Chilean Teachers' Reading
Description
This dataset contains responses from 385 Chilean educators who participated in a study validating a Title Recognition Test (TRT) designed to objectively measure print exposure among adults. The TRT includes 55 book titles: 40 real titles and 15 foils (fake titles). For each title (variables tit1 to tit40 and foil1 to foil15), participants indicated whether they recognized it (1 = recognized, 0 = not recognized). Final TRT scores (trt_z) were computed by summing recognized valid titles from a validated 19-item subset and subtracting two points per foil falsely identified, then standardizing the result. Valid items were: tit1 tit2 tit3 tit8 tit9 tit10 tit11 tit17 tit18 tit23 tit28 tit33 tit34 tit35 tit36 tit37 tit38 tit39 tit40. Additional variables capture participants’ self-reported reading motivation (mot_z), reading frequency (frecuencia_z), and books read in the past 12 months (volumen_z), all standardized as z-scores. Demographic and professional information includes sex, school type (school_type), role in school (role_group), year of birth, and years of in-service experience. Subject specialization is indicated by dummy variables (e.g., subj_lang_social, subj_stem_tech). This dataset supports analyses of print exposure and reading habits in relation to educators' professional roles and school contexts. Variable labels correspond to book titles or descriptive survey items. The dataset is suitable for Item Response Theory modeling, group comparisons, and correlational analyses exploring the relationship between objective and self-reported reading measures.
Files
Steps to reproduce
To replicate the analyses presented in our study, follow these steps: Access the dataset: Download the anonymized dataset trt_prof_all.dta from Mendeley Data [DOI pending]. Software requirements: Analyses were conducted using Stata 18. Ensure you have Stata 15 or later installed to ensure compatibility with factor variables and graphics used. Variable labeling (optional): If importing the dataset without embedded labels, label each tit and foil variable using the corresponding book title (a complete labeling script is available in the supplementary materials). Reconstruct composite variables (already included in dataset as z-scores): TRT Score: Sum of 19 valid real titles marked as recognized, minus 2 points for each foil falsely recognized. Reading Motivation, Frequency, Volume, and Uninterrupted Reading: Already standardized (variables mot_z, frecuencia_z, volumen_z, sinpausa_z). Descriptive analyses: Use summarize and tabstat commands to compute group-wise means and standard deviations by school type, role, subject area, and sex. Statistical comparisons: Use ttest for two-group comparisons (e.g., by sex). Use anova for multi-group comparisons when assumptions of normality and homogeneity of variance are met. Use kwallis for ordinal or non-parametric comparisons when assumptions are not met. IRT analysis (optional replication): To reproduce the IRT validation of the TRT, use R (packages: ltm, mirt, or TAM) or dedicated IRT software. Only real titles were submitted to IRT modeling; DIF analysis was performed across sex and school type to remove biased items. Graphics: Wright Map and group comparison plots were generated in R. Code is available upon request.