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A DIGITAL ADAPTIVE LEARNING SYSTEM FOR DIAGNOSTICS AND SUPPORT OF BASIC ARITHMETIC COMPETENCIES

Authors:
Jingyi Lai at University of Cologne
Jingyi Lai
Parviz Asghari at Amirkabir University of Technology
Parviz Asghari
Lukas Baumanns at TU Dortmund University
Lukas Baumanns
Alexander Pihl
Alexander Pihl
Alexander Pihl
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2022. In C. Fernández, S. Llinares, A. Gutiérrez, & N. Planas (Eds.). Proceedings of the 45th Conference of the
International Group for the Psychology of Mathematics Education, Vol. 4, p. 368). PME.
A DIGITAL ADAPTIVE LEARNING SYSTEM
FOR DIAGNOSTICS AND SUPPORT
OF BASIC ARITHMETIC COMPETENCIES
Jingyi Lai1, Parviz Asghari1, Lukas Baumanns1, Alexander Pihl1,
Achim J. Lilienthal2, Anna L. Simon1, & Maike Schindler1
1University of Cologne, 2Örebro University
Basic arithmetic competencies are a core content of primary mathematics education.
However, some students leave primary school without acquiring sufficient basic
arithmetic competencies, which then often cascades to greater difficulties in the first
years of secondary school (Ehlert et al., 2013). This problem also emerges since, in
practice, teachers may lack resources to individually diagnose student difficulties and
to provide individual support. The KI-ALF project aims at developing a digital
adaptive learning system for diagnosis and support of basic arithmetic competencies,
to facilitate individualized diagnostics and support of students with difficulties.
Eye tracking, the recording of students’ eye movements, has been proven to provide
valuable insights into students’ approaches on arithmetic tasks—especially for students
with mathematical difficulties (Schindler & Lilienthal, 2018). Therefore, the digital
adaptive learning system developed in the KI-ALF project uses eye-tracking data to
diagnose and support students in basic arithmetic competencies.
The poster shows the results of a first study with 24 fifth-graders in a German
comprehensive school, in which we piloted the digital adaptive learning system. For
this purpose, students worked on different kinds of arithmetic tasks on a computer
screen, while their gazes were tracked. The tasks involved, for example, quantity
recognition in structured representations, number line estimation, as well as addition,
subtraction, and multiplication in different representations. In the poster presentation,
we will present the digital adaptive learning system as well as the findings on the
diagnosis of students’ approaches on and difficulties with the basic arithmetic tasks.
Acknowledgment
This project has received funding by the Federal Ministry of Education and Research
as a part of the program KI-ALF (01NV2123). The responsibility for the content of
this publication remains with the authors.
References
Ehlert, A., Fritz, A., Arndt, D., & Leutner, D. (2013). Basic arithmetic competencies of
secondary school students from grades 5 to 7. Journal für Mathematik-Didaktik, 34, 237–
263.
Schindler, M., & Lilienthal, A. J. (2018). Eye-tracking for studying mathematical difficulties
— also in inclusive settings. In E. Bergqvist, M. Österholm, C. Granberg, & L. Sumpter
(Eds.), Proceedings of the 42nd Conference of the IG PME (Vol. 4, pp. 115–122). PME.
Eye Tracking Auto-Correction Using Domain Information
Chapter
  • Jul 2023
  • Lect Notes Comput Sci
Webcam-based eye tracking (wcET) comes with the promise to become a pervasive platform for inexpensive, easy, and quick collection of gaze data without requiring dedicated hardware. To fulfill this promise, wcET must address issues with poor and variable spatial accuracy due to, e.g., participant movement, calibration validity, and the uncertainty of the gaze prediction method used. Eye-tracking (ET) data often suffer particularly from a considerable spatial offset that reduces data quality and heavily affects both qualitative and quantitative ET data analysis. Previous works attempted to mitigate the specific source of spatial offset, e.g., by using chin rests to limit participant movement during ET experiments, by frequent re-calibration or by incorporating head position and facial features into the gaze prediction algorithm. Yet spatial offset remains an issue for wcET, particularly in daily life settings involving children. It is currently unclear (1) if spatial offset can be automatically estimated in absence of ground truth; and (2) whether the estimated offset can be used to obtain substantially higher data quality. In response to the first research question, we propose a method to estimate the spatial offset using domain information. We estimate the spatial offset by maximizing the ET data correlation with Areas of Interests (AOIs) defined over the stimulus. To address the second research question, we developed a wcET system and ran it simultaneously with a commercial remote eye tracker, the Tobii Pro X3-120. After temporal synchronization, we calculated the average distance between the gaze points of the two systems as a measure of data quality. For all tasks investigated, we obtained an overall improvement of the raw data. Specifically, we observed an improvement of 1.35∘^{\circ }, 1.02∘^{\circ }, and 0.92∘^{\circ } in three tasks with varying characteristics of AOIs. This is an important step towards pervasive use of wcET data with a large variety of practical applications.KeywordsEye trackingWebcam-based eye trackingSpatial OffsetSpatial offset correctionData quality
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Eye-tracking for studying mathematical difficulties - also in inclusive settings
Conference Paper
Full-text available
  • Jun 2018
Eye-Tracking (ET) is a promising tool for mathematics education research. Interest is fueled by recent theoretical and technical developments, and the potential to identify strategies students use in mathematical tasks. This makes ET interesting for studying students with mathematical difficulties (MD), also with a view on inclusive settings. We present a systematic analysis of the opportunities ET may hold for understanding strategies of students with MD. Based on an empirical study with 20 fifth graders (10 with MD), we illustrate that and why ET offers opportunities especially for students with MD and describe main advantages. We also identify limitations of think aloud protocols, using ET as validation method, and present characteristics of students' strategies in tasks on quantity recognition in structured whole number representations.
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Basic arithmetic competencies of secondary school students from grades 5 to 7
  • Jan 2013
  • 237-263
  • A Ehlert
  • A Fritz
  • D Arndt
  • D Leutner
Ehlert, A., Fritz, A., Arndt, D., & Leutner, D. (2013). Basic arithmetic competencies of secondary school students from grades 5 to 7. Journal für Mathematik-Didaktik, 34, 237-263.