The role of the school library in college access and choice

LIBINF-00865; No. of pages: 8; 4C: Library & Information Science Research xxx (2016) xxx–xxx

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Library & Information Science Research

The role of the school library in college access and choice Enyu Zhou a, Denice Adkins b,⁎ a b

Department of Educational Leadership and Policy Analysis, University of Missouri, 202 Hill Hall, Columbia, MO 65211, United States School of Information Science & Learning Technologies, University of Missouri, 303 Townsend Hall, Columbia, MO 65211, United States

1. Introduction Higher education researchers have developed several models to explain how students choose whether to attend college Past research on college access has been theoretically grounded in economic and sociological arguments, but both theoretical models acknowledge the importance of information. Human capital investment theory explains college choice by assuming that people are rational actors who decide whether and where to attend college, with the intention of maximizing their expected benefits and minimizing their anticipated costs. These rational actors are expected to make the best decision given the information they have; however, “differential access to information” affects their abilities to make the best decision for themselves (Perna, 2006, p. 108). Theories of social and cultural capital suggest that the predisposition to attend college is mediated through social networks that support college attendance and access to cultural knowledge that is derived from class or cultural statuses. Structural barriers make it harder for people outside the designated social network to access resources that support college attendance, including information resources and supports (Perna, 2006, p.112). Most research on college access has focused on the topics of college aspiration (the motive to attend college at all) and college choice (deciding which college to attend), but not on the college information search process. When research does focus on the college search process, it does not look specifically on searching for information about colleges. Search is operationalized “in terms of the sources of college-related information that students and parents use… and/or the number of colleges that students consider or to which they apply” (Perna, 2006, p.102). While information use may be defined as information search (Kari, 2010), this operationalization of information use is dependent upon information-seeking, and so ignores the information seeking process and the sources of information available to the student.

that increased information about college will help students make better decisions underpins even the United States Department of Education's decision to develop a college ratings system (U.S. Department of Education, 2015). Theoretical models of college access and choice present an economic information problem, but researchers in this area ignore a fundamental information resource available to high school students: the school library. The school library is a specific venue where students might access multiple sources of college information, but no studies explore whether students actually use those sources. This study attempts to remedy that gap in scholarship. What role does the high school library play in college access and choice? Specifically, does the school library serve as an information resource for collegebound students? The library and information science (LIS) literature presents the role of the school library as being primarily focused on teaching information literacy skills, providing resources to support the school's curriculum, and providing leisure resources for students' entertainment purposes. High school libraries are documented as providing study and leisure materials. Considering the provision of study and leisure materials, which are expected services of a high school library, is there a difference between a high school library's role in providing college information and its role in providing general study and leisure materials and services? In an ideal world, poor and rich students alike would have access to school libraries with equivalent resources and services. In the real world, poor and underrepresented students have fewer school library resources and services in their school libraries than rich students do. If the high school library does play a role in college access and choice, does that role differ based on students' ethnicity, race, or socioeconomic status? A better understanding of the role of school libraries in this process would be beneficial to school librarians, school administrators, and above all, high school students. 3. Literature review

2. Problem statement Both economic and sociological approaches assume that information about college is present, but that it is not equally accessible to all students, creating an information asymmetry in which some students have better access to college information than others. The premise ⁎ Corresponding author. E-mail address: [email protected] (D. Adkins).

Educational policy and LIS literature take different perspectives on college access and choice and the role of high school personnel in helping students make decisions about college. LIS literature focuses on the role of school librarians in preparing students for the information tasks they will face in college, specifically by ensuring they have the specific information literacy skills needed for college-level coursework. Only a few articles acknowledge that students' needs will differ based on their socioeconomic or racial/ethnic status.

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Please cite this article as: Zhou, E., & Adkins, D., The role of the school library in college access and choice, Library & Information Science Research (2016), http://dx.doi.org/10.1016/j.lisr.2016.11.009

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Educational policy literature posits college access and choice as an economic information problem. Going to college presents an immediate cost and an uncertain payoff, and those who have fewer material resources can afford less to invest those resources in an uncertain venture. Students have limited information about college options and the quality of those options (i.e., graduation rate and post-graduation employment rates). High socioeconomic status (SES) students have more access to information about college quality than low SES students, through their social capital (e.g., asking for advice from other graduates) and their financial capital (e.g., ability to visit several colleges). Low SES and aspiring first-generation college students are more at risk. For instance they often have to take out large student loans to pay for unaccredited or less well regarded degree programs. At the same time, few educational policy studies focus on the skills students need in order to succeed in college or how those skills are transmitted through the formal institution of schooling. 3.1. College access and choice Dolinsky (2010) posits a three-stage process, “predisposition, search, and choice,” in which during the search stage students “acquire information about different colleges” (p. 762). Each stage in the college access and choice process is affected by both internal and external factors. Internal factors include background characteristics and academic preparation. External factors include high school characteristics, information seeking resources, public policy, and college characteristics (Plank & Jordan, 2001, p. 953). High school GPA, class ranking, and standardized test scores also relate to college application (Long & Riley, 2007; Perna, 2006). Students from low-income families are less likely to be well prepared for college. They are less likely to take the ACT/ SAT and more likely to have a lower high school GPA (Advisory Committee on Student Financial Assistance, 2010). The phenomenon of college access and choice is recognized as hierarchical and layered. Perna's (2006) conceptual framework of college access uses a four-layer design made up of 1) habitus, that is, “demographic characteristics … as well as cultural and social capital” (p. 117), 2) school and community context, 3) higher education context, and 4) social, economic, and policy context. All of these elements contribute to the college access and choice decision, which is itself predicated on the student's predisposition towards higher education, supply of resources, expected benefits, and expected costs. Nuñez and Kim (2012) developed a multicontextual model that uses characteristics of the students, their schools, and their state of residence to demonstrate factors that affect Latino college access. These layered models indicate that some factors which influence college access are beyond the control of aspiring college students and their families. For instance, poor state education funding has an impact on students' ability to attend college. However, an individual 17-yearold high school student has relatively little control over state education funding, as those decisions are made by legislators and reinforced or challenged by adult voters. Information alone is not sufficient to influence the college-going decision of low-income or racially diverse students. Beyond mere knowledge of an option, students need to trust that the option is available to them, trust the people who are promoting the option, and have support throughout the college application process. Hands-on support and the creation of a support network help students navigate the college process, such as when tax preparers assist students and families in filling out the Federal Application for Student Financial Aid (Nuñez & Kim, 2012, p. 252), or when empowerment agents defy schools' organizational norms to provide low-income students with individualized support (Stanton-Salazar, 2011). 3.2. College information sought and information sources Dolinsky (2010) asked current college freshmen about college information in order to determine whether institutions' marketing messages

needed to change. Information factors noted by Dolinsky included college catalogs, campus visits, guidance counselors, friends, and students enrolled in college. Information sought included academic quality, majors and programs of study, tuition costs, location, financial aid, and career prospects. Men were more interested than women in knowing about college athletics, while women were interested in campus safety. Tsai (2012) looked at first-generation college students during their first year, examining their information source preferences when selecting courses and determining majors or programs of study. These first-year students preferred consulting information sources over human sources, and used course catalogs, university or department web resources, and personal collections. The information needs of these first-year college students are likely to be shared to some degree by high school students seeking information about college. Both these studies recognized that college information needs are multifaceted, and students require not only information but also advice and moral support. Literature about student information seeking shows that low-income students have less knowledge of the college application process and general college information than wealthier students (Long & Riley, 2007). Differences in knowledge of college information are exacerbated by the need for additional support for low-income and firstgeneration students (Nuñez & Kim, 2012, pp. 251–252). 3.3. High school to college transition and college choice Research on the role of high school libraries in facilitating college access and college transition has not focused on libraries' provision of college information to high school students in the college access and choice process. Instead, LIS research has been focused on information literacy training, addressing the concern that high school students are not prepared for college-level research and study. Some studies use college requirements to determine high school curricula. Oakleaf and Owen (2010) describe using a review of first-year college syllabi to determine what information literacy skills are necessary for graduating high school seniors. The purpose was to ease students' college transition by increasing their command of higher-level information skills. Smith, Given, Julien, Ouellette, and DeLong (2013) reviewed high school students' performance on an academic-level information literacy test in relation to Canadian university information literacy requirements. Other studies examined high school information literacy curricula to determine whether new college freshmen are likely to have specific information literacy skills (Islam & Murno, 2006; Nix, Hageman, & Kragness, 2011). Julien and Barker (2009) examined the development of high school students' information literacy skills and found that schools, teachers and curricula play important roles in providing information literacy instruction. Fabbi (2015) looked at first-year students' scores on a standardized test in relation to student variables (race, gender, GPA, and number of honors courses taken), and found that the main predictor of high test scores was honors courses. In addition, the information literacy skills students learned in high school have been shown to have a positive impact on high school college transition and first-year college experience (Fitzgerald, 2004). Some information literacy projects have acknowledged the broader information and support needs of students in the high school to college transition. Martin, Garcia, and McPhee (2012) detailed a partnership between a highly diverse, low SES high school and an academic library. The academic librarians provided information literacy training and helped students with major research projects. This partnership has also had the effect of fostering relationships between students and university personnel and allowing students to become familiar with the university environment. Regalado (2003) described a project at Brooklyn College designed to provide underprepared first-year students with foundational knowledge about the library and information literacy (p. 90). While the information literacy element was intended to help students develop information literacy skills, another goal of the larger program was to let students know “where to go for student supports

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E. Zhou, D. Adkins / Library & Information Science Research xxx (2016) xxx–xxx

(i.e., tutoring, financial aid and health services)” (p. 91). Regalado noted that first-year students do not succeed by competence alone, but also need confidence in their abilities to use the college library, and connections with other people who can encourage that use. These findings correspond with Julien's (1999) finding that high school students transitioning into the job market lacked confidence in their abilities to seek career-related information and did not feel they could find trustworthy information sources. Library resources and staffing have been shown to influence students' information literacy skills, at both the high school and college levels. Having access to a high school librarian positively related to student achievement and college success (Smalley, 2004). Hutchison's (1982) study on the impact of library instruction on 269 tenth grade students' library use showed that increasing library resources did not increase usage if library instruction was not provided. Kuh and Gonyea (2003) found that academic libraries increased student information literacy and promoted student learning. Using different library resources and services has been found to be positively related to academic performance (Wells, 1995; Whitmire, 2002) and critical thinking (Whitmire, 1998). Currently, no research demonstrates the relationship between school library resources and library use for seeking college information. 4. Conceptual framework Given the importance of seeking college information during the high school years for access to college afterward, an obvious question is what resources school libraries have to support college information seeking, and whether students themselves are inclined to view the library as a source for college information. The conceptual framework (Fig. 1) explains the key factors involved in using high school libraries to pursue information about colleges. This framework privileges information seeking and information access as the main variables of interest. The conceptual framework was informed by three sets of literature: (1) K-16 literature about the relationship between library resources and library use during students' elementary, secondary, and college years; (2) higher education literature about student characteristics, college experience, and library use; and (3) literature about college access. The conceptual framework is broken into four areas representing student and library variables. First, student background characteristics, or demographics, allow researchers to look at whether additional circumstances might affect the students' abilities to gain access to college. Second, school experiences are factors over which the student has some degree of control. Third, library resources indicate whether, and to what degree, the school provides information resources that can be used to benefit students. Fourth, school library services indicate the school's commitment to the library as a student resource, manifested in funding of librarians, staff, and systems. Each of these factors

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combines to influence a student's behavior in terms of their use of the school library for college information. Looking at students' library use for study and leisure provides a measure against which to compare college information seeking. 5. Method 5.1. Data sources and variables The Education longitudinal study of 2002 (ELS:2002) data set from the National Center for Education Statistics (2015) follows a nationally representative sample of students who were in 10th grade in 2002. Three follow-ups on this cohort took place in 2004 when they were in 12th grade, in 2006, and in 2012. The intention of ELS:2002 was to provide a view of students' post-high school trajectories into college, the work force, or other areas, and to identify patterns in college access. ELS:2002 provides multilevel information on the high school student cohort of 2002. The ELS:2002 sample includes 16,197 students who participated in the first follow-up survey and the school library survey. These students were randomly selected from the high school cohort of 2002 across the United States. The dependent variables are (1) library use for college information, (2) library use for study, and (3) library use for leisure. Library use for college information is measured by a dichotomous variable indicating whether a student has used the school library to get college information. If a student “has gone to a source for college information”, it is coded as 1, and if a student “has not gone to a source”, as 0. The library use measures were reduced from nine variables to two factor scales through principal component factor analysis with promax rotation. One factor scale measures library use for study, and includes use of school library for in-school projects, for assignments, for research papers, for Internet access, and for homework. The other factor scale measures library use for leisure time, and includes use of school libraries for leisure reading, including books, magazines, and newspapers, and for interests outside of school. These variables were measured to determine whether college information seeking was representative of other types of library use. Table 1 shows the variable definitions and values. Three independent variables are (1) background characteristics, (2) high school experience, and (3) school library resources and services. Background characteristics include gender, race/ethnicity, family income, and parents' education. High school experience measures included plans to take SAT or ACT tests, attendance at a college preparatory program at any time, overall GPA, hours spent on reading, and hours spent on assignments per week. The library resource factor includes availability of college/career databases, academic subject databases, and educational software. The library service factor includes the number of full-time certified librarians, number of full-time library media resource center staff, whether a library has automated book circulation

Fig. 1. Conceptual framework to explain effects of library use for college information, study, and leisure.

Please cite this article as: Zhou, E., & Adkins, D., The role of the school library in college access and choice, Library & Information Science Research (2016), http://dx.doi.org/10.1016/j.lisr.2016.11.009

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system, circulation per week, and the statistics of students use of the library per week.

Table 1 List of variables. Variable Dependent variable Library use for college information Has gone to school library for college information Library use for study Use of school library for assignments Use of school library for in-school projects Use of school library for homework Use of school library for research papers Use of school library for Internet access Library use for leisure Use of school library for leisure reading Use of school library to read magazines/newspapers Use of school library to read books for fun Use of school library for interests outside of school Independent variable Demographic variables Gender Race Socioeconomic status

Parents' highest level of education Academic experience Plans to take SAT or ACT Ever in program to help prepare for college GPA for all courses taken in the 9th–12th grades Hours/week spent reading outside of school Hours/week spent on homework Library resources College/career databases available Academic subject databases available Educational software available Library Services # of full-time state-certified librarians # of full-time library media resource center staff Library has automated book circulation system Total circulation per week # of students use library per week

Value

Name

5.2. Procedures Yes = 1, No 0

F1S48K

Never = 1, Rarely = 2,

F1S29A

Sometimes = 3, Often = 4

F1S29B F1S29C F1S29D F1S29I

Never = 1, Rarely = 2,

F1S29E

Sometimes = 3, Often = 4

F1S29F

F1S29G F1S29H

Male = 1, Female = 0 Asian = 1, African American = 2, Hispanic = 3, Other = 4, White = 5 Lowest quartile = 1, Second quartile = 2, Third quartile = 3, Highest quartile = 4 Attend some college = 1, Have not attended college = 0

BYS14 BYRACE BYSES1QU

BYPARED

Yes = 1, No = 0 Yes = 1, No = 0

BYS55B BYS33L

Scale

F1RGPP2

Scale

F1S33

Scale

F1S31

Yes =1, No =0

BYL12G

Yes =1, No =0

BYL12H

Yes =1, No =0

BYL12J

Scale

BYL06AB

Scale

F1A30

Yes =1, No =0

BYL11JA

Yes =1, No =0

BYL25

Fewer than 100 = 1, 100–249 = 2, 250–499 = 3, 500–999 = 4, 1000 or more =5

BYL24

Note: Source: National Center for Educational Statistics (2015).

School library resources and services measure were reduced from eight library performance variables through principal component factor analysis with promax rotation. School library resources and services are highly correlated – a wealthy school can afford more of both, while a poor school can afford fewer of both. Oblique rotation was used to allow for correlation between factors. Table 2 shows the principal component analysis for Factors 1 and 2 in matrices. Table 3 shows the Principal Component Analysis for Factors 3 and 4 for the pattern and structure matrices. The rotation method promax was used. The Eigenvalue N 1 rule and Bartlett's chi-square test determined how many factors to retain. Bartlett's chi-square test was statistically significant, and the null hypothesis that the correlation matrix is an identity matrix was rejected. Coefficients of the pattern matrix N 00.40 were retained for that factor. The coefficients of the structure matrix (above 0.40) were checked to confirm the selection of an item (Henson & Roberts, 2006, p. 7). After the reduction, the factor scores were saved and used. After data preparation, descriptive statistics were run to assess high school students' library use for college information, study, and leisure across student demographics, student intentions, and school provision of college information. Logistic multiple regression models were then used to examine the relationship between library resources and high school students' library use while controlling for students' background characteristics and school experience. Students' use of the school library for college information is a dichotomous variable – either they have used it or they have not. Logistic regression was used to accommodate the dichotomous nature of that variable. While ordinary least squares regression can predict the degree to which an independent variable increases the value of a continuous dependent variable like grade point average, logistic regression predicts the odds that the independent variable will change a dichotomous dependent variable like such as whether or not one is admitted to college. 6. Findings Table 4 presents a descriptive analysis of means and standard deviations of high school students' background characteristics and school experience. The sample was 57% White; 15% Hispanic; 13% Black; 10% Asian; and 1% American Indian and unknown race. Over half of the students indicated their parents had some college experience, and almost three-quarters intended to take the SAT or ACT, but fewer than a quarter were involved in college preparatory programs. Students reported spending three hours per week reading and four hours per week on homework, but both of these figures had fairly large standard deviations. The same was true of GPA and family income: both were above the median, but the standard deviation suggests that not all students were doing so well. Library use, service, and resources were normalized so that the mean was zero and the standard deviation was 1.0. Table 5 shows the distribution of the 2002 high school student cohort by library use across gender and race/ethnicity. The majority of the high school students in the sample did not use the school library for college information. Slightly more female than male students had used the library for college information, but this finding was in exact proportion to their share of the sample. Black students were more likely to go to the school library for college information, and White students were less likely to do so. Hispanic female students were more likely to use the school library for college information than were Hispanic male students, and the same was found for American Indian, Asian, and multiracial female students and their male counterparts. These results suggest that students were not necessarily making the connection between the library and the provision of college information.

Please cite this article as: Zhou, E., & Adkins, D., The role of the school library in college access and choice, Library & Information Science Research (2016), http://dx.doi.org/10.1016/j.lisr.2016.11.009

E. Zhou, D. Adkins / Library & Information Science Research xxx (2016) xxx–xxx

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Table 2 Pattern/structure matrix rotated to the promax criterion for dependent variables. Pattern matrix

Structure matrix

Variables

Factor 1: For study

Factor 2: For leisure

Factor 1: For study

Factor 2: For leisure

h2

Library use for assignments Library use for in-school projects Library use for homework Library use for research papers Library use leisure reading Library use to read books for fun Library use for interests outside of school Library use for Internet access Library use to read magazines/newspapers % of variance

0.84 0.90 0.52 0.85 −0.03 −0.11 0.13 0.67 0.02 48.47

−0.01 −0.11 0.31 −0.07 0.88 0.90 0.71 0.12 0.79 16.66

0.84 0.85 0.67 0.82 0.38 0.31 0.46 0.72 0.39 48.47

0.39 0.32 0.56 0.33 0.86 0.85 0.77 0.43 0.80 16.66

0.70 0.73 0.52 0.67 0.74 0.73 0.60 0.54 0.63 65.13

Notes. Extraction method is principal component analysis. The eigenvalue of the third, unretained, factor was 0.65. h2 = communality coefficient. Coefficients N 0.40 are in boldface.

Table 6 reports the results of logistic regression models analyzing the relations between library resources and library use for college information. Model 1 looks just at background characteristics as predictors of library use for college information. In Model 1, Black or American Indian students utilized the library for college information, while increased family income was associated with less library use to search college information. Model 2 adds students' school experiences, which demonstrate their college predisposition. In Model 2, higher GPA is associated with less library use for college information; however, plans to take the SAT or ACT, college prep programs, and hours per week spent reading and doing homework are all positively associated with library use for college information. Additionally, the three significant factors from Model 1 are still significant in Model 2. In Model 3, increased library services and resources are not significant factors in predicting students' use of the school library for college information. However, when those factors are added into the equation, students' plans to take the SAT or ACT become insignificant predictors of school library use for college information, as does whether a student has American Indian heritage. Tables 7 and 8 examine the likelihood of school library use for study and leisure, based on background characteristics, school experiences that show college predisposition, and library resources and services. These tables are used to compare the factors that make students more likely to use school libraries for college information and those that make them more likely to use school libraries for study and leisure. Table 7 focuses on library use for study. Model 1, with background characteristics only, shows that being male or having a higher family income has a significant negative influence on the odds of library use for study, while being Black has a positive influence on those odds. Model 2 adds school experience factors. In Model 2, higher GPA has a negative influence on the odds of library use for study, while hours spent on reading and homework, college prep classes, and plans to take the SAT or ACT all have a positive influence on the odds. In Model 2, being

male, Asian, or Hispanic has a negative influence on the odds, but when school experiences are added to the equation, increased family income and increased family education also have negative effects on library use for study. Library services and resources are added to Model 3, and the quality of library services has a positive effect on the odds of students using the library for study. All significant variables from Model 2 are still significant in Model 3 except for being Hispanic. Increased library services are positively associated with library use for study. School libraries that have more full-time library media resource center staff, more fulltime certified librarians, automated book circulation systems, and greater weekly circulation also have more library use for study. Table 8 reports the results of regression models, analyzing the relation between library resources and library use for leisure. In Model 1, being male, American Indian, Asian, Black, or Hispanic all positively influence school library use for leisure, while increased family income has a negative effect. Model 2 shows that hours spent on reading, hours spent on homework, and being in a college prep program all positively affect library use for leisure, but having a high GPA negatively affects those odds. After adding library services and resources in Model 3, increased library services have a negative effect on the likelihood of school library use for leisure. Hours spent in reading, being in a college prep program, being Asian, American Indian, and male all have positive influence on school library use for leisure. However, increased family income and increased GPA have a negative influence. In Model 3, being Black or Hispanic are no longer significant predictors of t using a library for leisure. 7. Discussion The research question under investigation was whether the high school library plays a role in college choice and access, and whether that role might differ by students' race, ethnicity, or socioeconomic

Table 3 Pattern/structure matrix rotated to the promax criterion for independent variables. Pattern matrix

Structure matrix

Variables

Factor 3: Library services

Factor 4: Library resources

Factor 3: Library services

Factor 4: Library resources

h2

College/career databases available Academic subject databases available Educational software available # of full-time state-certified librarians # of full-time library media resource center staff Library has automated book circulation system Total circulation per week # of students use library per week % of variance

−0.12 0.12 −0.05 0.61 0.78 0.47 0.48 0.62 25.39

0.80 0.66 0.61 0.03 0.01 −0.07 −0.18 0.15 16.44

0.05 0.26 0.08 0.62 0.78 0.45 0.44 0.66 25.39

0.77 0.69 0.60 0.16 0.18 0.03 −0.07 0.29 16.44

0.61 0.49 0.37 0.38 0.61 0.21 0.22 0.45 41.82

Notes. Extraction method is principal component analysis. The eigenvalue of the third, unretained, factor was 0.98. h2 = communality coefficient. Coefficients N 0.40 are in boldface.

Please cite this article as: Zhou, E., & Adkins, D., The role of the school library in college access and choice, Library & Information Science Research (2016), http://dx.doi.org/10.1016/j.lisr.2016.11.009

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Table 4 Descriptive statistics.

Male American Indian and other race Asian Black Hispanic White Parents attend some college Family income GPA Plans to take SAT/ACT Ever in program to help prepare for college Hours/week spent on reading Hours/week spent on homework Library use for college information Factor 1: Library use for study Factor 2: Library use for leisure Factor 3: Library services Factor 4: Library resources

N

Min.

Max.

M

SD

15,370 15,244 15,244 15,244 15,244 15,244 15,321 16,197 14,796 13,771 14,311 14,863 13,631 9702 12,741 12,741 8838 8838

0 0 0 0 0 0 0 0 0 0 0 1 1 0 −2.2 −1.2 −3.4 −3.2

1 1 1 1 1 1 1 12 6 1 1 8 9 1 1.9 3.1 3.2 1.2

0.50 0.06 0.10 0.13 0.15 0.57 0.63 8.06 3.91 0.71 0.22 3.07 4.27 0.13 0.00 0.00 0.00 0.00

0.50 0.23 0.29 0.34 0.35 0.50 0.48 2.43 1.54 0.45 0.42 1.80 1.79 0.33 1.00 1.00 1.00 1.00

status. In other words, does the school library help ameliorate uneven access to college information based upon different economic status? No overarching relationship was found between library resources and services and library use for college information. However, black students and students with lower parental income were more likely to use the school library for college information than their peers. This contrasts with school library use for study, which increased in students with lower parental education and income, students who planned to take the SAT or ACT, students who had enrolled in college preparatory programs, and students who spent more hours on reading and homework. Male, Asian, and American Indian students, those with lower family income, those in a college preparatory program, and who spent more time on reading and homework were more likely to use the school library for leisure.

Table 5 Library use for college information by gender and race/ethnicity. Has gone to school library for college information No

Gender Male Female Race/ethnicity American Indian and other race Asian Black Hispanic White Race with gender American Indian and other race Male Female Asian Male Female Black Male Female Hispanic Male Female White Male Female

Yes

N

%

N

%

4054 4398

48 52

587 639

48 52

413 850 913 1053 5221

5 10 11 12 62

74 133 208 152 658

6 11 17 12 54

206 207

50 50

34 40

46 54

434 416

51 49

61 72

46 54

405 508

44 56

97 111

47 53

491 249

66 34

77 75

51 49

2516 2705

48 52

318 340

48 52

Note: Source: National Center for Educational Statistics (2015).

Findings demonstrate the relationships between school library resources and services and high school students' library use for different purposes: for seeking college information, for study and for leisure. There was a positive relationship between library services and library use for study that supported previous research suggesting that libraries with more staff who had greater availability are better able to support teachers and students in their scholarly work. The negative relationship between library services and library use for leisure may suggest that well-staffed libraries provide more opportunities for students to be actively engaged in learning. It is not necessarily surprising that increased library resources do not significantly predict library use for leisure, as the library resources under review are primarily academic resources such as educational software and subject databases. Findings suggest that students' background characteristics and school experiences play a much stronger role in students' access and choice of college than do the factors of school library resources and services. Nevertheless, student decisions are dictated in part by the information they have access to, and by the visibility of that information, and school libraries are a major source to which students have ready access. While second- and subsequent-generation college students have their family experiences to fall back on to help them with their college attendance questions, aspiring first-generation college students may have only the information they can glean from their secondary schools and the popular media. Unfortunately for first generation and low SES students, the provision of college information is not always equitable. Pribesh, Gavigan, and Dickinson (2011) noted the access gap for poor children, whose school libraries were under-resourced as compared to school libraries for wealthier children. Stanton-Salazar (2011) noted that low SES and first generation students may need additional support in the college choice process. This creates a vicious circle, in which poor students are less likely to get the support they need from their parents, families, schools, or school libraries. One strategy suggested in the literature to offset poor students' limited access to college information is the creation of a support network of empowerment agents to help students navigate the college application and financial aid processes. Can the school librarian serve as the institutional agent who advocates for students' college access and uses her social capital for that purpose, as Stanton-Salazar (2011) suggests? This has traditionally been the role of high school guidance counselors, who would use their specialized knowledge of the student and their preferences to guide the student to the right choice for them. The school librarian's traditional role would be to teach students how to find and use information about colleges, but not to make a value judgment about that information. Developing a supportive relationship with guidance counselors may, therefore, be a more appropriate approach, allowing each party to bring their strengths to the relationship rather than having the already-short staffed school library adds another objective to its list of duties. Future research is needed to clarify the roles that school libraries can play with regard to the provision of college information. Qualitative research might focus on high school students and their direct experiences with finding college information at the school library – what sources do they use and what barriers do they face in finding college information at the school library? Another avenue of potential investigation regards authority and trust, and whether high school students view the high school library as a credible source for college information. Research along these lines has the potential to identify differences between students of different racial, ethnic, and socioeconomic backgrounds, which could provide support for school libraries and information creators in developing a more evidence-based presentation of information that has been personalized for community information needs and trust. Future research can also help identify what school libraries contribute to students' predispositions to attend college, as signified by students' school experiences articulated in Factor 2. School libraries may not be able to influence grade point average directly, but they can create an environment that encourages students to take the ACT or SAT, they can

Please cite this article as: Zhou, E., & Adkins, D., The role of the school library in college access and choice, Library & Information Science Research (2016), http://dx.doi.org/10.1016/j.lisr.2016.11.009

E. Zhou, D. Adkins / Library & Information Science Research xxx (2016) xxx–xxx

7

Table 6 Regressions of library resources and services on library use for college information. Model 1

Model 2

B

SE

Exp(B)

0.02

0.06

1.02

Background characteristics Male Female (reference) American Indian and other race Asian Black Hispanic White (reference) Parents' education Family income School experiences GPA Plans to take SAT or ACT College preparation program Hours/week spent on reading Hours/week spent on homework Library services Library resources

0.31 0.15 0.48 0.03

0.13 0.10 0.09 0.10

1.37 1.16 1.62 1.03

−0.04 −0.06

0.07 0.01

0.96 0.94

χ2 df Sig. Nagelkerke R2

67.98 7 0.00 0.01

Sig.

⁎

Model 3

B

SE

Exp(B)

0.08

0.07

1.08

Sig.

B

SE

Exp(B)

0.01

0.08

1.02

⁎⁎

0.24 −0.07 0.36 −0.08

0.16 0.13 0.12 0.13

1.28 0.93 1.44 0.92

⁎⁎

−0.14 −0.06

0.09 0.02

0.87 0.94

⁎⁎⁎

−0.08 0.17 0.50 0.08 0.13 0.07 0.07

0.03 0.10 0.08 0.02 0.02 0.04 0.04

0.93 1.18 1.66 1.09 1.14 1.08 1.08

⁎

⁎⁎⁎

0.28 0.03 0.34 −0.01

0.14 0.11 0.11 0.11

1.32 1.04 1.40 1.00

⁎⁎⁎

−0.09 −0.07

0.08 0.02

0.92 0.93

⁎⁎⁎

−0.10 0.25 0.46 0.07 0.12

0.03 0.09 0.07 0.02 0.02

0.90 1.29 1.58 1.08 1.13

⁎⁎ ⁎⁎ ⁎⁎⁎ ⁎⁎⁎ ⁎⁎⁎

184.69 12 0.00 0.04

Sig.

⁎ ⁎⁎⁎ ⁎⁎⁎ ⁎⁎⁎

165.16 14 0.00 0.05

Source: National Center for Educational Statistics (2015). ⁎ p b 0.05. ⁎⁎ p b 0.01. ⁎⁎⁎ p b 0.001.

allow students space and resources for reading and homework, and they can promote materials for college preparatory programs. The influence of the school library is not represented in these variables, even though

school libraries may play a significant role in shaping these experiences. This is another area which can be reviewed for differences in availability for students of different racial, ethnic, and socioeconomic status.

Table 7 Regressions of library resources and services on library use for study.

Table 8 Regressions of library resources and services on library use for leisure.

Model 1 B Background characteristics Male Female (reference) American Indian and other race Asian Black Hispanic White (reference) Parents' education Family income School experiences GPA Plans to take SAT or ACT College preparation program Hours/week spent on reading Hours/week spent on homework Library services Library resources df Sig. Adjusted R2

Model 2 SE

Sig. B

Model 3 SE

Sig. B

Model 1 SE

Sig.

−0.13 0.02 ⁎⁎⁎

−0.11 0.02 ⁎⁎⁎

−0.12 0.02 ⁎⁎⁎

0.00

−0.03 0.04

0.01

−0.05 0.03 0.14 0.03 ⁎⁎⁎ −0.04 0.03

−0.12 0.03 ⁎⁎ 0.06 0.03 −0.07 0.03 ⁎

−0.15 0.04 ⁎⁎⁎ 0.05 0.04 −0.06 0.04

−0.02 0.02 −0.01 0.00 ⁎⁎

−0.05 0.02 ⁎ −0.02 0.01 ⁎⁎⁎

−0.06 0.03 ⁎⁎ −0.01 0.01 ⁎⁎

−0.07 0.01 ⁎⁎⁎ 0.12 0.02 ⁎⁎⁎

−0.06 0.01 ⁎⁎⁎ 0.15 0.03 ⁎⁎⁎

7 0.00 0.008

0.04

0.05

0.10

0.02 ⁎⁎⁎

0.13

0.03 ⁎⁎⁎

0.02

0.01 ⁎⁎⁎

0.02

0.01 ⁎

0.08

0.01 ⁎⁎⁎

0.08

0.01 ⁎⁎⁎

0.03 0.02

0.01 ⁎⁎ 0.01

12 0.00 0.038

Source: National Center for Educational Statistics (2015). ⁎ p b 0.05. ⁎⁎ p b 0.01. ⁎⁎⁎ p b 0.001.

14 0.00 0.04

Background characteristics Male Female (reference) American Indian and other race Asian Black Hispanic White (reference) Parents' education Family income School experiences GPA Plans to take SAT or ACT College preparation program Hours/week spent on reading Hours/week spent on homework Library services Library resources df Sig. Adjust. R2

Model 2 Sig. B

Model 3

B

SE

0.09

0.02 ⁎⁎⁎

0.12

0.02 ⁎⁎⁎

0.12

0.02 ⁎⁎⁎

0.22

0.04 ⁎⁎⁎

0.15

0.04 ⁎⁎⁎

0.12

0.05 ⁎

0.17 0.16 0.11

0.03 ⁎⁎⁎ 0.03 ⁎⁎⁎ 0.03 ⁎⁎⁎

0.10 0.07 0.05

0.03 ⁎⁎ 0.03 ⁎ 0.03 ⁎

0.13 0.06 0.06

0.04 ⁎⁎⁎ 0.04 0.04

0.02 0.02 −0.04 0.00 ⁎⁎⁎

SE

Sig. B

SE

Sig.

−0.03 0.02 −0.04 0.01 ⁎⁎⁎

0.00 0.03 −0.04 0.01 ⁎⁎⁎

−0.05 0.01 ⁎⁎⁎ 0.01 0.02

−0.05 0.01 ⁎⁎⁎ 0.01 0.03

0.12

0.02 ⁎⁎⁎

0.13

0.03 ⁎⁎⁎

0.15

0.01 ⁎⁎⁎

0.16

0.01 ⁎⁎⁎

0.03

0.01 ⁎⁎⁎

0.03

0.01 ⁎⁎⁎

−0.03 0.01 ⁎⁎ 0.00 0.01 7 0.00 0.022

12 0.00 0.11

14 0.00 0.11

Source: National Center for Educational Statistics (2015). ⁎ p b 0.05. ⁎⁎ p b 0.01. ⁎⁎⁎ p b 0.001.

Please cite this article as: Zhou, E., & Adkins, D., The role of the school library in college access and choice, Library & Information Science Research (2016), http://dx.doi.org/10.1016/j.lisr.2016.11.009

8

E. Zhou, D. Adkins / Library & Information Science Research xxx (2016) xxx–xxx

8. Conclusion The findings provide a better understanding of the relationship between high school students' background characteristics and school experience, and their library use behaviors. The differences across race/ ethnicity in terms of library use for college information, study and leisure have implications for resource and service allocation to school libraries. This research provides school administrators and librarians with more information which they can use to create strategies that will increase students' library use for different purposes. The findings are by definition limited in time and broad in scope. However, when supplemented with actual current use data from a district's school libraries, this information may help to show patterns in students' use of school libraries. School libraries have a role to play in encouraging and supporting college access and choice. More research is needed to demonstrate the depth of work they already do to support college access and choice, and to determine the best ways to present information about colleges to diverse audiences with different levels of experience and trust. References Advisory Committee on Student Financial Assistance (2010). The rising price of inequality: How inadequate grant aid limits college access and persistence. Report to congress and the secretary of education. Washington, DC: Author. Dolinsky, A. L. (2010). The adequacy of the information that students utilize when choosing a college: An attribute importance and information sufficiency approach. College Student Journal, 44(3), 762–776. Fabbi, J. L. (2015). Fortifying the pipeline: A quantitative exploration of high school factors impacting the information literacy of first-year college students. College & Research Libraries, 76, 31–42. Fitzgerald, M. A. (2004). Making the leap from high school to college: Three new studies about information literacy skills of first-year college students. Knowledge Quest, 32(4), 19–24. Henson, R. K., & Roberts, J. K. (2006). Use of exploratory factor analysis in published research: Common errors and some comment on improved practices. Educational and Psychological Measurement, 66(3), 393–416. Hutchison, L. F. (1982). The relationship between library use and academic category among tenth grade students. The Clearing House, 56(1), 34–37. Islam, R. L., & Murno, L. A. (2006). From perceptions to connections: Informing information literacy program planning in academic libraries through examination of high school library media center curricula. College & Research Libraries, 67(6), 492–514. Julien, H. E. (1999). Barriers to adolescents' information seeking for career decision making. Journal of the American Society for Information Science, 50, 38–48. Julien, H., & Barker, S. (2009). How high-school students find and evaluate scientific information: A basis for information literacy skills development. Library and Information Science Research, 31, 12–17. Kari, J. (2010). Diversity in the conceptions of information use. Information Research, 15(3) Retrieved from http://www.informationr.net/ir/15-3/colis7/colis709.html Kuh, G. D., & Gonyea, R. M. (2003). The role of the academic library in promoting student engagement in learning. College & Research Libraries, 64, 256–282. Long, B. T., & Riley, E. (2007). Financial aid: A broken bridge to college access? Harvard Educational Review, 77(1), 39–63.

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Please cite this article as: Zhou, E., & Adkins, D., The role of the school library in college access and choice, Library & Information Science Research (2016), http://dx.doi.org/10.1016/j.lisr.2016.11.009