Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | LAK 2022 - Conference Proceedings |
| Untertitel | Learning Analytics for Transition, Disruption and Social Change - 12th International Conference on Learning Analytics and Knowledge |
| Seiten | 563-569 |
| Seitenumfang | 7 |
| ISBN (elektronisch) | 9781450395731 |
| Publikationsstatus | Veröffentlicht - 21 März 2022 |
| Extern publiziert | Ja |
| Veranstaltung | 12th International Conference on Learning Analytics and Knowledge: Learning Analytics for Transition, Disruption and Social Change, LAK 2022 - Virtual, Online, USA / Vereinigte Staaten Dauer: 21 März 2022 → 25 März 2022 |
Publikationsreihe
| Name | ACM International Conference Proceeding Series |
|---|
Abstract
Informal learning procedures have been changing extremely fast over the recent decades not only due to the advent of online learning, but also due to changes in what humans need to learn to meet their various life and career goals. Consequently, online, educational platforms are expected to provide personalized, up-to-date curricula to assist learners. Therefore, in this paper, we propose an Artificial Intelligence (AI) and Crowdsourcing based approach to create and update curricula for individual learners. We show the design of this curriculum development system prototype, in which contributors receive AI-based recommendations to be able to define and update high-level learning goals, skills, and learning topics together with associated learning content. This curriculum development system was also integrated into our personalized online learning platform. To evaluate our prototype we compared experts' opinion with our system's recommendations, and resulted in 89%, 79%, and 93% F1-scores when recommending skills, learning topics, and educational materials respectively. Also, we interviewed eight senior level experts from educational institutions and career consulting organizations. Interviewees agreed that our curriculum development method has high potential to support authoring activities in dynamic, personalized learning environments.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Software
- Informatik (insg.)
- Mensch-Maschine-Interaktion
- Informatik (insg.)
- Maschinelles Sehen und Mustererkennung
- Informatik (insg.)
- Computernetzwerke und -kommunikation
Zitieren
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- Harvard
- Apa
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- BibTex
- RIS
LAK 2022 - Conference Proceedings: Learning Analytics for Transition, Disruption and Social Change - 12th International Conference on Learning Analytics and Knowledge. 2022. S. 563-569 (ACM International Conference Proceeding Series).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Hybrid Human-AI Curriculum Development for Personalised Informal Learning Environments
AU - Tavakoli, Mohammadreza
AU - Faraji, Abdolali
AU - Molavi, Mohammadreza
AU - Mol, Stefan T.
AU - Kismihók, Gábor
PY - 2022/3/21
Y1 - 2022/3/21
N2 - Informal learning procedures have been changing extremely fast over the recent decades not only due to the advent of online learning, but also due to changes in what humans need to learn to meet their various life and career goals. Consequently, online, educational platforms are expected to provide personalized, up-to-date curricula to assist learners. Therefore, in this paper, we propose an Artificial Intelligence (AI) and Crowdsourcing based approach to create and update curricula for individual learners. We show the design of this curriculum development system prototype, in which contributors receive AI-based recommendations to be able to define and update high-level learning goals, skills, and learning topics together with associated learning content. This curriculum development system was also integrated into our personalized online learning platform. To evaluate our prototype we compared experts' opinion with our system's recommendations, and resulted in 89%, 79%, and 93% F1-scores when recommending skills, learning topics, and educational materials respectively. Also, we interviewed eight senior level experts from educational institutions and career consulting organizations. Interviewees agreed that our curriculum development method has high potential to support authoring activities in dynamic, personalized learning environments.
AB - Informal learning procedures have been changing extremely fast over the recent decades not only due to the advent of online learning, but also due to changes in what humans need to learn to meet their various life and career goals. Consequently, online, educational platforms are expected to provide personalized, up-to-date curricula to assist learners. Therefore, in this paper, we propose an Artificial Intelligence (AI) and Crowdsourcing based approach to create and update curricula for individual learners. We show the design of this curriculum development system prototype, in which contributors receive AI-based recommendations to be able to define and update high-level learning goals, skills, and learning topics together with associated learning content. This curriculum development system was also integrated into our personalized online learning platform. To evaluate our prototype we compared experts' opinion with our system's recommendations, and resulted in 89%, 79%, and 93% F1-scores when recommending skills, learning topics, and educational materials respectively. Also, we interviewed eight senior level experts from educational institutions and career consulting organizations. Interviewees agreed that our curriculum development method has high potential to support authoring activities in dynamic, personalized learning environments.
KW - Artificial Intelligence
KW - Crowdsourcing
KW - Curriculum Development
KW - Informal Learning
UR - http://www.scopus.com/inward/record.url?scp=85126186897&partnerID=8YFLogxK
U2 - 10.1145/3506860.3506917
DO - 10.1145/3506860.3506917
M3 - Conference contribution
AN - SCOPUS:85126186897
T3 - ACM International Conference Proceeding Series
SP - 563
EP - 569
BT - LAK 2022 - Conference Proceedings
T2 - 12th International Conference on Learning Analytics and Knowledge: Learning Analytics for Transition, Disruption and Social Change, LAK 2022
Y2 - 21 March 2022 through 25 March 2022
ER -