Education
Contributions: This study offers valuable insights to MOOC designers about user priorities associated with web accessibility principles for designing web content that provides higher levels of user experience, motivating course completions. Background: MOOCs improve access to quality education. Despite policy support and more involvement by leading educational institutions worldwide, poor course completion rates undermine the objectives for MOOC diffusion.
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Contributions: This study offers valuable insights to MOOC designers about user priorities associated with web accessibility principles for designing web content that provides higher levels of user experience, motivating course completions. Background: MOOCs improve access to quality education. Despite policy support and more involvement by leading educational institutions worldwide, poor course completion rates undermine the objectives for MOOC diffusion.
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LinguoInsight English Textbook Corpus
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In the domain of Natural Language Processing (NLP), the English Writing Fluency Improvement for non-native speakers, particularly in academic contexts, poses significant challenges. While Sentence-level Revision (SentRev) endeavors to address this concern, the existing evaluation corpus, SMITH, falls short in offering a robust and comprehensive assessment of the task. To bridge this gap, our research offers a novel evaluation corpus generation scheme, leading to the creation of Ten-Country Non-native Academic English Corpus (TCNAEC).
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This survey dataset delves into the diverse experiences and perspectives of individuals, focusing on key aspects of their educational journey and subsequent career choices. Comprising more than 60 questions or attributes,respondents were asked to share insights into their personal background, educational history, university preferences, and current professional status. The questionnaire covers a range of topics, including high school experiences, university decision-making criteria, major selection influences, and post-graduation outcomes.
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The Numerical Latin Letters (DNLL) dataset consists of Latin numeric letters organized into 26 distinct letter classes, corresponding to the Latin alphabet. Each class within this dataset encompasses multiple letter forms, resulting in a diverse and extensive collection. These letters vary in color, size, writing style, thickness, background, orientation, luminosity, and other attributes, making the dataset highly comprehensive and rich.
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Gamification is a rapidly evolving field that seeks to integrate game mechanics and elements into non-game contexts to enhance the learning experience of computer science students.
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RITA (Resource for Italian Tests Assessment), is a new NLP dataset of academic exam texts written in Italian by second-language learners for obtaining the CEFR certification of proficiency level.
RITA dataset is available for automatic processing in CSV and XML format, under an agreement of citation.
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This dataset comprises data created during research on AI-generated code, with a focus on software engineering use-cases. The purpose of the research was to investigate how AI should be integrated into university software engineering curricula.
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