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Dascalu, Marina-Dorinela; Ruseti, Stefan; Dascalu, Mihai; McNamara, Danielle; Trausan-Matu, Stefan – Grantee Submission, 2020
Reading comprehension requires readers to connect ideas within and across texts to produce a coherent mental representation. One important factor in that complex process regards the cohesion of the document(s). Here, we tackle the challenge of providing researchers and practitioners with a tool to visualize text cohesion both within (intra) and…
Descriptors: Network Analysis, Graphs, Connected Discourse, Reading Comprehension
Nicula, Bogdan; Perret, Cecile A.; Dascalu, Mihai; McNamara, Danielle S. – Grantee Submission, 2020
Theories of discourse argue that comprehension depends on the coherence of the learner's mental representation. Our aim is to create a reliable automated representation to estimate readers' level of comprehension based on different productions, namely self-explanations and answers to open-ended questions. Previous work relied on Cohesion Network…
Descriptors: Network Analysis, Reading Comprehension, Automation, Artificial Intelligence
Spezio, Michael; Peterson, Gregory; Roberts, Robert C. – Journal of Moral Education, 2019
Exploring the concept of virtuous humility helps to highlight paths of human flourishing. Yet humility is difficult to study because it is often stereotyped as shame or self-abasement, it tends to defy uniform conceptualization across contexts and cultures, definitions are difficult to justify, and operationalizing humility challenges standard…
Descriptors: Stereotypes, Cultural Differences, Personality Traits, Self Concept
Nicula, Bogdan; Perret, Cecile A.; Dascalu, Mihai; McNamara, Danielle S. – Grantee Submission, 2020
Open-ended comprehension questions are a common type of assessment used to evaluate how well students understand one of multiple documents. Our aim is to use natural language processing (NLP) to infer the level and type of inferencing within readers' answers to comprehension questions using linguistic and semantic features within their responses.…
Descriptors: Natural Language Processing, Taxonomy, Responses, Semantics
Zhao, Xiaowei; Li, Ping – International Journal of Bilingual Education and Bilingualism, 2010
In this paper we present an unsupervised neural network model of bilingual lexical development and interaction. We focus on how the representational structures of the bilingual lexicons can emerge, develop, and interact with each other as a function of the learning history. The results show that: (1) distinct representations for the two lexicons…
Descriptors: Second Language Learning, Bilingualism, Vocabulary Development, Age

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