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Let's Learn from Children: Scaffolding to Enable Search as Learning in the Educational Environment 让我们向孩子们学习:在教育环境中让搜索成为学习的脚手架
INRA/IWILDS@SIGIR Pub Date : 2022-09-06 DOI: 10.48550/arXiv.2209.02338
M. Landoni, M. S. Pera, Emiliana Murgia, T. Huibers
{"title":"Let's Learn from Children: Scaffolding to Enable Search as Learning in the Educational Environment","authors":"M. Landoni, M. S. Pera, Emiliana Murgia, T. Huibers","doi":"10.48550/arXiv.2209.02338","DOIUrl":"https://doi.org/10.48550/arXiv.2209.02338","url":null,"abstract":"In this manuscript, we argue for the need to further look at search as learning (SAL) with children as the primary stakeholders. Inspired by how children learn and considering the classroom (regardless of the teaching modality) as a natural educational ecosystem, we posit that scaffolding is the tie that can simultaneously allow for learning to search while searching for learning. The main contribution of this work is a list of open challenges focused on the primary school classroom for the IR community to consider when setting up to explore and make progress on SAL research with and for children and beyond.","PeriodicalId":374222,"journal":{"name":"INRA/IWILDS@SIGIR","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133178698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Understanding the Relation of User and News Representations in Content-Based Neural News Recommendation 基于内容的神经新闻推荐中用户与新闻表示关系的理解
INRA/IWILDS@SIGIR Pub Date : 2022-07-29 DOI: 10.48550/arXiv.2207.14704
Lucas Moller, Sebastian Padó
{"title":"Understanding the Relation of User and News Representations in Content-Based Neural News Recommendation","authors":"Lucas Moller, Sebastian Padó","doi":"10.48550/arXiv.2207.14704","DOIUrl":"https://doi.org/10.48550/arXiv.2207.14704","url":null,"abstract":"A number of models for neural content-based news recommendation have been proposed. However, there is limited understanding of the relative importances of the three main components of such systems (news encoder, user encoder, and scoring function) and the trade-offs involved. In this paper, we assess the hypothesis that the most widely used means of matching user and candidate news representations is not expressive enough. We allow our system to model more complex relations between the two by assessing more expressive scoring functions. Across a wide range of baseline and established systems this results in consistent improvements of around 6 points in AUC. Our results also indicate a trade-off between the complexity of news encoder and scoring function: A fairly simple baseline model scores well above 68% AUC on the MIND dataset and comes within 2 points of the published state-of-the-art, while requiring a fraction of the computational costs.","PeriodicalId":374222,"journal":{"name":"INRA/IWILDS@SIGIR","volume":"427 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122873214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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