The Power of Giving Feedback and Receiving Feedback in Peer Assessment

Despite well-documented promises of peer assessment, it is still unclear how peer as-sessment works and what contributes to students\u2019 learning gains. In order to identify cognitive processes that lead to learning enhancement, this study examined 41 stu-dents\u2019 responses to online surveys and also their online written interactions when they participated in a peer assessment activity. Data analysis revealed that students were en-gaged in various learning processes in the phases of giving and receiving feedback. While students acknowledged that both phases contributed to their learning, a greater number of students indicated that they perceived more learning benefits from giving feedback rather than receiving feedback. Interpretations and implications were dis-cussed

Calibrating nonconvex penalized regression in ultra-high dimension

We investigate high-dimensional nonconvex penalized regression, where the number of covariates may grow at an exponential rate. Although recent asymptotic theory established that there exists a local minimum possessing the oracle property under general conditions, it is still largely an open problem how to identify the oracle estimator among potentially multiple local minima. There are two main obstacles: (1) due to the presence of multiple minima, the solution path is nonunique and is not guaranteed to contain the oracle estimator; (2) even if a solution path is known to contain the oracle estimator, the optimal tuning parameter depends on many unknown factors and is hard to estimate. To address these two challenging issues, we first prove that an easy-to-calculate calibrated CCCP algorithm produces a consistent solution path which contains the oracle estimator with probability approaching one. Furthermore, we propose a high-dimensional BIC criterion and show that it can be applied to the solution path to select the optimal tuning parameter which asymptotically identifies the oracle estimator. The theory for a general class of nonconvex penalties in the ultra-high dimensional setup is established when the random errors follow the sub-Gaussian distribution. Monte Carlo studies confirm that the calibrated CCCP algorithm combined with the proposed high-dimensional BIC has desirable performance in identifying the underlying sparsity pattern for high-dimensional data analysis.Comment: Published in at http://dx.doi.org/10.1214/13-AOS1159 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

A unified variance-reduced accelerated gradient method for convex optimization

We propose a novel randomized incremental gradient algorithm, namely, VAriance-Reduced Accelerated Gradient (Varag), for finite-sum optimization. Equipped with a unified step-size policy that adjusts itself to the value of the condition number, Varag exhibits the unified optimal rates of convergence for solving smooth convex finite-sum problems directly regardless of their strong convexity. Moreover, Varag is the first accelerated randomized incremental gradient method that benefits from the strong convexity of the data-fidelity term to achieve the optimal linear convergence. It also establishes an optimal linear rate of convergence for solving a wide class of problems only satisfying a certain error bound condition rather than strong convexity. Varag can also be extended to solve stochastic finite-sum problems.Comment: 33rd Conference on Neural Information Processing Systems (NeurIPS 2019

Service providers' adherence to methadone maintenance treatment protocol in China.

BACKGROUND:Methadone maintenance treatment (MMT) programs have expanded rapidly in China during the last decade. However, variance in service providers' practice may have an impact on the quality of care received by the patients. This study examined Chinese service providers' adherence to the MMT protocol and its associated factors. METHODS:The study used baseline data from a randomized intervention trial implemented in MMT clinics in five provinces of China. The data were collected from January 2012 to August 2013. A total of 418 service providers from 68 MMT clinics participated in the study. Demographic and job-related characteristics were collected. The providers' adherence to the MMT protocol, MMT knowledge, negative attitudes towards people who use drugs (PWUD), and perceived institutional support were assessed. RESULTS:The average adherence score was 36.7 ± 4.3 (out of 9-45). Fewer providers adhered to the protocol items where communications with patients or families were required. After controlling for potential confounders, adherence to the MMT protocol was positively associated with perceived institutional support (standardized β = 0.130; p = 0.0052), and negatively associated with prejudicial attitudes towards PWUD (standardized β = -0.357; p < 0.0001). Reception of national-level MMT training was not associated with higher level of adherence to protocol. CONCLUSION:The findings suggest the potential benefits of providing institutional support to MMT providers to enhance their level of adherence to the MMT protocol. Intervention effort is needed to reduce negative attitudes towards PWUD among MMT service providers to achieve greater consistency with best-practice recommendations