Building an online adaptive learning and recommendation platform

Hsiao Chien Tseng; Chieh Feng Chiang; Jun Ming Su; Jui Long Hung; Brett E. Shelton

doi:10.1007/978-3-319-52836-6_45

Building an online adaptive learning and recommendation platform

Hsiao Chien Tseng, Chieh Feng Chiang, Jun Ming Su, Jui Long Hung, Brett E. Shelton

Educational Leadership, Research, and Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

18 Scopus citations

Abstract

In the traditional e-learning environment lack of immediate learning assistance. This online adaptive learning and recommendation platform (ALR) provide tracking tool for instructors to “observe” or “monitor” individual students’ learning activities. Students can learn through the ALR platform using the learning path to get the immediate assistance. Individual students’ learning strengths and weaknesses can be revealed via analyzing learning activities, learning process, and learning performance. Related analysis results can be utilized to develop corresponding automatic interventions in order to achieve goals of adaptive learning. Therefore, the purpose of this study aims to construct the concept map for adaptive learning, provide educational recommender for individual students. On the top of these prior projects, this project will develop the following intelligent components: (1) personalized dynamic concept maps for adaptive learning; (2) personalized learning path recommendation; and (3) context-based recommendation for meeting personal learning needs. Each of components will be strictly validated to ensure its practicability. This study introduce the ALR platform.

Original language	American English
Title of host publication	Emerging Technologies for Education - 1st International Symposium, SETE 2016 Held in Conjunction with ICWL 2016, Revised Selected Papers
Editors	Rosella Gennari, Yiwei Cao, Yueh-Min Huang, Wu Wu, Haoran Xie
Publisher	Springer Verlag
Pages	428-432
Number of pages	5
ISBN (Print)	9783319528359
DOIs	https://doi.org/10.1007/978-3-319-52836-6_45
State	Published - 2017
Event	1st International Symposium on Emerging Technologies for Education, SETE 2016 Held in Conjunction with ICWL 2016 - Rome, Italy Duration: 26 Oct 2016 → 29 Oct 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10108 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	1st International Symposium on Emerging Technologies for Education, SETE 2016 Held in Conjunction with ICWL 2016
Country/Territory	Italy
City	Rome
Period	26/10/16 → 29/10/16

Keywords

Adaptive learning
Concept mapping
Educational recommender

EGS Disciplines

Instructional Media Design

Access to Document

10.1007/978-3-319-52836-6_45

https://doi.org/10.1007/978-3-319-52836-6_45

Cite this

Tseng, H. C., Chiang, C. F., Su, J. M., Hung, J. L., & Shelton, B. E. (2017). Building an online adaptive learning and recommendation platform. In R. Gennari, Y. Cao, Y.-M. Huang, W. Wu, & H. Xie (Eds.), Emerging Technologies for Education - 1st International Symposium, SETE 2016 Held in Conjunction with ICWL 2016, Revised Selected Papers (pp. 428-432). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10108 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-52836-6_45

Tseng, Hsiao Chien ; Chiang, Chieh Feng ; Su, Jun Ming et al. / Building an online adaptive learning and recommendation platform. Emerging Technologies for Education - 1st International Symposium, SETE 2016 Held in Conjunction with ICWL 2016, Revised Selected Papers. editor / Rosella Gennari ; Yiwei Cao ; Yueh-Min Huang ; Wu Wu ; Haoran Xie. Springer Verlag, 2017. pp. 428-432 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{a0d11125aa6147e2a3ddf5f68350ea07,

title = "Building an online adaptive learning and recommendation platform",

abstract = "In the traditional e-learning environment lack of immediate learning assistance. This online adaptive learning and recommendation platform (ALR) provide tracking tool for instructors to “observe” or “monitor” individual students{\textquoteright} learning activities. Students can learn through the ALR platform using the learning path to get the immediate assistance. Individual students{\textquoteright} learning strengths and weaknesses can be revealed via analyzing learning activities, learning process, and learning performance. Related analysis results can be utilized to develop corresponding automatic interventions in order to achieve goals of adaptive learning. Therefore, the purpose of this study aims to construct the concept map for adaptive learning, provide educational recommender for individual students. On the top of these prior projects, this project will develop the following intelligent components: (1) personalized dynamic concept maps for adaptive learning; (2) personalized learning path recommendation; and (3) context-based recommendation for meeting personal learning needs. Each of components will be strictly validated to ensure its practicability. This study introduce the ALR platform.",

keywords = "Adaptive learning, Concept mapping, Educational recommender",

author = "Tseng, \{Hsiao Chien\} and Chiang, \{Chieh Feng\} and Su, \{Jun Ming\} and Hung, \{Jui Long\} and Shelton, \{Brett E.\}",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 1st International Symposium on Emerging Technologies for Education, SETE 2016 Held in Conjunction with ICWL 2016 ; Conference date: 26-10-2016 Through 29-10-2016",

year = "2017",

doi = "10.1007/978-3-319-52836-6\_45",

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isbn = "9783319528359",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "428--432",

editor = "Rosella Gennari and Yiwei Cao and Yueh-Min Huang and Wu Wu and Haoran Xie",

booktitle = "Emerging Technologies for Education - 1st International Symposium, SETE 2016 Held in Conjunction with ICWL 2016, Revised Selected Papers",

address = "Germany",

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Tseng, HC, Chiang, CF, Su, JM, Hung, JL & Shelton, BE 2017, Building an online adaptive learning and recommendation platform. in R Gennari, Y Cao, Y-M Huang, W Wu & H Xie (eds), Emerging Technologies for Education - 1st International Symposium, SETE 2016 Held in Conjunction with ICWL 2016, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10108 LNCS, Springer Verlag, pp. 428-432, 1st International Symposium on Emerging Technologies for Education, SETE 2016 Held in Conjunction with ICWL 2016, Rome, Italy, 26/10/16. https://doi.org/10.1007/978-3-319-52836-6_45

Building an online adaptive learning and recommendation platform. / Tseng, Hsiao Chien; Chiang, Chieh Feng; Su, Jun Ming et al.
Emerging Technologies for Education - 1st International Symposium, SETE 2016 Held in Conjunction with ICWL 2016, Revised Selected Papers. ed. / Rosella Gennari; Yiwei Cao; Yueh-Min Huang; Wu Wu; Haoran Xie. Springer Verlag, 2017. p. 428-432 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10108 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Building an online adaptive learning and recommendation platform

AU - Tseng, Hsiao Chien

AU - Chiang, Chieh Feng

AU - Su, Jun Ming

AU - Hung, Jui Long

AU - Shelton, Brett E.

N1 - Publisher Copyright: © Springer International Publishing AG 2017.

PY - 2017

Y1 - 2017

N2 - In the traditional e-learning environment lack of immediate learning assistance. This online adaptive learning and recommendation platform (ALR) provide tracking tool for instructors to “observe” or “monitor” individual students’ learning activities. Students can learn through the ALR platform using the learning path to get the immediate assistance. Individual students’ learning strengths and weaknesses can be revealed via analyzing learning activities, learning process, and learning performance. Related analysis results can be utilized to develop corresponding automatic interventions in order to achieve goals of adaptive learning. Therefore, the purpose of this study aims to construct the concept map for adaptive learning, provide educational recommender for individual students. On the top of these prior projects, this project will develop the following intelligent components: (1) personalized dynamic concept maps for adaptive learning; (2) personalized learning path recommendation; and (3) context-based recommendation for meeting personal learning needs. Each of components will be strictly validated to ensure its practicability. This study introduce the ALR platform.

AB - In the traditional e-learning environment lack of immediate learning assistance. This online adaptive learning and recommendation platform (ALR) provide tracking tool for instructors to “observe” or “monitor” individual students’ learning activities. Students can learn through the ALR platform using the learning path to get the immediate assistance. Individual students’ learning strengths and weaknesses can be revealed via analyzing learning activities, learning process, and learning performance. Related analysis results can be utilized to develop corresponding automatic interventions in order to achieve goals of adaptive learning. Therefore, the purpose of this study aims to construct the concept map for adaptive learning, provide educational recommender for individual students. On the top of these prior projects, this project will develop the following intelligent components: (1) personalized dynamic concept maps for adaptive learning; (2) personalized learning path recommendation; and (3) context-based recommendation for meeting personal learning needs. Each of components will be strictly validated to ensure its practicability. This study introduce the ALR platform.

KW - Adaptive learning

KW - Concept mapping

KW - Educational recommender

UR - https://www.scopus.com/pages/publications/85014250115

U2 - 10.1007/978-3-319-52836-6_45

DO - 10.1007/978-3-319-52836-6_45

M3 - Conference contribution

SN - 9783319528359

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 428

EP - 432

BT - Emerging Technologies for Education - 1st International Symposium, SETE 2016 Held in Conjunction with ICWL 2016, Revised Selected Papers

A2 - Gennari, Rosella

A2 - Cao, Yiwei

A2 - Huang, Yueh-Min

A2 - Wu, Wu

A2 - Xie, Haoran

PB - Springer Verlag

T2 - 1st International Symposium on Emerging Technologies for Education, SETE 2016 Held in Conjunction with ICWL 2016

Y2 - 26 October 2016 through 29 October 2016

ER -

Tseng HC, Chiang CF, Su JM, Hung JL , Shelton BE. Building an online adaptive learning and recommendation platform. In Gennari R, Cao Y, Huang YM, Wu W, Xie H, editors, Emerging Technologies for Education - 1st International Symposium, SETE 2016 Held in Conjunction with ICWL 2016, Revised Selected Papers. Springer Verlag. 2017. p. 428-432. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-52836-6_45

Building an online adaptive learning and recommendation platform

Abstract

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Keywords

EGS Disciplines

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