@inproceedings{a1e19e4a14a14968bcdebae1d46d2898,
title = "Evaluating the effect of uncertainty visualisation in open learner models on students{\textquoteright} metacognitive skills",
abstract = "Self-assessment is widely used in open learner models (OLMs) as a metacognitive process to enhance students{\textquoteright} self-regulated learning. Yet little research has investigated the impact of the visualisation when the OLM shows the conflict (i.e., uncertainty) between the system{\textquoteright}s beliefs about student knowledge and students{\textquoteright} confidence in the correctness of their answers. We deployed such an OLM and studied its use. The impact of the uncertainty visualisation on student learning, confidence gains and actions was determined by comparing these measures across two treatment conditions and a control condition. Those who accessed the OLM performed significantly better on the post-test, and those in the treatment group who could see both sets of beliefs separately showed greater confidence gains and used the system more.",
keywords = "Learning dashboards, Metacognitive skills, Open learner models, Self-confidence, Uncertainty, Visualisation",
author = "Lamiya Al-Shanfari and {Demmans Epp}, Carrie and Chris Baber",
note = "Part of the Lecture Notes in Computer Science book series (LNCS, volume 10331). Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 10331).; 18th International Conference on Artificial Intelligence in Education, AIED 2017 ; Conference date: 28-06-2017 Through 01-07-2017",
year = "2017",
month = jun,
day = "23",
doi = "10.1007/978-3-319-61425-0_2",
language = "English",
isbn = "9783319614243",
volume = "10331 LNAI",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "15--27",
booktitle = "Artificial Intelligence in Education",
}