Reducing Inequality in Student Outcomes in U.S. Geography Education: The Importance of Understanding Student Attitudes

Abstract

This study examines relationships between geography achievement and the psychological characteristics of geography learners in eighth grade. Using data provided by the National Assessment of Educational Progress (NAEP), the researchers developed a statistical model of geography achievement comprising student and teacher/school-level predictor variables. The model included five predictor variables based on composite measures of student affective disposition. Hierarchical linear modeling accounted for data clustering. Controlling for the full set of predictors, geography achievement was positively associated with students’ self-reported enjoyment of complex problems, academic self-discipline, and interest in and enjoyment of geography, whereas lower levels of geography achievement were associated with students’ self-reported level of persistence in learning. Race, gender, disability, minority language status, and instructional exposure were predictive of affective differences between groups of geography learners. The results of the study underscore the need to consider student attitudes in efforts to close achievement gaps and encourage the future geography intentions of students in U.S. geography education.

1. Introduction

Social disparities in geography achievement at the end of lower secondary education are associated with numerous educational and non-educational factors [1]. In this article, we explore relationships between geography achievement, instructional exposure, and the affective dispositions of different groups of geography learners in the eighth grade. Two questions specify the aims of this research:

• How is student achievement associated with the psychological traits of learners in the context of U.S. geography education?
• To what extent are student characteristics and geography educational experiences predictive of attitudes about learning in general and geography in particular?

To address these questions, we build on a recent analysis of geography achievement data provided by the National Assessment of Educational Progress (NAEP) [1]. In that study, we developed a two-level predictive model comprising contextual variables related to the students, teachers, and schools participating in the most recent NAEP Geography assessment in 2018. Using hierarchical linear modeling (HLM), we estimated geography achievement for each predictor variable while holding constant all other predictors. Most of the variability in geography achievement was found to be due to within-school factors; statistically significant predictors included race/ethnicity, disability, minority language status (English language learners), gender, socioeconomic status, and exposure to different types of learning activities. At the teacher/school level, geography achievement was affected by factors including teachers’ years of experience teaching social studies, the availability of professional development programs for improving social studies instruction, and school neighborhood poverty levels. We also identified several categories of variables that were not predictive of student outcomes in U.S. geography education, including teaching time, class size, and the academic degrees earned by geography teachers.

As a large-scale school-based assessment study, the NAEP program measures students’ degree of competency over subject matter that is consistent with the epistemic qualities of powerful knowledge (i.e., the substantive and conceptual knowledge that enables people to think geographically) [2]. The NAEP Geography assessment is based on a nationally representative sample of students in eighth grade, even though the nature of geography curriculum in the United States is primarily determined by educational policy at the state- and local district levels. NAEP results for geography are therefore generalizable to the nation as opposed to any particular state or school district.

The NAEP Geography modeling results point to important clues about the role of opportunity to learn (OTL) in shaping patterns of student achievement. Students exposed to instruction that taught them how to practice geography (e.g., by analyzing human–environment relations or patterns of migration) while studying geography topics were more likely to be able to apply geography for problem solving. Students’ knowledge and comprehension of geography also benefited from taking geography courses prior to the eighth grade. In contrast, overexposure to process-oriented instructional activities, such as going on field trips, role-playing, and creating multimedia presentations, resulted in lower levels of geography achievement. Other factors contributing to differences in the performance of students and schools, such as high poverty levels around school neighborhoods and unequal access to functional computers in classrooms, are beyond the direct control of geography educators.

One aspect of educational inequality that can be addressed through curriculum and instruction pertains to the degree to which students are interested in what they learn [3]. Student attitudes in education, including their interest in different subjects, self-efficacy and confidence as learners, and perceptions of the value, relevance, and importance of subject matter interact with their motivations to learn different subjects in ways that affect their educational capabilities and performance goals in school [4,5,6]. In addition, understanding student aspirations and attitudes is an important input in curriculum making aimed at inspiring students’ future college and career intentions [7,8,9,10,11,12].

Research and curriculum development in geography education has only given cursory attention to the values, beliefs, and attitudes of geography learners. National standards for U.S. geography education recommend detailed content and performance goals for students [13], yet none were written with the explicit goal of enhancing students’ appreciation of the subject. In the early 1990s, the developers of world geography curriculum modules found that the inclusion of U.S. case studies for comparative analysis with other world regions was important for enhancing students’ appreciation of global issues, including nationalism, population growth, globalization, and sustainable development [14]. Later in the decade, the National Council for Geographic Education received federal funding for the Finding a Way project with the goal of making geography lessons more appealing, interesting, and relevant to girls and ethnic minorities [15]. Overall, research into the attitudes of groups of geography learners has not consistently identified significant relationships with student outcomes [16,17,18]. However, those studies are difficult to compare because they were based on local cases and were conducted in different international contexts with no common measurement of student affective disposition. Because the research literature associated with student affect in geography education is limited by small samples and case studies, researchers have recommended empirical studies using large-scale educational assessment datasets [19].

In the present study, we expanded our two-level predictive model of geography achievement to include student-level predictor variables pertaining to the attitudes of learners in eighth grade. The attitudes of interest relate to students’ perceptions of themselves as learners and of geography as a school subject.

2. Materials and Methods

Portions of text in this section originally appeared in the authors’ open-access article reporting the methodology and results of the second phase of NAEP Geography modeling [1]. NAEP samples are representative of the geographic, racial and ethnic, and socioeconomic diversity of the United States (U.S. Department of Education 2022). The National Center for Education Statistics (NCES) oversees NAEP data collection to ensure the highest levels of consistency, accuracy, and fairness. Additional oversight is provided by the NAEP Validity Studies panels organized by the American Institutes of Research (AIR).

The 2018 NAEP Geography assessment was taken by a nationally representative sample of 12,900 eighth graders from 780 schools. The sample included 1840 teachers. Students and schools were selected at random, and participation was voluntary. Each student was given two blocks of cognitive assessment questions featuring a variety of item types, such as multiple-choice and constructed response items. Students also completed a contextual survey with questions common to all NAEP assessments (e.g., students self-report their characteristics including race, ethnicity, parental education, and whether they identify as male or female) and questions specific to geography education (e.g., students self-report how frequently they went on field trips to study geography topics, whether they took a geography class prior to eighth grade, etc.). The examination lasted 75 min. Following the assessment, item response theory (IRT) procedures were used by the assessment analysts to generate multiple plausible values (PVs) for each student’s performance on the overall assessment as well as on each specific content area represented in the assessment.

NAEP questionnaires for students, teachers, and schools are validated via a process that includes reviews by external advisory groups and field testing. The variables related to student affective disposition analyzed in this study derive from the responses to these questionnaires.

For the present study, we incorporated items from the NAEP student background questionnaire that the NAEP program developed to address affective variables of interest to educational policymakers and which relate to students’ motivational characteristics as learners. The items were used by the NAEP program to create indices that serve as composite measures of (1) students’ persistence in learning (i.e., students’ tendency to persevere and work hard in the face of challenges); (2) students’ academic self-discipline (i.e., students’ tendency to pay attention and stay on task when learning); (3) students’ enjoyment of complex problems (i.e., students’ enjoyment of problems and activities that challenge them to think); (4) students’ interest/enjoyment of geography (i.e., students’ interest in and enjoyment of geography topics, and their views of the importance of learning about geography); and (5) students’ mastery goals in geography (i.e., students’ motivation to learn as much as they can about geography and master new skills in their class) [20]. According to NAEP technical documentation, these indices were developed using methods that satisfied both theoretical criteria based on content analysis and empirical criteria based on multivariate statistical techniques [20].

To address our first research question, we accounted for clustering in the NAEP data by using hierarchical linear modeling (HLM) with PVs of theta (approximate mean and standard deviation of 0 and 1, respectively) for the geography composite score as the outcome variable. All analyses were conducted using the NAEP-supplied inverse probability sampling weights.

We followed a consistent algorithm to identify potential shifts in the strength, direction, and statistical significance of relationships between geography achievement and student affective disposition. The student affect predictors are factor scores from principal axis factor analyses; they represent two or more original variables that are conceptually related measures of a construct. These predictors have means of approximately 0 and standard deviations ranging from 1.63 to 2.20 (

Table 1. 2018 NAEP Geography descriptive statistics for student-level (level 1) predictors.

Predictor Variable	N	Mean	SD	Minimum	Maximum
Factor score
Persistence in learning	12,000	0.00	1.72	−5.46	2.81
Academic self-discipline	11,620	0.00	1.63	−4.96	3.23
Enjoyment of complex problems	11,100	0.00	1.90	−4.34	3.54
Interest in and enjoyment of geography	9100	0.00	1.91	−3.33	4.72
Mastery goals in geography	9790	0.00	2.20	−4.23	3.71

Sample size is unweighted and rounded to the nearest 10. Mean and standard deviation are unweighted statistics. Source: U.S. Department of Education, National Center for Education Statistics, National Assessment of Educational Progress (NAEP) Geography, 2018.

and

Table 2. Specifications for NAEP Geography student affective disposition predictor variables, 2018.

Level	Variable Category	Description
Student	Persistence in learning	Factor score: How much does each of the following statements describe a person like you? I finish whatever I begin. I try very hard even after making mistakes. I keep working hard even when I feel like quitting. I keep trying to improve myself, even when it takes a long time to get there. Answer choices: Not at all like me, A little bit like me, Somewhat like me, Quite a bit like me, Very much like me.
	Academic self-discipline	Factor score: In this school year, how often have you done each of the following? I started working on assignments right away rather than waiting until the last minute. I paid attention and resisted distractions. I stayed on task without reminders from my teacher. I paid attention in class even when I was not interested. Answer choices: Never or hardly ever, Less than half of the time, About half of the time, More than half of the time, All or almost all of the time.
	Enjoyment of complex problems	Factor score: How much does each of the following statements describe a person like you? I like complex problems more than easy problems. I like activities that challenge my thinking abilities. I enjoy situations where I will have to think about something. I enjoy thinking about new solutions to problems. Answer choices: Not at all like me, A little bit like me, Somewhat like me, Quite a bit like me, Very much like me.
	Interest in and enjoyment of geography	Factor score: How much does each of the following statements describe you? Geography is one of my favorite subjects to study. I enjoy doing schoolwork about geography. I enjoy discussing geography topics with others. I think that geography schoolwork helps me understand what is happening in the world around me. I think that learning about geography topics will be important for my future. Answer choices: Not at all like me, A little bit like me, Somewhat like me, Quite a bit like me, Exactly like me.
	Mastery goals in geography	Factor score: How much does each of the following statements describe you? I want to learn as much as possible about geography in my class. I want to master a lot of new geography skills in my class. I want to become a better geography student this year. I want to understand as much as I can about geography in my class. Answer choices: Not at all like me, A little bit like me, Somewhat like me, Quite a bit like me, Exactly like me.

Source: U.S. Department of Education, National Center for Education Statistics, National Assessment of Educational Progress (NAEP) Geography, 2018.

). A one-unit change in one of these predictors therefore represents a change in less than one standard deviation in that predictor. Coefficients for these predictors therefore represent the expected change in standard deviations of achievement per <1 standard deviation change in the factor score, controlling for all other predictors in the model.

To address our second research question, each composite measure of student affective disposition was set as the outcome variable in an HLM. The full set of school-level predictors (descriptive, geographic, demographic, poverty, and OTL) was included, as was the full set of student-level predictors (descriptive, demographic, instructional, and OTL). The remaining four affective disposition variables were not included as predictors in each of these five models.

All predictors from the previous statistical analyses of the 2018 NAEP Geography assessment were retained in the new models (

Table 3. NAEP Geography level 1 and level 2 predictor variables (controlled in model), 2018.

Level	Variables
1 (Student)	Sex, race, and ethnicity, Free/reduced-price lunch eligibility, English language learner (ELL), Individualized education plan (IEP), Above modal age, Books in home, Parental education, Took geography class before grade 8, Instructional exposure (learn geography practices, study geography topics, process-oriented learning activity, computer-mediated process-oriented learning activity), days absent, use computer technology in classes.
2 (Teacher/school)	School urbanicity, School region, School composition, School type, Functionality and speed of school computers, Years of social studies teaching experience, Teacher beliefs about student success in social studies, School offers professional development to improve social studies instruction, School offers professional development to improve reading and writing instruction.

Source: U.S. Department of Education, National Center for Education Statistics, National Assessment of Educational Progress (NAEP) Geography, 2018.

). The reported results for each predictor are therefore conditional on all level 1 and 2 predictors. Additional technical details about the NAEP Geography sampling design, psychometric theory, HLM, and retained predictor variables may be found in the article reporting the results of the preceding study [1].

3. Results

We first present the regression coefficients for the student affective disposition predictors of geography achievement. The second section of results is for student-level variables that are predictive of student attitudes about learning and geography education.

3.1. Relationships between Geography Achievement and Student Affective Disposition

Three composite measures of student affect showed net positive associations with geography achievement (

Table 4. Regression results for student affective disposition variables predicting 8th-grade student achievement in geography (controlling for all level 1 and 2 predictors), 2018, based on an analytic sample size of 5025 students, 773 teachers, and 276 schools.

Variable	γ (se)
Persistence in learning	−0.03 (0.01) *
Academic self-discipline	0.03 (0.01) *
Enjoyment of complex problems	0.07 (0.01) ***
Interest in and enjoyment of geography	0.03 (0.01) *
Mastery goals in geography	−0.02 (0.01)

* p < 0.05, *** p < 0.001. Source (all tables): U.S. Department of Education, National Center for Education Statistics, National Assessment of Educational Progress (NAEP) Geography, 1994–2018.

). Academic self-discipline is a factor score composite measure of how often in the school year students said that they started working on assignments right away, paid attention and resisted distractions, stayed on task without reminders, and paid attention in class even if they were uninterested. Each unit increase in the factor score for academic self-discipline results in an increase in NAEP Geography scores of about 0.03 standard deviations on average.

Interest in and enjoyment of geography is a factor score composite measure of how much students consider geography to be a favorite subject, like geography schoolwork and discussing geography topics, and believe learning geography is important and something that will help them understand the world. Each unit increase in the factor score for interest in and enjoyment of geography results in an increase in NAEP Geography scores of about 0.03 standard deviations on average.

Enjoyment of complex problems is a factor score composite measure of how much students prefer complexity over simple problems, being challenged as thinkers, and producing new solutions. Each unit increase in the factor score for enjoyment of complex problems results in an increase in NAEP Geography scores of about 0.07 standard deviations on average.

One of the student affective disposition predictors showed a negative net association with geography achievement. Persistence in learning is a factor score composite measure of how much students perceive themselves as a learner who finishes what they start, continues to try even in the face of mistakes and fatigue, and works to improve themselves even though the process can take a long time. Each unit increase in the factor score for persistence in learning results in a decrease in NAEP Geography scores of about 0.03 standard deviations on average.

Students’ mastery goals in geography were not predictive of geography achievement. This is a factor score composite measure of how much students want to learn geography, master geography skills, become better geography students, and understand as much geography as possible.

3.2. Predictors of Student Affective Disposition

Student attitudes varied in relation to the characteristics and experiences of students in geography education (Table 5, Table 6, Table 7 and Table 8).

• Race and ethnicity. Compared to White students, lower academic self-discipline was associated with Black students and students identifying with two or more races. Higher levels of academic self-discipline and enjoyment of complex problems were associated with Asian students.
• Gender. Compared to male students, female students had lower levels of interest in and enjoyment of geography but higher levels of academic self-discipline.
• ELL. Compared to students who are not classified as English language learners (ELL), ELL students had higher levels of interest in and enjoyment of geography.
• IEP. Students with disabilities were associated with lower levels of persistence in learning compared to students who did not receive learning accommodations under an individualized education plan (IEP).
• Above modal age. Older eighth graders were associated with higher levels of persistence in learning.
• Books at home. Larger home libraries were predictive of higher levels of students’ interest in and enjoyment of geography, persistence in learning, academic self-discipline, and enjoyment of complex problems.
• Parental education. Students with at least one college-educated parent were associated with higher levels of persistence in learning, academic self-discipline, and enjoyment of complex problems.
• Absenteeism. Higher numbers of days absent from school are associated with lower levels of students’ interest in and enjoyment of geography, persistence in learning, academic self-discipline, and enjoyment of complex problems.
• Computers and technology usage. Students who reported using computers and technology during most or all of their classes were associated with higher levels of persistence in learning, academic self-discipline, and enjoyment of complex problems.
• Taking geography prior to eighth grade. Eighth graders who took a geography class in earlier grades had higher levels of interest in and enjoyment of geography, academic self-discipline, and enjoyment of complex problems.
• Instructional exposure. Higher levels of enjoyment of complex problems, academic self-discipline, persistence in learning, and interest in and enjoyment of geography were associated with students who learned geography practices while studying geography topics. Similar relationships with student affect were found for students exposed to different modalities of process-oriented learning activities (e.g., going on field trips, participating in debates about geography topics, role-playing).

Table 5. Regression results for student characteristics predicting 8th-grade student interest in and enjoyment of geography (controlling for all level 1 and 2 predictors), 2018, based on an analytic sample size of 5025 students, 773 teachers, and 276 schools.

Variable	γ (se)
Books in home	0.21 (0.04) ***
Days absent	−0.08 (0.04) *
ELL	0.37 (0.15) **
Female	−0.22 (0.07) **
Took geography before grade 8	0.55 (0.08) ***
Instructional exposure (process-oriented learning activity)	0.19 (0.05) ***
Instructional exposure (learn geography practices)	0.45 (0.07) ***
Instructional exposure (computer-mediated process-oriented learning activity)	0.45 (0.05) ***

* p < 0.05, ** p < 0.01, *** p < 0.001. Source (all tables): U.S. Department of Education, National Center for Education Statistics, National Assessment of Educational Progress (NAEP) Geography, 1994–2018.

Table 5. Regression results for student characteristics predicting 8th-grade student interest in and enjoyment of geography (controlling for all level 1 and 2 predictors), 2018, based on an analytic sample size of 5025 students, 773 teachers, and 276 schools.

Variable	γ (se)
Books in home	0.21 (0.04) ***
Days absent	−0.08 (0.04) *
ELL	0.37 (0.15) **
Female	−0.22 (0.07) **
Took geography before grade 8	0.55 (0.08) ***
Instructional exposure (process-oriented learning activity)	0.19 (0.05) ***
Instructional exposure (learn geography practices)	0.45 (0.07) ***
Instructional exposure (computer-mediated process-oriented learning activity)	0.45 (0.05) ***

* p < 0.05, ** p < 0.01, *** p < 0.001. Source (all tables): U.S. Department of Education, National Center for Education Statistics, National Assessment of Educational Progress (NAEP) Geography, 1994–2018.

Table 6. Regression results for student characteristics predicting 8th-grade student persistence in learning (controlling for all level 1 and 2 predictors), 2018, based on an analytic sample size of 5025 students, 773 teachers, and 276 schools.

Variable	γ (se)
Books in home	0.23 (0.04) ***
Days absent	−0.18 (0.03) ***
Parental education	0.10 (0.04) *
How often use computers and technology during classes	0.11 (0.03) ***
IEP	−0.29 (0.14) *
Above modal age	0.21 (0.08) **
Instructional exposure (learn geography practices)	0.23 (0.04) ***
Instructional exposure (computer-mediated process-oriented learning activity)	0.11 (0.05) *

* p < 0.05, ** p < 0.01, *** p < 0.001. SOURCE (all tables): U.S. Department of Education, National Center for Education Statistics, National Assessment of Educational Progress (NAEP) Geography, 1994–2018.

Table 6. Regression results for student characteristics predicting 8th-grade student persistence in learning (controlling for all level 1 and 2 predictors), 2018, based on an analytic sample size of 5025 students, 773 teachers, and 276 schools.

Variable	γ (se)
Books in home	0.23 (0.04) ***
Days absent	−0.18 (0.03) ***
Parental education	0.10 (0.04) *
How often use computers and technology during classes	0.11 (0.03) ***
IEP	−0.29 (0.14) *
Above modal age	0.21 (0.08) **
Instructional exposure (learn geography practices)	0.23 (0.04) ***
Instructional exposure (computer-mediated process-oriented learning activity)	0.11 (0.05) *

* p < 0.05, ** p < 0.01, *** p < 0.001. SOURCE (all tables): U.S. Department of Education, National Center for Education Statistics, National Assessment of Educational Progress (NAEP) Geography, 1994–2018.

Table 7. Regression results for student characteristics predicting 8th-grade student academic self-discipline (controlling for all level 1 and 2 predictors), 2018, based on an analytic sample size of 5025 students, 773 teachers, and 276 schools.

Variable	γ (se)
Black	−0.28 (0.12) *
Asian	0.30 (0.13) *
2 or more races	−0.28 (0.14) *
Female	0.41 (0.06) ***
Books in home	0.29 (0.04) ***
Days absent	−0.20 (0.04) ***
Parental education	0.08 (0.04) *
How often use computers and technology during classes	0.07 (0.03) **
Took geography before grade 8	0.25 (0.10) **
Instructional exposure (learn geography practices)	0.23 (0.04) ***
Instructional exposure (computer-mediated process-oriented learning activity)	0.13 (0.05) **

* p < 0.05, ** p < 0.01, *** p < 0.001. Source (all tables): U.S. Department of Education, National Center for Education Statistics, National Assessment of Educational Progress (NAEP) Geography, 1994–2018.

Table 7. Regression results for student characteristics predicting 8th-grade student academic self-discipline (controlling for all level 1 and 2 predictors), 2018, based on an analytic sample size of 5025 students, 773 teachers, and 276 schools.

Variable	γ (se)
Black	−0.28 (0.12) *
Asian	0.30 (0.13) *
2 or more races	−0.28 (0.14) *
Female	0.41 (0.06) ***
Books in home	0.29 (0.04) ***
Days absent	−0.20 (0.04) ***
Parental education	0.08 (0.04) *
How often use computers and technology during classes	0.07 (0.03) **
Took geography before grade 8	0.25 (0.10) **
Instructional exposure (learn geography practices)	0.23 (0.04) ***
Instructional exposure (computer-mediated process-oriented learning activity)	0.13 (0.05) **

* p < 0.05, ** p < 0.01, *** p < 0.001. Source (all tables): U.S. Department of Education, National Center for Education Statistics, National Assessment of Educational Progress (NAEP) Geography, 1994–2018.

Table 8. Regression results for student characteristics predicting 8th-grade student enjoyment of complex problems (controlling for all level 1 and 2 predictors), 2018, based on an analytic sample size of 5025 students, 773 teachers, and 276 schools.

Variable	γ (se)
Asian	0.50 (0.11) ***
Books in home	0.45 (0.04) ***
Days absent	−0.17 *0.05) ***
Parental education	0.15 (0.07) *
How often use computers and technology during classes	0.08 (0.03) *
Took geography before grade 8	0.39 (0.12) ***
Instructional exposure (learn geography practices)	0.31 (0.05) ***
Instructional exposure (computer-mediated process-oriented learning activity)	0.13 (0.06) *

* p < 0.05, *** p < 0.001. Source (all tables): U.S. Department of Education, National Center for Education Statistics, National Assessment of Educational Progress (NAEP) Geography, 1994–2018.

Table 8. Regression results for student characteristics predicting 8th-grade student enjoyment of complex problems (controlling for all level 1 and 2 predictors), 2018, based on an analytic sample size of 5025 students, 773 teachers, and 276 schools.

Variable	γ (se)
Asian	0.50 (0.11) ***
Books in home	0.45 (0.04) ***
Days absent	−0.17 *0.05) ***
Parental education	0.15 (0.07) *
How often use computers and technology during classes	0.08 (0.03) *
Took geography before grade 8	0.39 (0.12) ***
Instructional exposure (learn geography practices)	0.31 (0.05) ***
Instructional exposure (computer-mediated process-oriented learning activity)	0.13 (0.06) *

* p < 0.05, *** p < 0.001. Source (all tables): U.S. Department of Education, National Center for Education Statistics, National Assessment of Educational Progress (NAEP) Geography, 1994–2018.

4. Discussion

This study represents the third multilevel statistical analysis of the 2018 NAEP Geography assessment of U.S. students in eighth grade. The first phase was a descriptive analysis of student- and school-level predictors of geography achievement [21]. Phase two expanded the initial model to include a wide array of explanatory variables at both levels of the model [1]. The present study captured additional variability in the dataset via the inclusion of composite measures of student affective disposition. Because of missing data associated with the retained contextual variables at both levels of the model, there was a loss of sample size at the student level, and as such, the results of the present study are not generalizable to the national population of eighth graders. We turn next to a discussion of the relationships between geography achievement and student attitudes and what we have learned about the student groups that tend to be associated with those attitudes.

Although the effect sizes associated with student affective disposition variables were small relative to the predictors retained from our previous models, their statistical significance warrants closer examination. Students who enjoy complex problems and who are focused, conscientious learners perform at higher levels in geography education. Students who fit both descriptions are more likely to be Asian, have parents who completed at least some college education, come from households with higher social capital, and have good school attendance records.

A third psychological trait, persistence in learning, was negatively associated with geography achievement. This result may seem surprising given the students who are the most persistent learners are those advantaged by high social capital at home, which we previously found to be predictive of superior performance in geography education. A possible explanation for this outcome might be the relative difficulty or demands that other subjects pose for some of these learners, who then compensate by dedicating more time and effort to schoolwork in those areas. The results also indicate that less persistent learners are those with disabilities and high rates of absenteeism, both of which are predictive of lower levels of geography achievement.

Student attitudes about geography also predict how well students perform in geography education. The social capital afforded by growing up in households with higher education degree holders and ample educative materials is associated with greater interest in and enjoyment of geography. Early geography educational experiences also matter whereas absenteeism appears to degrade the perceived importance and enjoyable qualities of learning geography. Although race and ethnicity did not differentiate students in terms of their interest and enjoyment levels, female students were less positive in their appraisal of geography than male students. And while we previously found ELL students to be associated with some of the largest achievement gaps in geography education, they nonetheless had more interest in geography and enjoyed their experiences in geography education more than their counterparts.

As for the reasons why affective disposition is associated with geography achievement in ways that vary among student groups, the collective results of the NAEP Geography analyses point to differences in opportunity to learn as a key factor. Taking a geography class earlier in middle school is predictive of more proficient outcomes and higher levels of interest in and enjoyment of geography at the end of lower secondary education. Students who had a prior opportunity to learn geography are also more likely to be disciplined learners who like to be challenged in their thinking and problem solving. More proficient achievement in and favorable dispositions about geography education tend to be associated with students who are White, Asian, male, and economically advantaged.

Another aspect of the results carries important implications for geography teaching. Students exposed to instruction in the practices of geography not only perform at higher levels on the NAEP Geography assessment, but this pedagogy also results in greater levels of interest in and enjoyment of the subject, academic self-discipline, and enjoyment of complex problems—all of which predict superior academic outcomes.

On the other hand, various forms of process-oriented geography instruction also associate positively with these same categories of student attitudes. The crucial difference pertains to the lower level of geography achievement among students who spend excessive amounts of time role-playing, going on field trips, debating geography topics, creating multimedia, searching the internet, and other process-oriented activities that do not involve studying geographic content knowledge and applying geography knowledge and skills to address and solve problems. Process-oriented instructional methods may well appeal to students and their sense of creativity as learners, but unless geography teachers maintain a high-fidelity commitment to powerful knowledge, students may not gain the substantive and conceptual knowledge required to think geographically at a high level of proficiency.

Based on what we have learned from the multiple phases of NAEP Geography models, the following measures are recommended for reducing inequality in student outcomes. First, it is important to design a geography curriculum based on conceptions of powerful knowledge—the substance and concepts of geography that enable students to think like geographers and apply what they learn to solve problems [22]. To foster a desire to learn among students and to help them see the relevance and applicability of geography, teachers should also account for the characteristics of their students using culturally and community-responsive approaches to geography curriculum making.

A logical research aim moving forward should be to understand how curriculum making based on the idea of powerful knowledge can simultaneously enhance students’ appreciation of geography. This research has considerable potential to result in strategies for reducing achievement gaps but also to inspire the future geography college and career intentions of students across the country. Considering the longstanding social disparities in geography achievement, alternatives to the content guidance of national education standards and other top-down educational reforms will likely be necessary for attracting diverse youth to geography learning opportunities and careers.

In the United States, the Powerful Geography initiative led by the National Center for Research in Geography Education seeks to support efforts by teachers to align the teaching of geography with the diverse aspirations and job prospects of students [23]. Powerful Geography’s theory of change focuses on a sequence of questions at the heart of high-quality curriculum making [24]. First, teachers account for “who” students are with special attention to their life and career aspirations. Second, teachers consider real-world evidence of “why” geography education is important for effective work and informed democratic citizenship. This leads to teachers addressing “what” subject matter to teach and its relationship to student aspirations. Finally, teachers consider “how” to teach the applications and relevance of geography via inquiry and complementary methods.

Powerful Geography’s theory of change explicitly draws on research into the science of broadening participation that emphasizes the importance of understanding student aspirations and attitudes to encourage the future geography intentions of young people. And, importantly, Powerful Geography is designed to help U.S. teachers meet new demands on their practice and profession.

According to the National Academies report Changing Expectations for the K-12 Teacher Workforce: Policies, Preservice Education, Professional Development, and the Workplace [25], teachers are increasingly responsible for setting teaching goals that require improved disciplinary content knowledge and culturally relevant pedagogy while preparing students for the workforce by helping them apply content to novel problems and situations; creating equitable learning environments that account for the greater diversity of students and the experiences they bring into schools; and selecting subject matter and creating instructional materials that support the implementation of new curriculum standards in the states.

Addressing the contemporary professional expectations of teachers via Powerful Geography would be a step away from top-down prescriptive standards and curriculum toward a Deweyan future attuned to the local autonomy of students, teachers, and communities [26]. Such a transition would offer geography educators a pragmatic opportunity to include the enhancement of students’ geography intentions as a desired goal of the future geography curriculum.