Student's health problem experience in a year (yes=1; no=0)

Grade 10 ESLCE average score of a student

Availability of books at home (yes = 1; no = 0)

Availability of computer at home (yes = 1; no = 0)

Availability of cell phone at home (yes = 1; no = 0)

Annual income of the family in Birr.

(employed = 1; unemployed = 0)

(employed = 1; unemployed = 0)

Age of the father in year

Age of the mother in year

(illiterate = 0; elementary = 1; high school = 2; above high school)

(illiterate = 0; elementary = 1; high school = 2; above high school)

(married = 1; divorced = 0, widowed = 2)

(two-parent family=1; single-parent family=0)

(intact = 1; one biological = 2; others = 0)

Number of members of a family

(high = 1, moderate = 2, low = 0)

(strong = 1; moderate =2; weak = 0)

(large = 1; medium = 2; small = 0)

The ratio of student to teachers is a student's class

Number of girls in a class of a student

Number of male teachers who taught the student in the year

Number of female teachers who taught the student in the year

Number of hour a library is opened for the student

(active learning = 1; conventional = 0)

(private = 0; public = 1; community= 2)

Amount of time a student accessed internet services per week

The field of study a student currently attending (SS = 0; NS = 1)

(full-day = 1; part-day = 0)

Percentage of days a student attended annually

(high = 1; moderate = 2; low = 0)

(high = 1; moderate = 2; low = 0)

(high = 1; moderate = 2; low = 0)

(positive = 1; negative = 0)

(high = 1; moderate = 2; low = 0)

(high = 1; moderate = 2; low = 0)

(high = 1; moderate = 2; low = 0)

(high = 1; moderate = 2; low = 0)

(high = 1; moderate = 2; low = 0)

(high = 1; moderate = 2; low = 0)

Note: SS = social science; and NS = natural sciences

School related explanatory variables, on the other hand, include the size of a particular class, student teacher ratio in a given classroom, percentages of girls in a classroom, gender of teachers, grade ten ESLC grade, accessibility of library, type of learning and reaching process, elementary school type, internet access, and field of study.

13.7. Data Collection Instruments and Procedures

A structured self administrative questionnaire consisted of 46 close-ended questions: 1 for dependent variable, 7 for student related variables, 16 for family related variables, and the remaining 22 for those schools related will be designed by the researchers. For the first time, the questionnaire will be written in English, and then translated into Amharic language using two expert language translators who speak both Amharic and English languages fluently. The translation process will go under the procedure called forward-and-backward translation in order to produce a refined final Amharic version where the possible errors will be reduced to their minimum levels.

Thus, the Amharic version of the questionnaire will directly be used for the actual data collection process. The questionnaire will be tested on 15 individuals before actual data collection will have been started so as to establish content validity by improving the quality of the questions, format of the questionnaire, scales of measurement, and the language used. It is after this process will have been completed that the questionnaire will be used to collect the data on the field.

Data from participants will be gathered through questionnaires distributed by data collectors which are selected among sample school teachers. Selecting data collectors from the study area is assumed to increase the respondents' trust on the research and researchers. During data collection, the principal investigator will work both as researcher and supervisor. Data from sample schools will be collected at the same time. The data will be gathered from the respondents after respondents will have read the Informed Consent and after they will have been agreed upon the statements of the form either by signing on it or simply by finishing filling of the questionnaire.

13.8. Data presentation, analysis and discussion

The gathered data will be coded and entered the Predictive Analysis Software (PASW) version 18.0 by the co-investigator for the analysis process to proceed with the help of the statistical software. Besides, the data analysis process will be held depending on the outcomes of the multiple regression model as the outcome variable is a continuous variable. Some of the tools for data presentation include tables, figures, and graphs. The findings of the research that will be gained from the multiple regression will be discussed in comparison with the findings of earlier research works of other investigators all over the world that will have explicitly been presented in the literature review section of the research.

14. Benefits and Beneficiaries of the Study

This research will contribute to the knowledge base of the scientific community about the determining factor for students' academic achievement in Ethiopia. It will help practitioners and decision makers in the area of high school educational achievement since it will reveal the point at which intervention should be made. The main beneficiaries of this research are student of high schools as well as schools in the study area. Different educational bureaus and offices which are working at different levels of intervention will be other beneficiaries of the outcomes of this research. Researchers will also benefit a lot from the findings of this research.

15. Ethical issues of the study

From the beginning of the study, we have taken some situations into consideration which are assumed to have some ethical issues for different involving bodies with a special attention to participants of the study at different stages. In the problem statement stage, we assumed that participants may suspect that the research might not bring any benefits to them albeit the problem stated in the study is not as such a useless one. It has also thought that, during the data gathering stage, too, participants would be disappointed with completing a long, detailed, and structured questionnaire since it might cause them feel somewhat latently compellingly committed to finish filling all the questions in the questionnaire. In the analysis process, we also have thought that there may be misuse of data unknowingly. Besides, we have also thought about the possibility of the use of languages that can disappoint the survey population during reporting the findings.

Taking all these ethical issues into account, we planned to take every possible measure so as to mitigate them. First, in building trust that can avoid suspicion among both participants and the survey population, we will conduct a pilot research during which we may have a chance to clearly show out the interest of the study. Besides, we will hire data collectors among the survey population themselves (teachers of sample schools) so that their sense of participation and ownership in the research will be boosted which in turn can reduce the possible suspicion about the aim of the research. We will also work with people who are in authority in the research areas in order to create a smooth relationship with them before directly engaging both in the pilot and actual data collection. This will raise some sort of trust between the researchers and the respondents which will enable us to get valid evidence about the measurements of the study.

An Informed Consent Form, to be signed by participants will be prepared as a mechanism for, to some extent, reducing some of the ethical issues that may put the participants at risk during our research since it will clarify the rights of the respondents to participate voluntarily and to withdraw at any time whenever they want to do so. This will help participants to be conscious of not to be forcefully committed to the research. The form will contains (1) the purpose of the research that will make participants aware of the nature of the study and its likely impacts on them, (2) the procedures of the study that will assist participants to reasonably evaluate what will be produced by the research, (3) the right to ask question, to obtain a copy of result, and to have their privacy respected and benefits of the study that would accrue to the individual, and (4) the confirmation signature of both the investigator and participants indicating a non-coercive involvement in the study.

Regarding those possibly assumed ethical problems that may appear during data collection and analysis procedures, we will exert efforts like clearly getting the permission of individuals in authority in the area; distributing the questionnaire by people whom participants know; strictly following the ethical codes of the social work profession; avoiding personal identifications of respondents; and respecting the academic ethical and moral obligations of social science researchers.

16. Description of Facilities at Sites of Performance

Northern Gondar administration educational official and school principals are interested in the study, and have taken the benefits of the research into account. The concerned bodies have promised to work in collaboration with the investigators and to assist them in terms of their security. They will also help the research by motivating participants of the study to genuinely involve.

17. Component Steps of the Project

Phase

Duration

Description

1

September

to

January

Review of literature

Instrument development

Questionnaires

Data Gathering

Pilot testing

Sample selection

Data collection

2

January

to

June

Data Presentation, Analysis and interpretation

Tabulation and coding

Data entry and statistical analysis

Interpretation

Writing the report

Edition and printing

Presentation/dissemination of findings

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