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Toward Better Outcomes in Audiology Distance Education: An Educational Data Mining Approach.

Bruno Elias Penteado1, Paula Maria Pereira Paiva2, Marina Morettin-Zupelari2

  • 1Institute of Mathematical and Computer Sciences, University of São Paulo, São Carlos, Brazil.

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Educational Data Mining (EDM) offers audiology educators new tools to analyze student data from online courses. This approach enhances understanding and management of educational processes in audiology distance learning.

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Area of Science:

  • Educational Data Mining (EDM)
  • Digital Learning Analytics

Background:

  • The field of Educational Data Mining (EDM) provides a framework for understanding educational processes.
  • Audiology educators can benefit from data-driven insights to improve online course delivery.

Purpose of the Study:

  • To introduce EDM concepts, taxonomy, and applications to audiology educators.
  • To provide a foundation for developing EDM in audiology distance education.

Main Methods:

  • A narrative review of EDM concepts and methodologies.
  • Exemplification of EDM methods using real data from an online pediatric auditory rehabilitation course.

Main Results:

  • Overview of EDM concepts, applications, and methods.
  • Demonstration of EDM for predicting help-seeking, modeling interactions, analyzing student trajectories, and understanding group work.
  • Insights into supporting teaching and learning processes.

Conclusions:

  • EDM methods uncover knowledge from digital traces (logs) to inform stakeholders.
  • This approach can improve awareness of course dynamics and foster better management of audiology distance education.