research-article

KELDEC: A Recommendation System for Extending Classroom Learning with Visual Environmental Cues

Authors:

Shampa Chakraverty,

Pinaki Chakraborty,

Shikhar Agnihotri,

Soumya Mohapatra,

Prakriti BansalAuthors Info & Claims

NLPIR '19: Proceedings of the 2019 3rd International Conference on Natural Language Processing and Information Retrieval

Pages 99 - 103

https://doi.org/10.1145/3342827.3342849

Published: 28 June 2019 Publication History

Abstract

We develop an innovative personalized recommendation system called KELDEC that links the notes that students take in class with their outdoor experiences captured with camera, to suggest websites that extend their knowledge. Despite the plethora of educational recommendation systems, there is a dearth of effective tools that make evident the practical application of theory in the real world. KELDEC extracts the core learning points from class notes and distinctive labels that describe objects in a picture. It then mines the web to first extract the technical context of the picture, and subsequently culls out websites that establish linkages between notes and the picture. Response to user surveys garnered from students studying Software Engineering in the undergraduate Computer Engineering course reveal that they gain new and practical extension of classroom knowledge.

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Index Terms

KELDEC: A Recommendation System for Extending Classroom Learning with Visual Environmental Cues
1. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Recommender systems

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cover image ACM Other conferences

NLPIR '19: Proceedings of the 2019 3rd International Conference on Natural Language Processing and Information Retrieval

June 2019

171 pages

ISBN:9781450362795

DOI:10.1145/3342827

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Southwest Jiaotong University

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Association for Computing Machinery

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Published: 28 June 2019

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NLPIR 2019

NLPIR 2019: 2019 the 3rd International Conference on Natural Language Processing and Information Retrieval

June 28 - 30, 2019

Tokushima, Japan

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Cited By

Monika Garg UKanika (2024)The Role of Feature Based Classification Models in Early Detection of Brain Stroke2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)10.1109/ICCCNT61001.2024.10724564(1-6)Online publication date: 24-Jun-2024
https://doi.org/10.1109/ICCCNT61001.2024.10724564
Kaur MBehki PKaur ANaaz ARadha Mehta P(2024)Security Camera with Frame Detection2024 International Conference on Emerging Smart Computing and Informatics (ESCI)10.1109/ESCI59607.2024.10497220(1-5)Online publication date: 5-Mar-2024
https://doi.org/10.1109/ESCI59607.2024.10497220
Kanika Dutta PKaur AKumar MVerma A(2023)AENTO: A Note-Taking Application for Comprehensive LearningProceedings of the International Conference on Intelligent Computing, Communication and Information Security10.1007/978-981-99-1373-2_14(181-194)Online publication date: 4-Jul-2023
https://doi.org/10.1007/978-981-99-1373-2_14
Kanika KChakraverty SChakraborty PMadan MGupta GAggarwal A(2021)VISTA: A teaching aid to enhance contextual teachingComputer Applications in Engineering Education10.1002/cae.2240729:6(1526-1541)Online publication date: 21-Mar-2021
https://doi.org/10.1002/cae.22407

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