Comparing students’ self-discipline and self-regulation measures and their prediction of academic achievement

Using a multi-source, multi-measure research design involving 507 high school students and their teachers, we compared prediction of these students’ academic achievement by a composite of students’ and teachers’ measures of students’ self-regulation (SR) with a composite of students’ and teachers’ measures of students’ self-discipline (SD). Hierarchical regression analyses revealed that the SR composite was more predictive of students’ grade point average and performance on a state-wide achievement test than the SD composite. Confirmatory factor analyses showed that, although SD and SR latent factors correlated significantly, a two-factor solution provided an acceptable fit for the results. Structural Equation Modeling analyses indicated that the SR latent factor predicted both measures of students’ achievement significantly, but the SD factor did not predict either achievement measure significantly. No significant gender differences were found with students’ SD, SR, or achievement measures. These results suggest a path for integrating two relatively separate streams in self-regulation research on the basis of a well-established distinction between learning and performance processes.     

Oral Language and Reading in Bilingual Children

This article examines the question: Do lexical, syntactic, fluency, and discourse measures of oral language collected under narrative conditions predict reading achievement both within and across languages for bilingual children? More than 1,500 Spanish–English bilingual children attending kindergarten–third grade participated. Oral narratives were collected in each language along with measures of Passage Comprehension and Word Reading Efficiency. Results indicate that measures of oral language in Spanish predict reading scores in Spanish and that measures of oral language skill in English predict reading scores in English. Cross‐language comparisons revealed that English oral language measures predicted Spanish reading scores and Spanish oral language measures predicted English reading scores beyond the variance accounted for by grade. Results indicate that Spanish and English oral language skills contribute to reading within and across languages.     

The neuropsychology of Down syndrome: evidence for hippocampal dysfunction

This study tested prefrontal and hippocampal functions in a sample of 28 school-aged (M = 14.7 years, SD = 2.7) individuals with Down syndrome (DS) compared with 28 (M = 4.9 years, SD = .75) typically developing children individually matched on mental age (MA). Both neuropsychological domains were tested with multiple behavioral measures. Benchmark measures of verbal and spatial function demonstrated that this DS sample was similar to others in the literature. The main finding was a significant Group x Domain interaction effect indicating differential hippocampal dysfunction in the group with DS. However, there was a moderate partial correlation (r = .54, controlling for chronological age) between hippocampal and prefrontal composite scores in the DS group, and both composites contributed unique variance to the prediction of MA and adaptive behavior in that group. In sum, these results indicate a particular weakness in hippocampal functions in DS in the context of overall cognitive dysfunction. It is interesting that these results are similar to what has been found in a mouse model of DS. Such a model will make it easier to understand the neurobiological mechanisms that lead to the development of hippocampal dysfunction in DS.     

Moving Beyond the Brag Sheet: A Meta-Analysis of Biodata Measures Predicting Student Outcomes

Measures of biographical data, or biodata, provide indicators of one's life history and past experiences. Biodata information is often available in various forms during processes of academic admissions to higher education. Such information can be used, in combination with other factors, to predict students’ future academic and extra-curricular accomplishments. There is a scattered body of literature investigating relationships between standardized biodata measures and a number of student criteria in college. The current study uses meta-analysis methods to summarize findings on how various biodata measures—overall scores or scale scores—predict student accomplishments, including grades, self- and other-rated performances, persistence, and extracurricular accomplishments. Data from 46 independent samples, consisting of 38,478 students and resulting in 74 individual predictor–criterion relationships were analyzed. Results indicate, generally, that biodata measures predict substantially students’ academic and extra-curricular accomplishments. Overall biodata scores correlate with grades at .39, persistence at .25, and point-hour ratios at .35. Students’ accomplishments in leadership, visual and performing arts, music, and science were predicted best by biodata measures developed specifically to target those outcomes. This meta-analytic study provides support for the predictive validity of biographical data inventories with respect to student outcomes and adds justification to the use of biodata in academic selection.     

Kindergarten Predictors of Math Learning Disability

The aim of the present study was to address how to effectively predict mathematics learning disability (MLD). Specifically, we addressed whether cognitive data obtained during kindergarten can effectively predict which children will have MLD in third grade, whether an abbreviated test battery could be as effective as a standard psychoeducational assessment at predicting MLD, and whether the abbreviated battery corresponded to the literature on MLD characteristics. Participants were 226 children who enrolled in a 4‐year prospective longitudinal study during kindergarten. We administered measures of mathematics achievement, formal and informal mathematics ability, visual‐spatial reasoning, and rapid automatized naming and examined which test scores and test items from kindergarten best predicted MLD at grades 2 and 3. Statistical models using standardized scores from the entire test battery correctly classified ～80–83 percent of the participants as having, or not having, MLD. Regression models using scores from only individual test items were less predictive than models containing the standard scores, except for models using a specific subset of test items that dealt with reading numerals, number constancy, magnitude judgments of one‐digit numbers, or mental addition of one‐digit numbers. These models were as accurate in predicting MLD as was the model including the entire set of standard scores from the battery of tests examined. Our findings indicate that it is possible to effectively predict which kindergartners are at risk for MLD, and thus the findings have implications for early screening of MLD.     

Cross‐time attitudes,concept formation,and achievement in college freshman physics

The relationships among science and engineering attitude, physics conceptual understanding, and physics achievement were explored for a population of college freshman engineering students over two semesters. Gender and SAT‐Quantitative measures were included as exogenous variables in a longitudinal path analysis. Attitude was theorized to predict achievement contemporaneously and at the next time point, while conceptual understanding was theorized to predict physics achievement contemporaneously and at the next time point. Each at one time was theorized to predict scores at the next time. A sample of 200 freshman engineering students participating in an integrated curriculum were assessed in September, December, and April (with a loss of 64 students) with the Force Concepts Inventory (FCI), Mechanics Baseline Test (MBT), and a locally developed attitude measure. The observed model indicated that the FCI predicted attitude at time 1 with no other paths between them, that FCI at time 1 predicted MBT at time 1 and time 2, FCI at time 2 predicted MBT at time 3, and MBT at time 1 predicted FCI at time 2. Gender and SAT‐Quantitative scores were predictive only of FCI and MBT at time 1. Results supported an interactive model of conceptual understanding and achievement, with attitude largely irrelevant to the process for this population. © 2000 John Wiley & Sons, Inc. J Res Sci Teach 37: 1112–1120, 2000     

Do organizational variables influence satisfaction with nursing student practices?

Clinical practices are a vital component in the education of registered nursing students. This study analyzed the influence of organizational variables on satisfaction with clinical practices. A cross-sectional study design involved 572 registered nursing students. Two statistical methodologies, hierarchical regression models and qualitative comparative analysis of diffuse sets, were used for data analysis. In the hierarchical regression models the number of students supervised predicted satisfaction with clinical educator (β = -.22; p ≤ .001), environment (β = -.13; p ≤ .05) and overall satisfaction (β = -.15; p ≤ .05). However, in the qualitative comparative analysis, the type of center, as well as the number of services assigned to the clinical educator and the number of students per clinical educator period were conditions that influence satisfaction with clinical practices. The type of center and the clinical educator are key factors related to registered nursing students’ satisfaction with clinical practices.     

Predictors of Hispanic School Teachers' Self-efficacy in the Pedagogical Uses of Technology

A study to predict teachers' self-efficacy in using technology for pedagogical purposes was conducted in a predominantly Hispanic school district in south Texas; 438 elementary teachers completed a 32-item survey aligned to the National Educational Technology Standards for Teachers. Findings suggested that the instrument is highly reliable in measuring Hispanic school teachers' self-efficacy when they are asked to rate their confidence in their ability to perform technology tasks for educational purposes. An exploratory factor analysis (orthogonal and nonorthogonal) allowed the derivation of composite measures. Three subscales regarding issues of pedagogy composed the dependent variable. Regression analyses (OLS and 2SLS) revealed that two derived composite measures and two contrast variables listed in the general information of the survey strongly predicted the response variable.     

The influence of student experiences on post-graduation surveys

This study attempts to establish the extent to which in-class teaching quality instruments can be used to predict post-graduation survey results. It examines the responses for the Good Teaching Scale of the Course Experience Questionnaire administered to 10,433 students who completed their studies at a major Australian tertiary institution from 2003 to 2005 using a unique data-set that matched student records and measures of class characteristics to the individual survey responses. The findings indicate that the overall degree experiences of particular students can be predicted by measures of class differences as measured by teaching quality instruments and the grade distributions of the classes they completed. These factors are in addition to the effects of students’ own performance as measured by their grades, their field of study and their post-graduation experience. It was found that in-class administered teaching quality instruments have an asymmetric influence on post-graduation survey results. Higher than expected scores appear to have little impact, and lower than expected results were found to have a significant negative impact on post-graduation recollections. The grade distribution in classes taken was also found to be an important factor in explaining variation in degree satisfaction.     

Prediction of College Major Persistence Based on Vocational Interests, Academic Preparation, and First-Year Academic Performance

We hypothesized that college major persistence would be predicted by first-year academic performance and an interest-major composite score that is derived from a student’s entering major and two work task scores. Using a large data set representing 25 four-year institutions and nearly 50,000 students, we randomly split the sample into an estimation sample and a validation sample. Using the estimation sample, we found major-specific coefficients corresponding to the two work task scores that optimized the prediction of major persistence. Then, we applied the estimated coefficients to the validation sample to form an interest-major composite score representing the likelihood of persisting in entering major. Using the validation sample, we then tested a theoretical model for major persistence that incorporated academic preparation, the interest-major composite score, and first-year academic performance. The results suggest that (1) interest-major fit and first-year academic performance work to independently predict whether a student will stay in their entering major and (2) the relative importance of two work task scores in predicting major persistence depends on the entering major. The results support Holland’s theory of person-environment fit and suggest that academic performance and interest-major fit are key constructs for understanding major persistence behavior.     

Subgroups of adult basic education learners with different profiles of reading skills

The purpose of this study was to identify subgroups of adult basic education (ABE) learners with different profiles of skills in the core reading components of decoding, word recognition, spelling, fluency, and comprehension. The analysis uses factor scores of those 5 reading components from on a prior investigation of the reliability and construct validity of measures of reading component skills (MacArthur, Konold, Glutting, & Alamprese, 2010). In that investigation, confirmatory factor analysis found that a model with those 5 factors fit the data best and fit equally well for native and non-native English speakers. The study included 486 students, 334 born or educated in the United States (native) and 152 not born nor educated in the US (non-native) but who spoke English well enough to participate in English reading classes. The cluster analysis found an 8-cluster solution with good internal cohesion, external isolation, and replicability across subsamples. Of the 8 subgroups, 4 had relatively flat profiles (range of mean scores across factors <0.5 SD), 2 had higher comprehension than decoding, and 2 had higher decoding than comprehension. Profiles were consistent with expectations regarding demographic factors. Non-native speakers were overrepresented in subgroups with relatively higher decoding and underrepresented in subgroups with relatively higher comprehension. Adults with self-reported learning disabilities were overrepresented in the lowest performing subgroup. Older adults and men were overrepresented in subgroups with lower performance. The study adds to the limited research on the reading skills of ABE learners and, from the perspective of practice, supports the importance of assessing component skills to plan instruction.     

TAKING A “SIMPLE VIEW” OF THE DYNAMIC INDICATORS OF BASIC EARLY LITERACY SKILLS AS A PREDICTOR OF MULTIPLE MEASURES OF THIRD‐GRADE READING COMPREHENSION

The purpose of this study was to examine the validity evidence of first‐grade Dynamic Indicators of Basic Early Literacy Skills (DIBELS) scores for predicting third‐grade reading comprehension scores. We used the “simple view” of reading as the theoretical foundation for examining the extent to which DIBELS subtest scores predict comprehension through both word recognition and language comprehension. Scores from the DIBELS Oral Reading Fluency (ORF) subtest, a measure of word recognition speed and accuracy, strongly and significantly predicted multiple measures of reading comprehension. No other DIBELS subtest score explained additional variance beyond DIBELS ORF. Although experimental DIBELS Word Use Fluency (WUF) was significantly correlated with a language comprehension measure and measures of reading comprehension, WUF scores did not predict reading comprehension beyond ORF scores. Alternatively, first‐grade Peabody Picture Vocabulary Test scores did predict additional, significant variance in reading comprehension, beyond DIBELS ORF.     

Kindergarten screening results as predictors of academic achievement,potential, and placement in second grade

The ability of a battery of kindergarten screening measures to predict educationally relevant criteria was investigated. Subtest scores on The Vane Test of Language and The Vane Kindergarten Test administered at the beginning of kindergarten were examined and compared to the Metropolitan Achievement Test scores in reading and math, The Otis-Lennon School Ability Test index, and placement into special education or high achievement programs at the end of second grade. A weighted combination of subtests accurately predicted 77% of the children classified as special education students. The same battery also predicted 73% of the children who were classified as high-achieving students.     

Psychometric properties of a youth self-report measure of neglectful behavior by parents

Objective

This study aimed to empirically assess psychometric properties of a multi-dimensional youth self-report measure of neglectful behavior by parents.

Method

Data were gathered from 593 12-year-old youth participating in the Longitudinal Studies of Child Abuse and Neglect (LONGSCAN) consortium; 272 also had data at age 14. Youth responded to a 25-item measure of their experiences of neglect. Expert raters classified items into 4 factors, followed by confirmatory factor analyses. We evaluated cross group measurement equivalence by gender and longitudinal measurement equivalence from age 12 to age 14. Validity was assessed by the relationships between factor scores and (1) neglect reports to child protective services (CPS), (2) quality of parent-child interactions, and (3) parental monitoring.

Results

A 3-factor model (Physical Needs, Emotional Support, and Parental Monitoring) of neglect was obtained, with equivalence across gender and longitudinally (age 12-14). The pattern of correlations between the factor scores, CPS reports, and measures of the parent-child relationship offered modest to moderate support for convergent validity.

Conclusions

The findings suggest a promising and relatively brief youth self-report measure of neglect to help advance research in this area.     

Using structural equation modeling techniques to evaluate HIV risk models

Structural equation modeling (SEM) techniques were used to compare 5 methods of assessing HIV/AIDS sexual risk in a large prediction model. These were: (a) multiple measures; (b) a single latent factor; (c) modifying the computation of the dependent variables used in Methods 1 and 2 to weight sexual encounters by specific partner risk; (d) use of risk composites, obtained by multiplying number of sexual partners by number of occasions of unprotected sex; and (e) use of risk indexes that assign a number based on responses to general questions about risk behaviors. Data from 452 at‐risk women from a New England community were analyzed in 5 versions of an HIV/AIDS sexual risk prediction model. Models were compared in terms of SEM empirical fit indexes (x² [df], average absolute standardized residuals, and Comparative Fit Index); significant paths, explained variance, theoretical fit, and simplicity. Results indicate that: (a) multiple measures and latent factor models are preferable to all others by each of the standards of comparison, (b) in the composite dependent variable models, including information about the partners' number of partners provided little additional explained variance beyond knowing the number of occasions of unprotected sex, and (c) dependent measures that did not remain close to Centers for Disease Control criteria may not be adequately predicting HIV/AIDS sexual risk. Several recommendations are presented for selecting an appropriate conceptualization of HIV/AIDS sexual risk.     

Interpersonal problem solving and children's social competence: Are current measures valid?

Ninety-four first- and second-grade students participated in a study designed to determine whether a measure of interpersonal problem-solving skill would predict the social competence of children with no clinical history. The social competence measures used in the study included peer ratings (sociometric scores) and teacher ratings. The interpersonal problem-solving measure used yielded three separate scores obtained from ratings of open-ended responses to hypothetical peer problems. To enable control of other variables known to affect social competence, measures of IQ, academic achievement, and SES also were included. Results did not confirm a prior expectation that problem-solving scores would correlate well with competence measures. Correlations between the three problem-solving scores and both peer and teacher ratings all were in the range between .04 and .20. On the other hand, intelligence, achievement, and SES had moderate to high correlations with competence measures (range = .04–.77). In stepwise multiple regressions, only achievement and SES predicted peer and teacher ratings when other variables were controlled.     

The visual Aural digit span test and Bender gestalt test as predictors of wide range achievement test-revised scores

Visual Aural Digit Span Test (VADS) scores and Bender Gestalt Test (BG) scores as predictors of Wide Range Achievement Test-Revised (WRAT-R) scores were examined in this study. The sample consisted of 115 children referred for low academic achievement. They were divided into three age groups: (Low) 6–0 to 7–11; (Middle) 8–0 to 9–11; and (High) 10–0 to 11–11. The scores on the 11 VADS measures and BG errors were used to predict the WRAT-R achievement. The VADS Test scores were found to predict Reading and Arithmetic in the Low Group. The BG Test did not correlate with achievement in the Low Group. In the Middle Group, the VADS Test correlated with Reading and Spelling, but not with Arithmetic. The BG correlated with all three achievement measures. In the High Group, neither the VADS Test nor BG correlated with any of the achievement measures. The results suggest that the BG and VADS Test can be used as an effective screening device for young children with potential learning problems.     

Precision Teaching and Fluency Training: Making maths easier for pupils and teachers

A 12-week programme was designed for five children in a primary class (9-10 years of age) who were failing to keep pace with their peers in the maths curriculum. The programme drew on principles of precision teaching and emphasised fluency training in the component skills required for the performance of a composite maths skill. The class teacher identified a target composite skill, and the five children's scores were compared before and after the programme, and compared with the rest of the class. On post-programme measures, the precision teaching children out-performed all but one of their peers on the target skill. This paper adds to a growing database demonstrating the importance of fluency training and frequent monitoring of children's progress (fundamentals of precision teaching). It also shows that expensive and time-consuming additional resources are not required to successfully implement such programmes.     

Measurement invariance of the ICT engagement construct and its association with students’ performance in China and Germany: Evidence from PISA 2015 data

The present study investigated the factor structure of and measurement invariance in the information and communication technology (ICT) engagement construct, and the relationship between ICT engagement and students’ performance on science, mathematics and reading in China and Germany. Samples were derived from the Programme for International Student Assessment (PISA) 2015 survey. Configural, metric and scalar equivalence were found in a multigroup exploratory structural equation model. In the regression model, a significantly positive association between interest in ICT and student achievement was found in China, in contrast to a significantly negative association in Germany. All achievement scores were negatively and significantly correlated with perceived ICT competence scores in China, whereas science and mathematics achievement scores were not predicted by scores on ICT competence in Germany. Similar patterns were found in China and Germany in terms of perceived autonomy in using ICT and social relatedness in using ICT to predict students’ achievement. The implications of all the findings were discussed.     

The effects of achievement goals and self-regulated learning behaviors on reading comprehension in technology-enhanced learning environments

Studies examining students’ achievement goals, cognitive engagement strategies and performance have found that achievement goals tend to predict classes of cognitive strategy use which predict performance on measures of learning. These studies have led to deeper theoretical understanding, but their reliance on self-report data limit the conclusions that can be drawn. We employed a behavioral approach instead and assessed learning processes by logging learners’ behaviors as they used educational technology. We examined the relationship between achievement goals, strategy use, and comprehension scores of 160 undergraduates who studied a hypertext passage in a technology-enhanced learning environment (TELE) equipped with tools that support learning behaviors including highlighting, taking notes, review of annotations, seeking additional information and monitoring understanding. Results of a path analysis indicated that higher mastery goals predicted more information-seeking and note-taking and marginally more monitoring of learning. Performance avoidance goals negatively predicted note-taking and information-seeking. Performance approach goals did not predict the behaviors we traced. Of the behaviors we traced, highlighting and monitoring predicted increases in comprehension scores. A behavioral approach to assessing learning processes confirmed only a subset of paths from achievement goals to learning processes to learning outcomes originally discovered with self-report data.