A meta-analysis of the effectiveness of intelligent tutoring systems on college students' academic learning

© 2013 American Psychological Association.This meta-analysis synthesizes research on the effectiveness of intelligent tutoring systems (ITS) for college students. Thirty-five reports were found containing 39 studies assessing the effectiveness of 22 types of ITS in higher education settings. Most frequently studied were AutoTutor, Assessment and Learning in Knowledge Spaces, eXtended Tutor-Expert System, and Web Interface for Statistics Education. Major findings include (a) Overall, ITS had a moderate positive effect on college students' academic learning (g = .32 to g = .37); (b) ITS were less effective than human tutoring, but they outperformed all other instruction methods and learning activities, including traditional classroom instruction, reading printed text or computerized materials, computer-assisted instruction, laboratory or homework assignments, and no-treatment control; (c) ITS's effectiveness did not significantly differ by different ITS, subject domain, or the manner or degree of their involvement in instruction and learning; and (d) effectiveness in earlier studies appeared to be significantly greater than that in more recent studies. In addition, there is some evidence suggesting the importance of teachers and pedagogy in ITS-assisted learning

Short-term efficacy and usage recommendations for a large-scale implementation of the math-whizz tutor

This paper adds to the evidence of the efficacy of intelligent tutoring systems (ITS) in mathematics learning by evaluating a large-scale intervention at the state of Aguascalientes, Mexico. We report the results of a quasi-experimental study, addressing at the same a particular request of the decision-makers responsible for the rollout to provide, from early stages of the intervention, independent evidence of the efficacy of Math-Whizz Tutor beyond its internal metrics, and recommendations in terms of the expected weekly usage levels to guide the blended learning approach

Cryptococcus neoformans Capsular Enlargement and Cellular Gigantism during Galleria mellonella Infection

We have studied infection of Cryptococcus neoformans in the non-vertebrate host Galleria mellonella with particular interest in the morphological response of the yeast. Inoculation of C. neoformans in caterpillars induced a capsule-independent increase in haemocyte density 2 h after infection. C. neoformans manifested a significant increase in capsule size after inoculation into the caterpillar. The magnitude of capsule increase depended on the temperature, being more pronounced at 37°C than at 30°C, which correlated with an increased virulence of the fungus and reduced phagocytosis at 37°C. Capsule enlargement impaired phagocytosis by haemocytes. Incubation of the yeast in G. mellonella extracts also resulted in capsule enlargement, with the polar lipidic fraction having a prominent role in this effect. During infection, the capsule decreased in permeability. A low proportion of the cells (<5%) recovered from caterpillars measured more than 30 µm and were considered giant cells. Giant cells recovered from mice were able to kill the caterpillars in a manner similar to regular cells obtained from in vivo or grown in vitro, establishing their capacity to cause disease. Our results indicate that the morphological transitions exhibited by C. neoformans in mammals also occur in a non-vertebrate host system. The similarities in morphological transitions observed in different animal hosts and in their triggers are consistent with the hypothesis that the cell body and capsular responses represent an adaptation of environmental survival strategies to pathogenesis

Prediction Tools for Unfavourable Outcomes in Clostridium difficile Infection: A Systematic Review

CONTEXT: Identifying patients at risk for adverse outcomes of Clostridium difficile infection (CDI), including recurrence and death, will become increasingly important as novel therapies emerge, which are more effective than traditional approaches but very expensive. Clinical prediction rules (CPRs) can improve the accuracy of medical decision-making. Several CPRs have been developed for CDI, but none has gained a widespread acceptance. METHODS: We systematically reviewed studies describing the derivation or validation of CPRs for unfavourable outcomes of CDI, in medical databases (Medline, Embase, PubMed, Web of Science and Cochrane) and abstracts of conferences. RESULTS: Of 2945 titles and abstracts screened, 13 studies on the derivation of a CPR were identified: two on recurrences, five on complications (including mortality), five on mortality alone and one on response to treatment. Two studies on the validation of different severity indices were also retrieved. Most CPRs were developed as secondary analyses using cohorts assembled for other purposes. CPRs presented several methodological limitations that could explain their limited use in clinical practice. Except for leukocytosis, albumin and age, there was much heterogeneity in the variables used, and most studies were limited by small sample sizes. Eight models used a retrospective design. Only four studies reported the incidence of the outcome of interest, even if this is essential to evaluate the potential usefulness of a model in other populations. Only five studies performed multivariate analyses to adjust for confounders. CONCLUSIONS: The lack of weighing variables, of validation, calibration and measures of reproducibility, the weak validities and performances when assessed, and the absence of sensitivity analyses, all led to suboptimal quality and debatable utility of those CPRs. Evidence-based tools developed through appropriate prospective cohorts would be more valuable for clinicians than empirically-developed CPRs

DPHL: A DIA Pan-human Protein Mass Spectrometry Library for Robust Biomarker Discovery

To address the increasing need for detecting and validating protein biomarkers in clinical specimens, mass spectrometry (MS)-based targeted proteomic techniques, including the selected reaction monitoring (SRM), parallel reaction monitoring (PRM), and massively parallel data-independent acquisition (DIA), have been developed. For optimal performance, they require the fragment ion spectra of targeted peptides as prior knowledge. In this report, we describe a MS pipeline and spectral resource to support targeted proteomics studies for human tissue samples. To build the spectral resource, we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on Docker. We then applied the workflow to generate DPHL, a comprehensive DIA pan-human library, from 1096 data-dependent acquisition (DDA) MS raw files for 16 types of cancer samples. This extensive spectral resource was then applied to a proteomic study of 17 prostate cancer (PCa) patients. Thereafter, PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was validated. As a second application, the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma (DLBCL) patients and 18 healthy control subjects. Differentially expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker discovery. DPHL is freely accessible at https://www.iprox.org/page/project.html?id=IPX0001400000

Cryptococcus: from environmental saprophyte to global pathogen.

Cryptococcosis is a globally distributed invasive fungal infection that is caused by species within the genus Cryptococcus which presents substantial therapeutic challenges. Although natural human-to-human transmission has never been observed, recent work has identified multiple virulence mechanisms that enable cryptococci to infect, disseminate within and ultimately kill their human host. In this Review, we describe these recent discoveries that illustrate the intricacy of host-pathogen interactions and reveal new details about the host immune responses that either help to protect against disease or increase host susceptibility. In addition, we discuss how this improved understanding of both the host and the pathogen informs potential new avenues for therapeutic development