Exploring students’ affective states during learning with external representations

Beate Grawemeyer, Manolis Mavrikis, Claudia Mazziotti, Alice Hansen, Anouschka van Leeuwen, Nikol Rummel

Research output: Chapter in Book/Report/Conference proceedingConference proceedingpeer-review

1 Citation (Scopus)
15 Downloads (Pure)


We conducted a user study that explored the relationship between students’ usage of multiple external representations and their affective states during fractions learning. We use the affective states of the student as a proxy indicator for the ease of reasoning with the representation. Extending existing literature that highlights the advantages of learning with multiple external representations, our results indicate that low-performing students have difficulties in reasoning with representations that do not fully accommodate the fraction as a part-whole concept. In contrast, high-performing students were at ease with a range of representations, including the ones that vaguely involved the fraction as part-whole concept.

Original languageEnglish
Title of host publicationArtificial Intelligence in Education - 18th International Conference, AIED 2017, Proceedings
PublisherSpringer-Verlag London Ltd
Number of pages5
Volume10331 LNAI
ISBN (Electronic)978-3-319-61425-0
ISBN (Print)9783319614243
Publication statusE-pub ahead of print - 23 Jun 2017
Externally publishedYes
Event18th International Conference on Artificial Intelligence in Education, AIED 2017 - Wuhan, China
Duration: 28 Jun 20171 Jul 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10331 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference18th International Conference on Artificial Intelligence in Education, AIED 2017

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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