{"product_id":"9783658392024","title":"BestMasters","description":"\u003ch1\u003eBestMasters\u003c\/h1\u003e \u003ch2\u003eRichner, Robin\u003c\/h2\u003e \u003cp\u003eTeachers spend a great amount of time grading free text answer type questions. To encounter this challenge an auto-grader system is proposed. The thesis illustrates that the auto-grader can be approached with simple, recurrent, and Transformer-based neural networks. Hereby, the Transformer-based models has the best performance. It is further demonstrated that geometric representation of question-answer pairs is a worthwhile strategy for an auto-grader. Finally, it is indicated that while the auto-grader could potentially assist teachers in saving time with grading, it is not yet on a level to fully replace teachers for this task.\u003c\/p\u003e \u003ch3\u003eDetails\u003c\/h3\u003e \u003cp\u003ePublished by: Springer Gabler\u003c\/p\u003e \u003cp\u003ePublication Date: 2022-10-15\u003c\/p\u003e \u003cp\u003eFormat: Paperback\u003c\/p\u003e \u003cp\u003eISBN-13: 9783658392024\u003c\/p\u003e \u003cp\u003eDOI: 10.1007\/978-3-658-39203-1\u003c\/p\u003e \u003cp\u003eDimensions: 210cm x148cm\u003c\/p\u003e \u003cp\u003ePages: 96\u003c\/p\u003e ","brand":"Springer Fachmedien Wiesbaden","offers":[{"title":"Default Title","offer_id":47409353130124,"sku":"9783658392024","price":49.49,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9783658392024.jpg?v=1775835249","url":"https:\/\/fh90cf-fv.myshopify.com\/products\/9783658392024","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}