An educational video scoring scheme for level and topic-based recommendation

Seonmi Ji, Yongsung Kim, Seungwon Jung, Een Jun Hwang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Recently, a huge amount of educational video contents have become available due to diverse IT technologies and rapidly growing demand for online learning. Popular resources for various high quality educational contents include OCW (OpenCourseWare), MOOC (Massive Open Online Course) and TED (Technology, Entertainment, Design). Moreover, learners can easily access such contents via the Internet by using common video sharing platforms such as YouTube and Vimeo. However, one critical problem that many users experience in this environment is that it is difficult and time consuming to find out educational contents that is appropriate to them in terms of topic and difficulty level. To solve this problem, in this paper, we propose an educational contents scoring scheme for topic and difficulty level based contents recommendation. The scoring is based on the linguistic difficulty of the video and the topic similarity. To measure the linguistic difficulty, we apply various readability metrics to the video script. To measure the topic similarity between videos, we extract keywords from each video script and then calculate their cosine similarity. We show the effectiveness of our proposed scheme by various experiments.

Original languageEnglish
Title of host publicationProceedings of the 12th International Conference on Ubiquitous Information Management and Communication, IMCOM 2018
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450363853
DOIs
Publication statusPublished - 2018 Jan 5
Event12th International Conference on Ubiquitous Information Management and Communication, IMCOM 2018 - Langkawi, Malaysia
Duration: 2018 Jan 52018 Jan 7

Other

Other12th International Conference on Ubiquitous Information Management and Communication, IMCOM 2018
CountryMalaysia
CityLangkawi
Period18/1/518/1/7

Fingerprint

Linguistics
Internet
Experiments

Keywords

  • Educational video
  • Level and topic-based recommendation
  • Ranking score

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

Cite this

Ji, S., Kim, Y., Jung, S., & Hwang, E. J. (2018). An educational video scoring scheme for level and topic-based recommendation. In Proceedings of the 12th International Conference on Ubiquitous Information Management and Communication, IMCOM 2018 [12] Association for Computing Machinery. https://doi.org/10.1145/3164541.3164636

An educational video scoring scheme for level and topic-based recommendation. / Ji, Seonmi; Kim, Yongsung; Jung, Seungwon; Hwang, Een Jun.

Proceedings of the 12th International Conference on Ubiquitous Information Management and Communication, IMCOM 2018. Association for Computing Machinery, 2018. 12.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ji, S, Kim, Y, Jung, S & Hwang, EJ 2018, An educational video scoring scheme for level and topic-based recommendation. in Proceedings of the 12th International Conference on Ubiquitous Information Management and Communication, IMCOM 2018., 12, Association for Computing Machinery, 12th International Conference on Ubiquitous Information Management and Communication, IMCOM 2018, Langkawi, Malaysia, 18/1/5. https://doi.org/10.1145/3164541.3164636
Ji S, Kim Y, Jung S, Hwang EJ. An educational video scoring scheme for level and topic-based recommendation. In Proceedings of the 12th International Conference on Ubiquitous Information Management and Communication, IMCOM 2018. Association for Computing Machinery. 2018. 12 https://doi.org/10.1145/3164541.3164636
Ji, Seonmi ; Kim, Yongsung ; Jung, Seungwon ; Hwang, Een Jun. / An educational video scoring scheme for level and topic-based recommendation. Proceedings of the 12th International Conference on Ubiquitous Information Management and Communication, IMCOM 2018. Association for Computing Machinery, 2018.
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