academic orientation and parental involvement in education during high school

Academic Orientation and Parental Involvement in Education during High SchoolAuthor(s): Robert CrosnoeSource: Sociology of Education, Vol. 74, No. 3 (Jul., 2001), pp. 210-230Published by: American Sociological AssociationStable URL: http://www.jstor.org/stable/2673275 .

Accessed: 28/06/2014 13:07

Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at .http://www.jstor.org/page/info/about/policies/terms.jsp

.JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range ofcontent in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new formsof scholarship. For more information about JSTOR, please contact [email protected].

.

American Sociological Association is collaborating with JSTOR to digitize, preserve and extend access toSociology of Education.

http://www.jstor.org

This content downloaded from 92.63.103.2 on Sat, 28 Jun 2014 13:07:24 PMAll use subject to JSTOR Terms and Conditions

http://www.jstor.org/action/showPublisher?publisherCode=asa

http://www.jstor.org/stable/2673275?origin=JSTOR-pdf

http://www.jstor.org/page/info/about/policies/terms.jsp


Academic Orientation and Parental Involvement in Education

During High School

Robert Crosnoe University of Texas at Austin

This study applied a life course perspective to the phenomena of adolescent academic orientation and parental involvement in education. Applying latent growth modeling to transcript and survey data from a sample of California high school students revealed that while college-preparatory track students begin high school the highest in orientation and involvement, they also experience sharp declines in both over time. Within the college-preparatory track, the decline in involvement is the greatest among the highest-achieving students, whereas within the remedial track, the decline is the greatest among minority students. Finally, initial academic orientation promotes increasing parental involvement, but only in the two non-college-preparatory tracks.

oung people are embedded in a a m ^system of overlapping contexts,

including the school and the family. Investigating the interac-

tive influences of these institutions and the place of the individual in the process is crucial to understanding the academic development of adolescents. In this study, I sought to illuminate the complex relation among school, family, and adolescents by examining trajectories of academic orientation and perceived parental involvement in education among high school students at different levels of the curricular hierarchy.

Life course theory provides a useful approach to these trends. First, it views lives as interlocking trajectories embedded in a sociohistorical context (Elder 1998). The social pathways of young people are linked to those closest to them, including their parents, and are embedded in the structure of the school. Second, unlike human ecology and other perspectives, life

course theory emphasizes the importance of following lives across time (Elder 1998). Thus, applying this theoretical orientation to the high school years captures the dynamic nature of adolescents' educational experiences as they develop within structural and interpersonal constraints.

By tracing the changing nature of adolescents' feelings about school and percep- tions of parental involvement, I sought to illustrate how adolescents develop academically, how this development is intimate- ly and reciprocally related to changes in their relationships with parents, and how these interwoven processes are embedded in the structural organization of the school. Such research is important for several reasons. First, unlike past research on academic orientation and parental involvement (e.g., Sanders 1998; Stevenson and Baker 1987), I sought to determine how these two phenomena have evolved over time. Second, I drew on a data source that is longitudinal, contains an ethnically diverse

Sociology of Education 2001, Vol. 74 (July): 210-230 210



Academic Orientation and Parental Involvement in Education 211

sample, and combines adolescents' self- reports with information from official high school transcripts. Third, I used latent growth-curve modeling, which allows the examination of interindividual differences in intraindividual change and the determination of the social factors that contribute to both.

BACKGROUND

Academic Orientation in High School Academically oriented students feel commit- ted to the educational system and believe that education is the key to success as adults (Connell, Beale-Spencer, and Aber 1994). This orientation has been studied less than other academic factors, such as achievement, but it is known that it promotes academic competence (Newman, Wehlage, and Lamborn 1992; Sanders 1998). Academic orientation also reduces the association with and susceptibility to deviant friends as well as delinquent behavior (Crosnoe, Erickson, and Dornbusch forthcoming; Erickson, Crosnoe, and Dornbusch 2000). By bonding students to the school and conventional society, this psychological characteristic plays an important role in the academic and social development of young people and warrants closer inspection.

The first goal of this study was to determine whether the academic orientation of students changes over the course of high school. What little research has been done in this area has suggested that academic orientation declines over time. For instance, older students tend to be less oriented to school (Sanders 1998). Similarly, research from the National Longitudinal Study of Adolescent Health has found that school attachment, a related concept that taps students' feelings about their school environment, is lower in high school than in junior high school and is negatively related to grade level (Johnson, Crosnoe, and Elder forthcoming; Moody 1997). These studies have provided preliminary information that academic orientation is best viewed as a trajectory.

The second goal of this study was to deter-

mine whether trajectories of academic orientation differ across curricular tracks. Most public secondary schools have stratified curricula, in which students are assigned to general arrays of classes, usually related to their ability levels in math, English, and science, on the basis of teachers' recommendations, test scores, grades, and other criteria (Dornbusch, Glasgow, and Lin 1996). Past research has demonstrated that different tracks offer vastly different educational experiences to students, are directly related to students' academic and social status in the school, and promote differential achievement that widens inequality among students (Hallinan 1996).

Curricular status and academic orientation are intricately related. Valuing education is embedded in what students feel they are "getting" from school, which, in turn, is related to their track location. Students over- whelmingly want to go to college and enter professional occupations, but few of them are on the correct path to do so (Schneider and Stevenson 1999). Some curricula prepare students for this future, while others do not. These discrepancies between progress and prospects doubtlessly influence how students feel about school.

For instance, that students in the lower tracks are less academically oriented has been well established (Bennett and LeCompte 1990). These students are enrolled in less challenging and less rewarding classes, and they are aware of their status location in the school hierarchy and of the message that this status sends about their ability to succeed (Oakes 1995). Their less positive feelings about school are not surprising. The academic orientation of these students may also decline more rapidly across high school as they gradually realize that their educational experience is not preparing them for their desired future. Though they may, at first, have less knowledge about the insufficiency of their education for college admission and the higher earnings and occu- pational status they know is tied to admission, they are likely to grow more aware of this insufficiency as they near graduation. Since the educational system has, in a sense, failed them, they may devalue the importance of education over time (Csikszentmihalyi and Schneider 2000; Oakes 1995).



212 Crosnoe

Conversely, students in the higher tracks have a greater stake in the educational process, enjoy higher status, and participate more in challenging and rewarding course work (Csikszentmihalyi and Schneider 2000; Oakes 1995). As a result, they are more academically oriented in general. This orientation is unlikely to decline over time. Unlike their lower-track counterparts, these students can see where success in high school is taking them-to college and beyond. They have clear expectations for the future and view high school as one important piece of the process (Csikszentmihalyi and Schneider 2000).

Thus, if high school students generally become less academically oriented over time, as is hypothesized, this trend is probably driven by students in the non-college-preparatory tracks.

The third goal of this study was to determine what social and individual factors contribute to academic orientation at the start of high school and to change in orientation over time and whether these contributions differ by track. In addition to age, socioeconomic factors (e.g., intact family and educated parents), being female, and being African American have been associated with greater academic orientation (Erickson et al. 2000; Mickelson 1990; Sanders 1998). Furthermore, social disadvantages may differentiate higher-track students more than lower-track students (Hallinan 1996). Students who do well in school tend to be more academically oriented, but the direction of this relationship is difficult to determine (Sanders 1998). Controls for pretrack achievement are needed to disentangle this association. Again, less is known about whether these factors lead to changes in academic orientation over time.

Parents' Involvement in Their Adolescents' Education The extent to which parents are involved in the education of their adolescents has been more extensively studied than has academic orientation. Involvement generally refers to parents' management of their adolescents' careers (e.g., helping to select courses), active assistance (e.g., helping with homework), encouragement of educational goals, and

attendance at school events (Muller 1995). In general, such involvement promotes academic success, even when previous achievement is taken into account, though the importance of involvement may decline with time (Muller 1998; Steinberg, Lamborn, Dornbusch, and Darling 1992).

I asked the same three questions about parental involvement as for academic orientation: (1) Does parental involvement change over time? (2) Do trajectories of parental involvement differ across curriculum tracks? and (3) What social and individual factors contribute to initial levels and rates of change in parental involvement? In addition, I sought to determine whether trajectories of academic orientation and parental involvement are related to each other.

Past research has suggested that parents tend to become less involved in their children's educational careers over time, especially after elementary school (Stevenson and Baker 1987). This decline may occur because students desire more autonomy as they grow older, because parents give more space to their adolescents, and because parents feel less knowledgeable about more complex material (Muller 1998; Steinberg, Brown, and Dornbusch 1996). In general, research on changes in parental involvement has compared mean levels at different points, but no studies have attempted to model the underlying trajectories of involvement.

According to Muller (1 998), parental involvement is context specific, such that parents respond to their adolescents' needs and adjust their involvement at home or in school accordingly. The contextual nature of involvement helps to explain the general disengage- ment of parents over time, but it also sheds light on why the parents of more successful students may be more likely to disengage. When students are doing well in school, their parents see less need to monitor their progress, have less motivation to engage actively in school-related activities, and have less reason to meet with teachers, whereas when students are having trouble in school, their parents may be more likely to become involved (McNeal 1999; Sanders 1998).

This phenomenon accounts for occasional negative cross-sectional correlations between




involvement and students' achievement, but it also points to possible track differences in trajectories of parental involvement. Parental involvement is generally greater in higher tracks (Useem 1992), but it may decline more rapidly in these tracks as parents see that their adolescents are on the right course. These parents know that their adolescents are taking the appropriate steps toward the ultimate goal of college and, therefore, can afford to grant them more independence (Csikszentmihalyi and Schneider 2000). Alternatively, parental involvement is generally less common in the lower tracks, but the parents of these students may be less likely to disengage over time since their adolescents need more guidance. Thus, if parents tend to become less involved over time, as is hypothesized, this trend is probably driven by students in the higher tracks.

Social advantages, in the form of intact families, parental education, and ethnic majority status, tend to predict greater involvement. Such parents are more knowledgeable about educational systems, more confident about intervening, and have more time to take an active role (Csikszentmihalyi and Schneider 2000; McGrath, Swisher, Elder, and Conger forthcoming). Again, these factors have rarely, if ever, been related to changes in parental involvement over the course of high school.

Finally, academic orientation and parental involvement may interact. Involved parents serve as models for their adolescents, giving solid evidence that they view education as important. At the same time, more engaged students may draw parents into their educational careers (Steinberg et al. 1 996). Whether trajectories of academic orientation and parental involvement are interwoven over time is less clear. The final goal of this study was to determine the extent to which initial starting points and rates of change in this individual factor and this family factor are related to each other and whether these relationships differ across curricular tracks.

Linking the Adolescent, Home, and School Academic orientation lies at the intersection between the individual student and his or her

environment. Parental involvement represents the interdependent lives of young people and their parents. Both may fluctuate with time and changing conditions, and both are best viewed as trajectories. In addition to being related to each other, these two factors are intricately related to the curricular location of the student. For instance, more academically oriented students tend to be in higher tracks, while more involved parents are better able to steer their adolescents into higher tracks (Oakes 1985; Useem 1992). Yet, track location may also enhance or diminish both factors in dynamic ways.

The tangled nature of these relationships illustrates the complexity of the life course, even in the early stage of adolescence. Rather than view tracking, academic orientation, and parental involvement in isolation, life course theory helps us to conceptualize how they come together. Rather than view these factors as static, life course theory reveals their dynamic nature.

In my study, I drew on life course principles to examine how academic orientation and parental involvement change over time, how these trajectories are moderated by track location, which factors predict the different components of these trajectories within tracks, and the extent to which these two trajectories are interwoven with each other and embedded in high school curricular organization.

METHOD

Source of Data To examine the educational trajectories of high school students, I drew on a data set of adolescents who were part of a larger longitudinal study of nine high schools in California and Wisconsin from 1987 to 1990 (see Steinberg et al. 1996). Students com- pleted one extensive survey, covering social, educational, and psychological factors, per semester in three consecutive school years. The two questionnaires administered in each school year are complementary, so that each year serves as one time point.

As part of this study, high school tran-



214 Crosnoe

scripts were obtained for a subsample of 1,245 students. These students were enrolled in the California schools, located in two districts in two counties with a combined population exceeding 2 million. This subsample was selected to maximize variability in school performance for non-Hispanic whites, Asian Americans, African Americans, and Hispanic Americans. Within each of the six California schools, to the extent possible, equal num- bers of students were selected at random from high-, mid-, and low-performing students within each ethnic-gender group. All the participants provided informed consent before the data were collected.

The study presented in this article was based on this special subsample, which combined adolescents' self-report data with information from official school transcripts. An additional selection criterion led to the study sample. Modeling trajectories requires a min- imum of three time points. The study covered three years, but because data collection was school based, not all students participated in data collection in each of these years. For example, students who were seniors in year 1 of the data collection did not participate in subsequent years. Thus, only students who were freshmen and sophomores in year 1 could potentially be included in all three waves of data collection.

Therefore, the final study sample con- tained 692 students, all freshmen and sophomores in year 1, from six schools. This sample, on the individual and school levels, is not representative of the nation as a whole, but it does provide sufficient diversity, richness, and span for a more in-depth exploration of educational trajectories than has been done in the past.

On the individual level, the students were ethnically heterogeneous (35 percent white, 1 7 percent African American, 19 percent Asian American, and 29 percent Hispanic American), reflecting the diversity of the communities from which the sample was drawn. This ethnic composition is similar to the composition of the two California school districts, although minority students were overrepre- sented in the sample because of purposeful oversampling. As for other characteristics, the sample was roughly evenly split by gender

(51 percent female, 49 percent male). The majority of the students (61 percent) were liv- ing with two biological parents, and the average parent in this sample had some post-high school education (M = 1 3.25, SD = 3.29).

On the school level, the sample also encompassed a broad swath of ecological strata. Such diversity has implications for the analysis of educational trajectories (Kerbow and Bernhardt 1993). Although the size of the sample did not provide enough power for the study of school-to-school differences, I give a fuller description of each school so that readers can place this sample in a national context.

Table 1 presents descriptive statistics for each school (based on the full sample for each school), which I supplement with more qualitative information. Three schools repre- sented advantaged educational environ- ments-predominantly white, higher socioeconomic status (SES), and situated in sup- portive suburban communities. These schools had minority representation through busing. They also had high achievement. In fact, School 1 won a national award for academic excellence. The other schools were more disadvantaged-greater minority representation, lower SES, and lower achievement. Their community settings provided unique chal- lenges. School 4 was near the center of a large metropolitan area. School 5 was located in a working-class community, but because of liberal transfer policies, it was rapidly losing students. School 6 was situated in a suburb that was undergoing major growth.

These schools differed in two key ways: ethnic composition and curricular structure. Though all the schools were predominantly white, some had one clear minority (such as Asian Americans in School 6). Three schools (3, 4, and 5) had few African American students, while one (School 2) had a sizable representation. In addition to being a marker of social advantage, ethnic composition may influence how minority students feel about education and how welcome their parents feel in the educational process (Johnson et al. forthcoming, Kerbow and Bernhardt 1993). In most schools, the college-preparatory track housed the largest percentage of students (ranging from 36 percent to 52 percent). In



Academk Orientation and Parental Involvement in Education 215

Table 1. Descriptive Statistics for the Six Study Schools

More Advantaged More Disadvantaged

School 1 School 2 School 3 School 4 School 5 School 6

% White 64.2a 58.7b 62.3ab 5 3c 62.5ab 41.3d % African American 5.1 c 1 6.9a 2.6c 3.0c 2.6c 7.7b % Hispanic American 14.1d 18.2c 13.7d 35.2a 23.7b 15.2cd % Asian American 1 6.6c 6.3ed 21 .3b 8.6d 11 .2d 35.8a Mean parent education 15.03a 14.79ab 14.56b 13.48C 13.02d 13.62C

(2.79) (3.24) (2.60) (3.19) (2.71) (2.65) Mean academic achievement 3.06a 2.88b 2.88b 2.70d 2.58C 2.67de

(.78) (.81) (.83) (.79) (.77) (.93)

% Remedial track 26.7a 38.5a 27.5a 36.1a 16.8b 20.9a % General track 25.7b 25.4b 33.6ab 22.9b 47.4a 27.5ab % College-preparatory

track 47.6 36.1 38.9 41.0 35.8 51.5 Total enrollment 2,640 3,015 2,699 2,700 2,033 3,920 Study N 112 142 116 86 101 135

Note: For means, standard deviations are presented in parentheses. Coefficients with different subscripts differ significantly (p < .05) across schools, as determined by a one-way ANOVA with Scheffe post- hoc tests. Subscript a represents the strongest coefficient, with b, c, d, and e indicating coefficients in descending order from the strongest. Coefficients with the same subscript do not differ significantly.

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

one disadvantaged school (School 5), the general track was modal. In one advantaged school (School 2), the remedial track was slightly larger than the college-preparatory track. This school, located in a wealthy area, had a sizable proportion of students who were bused in from one of the lowest-performing elementary school districts in the state. These differences suggest that tracking may provide different educational contexts within different schools.

Measures For academic orientation and parental involvement in education, measures were cre- ated for all three years of data collection. For the remaining variables, measures were creat- ed for year 1 only.

Academic Orientation Each year, adolescents indicated agreement with the following six statements: "Success in life does not have much to do with the things studied in

school," "The best way to get through most days at school is to goof off with friends," "I'm losing interest in school because my teachers keep going over the same old thing," "Most of the teachers don't really expect very good work from me," "Most of my classes are boring," and "I feel satisfied with school because I am learning a lot." The responses ranged from "strongly agree" (1) to "strongly disagree" (4). The last item was reverse coded so that higher scores on all items indicated greater orientation. The six items were then averaged into a composite scale for each year (M = 2.80, SD = .56, oc = .69). This measure has been used, as both an independent and a dependent variable, in several studies (Crosnoe et al. forthcoming; Steinberg et el. 1992).

Parental Involvement in Education Each year, adolescents answered a set of five questions about their mothers and fathers. For each parent, they estimated how often that parent helped them with homework when



216 Crosnoe

asked, knew how they were doing in school, attended school programs for parents, watched them in sports or school activities, and helped them in choosing courses (ct = .71 for mother and .77 for father). The responses ranged from 1 (never) to 3 (usually). I took the mean of the five items for each parent and then took the mean of both parents' scores for each year if both parents had valid information (M = 2.06, SD = .50). If only one parent had valid information, then that parent's value served as the measure of involvement. Of the 39 students who did not live with either parent, all but one lived with some legal guardian. Twenty-five of these students responded to the parental involvement items in reference to one or more guardian, and the remaining 14 were treated as missing.

This measure, which has been used extensively (Steinberg et al. 1992), represents a combination of the numerous involvement factors detailed by Muller (1998). Since the items tap into different aspects of involvement, however, I provided a conceptual and empirical check on the main analyses by breaking down the composite into its con- stituent items and reestimating the basic models for each.

Curriculum Track Official school transcripts list the track level of all classes. I used freshman-year math classes to assess the freshman-year track level because math tracks tend to be the most rigid across high school and because educational differences tend to be the widest across math tracks (Bennett and LeCompte 1990; Hallinan 1996). I col- lapsed several classes into three categories: remedial, general, and college preparatory. The general track includes all classes that do not prepare students for college admission and is similar to the basic and regular distinc- tions in past research (Hallinan 1996), while the college-preparatory track includes Advanced Placement and honors classes.

Over 90 percent of the students did not change tracks during their freshmen year. For those who did, the track level of the second semester math class serves as the overall track level, since using this information distinguish- es downward from upward trajectories in the curriculum. Only 36 students did not enroll in

any math class during this period, and they were dropped from track-related analyses. Because track serves as a moderator in these analyses, missing track information cannot be estimated (or imputed). Most students (42.1 percent) were enrolled in the college- preparatory track in their freshman year, while 30.2 percent were enrolled in the general track, and 27.7 percent were taking remedial math classes.

Academic Achievement Achievement was measured from information on grades in math, English, science, and social studies list- ed in the official school transcripts. Not all students took all four subjects in each year, so this estimated grade point average reflects their success in the core classes in which they were enrolled. Grades were converted to a four-point scale, averaged across semesters for each subject, and then averaged across subjects (M = 2.16, SD = 1 .01).

Standardized Test Performance Transcripts provide percentile scores on pre-high school (and pretrack) standardized tests: either CTBS or Iowa tests taken in the seventh and eighth grades (M = 61.16, SD = 24.18).

Demographic Characteristics I included four demographic variables, all based on adolescents' self-reports: gender (1 = female, 0 = male), family structure (1 = intact family, 0 = nonintact), parents' education (mean of parents' years of schooling), and dummy variables for ethnicity (African American, Hispanic American, and Asian American, with non- Hispanic white as the reference category).

Plan of Analysis To study the trajectories of academic orientation and parental involvement in education, I used latent growth modeling, a specific type of random coefficient model that models change in a phenomenon and individual differences in such change over time. In this technique, time-specific measures of some construct are used to estimate an underlying growth trajectory-a single line that best fits the multiple time-specific measures. As in a general structural equation modeling frame-




work, this trajectory can be characterized by unobserved latent factors, in this case, the intercept and the slope (Curran 2000).

Figure 1 depicts a linear growth model for academic orientation. Measures of academic orientation at three consecutive time points are used to estimate the over-time trajectory in orientation. The first latent factor represents the intercept, or starting point, of the trajectory. Factor loadings for this latent factor are set to 1 to represent the starting point of the trajectory in year 1. The second latent factor represents the slope, or the rate of change in academic orientation across three years. To define the slope as linear, the factor loadings for this latent factor are set to 0, 1, and 2. The mean of the latent intercept factor gives the average starting point of the trajectory for the population, while the mean of the latent slope factor gives the average rate of change for the population. The variance estimates of the two latent factors give the variation of each individual around the overall means for the starting point and the rate of change for the trajectory of orientation. This estimation of variation in individual trajectories is why this technique can be considered a type of random coefficients model (Curran 2000).

The analyses in this study proceed in three

steps. First, I estimate separate unconditional models for academic orientation and parental involvement. The unconditional models estimate the means and variances of the two latent factors for each construct, as captured in Figure 1.

Second, I perform group comparisons to determine whether these trajectories differ by curricular track. To explain this procedure, I use parental involvement as an example. In the first step, I freely estimate all parameters within each track, and, in the second step, I constrain some component of the model, the mean of the intercept for instance, to be equal across the remedial track and the general track. If using the constraint significantly reduces the X2/df of the model, I can con- clude that the starting point in parental involvement differs significantly for these two groups. This procedure is repeated for all possible track combinations-for the mean and variance of both the intercept and the slope.

Third, I treat the two latent factors as dependent variables to be predicted by individual and social factors. The parameter estimates of this model reflect the degree to which such characteristics affect starting points and/or rates of change in academic orientation and parental involvement. Fourth, I combine the latent growth trajectories for

Figure 1. Linear Growth Model for Academic Orientation over Three Years of High School

Orient. Orient. Orient. Year 1 Year 2 Year 3

intercept lope



218 Crosnoe

academic orientation and parental involvement into one model to determine whether growth in one of these constructs is related to growth in the other. All these models are estimated in Mplus (Muthen and Muthen 1999), which employs a maximum likelihood estima- tor that uses information from all observa- tions to estimate missing data.

RESULTS

Trajectories of Academic Orientation and Parental Involvement Past research has suggested that students become less academically oriented as they move through high school, while their parents become less involved in their educational careers (Sanders 1998; Stevenson and Baker 1987). The first goal of this study was to use latent growth modeling to determine whether these trends do occur in a diverse longitudinal sample of high school students.

In the unconditional model for academic orientation (see Table 2), for all students, the estimate of the mean of the latent intercept factor is 2.80 (p < .001, on a scale of 1 to 4), the estimate of the mean of the latent slope factor is -.04 (p < .01), the estimate of the variance of the intercept is .18 (p < .001), and the estimate of the variance of the slope is .03 (p < .05). Thus, students begin high school with a moderate level of academic orientation but experience a decline across high school. Moreover, students vary significantly in their initial levels and rates of change.

A similar trend is seen for parental involvement in education. Parents are moderately to highly involved at the start of adolescents' high school careers but become less involved over time. According to students' reports, however, not all parents are alike in their initial involvement or in their change in involvement over the next three years. For all students, the mean of the intercept is 2.05 (p < .001, on a scale of 1 to 3), and the mean of the slope is -.04 (p < .001). The variance of the intercept is .20 (p < .001), and the variance of the slope is .03 (p < .05).

Of course, the composite measure of involvement combines several behaviors. Perhaps this downward trend is driven by a subset of these behaviors, or perhaps different behaviors demonstrate different, or even oppo- site, trends. To test this possibility, I reestimated the unconditional model for each behavior (see Table 3). The general downward trend is seen for helping with homework and course selection, being knowledgeable about school, and attending school programs. The fifth item, parental attendance at sporting and extracurricular events, also mirrors the decline of the overall composite, but this negative slope is not statistically significant. Therefore, in general, the various behaviors that constitute the phenomenon of parental involvement are similar in their change over time. In sum, both academic orientation and parental involvement differ as trajectories across different stages of high school, reinforcing the value of a dynamic approach.

My second goal was to determine whether these trends in academic orientation and parental involvement differ across curriculum tracks. In other words, track may explain some of the variation in the intercepts and slopes of these two trajectories. To examine whether academic trajectories differ across tracks, I estimated the latent growth models within each track and determined whether the mean and variance of the two latent factors differ significantly across tracks, as explained earlier (see Table 2).

Contrary to expectations, the downward trend in academic orientation seen for all students is driven by the higher-track students. Initially, college-preparatory students have the highest level of academic orientation (intercept = 2.89, p < .001), but they become less oriented to school over time (slope = -.06, p < .001). General students start out somewhat less oriented to school, but they also experience a significant decline in orientation. Remedial students begin school with the lowest level of academic orientation, but, unlike their higher-track counterparts, they remain relatively constant in their orientation over time. In all tracks, initial academic orientation is not correlated with change in orientation over time. Figure 2 presents these trajectories in graphical form.



Academk Orientation and Parental Involvement in Education 219

I 4-i w c: > w -a E > -P C: Im C: V)0

L- '-"' .:3C m co 00 00m 4-J E 0 D- rn -0 U m

> 0 -C C: 4-j 4-i -cE C: 1--i 0

C: > rn o 0 > rn v

rn 4-i C: C: W

U

m 00 0 I- co 0 C:

0 E C:

C: w 0 0)

C: m m 4-i -P -C C: C: u u

rn rn c:

4-i U U E VI w cn C:

u 0 V) C:

w 4-J

rn U :5 C: C:

-C m 4-J .? 4-J

C: m U -rU

4-J C: m C\N rn _ C: m 00 0 U 0) 0 r-L

U 0 0 4-J

L-

m u o U

4-J

C: .1-j 4-J C: 0)o r-L mC: C:

4-J u m C: 0 4-J L- 0 C: CE 4- -0 (L) u

-5 (L) 4-J .C Q-

0 u 4.J -C:

u u V) C: V) V) 00 W

m \0 0 CL L-0 u L-m CL C:

w u V) C: o

0 4-i 4-i

V) CL . 4-i oo 4-j- C: C:" u u V) V)

00 rn rn m 00 0 E 4-i V) V) VI

ui C: m

C: E 00 W = 4-i

U 0 u

4-i 4-i 11 4-- E C: z W w 4

0 0 'a C: U U Izal Q) L- - .- r-L r-L 4-J m U 0 0 0

S3 z C: w

0 W 0

u E 40-u



220 Crosnoe

Table 3. Parameter Estimates for Individual Growth Models of Five Behaviors in Parental Involvement Composite

Intercept Slope

Involvement Items Variance Mean Variance Mean

Homework All students .32*** 2.27*** .05* -.04* Remedial .42*** 2.09*** .04 .03 General .30*** 2.26*** .06 .02 College preparatory .25*** 2.40***a .03 -.1 1 ***a

Knowledge All students .19*** 2.52*** .03+ -.05** Remedial .24** 2.39***b .01 *00b General .19** 2.49*** ab .05 01b College preparatory .1 3** 2.63***a .01 -.08**a

Attend Programs All students .30*** 1 .62*** .03+ -.03* Remedial .24*** 1.51 *** .02 -.02 General .1 8** 1.56***b .01 .00 College preparatory .36*** 1. 72***a .04 -.05*

Attend Activities All students .40*** 1 .87*** .04 -.03 Remedial .37*** 1.68***c .10 -.03 General .31*** 1.91 *** .10 -.03 College preparatory .45*** 1.97***a .03 -.03

Course Selection All students .39*** 1 .99*** .08** -.07*** Remedial .47*** 1 79***b .12* -.01 b General .37*** 1.94***b .07+ -.03 College preparatory .35*** 2.1 4***a .06* -.1 2***

Note: All coefficients are unstandardized parameter estimates. Coefficients with different subscripts differ significantly across tracks, as indicated by significant changes in X2/df (p < .05) with no adjustment for multiple comparisons. The subscript a represents the strongest coefficient, with b and c indicating coefficients in descending order from the strongest. Coefficients with the same subscript or no subscripts do not differ significantly.

*** p < .001, ** p < .01, * p < .05, + p < .10.

These findings support past research, in that they demonstrate that college-preparatory students are more oriented toward school, at least at the start of high school. This finding is not surprising, given that preliminary analyses reveal that these students come from more advantaged backgrounds,

in terms of family structure and parental education, and that they are more successful in school, as evidenced by their significantly higher mean levels of standardized test scores and academic achievement (significance determined by a one-way analysis of variance, ANOVA, results not shown). Yet, these find-




Figure 2. Trajectories of Academic Orientation, by Curriculum Track

3.55

3-35 - | Remedial

, 3.1 5 - General

2.95 -.- College-Preparatory

2.75

2.55

o 2.35

O 2.15

1.95 ......l 1- T r. r l l I. .r. . r. I. ..1

lz- 0* CO 0 sw

1, tK co (b ?7 >>> ?t 3 Q0* O c*

I N. N, N, N, Ye ar

School Years

ings also suggest that these more advantaged and higher-achieving students become more disconnected from school over the course of their educational careers. On the other hand, remedial students enter school lower in academic orientation, but despite their academic problems, they do not become less oriented over time.

One caveat to these findings must be noted. The statistical significance of these observed curricular differences in academic orientation may be overestimated because multiple comparisons were conducted on the same parameter. Adjusting for multiple comparisons in structural equation modeling is complicated. In the most conservative test, the alpha level is divid- ed by the number of groups to raise the thresh- old of statistical significance for the change in X2/df. This test is restrictive, but employing it gives some perspective on the degree of curricular differences in academic orientation.

When this adjustment is made, college- preparatory students are significantly greater than remedial students in initial level, with general students not different from either. Furthermore, the difference in slopes between remedial students and those from higher tracks narrowly misses statistical significance. A comparison of the results from the nonadjusted models to the most restrictive model indicates that the apparent curricular differences in trends of academic orientation are not great.

More in line with expectations, the downward trend in parental involvement, for all students, is also driven by the parents of college-preparatory students. These parents are the most involved when their adolescents enter high school (intercept = 2.18, p < .001), but their involvement drops across their adolescents' high school careers (slope = -.08, p < .001). The general-track students have more involved parents than do the remedial students, but the parents of neither of these groups decrease their involvement across three years. By the end of high school, the involvement of parents of college-preparatory students falls between the involvement of parents of students in the general and remedial tracks. These curricular differences do not change when probability levels are adjusted for multiple comparisons. Figure 3 presents these trajectories in graphical form.

Again, I turn to the question of whether these within-track trends hold across the different types of involvement (see Table 3). For four behaviors, the college-preparatory students begin school with the most involved parents, who then become significantly less involved over time. On these same behaviors, the parents of the general and remedial students, though lower on initial involvement, do not significantly decline. Attendance at sporting and extracurricular events, which does not drop in any track, is the one excep- tion. Thus, the parents of college-preparatory



222 Crosnoe

Figure 3. Trajectories of Parental Involvement in Education, by Curriculum Track

= 2.76 | Remedial CD E 2.56 General > : CollegePreparatory > 2.36

2.16 <-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ A 16 A

:L 1.76 0

-3 1.56

1.36

1 . 1 6 ... ........ .........1 -T i.........r i .........i.........r r I i.........r T -

-T -T T .........I........I.........r 7 7 - ........I........ l I.........I.........I......... 1

111-T...

School Years

students appear to drive this trend in involvement almost across the board.

Past research reporting that the parents of higher-track students are the most involved in their adolescents' educational careers has missed an important point: This advantage of college-preparatory students may diminish or even disappear as high school progresses. Snapshots of parental involvement at only one point in time obscure such trends. In sum, trajectories of both academic orientation and parental involvement are embedded in the structure of schools.

The Foundations of Educational Trajectories In the analysis of academic orientation, the variation in intercept, but not slope, remains significant, even after differences in curriculum are accounted for. Thus, background characteristics and academic behaviors can explain only the starting points of academic orientation within tracks, not rates of change (Curran 2000). To explore predictors of individual starting points in academic orientation, I regressed the intercept latent factor on gender, ethnicity, family structure, parent education, academic achievement, and standardized test scores within each track (see Table 4).

Across tracks, three factors predict the starting level of academic orientation: African American status (compared to white), achievement level, and test scores. Being

African American predicts higher academic orientation in the two higher tracks, but group modeling reveals that these parameter estimates do not differ significantly. Test performance predicts higher orientation for general-track students only, but again, this parameter estimate is not significantly different from those for the other tracks. Finally, in all tracks, higher grades predict greater orientation. Students who are receiving better grades, according to their official transcripts, are more oriented toward school. Of course, this model cannot tease out the direction of this effect, which is unfortunate, since the relationship between achievement and feelings about school is likely to be bidirectional.

Unlike academic orientation, the variation in the intercept and slope latent factors for parental involvement remains significant even after curricular differences are taken into account. Thus, background characteristics and academic behaviors can explain differences in both the starting point and rate of change of tracked students' trajectories of perceived parental involvement (see Table 5).

Across tracks, six factors predict the starting level of parental involvement: female gender, African American and Asian American status (compared to white), intact family structure, parental education, and academic achievement. Though adjusting the probability levels for multiple comparisons of parameter estimates slightly alters some of the results in Table 5, these changes do not significantly




Table 4. Time-invariant Predictors of the Initial Level of Academic Orientation, by Curriculum Track

Remedial General College-Preparatory Predicting Intercept Factor Track Track Track

Female .09) .11 .03 (.07) (.06) (.05)

African American .21 .24*** .28** (.1 1) (.09) (.10)

Hispanic American .17 .03 .07 (.1 1) (.08) (.07)

Asian American .28 .03 .04 (.16) (.1 0) (.06)

Intact family -.06 .10 .03 (.08) (.07) (.06)

Parent education -.01 -.01 -.01 (.01) (.01) (.01)

Academic achievement .1 7*** .1 9*** .1 7*** (.04) (.04) (.03)

Test scores .00 .01 * -.00 (.00) (.00) (.00)

Note: X2/df = 50.44/54, RSMEA = .01. Unstandardized coefficients are presented with standard errors in parentheses. No coefficients differ significantly (p < .05) across tracks.

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

alter the substantive interpretation of these analyses.

Regarding gender, girls are more likely to have involved parents, controlling for other factors, in the remedial track, but they are less likely to have involved parents in the two higher tracks, especially in the general track. Breaking down involvement into its con- stituent behaviors (these results are summa- rized but not shown in tabular form) reveals a more nuanced picture of this gender difference. The lower involvement of girls' parents in the higher tracks seems to be confined to more active behaviors: helping with homework, attending parent-teacher programs and sporting or extracurricular events, and helping with course selection. Apparently, as the curricular status of boys increases, their parents take a more active role in their education.

For ethnicity, African American adolescents have more involved parents than do white adolescents in all tracks, though this relationship reaches significance only in the remedial track. For these lowest-status students, African American parents take a more active

role than do white parents. Asian Americans have more involved parents than do whites in the remedial track, but less involved parents in the two higher tracks. This difference across tracks is statistically significant. The lower involvement of the Asian American parents of higher-track students, especially college-preparatory students, cuts across almost all types of involvement. Unless their adolescents are in remedial classes, Asian American parents stand at a greater distance from the schooling process.

For family background, two factors generally predict higher parental involvement, of all types, in all three tracks: coming from an intact family and having more educated parents. Finally, the positive relationship between academic achievement and greater parental involvement characterizes college-preparatory students only. This trend is especially true for three behaviors: helping with homework, knowing how the adolescent is doing in school, and helping with course selection. These behaviors probably reflect parents' long-term educational goals for adolescents (Csikszentmihalyi and Schneider 2000)



224 Crosnoe

Table 5. Time-invariant Predictors of the Initial Level of and Rate of Change in Parental Involvement, by Curriculum Track

Remedial General College-Preparatory Factor Track Track Track

Predicting Intercept Factor Female .1 3b -1 7**a -.04ab

(.07) (.06) (.05) African American .30** .14 .16

(.12) (.09) (.10) Hispanic American .00 -.04 -.10

(.12) (.08) (.07) Asian American .21 b -.24*a -. 29***a

(.16) (.09) (.06) Intact family .24** .23*** .12*

(.08) (.10) (.06) Parent education .04** .04*** .06***

(.01) (.01) (.01) Academic achievement 07b .02ab 09**a

(.04) (.04) (.03) Test scores .00 .00 -.00

(.00) (.00) (.00)

Predicting Slope Factor Female -.00 -.01 .00

(.04) (.04) (.03) African American - .24*** a.04

(.07) (.07) (.06) Hispanic American -.1 8** -.1 1 -.07

(.07) (.06) (.05) Asian American -.13 .01 -.07

(.10) (.07) (.04) Intact family .10 -.05 .03

(.05) (.05) (.04) Parent education .00 -.01 -.00

(.01) (.01) (.01) Academic achievement -.02 -.01 -.04*

(.03) (.03) (.02) Test scores .00 .00 .00

(.00) (.00) (.01)

Note: X2/df = 29.42/27, RSMEA= .02. Unstandardized coefficients are presented with standard errors in parentheses. Coefficients with different subscripts differ significantly across tracks, as indicated by significant changes in X2/df (p < .05) with no adjustment for multiple comparisons. The subscript a represents the strongest coefficient, with b and c indicating coefficients in descending order (by strength and sign) from the strongest. Coefficients with the same subscript or no subscripts do not differ significantly.

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




Three factors predict the rate of change in parental involvement: African American or Hispanic American status (compared to white) and achievement. Being a member of a disadvantaged minority negatively predicts the rate of change in parental involvement in the remedial track only and is not related to change in the two higher tracks. This trend centers on one behavior: helping with course selection. Because the overall slope of involvement for remedial students is zero, these negative relationships indicate that remedial students of these two ethnicities have parents who become less involved in their educational careers over time. Thus, the overall tenden- cy for parents of remedial students to main- tain a constant level of involvement across three years is primarily a white phenomenon.

Academic achievement negatively predicts the rate of change in parental involvement in the college-preparatory track only. Because the overall slope of parental involvement is negative for college-preparatory students, this negative relationship indicates that achievement is related to the slope in involvement becoming even more negative (or more steeply negative). This trend appears only when the general phenomenon of parental involvement, not the individual behaviors, is examined. Overall, parents of college- preparatory students become less involved in their adolescents' educational careers over time, even more so when their adolescents are doing well in school.

In sum, the factors that contribute to the academic orientation of students who are starting high school do not really differ across tracks. At all levels of the curriculum, minority status and academic success predict greater initial orientation to school. Students in different tracks differ sharply in their rate of change in academic orientation, but these differences are related to their track locations, rather than to individual differences.

Parental involvement is more dynamic and variable. Family advantages boost parental involvement at the start of the students' high school careers for students of all tracks. Ethnicity, however, is more interesting. The parents of minority adolescents in the remedial track are especially involved, compared to the parents of white remedial students, but

they tend to distance themselves from the school as their adolescents advance, more so than their white counterparts. The achievement level of a student is related to his or her parents' involvement in the college-preparatory track. The parents of the highest-achieving students in the highest track are the most involved in the beginning, but they also demonstrate the greatest downward change in involvement over the next three years. Thus, the nature of linked lives differs by structural position.

The Interplay of Educational Trajectories These analyses have demonstrated that students in the higher curricula begin high school with the highest levels of academic orientation and the most involved parents, but also that they experience the greatest amount of downward change in both as they progress through high school. As a result, the student body becomes more similar over time in feelings about school and in parental involvement, even though the curricular structure continues to sharply differentiate achievement among students (e.g., the students still demonstrate expected significant differences in achievement at the end of high school). I now turn to the final goal of this research: to explore how the trajectories of academic orientation and parental involvement are intertwined over time.

Figure 4 presents the model that combines these two trajectories. Recall that once track is controlled, the variance in the slope of academic orientation is not significant, indicating no variability in the rate of change to be explained. Thus, the background and academic variables predict the intercept of academic orientation, the intercept of parental involvement, and the slope of parental involvement. I also correlate the two intercept factors across constructs, as well as correlat- ing the intercept and slope factor for parental involvement. Finally, the slope factor for parental involvement is regressed on the intercept factor for academic orientation. Ideally, I would also regress the slope factor of academic orientation on the intercept factor for parental involvement, but the lack of sig-



226 Crosnoe

Figure 4. Conditional Growth Model for Academic Orientation and Parental Involvement, by Curriculum Track

n Acadei JIl Acael c

Gender/\ Ethnicity/\ Faml{y Structure /\ Parenat EducationC\ Acsademic\

nificant variance in the slope factor of academic orientation renders this step moot.

In the remedial and general tracks, the intercept of academic orientation positively predicts the slope factor of parental involvement (parameter estimate = .20, p < .05 for both tracks). Since the overall slope of parental involvement for remedial and general students is zero, these positive relationships indicate that the students in these tracks who begin high school more academically oriented have parents who become more involved in their educational careers over time. This relationship does not hold for college- preparatory students (parameter estimate = .07, n.s.). The difference between the non- college-preparatory tracks and the college- preparatory track is statistically significant.

Interestingly, these findings for the overall composite do not hold for the one involvement behavior that demonstrates a significant variance in slope within tracks. In all tracks, initial academic orientation is not significantly related to changes in parental helping with course selection over time. The relationship between initial orientation and changes in parental behavior over time characterizes the general phenomenon of involvement, rather than specific types of involvement.

Thus, trajectories in academic orientation and parental involvement are intertwined over the course of high school, but only in the non-college-preparatory tracks. For these stu-

dents, parents appear more responsive to their adolescents' feelings about school. Lower-track students who value education may actively engage their parents in the educational process, and their parents may become more excited about helping them reach their goals. This relationship may be less true of college-preparatory students, for whom such involvement is more normative.

CONCLUSION

The purpose of this study was to take a new look at adolescents' academic orientation and parental involvement in education-new in the sense that I view these two phenomena as interrelated and embedded in the curricular structure of high school and as dynamic and evolving. The life course framework allowed me to bring together the individual, family, and school to create a portrait of academic pathways that are neither timeless nor removed from context.

The Value of Examining Trajectories The literature suggests that academic orientation and parental involvement are associated with track, with the highest levels found in the higher tracks, and that both may diminish over the course of high school. This study brought these threads together and con-




firmed them with a novel twist. These downward trends more often characterize the highest-status students. Over the course of high school, there is a convergence in both academic orientation and parental involvement, if not in achievement, with most of the movement coming from college-preparatory students.

Students do devalue the importance of education over time, but this general trend does not adequately reflect the experiences of all students. It is interesting that the higher- track students appear to be driving this trend. Yes, they are more academically oriented in general, which is largely related to their higher achievement, but they downgrade their feelings about school as the years pass, more so than their counterparts in the remedial track. In fact, track location offers the best explanation for differences in trajectories of orientation, as witnessed by the lack of variation of the latent slope factor within tracks.

The trajectories of students in each track probably reflect qualitatively different phenomena. Remedial students, who have the least to lose in devaluing education, do not become disenchanted with education over time. These students probably have struggled academically for years, so they may gradually give up on the idea of higher education alto- gether. If this is the case, then by the end of high school, they may experience less disso- nance between their goals and their academic status. If graduating from high school becomes a goal itself, then remedial education will not block them from this goal. The messages that schools send to different types of students may also be important in shaping students' views about education (Schneider and Stevenson 1999). Teachers and adminis- trators may put more effort into emphasizing the value of education and the benefits of being enrolled in school for remedial students, since these students are the most likely to drop out of school.

On the other hand, the higher-track students decline in academic orientation over time, even though they have a greater stake in education and the weakest rationale for disliking school. For students in the general track, this downward trend may result from their growing awareness that their high

school course work is not preparing them for higher education. Since their academic status is somewhat less clear than that of students at the two extremes of the school hierarchy, they may feel a greater disconnect between what they want to do and what they are pre- pared to do. In this sense, education has not helped them as they once believed it would (Schneider and Stevenson 1999).

For college-preparatory students, academic orientation may be an advantage at the start of school, pushing them toward higher achievement and into more challenging classes. As they near the end of successful high school careers, however, their orientation may become less important and settle to a lower, but still high, plateau. Secondary education has served its purpose, and now they may turn their sights to the next level. Ironically, their success decreases their stake in the present institution. In such a way, these students embody the contemporary view of secondary education as primarily a training ground for college admittance (Schneider and Stevenson 1999). Certainly, teachers may also feel less need to emphasize the importance of education to these students who, as evidenced by their behavior, have already internalized the message.

Parents do become less involved in education as their adolescents move through high school. Again, this trend does not occur at all curricular levels, but, instead, is driven by the college-preparatory students. Yes, these high- status students have the most involved parents, but, unlike other students, their parents tend to pull out of their educational careers as the years pass. This trend cuts across behaviors: helping, participation, and staying knowledgeable about academic progress.

This finding illustrates an important paradox found in past research. Parental involvement may improve performance, but improved performance may obviate the need for parental involvement. Though achievement levels may vary within the college- preparatory track, the most successful students are generally moving toward higher education. The involvement of parents (in keeping abreast of their adolescents' progress in school and helping with course selection, in particular) is probably crucial to steering



228 Crosnoe

them onto the right path, but as the years pass, these students have less need for their parents' help.

This trend illustrates the gradual granting of autonomy to adolescents that is the hall- mark of authoritative parenting. As further evidence that this is the case, the parents of the highest achievers in the highest track are the most likely to exhibit this downward trend. Over time, the success of these adolescents enables their parents to give them a wider berth. This freedom does not equal dis- engagement. Like their adolescents, these parents may have turned their attention to the next level.

Variations in Educational Trajectories As with many educational issues, these trends differ by ethnicity. First, academic orientation tends to be stronger among African American students, which is consistent with past research. Mickelson (1990) argued that the greater value that African American students place on education results from their abstract attitudes about the general importance of education, rather than concrete attitudes about how education has helped the people whom they know. The measure in this study is more closely akin to Mickelson's notion of abstract attitudes. This characteristic of African American students may be stronger in the nonremedial tracks. Because African American students tend to cluster at the bot- tom of the curriculum, those who move up the hierarchy are likely to be those who strongly believe that education is the key to the future. Despite these initial differences, African American students do not differ from other groups in their trajectories of academic orientation over time.

Second, the general trend of parental involvement decreasing more for higher-status, higher-achieving students also may not hold for minority families. The parents of African American students in the remedial track, who are the most at risk, start out higher than do the parents of white students in this track. This ethnic gap does not occur in other tracks. Apparently, the parents of more troubled students do get more involved. Yet,

African American and Hispanic American parents of remedial students tend to reduce their involvement over time at a greater rate than do white parents. This trend seems to involve one behavior in particular, helping with course selection, and could occur for a number of reasons: minority parents feeling pow- erless as the years pass, minority students rejecting their parents' attempts to remain involved as they continue to struggle, or schools being less receptive to the involvement of minority parents.

Avenues of Future Research Because so little research has focused on academic trajectories or attempted to place academic orientation or parental involvement in the context of the life course, this study is necessarily preliminary. The next steps in research should consider three issues. First, the role of academic achievement needs to be explored. I was able to account for initial achievement and ability, but I did not investi- gate the contemporaneous effects of achievement at different levels. Students in this sample did not show a significant change in achievement over time, but this finding does not rule out time-varying effects.

Second, other academic trajectories, such as participation in extracurricular activities, may interweave with psychological orientations to school and parental orientations to adolescents' education. Studying multiple trajectories simultaneously requires more power than the current data allow. Future projects may take advantage of nationally representative data sets, especially those that include information from school transcripts (e.g., the National Educational Longitudinal Study). Such national data sets often track dropouts, which could minimize one flaw of this school-based study: the attrition of adolescents who leave school or are absent from school during data collection. This problem may lead to an underestimation of curricular differences in educational experiences, since lower-track students are more likely to miss or leave school. For these reasons, future studies need to examine less biased samples.

Third, we need to know how school structure shapes these processes. For instance, eth-




nic composition may influence how students feel about school, with the most positive feelings coming from those who are in schools with a large representation of their own ethnicity (Johnson et al. forthcoming). At the same time, ethnic composition may influence parental involvement, with minority parents feeling less comfortable participating in predominantly white schools (Kerbow and Bernhardt 1 993). Curricular structure (e.g., the size and composition of tracks) may also shape the experiences of students and their parents (Hallinan 1996; Useem 1992).

Such factors are relevant to this study, given the diversity of the schools in the sample. Unfortunately, the limited power of this special sample (with about 100 students per school) makes it difficult to explore school differences. Some basic analyses are possible: unconditional models for academic orientation and parental involvement within schools (8 of these 12 models have adequate model fit). The results of these analyses generally support and never contradict the overall findings of this study. Still, much more can be done in this area with other, larger data sets if not this one. One important avenue of future research is to examine how structural fea- tures, such as ethnic composition, academic climate, and curricular differentiation, moderate academic and social trajectories as well as ethnic differences in such trajectories.

Both academic orientation and parental involvement are embedded in school structure, in the form of curriculum tracking, and social structure, in the form of ethnicity and SES. Moreover, both are fluid, rather than static, attributes of the individual or family. For these reasons, both illustrate life course principles. The relationship between students' academic development and their parents' involvement reflects the interdependence of individuals, especially the linked lives of family members. The parent-adolescent relationship is not uniform by any means, but depends on the characteristics of adolescents, their parents, and the circumstances in which they all live. The relationship of curricular tracking to both factors indicates the social embeddedness of lives and relationships. Finally, the fluidity of both across the high school years shows the importance of tempo-

rality. Taking snapshots of academic behavior or family processes at any point of time is informative, but we add to our knowledge when we examine continuity and change over time.

As in other stages of the life course, adolescents' lives are connected to others, grounded in social institutions and larger structural forces, and subject to change and evolution. Education is a key factor in this stage. To gain a better understanding of the development of young people, we must study their educational development. To gain a better understanding of their educational development, we must study it within the complexity of adolescents' lives.

REFERENCES

Bennett, Kathleen, and Margaret LeCompte. 1990. The Way Schools Work. New York: Longman.

Connell, James Patrick, Margaret Beale-Spencer, and J. Lawrence Aber. 1994. "Educational Risk and Resilience in African-American Youth: Context, Self, Action, and Outcomes in School." Child Development 65:493-506.

Crosnoe, Robert, Kristan Erickson, and Sanford Dornbusch. Forthcoming. "Protective Functions of Family Relationships and School Factors on the Deviant Behavior of Adolescent Boys and Girls: Reducing the Impact of Risky Friendships." Youth and Society.

Csikszentmihalyi, Mihaly, and Barbara Schneider. 2000. Becoming Adult: How Teenagers Prepare for the World of Work. New York: Basic Books.

Curran, Patrick J. 2000. "A Latent Curve Framework for Studying Developmental Trajectories of Adolescent Substance Use." Pp. 1-42 in Multivariate Applications in Substance Use Research, edited by J. Rose, Laurie Chassin, Clark Presson, and Steven J. Sherman. Hillsdale, NJ: Lawrence Erlbaum.

Dornbusch, Sanford, Kristan Glasgow, and In-Chun Lin. 1996. "The Social Structure of Schooling." Annual Review of Psychology 47:401-29.

Elder, Glen H., Jr. 1998. "Life Course and Human Development." Pp. 939-91 in Handbook of Child Psychology, edited by William Damon. New York: John Wiley & Sons.

Erickson, Kristan, Robert Crosnoe, and Sanford M. Dornbusch. 2000. "A Social Process Model of Adolescent Deviance: Combining Social Control and Differential Association



230 Crosnoe

Perspectives." Journal of Youth and Adolescence 16:395-425.

Hallinan, Maureen T. 1996. "Track Mobility in Secondary School." Social Forces 74: 983-1002.

Johnson, Monica K., Robert Crosnoe, and Glen H. Elder, Jr. forthcoming. "Student Attachment and Academic Engagement: The Role of Ethnicity." Sociology of Education.

Kerbow, David, and Annette Bernhardt. 1993. "Parental Involvement in the School: The Context of Minority Involvement." Pp. 1 15-46 in Parents, their Children, and Schools, edited by Barbara Schneider and James S. Coleman. Boulder, CO: Westview Press.

McGrath Daniel J., Raymond R. Swisher, Glen H. Elder, Jr., and Rand D. Conger. Forthcoming. "Breaking New Ground: Diverse Routes to College in Rural America." Rural Sociology.

McNeal, Ralph B. 1999. "Parent Involvement as Social Capital: Differential Effectiveness on Science Achievement, Truancy, and Dropping Out." Social Forces 78:11 7-44.

Mickelson, Roslyn Arlin. 1990. "The Attitude- Achievement Paradox among Black Adolescents." Sociology of Education 63:44-61.

Moody, James. 1997. "The Contextual Determinants of School Attachment." Unpublished master's thesis, Department of Sociology, University of North Carolina at Chapel Hill.

Muller, Chandra. 1995. "Maternal Employment, Parent Involvement, and Mathematics Achievement Among Adolescents." Journal of Marriage and the Family 5 7:85-1 00. 1998. "Gender Differences in Parental

Involvement and Adolescents' Mathematics Achievement." Sociology of Education 71:336-56.

Muthen, Linda K., and Bengt 0. Muthen. 1999. Mplus User's Guide. Los Angeles: Author.

Newmann, Fred, Gary Wehlage, and Susie Lamborn. 1992. "The Significance and Sources of Student Engagement." Pp. 11-39 in Student Engagement and Achievement in American Secondary Schools, edited by Fred Newmann. New York: Teacher's College Press.

Oakes, Jeannie. 1985. Keeping Track. New Haven, CT: Yale University Press. 1995. "Two Cities' Tracking and Within School Segregation." Teachers College Record 96:681-90.

Sanders, Mavis G. 1998. "The Effect of School, Family, and Community Support on the Academic Achievement of African-American Adolescents." Urban Education 33:385-409.

Schneider, Barbara, and David Stevenson. 1999. The Ambitious Generation: America's Teenagers, Motivated but Directionless. New Haven, CT: Yale University Press.

Steinberg, Laurence, Bradford Brown, and Sanford Dornbusch. 1996. Beyond the Classroom: Why School Reform Has Failed and What Parents Need to Do. New York: Simon & Schuster.

Steinberg, Laurence, Susie Lamborn, Sanford Dornbusch, and Nancy Darling. 1992. "Impact of Parenting Practices on Adolescent Achievement: Authoritative Parenting, School Involvement, and Encouragement to Succeed." Child Development 63:1266-81.

Stevenson, David, and David Baker. 1987. "The Family-School Relation and the Child's School Performance." Child Development 58:1 348-5 7.

Useem, Elizabeth. 1992. "Student Selection into Course Sequence in Mathematics: The Impact of Parental Involvement and School Policies." Journal of Research on Adolescence 1:231-50.

Robert Crosnoe, Ph.D., is Assistant Professor, Department of Sociology, University of Texas at Austin. His main fields of interest are the life course and human development, education, and social psychology. He is currently investigating issues of risk and resilience in education-the social resources (e.g., personal relationships) that allow at-risk students (e.g., ethnic-minority and eco- nomically disadvantaged students) to succeed in school-for example, how social support from teachers promotes educational resilience among African American and Hispanic American students.

Data collection was funded by the Carnegie Corporation of New York and the Spencer Foundation. The author also acknowledges funding from the National Institute of Mental Health (Grant MH 57549) and the National Institute of Child Health and Human Development (PO 1 -HD3 192 1A) and the assistance of Sanford M. Dornbusch, Glen H. Elder, Jr., and Monica K. Johnson. Address all cor- respondence to Dr. Robert Crosnoe, Department of Sociology, University of Texas at Austin, Burdine Hall 336, Austin, Texas 78712; e-mail: [email protected].



academic orientation and parental involvement in education during high school

Documents