What happens when students engage in learning how to reason about Dutch historical literature in a digital game? : A case study of an upper secondary school classroom in the Netherlands
L1 teachers expect quite a lot from their students when dealing with L1 literature. It is therefore important that teachers adequately equip them in developing their skills in reading, understanding, and reflecting on literature. But what happens...
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L1 teachers expect quite a lot from their students when dealing with L1 literature. It is therefore important that teachers adequately equip them in developing their skills in reading, understanding, and reflecting on literature. But what happens when a digital method is used to achieve this all? As part of her PhD-research, Renate van Keulen developed a digital game to teach students how to reason about and with historical literature. Looking at the implementation of this game, this contribution tackles two main issues at hand in her class. First, we examine the effects of digitalization of literature teaching based on students' assignments and evaluations. Second, based on an ethnographic interpretive inquiry focused on the teaching of literature via this digital method, we advance some considerations on what is gained and what is lost by these students when approaching reasoning about literature at the online-offline nexus. We conclude by reflecting on the current position of L1 teaching and the implications that digitalization and game-based learning platforms may have for students' ownership of how to reason about literature.
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Building bridges. Reconstructing implicit information in argumentative texts using commonsense knowledge
In many argumentative texts a substantial amount of knowledge remains implicit. This implicit knowledge is often crucial for a deep understanding and correct interpretation of arguments. In this work we investigate how to automatically reconstruct...
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In many argumentative texts a substantial amount of knowledge remains implicit. This implicit knowledge is often crucial for a deep understanding and correct interpretation of arguments. In this work we investigate how to automatically reconstruct implicit knowledge in argumentative texts, and how the reconstruction of implicit knowledge can help in improving computational argument analysis. We point out that knowledge which stays implicit can in most cases be framed as commonsense knowledge, which has been shown to be helpful for solving many Natural Language Processing (NLP) tasks. However, it has not yet been leveraged for an in-depth analysis of arguments. This work closes this research desideratum by integrating commonsense knowledge in computational argument analysis. We explore ways to fill implicit knowledge gaps in arguments automatically by utilizing commonsense knowledge, in order to build bridges between argumentative sentences – with the ultimate goal of improving argument analysis.
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