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Curricula customization with the readerbench Framework

Curricula customization with the readerbench Framework
Curricula customization with the readerbench Framework
Providing customized curricula tailored to learner's needs became a stringent problem while relating to the increasing number of people attending Massive Open Online Courses (MOOCs) and eLearning platforms because the same content is provided to all students. This study presents a Moodle plugin created on top of an eLearning course that enables curricula customization based on the learning needs of a high number of participants. With the help of the Mass Customization approach, two categories of attendees were identified in a previous research and imposed multiple filtering criteria, out of which the first one refers to participants’ profession. The second criterion, topics of interest, allows learners to select keywords of interest from a predefined two-level word list, but also to enumerate their own terms using natural language. With the support of ReaderBench, an advanced Natural Language Processing framework, the most relevant lessons are retrieved in descending order of semantic relatedness. Third, an additional specific parameter allows participants to establish what kind of learning materials they require - i.e., theoretical and background oriented, practice and counseling documents, or guidelines. Our collection of documents is composed of lessons with a short description and their title, together with lists of pre- and post-requisite lessons. Our tool provides a comprehensive list of recommended lessons that best match the input criteria, corroborated with the list of related pre- and post-requisite lessons. Moreover, we provide information in terms of the duration of each lesson, as well as potential Continuous Medical Education points gained after finishing all selected lessons.
Curricula Customization, Mass Customization, Topics of Interest, Learning Needs, Text Cohesion, Discourse Analysis, Inter-disciplinary Research
385-392
National Defence University Publishing House
Gutu-Robu, Gabriel
0c82967b-d2f5-4af7-b991-7a3fa4dc3108
Trausan-Matu, Stefan
daebf5ac-ada8-43b7-8f5e-261592e619e4
Dascalu, Mihai
4514ff6a-4a9a-4eb9-87fa-4b93cd2bf5ed
Carabas, Mihai
c564e8e9-e564-4a38-9ac3-34c056ed2180
Elisei, Alexandru
34b2d8ac-3d20-4fb6-b3b5-cc8e42b9eb05
Nistor, Nicolae
5250b999-a390-4619-b694-b5eac70cca57
Choi, Sunhea
1d0e766d-38d5-4d01-aea7-639c4334334f
Spoerl, Rebecca
3b662fce-1e29-4e5e-9dfd-d94759135602
Koletzko, Berthold
22ab3df4-675f-4a6b-972b-03711bfdb8e4
Roceanu, Ion
Beligan, Daniel
Ciolan, Lucian
Stefan, Ioana
Gutu-Robu, Gabriel
0c82967b-d2f5-4af7-b991-7a3fa4dc3108
Trausan-Matu, Stefan
daebf5ac-ada8-43b7-8f5e-261592e619e4
Dascalu, Mihai
4514ff6a-4a9a-4eb9-87fa-4b93cd2bf5ed
Carabas, Mihai
c564e8e9-e564-4a38-9ac3-34c056ed2180
Elisei, Alexandru
34b2d8ac-3d20-4fb6-b3b5-cc8e42b9eb05
Nistor, Nicolae
5250b999-a390-4619-b694-b5eac70cca57
Choi, Sunhea
1d0e766d-38d5-4d01-aea7-639c4334334f
Spoerl, Rebecca
3b662fce-1e29-4e5e-9dfd-d94759135602
Koletzko, Berthold
22ab3df4-675f-4a6b-972b-03711bfdb8e4
Roceanu, Ion
Beligan, Daniel
Ciolan, Lucian
Stefan, Ioana

Gutu-Robu, Gabriel, Trausan-Matu, Stefan, Dascalu, Mihai, Carabas, Mihai, Elisei, Alexandru, Nistor, Nicolae, Choi, Sunhea, Spoerl, Rebecca and Koletzko, Berthold (2018) Curricula customization with the readerbench Framework. Roceanu, Ion, Beligan, Daniel, Ciolan, Lucian and Stefan, Ioana (eds.) In eLearning challenges and new horizons: Proceedings of the 14th International Scientific Conference "eLearning and Software for Education". National Defence University Publishing House. pp. 385-392 . (doi:10.12753/2066-026X-18-123).

Record type: Conference or Workshop Item (Paper)

Abstract

Providing customized curricula tailored to learner's needs became a stringent problem while relating to the increasing number of people attending Massive Open Online Courses (MOOCs) and eLearning platforms because the same content is provided to all students. This study presents a Moodle plugin created on top of an eLearning course that enables curricula customization based on the learning needs of a high number of participants. With the help of the Mass Customization approach, two categories of attendees were identified in a previous research and imposed multiple filtering criteria, out of which the first one refers to participants’ profession. The second criterion, topics of interest, allows learners to select keywords of interest from a predefined two-level word list, but also to enumerate their own terms using natural language. With the support of ReaderBench, an advanced Natural Language Processing framework, the most relevant lessons are retrieved in descending order of semantic relatedness. Third, an additional specific parameter allows participants to establish what kind of learning materials they require - i.e., theoretical and background oriented, practice and counseling documents, or guidelines. Our collection of documents is composed of lessons with a short description and their title, together with lists of pre- and post-requisite lessons. Our tool provides a comprehensive list of recommended lessons that best match the input criteria, corroborated with the list of related pre- and post-requisite lessons. Moreover, we provide information in terms of the duration of each lesson, as well as potential Continuous Medical Education points gained after finishing all selected lessons.

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More information

Published date: April 2018
Keywords: Curricula Customization, Mass Customization, Topics of Interest, Learning Needs, Text Cohesion, Discourse Analysis, Inter-disciplinary Research

Identifiers

Local EPrints ID: 424661
URI: http://eprints.soton.ac.uk/id/eprint/424661
PURE UUID: 704574c0-f22c-4e4e-9972-0ada1bbd8d85

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Date deposited: 05 Oct 2018 11:39
Last modified: 15 Mar 2024 21:19

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Contributors

Author: Gabriel Gutu-Robu
Author: Stefan Trausan-Matu
Author: Mihai Dascalu
Author: Mihai Carabas
Author: Alexandru Elisei
Author: Nicolae Nistor
Author: Sunhea Choi
Author: Rebecca Spoerl
Author: Berthold Koletzko
Editor: Ion Roceanu
Editor: Daniel Beligan
Editor: Lucian Ciolan
Editor: Ioana Stefan

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