107 research outputs found
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
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Document Cohesion Flow: Striving towards Coherence
Text cohesion is an important element of discourseprocessing. This paper presents a new approach to modeling,quantifying, and visualizing text cohesion using automatedcohesion flow indices that capture semantic links amongparagraphs. Cohesion flow is calculated by applyingCohesion Network Analysis, a combination of semanticdistances, Latent Semantic Analysis, and Latent DirichletAllocation, as well as Social Network Analysis. Experimentsperformed on 315 timed essays indicated that cohesion flowindices are significantly correlated with human ratings of textcoherence and essay quality. Visualizations of the globalcohesion indices are also included to support a more facileunderstanding of how cohesion flow impacts coherence interms of semantic dependencies between paragraphs
ReaderBench: An Integrated Cohesion-Centered Framework
Dascalu, M., Stavarache, L.L., Dessus, P., Trausan-Matu, S., McNamara, D.S., & Bianco, M. (2015). ReaderBench: An Integrated Cohesion-Centered Framework. In G. Conole, T. Klobucar, C. Rensing, J. Konert & Ă. LavouĂ© (Eds.), 10th European Conf. on Technology Enhanced Learning (pp. 505â508). Toledo, Spain: Springer.ReaderBench is an automated software framework designed to support both students and tutors by making use of text mining techniques, advanced natural language processing, and social network analysis tools. ReaderBench is centered on comprehension prediction and assessment based on a cohesion-based representation of the discourse applied on different sources (e.g., textual materials, behavior tracks, metacognitive explanations, Computer
Supported Collaborative Learning â CSCL â conversations). Therefore, ReaderâBench can act as a Personal Learning Environment (PLE) which incorporates both individual and collaborative assessments. Besides the a priori evaluation of textual materialsâ complexity presented to learners, our system supports the identification of reading strategies evident within the learnersâ self-explanations or summaries. Moreover, ReaderBench integrates a dedicated cohesion-based module to assess participation and collaboration in CSCL conversations.This study is part of the RAGE project. The RAGE project has received funding from the European Unionâs 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
Mouth rinsing with a sweet solution increases energy expenditure and decreases appetite during 60 minutes of self-regulated walking exercise
Carbohydrate mouth rinsing can improve endurance exercise performance and is most ergogenic when exercise is completed in the fasted state. This strategy may also be beneficial to increase exercise capacity and the energy deficit achieved during moderate intensity exercise relevant to weight control when performed after an overnight fast. Eighteen healthy men (mean(SD); age 23(4)years, body mass index 23.1(2.4)kg.m-2 ) completed a familiarisation trial and three experimental trials. After an overnight fast, participants performed 60-minutes of treadmill walking at a speed that equated to a rating of perceived exertion of 13 (âfairly hardâ). Participants manually adjusted the treadmill speed to maintain this exertion. Mouth rinses for the experimental trials contained either a 6.4% maltodextrin solution with sweetener (CHO), a taste-matched placebo (PLA) or water (WAT). Appetite ratings were collected using visual analogue scales and exercise energy expenditure and substrate oxidation were calculated from online gas analysis. Increased walking distance during CHO and PLA induced greater energy expenditure compared with WAT (mean difference (90% CI); 79(60)kJ; P=0.035; d=0.24 and 90(63)kJ; P=0.024; d=0.27, respectively). Appetite area under the curve was lower in CHO and PLA than WAT (8(6)mm; P=0.042; d=0.43 and 6(8)mm; P=0.201; d=0.32, respectively). Carbohydrate oxidation was higher in CHO than PLA and WAT (7.3(6.7)g; P=0.078; d=0.47 and 10.1(6.5)g; P=0.015; d=0.81, respectively). This study provides novel evidence that mouth rinsing with a sweetened solution may promote a greater energy deficit during moderate exertion walking exercise by increasing energy expenditure and decreasing appetite. A placebo effect may have contributed to these benefits
How well do activity monitors estimate energy expenditure? A systematic review and meta-analysis
Objective: To determine the accuracy of wrist and arm-worn activity monitorsâ estimates of energy expenditure (EE).
Data sources: SportDISCUS (EBSCOHost), PubMed, MEDLINE (Ovid), PsycINFO (EBSCOHost), Embase (Ovid) and CINAHL (EBSCOHost).
Design: A random effects meta-analysis was performed to evaluate the difference in EE estimates between activity monitors and criterion measurements. Moderator analyses were conducted to determine the benefit of additional sensors and to compare the accuracy of devices used for research purposes with commercially available devices.
Eligibility criteria: We included studies validating EE estimates from wrist-worn or arm-worn activity monitors against criterion measures (indirect calorimetry, room calorimeters and doubly labelled water) in healthy adult populations.
Results: 60 studies (104 effect sizes) were included in the meta-analysis. Devices showed variable accuracy depending on activity type. Large and significant heterogeneity was observed for many devices (I2 >75%). Combining heart rate or heat sensing technology with accelerometry decreased the error in most activity types. Research-grade devices were statistically more accurate for comparisons of total EE but less accurate than commercial devices during ambulatory activity and sedentary tasks.
Conclusions: EE estimates from wrist and arm-worn devices differ in accuracy depending on activity type. Addition of physiological sensors improves estimates of EE, and research-grade devices are superior for total EE. These data highlight the need to improve estimates of EE from wearable devices, and one way this can be achieved is with the addition of heart rate to accelerometry.
PROSPEROregistration number: CRD42018085016
Concept-based topic model improvement
We propose a system which employs conceptual knowledge to improve topic models by removing unrelated words from the simplified topic description. We use WordNet to detect which topical words are not conceptually similar to the others and then test our assumptions against human judgment. Results obtained on two different corpora in different test conditions show that the words detected as unrelated had a much greater probability than the others to be chosen by human evaluators as not being part of the topic at all. We prove that there is a strong correlation between the said probability and an automatically calculated topical fitness and we discuss the variation of the correlation depending on the method and data used. © 2011 Springer-Verlag Berlin Heidelberg
Improving topic evaluation using conceptual knowledge
The growing number of statistical topic models led to the need to better evaluate their output. Traditional evaluation means estimate the model's fitness to unseen data. It has recently been proven than the output of human judgment can greatly differ from these measures. Thus the need for methods that better emulate human judgment is stringent. In this paper we present a system that computes the conceptual relevance of individual topics from a given model on the basis of information drawn from a given concept hierarchy, in this case WordNet. The notion of conceptual relevance is regarded as the ability to attribute a concept to each topic and separate words related to the topic from the unrelated ones based on that concept. In multiple experiments we prove the correlation between the automatic evaluation method and the answers received from human evaluators, for various corpora and difficulty levels. By changing the evaluation focus from a statistical one to a conceptual one we were able to detect which topics are conceptually meaningful and rank them accordingly
Automatic extraction of conceptual labels from topic models
This work outlines a novel system that automatically extracts conceptual labels for statistically obtained topics. By creating a projection of the topic, which is a distribution over all the vocabulary words, over the WordNet ontology we succeed in associating concepts to the said groups of words. The most important contributions of this paper are connected to the validation of the role of these concepts as topical labels and the determination of correlations that emerge between the utility of these labels and the strength of the relation between the concepts and the topics
Effect of dietary nitrate supplementation on swimming performance in trained swimmers
Nitrate supplementation appears to be most ergogenic when oxygen availability is restricted and subsequently may be particularly beneficial for swimming performance due to the breath-hold element of this sport. This represents the first investigation of nitrate supplementation and swimming time-trial (TT) performance.
In a randomised double-blind repeated-measures crossover study, ten (5male, 5female) trained swimmers ingested 140ml nitrate-rich (~12.5mmol nitrate) or nitrate-depleted (~0.01mmol nitrate) beetroot juice. Three hours later, subjects completed a maximal effort swim TT comprising 168m (8 x 21m lengths) backstroke.
Pre-exercise fractional exhaled nitric oxide concentration was significantly elevated with nitrate compared to placebo (17±9 vs. 7±3p.p.b., p=0.008). Nitrate supplementation had a likely trivial effect on overall swim TT performance (mean difference 1.22s; 90% CI -0.18â 2.6s; 0.93%; p=0.144; d=0.13; unlikely beneficial (22.6%), likely trivial (77.2%), most unlikely negative (0.2%)). The effects of nitrate supplementation during the first half of the TT were trivial (mean difference 0.29s; 90% CI -0.94â1.5s; 0.46%; p=0.678; d=0.05), but there was a possible beneficial effect of nitrate supplementation during the second half of the TT (mean difference 0.93s; 90% CI 0.13â1.70s; 1.36%; p=0.062; d=0.24; possibly beneficial (63.5%), possibly trivial (36.3%), most unlikely negative (0.2%)). The duration and speed of underwater swimming within the performance did not differ between nitrate and placebo (both p>0.30).
Nitrate supplementation increased nitric oxide bioavailability but did not benefit short-distance swimming performance or the underwater phases of the TT. Further investigation into the effects of nitrate supplementation during the second half of performance tests may be warranted
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