The value of multimodal data in classification of social and emotional aspects of tutoring

Mutlu Cukurova; Carmel Kent; Rosemary Luckin

doi:10.1007/978-3-030-23207-8_9

The value of multimodal data in classification of social and emotional aspects of tutoring

Mutlu Cukurova, Carmel Kent, Rosemary Luckin

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

Abstract

There are many aspects of tutoring that are associated with social and emotional learning. These are complex processes that involve dynamic combinations of skills, abilities and knowledge. Here, we present the results of our investigation on the particular personal, emotional, and experience traits of tutors who are likely to be successful at social and emotional aspects of tutoring. In particular, we present our approach to measure the social and emotional aspects of tutoring through classification models of 47 candidates’ multimodal data from audio and psychometric measures. Moreover, we compare the accuracy of models with unimodal and multimodal data, and show that multimodal data leads to more accurate classifications of the candidates. We argue that when evaluating the social and emotional aspects of tutoring, multimodal data might be more preferrable.

Original language	English
Title of host publication	Artificial Intelligence in Education - 20th International Conference, AIED 2019, Proceedings
Editors	Seiji Isotani, Eva Millán, Amy Ogan, Bruce McLaren, Peter Hastings, Rose Luckin
Publisher	Springer Verlag
Pages	46-51
Number of pages	6
ISBN (Print)	9783030232061
DOIs	https://doi.org/10.1007/978-3-030-23207-8_9
State	Published - 2019
Externally published	Yes
Event	20th International Conference on Artificial Intelligence in Education, AIED 2019 - Chicago, United States Duration: 25 Jun 2019 → 29 Jun 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11626 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	20th International Conference on Artificial Intelligence in Education, AIED 2019
Country/Territory	United States
City	Chicago
Period	25/06/19 → 29/06/19

Bibliographical note

Publisher Copyright:
© Springer Nature Switzerland AG 2019.

Keywords

Multimodal data
Social and emotional learning
Tutoring

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-030-23207-8_9

Cite this

Cukurova, M., Kent, C., & Luckin, R. (2019). The value of multimodal data in classification of social and emotional aspects of tutoring. In S. Isotani, E. Millán, A. Ogan, B. McLaren, P. Hastings, & R. Luckin (Eds.), Artificial Intelligence in Education - 20th International Conference, AIED 2019, Proceedings (pp. 46-51). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11626 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-030-23207-8_9

Cukurova, Mutlu ; Kent, Carmel ; Luckin, Rosemary. / The value of multimodal data in classification of social and emotional aspects of tutoring. Artificial Intelligence in Education - 20th International Conference, AIED 2019, Proceedings. editor / Seiji Isotani ; Eva Millán ; Amy Ogan ; Bruce McLaren ; Peter Hastings ; Rose Luckin. Springer Verlag, 2019. pp. 46-51 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "The value of multimodal data in classification of social and emotional aspects of tutoring",

abstract = "There are many aspects of tutoring that are associated with social and emotional learning. These are complex processes that involve dynamic combinations of skills, abilities and knowledge. Here, we present the results of our investigation on the particular personal, emotional, and experience traits of tutors who are likely to be successful at social and emotional aspects of tutoring. In particular, we present our approach to measure the social and emotional aspects of tutoring through classification models of 47 candidates{\textquoteright} multimodal data from audio and psychometric measures. Moreover, we compare the accuracy of models with unimodal and multimodal data, and show that multimodal data leads to more accurate classifications of the candidates. We argue that when evaluating the social and emotional aspects of tutoring, multimodal data might be more preferrable.",

keywords = "Multimodal data, Social and emotional learning, Tutoring",

author = "Mutlu Cukurova and Carmel Kent and Rosemary Luckin",

note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019.; 20th International Conference on Artificial Intelligence in Education, AIED 2019 ; Conference date: 25-06-2019 Through 29-06-2019",

year = "2019",

doi = "10.1007/978-3-030-23207-8_9",

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Cukurova, M, Kent, C & Luckin, R 2019, The value of multimodal data in classification of social and emotional aspects of tutoring. in S Isotani, E Millán, A Ogan, B McLaren, P Hastings & R Luckin (eds), Artificial Intelligence in Education - 20th International Conference, AIED 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11626 LNAI, Springer Verlag, pp. 46-51, 20th International Conference on Artificial Intelligence in Education, AIED 2019, Chicago, United States, 25/06/19. https://doi.org/10.1007/978-3-030-23207-8_9

The value of multimodal data in classification of social and emotional aspects of tutoring. / Cukurova, Mutlu; Kent, Carmel; Luckin, Rosemary.
Artificial Intelligence in Education - 20th International Conference, AIED 2019, Proceedings. ed. / Seiji Isotani; Eva Millán; Amy Ogan; Bruce McLaren; Peter Hastings; Rose Luckin. Springer Verlag, 2019. p. 46-51 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11626 LNAI).

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

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AU - Luckin, Rosemary

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PY - 2019

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N2 - There are many aspects of tutoring that are associated with social and emotional learning. These are complex processes that involve dynamic combinations of skills, abilities and knowledge. Here, we present the results of our investigation on the particular personal, emotional, and experience traits of tutors who are likely to be successful at social and emotional aspects of tutoring. In particular, we present our approach to measure the social and emotional aspects of tutoring through classification models of 47 candidates’ multimodal data from audio and psychometric measures. Moreover, we compare the accuracy of models with unimodal and multimodal data, and show that multimodal data leads to more accurate classifications of the candidates. We argue that when evaluating the social and emotional aspects of tutoring, multimodal data might be more preferrable.

AB - There are many aspects of tutoring that are associated with social and emotional learning. These are complex processes that involve dynamic combinations of skills, abilities and knowledge. Here, we present the results of our investigation on the particular personal, emotional, and experience traits of tutors who are likely to be successful at social and emotional aspects of tutoring. In particular, we present our approach to measure the social and emotional aspects of tutoring through classification models of 47 candidates’ multimodal data from audio and psychometric measures. Moreover, we compare the accuracy of models with unimodal and multimodal data, and show that multimodal data leads to more accurate classifications of the candidates. We argue that when evaluating the social and emotional aspects of tutoring, multimodal data might be more preferrable.

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Cukurova M, Kent C, Luckin R. The value of multimodal data in classification of social and emotional aspects of tutoring. In Isotani S, Millán E, Ogan A, McLaren B, Hastings P, Luckin R, editors, Artificial Intelligence in Education - 20th International Conference, AIED 2019, Proceedings. Springer Verlag. 2019. p. 46-51. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-23207-8_9

The value of multimodal data in classification of social and emotional aspects of tutoring

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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