Analiza complexităţii manualelor şcolare din sistemul de învăţământ francez primar

National audienceRezumat. Una din sarcinile dificile din prelucrarea limbajului natural ţine de evaluarea complexităţii sau a dificultăţii înţelegerii a textelor. Astfel, de un interes aparte sunt instrumentele de analiză automată a textelor care permit realizarea unei predicţii a complexităţii textelor pornind de la factori lexicali, sintactici, morfologici sau chiar semantici în funcţie de specificitatea abordării. Totodată, elementele de complexitate sunt dependente de context şi de domeniul de aplicare. Astfel, o analiză pur tehnică care se bazează doar pe metrici fără să ia în considerare constrângerile de psihologie, modele umane, vârstă şi motivaţia este insuficientă pentru a realiza o predicţie adecvată. În plus, alte aspecte ale analizei complexităţii sunt corelate cu etapele de achiziţie (împreună cu acurateţea şi fluenţa), corelate cu adaptarea mesajului comunicat audienţei din prisma corectitudinii, coerenţei şi adaptabilităţii la nivelul acesteia. Adiţional, metricile de complexitate textuală reprezintă indicatori importanţi de înţelegere şi coerenţă pentru texte comune întâlnite uzual în Internet, lucrări publicate şi cărţi

Analiza complexităţii manualelor şcolare din sistemul de învăţământ francez primar

National audienceRezumat. Una din sarcinile dificile din prelucrarea limbajului natural ţine de evaluarea complexităţii sau a dificultăţii înţelegerii a textelor. Astfel, de un interes aparte sunt instrumentele de analiză automată a textelor care permit realizarea unei predicţii a complexităţii textelor pornind de la factori lexicali, sintactici, morfologici sau chiar semantici în funcţie de specificitatea abordării. Totodată, elementele de complexitate sunt dependente de context şi de domeniul de aplicare. Astfel, o analiză pur tehnică care se bazează doar pe metrici fără să ia în considerare constrângerile de psihologie, modele umane, vârstă şi motivaţia este insuficientă pentru a realiza o predicţie adecvată. În plus, alte aspecte ale analizei complexităţii sunt corelate cu etapele de achiziţie (împreună cu acurateţea şi fluenţa), corelate cu adaptarea mesajului comunicat audienţei din prisma corectitudinii, coerenţei şi adaptabilităţii la nivelul acesteia. Adiţional, metricile de complexitate textuală reprezintă indicatori importanţi de înţelegere şi coerenţă pentru texte comune întâlnite uzual în Internet, lucrări publicate şi cărţi

Reflecting Comprehension through French Textual Complexity Factors

International audienceResearch efforts in terms of automatic textual complexity analysis are mainly focused on English vocabulary and few adaptations exist for other languages. Starting from a solid base in terms of discourse analysis and existing textual complexity assessment model for English, we introduce a French model trained on 200 documents extracted from school manuals pre-classified into five complexity classes. The underlying textual complexity metrics include surface, syntactic, morphological, semantic and discourse specific factors that are afterwards combined through the use of Support Vector Machines. In the end, each factor is correlated to pupil comprehension metrics scores, spanning throughout multiple classes, therefore creating a clearer perspective in terms of measurements impacting the perceived difficulty of a given text. In addition to purely quantitative surface factors, specific parts of speech and cohesion have proven to be reliable predictors of learners' comprehension level, creating nevertheless a strong background for building dependable French textual complexity models

Predicting Comprehension from Students’ Summaries

International audienceComprehension among young students represents a key component of their formation throughout the learning process. Moreover, scaffolding students as they learn to coherently link information, while organically construct- ing a solid knowledge base, is crucial to students’ development, but requires regular assessment and progress tracking. To this end, our aim is to provide an automated solution for analyzing and predicting students’ comprehension levels by extracting a combination of reading strategies and textual complexity factors from students’ summaries. Building upon previous research and enhancing it by incorporating new heuristics and factors, Support Vector Machine classification models were used to validate our assumptions that automatically identified reading strategies, together with textual complexity indices applied on students’ summaries, represent reliable estimators of comprehension

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 & É. Lavoué (Eds.), 10th European Conf. on Technology Enhanced Learning (pp. 505–508). 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 – CSCL – conversations). Therefore, Reader‐Bench can act as a Personal Learning Environment (PLE) which incorporates both individual and collaborative assessments. Besides the a priori evaluation of textual materials’ complexity presented to learners, our system supports the identification of reading strategies evident within the learners’ 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 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

BlogCrawl: Customized Crawling of Online Communities

With half of the world already connected to the Internet, we are facing a growing amount of information available online, that is expected to increase exponentially in the following years. Educational environments are transitioning from closed structures to open, collaborative environments, using technology to build virtual classrooms. In this paper we present a customized crawler dedicated to alternative knowledge building environments used for potential community inquiry, that is unique in its power to combine data extraction and indexing capabilities that facilitate discourse-driven community network analysis integrated into the ReaderBench framework.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

Informal Learning in Online Knowledge Communities: Predicting Community Response to Visitor Inquiries

Informal learning in online knowledge communities (OKCs) comprises visitor inquiries on specific topics. Learning can occur only if the OKC adequately respond. This study aims to predict OKC response, using a social learning analytics approach based on computational linguistics and Bakhtin’s theory of dialogism. Observing the blog topic (cooking vs. politics & economics) and the visitor inquiry format (off-topic vs. on-topic), a field experiment with a 2 × 2 factorial design was conducted on a sample of N = 68 blogger communities with a total of 25,303 members. For the entire sample, the community response was influenced only by the inquiry format. In a separate examination of experimental groups, only for one examined topic (cooking) this remained true, while for the other (politics & economics) the community response only depended on the previously established dialog quality. The findings suggest identification criteria for responsive communities, which can support OKC integration in learning environments