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Missing data are ubiquitous in psychological research. They may come about as an unwanted result of coding or computer error, participants' non-response or absence, or missing values may be intentional, as in planned missing designs. We discuss the effects of missing data on χ²-based goodness-of-fit indices in Structural Equation Modeling (SEM), specifically on the Root Mean Squared Error of Approximation (RMSEA). We use simulations to show that naive implementations of the RMSEA have a downward bias in the presence of missing data and, thus, overestimate model goodness-of-fit. Unfortunately, many state-of-the-art software packages report the biased form of RMSEA. As a consequence, the scientific community may have been accepting a much larger fraction of models with non-acceptable model fit. We propose a bias-correction for the RMSEA based on information-theoretic considerations that take into account the expected misfit of a person with fully observed data. The corrected RMSEA is asymptotically independent of the proportion of missing data for misspecified models. Importantly, results of the corrected RMSEA computation are identical to naive RMSEA if there are no missing data.

In this article we describe the origins of the subtests that appear on the modern Stanford-Binet Intelligence Scales (SB5), Wechsler Preschool and Primary Scale of Intelligence (WPPSI-IV), Wechsler Intelligence Scale for Children (WISC-V), and Wechsler Adult Intelligence Scale (WAIS-IV). We found that the majority of these subtest formats were first created in 1908 or earlier and that only three have been created since 1980. We discuss the implications of these findings, which are that (1) many subtests have lengthy research histories that support their use in measuring intelligence; (2) many subtests have formats that predate modern theories of test creation, cognitive psychology, and intelligence; and (3) the history of many subtests is more complex than psychologists probably realize.

A wide variety of effect size indices have been proposed for quantifying the magnitude of treatment effects in single-case designs. Commonly used measures include parametric indices such as the standardized mean difference as well as nonoverlap measures such as the percentage of nonoverlapping data, improvement rate difference, and nonoverlap of all pairs. Currently, little is known about the properties of these indices when applied to behavioral data collected by systematic direct observation, even though systematic direct observation is the most common method for outcome measurement in single-case research. This study uses Monte Carlo simulation to investigate the properties of several widely used single-case effect size measures when applied to systematic direct observation data. Results indicate that the magnitude of the nonoverlap measures and of the standardized mean difference can be strongly influenced by procedural details of the study's design, which is a significant limitation to using these indices as effect sizes for meta-analysis of single-case designs. A less widely used parametric index, the log response ratio, has the advantage of being insensitive to sample size and observation session length, although its magnitude is influenced by the use of partial interval recording. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Given significant changes to legislation, practice, research, and instrumentation, the purpose of this study was to examine the course on cognitive assessment in school psychology programs and to describe the (a) structure, (b) instructional strategies, (c) content, and (d) interpretative strategies taught to school psychology graduate students. 127 instructors were surveyed, and results suggest that over the last 20 years support for teaching cognitive assessment has decreased while the content and instructional strategies have remained largely the same. Results of this study also indicate that the interpretation strategies taught rely heavily on Cattell-Horn-Carroll theory and related interpretive frameworks (e.g., cross-battery assessment). Additionally, instructors are placing greater emphasis on and multicultural sensitivity/ culturally and linguistically diverse assessment than in previous decades. Implications for future research, training and practice are discussed.

Many prominent intelligence tests (e.g., WISC-V & RIAS-2) offer methods for computing subtest- and composite-level difference scores. This current study uses data provided in the technical manual of the Wechsler Intelligence Scale for Children, Fifth Edition (WISC-V) and Reynolds Intellectual Abilities Scale, Second Edition (RIAS-2) to calculate reliability coefficients for difference scores. Subtest-level difference score reliabilities range from 0.59 to 0.99 for the RIAS-2 and from 0.53 to 0.87 for the WISC-V. Composite-level difference score reliabilities generally range from 0.23 to 0.95 for the RIAS-2 and from 0.36 to 0.87 for the WISC-V. Emphasis is placed on comparisons recommended by test publishers and a discussion of minimum requirements for interpretation of differences scores is provided.

In the present research, we investigated the relation between changes in students’ state self-control capacity and their motivational test-taking effort over the course of an achievement test. Thereby, we considered trait self-control as a major predictor of achievement-related behavior as a covariate. N = 1,840 apprentices repeatedly rated their state self-control capacity and the test-taking effort they invested while working on a 140-minute achievement test in mathematics and science. Using growth curve analyses, our results revealed correlated decreases in state self-control capacity and the test-taking effort invested over the course of the test. Furthermore, we found that trait self-control helped to keep state self-control capacity and test-taking effort at a higher level over the course of the test. Our results support the assumption of the process model of self-control that waning self-control capacity is reflected in reduced motivational effort. Furthermore, our findings provide evidence that self-control might play a crucial role in students’ test-taking behavior in large-scale assessment studies. By modeling changes in state self-control capacity and effort investment while considering trait self-control, we provide an alternative approach for investigating self-control-dependent processes and the underlying mechanisms of self-control in achievement situations.

Research points to the positive impact that gender-segregated schooling and classroom initiatives exert on academic attainment. An evaluation of these studies which reveal positive effects highlights, however, that students are typically selectively assigned to single- or mixed-gender instructional settings, presenting a methodological confound. The current study controls for students’ prior attainment to appraise the efficacy of a single-gender classroom initiative implemented in a co-educational high school in the United Kingdom. Secondary data analysis (using archived data) was performed on 266 middle-ability, 11–12 year-old students’ standardized test scores in Languages (English, foreign language), STEM-related (Mathematics, Science, Information and Communication Technology), and Non-STEM subjects (art, music, drama). Ninety-eight students (54, 55% female) were taught in single-gender and 168 (69, 41% female) in mixed-gender classrooms. Students undertook identical tests irrespective of classroom type, which were graded in accordance with U.K national curriculum guidelines. Controlling for students’ prior attainment, findings indicate that students do not appear to benefit from being taught in single-gender relative to mixed-gender classrooms in Language and STEM-related subjects. Young women benefitted from being taught in mixed-gender relative to single-gender classes for Non-STEM subjects. However, when prior ability is not controlled for, the intervention appears to be effective for all school subjects, highlighting the confounding influence of selective admissions. These findings suggest that gender-segregated classroom initiatives may not bolster students’ grades. It is argued that studies that do not control for selection effects may tell us little about the effectiveness of such interventions on scholastic achievement. Electronic supplementary material The online version of this article (doi:10.1007/s11199-017-0799-y) contains supplementary material, which is available to authorized users.

Many children around the world grow up bilingual, learning and using two or more languages in everyday life. Currently, however, children’s language backgrounds are not always reported in developmental studies. There is mounting evidence that bilingualism interacts with a wide array of processes including language, cognitive, perceptual, brain, and social development, as well as educational outcomes. As such, bilingualism may be a hidden moderator that obscures developmental patterns, and limits the replicability of developmental research and the efficacy of psychological and educational interventions. Here, we argue that bilingualism and language experience in general should be routinely documented in all studies of infant and child development regardless of the research questions pursued, and provide suggestions for measuring and reporting children’s language exposure, proficiency, and use.

Résumé : Bien que lesprit critique soit un prérequis à bon nombre de disciplines enseignées à l’université, il est généralement difficile dintéresser les étudiants aux enseignements de méthodologie scientifique. Nous présentons deux méthodes complémentaires pour éviter cet écueil. La première consiste à présenter un faux concept scientifique, le syndrome de Bill Shankly. Les étudiants prennent généralement en note sans questionner, d’autant plus facilement que l’enseignant s’est présenté comme spécialiste mondial et a fait preuve d’autorité. La seconde méthode, utilisée en petits groupes, vise à entraîner les étudiants à vérifier les preuves et les sources. Cette approche qui allie les théories et pratiques de la psychologie sociale, cognitive, de l’apprentissage et des sciences de l’éducation, peut s’utiliser pour d’autres enseignements et disciplines.

Playing computer and video games is a popular pastime activity for many adolescents worldwide. However, the increasing amount of time spent on these games each day raised fears that this comes at the expense of school and, over the long run, impairs academic achievement. Extending prior research, the present study on a sample of N = 3,554 German adolescents (56% girls) adopted a prospective design and examined the effects of the time playing computer games each day on grades and domain-specific competences in mathematics and reading over time. Robust polynomial regressions combined with specification curve analyses showed that longer gaming times predicted worse grades two years later. These results could be replicated after controlling for initial grades and reasoning abilities. In contrast, mathematical and reading competences were not affected by gaming times. Thus, playing computer and video games can result in a noticeably, albeit small, loss of educational returns, but it does not affect basic competences.

The global Higher Education sector (HE) is undergoing a metamorphosis. No longer is HE the sole preserve of the privileged few but rather it is now accessible for the masses. The result of such an expansionist philosophy is here and today’s undergraduate students can expect to study at a university that is unrecognisable to higher education establishments of a few decades ago. This is not a one-sided affair and academic staff i.e., the professoriate who encounter the results of such expansionism on a daily basis are also faced with a vastly complex working environment (see e.g., Knight & Senior, 2017). Phrases such as internationalisation, employability, work-based learning as well as the almost ephemeral notion of student satisfaction, among many other things, regular assail the collective consciousness of academic staff around the world. Yet despite such complexity a new model is emerging and this is one firmly embedded within consumer psychology and it firmly places the student as a customer. Here we highlight some negative issues that may arise when HE embraces consumerism. We also discuss a potential solution that may not only ameliorate these issues but actually facilitate excellence in the student learning journeys. Higher education can meet this vast array of modern day concepts face-to-face and still ensure that it serves its core mission and that is to provide students with a higher understanding of various conceptual issues.

Paper details and compares 6 different modifications to the k-means algorithm on simulated data and applies disparate algorithms to a college risk behavior dataset to understand risk groups among college populations. Study was MS thesis at University of Miami, 2014.

Important advances in understanding traumatic stress reactions in children and young people have been made in recent years. The aim of this review was to synthesise selected recent research findings, with a focus on their relevance to clinical practice. We therefore address: findings on the epidemiology of trauma exposure and Posttraumatic Stress Disorder (PTSD); recent changes to diagnostic classification; implications for screening and assessment of traumatic stress reactions; and treatment outcome studies including interventions for acute and chronic PTSD, dissemination of effective treatments into community settings, and early interventions. We conclude with recommendations for clinical practice and suggestions for future areas of research.

As a result of the U.S. government’s involvement in Native American education, the current experiences of Native American college students are characterized by educational disparities. Higher education professionals are in an ideal position to meet the needs and interests of Native American students; however, most of the literature concerning this population takes a deficit approach. The present paper offers a reconceptualization of Bronfenbrenner’s ecological systems model as an alternative framework for the experiences of Native American college students. In privileging historical and cultural factors, this reconceptualization demonstrates how transforming educational institutions could influence the experiences of Native American college students.

We present evidence for the strengths of the intellectual virtues that philosophers and behavioral scientists characterize as key cognitive elements of wisdom. Wisdom has been of centuries-long interest for philosophical scholarship, but relative to intelligence largely neglected in public discourse on educational science, public policy, and societal well-being. Wise reasoning characteristics include intellectual humility, recognition of uncertainty, consideration of diverse viewpoints, and an attempt to integrate these viewpoints. Emerging scholarship on these features of wisdom suggest that they uniquely contribute to societal well-being, improve leadership, shed light on societal inequality, promote cooperation in Public Goods Games and reduce political polarization and intergroup-hostility. We review empirical evidence about macro-cultural, ecological, situational, and person-level processes facilitating and inhibiting wisdom in daily life. Based on this evidence, we speculate about ways to foster wisdom in education, organizations, and institutions.

Fluency is an essential feature of skilled reading. Reading speed is an overt reflection of automaticity in decoding and similarly deft control over other component skills. There is considerable support for oral reading speed as a valid and reliable indicator of general reading skill. In fluent reading, whether oral or silent, processes of word recognition, comprehension, and eye movement control must be tightly coordinated, as characterized in several implemented models of eye movements over print (Reichle et al., 2013; Reilly & Radach, 2006; Engbert et al., 2005). Oral reading, in addition to those requirements shared with silent reading, places an additional demand on the reader: the need to produce accurate, prosodically appropriate speech in conjunction with the reading process itself. Both oral and silent reading rely not only on good control of component processes, but also on facile coordination of those processes (Berninger et al., 2001; Breznitz, 2003). Rapid automatized naming (RAN) is another fluencylike predictor of reading skills (see Bowey, 2005; Kirby et al., 2010; Hulme & Snowling, 2012; Cutting & Scarborough, 2006; Wolf et al., 2000). RAN’s task demands overlap considerably with reading, especially oral reading (Denckla & Rudel, 1974). Yet, the nature of the connections between the two capabilities remains uncertain. This research exploits commonalities between reading and RAN to help resolve uncertainties in their causes. We do so by working toward a unified, theoretical account of performance across tasks. Our main purpose is not to explain RAN as such, but a model of reading fluency that explicitly handles RAN will have distinct advantages over one that does not. It will be constrained by the need to accommodate both tasks, and so may provide insight into relationships between the two that will prove helpful in refining practical uses of RAN as a reading assessment. Our approach is two-fold. First, we will assess relationships among oral and silent reading, and standard indicators of reading skillin three critical periods in the development of skilled reading: a learning-to-read group (7-8yo), a transition-to-fluency group (10-11yo), and a full-literacy group (17-18yo). We will evaluate developmental differences between groups and individual differences within groups. We will apply new ways to investigate RAN performance and oral and silent reading fluency derived from analysis of gaze behavior, and of asynchronies in gaze and speech behaviors produced during these tasks (Jones et al., 2008). We make novel use of speech processing technology to facilitate alignment of speech and gaze signals to accommodate the large volume of speech data generated by the project. Second, we will implement a unified model of coordination among component processes for oral and silent reading(Reichle et al., 2009; Reichle, Pollatsek, et al., 2012). A successful unified model will serve as a testbed for investigating structural relationships among oral and silent reading, RAN and component skills.

Attempting recall of information from memory, as occurs when taking a practice test, is one of the most potent training techniques known to learning science. However, does testing yield learning that transfers to different contexts? In the present article, we report the findings of the first comprehensive meta-analytic review into that question. Our review encompassed 192 transfer effect sizes extracted from 122 experiments and 67 published and unpublished articles (N = 10,382) comprising over 40 years of research. A random-effects model revealed that testing can yield transferrable learning as measured relative to a non-testing reexposure control condition (d = 0.40, 95% CI [0.31, 0.50]). That transfer of learning is greatest across test formats, to application and inference questions, to problems involving medical diagnoses, and to mediator and related word cues; it is weakest to rearranged stimulus-response items, to untested materials seen during initial study, and to problems involving worked examples. Moderator analyses further indicated that response congruency and elaborated retrieval practice, as well as initial test performance, strongly influence the likelihood of positive transfer. In two assessments for publication bias (using PET-PEESE and various selection methods), the moderator effect sizes were minimally affected. However, the intercept predictions were substantially reduced, often indicating no positive transfer when none of the aforementioned moderators are present. Overall, our results motivate a three-factor framework for transfer of test-enhanced learning and have practical implications for the effective use of practice testing in educational and other training contexts.

With the advent of computers in education, and the ample availability of online learning and practice environments, enormous amounts of data on learning become available. The purpose of this paper is to present a decade of experience with analyzing and improving an online practice environment for math, which has thus far recorded over a billion responses. We present the methods we use to both steer and analyze this system in real-time, using scoring rules on accuracy and response times, a tailored rating system to provide both learners and items with current ability and difficulty ratings, and an adaptive engine that matches learners to items. Moreover, we explore the quality of fit by means of prediction accuracy and parallel item reliability. Limitations and pitfalls are discussed by diagnosing sources of misfit, like violations of unidimensionality and unforeseen dynamics. Finally, directions for development are discussed, including embedded learning analytics and a focus on online experimentation to evaluate both the system itself and the users’learning gains. Though many challenges remain open, we believe that large steps have been made in providing methods to efficiently manage and research educational big data from a massive online learning system.

Given the shortfall in students studying science, promotion of motivation and engagement in science education is a priority. The current study applied the trans-contextual model to study the motivational predictors of participation in science learning activities in secondary-school students. In a three-wave prospective design, secondary-school students completed measures of perceived autonomy support, autonomous and controlled motivation, social-cognitive beliefs (attitudes, subjective norms, perceived control), intentions, and self-reported participation in out-of-school science learning activities. Five-weeks later, students self-reported their science learning activities. Students’ averaged science grades over the semester period were obtained. Bayesian path analyses supported model hypotheses: in-school autonomous motivation predicted out-of-school autonomous motivation, beliefs, intentions, science activity participation, and science grades. Specifying informative priors in the Bayesian analysis yielded greater precision in estimates. Findings provide initial evidence of a link between students’ autonomous motivation toward science activities across contexts and may inform interventions promoting motivation and participation in science activities.

Conspiracy theories play a troubling role in political discourse, yet the motivations of conspiracy endorsers can be obscure to outsiders. Online forums provide a valuable window into the day-to-day discourse of conspiracy theorizing, but one that is difficult to quantify. We used non-negative matrix factorization to create a topic model of the r/conspiracy forum on Reddit.com. This subreddit provides a large and unique corpus which spans many years and numerous authors. We show that within the forum, there are multiple sub-populations distinguishable by their topic loading. Further, these differences are readily interpretable as differences in background beliefs and motivations. These groups regularly interact with one another by commenting; hence topic modeling reveals subgroups that would not be revealed by simple network analyses. The diversity of the distinct subgroups places constraints on theories of what generates conspiracy theorizing: neither simple irrationality nor common preoccupations of topics seem to fit the bill. Instead, we suggest, conspiracy theorizing seems to be primarily driven by higher-order preoccupations with evidence and argument, along with rhetorical strategies which allow diverse groups to each address any particular theme.

Studies of highly and profoundly gifted children typically involve small sample sizes, as the population is relatively rare, and many statistical methods cannot handle these small sample sizes well. However, topological data analysis (TDA) tools are robust, even with very small samples, and can provide useful information as well as robust statistical tests.This study demonstrates these capabilities on data simulated from previous talent search results (small and large samples), as well as a subset of data from Ruf’s cohort of gifted children. TDA methods show strong, robust performance and uncover insight into sample characteristics and subgroups, including the appearance of similar subgroups across assessment populations.

Students who have better relationships with their peers and teachers are more likely to be motivated to engage in learning activities. The aim of the present study was to introduce the application of a novel methodological approach in order to explore plausible mechanisms with which teachers’ perceived approach to multiculturalism influences student motivation in relation to students’ peer relationships. We constructed psychological network models, using existing data, to map out multicultural classroom interactions. We conclude that teachers’ approach to multiculturalism might constitute a distal (main) factor of influence on both ethnic majority and minority students’ motivation. In addition, social integration might constitute a more proximate (more immediate) factor of influence for ethnic minority group children, signaling a possible process of mediation. The hypothesis generating nature of our study speaks to the need for further investigating the influence of teachers’ approach to multiculturalism on student motivation in relation to social integration.

Previous research suggests that metacognitive learning strategies and beliefs may predict success in online learn-ing, but little research has explored specific belief scales for this context. This paper examines how students’ beliefs about learning predict course performance, satisfaction, and openness to feedback in both a massive open online course and an online experiment. An abbreviated Learning Beliefs scale based on previous scales was developed and tested. Study 1 found that Learning Beliefs significantly predicted 125 participants’ positive attitudes towards an online cognitive task, as well as their perception that feedback on their performance was helpful. Study 2 tested the Learning Beliefs scale in an online course with 171 participants, finding that Learning Beliefs predicted course performance and enjoyment. These studies suggest that even a brief metacognitive scale can provide meaningful information about online learners. These findings highlight the benefits of understanding how online students’ learning beliefs impact their course success.

Using a person-centered analysis, we identified adaptive and maladaptive procrastination styles associated with academic and alcohol outcomes in a sample of 1106 college undergraduates. Productive procrastination is defined by the replacement of one adaptive behavior with another adaptive—albeit less important—behavior (e.g., organizing notes instead of studying for an exam). Cluster analysis identified five unique academic procrastination styles—non-procrastinators, academic productive procrastinators, non-academic productive procrastinators, non-academic procrastinators (high levels of unproductive and productive non-academic procrastination) and classic procrastinators. Controlling for gender, procrastination style predicted alcohol-related problems, risk of alcohol use disorders, and GPA (all ps < .01). Academic productive procrastinators and non-procrastinators reported the most positive academic and alcohol outcomes. Non-academic procrastinators reported lower GPA, more alcohol-related problems and increased risk of alcohol use disorders. Non-academic procrastinators’ lower GPA was mediated by alcohol cravings and alcohol-related problems, as measured by AUDIT and RAPI scores. These findings suggest that certain maladaptive styles of procrastination may be a useful risk indicator for preventative and intervention efforts.