1. Introduction

In the most recent global comparative educational assessment, 15-years-old in the United Stated ranked in the 13th place out of 35 Organisation for Economic Co-operation and Development (OECD) countries in reading. In the US context, the National Assessment of Educational Progress (NAEP) conducted in 2019 showed that students’ overall reading comprehension skills have been decreasing. Indeed, the average reading scores were lower for both fourth- and eighth-grade students compared to 2017. In grade 12, the average score was 2 points lower than in 2015. Additionally, the average score in grade 12 was lower than in 1992. Research for understanding the factor that explains variability in reading performance has primarily focused on demographic, cognitive (Oakhill & Cain, 2011), personality, and learning skills as self-regulation. For example, National Center for Educational Statistics NCES (2018) claims that reading skills are strongly related to the increase in the number of children with limited English proficiency enrolled in public schools, which has steadily increased during the last years. Compared to their monolingual peers, most Spanish-English bilingual and Black students evidence underdeveloped reading comprehension outcomes and a high risk of developing academic difficulties (NCES, 2011). According to NAEP, 50% and 40% of Black and Hispanic students in eight grades in the NYC School District have a reading comprehension achievement level below basic skill. However, studies that relate non cognitive constructs of belief and attitudes to academic performance are scarce.

Available large-scale assessments of student performance can provide a window into broadly defined concepts of student achievement and a wide range of student background, attitudes, perceptions, school, and home characteristics. In that sense, the Programme for International Student Assessment (PISA), a one-large-scale and internationally representative dataset, can be used to assess s a broad range of competencies relevant to coping with the adult life of a 15-year-old-students. The overall aim of the present study is to investigate both the measurement and structural validity of the theory of planned behavior framework to investigate the relationship between non cognitive factors on reading literacy students’ performance in the US PISA 2018 sample.

1.1 Theory Planned Behavior

The theory of planned behavior (TPB) proposed by Ajzen (1991) was developed to understand the links between attitudes and behavior in a variety of life domains (Conner & Armitage, 1998). The three attitude determinants or exogenous components of the TPB (attitude towards the behavior, subjective norms, and perceived behavioral control), are hypothesized to predict behavioral intentions and subsequent attitude-related behavior. Intentions are conceptualized as mediators between the three determinants and behavior. Furthermore, the TPB posits that perceived behavioral control also has an indirect, mediated effect on behavior through intentions (see Figure 1). Overall, it is expected that the relations among the constructs within the TPB framework are positive such that the three determinants are positively related to intentions and behavior, and the construct of intentions is positively related to behavior.

The use of the TPB is scarce in educational research. However, some efforts to promote this theoretical model in understanding student behavior and achievement have been implemented. For example, Gjicali et al. (2021) used the theory of planned behavior (TPB) to explain high school student’s performance in mathematics in large-scale assessment data by using the PISA 2012, showing that the applicability of an attitude-behavior framework in educational research for understanding the academic performance and the importance of perceived control and self-efficacy beliefs for predicting behavioral engagement in mathematics and subsequent mathematics performance. Additionally, Burrus and Moore (2016) conducted a study with a sample of high school juniors and seniors who took the ACT (American College Testing). Results indicated that TBP components were all significantly correlated with mathematics grades in school and mathematics test scores.

1.2 Present study and research questions

Using data from the U.S. sample of the PISA 2018, this study aimed to answer a series of questions on the direct and indirect effects of students’ attitudes on intentions, behavioral engagement and reading performance. The following research questions were examined to assess both the measurement and structural viability of the TPB framework by using the the United States sample of PISA 2018:

RQ1. Which indicators best measure the latent constructs of the attitude determinants (attitude towards behavior, subjective norms, perceived behavioral control), intentions, and behavioral engagement?

RQ2. Is the structure of the theory of planned behavior (Ajzen, 1991, 2005, Gjicali et al., 2021) identified in the U.S. PISA 2018 sample?

RQ3. What are the magnitudes of the direct and indirect effects of (a) the attitude determinants on intentions, behavioral engagement, and reading performance, (b) intentions on reading behavioral engagement and reading performance, and (c) reading behavioral engagement on reading performance?

RQ4. Does perceive behavioral control have a significant, indirect effect on reading performance through behavioral engagement alone?

Figure 1. he theory of planned behavior components predicting academic achievement

2. Method

2.1 Data and Sample

The current analysis is based on the United States PISA 2012 public-use data file. PISA measures 15-year-old’ ability to use their reading, mathematics, and science knowledge and skills to meet real-life challenges. In 2018, 612204 students participated in PISA, representing about 32 million 15-year-old in the schools of the 79 participating countries and economies. The data set used in the current study included N= 4,838 participants (49% female). The mean age of students participating in the assessment was 15.84 (SD = 0.285), 1.46% repeated between grades 10–12. Over 78.8% of the students were native, those students who had at least one parent born in the country) 16% were born in the U.S, but their parent(s) were born in another country (second-generation), and 5.2% were first-generation. After selecting variables for analysis, participants with more than 60% of omission were removed from the data set (2.2%). A total of 4730 observations were used in the analysis.

2.2 Variables

Control Variables

Gender and socioeconomic status were controlled in the analysis, given the research basis of this variable as factors for explaining differences om academic performance. The index of economic, social, and cultural status (ESCS) is a composite score based on education, occupational status, and income. In PISA 2018, the ESCS was constructed as the arithmetic mean of the three indicators after their imputation and standardization. The ESCS scale has a mean of 0 and a standard deviation of 1, when values less than 0 imply means an ESCS lower than the OCDE average.

Latent Variables: Attitudinal Constructs, Intentions, and Behavioral Engagement

In the self-report background questionnaire of the PISA, students provided responses to survey questions relevant to attitude towards school, instrumental motivation of reading, and perceived levels of teacher support in reading class, among other noncognitive constructs. Following the TPB framework (Ajzen, 1991), the items that were conceptually relevant to either students’ attitudes (attitudes towards reading, subjective norms, perceived behavioral control), intentions, and behavioral engagement (reading-related behaviors) were considered for analysis, a total of 94 individual items were initially selected. The majority of items were rated on a Likert scale from four through six-point categories (e.g., strongly agree to disagree strongly, not all true to extremely true). First, the items were grouped by construct based on the operational definition provided by PISA. Then, items conceptually similar to another and indicated statistically significant correlations were averaged to create composite variables (i.e., item parcels) (Masaki, 2008). Composite scores of multiple item parcels were considered in the development and analyses of measuring each of the latent factors. Table 1 presents the variables from the data set considered for analysis, the variable names, examples of items included in the construct, and the reliability statistics (Cronbach’s \(\alpha\)) of the item parcels organized by the constructs of interest in this study.

Table 1. Variables selected for analysis (Item Parcels) by construct
Variable Item Example No. items No. categories Reliability
Attitudes
Attitudes toward reading-negative* How much do you agree or disagree? I read only if I have to. 3 4 0.826
Attitudes toward reading-positive How much do you agree or disagree? Reading is one of my favourite hobbies. 2 4 0.779
Attitudes toward school* Thinking about your school: Trying hard at school will help me get a good job. 3 4 0.897
Motivation - Mastery achievement I find satisfaction in working as hard as I can. 3 4 0.774
Behavioral Engagement
Behavior - Media Use How often involved in: Taking part in online group discussions or forums 6 6 0.746
Behavior - Read How often do you read these materials because you want to? Non-fiction books (informational, documentary) 5 5 0.683
Enjoy reading About how much time do you usually spend reading for enjoyment? 1 5 NA
Metacognition - assesing credibility How appropriate in reaction to this email: Answer the email and ask for more information about the smartphone 3 6 0.654
Metacognition - planning Usefulness for understanding and memorising text: I underline important parts of the text. 2 6 0.716
Metacognition - self-evaluation Usefulness for understanding and memorising text: After reading the text, I discuss its content with other people. 3 6 0.622
Metacognition - sumarizing Usefulness for writing a summary: I try to copy out accurately as many sentences as possible. 2 6 0.784
Metacognition - understanding Usefulness for understanding and memorising text: I quickly read through the text twice. 2 6 0.552
Intention
Education Level* Do you expect to complete? <ISCED level 5B> 1 2 NA
Intentions How true for you: My goal is to understand the content of my classes as thoroughly as possible. 1 5 NA
Perceived Control
Perceived control negative* I have always had difficulty with reading. 3 4 0.765
Perceived control positive I read fluently. 3 4 0.849
Subjective Norms
Cognitive activation - Contrast* When you have to read, does the teacher ask you to: Compare the content of the book or the chapter with your own 2 2 0.545
Cognitive activation - Groups* When you have to read, does the teacher ask you to: Discuss in small groups with other students who read the same 1 2 NA
Cognitive Activation - Participation In your language lessons, how often: The teacher encourages students to express their opinion about a text. 2 4 0.776
Cognitive activation - Reflecting* When you have to read, does the teacher ask you to: Select a passage you liked or disliked and explain why 3 2 0.495
Cognitive Activation - Writing* When you have to read, does the teacher ask you to: List and write a short description of the main characters 3 2 0.575
Formative Assessment How often during language lessons: The teacher tells me how I can improve my performance. 3 4 0.903
Student Orientation How often in language lessons: The teacher adapts the lesson to my class’s needs and knowledge. 3 4 0.799
Subjective Norms - Parents Thinking about this academic year: My parents support my educational efforts and achievements. 3 4 0.898
Subjective Norms -competition Think about your school, how true: Students seem to share the feeling that competing with each other is important. 3 4 0.853
Subjective Norms -cooperation Think about your school, how true: Students feel that they are encouraged to cooperate with others. 4 4 0.904
Teacher Directed Instruction* How often during language lessons: The teacher asks questions to check whether we have understood what was taught 4 4 0.806
Teacher Support* How often during language lessons: The teacher helps students with their learning. 4 4 0.895
NA NA 78 NA NA
* Categories of respose were reverse before conducting the analysis

the present study.

2.3 Analytic Plan

First, the data were downloaded, cleaned, recoded, and reverse coded, where necessary, using R (See Scripts 01 and 02). Second, all factor analyses, measurement model comparisons, and structural equation model (SEM) analyses were executed using Lavaan package in R. For treating messing data, a full information maximum likelihood (FIML) was implemented in using all available data to estimate models measurement model instead of listwise deletion automatically implemented by ML estimator. FIML estimation has been shown to produce unbiased parameter estimates and standard errors under the assumptions of missing at random (MAR) and missing completely at random (MCAR) (Enders & Bandalos, 2001).

In order to examine the first research question regarding the measurement model of attitudes, intentions, and behaviors, a series of confirmatory factor analyses (CFA) was conducted. CFA models were compared based on global model fit indices. Model fit were assessed following existing conventions: (1) overall fit assessed using the \(\chi^{2}\) statistic that evaluates the magnitude of discrepancy between the sample and the model-estimated, largest values of \(\chi^{2}\) indicate a bad fit; (2) the Comparative Fit Index (CFI), Tucker-Lewis index (TLI), and Normed Fit Index (NFI) with values >.90 indicating an acceptable fit and values >.95 indicating a good fit; (3) the Standardized Root Mean Square Residual (SRMR) <.10 being indicative of good fit (preferably < 0.08); and (4) the Root Mean Square Error of Approximation (RMSEA) with values <.05 indicating a good fit and >.10 unacceptable.

After the first CFA iteration, the model fit indices were examined, and indicators that had a standardized factor loading \(\lambda \geq\) 0.3 were included as an item in the factor. In subsequent CFA models, items were removed based on their factor loading, and model fit indices were examined to determine if an alternative factor model resulted in a better fit. Modification indices analysis was also conducted to improve model fit. In order to examine research questions 2 through 4, the CFA model that indicated the best model fit was used as the basis of the structural model. In the SEM model, the following direct effects were specified: (1) the exogenous attitude constructs (attitude towards reading behaviors, subjective norms, perceived behavioral control) on intention to pursue learning goals and future career, (2) intention to pursue learning goals and future career on reading behavioral engagement, and reading behavioral engagement on reading performance. The indirect relation of perceived behavioral control on behavioral engagement through intention was also examined. All paths controlled for student gender and socioeconomic status. Standardized coefficients and 95% confidence intervals for all direct and indirect estimates were also generated.

3. Results

3.1 Descriptive Data

Means, standard deviation, and range for all variables of the current analysis are showed in Table 2. The socioeconomic and cultural status index that was used as a control variable was centered close to zero (M = 0.07, SD = 1.01), ranging from -4.10 and 3.25. The mean of the first plausible values for reading performance of the U.S. PISA 2018 sample was 501.89 (S.D =108.15) ranged from 161.34 to 868.87. The correlation matrix among all study variables are presented in Table A1 in Appendix. The majority of the correlation coefficient estimates were positive, suggesting positive relations among the attitude indicators and between attitudes and reading performance.

Table 2. Descriptive Statistics of Study Variables
Construct Variable Mean Median SD Range Min Max
ESCS Economic, social and cultural status index (ESCS) 0.07 0.16 1.01 7.35 -4.10 3.25
Academic Performance Reading Performance (PV1READ) 501.89 505.61 108.15 707.53 161.34 868.87
Attitudes Attitudes - Reading, Wast of time (ATTNEG) 2.56 2.67 0.83 3.33 0.67 4.00
Attitudes Attitudes - Reading, Useful furture (ATTPOS) 2.17 2.00 0.86 3.50 0.50 4.00
Attitudes Attitudes - School (ATTSCHOL) 3.48 3.67 0.70 3.67 0.33 4.00
Attitudes Attitude Motivation - Mastery Achievement (MOTMAST) 3.09 3.00 0.63 3.67 0.33 4.00
Behavioral Engagement Behavior - Reading (BEHREAD) 2.17 2.00 0.78 4.80 0.20 5.00
Behavioral Engagement Behavior - Media Use (BEHMEDIA) 3.51 3.50 0.77 4.83 0.17 5.00
Behavioral Engagement Metacognition - Understanding (METUNDER) 3.30 3.50 1.27 5.50 0.50 6.00
Behavioral Engagement Metacognition - Self-evaluation (METSELFEV) 3.29 3.33 1.24 5.67 0.33 6.00
Behavioral Engagement Metacognition - Planning (METPLANN) 4.03 4.00 1.43 5.50 0.50 6.00
Behavioral Engagement Metacognition - Sumarizing (METSUMRA) 4.27 4.50 1.42 5.50 0.50 6.00
Behavioral Engagement Metacognition - Assesing credibility (METCREDI) 3.52 3.33 1.37 5.67 0.33 6.00
Perceived Behavioral Perceived Control Positive (CONTPOS) 3.01 3.00 0.67 3.67 0.33 4.00
Perceived Behavioral Perceived Control Positive (CONTNEG) 2.83 3.00 0.70 3.67 0.33 4.00
Subjective Norms Norms Clasroom - Environment (CLASSENV) 1.98 2.00 0.71 3.80 0.20 4.00
Subjective Norms Norms Clasroom - Teacher Support (TCHSUPP) 3.14 3.25 0.78 3.50 0.50 4.00
Subjective Norms Norms Clasroom - Teacher Directed Instruction (DIRINSTR) 2.98 3.00 0.74 3.25 0.75 4.00
Subjective Norms Norms Clasroom - Student Orientation (STUORIEN) 2.57 2.67 0.78 3.67 0.33 4.00
Subjective Norms Norms Clasroom - Formative Assessment (FORASSMN) 2.55 2.67 0.89 3.33 0.67 4.00
Subjective Norms Norms Clasroom - Cognitive activation Comparison (COGAC_COMP) 1.62 1.50 0.41 1.50 0.50 2.00
Subjective Norms Norms Clasroom - Cognitive activation Reflecting (COGAC_REFLEC) 1.73 1.67 0.30 1.33 0.67 2.00
Subjective Norms Norms Clasroom - Cognitive activation Exposition (COGAC_PART) 2.72 3.00 0.84 3.50 0.50 4.00
Subjective Norms Norms Clasroom - Cognitive activation Writing (COGAC_WRIT) 1.67 1.67 0.35 1.67 0.33 2.00
Subjective Norms Norms - Parents (PARENTS) 3.36 3.67 0.73 3.33 0.67 4.00
Subjective Norms Norms Clasroom - Competence (COMPETEN) 2.76 3.00 0.75 3.67 0.33 4.00
Subjective Norms Norms Clasroom - Cooperation (COOPERAT) 2.54 2.50 0.68 3.75 0.25 4.00

3.2 Confirmatory Factor Analysis

Iterations of three-factor CFAs representing attitude (Cronbach’s \(\alpha\) = 0.53), subjective norms (\(\alpha\) = 0.75), perceived behavioral control (\(\alpha\) = 0.68 ), intentions (\(\alpha\) = 0.8), and behavioral engagement (\(\alpha\) = 0.72) as latent factors were performed to generate a measurement model with appropriate model fit. Model 1 contained all of the indicators that were initially considered as relevant based on the operational definitions of each construct (29 items or parcels items). Model 1 showed unacceptable model fit: RMSEA = 0.079, 90% CI [0.078, 0.081]; CFI = 0.717 ; TLI = 0.689; SRMR = 0.088 (see Table 3). Then, indicators with loading factors \(\lambda \leq\) 0.3 were dropped during this iterations. Table A2 in Appendix showed the laoding factors for Model 1 and 2. Although indices showed a slightly improvement compare with Model 1, Model 2 also showed an unacceptable model fit: RMSEA = 0.082, 90% CI [0.081, 0.084]; CFI = 0.831 ; TLI = 0.802; SRMR = 0.072. In Model 3 two residual covariance specification between items and two cross-loadings factors, that indicated high factor loadings in a one attitudinal factor, were suggested by the indices modification analysis to improve model fit (Worthington & Whittaker, 2006). After conducted Model 3, changes in loading factors were verified and those \(\lambda \leq\) 0.3 were deleted from model. Measurement Model 3 showed a good model fit as indicated by conventional indices: RMSEA = 0.045 , 90% CI [0.043, 0.047]; CFI = 0.950 ; TLI = 0.940; SRMR = 0.043.

Table 3. Comparison Measurement Models (CFAs) Fit Statistics
RMSEA 90% CI
Model DVs Chisq df p-value CFI TLI NFI SRMR RMSEA LL UL
Model 1 100 12186.701 395 0 0.717 0.689 0.711 0.088 0.079 0.078 0.081
Model 2 73 5936.913 179 0 0.831 0.802 0.827 0.072 0.082 0.081 0.084
Model 3 75 1891.311 177 0 0.950 0.940 0.945 0.043 0.045 0.043 0.047

Model 3 was the measurement model accepted for subsequent analyses, which was the best fitting model among the iterations (see Table 3). The finalized standardized estimates of the factor loading of measurement Model 3 from the structural model analysis ranged from 0.322 \(\leq \lambda \leq\) 0.893, and were all significant at p-value < 0.001 (see Table 4).

All latent variables were found to be positive intercorrelated, as was hypothesized. Attitude was most highly correlated with perceived behavioral control (r = 0.473), followed by behavior (r = 0.328), subjective norms (r =0.185), and intentions (r = 0.182). Subjective norms was correlated with behavior (r = 0.385), intentions (r = 0.298), and perceived behavioral control (r = 0.246). Perceived behavioral control was correlated with intentions (r = 0.195), and behavior (r = 0.307). Finally, intentions was correlated with behavior (r = 0.396). In sum, the highest correlation was observed between attitude and perceived behavioral control (r = 0.473) and the weakest correlation was observed between attitudes and intentions (r = 0.182). All correlations among latent constructs were statistically significant (p <0.001)

Table 4. Final Standarized Factor Loading Measurement Model
95% CI
Variable Loading SE LL UL
Attitudes
Attitudes - Reading, Wast of time 0.822 0.009 0.804 0.840
Attitudes - Reading, Useful furture 0.809 0.009 0.791 0.828
Behavior - Enjoy Reading 0.743 0.009 0.726 0.760
Behavior - Reading 0.476 0.013 0.450 0.501
Behavioral Engagement
Behavior - Media Use 0.323 0.017 0.290 0.355
Metacognition - Understanding 0.343 0.016 0.311 0.374
Metacognition - Self-evaluation 0.721 0.010 0.702 0.741
Metacognition - Planning 0.783 0.009 0.765 0.802
Metacognition - Sumarizing 0.760 0.010 0.740 0.779
Metacognition - Assesing credibility 0.394 0.016 0.363 0.425
Intention
Intentions - Learn 0.801 0.009 0.783 0.818
Intentions - Master materials 0.882 0.007 0.869 0.895
Intentions - Understand 0.858 0.008 0.843 0.874
Perceived Control
Perceived Control Positive 0.893 0.020 0.853 0.933
Perceived Control Negative 0.581 0.019 0.543 0.619
Subjective Norms
Norms Clasroom - Teacher Support 0.614 0.013 0.589 0.639
Norms Clasroom - Teacher Directed Instruction 0.568 0.014 0.541 0.596
Norms Clasroom - Student Orientation 0.753 0.010 0.733 0.773
Norms Clasroom - Formative Assessment 0.695 0.011 0.674 0.716
Norms Clasroom - Cognitive activation Exposition 0.699 0.011 0.677 0.720
Norms Clasroom - Cooperation 0.361 0.017 0.329 0.394

3.3. Predicting students’ reading intentions, behavioral engagement, and achievement

One model was conducted for predicted the structure proposed by the TPB framework for predicting reading behaviors and performance in the U.S PISA 2018. The model with all effects resulted in a SRMR = 0.061, indicating an acceptable model fit.

Direct effects of demographic control variables on outcomes

The standardized effects of gender and socioeconomic and cultural index on academic outcome (standarized scores), intentions and behavior are showed in Table 5. Results indicates that females have higher intentions to pursue learning goals in reading (\(\beta = 0.177\), p-value = 0.000), behavioral engagement (\(\beta = 0.131\), p-value = 0.000), and academic performance in reading (\(\beta = 0.067\), p-value = 0.000) when compared to males students. Also, The effect of socioeconomic and cultural status index (ESCS) was positive and statistically significant on behavioral engagement (\(\beta = 0.091\), p-value = 0.000) and reading performance (\(\beta = 0.091\), p-value = 0.307), respectively. However, findings suggested that intentions are not statistically moderate by ESCS (\(\beta = 0.003\), p-value = 0.824).

Table 5. Direct Standardized Effects of Gender and Socioeconomic Status on Reading Performance
95% CI
Variable Estimate SE p-value LL UL
Intentions
Student Gender (1 = Female) 0.177 0.015 0.000 0.147 0.206
Economic, social and cultural status index 0.003 0.016 0.824 -0.027 0.034
Behavioral Engagement
Student Gender (1 = Female) 0.131 0.015 0.000 0.101 0.161
Economic, social and cultural status index 0.091 0.016 0.000 0.060 0.122
Reading Performance
Student Gender (1 = Female) 0.067 0.014 0.000 0.040 0.095
Economic, social and cultural status index 0.307 0.013 0.000 0.282 0.333

Direct effects of demographic control variables on outcomes

The SEM results of the direct and indirect standardized regression coefficients whit 95% of CI, controlled by gender and socioeconomic and cultural status index, are presented in Table 6. Subjective norms (\(\beta = 0.274\)) and Perceived Behavioral (\(\beta\) = 0.103) have a direct and significant effect on intentions to pursue learning goals in reading and future careers in post-secondary education. However, Attitudes did not show any significant effect on students’ intentions (\(\beta\) = 0.040, p-value =0.069).

The direct effects of perceived behavioral control (\(\beta\) = 0.317) and intentions (\(\beta\) = 0.272) on behavioral engagement with reading were positive and statistically significant. Finally, behavioral engagement was directly related to reading performance (\(\beta\) = 0.215). The indirect effects of the attitude determinants on reading performance through intentions was not statistically significant (\(\beta\) = 0.013, p-value = 0.075). In contrast, positive and significant effects of perceived behavioral control and subjective norms on behavioral engagement with reading activities through intentions were observed. Moreover, the indirect effect of perceived behavioral control and subjective norms on reading performance through intentions and behavior (i.e., multiple mediators) was statistically significant. In contrast, the specific indirect effect of attitudes on reading performance through intentions and behavior was not statistically significant (\(\beta\) = 0.003, p-value=0.076). Furthermore, the indirect effect of intentions on reading performance through Behavior Engagement with reading activities was significant (\(\beta\) = 0.068). Finally, the specific indirect effect of perceived behavioral control on reading performance through behavioral engagement alone (RQ4) was also positive and statistically significant (\(\beta\) = 0.058).

Table 6. SEM Results Direct and Indirect Standardized Effects
95% CI
Independent (X) Dependent (Y) Type of Effect Mediator Estimate SE p-value LL UL
Direct Effects
Attitudes Intentions Direct N/A 0.040 0.022 0.069 -0.003 0.084
Subjective Norms Intentions Direct N/A 0.274 0.019 0.000 0.238 0.310
Perceived Behavioral Intentions Direct N/A 0.103 0.025 0.000 0.055 0.152
Intentions Behavioral Engagement Direct N/A 0.317 0.018 0.000 0.281 0.352
Perceived Behavioral Behavioral Engagement Direct N/A 0.272 0.022 0.000 0.229 0.315
Behavioral Engagement Reading Performance Direct N/A 0.215 0.017 0.000 0.182 0.248
Indirect Effects
Attitudes Behavioral Engagement Indirect Intentions 0.013 0.007 0.075 -0.001 0.027
Subjective Norms Behavioral Engagement Indirect Intentions 0.087 0.009 0.000 0.070 0.104
Perceived Behavioral Behavioral Engagement Indirect Intentions 0.033 0.008 0.000 0.018 0.048
Attitudes Reading Performance Indirect Intentions, Behavior 0.003 0.002 0.076 0.000 0.006
Subjective Norms Reading Performance Indirect Intentions, Behavior 0.019 0.002 0.000 0.014 0.023
Perceived Behavioral Reading Performance Indirect Intentions, Behavior 0.007 0.002 0.000 0.004 0.010
Perceived Behavioral Reading Performance Indirect Behavior 0.058 0.008 0.000 0.043 0.074
Intentions Reading Performance Indirect Behavior 0.068 0.006 0.000 0.057 0.079

4. Discussion

Using a structural equation modeling approach, the goal of this study was to use the Theory of Planned Behavior to apply to the domain of reading behavior attitudes to predict reading performance. Overall, the results indicate that the TBP is an adequate theoretical framework for predicting U.S high school students reading performance, as measured by PISA 2018. Similar results were also observed by Gjicali et al. (2021) using data from PISA 2012 and mathematics performance as the main domain. Overall, all research questions were supported for previous analysis, even after controlling by gender and socioeconomic and cultural status index. The structural model results were consistent in the directional and significance of intentions factors regarding subjective norms and perceived control. However, attitudes showed a non-significant effect. As expected, the direct effects of intentions and perceived behavioral control on behavior and the direct effect of behavior on mathematics performance were positive and statistically significant. Furthermore, mediation analyses indicated that the attitudes did not indirectly affect behavioral engagement and academic performance in reading mediated by intentions and intentions and behavioral engagement, respectively.

In summary, the results suggest that: (1) attitude toward reading has a no significant relation to academic outcomes, (2) social norms have an overall positive effect on academic outcomes, and (3) self-efficacy and control beliefs have the strongest effect on reading behaviors, and (4) behavioral engagement is a predictor of achievement. These results could have important implications for instruction and support students’ academic performance because they suggest that reducing social pressures, increasing self-efficacy, and explicitly teaching effective reading-related behaviors in the classroom could improve academic performance in reading.

Some important limitations should be considered in future research. First, the lack of use of a complete methodological design of the PISA data survey (weights and plausible values) need to be taken into account to improve the estimation of effects. Also, the omitted variables bias is a concern, and the use of composite scores to represent items (parcel items). Future studies require improving the estimation of indicators, such as IRT methods, and conducting invariance analysis to check the consistency of models across different groups (gender and race/ethnic).

References

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human DecisionProcesses, 50(2), 179–211.

Ajzen, I. (2005). Attitudes, personality, and behavior. McGraw-Hill Education (UK).

Ajzen, I., & Madden, T. J. (1986). Prediction of goal-directed behavior-attitudes, intentions, and perceived behavioral-control. Journal of Experimental Social Psychology, 22(5), 453–474

Burrus, J., & Moore, R. (2016). The incremental validity of beliefs and attitudes for predicting mathematics achievement. Learning and Individual Differences, 50, 246–251.

Enders, C., & Bandalos, D. (2001). The relative performance of full information maximum likelihood estimation for missing data in structural equation models. Structural Equation Modeling, 8(3), 430–457.

Gjicali, K. & Lipnevich, A. (2021) Got math attitude? (In)direct effects of student mathematics attitudes on intentions, behavioral engagement, and mathematics performance in the U.S. PISA. Contemporary Educational Psychology 67.

Masaki Matsunaga (2008) Item Parceling in Structural Equation Modeling: A Primer, Communication Methods and Measures, 2:4, 260-293, DOI: 10.1080/19312450802458935

Oakhill, Jane & Cain, Kate. (2012). The Precursors of Reading Ability in Young Readers: Evidence From a Four-Year Longitudinal Study. Scientific Studies of Reading. 16. 91-121. 10.1080/10888438.2010.529219.

Appendix

Table A1. Correlation Matrix
Variable 1 2 3 4 5 6 7 8 9
  1. Economic, social and cultural status index
1.00 0.34 0.14 0.14 0.07 0.11 0.09 0.17 0.01
  1. Reading Performance
0.34 1.00 0.33 0.27 0.09 0.16 0.04 0.16 -0.05
  1. Attitudes - Reading, Wast of time
0.14 0.33 1.00 0.66 0.07 0.10 0.37 0.08 -0.03
  1. Attitudes - Reading, Useful furture
0.14 0.27 0.66 1.00 0.04 0.14 0.40 0.10 0.03
  1. Attitudes - School
0.07 0.09 0.07 0.04 1.00 0.20 0.02 0.09 0.05
  1. Attitude Motivation - Mastery Achievement
0.11 0.16 0.10 0.14 0.20 1.00 0.15 0.21 0.16
  1. Behavior - Reading
0.09 0.04 0.37 0.40 0.02 0.15 1.00 0.27 0.11
  1. Behavior - Media Use
0.17 0.16 0.08 0.10 0.09 0.21 0.27 1.00 0.13
  1. Metacognition - Understanding
0.01 -0.05 -0.03 0.03 0.05 0.16 0.11 0.13 1.00
  1. Metacognition - Self-evaluation
0.14 0.16 0.16 0.24 0.08 0.25 0.20 0.22 0.28
  1. Metacognition - Planning
0.09 0.17 0.18 0.21 0.11 0.27 0.20 0.22 0.24
  1. Metacognition - Sumarizing
0.12 0.27 0.22 0.23 0.12 0.29 0.20 0.23 0.23
  1. Metacognition - Assesing credibility
0.11 0.16 0.11 0.11 0.04 0.18 0.14 0.19 0.20
  1. Perceived Control Positive
0.24 0.36 0.35 0.34 0.09 0.21 0.21 0.20 0.08
  1. Perceived Control Negative
0.18 0.34 0.29 0.21 0.09 0.12 0.10 0.07 -0.05
  1. Norms Clasroom - Environment
-0.10 -0.20 -0.12 -0.11 -0.09 -0.14 -0.06 -0.04 -0.04
  1. Norms Clasroom - Teacher Support
0.04 0.07 0.08 0.08 0.13 0.15 0.08 0.09 0.08
  1. Norms Clasroom - Teacher Directed Instruction
-0.02 -0.07 0.03 0.04 0.10 0.12 0.12 0.12 0.13
  1. Norms Clasroom - Student Orientation
0.08 0.12 0.09 0.11 0.11 0.19 0.09 0.12 0.12
  1. Norms Clasroom - Formative Assessment
0.06 0.05 0.08 0.10 0.09 0.16 0.15 0.13 0.12
  1. Norms Clasroom - Cognitive activation Comparison
0.06 -0.08 0.01 0.05 0.03 0.08 0.10 0.11 0.09
  1. Norms Clasroom - Cognitive activation Reflecting
0.05 -0.05 0.02 0.04 0.05 0.10 0.11 0.14 0.11
  1. Norms Clasroom - Cognitive activation Exposition
0.15 0.20 0.15 0.19 0.08 0.19 0.15 0.17 0.10
  1. Norms Clasroom - Cognitive activation Writing
0.00 -0.16 -0.03 -0.02 0.04 0.08 0.12 0.11 0.12
  1. Norms - Parents
0.14 0.11 0.05 0.06 0.17 0.26 0.05 0.11 0.08
  1. Norms Clasroom - Competence
0.14 0.10 0.03 0.06 0.04 0.17 0.08 0.15 0.10
  1. Norms Clasroom - Cooperation
0.09 0.05 0.03 0.06 0.09 0.23 0.12 0.14 0.15
Table A1. Correlation Matrix (Continued)
Variable 10 11 12 13 14 15 16 17 18
  1. Economic, social and cultural status index
0.14 0.09 0.12 0.11 0.24 0.18 -0.10 0.04 -0.02
  1. Reading Performance
0.16 0.17 0.27 0.16 0.36 0.34 -0.20 0.07 -0.07
  1. Attitudes - Reading, Wast of time
0.16 0.18 0.22 0.11 0.35 0.29 -0.12 0.08 0.03
  1. Attitudes - Reading, Useful furture
0.24 0.21 0.23 0.11 0.34 0.21 -0.11 0.08 0.04
  1. Attitudes - School
0.08 0.11 0.12 0.04 0.09 0.09 -0.09 0.13 0.10
  1. Attitude Motivation - Mastery Achievement
0.25 0.27 0.29 0.18 0.21 0.12 -0.14 0.15 0.12
  1. Behavior - Reading
0.20 0.20 0.20 0.14 0.21 0.10 -0.06 0.08 0.12
  1. Behavior - Media Use
0.22 0.22 0.23 0.19 0.20 0.07 -0.04 0.09 0.12
  1. Metacognition - Understanding
0.28 0.24 0.23 0.20 0.08 -0.05 -0.04 0.08 0.13
  1. Metacognition - Self-evaluation
1.00 0.58 0.52 0.30 0.17 0.05 -0.12 0.13 0.15
  1. Metacognition - Planning
0.58 1.00 0.61 0.25 0.20 0.11 -0.12 0.15 0.15
  1. Metacognition - Sumarizing
0.52 0.61 1.00 0.31 0.22 0.13 -0.15 0.16 0.14
  1. Metacognition - Assesing credibility
0.30 0.25 0.31 1.00 0.16 0.08 -0.07 0.08 0.07
  1. Perceived Control Positive
0.17 0.20 0.22 0.16 1.00 0.52 -0.09 0.09 0.08
  1. Perceived Control Negative
0.05 0.11 0.13 0.08 0.52 1.00 -0.12 0.07 0.04
  1. Norms Clasroom - Environment
-0.12 -0.12 -0.15 -0.07 -0.09 -0.12 1.00 -0.23 -0.17
  1. Norms Clasroom - Teacher Support
0.13 0.15 0.16 0.08 0.09 0.07 -0.23 1.00 0.66
  1. Norms Clasroom - Teacher Directed Instruction
0.15 0.15 0.14 0.07 0.08 0.04 -0.17 0.66 1.00
  1. Norms Clasroom - Student Orientation
0.19 0.17 0.19 0.11 0.16 0.09 -0.22 0.49 0.42
  1. Norms Clasroom - Formative Assessment
0.17 0.16 0.18 0.08 0.15 0.11 -0.19 0.39 0.40
  1. Norms Clasroom - Cognitive activation Comparison
0.14 0.10 0.04 0.05 0.04 -0.02 -0.02 0.11 0.19
  1. Norms Clasroom - Cognitive activation Reflecting
0.15 0.12 0.09 0.04 0.06 -0.01 -0.07 0.14 0.19
  1. Norms Clasroom - Cognitive activation Exposition
0.26 0.23 0.26 0.13 0.20 0.14 -0.25 0.44 0.41
  1. Norms Clasroom - Cognitive activation Writing
0.11 0.09 0.04 0.02 0.00 -0.07 0.00 0.06 0.14
  1. Norms - Parents
0.13 0.14 0.18 0.08 0.16 0.11 -0.12 0.17 0.15
  1. Norms Clasroom - Competence
0.14 0.11 0.12 0.13 0.15 0.06 0.04 0.04 0.05
  1. Norms Clasroom - Cooperation
0.23 0.17 0.20 0.12 0.08 0.03 -0.23 0.24 0.23
Table A1. Correlation Matrix (Continued)
Variable 19 20 21 22 23 24 25 26 27
  1. Economic, social and cultural status index
0.08 0.06 0.06 0.05 0.15 0.00 0.14 0.14 0.09
  1. Reading Performance
0.12 0.05 -0.08 -0.05 0.20 -0.16 0.11 0.10 0.05
  1. Attitudes - Reading, Wast of time
0.09 0.08 0.01 0.02 0.15 -0.03 0.05 0.03 0.03
  1. Attitudes - Reading, Useful furture
0.11 0.10 0.05 0.04 0.19 -0.02 0.06 0.06 0.06
  1. Attitudes - School
0.11 0.09 0.03 0.05 0.08 0.04 0.17 0.04 0.09
  1. Attitude Motivation - Mastery Achievement
0.19 0.16 0.08 0.10 0.19 0.08 0.26 0.17 0.23
  1. Behavior - Reading
0.09 0.15 0.10 0.11 0.15 0.12 0.05 0.08 0.12
  1. Behavior - Media Use
0.12 0.13 0.11 0.14 0.17 0.11 0.11 0.15 0.14
  1. Metacognition - Understanding
0.12 0.12 0.09 0.11 0.10 0.12 0.08 0.10 0.15
  1. Metacognition - Self-evaluation
0.19 0.17 0.14 0.15 0.26 0.11 0.13 0.14 0.23
  1. Metacognition - Planning
0.17 0.16 0.10 0.12 0.23 0.09 0.14 0.11 0.17
  1. Metacognition - Sumarizing
0.19 0.18 0.04 0.09 0.26 0.04 0.18 0.12 0.20
  1. Metacognition - Assesing credibility
0.11 0.08 0.05 0.04 0.13 0.02 0.08 0.13 0.12
  1. Perceived Control Positive
0.16 0.15 0.04 0.06 0.20 0.00 0.16 0.15 0.08
  1. Perceived Control Negative
0.09 0.11 -0.02 -0.01 0.14 -0.07 0.11 0.06 0.03
  1. Norms Clasroom - Environment
-0.22 -0.19 -0.02 -0.07 -0.25 0.00 -0.12 0.04 -0.23
  1. Norms Clasroom - Teacher Support
0.49 0.39 0.11 0.14 0.44 0.06 0.17 0.04 0.24
  1. Norms Clasroom - Teacher Directed Instruction
0.42 0.40 0.19 0.19 0.41 0.14 0.15 0.05 0.23
  1. Norms Clasroom - Student Orientation
1.00 0.55 0.12 0.14 0.51 0.07 0.16 0.07 0.24
  1. Norms Clasroom - Formative Assessment
0.55 1.00 0.15 0.16 0.48 0.10 0.16 0.09 0.22
  1. Norms Clasroom - Cognitive activation Comparison
0.12 0.15 1.00 0.47 0.16 0.43 0.06 0.07 0.08
  1. Norms Clasroom - Cognitive activation Reflecting
0.14 0.16 0.47 1.00 0.20 0.47 0.07 0.07 0.12
  1. Norms Clasroom - Cognitive activation Exposition
0.51 0.48 0.16 0.20 1.00 0.07 0.16 0.11 0.26
  1. Norms Clasroom - Cognitive activation Writing
0.07 0.10 0.43 0.47 0.07 1.00 0.04 0.04 0.08
  1. Norms - Parents
0.16 0.16 0.06 0.07 0.16 0.04 1.00 0.13 0.22
  1. Norms Clasroom - Competence
0.07 0.09 0.07 0.07 0.11 0.04 0.13 1.00 0.18
  1. Norms Clasroom - Cooperation
0.24 0.22 0.08 0.12 0.26 0.08 0.22 0.18 1.00
Table A2. Standarized Factors Loading CFA Models 1 and 2
Model 1
Model 2
Variable Loading SE Loading SE
Attitudes
Attitudes - Reading, Wast of time 0.794 0.013 0.801 0.016
Attitudes - Reading, Useful furture 0.824 0.013 0.829 0.015
Attitudes - School 0.105 0.018 NA NA
Attitude Motivation - Mastery Achievement 0.207 0.018 NA NA
Subjective Norms
Norms Clasroom - Teacher Support 0.693 0.013 0.719 0.013
Norms Clasroom - Teacher Directed Instruction 0.678 0.014 0.685 0.014
Norms Clasroom - Student Orientation 0.695 0.012 0.714 0.012
Norms Clasroom - Formative Assessment 0.649 0.012 0.653 0.012
Norms Clasroom - Cognitive activation Comparison 0.278 0.018 NA NA
Norms Clasroom - Cognitive activation Reflecting 0.312 0.018 NA NA
Norms Clasroom - Cognitive activation Exposition 0.671 0.011 0.670 0.012
Norms Clasroom - Cognitive activation Writing 0.208 0.019 NA NA
Norms - Parents 0.272 0.017 NA NA
Norms Clasroom - Competence 0.149 0.018 NA NA
Norms Clasroom - Cooperation 0.378 0.016 0.357 0.016
Norms Clasroom - Working in Groups 0.208 0.018 NA NA
Perceived Control
Perceived Control Positive 0.892 0.021 0.892 0.022
Perceived Control Negative 0.582 0.020 0.582 0.020
Intention
Intentions - Complete Post-Secondary 0.248 0.017 NA NA
Intentions - Learn 0.802 0.009 0.801 0.009
Intentions - Master materials 0.880 0.007 0.881 0.007
Behavioral Engagement
Intentions - Understand 0.859 0.008 0.859 0.008
Behavior - Reading 0.361 0.018 0.359 0.018
Behavior - Media Use 0.341 0.017 0.338 0.017
Metacognition - Understanding 0.338 0.016 0.338 0.016
Metacognition - Self-evaluation 0.710 0.010 0.710 0.010
Metacognition - Planning 0.760 0.010 0.762 0.010
Metacognition - Sumarizing 0.749 0.010 0.750 0.010
Metacognition - Assesing credibility 0.398 0.016 0.398 0.016
Behavior - Enjoy Reading 0.308 0.020 0.306 0.020