%0 Book Section %1 Lallé2017 %A Lallé, Sébastien %A Taub, Michelle %A Mudrick, Nicholas V. %A Conati, Cristina %A Azevedo, Roger %B Artificial Intelligence in Education: 18th International Conference, AIED 2017, Wuhan, China, June 28 -- July 1, 2017, Proceedings %C Cham %D 2017 %E André, Elisabeth %E Baker, Ryan %E Hu, Xiangen %E Rodrigo, Ma. Mercedes T. %E du Boulay, Benedict %I Springer International Publishing %K eye-tracking individual-differences intelligent-tutoring its %P 149--161 %R 10.1007/978-3-319-61425-0_13 %T The Impact of Student Individual Differences and Visual Attention to Pedagogical Agents During Learning with MetaTutor %U https://doi.org/10.1007/978-3-319-61425-0_13 %X In this paper, we investigate the relationship between students' (N = 28) individual differences and visual attention to pedagogical agents (PAs) during learning with MetaTutor, a hypermedia-based intelligent tutoring systems. We used eye tracking to capture visual attention to the PAs, and our results reveal specific visual attention-related metrics (e.g., fixation rate, longest fixations) that are significantly influenced by learning depending on student achievement goals. Specifically, performance-oriented students learned more with a long longest fixation and a high fixation rate on the PAs, whereas mastery-oriented students learned less with a high fixation rate on the PAs. Our findings contribute to understanding how to design PAs that can better adapt to student achievement goals and visual attention to the PA. %@ 978-3-319-61425-0

@inbook{Lallé2017, abstract = {In this paper, we investigate the relationship between students' (N = 28) individual differences and visual attention to pedagogical agents (PAs) during learning with MetaTutor, a hypermedia-based intelligent tutoring systems. We used eye tracking to capture visual attention to the PAs, and our results reveal specific visual attention-related metrics (e.g., fixation rate, longest fixations) that are significantly influenced by learning depending on student achievement goals. Specifically, performance-oriented students learned more with a long longest fixation and a high fixation rate on the PAs, whereas mastery-oriented students learned less with a high fixation rate on the PAs. Our findings contribute to understanding how to design PAs that can better adapt to student achievement goals and visual attention to the PA.}, added-at = {2017-11-29T15:41:17.000+0100}, address = {Cham}, author = {Lall{\'e}, S{\'e}bastien and Taub, Michelle and Mudrick, Nicholas V. and Conati, Cristina and Azevedo, Roger}, biburl = {https://www.bibsonomy.org/bibtex/2e122132c699c5a60238a6995d6342746/brusilovsky}, booktitle = {Artificial Intelligence in Education: 18th International Conference, AIED 2017, Wuhan, China, June 28 -- July 1, 2017, Proceedings}, description = {The Impact of Student Individual Differences and Visual Attention to Pedagogical Agents During Learning with MetaTutor | SpringerLink}, doi = {10.1007/978-3-319-61425-0_13}, editor = {Andr{\'e}, Elisabeth and Baker, Ryan and Hu, Xiangen and Rodrigo, Ma. Mercedes T. and du Boulay, Benedict}, interhash = {6ccf3bf09c9f3f98d03aca4cd29ba2ae}, intrahash = {e122132c699c5a60238a6995d6342746}, isbn = {978-3-319-61425-0}, keywords = {eye-tracking individual-differences intelligent-tutoring its}, pages = {149--161}, publisher = {Springer International Publishing}, timestamp = {2017-11-29T15:41:17.000+0100}, title = {The Impact of Student Individual Differences and Visual Attention to Pedagogical Agents During Learning with MetaTutor}, url = {https://doi.org/10.1007/978-3-319-61425-0_13}, year = 2017 }