A Parametric Bootstrap Version of Hedges’ Homogeneity Test

Hedges’ Q-test is frequently used in meta-analyses to evaluate the homogeneity of effect sizes, but for several kinds of effect size measures it does not always appropriately control the Type 1 error probability. Therefore we propose a parametric bootstrap version, which shows Type 1 error control under a broad set of circumstances. This is confirmed in a small simulation study

The Children’s Loneliness Scale : factor structure and construct validity in Belgian children

The present study examined the factor structure and construct validity of the Children's Loneliness Scale (CLS), a popular measure of childhood loneliness, in Belgian children. Analyses were conducted on two samples of fifth and sixth graders in Belgium, for a total of 1,069 children. A single-factor structure proved superior to alternative solutions proposed in the literature, when taking item wording into account. Construct validity was shown by substantial associations with related constructs, based on both self-reported (e.g., depressive symptoms and low social self-esteem), and peer-reported variables (e.g., victimization). Furthermore, a significant association was found between the CLS and a peer-reported measure of loneliness. Collectively, these findings provide a solid foundation for the continuing use of the CLS as a measure of childhood loneliness

Factors influencing ICU referral at the end of life in the elderly

Referral to the intensive care unit (ICU) and frequency of do-not-resuscitate (DNR) decisions at the end of life (EOL) in adult hospitalized patients a parts per thousand yen75 years and those < 75 years were examined and influencing factors in the elderly were determined. Data were prospectively collected in all adult patients who deceased during a 12-week period in 2007 and a 16-week period in 2008 at a university hospital in Belgium. Overall, 330 adult patients died of whom 33% were a parts per thousand yen75 years old. Patients a parts per thousand yen75 years old were less often referred to ICU at the EOL (42% vs. 58%, p=0.008) and less frequently died in the ICU (31% vs. 46%, p=0.012) as compared to patients < 75 years old. However, there was no difference in frequency of DNR decisions (87% vs. 88%, p=0.937) for patients dying on non-ICU wards. After adjusting for age, gender, and the Charlson comorbidity index, being admitted on a geriatric ward (OR 0.30, 95% CI 0.10-0.85, p=0.024) and having an active malignant disease (OR 0.39, 95% CI 0.19-0.78, p=0.008) were the only factors associated with a lower risk of dying in the ICU. Patients a parts per thousand yen75 years are less often referred to the ICU at the EOL as compared to patients < 75 years old. However, the risk of dying in the ICU was only lower for elderly with cancer and for those admitted to the geriatric ward

On the Use of Bayesian Probabilistic Matrix Factorization for Predicting Student Performance in Online Learning Environments

Thanks to the advances in digital educational technology, online learning (or e-learning) environments such as Massive Open Online Course (MOOC) have been rapidly growing. In the online educational systems, however, there are two inherent challenges in predicting performance of students and providing personalized supports to them: sparse data and cold-start problem. To overcome such challenges, this article aims to employ a pertinent machine learning algorithm, the Bayesian Probabilistic Matrix Factorization (BPMF) that can enhance the prediction by incorporating background information on the side of students and/or items. An experimental study with two prediction settings was conducted to apply the BPMF to the Statistics Online data. The results shows that the BPMF with using side information provided more accurate prediction in the performance of both existing and new students on items, compared to the algorithm without using any side information. When the data are sparse, it is demonstrated that a lower dimensional solution of the BPMF would benefit the prediction accuracy. Lastly, the applicability of the BPMF to the online educational systems were discussed in the context of educational assessment.Kim, J.; Park, JY.; Van Den Noortgate, W. (2020). On the Use of Bayesian Probabilistic Matrix Factorization for Predicting Student Performance in Online Learning Environments. En 6th International Conference on Higher Education Advances (HEAd'20). Editorial Universitat Politècnica de València. (30-05-2020):751-759. https://doi.org/10.4995/HEAd20.2020.11137OCS75175930-05-202

Examining focused L2 practice: From in vitro to in vivo

Behaviour-tracking technology has been used for decades in SLA research on focused practice with an eye toward elucidating the nature of L2 automatization (e.g. DeKeyser, 1997; Robinson, 1997). This involves longitudinally capturing learners’ judgments or linguistic production along with their response times in order to investigate how specific skills become automatic over time. However, previous research in this area has been conducted mostly in laboratories (i.e., in vitro), sometimes with artificial languages, thereby compromising ecological validity of the findings. Building on this work, this article reports on a one-month study in which learners’ (N = 126) behaviour was tracked while they practised two constructions of English grammar (varying in complexity) using mini-games that involved some time pressure and were embedded in meaning-focused reading and discussion activities in class. Feedback was randomly varied between participants. Multilevel statistical analyses of accuracy and response time suggest that practice helped to develop automaticity, and that rule complexity and metalinguistic feedback played a role. The methodological innovation of this study consists of the application of in vitro experimental research techniques in in vivo L2 learning contexts and of the use of statistical mixed effects models to account for the complexity of real-life tracking data

When Easy Becomes Boring and Difficult Becomes Frustrating: Disentangling the Effects of Item Difficulty Level and Person Proficiency on Learning and Motivation.

The research on electronic learning environments has evolved towards creating adaptive learning environments. In this study, the focus is on adaptive curriculum sequencing, in particular, the efficacy of an adaptive curriculum sequencing algorithm based on matching the item difficulty level to the learner’s proficiency level. We therefore explored the effect of the relative difficulty level on learning outcome and motivation. Results indicate that, for learning environments consisting of questions focusing on just one dimension and with knowledge of correct response, it does not matter whether we present easy, moderate or difficult items or whether we present the items with a random mix of difficulty levels, regarding both learning and motivation

A meta-analysis of the efficacy of case management for substance use disorders : a recovery perspective

Background: Case management is a client-centered approach to improve the coordination and continuity of service delivery, especially for persons with substance use disorders (SUD) and multiple and complex support needs. This intervention supports individuals by helping them identify needed services, facilitate linkage with services, and promote participation and retention in services. However, it is questionable whether case management is equally effective in promoting recovery and aspects of personal functioning. The objective was to conduct an updated meta-analysis and to assess whether case management was more effective than treatment as usual (TAU) among persons with SUD for improving treatment-related (e.g., successful linkage with and retention in treatment) as well as personal functioning outcomes (e.g., substance use). Methods: This meta-analysis focuses on randomized controlled trials (RCTs) that included persons with alcohol or drug use disorders and compared case management with TAU. To be eligible, interventions had to meet core case management functions as defined in the literature. We conducted searches of the following databases to May 2017: the Cochrane Drugs and Alcohol Specialized Register, CENTRAL, PubMed, Embase, CINAHL, and Web of Science. Also, reference lists of retrieved publications were scanned for relevant (un) published studies. Results: The overall effect size for case management compared to TAU across all outcome categories and moments was small and positive (SMD = 0.18, 95% CI 0.07-0.28), but statistically significant. Effects were considerably larger for treatment tasks (SMD = 0.33, 95% CI 0.18-0.48) than for personal functioning outcomes (SMD = 0.06, 95% CI -0.02 to 0.15). The largest effect sizes were found for retention in substance abuse treatment and linkage with substance abuse services. Moderator effects of case management models and conditions were assessed, but no significant differences were observed. Conclusions: The primary results from earlier meta-analyses were supported: case management is more effective than TAU conditions for improving outcomes, but this effect is significantly larger for treatment-related tasks than for personal functioning outcomes. Case management can be an important supplement to available services for improving linkage and retention, although further research is needed to assess its potential for supporting recovery from a longitudinal perspective

Exploring burnout among preschool teachers in rural China: a job demands-resources model perspective

Rural preschool teachers are increasingly experiencing job burnout, which could lead to their intention to leave and negatively impact education quality. This research explored the prevalence of job burnout among preschool teachers in rural China. It further investigated the potential influence of job-related characteristics on their levels of burnout. This study surveyed 10,581 preschool teachers across 34 counties in 18 provinces in China, utilizing multilevel structural equation models to analyze the situation and factors influencing job burnout. The findings indicate that the situation regarding job burnout among preschool teachers is not encouraging, particularly in the western areas and independent public kindergartens. Job resources were found to be associated with a reduction in burnout, while job demands had the opposite effect. The findings also revealed that job demands served as a mediating variable between job resources and job burnout. Moreover, the results also showed that reduced job burnout among preschool teachers was related to teacher cooperation, decision making, kindergarten resources and salary. On the other hand, role commitments, business issues, and classroom management were associated with increased burnout among preschool teachers. Furthermore, the impact of demands and resources on burnout was found to be intensified by kindergarten variables. To address the issue of burnout, it is essential to recognize the diversity and heterogeneity of kindergartens and take specific measures to reduce work demands while providing adequate and specific resources. Attention should be given to diversity and integration to ensure a positive work environment that can effectively prevent job burnout among preschool teachers