Learning requires a multitude of metacognitive activities that support knowledge acquisition and direct the learning process. These include selecting and planning goals, applying, observing and evaluating learning strategies as well as regulatory efforts required for goal achievement. We introduce an example of how learners can be supported to set goals, implement periods of focused work and integrate a meaningful break management by using the AI-based training software ACTrain. Metacognitive feedback based on principles of machine learning conveys the value of staying focused on goal-related activities. Pilot results already indicate positive effects of the presented approach and suggest further investigation. We will explore potentials for integrating such approach in school settings and how this could affect the role of teachers.
%0 Generic
%1 wirzberger2021actrainschool
%A Wirzberger, Maria
%B EARLI 2021 - Online
%D 2021
%K AI attention classroom learning myown self-regulation
%T ACTrain@School: Can we bring AI to the classroom to foster self-regulated learning?
%U https://maria-wirzberger.de/wp-content/uploads/2021/04/ICT_Demo_ACTrain_Schools_final.pdf
%X Learning requires a multitude of metacognitive activities that support knowledge acquisition and direct the learning process. These include selecting and planning goals, applying, observing and evaluating learning strategies as well as regulatory efforts required for goal achievement. We introduce an example of how learners can be supported to set goals, implement periods of focused work and integrate a meaningful break management by using the AI-based training software ACTrain. Metacognitive feedback based on principles of machine learning conveys the value of staying focused on goal-related activities. Pilot results already indicate positive effects of the presented approach and suggest further investigation. We will explore potentials for integrating such approach in school settings and how this could affect the role of teachers.
@conference{wirzberger2021actrainschool,
abstract = {Learning requires a multitude of metacognitive activities that support knowledge acquisition and direct the learning process. These include selecting and planning goals, applying, observing and evaluating learning strategies as well as regulatory efforts required for goal achievement. We introduce an example of how learners can be supported to set goals, implement periods of focused work and integrate a meaningful break management by using the AI-based training software ACTrain. Metacognitive feedback based on principles of machine learning conveys the value of staying focused on goal-related activities. Pilot results already indicate positive effects of the presented approach and suggest further investigation. We will explore potentials for integrating such approach in school settings and how this could affect the role of teachers.},
added-at = {2021-04-07T12:37:01.000+0200},
author = {Wirzberger, Maria},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2a890e58a66f50878855f0536ab5f019c/mariawirzberger},
booktitle = {EARLI 2021 - Online},
interhash = {7b273695105a95d40f5ea507bdf31191},
intrahash = {a890e58a66f50878855f0536ab5f019c},
keywords = {AI attention classroom learning myown self-regulation},
timestamp = {2023-09-23T09:28:05.000+0200},
title = {ACTrain@School: Can we bring AI to the classroom to foster self-regulated learning?},
url = {https://maria-wirzberger.de/wp-content/uploads/2021/04/ICT_Demo_ACTrain_Schools_final.pdf},
venue = {EARLI 2021 - Online},
year = 2021
}
