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Combining physics education and machine learning research to measure evidence of students’ mechanistic sensemaking

Kaitlin Gili1,*, Kyle Heuton1, Astha Shah1, David Hammer2,†, and Michael C. Hughes1,†

  • 1Department of Computer Science, Tufts University, Medford, Massachusetts, USA
  • 2Department of Education and Department of Physics and Astronomy, Tufts University, Medford, Massachusetts, USA

  • *Contact author: kgili01@tufts.edu
  • †These authors contributed equally to this work.

Testing the validity of embedding-based similarity and clustering for handwritten physics solutions

Maike Tauschhuber and Gerd Kortemeyer

Phys. Rev. Phys. Educ. Res. 22 020147 (2026)

Enhancing high school students’ sensemaking through scientific sensemaking project-based learning

Sumardiana, Endang Purwaningsih, Lutfiyanti Fitriah, and Ahmad Taufiq

Multidiscip. Sci. J. 9 2027146 (2026)

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