{"type":"ScholarlyArticle","title":"Aligning Learning Outcomes to Learning Resources: A Lexico-Semantic Spatial Approach","authors":[{"name":"Swarnadeep Saha","slug":"swarnadeep-saha","given":"Swarnadeep","family":"Saha","affiliation":"IBM Research - India"},{"name":"Malolan Chetlur","slug":"malolan-chetlur","given":"Malolan","family":"Chetlur","affiliation":"IBM Research - India"},{"name":"Tejas Indulal Dhamecha","slug":"tejas-indulal-dhamecha","given":"Tejas Indulal","family":"Dhamecha","affiliation":"IBM Research - India"},{"name":"W M Gayathri K Wijayarathna","slug":"w-m-gayathri-k-wijayarathna","given":"W M Gayathri K","family":"Wijayarathna","affiliation":"Lee Kong Chian School of Medicine , Nanyang Technological University , Singapore"},{"name":"Red Mendoza","slug":"red-mendoza","given":"Red","family":"Mendoza","affiliation":"Lee Kong Chian School of Medicine , Nanyang Technological University , Singapore"},{"name":"Paul Gagnon","slug":"paul-gagnon","given":"Paul","family":"Gagnon","affiliation":"Lee Kong Chian School of Medicine , Nanyang Technological University , Singapore"},{"name":"Nabil Zary","slug":"nabil-zary","given":"Nabil","family":"Zary","affiliation":"Lee Kong Chian School of Medicine , Nanyang Technological University , Singapore"},{"name":"Shantanu Godbole","slug":"shantanu-godbole","given":"Shantanu","family":"Godbole","affiliation":"IBM Research - India"}],"abstract":"Aligning Learning Outcomes (LO) to relevant portions of Learning Resources (LR) is necessary to help students quickly navigate within the recommended learning material. In general, the problem can be viewed as finding the relevant sections of a document (LR) that is pertinent to a broad question (LO). In this paper, we introduce the novel problem of aligning LOs (LO is usually a sentence long text) to relevant pages of LRs (LRs are in the form of slide decks). We observe that the set of relevant pages can be composed of multiple chunks (a chunk is a contiguous set of pages) and the same page of an LR might be relevant to multiple LOs. To this end, we develop a novel Lexico-Semantic Spatial approach that captures the lexical, semantic, and spatial aspects of the task, and also alleviates the limited availability of training data. Our approach first identifies the relevancy of a page to an LO by using lexical and semantic features from each page independently. The spatial model at a later stage exploits the dependencies between the sequence of pages in the LR to further improve the alignment task. We empirically establish the importance of the lexical, semantic, and spatial models within the proposed approach. We show that, on average, a student can navigate to a relevant page from the first predicted page by about four clicks within a 38 page slide deck, as compared to two clicks by human experts.","doi":"10.24963/ijcai.2019/718","url":"https://ijcai.org/proceedings/2019/718","pdf":"https://ijcai.org/proceedings/2019/0718.pdf","markdown":"https://ijcai.org/proceedings/2019/718.md","bibtex":"https://ijcai.org/proceedings/2019/bibtex/718","volume":{"slug":"2019","title":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2019","url":"https://ijcai.org/proceedings/2019/","year":2019,"location":"Macao","dates":"10-16 August 2019","editors":"Sarit Kraus","isbn":"978-0-9992411-4-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2019"},"section":"Natural Language Processing","track":"Main track","number":718,"pages":{"first":5168,"last":5174},"keywords":["Natural Language Processing: NLP Applications and Tools","Humans and AI: Computer-Aided Education","Natural Language Processing: Text Classification"],"videos":[],"references":[{"position":1,"raw":"LOs Lexical Lexical+Spatial Semantic Semantic+Spatial Lexico-Semantic Spatial Gold LO1 [35-37] , 38 , 39 [35-37] , [38-39] 10,33 , [35-39] 34 , [35-39] [35-39] [35-39] LO2 6 , [8-9] [6-7] , [8-9] 7 , 8 , 9 , 15 7 , [8-9] , 15 7 , [8-9] [8-9] LO3 17 , 18 , 19 , [26-28] [17-19] , [26-28] 17 , 18 , 19 , [26-28] , 30 [14-16] , 17 , 18 , 19 , [26-28] , 30 [17-19] , [26-28] [17-19] , [26-28] LO4 [5-11] [] [5-11] [] 5 , [6-9] , [10-11] [5-6] , 7 , [8-10] , 11 [5-10] , 11 [5-11] LO5 39 , [40-45] , 46 [39-40] , [41-43] , [44-46] 6 , [40-41] , [42-43] , [44-45] [40-41] , [42-43] , [44-45] [39-41] , 42 , [43-46]","title":"LOs Lexical Lexical+Spatial Semantic Semantic+Spatial","authors":null,"year":null,"venue":"Lexico-Semantic Spatial Gold LO","doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Bhartiya et al., 2016] Divyanshu Bhartiya, Danish Contrac- tor, Sovan Biswas, Bikram Sengupta, and Mukesh K Mo- hania. 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