Validating the Automated Assessment of Participation and of Collaboration in Chat Conversations

International audienceAs Computer Supported Collaborative Learning (CSCL) gains a broader usage as a viable alternative to classic educational scenarios, the need for automated tools capable of supporting tutors in the time consuming process of analyzing conversations becomes more stringent. Moreover, in order to fully explore the benefits of such scenarios, a clear demarcation must be made between participation or active involvement, and collaboration that presumes the intertwining of ideas or points of view with other participants. Therefore, starting from a cohesion-based model of the discourse, we propose two computational models for assessing collaboration and participation. The first model is based on the cohesion graph and can be perceived as a longitudinal analysis of the ongoing conversation, thus accounting for participation from a social knowledge-building perspective. In the second approach, collaboration is regarded from a dialogical perspective as the intertwining or overlap of voices pertaining to different speakers, therefore enabling a transversal analysis of subsequent discussion slices

Finding the Needle in a Haystack: Who are the Most Central Authors Within a Domain?

The speed at which new scientific papers are published has increased dramatically, while the process of tracking the most recent publications having a high impact has become more and more cumbersome. In order to support learners and researchers in retrieving relevant articles and identifying the most central researchers within a domain, we propose a novel 2-mode multilayered graph derived from Cohesion Network Analysis (CNA). The resulting extended CNA graph integrates both authors and papers, as well as three principal link types: coauthorship, co-citation, and semantic similarity among the contents of the papers. Our rankings do not rely on the number of published documents, but on their global impact based on links between authors, citations, and semantic relatedness to similar articles. As a preliminary validation, we have built a network based on the 2013 LAK dataset in order to reveal the most central authors within the emerging Learning Analytics domain.This study is part of the RAGE project. The RAGE project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 644187. This publication reflects only the author's view. The European Commission is not responsible for any use that may be made of the information it contains

Identification of temperature profile and heat transfer on a dielectric membrane for gas sensors by `COSMOS' program simulation

The application of commercial 3-D software `COSMOS' for the design and thermal analysis of the low power consumption test structures with dielectric membrane for gas microsensors is presented. Within this work, the simulation provides the estimation of the temperature profile on the active area and the whole membrane including the four bridges and the heating efficiency in the temperature range 20-500 °C. Unravelling of the heat loss mechanisms in terms of radiation, convection, conduction by air and solid materials during heat transfer on the dielectric membrane is reported for the first time as a mean to evaluate by 3-D simulation the contribution of technological processes and lay-out design to the total heat losses

Studii privind comportarea unor soiuri de mar cultivate in ferma horticola „V. Adamachi” Iasi

Apple is the species which occupy in temperated areas first place as volume of production and surfaces. In the period 2013-2015 were performed biometric measurements on three apple varieties (Idared, Generos and Florina), planted in intensive system from horticultural farm "V. Adamachi" Iaş

A simple model of ac hopping surface conductivity in ionic liquids

The boundary conditions proposed to discuss the charge exchange taking place in an ionic liquid in contact with non-blocking electrodes are reconsidered in a dynamic situation. Assuming that the variation of the bulk ionic current density depends linearly on the surface value of the ionic current density, the frequency dependence of the phenomenological parameter is determined. The analysis has been performed in the framework where the relaxation times are smaller than a maximum relaxation time τM, and that the response function is independent on the value of the relaxation time. Using simple physical considerations, an expression for the surface conductivity describing the ionic charge exchange at the electrode is obtained. According to our calculations, its frequency dependence is similar to that predicted for the electric conductivity in disordered materials when the mechanism is of the hopping type. From measurements of impedance spectroscopy, by the best fit of the experimental data, the temperature dependence of the hopping time, of the dc surface conductivity, and of the diffusion coefficient are derived. They are in good agreement with the theoretical predictions obtained with the random distribution of surface energy barrier. Keywords: Ionic liquids, Non-blocking electrodes, Electrical impedance spectroscopy, AC hopping surface conductivit

Classification of Russian textbooks by grade level and topic using ReaderBench

This article analyzes automated methods for classifying Russian-language textbooks in two dimensions, and precisely on the topic of the text and its complexity, reflected by the corresponding school level (class

Discourse complexity: driving forces of the new paradigm

In the article, the authors investigate what makes the text difficult for a certain category of readers, thereby expanding the object of research from " text" to "text and reader", or, more specifically, "alignment of text and reader". Texts are examined for complexity, i.e. features of the text that affect its understandin

MELPF version 1: Modeling Error Learning based Post-Processor Framework for Hydrologic Models Accuracy Improvement

This paper studies how to improve the accuracy of hydrologic models using machine-learning models as postprocessors and presents possibilities to reduce the workload to create an accurate hydrologic model by removing the calibration step. It is often challenging to develop an accurate hydrologic model due to the time-consuming model calibration procedure and the nonstationarity of hydrologic data. Our findings show that the errors of hydrologic models are correlated with model inputs. Thus motivated, we propose a modeling-error-learning-based post-processor framework by leveraging this correlation to improve the accuracy of a hydrologic model. The key idea is to predict the differences (errors) between the observed values and the hydrologic model predictions by using machine-learning techniques. To tackle the nonstationarity issue of hydrologic data, a moving window-based machine-learning approach is proposed to enhance the machine-learning error predictions by identifying the local stationarity of the data using a stationarity measure developed based on the Hilbert–Huang transform. Two hydrologic models, the Precipitation–Runoff Modeling System (PRMS) and the Hydrologic Modeling System (HEC-HMS), are used to evaluate the proposed framework. Two case studies are provided to exhibit the improved performance over the original model using multiple statistical metrics