Download - The Effects of Divorce on the Academic Achievement of High School Seniors

The Effects of Divorceon the Academic Achievement

of High School Seniors

Barry D. Ham

ABSTRACT. The divorce rate in the United States has climbed at an as-tounding rate during the past 80 years. Consequences of this change infamily structure have impacted millions of children in a variety of ways.This study assessed the impact of divorce in relation to students’ aca-demic achievement. Two hypotheses were introduced reflecting expec-tations suggested by previous studies. High school seniors from a middleclass school in a Rocky Mountain State served as the population for thisstudy.

The results suggest that family structure impacts both the grade pointaverage and attendance of high school students. Adolescents from intactfamilies outperform those students from other family structures. One ofthe most surprising findings was that these results were most pronouncedfor females. Females were more negatively impacted by family struc-tures due to divorce than were males. [Article copies available for a feefrom The Haworth Document Delivery Service: 1-800-HAWORTH. E-mail ad-dress: <[email protected]> Website: <http://www.HaworthPress.com>© 2003 by The Haworth Press, Inc. All rights reserved.]

Barry D. Ham, PhD, is a Licensed Marriage and Family Therapist in private practice inColorado Springs, CO. He also works as a counselor with the Academy School District,and is an adjunct faculty member at Colorado Christian University.

Address correspondence to: Barry D. Ham, P.O. Box 63241, Colorado Springs, CO80962.

Journal of Divorce & Remarriage, Vol. 38(3/4) 2003http://www.haworthpress.com/store/product.asp?sku=J087

2003 by The Haworth Press, Inc. All rights reserved.10.1300J087v38n03_09 167

KEYWORDS. Divorce, intact-family, academic-achievement, family-structure, attendance, gender, high school students

INTRODUCTION/BACKGROUND

The current status of divorce is relatively new. It was not that longago that divorce was rare and unacceptable in society. In the 1920s, ap-proximately 100 women per thousand were married each year. The di-vorce rate at that time was running about 10 per thousand. However, thepicture changed dramatically over the next 70 years. By 1990, the firstmarriage rate of women had actually dropped to about 80 per thousandeach year, while the divorce rate had increased to 40 per thousand(Shiono & Quinn, 1994). In other words, the number of women gettingmarried for the first time had decreased by 20%; yet, the divorce ratehad increased by 300%.

Looking back even further, approximately 5% of marriages in theUnited States ended in divorce just after the Civil War. This increasedto 10% by the 1920s (as shown above), to 36% of 1964, and to 50% by1990 (Furstenberg, 1994). Furstenberg refers to this extraordinary in-crease in the divorce rate as being a result of the “divorce revolution.”From 1865 to 1990, a span of only 125 years, the divorce rate in thiscountry increased by 900%.

Shiono and Quinn (1994) have called attention to the dramatic way inwhich these numbers have affected children. In 1988, 15% of all chil-dren lived with a divorced or separated parent with an additional 11%living with a stepparent. This 26% translates into 17 million childrenliving in the resulting structures following divorce. More than one mil-lion children per year have experienced a divorcing family since themid-1970s.

During the early 1960’s, nearly 90% of children lived their first 18years in homes with two biological, married parents (Hetherington &Stanley-Hagan, 1999). However, during the past 40 years, that percent-age has diminished at an alarming rate. By 1995, it has been reported,18.9 million children under the age of 18 lived with one parent (“Sin-gle-parent kids”, 1997). This reflects the fact that 45% of all first mar-riages in the United States result in divorce within 14 years (Lamb,Sternberg, & Thompson, 1997).

This seemingly unabated rise in the number of children from di-vorced households has generated concern among educators, mentalhealth professionals, researchers, and society as a whole. With schools

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and teachers being faulted with lower test scores and grades by students,one wonders what role changes in family structure may have played inthese academic measures. If the rising divorce rate does have an impactupon student academic achievement, then parents and educators bothmay need to reexamine their roles in meeting the needs of these stu-dents.

Divorce affects children and adolescents in a variety of ways. Onearea that is of particular interest to this study is that of academicachievement. Numerous studies have observed that children from di-vorced families are impacted negatively when it comes to school per-formance. Frum (1996) pointed this out when he stated that childrenwho are raised with only one of their biological parents are twice aslikely to drop out of school than are children from two-parent families.He also noted that these children demonstrate poorer school attendanceand are less likely to attend college.

McManus (1993) emphatically states:

Compared to an American child, a Japanese child is four timesmore likely to be reared by both parents, according to the U.S.Census Bureau. The stability of Japanese families and the chaos ofAmerican families is a major reason that Japanese students are somuch more successful in school than are American children-and amajor reason for the success of the Japanese economy. (pg. 27-28)

Jeynes (1997) concludes in his research that there is a parallel be-tween the divorce rate in the U.S. and what has been perceived as the de-cline of education. He clearly states:

There has been a great deal of public criticism of the public schoolsystem due largely to: (1)declining standardized test scores duringthe 1963-1980 period; (2) consistently poor performances on in-ternational comparison tests; and (3) soaring rates of juvenilecrime in the schools. The tendency has often been for the public toblame the schools for these problems. And certainly, the schoolsdeserve some portion of the blame. But the results of this studycontribute some credence to the notion that the decreasing per-centage of children coming from intact families exerts a down-ward pressure on the average academic achievement of Americanchildren. It is probably far more than coincidence that the U.S. di-vorce rate which had been in a slow decline during the 1948-1962period, rose sharply in 1963 and continued to rise sharply after that

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during almost exactly the same period as the standardized testscore decline. (pg. 226-227)

Gunning (1998) conducted a study of the academic accomplishmentsof middle school students’, surveying 131 eighth grade science stu-dents, and recording their science grades for the current and four previ-ous years. While she examined family structure, gender of student,gender of custodial parent, and length of time since the divorce in rela-tion to academic performance, the only variable that showed signifi-cance was family structure. She discovered that the students fromdivorced families received significantly lower science grades than stu-dents from intact families.

Jeynes (1997) found similar results in his work with data from theNational Education Longitudinal Study (NELS). Particular attention, inhis study, was given to the results of the student questionnaire, test re-sults, and school data. “The analyses, overall, showed that the further afamily structure was from the intact two-part family, the more nega-tive an impact that the family structure had on academic achieve-ment” (pg. 225).

Using the same NELS data, Pong and Ju (2000), reported that highschool dropout rates were significantly lower for students who residedwith both parents than for adolescents of single parents. Interestingly,they discovered that any disruption to the two-parent family increasedthe odds of dropping out. It didn’t matter whether the child was movingfrom an intact family to a mother-only family, a father-only family, astep-family, or a guardian family. The dropout rate was approximatelydouble for any student in a family type other than an intact, two-parentfamily.

Using data from the National Longitudinal Survey of Youth (NLSY),Wojtkiewicz (1993) took particular interest in the living arrangementsof these individuals from birth to the age of 19. What he discovered wassignificant. Any child who lived in a non-intact family, during any yearof that time, experienced a decreased chance of graduation.

Data from the NLSY was used in another research project carried outby Sandefur, McLanahan, and Wojtkiewicz (1992). The results of theirstudy also demonstrated that students from divorced homes are lesslikely to graduate than students from intact homes.

One final study will be mentioned in this section regarding schoolperformance. In discussing school performance, some researchers re-port achievement by examining the scores from standardized achieve-ment tests, while others report school grades. Smith (1995) stated that


the method used makes a difference. It was his contention that familystructure and parental involvement would have a greater effect uponschool grades than upon standardized achievement. Grades seemed tobe more influenced by effort, parental availability, and other social fac-tors than standardized scores. He analyzed data from 1,688 seventh andninth graders from 14 public schools in Columbia, South Carolina. Hisresearch results supported his hypothesis. He found that the grades ofchildren from divorced families were negatively impacted much morethan they were for children from stable intact families. However, thedifferences in standardized scores were much smaller. This is an impor-tant difference in accurately measuring the effect of divorce on educa-tional performance. It is for this reason that this writer’s own researchwill examine school grades as opposed to achievement test scores.

The purpose of this study is to investigate the relationship betweendivorce and the academic achievement of adolescents. This study willinclude an examination of the GPAs of high school seniors from intactand divorced families. The research will also include a review of the at-tendance of these same students. As the results of this study are ana-lyzed, differences will be examined in relation to student gender andethnicity. The age of the students at the time of divorce will also benoted in order to determine if this variable alters the degree of impactfrom the divorce.

This study will test two hypotheses: (1) that the grade point averagesof high school seniors will be found to be lower for students from di-vorced families than for students from intact families, and (2) that highschool seniors from intact families will have higher school attendancethan students from divorced families.

METHODS AND DATA SOURCES

Population

The subjects for this study were students drawn from the AcademySchool District located in Colorado Springs, Colorado. This school dis-trict is situated in the northern-most part of the city and is comprised ofpredominately middle-class and upper middle-class families. At thetime of this study, Academy School District consisted of approximately17,500 students. Of this number, nearly one-third were high school stu-dents, representing four schools.

Barry D. Ham 171

For the purposes of this research, it was determined to examine dataspecifically related to high school seniors. There were approximately1,150 seniors in this district. Attempting to randomly sample studentsfrom all four high schools would have been logistically unwieldy.Therefore, a cluster sampling technique was used instead. One of thefour high schools was selected; Rampart High School, and all of the se-niors from that school were enlisted for this study. This included poten-tially 318 seniors.

However, it should be pointed out that there were guidelines thateliminated some seniors from participation. Only first semester seniorswere allowed as a part of this study. In other words, fifth year seniors, orthose who should have graduated the previous year, were not included.The obvious reason for this was to aid in limiting the age range. Fifthyear seniors would be a year older than first semester seniors.

Secondly, seniors in the study needed to be taking at least three coreacademic classes during the first semester, but no more than five. Coreacademic classes are considered to be those in the English, math, sci-ence, social studies, or foreign language departments. Taking fewerthan three classes could lead to an easier academic schedule resulting ina higher GPA than might result from a regular academic load. Con-versely, taking a load of greater than five classes could increase aca-demic difficulty leading to a lower GPA. Restricting the academic loadlimited the impact that this could have upon results.

Finally, students who are classified as ESL (English as a Second Lan-guage), SPED (Special Education), and foreign exchange were not in-cluded. These populations have special needs and their academics aremore greatly affected by factors outside of those that would be mea-sured here.

Of the 318 seniors enrolled, 265 were eligible for the study basedupon the above criteria.

Instrument

The instrument that was used for gathering independent variable datawas a demographic questionnaire. This tool asked for specific factualinformation concerning the students’ current living situation.

The first three items of the Questionnaire asked for the student’s I.D.number, his or her gender, and ethnic origin. The I.D. number was usedinstead of the individual’s name to aid in protecting confidentiality.

Item number four inquired about the size of the participant’s family,particularly the number of children. The following item requested infor-


mation regarding each parent’s level of completed education. Thiscould range from less than high school to college completion. Theseitems were included in an attempt to control for other variables thatmight also impact academic achievement.

Family structure was the subject of question six. Students could indi-cate whether they lived in a family in which both of their natural parentswere married, their parents were divorced, either mother or father wasdeceased, or their parents were never married. This was very important,as the hypotheses of this study were based upon family structure.

The final item was for those students whose natural parents are di-vorced. It inquired as to the student’s age at the time of his or her par-ents’ divorce. This item would attempt to help determine how the issueof time factors into the mix for these students.

As this study is quasi-experimental, the tool that is used is not onethat manipulates its subjects, or even one that inquires about percep-tions. It simply gathers data that best describes current status.

Family Structure Variables

Family of origin variables included: intact family, divorced parents,father is deceased, mother is deceased, and parents never married.

Intact family refers to those students whose natural parents were stillmarried to each other. Using dummy variables, intact families werecoded as 0 and those not from intact families were coded as 1.

Children whose natural parents were divorced were coded as 0. Evenif their parents had since remarried, this coding was still used because itreferred to the family of origin. Those in a category other than divorcednatural parents were coded 1.

If a student’s biological father was deceased, it was coded as 0 and asa 1 for all others.

Those whose natural mother was deceased was coded as 0, while allothers were also coded as 1.

The final family of origin variable was for those whose parents nevermarried. This could refer to a variety of situations. It could be that theparents of the child were young during the pregnancy and have had nofurther contact. Perhaps contact has continued with the child, but theparents have not maintained any form of relationship. Another possibil-ity is that the parents lived together for a period of time and then wentseparate ways. The parents may have lived together, never married, andstill live together but never were officially married. This variable en-

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compasses all of these possibilities and was coded 0, while those not fit-ting into this category were coded as 1.

Other Independent Variables

Gender–was coded with the value of 0 for males and 1 for females.This variable allowed for the consideration of differences in scores be-tween females and males.

Ethnicity–was coded 0 for white, 1 for African-American, 2 for His-panic, 3 for Asian, 4 for Native American, and 5 for other. This variableallowed for the controlling of ethnicity as a factor in family structurescore differences.

Family Size–to control for the influence of family size, families inwhich the student was an only child were coded as 0, families with 2-3children were coded as 1, and families of 4 or more children were codedas 2.

Mother’s Level of Education–was coded as 0 if she completed lessthan high school, 1 if she only completed high school, 2 if she attendedsome college, and 3 if she completed college. This variable allowed forthe consideration of differences in scores based upon the mother’s edu-cation.

Father’s Level of Education–was coded as 0 if he completed lessthan high school, 1 if he only finished high school, 2 if he attended somecollege, and 3 if he completed college. This variable allowed the exami-nation of differences based upon the father’s level of education.

Age at Time of Divorce–for those whose parents are divorced, stu-dents are asked what their age was at the time of the divorce. This vari-able would be helpful in determining the influence of age at the time ofdivorce on academic outcomes.

Academic Achievement Dependent Variables

Grade Point Average–This was the average of the grades that werereported from the Student’s academic core classes for the first semesterof their senior year. Grades were reported and recorded in January2001. Numerical values assigned in this school district for high schoolclasses and for this study were on what is referred to as a 5.0 scale. Thisis a traditional 4.0 scale that builds in weighted grades for more difficultclasses. All of the academic classes at Rampart High School were con-sidered to be college preparatory classes. However, advanced levelclasses were also offered. These advanced level classes fell into one of


three categories: AP (Advanced Placement), Honors (also known as tal-ented and gifted), and IB (International Baccalaureate). Therefore, de-pending on the class, the numerical value of the grade could vary. Thevalues for the regular college preparatory academic classes were as fol-lows: “A” = 4, “B” = 3, “C” = 2, “D” = 1, and “F” = 0. The numericalvalue for the grades received in the AP, Honors, and IB classes were:“A” = 5, “B” = 4, “C” = 3, “D” = 2, and “F” = 0.

Attendance–Absences were calculated based upon the number of sin-gle-period unexcused absences recorded by the attendance office dur-ing the first semester of school. Frequently when outside influencesimpact a student’s attendance, it can show up as absences only in themorning classes or only in the afternoon classes. Therefore, measuringsingle-period attendance was more accurate than simply recordingfull-day absences.

Data Gathering Procedures

In the fall semester of the 2000-2001 school year, seniors were giventhe parent information letter along with the parent permission slip re-garding student participation in this study. Following the return of thepermission slips, the demographic questionnaire was administered tothese students. Of the 265 eligible students, 199, or 75.1% completedand returned the questionnaire.

Once the first semester data was entered into the school’s computerprogram in January of 2001, the grade and attendance data were gath-ered.

Data Analysis

In analyzing the data collected, several different statistical methodswere used. First, tables were created for each dependent and independ-ent variable. A chi-square test was then used to determine whether ornot the row categories were independent of the column categories. Sec-ondly, a correlation coefficient was calculated for each independent cat-egory versus each dependent category from the tables. Finally, twolinear regression models were used. The first model simply examinedthe family of origin structure and its effects on academic achievement.The second model took into account the other independent family vari-ables. In each equation, the dependent variable is predicted by the com-bination of the independent variables. Two similar models were usedwhen examining the student’s age at the time of their parents’ divorce.

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RESULTS

Following the gathering of data, it was discovered that the ethnic dis-tributions were quite unbalanced. Due to the extremely small numbersin four of the categories, the ethnic groups were collapsed from five intothree groups; ‘White’, ‘Hispanic’, and ‘Other.’

Chi-Square tables were performed examining student GPAs in rela-tion to gender, ethnicity, family size, mother’s level of education, andfather’s level of education. Table 1 shows the results of the only cate-gory reporting any statistical significance. For the purposes of thechi-square test, students’ GPAs were collapsed into the categories asseen below. This was necessary due to the wide range of reported stu-dent GPAs.

It appears that, in general, females outperform males in the area ofgrades at a significant level.

Chi-square tests were also conducted on tables examining students’attendance in relation to the independent variables mentioned above.While the gender variable approached significance, no statistical signif-icance was found with any of these variables.

In examining the family of origin structures, it was discovered that thereported numbers in the categories of ‘father-deceased’, ‘mother-de-ceased’, and ‘parents never married’ were extremely small. Therefore,those family structures were not considered as separate family of originindependent variables in this analysis. Instead, chi-square tests wereperformed examining intact and divorced families in relation to GPAand attendance. Table 2 reports the mean GPAs and attendance figures.

This table shows that those students from intact families outperformthose students from divorced families across all categories. Whenchi-square tables were performed on the GPA data, the numbers ap-proached significance for all students, with a P-value of .153, were notsignificant for males alone, and were highly significant when examin-ing only females, with a P-value of .007.

Similar results were seen in relation to attendance. The chi-squaretest showed significance for all students, P-value = .018. However, thesignificance was more pronounced in relation to females over males.

Following the chi-square tests, the correlation coefficients for eachindependent variable were calculated in relation to the dependent vari-ables. The results of this are found in Table Three.

These coefficients would appear to indicate significance when GPAis correlated with ‘family of origin structure,’ ‘gender,’ and ‘mothers’education. Ethnicity was not shown to be significant, even when it was


divided into simply white and other. The coefficients appear to indicatethat the two factors that most greatly impact students’ attendance are‘family of origin structure’ and ‘ethnicity.’ In looking at specific data,the significance of ethnicity appears to be that ‘Whites’ have fewer ab-sences than do both ‘Hispanics’ and ‘Other.’

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TABLE 1. GPA and Gender

0-.99 1.00-1.99 2.00-2.99 3.00-3.99 4.00-5.00Males 4 8 23 39 19

4.30 8.60 24.73 41.94 20.43

Females 0 8 14 46 38

0 7.55 13.21 43.40 35.89

The number below the count line is the percentage of students in each category (N = 199).Chi-Square = 12.302, DF = 4, P-Value = 0.015

TABLE 2. Mean GPAs and Single-Period Absences of Family of Origin Struc-tures for All Students from Intact and Divorced Families and for Males and Fe-males Separately. The number of students is in parentheses. (N = 185)

GPA–All GPA–Males GPA–FemalesIntact 3.4088 (133) 3.2334 (58) 3.5444 (75)

Divorced 3.0719 (52) 2.9648 (27) 3.1876 (25)

Attendance–All Attendance–Males Attendance–FemalesIntact 5.827 (133) 6.534 (58) 5.280 (75)

Divorced 9.269 (52) 8.815 (27) 9.760 (25)

TABLE 3. Correlation Coefficients of GPA

GPA Attendance

Intact vs. Divorced Family Structure �.171* .198**

Gender .166* �.043

Ethnicity �.001 .181*

Family Size �.118 .060

Mother's Education .200** �.091

Father's Education .060 �.053

Attendance and each independent variable (N=185)*p < .05, **p < .01, ***p < .001, ****p < .0001

The multiple regression model 1 examined the family of origin sta-tus, intact and divorced families, in relation to GPA and attendance.This was used to determine the predictive value of these independentvariables in relation to the students’ two academic dependent variables.Table 4 notes the importance of the variables. In this particular model,for GPA, P = .026 and for attendance P = .034.

The second regression model encompassed the other independentvariables. Using a step-wise multiple regression formula, results indi-cate that only two other independent variables appear to impact GPAother than family structure: gender and mother’s education. This canbe seen in Table 5. When the regression formula was performed onmodel 2, it resulted in a value of P = .005. When it was run again usingonly the three independent variables mentioned, the significance waseven greater with a value of P = .002.

Included in this same table are the results of the model 2 regressionperformed for attendance in relation to the other independent variables.Again, a step-wise regression indicated that aside from the family of or-igin structure, the only other significantly impacting variable on atten-dance was ethnicity. Performing the model 2 regression on attendanceresulted in a value of P = .039. When the regression was conductedagain using only the two variables of family of origin structure andethnicity, the result was even greater significance of predictabilitywith P = .003.

In order to better control for the variables, the multiple regressionformulas were run again. This time it did not include the mother’s levelof education, since those numbers were small, and their size causedquestions of significance with other tests. For the dependent variableGPA, the regression was performed for males and females separately.When doing this, the test reported a value of P = .245 for males and .068for females.

For attendance, similar controls were enacted. Since ‘ethnicity’was the only other independent variable showing significance in thestep-wise regression, this was examined in relation to attendance. Thiswas performed by running the regression for attendance with ‘whites’,again for ‘Hispanics’, and a third time for ‘other.’ The resulting P valueswere, ‘whites’ P = .019, ‘Hispanics’ P = .576, and ‘other’ P = .551.

Results from the above analyses would suggest support for this firsthypothesis. It can be seen from the chi-square tables that aside from thesignificant impact of gender, the family structure is next in importancein addressing GPA. The GPAs of students from intact families were10.96% higher than the grades for students from divorced families.


When the statistics are broken down by gender, it would appear that theGPAs of females are more greatly influenced by divorce than those ofthe males.

The correlation coefficients also support the significance that the in-tact and divorced family structures seem to have on students’ GPA.Again, the independent ‘gender’ variable influences this as well.

The step-wise regression suggests that the ‘mother’s level of educa-tion’ may play a role in students’ academics. However, the chi-squaretable raised the possibility that the numbers may be too scattered for theeducation factor to genuinely influence the grades. The correlation co-efficient did not support the impact of mother’s level of education.

Family structure and gender again appear to strongly influence GPAwhen examined using the two regression formulas. Both the formulawith only the family of origin structures as well as the formula includingthe other independent variables seem to be meaningful predictors ofstudents’ academic GPA. The regression also supports better predictivevalue for females in relation to GPA than for males.

Barry D. Ham 179

TABLE 4. Coefficients from Regression Model 1–Family of Origin: SpecificallyIntact and Divorced (N = 185)

GPA Attendance

Intact vs. Divorced Family Structure �.3369* 3.442*

*< p. 05, ** < p.01, ***< p .001, ****, p .0001

TABLE 5. Coefficients from Multiple Regression Model 2–Family of Origin:Specifically Intact, Divorced, Gender, Ethnicity, Family Size, Mother's Level ofEducation, and Father's Level of Education (N = 185)

GPA Attendance

Intact vs. Divorced �0.2341 3.771*

Gender 0.2951* �1.025

Mother's Education 0.2063* �0.3967

Ethnicity 0.0000 3.209**

Family Size �0.2348 1.314

Father's Education �0.0168 0.537

*< p .05, **< p .01, ***< p .001, ****, p .0001

In examining single-period unexcused absence figures, it is notedthat students from divorced families missed an average of 59.06% moreclass periods than did those from intact families. This chi-square tablefor all students supported that this difference is significant. However, itwas interesting to discover that when only males were examined, thenumbers, 34.90% increase, were not considered to be as important.Conversely, the females were seen as more impacted, 84.85% absenceincrease. Similar to the findings in relation to GPA, females’ attendanceappears to be more greatly affected by the change of family status, fromintact to divorced, than do the males.

In running correlation coefficients, it was again found that family oforigin structure correlated highly with students’ attendance. Thoughunlike GPA, ‘gender’ and ‘mother’s level of education’ were not seenas significant. Yet, for attendance, ethnicity appears to play a significantrole. This too is different from the results found with GPA.

The step-wise regression formula also suggested that ‘family of ori-gin structure’ and ‘ethnicity’ were the two most significant independentvariables relating to attendance. Both the model 1 and model 2 regres-sions including the other independent variables indicate that these fac-tors were significant in predicting student absences. However, whenexamined specifically in relation to ethnicity, it would appear that being‘white’ is much more significant in predicting attendance when from anintact or divorced family structure. Being from a group other than‘white’ greatly reduces the formula’s predictive value.

The above data indicates support for the second hypothesis as well.While not a part of the original hypotheses, an examination was

conducted for those students from divorced homes to determinewhether or not a child’s age at the time of divorce would be a factorin academic achievement. In the questionnaire, students from di-vorced homes were simply asked what their age was at the time of di-vorce. The responses were relatively evenly distributed from agesone to eighteen. A chi-square table, correlation coefficient, and multi-ple linear regression were all performed using this data. While some dif-ferences were evident, no clear pattern emerged. When the results ofboth GPA and attendance are examined, little consistency was discov-ered. In looking at all of the students from divorced families together, itappears that students whose parents divorced when the child was be-tween the ages of six and nine, during the primary grades, had a higherGPA than other age categories. This same group also reported the low-est absence figures. Adolescents in the middle school years, falling inthe 10 to 14 years of age group, when their parents divorced, appeared


to perform more poorly than the other groups. Yet, it must be noted thatnone of these differences are statistically significant. When the samegroup of students was examined by gender, any patterns seemed tocompletely disappear.

DISCUSSION

Results of this research suggest that family of origin structure plays asignificant part in adolescents’ grades and attendance. The findingssupport the hypotheses that adolescents from intact homes performbetter academically and maintain better school attendance than dothose students from divorced homes. In conducting the statistical mea-sures, the one factor that consistently showed significance was familystructure. Students from intact families outperformed students fromdivorced families with GPAS nearly 11% higher. Similarly, when ex-amining single-period unexcused absences, the high school seniorsfrom divorced households missed almost 60% more class periods thandid those from intact families.

Findings from this research which suggest that family structure canbe a contributing factor to a student’s academic performance, provideadditional support to the earlier reported studies of Frum (1996), Jeynes(1997), Gunning (1998), and Pong and Ju (2000). Those students resid-ing with their two biological parents appear to be given an increasedchance to excel educationally over those students from any other mea-sured family structure.

Controlling for other variables produced some interesting results.The multiple regression model suggested that a mother’s level of educa-tion might be a predictive factor in a student’s GPA. Yet, the chi-squaretable indicated that the numbers might be too small to actually be mean-ingful.

Demo and Acock (1996) discussed the relationship of the mother’swell-being and her child’s academic success. This current study impliesa possible similar connection. There appears to be some correlation be-tween a mother’s level of education and the education of her adolescent.The further she has progressed in her own formal education, the betterher student seems to perform, supporting the findings of Garasky(1995). However, it is interesting to note that the same results were notfound when examining the father’s level of education. This is in con-trast to the findings of those who discovered a more pronounced effectwhen the father’s level of education was examined in relation to their

Barry D. Ham 181

student’s own level of attainment (Berends, Grissmer, Kirby, & Wil-liamson, 1999). One possible explanation for this result is that the moth-ers of the students in this study came with a broader range of levels ofacademic achievement. While almost all of the mothers had completedhigh school, only about a quarter of them attended some college and alittle less than half finished college. It was more difficult to find thiskind of variance in order to measure impact with the fathers. Approxi-mately 85% of the fathers attended college with nearly 70% graduating.This is not surprising when it is considered that the students in this highschool come from an upper middle class community. A less affluentarea quite possibly would have presented a greater variety of data alongwith more pronounced results. This area regarding mother’s level of ed-ucation is worthy of future investigation.

Ethnicity also showed up as a factor related to attendance. The His-panic students’ absences were slightly higher than those of white stu-dents or those from the ‘other’ category. Yet, the most noticeable effectwith regard to ethnicity was that the regression formula was more pre-dictive when examining the family structure for ‘whites.’ While thepopulation for this study was predominately white, the next largestgroup represented was Hispanic, which is a growing segment of thepopulation. Results of the 2000 census show that in the state of Colo-rado the Hispanic population has grown by 75% over the last 10 years(Ragan, March 20, 2001). Therefore, it would be beneficial to conductfurther research of this ethnicity to more accurately determine how theeffects of divorce impact this population.

Controlling for gender produced some surprising trends. For bothgrades and attendance it was seen that females were more greatly im-pacted negatively by divorce than were males. Attendance figures werethe most dramatically different. Consistent with the work of Neighbors,Forehand, and Armistead (1992), it was found that males from divorcedfamilies had lower GPAs than males from intact families. The same re-sults were found in relation to females. However, one important differ-ence was evident. While they found that males were more greatlyimpacted by the divorce, this study suggests that females are the mostimpacted. It is their belief that boys may have a closer relationship withtheir dads than the girls do. Therefore, when dad leaves, it is natural toassume that the boys are more traumatized. However, the results of thiscurrent study might suggest another possibility. Amato and Booth(1996) discovered that following a divorce the father’s affection for hischildren diminished. It has been reported that children’s self-esteem canbe tied directly to their attachment with their father (Coley, 1998). One


suggestion is that since the father and son may possess a stronger initialconnection, even following a divorce, they are in a better position tocontinue a relationship or at least have something to build upon. If thedaughters have a weaker relationship with their fathers before the par-ents separate, the diminished attachment following divorce may be allthat is needed to completely distance the two individuals. Most thera-pists recognize the importance of the father-daughter connection.Young women derive a significant degree of their self-esteem fromtheir relationship with their father. It seems logical that if this relation-ship is weakened or non-existent, their self-esteem suffers resulting indecreased academic success.

One of the most significant findings of this study is related to this in-creased impact that divorce appears to have on females over males. Thiswould be an important result to replicate as well as to examine further.Working to discover more specifically the reasons of the difference inimpact could help further efforts to reduce the negative consequencesfor these young women.

When it comes to a student’s age at the time of his or her parents’ di-vorce, this study found no significant correlation to GPA or atten-dance. This is consistent with the research of Gunning (1998) andJeynes (1997). However, Wallerstein’s work (Wallerstein & Kelly,1980; Wallerstein & Blakeslee, 1989, Wallerstein & Lewis, 1998, andWallerstein, Lewis, & Blakeslee, 2000), found that the effects of di-vorce often remained ten years and longer. The study conducted in Can-ada (Buchanan et al., 1996), found that problems for children fromdivorce seemed to peak around the age of 12, or during middle school.While the results of this current research project showed no signifi-cance, the numbers hinted that it might prove more difficult for studentswhen their parents divorce during their middle school years. Having ac-cess to a larger sample of students from divorced families might pro-duce more meaningful results for future researchers.

Another possibility for future study would be to conduct a longitudi-nal study with high school students. This might provide even more valu-able and accurate information. The data gathered for this study wasproduced over the period of one semester. For those students whose par-ents have been divorced for four or more years, it would have been in-teresting to follow their entire four years in high school. By doing so,one could observe both processing patterns as well as more cumulatingeffects.

The ethnic breakdown and socio-economic status of the majority ofstudents in this school district were fairly constant. Therefore, the find-

Barry D. Ham 183

ings of this study could be appropriately generalized to other seniorswithin this district as well as applied to students of schools in other loca-tions with similar ethnic and socio-economic make-up. However, theywould not necessarily be reflective of students in other locations with agreater variety of demographics.

One final suggestion is that greater study be conducted regardingwhat is working to reduce the impact of divorce on students in thiscountry. Any program that can help to reduce negative impact on chil-dren is worthy of research. Naturally, if successful methods were foundto help families in crisis, it would be necessary to validate their successand then make them available to people on a widespread basis. The ulti-mate goal should not be just to do research for the sake of scholarlyachievement. It should be for the purpose of helping to better lives ofboth children and their parents.

REFERENCES

Amato, Paul, & Booth, Alan (1996, May). A prospective study of divorce and par-ent-Child relationships. Journal of Marriage & the Family, 58 (2), 356-365.

Berends, Mark, Grissmer, David W., Kirby, Sheila Nataraj & Williamson, Stephanie(1999). The changing American family and student achievement trends. Researchin Sociology of Education and Socialization, 12, 67-101.

Buchanan, Christy M., Maccoby, Eleanor E., & Dornbusch, Sanford M. AdolescentsAfter Divorce. Harvard University Press: Cambridge, Massachusetts, 1996.

Coley, Rebekah Levine (1998, Feb.). Children’s socialization experiences and func-tioning in single-mother households: The importance of fathers and other men.Child Development, 69 (1), 219-230.

Demo, David H., & Acock, Alan C. (1996). Family structure, family process, and ado-lescent well-being. Journal of Research on Adolescence, 6 (4), 457-488.

Frum, David (1996, Feb.). The social cost of single parenthood. Reader’s Digest, Ca-nadian Edition, 148 (886), 29-30.

Furstenberg, Frank F. Jr. (Spring, 1994). History and current status of divorce in theUnited States. The Future of Children, 4 (1), 29-41.

Garasky, Steven (1995, Jan.). The effects of family structure on educational attain-ment: Do the effects vary by the age of the child? American Journal of Economics &Sociology, 54 (1), 89-105.

Gunning, Carryl (1998). Academic achievement in adolescents of divorce: A study ofstudent performance in an eighth grade science curriculum. Unpublished master’sthesis, Miami University, Oxford, Ohio.

Hetherington, E. Mavis, & Stanley-Hagan, Margaret (1999, Jan.). The adjustment ofchildren with divorced parents: A risk and resiliency perspective. Journal of ChildPsychology & Psychiatry & Allied Disciplines, 40 (1), 129-140.


Jeynes, William Hettich (1997, March). Assessing socio-economic theory’s explana-tion for the effects of divorce and remarriage on academic achievement. Unpub-lished doctoral dissertation, University of Chicago, Chicago, Illinois.

Lamb, Michael E., Sternberg, Kathleen J., & Thompson, Ross A. (1997, Oct.). The ef-fects of divorce and custody arrangements on children’s behavior, development,and adjustment. Family & Conciliation Courts Review, 35 (4), 393-404.

McManus, Michael J. (1993). Marriage Savers: Helping Your Friends and FamilyStay Married. Grand Rapids, Michigan: Zondervan Publishing House.

Neighbors, Bryan, Forehand, Rex, & Armistead, Lisa (1992, Fall). Is parental divorcea critical stressor for young adolescents? Grade point average as a case in point. Ad-olescence, 27 (107), 639-646.

Pong, Suet-Ling, & Ju, Dong-Beom (2000, March). The effects of change in familystructure and income on dropping out of middle and high school. Journal of FamilyIssues, 21 (2), 147-169.

Ragan, Tom (2001, March 20). Hispanic numbers skyrocket. The Gazette, ColoradoSprings, 129 (362), A6.

Sandefur, Gary D., McLanahan, Sara, & Wojtkiewicz, Roger A. (1992, Sept.). The ef-fects of parental marital status during adolescence on high school graduation. SocialForces, 71 (1), 103-121.

Shiono, Patricia H., & Quinn, Linda Sandham (Spring, 1994). Epidemiology of di-vorce. The Future of Children, 4 (1), 15-28.

Single-parent kids fair better if parent is divorced, rather than never married: Censusdata show (1997, Dec.). Jet, 93 (3), 48.

Smith, Thomas Ewin (1995). What a difference a measure makes: Parental-separationeffect on school grades, not academic achievement. Journal of Divorce & Remar-riage, 23 (3/4), 151-164.

Wallerstein, Judith S., & Blakesless, Sandra (1989). Second Chances: Men andWomen a Decade After Divorce. Boston: Houghton Mifflin Company.

Wallerstein, Judith S., & Kelly, Joan Berlin (1980). Surviving The Breakup: HowChildren and Parents Cope with Divorce. New York: Basic Books, Inc., Publishers.

Wallerstein, Judith S., & Lewis, Julia (1998, July). The long-term impact of divorce onchildren. Family & Conciliation Courts Review, 36 (3), 368-383.

Wallerstein, Judith, Lewis, Julia, & Blakeslee, Sandra (2000). The Unexpected Legacyof Divorce. New York: Hyperion.

Wojtkiewiez, Roger A. (1993, Nov.). Simplicity and complexity in the effects of pa-rental structure on high school graduation. Demography, 30 (4), 701-717.

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