Exploring human–AI control over dynamic transitions between individual and collaborative learning

Vanessa Echeverria; Kenneth Holstein; Jennifer Huang; Jonathan Sewall; Nikol Rummel; Vincent Aleven

doi:10.1007/978-3-030-57717-9_17

Exploring human–AI control over dynamic transitions between individual and collaborative learning

Vanessa Echeverria, Kenneth Holstein, Jennifer Huang, Jonathan Sewall, Nikol Rummel, Vincent Aleven

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

7 Citations (Scopus)

Abstract

Dynamically transitioning between individual and collaborative learning activities during a class session (i.e., in an un-planned way, as-the-need-arises) has advantages for students, but existing orchestration tools are not designed to support such transitions. This work reports findings from a technology probe study that explored alternative designs for classroom co-orchestration support for dynamically transitioning between individual and collaborative learning, focused on how control over the transitions should be divided or shared among teachers, students, and orchestration system. This study involved 1) a pilot in an authentic classroom scenario with AI support for individual and collaborative learning; and 2) design workshops and interviews with students and teachers. Findings from the study suggest the need for hybrid control between students, teachers, and AI systems over transitions as well as for adaptivity and/or adaptability for different classrooms, teachers, and students’ prior knowledge. This study is the first to explore human–AI control over dynamic transitions between individual and collaborative learning in actual classrooms.

Original language	English
Title of host publication	15th European Conference on Technology Enhanced Learning, EC-TEL 2020 Heidelberg, Germany, September 14–18, 2020 Proceedings
Editors	Carlos Alario-Hoyos, María Jesús Rodríguez-Triana, Maren Scheffel, Inmaculada Arnedillo-Sánchez, Sebastian Maximilian Dennerlein
Place of Publication	Cham Switzerland
Publisher	Springer
Pages	230-243
Number of pages	14
ISBN (Electronic)	9783030577179
ISBN (Print)	9783030577162
DOIs	https://doi.org/10.1007/978-3-030-57717-9_17
Publication status	Published - 2020
Externally published	Yes
Event	European Conference on Technology Enhanced Learning 2020 - Heidelberg, Germany Duration: 14 Sept 2020 → 18 Sept 2020 Conference number: 15th https://link.springer.com/book/10.1007/978-3-030-57717-9 (Proceedings)

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	12315
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	European Conference on Technology Enhanced Learning 2020
Abbreviated title	EC-TEL 2020
Country/Territory	Germany
City	Heidelberg
Period	14/09/20 → 18/09/20
Internet address	https://link.springer.com/book/10.1007/978-3-030-57717-9 (Proceedings)

Keywords

Human-AI co-orchestration
Individual and collaborative learning

Access to Document

10.1007/978-3-030-57717-9_17

Cite this

Echeverria, V., Holstein, K., Huang, J., Sewall, J., Rummel, N., & Aleven, V. (2020). Exploring human–AI control over dynamic transitions between individual and collaborative learning. In C. Alario-Hoyos, M. J. Rodríguez-Triana, M. Scheffel, I. Arnedillo-Sánchez, & S. M. Dennerlein (Eds.), 15th European Conference on Technology Enhanced Learning, EC-TEL 2020 Heidelberg, Germany, September 14–18, 2020 Proceedings (pp. 230-243). (Lecture Notes in Computer Science; Vol. 12315). Springer. https://doi.org/10.1007/978-3-030-57717-9_17

Echeverria, Vanessa ; Holstein, Kenneth ; Huang, Jennifer et al. / Exploring human–AI control over dynamic transitions between individual and collaborative learning. 15th European Conference on Technology Enhanced Learning, EC-TEL 2020 Heidelberg, Germany, September 14–18, 2020 Proceedings. editor / Carlos Alario-Hoyos ; María Jesús Rodríguez-Triana ; Maren Scheffel ; Inmaculada Arnedillo-Sánchez ; Sebastian Maximilian Dennerlein. Cham Switzerland : Springer, 2020. pp. 230-243 (Lecture Notes in Computer Science).

@inproceedings{ea15db7b305143c694c17b7da986128e,

title = "Exploring human–AI control over dynamic transitions between individual and collaborative learning",

abstract = "Dynamically transitioning between individual and collaborative learning activities during a class session (i.e., in an un-planned way, as-the-need-arises) has advantages for students, but existing orchestration tools are not designed to support such transitions. This work reports findings from a technology probe study that explored alternative designs for classroom co-orchestration support for dynamically transitioning between individual and collaborative learning, focused on how control over the transitions should be divided or shared among teachers, students, and orchestration system. This study involved 1) a pilot in an authentic classroom scenario with AI support for individual and collaborative learning; and 2) design workshops and interviews with students and teachers. Findings from the study suggest the need for hybrid control between students, teachers, and AI systems over transitions as well as for adaptivity and/or adaptability for different classrooms, teachers, and students{\textquoteright} prior knowledge. This study is the first to explore human–AI control over dynamic transitions between individual and collaborative learning in actual classrooms.",

keywords = "Human-AI co-orchestration, Individual and collaborative learning",

author = "Vanessa Echeverria and Kenneth Holstein and Jennifer Huang and Jonathan Sewall and Nikol Rummel and Vincent Aleven",

note = "Funding Information: Acknowledgements. This work was supported by grants IES R305A180301 and NSF (IIS) 1822861. The opinions expressed are those of the authors and do not represent the views of the funding agencies. Special thanks to all participating teachers and students. Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2020.; European Conference on Technology Enhanced Learning 2020, EC-TEL 2020 ; Conference date: 14-09-2020 Through 18-09-2020",

year = "2020",

doi = "10.1007/978-3-030-57717-9_17",

language = "English",

isbn = "9783030577162",

series = "Lecture Notes in Computer Science",

publisher = "Springer",

pages = "230--243",

editor = "Carlos Alario-Hoyos and Rodr{\'i}guez-Triana, {Mar{\'i}a Jes{\'u}s} and Maren Scheffel and Inmaculada Arnedillo-S{\'a}nchez and Dennerlein, {Sebastian Maximilian}",

booktitle = "15th European Conference on Technology Enhanced Learning, EC-TEL 2020 Heidelberg, Germany, September 14–18, 2020 Proceedings",

url = "https://link.springer.com/book/10.1007/978-3-030-57717-9",

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Echeverria, V, Holstein, K, Huang, J, Sewall, J, Rummel, N & Aleven, V 2020, Exploring human–AI control over dynamic transitions between individual and collaborative learning. in C Alario-Hoyos, MJ Rodríguez-Triana, M Scheffel, I Arnedillo-Sánchez & SM Dennerlein (eds), 15th European Conference on Technology Enhanced Learning, EC-TEL 2020 Heidelberg, Germany, September 14–18, 2020 Proceedings. Lecture Notes in Computer Science, vol. 12315, Springer, Cham Switzerland, pp. 230-243, European Conference on Technology Enhanced Learning 2020, Heidelberg, Germany, 14/09/20. https://doi.org/10.1007/978-3-030-57717-9_17

Exploring human–AI control over dynamic transitions between individual and collaborative learning. / Echeverria, Vanessa; Holstein, Kenneth; Huang, Jennifer et al.
15th European Conference on Technology Enhanced Learning, EC-TEL 2020 Heidelberg, Germany, September 14–18, 2020 Proceedings. ed. / Carlos Alario-Hoyos; María Jesús Rodríguez-Triana; Maren Scheffel; Inmaculada Arnedillo-Sánchez; Sebastian Maximilian Dennerlein. Cham Switzerland: Springer, 2020. p. 230-243 (Lecture Notes in Computer Science; Vol. 12315).

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

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AU - Echeverria, Vanessa

AU - Holstein, Kenneth

AU - Huang, Jennifer

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AU - Aleven, Vincent

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AB - Dynamically transitioning between individual and collaborative learning activities during a class session (i.e., in an un-planned way, as-the-need-arises) has advantages for students, but existing orchestration tools are not designed to support such transitions. This work reports findings from a technology probe study that explored alternative designs for classroom co-orchestration support for dynamically transitioning between individual and collaborative learning, focused on how control over the transitions should be divided or shared among teachers, students, and orchestration system. This study involved 1) a pilot in an authentic classroom scenario with AI support for individual and collaborative learning; and 2) design workshops and interviews with students and teachers. Findings from the study suggest the need for hybrid control between students, teachers, and AI systems over transitions as well as for adaptivity and/or adaptability for different classrooms, teachers, and students’ prior knowledge. This study is the first to explore human–AI control over dynamic transitions between individual and collaborative learning in actual classrooms.

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Echeverria V, Holstein K, Huang J, Sewall J, Rummel N, Aleven V. Exploring human–AI control over dynamic transitions between individual and collaborative learning. In Alario-Hoyos C, Rodríguez-Triana MJ, Scheffel M, Arnedillo-Sánchez I, Dennerlein SM, editors, 15th European Conference on Technology Enhanced Learning, EC-TEL 2020 Heidelberg, Germany, September 14–18, 2020 Proceedings. Cham Switzerland: Springer. 2020. p. 230-243. (Lecture Notes in Computer Science). doi: 10.1007/978-3-030-57717-9_17

Exploring human–AI control over dynamic transitions between individual and collaborative learning

Abstract

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Keywords

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