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license: MIT
title: 'sphereML: Analyzing Students'' Performance Dataset in Physics Education Research
  (SPHERE) using Machine Learning (ML)'
version: 0.1.0
doi: 10.32614/CRAN.package.sphereML
abstract: A shiny R package facilitating ML based analysis for physics education research
  (PER) purposes. The data has been made available in the CRAN repository through
  the spheredata package. SPHERE stands for Students' Performance in Physics Education
  Research (PER). The students are the eleventh graders learning physics at high school
  curriculum. We follow the stream of multidimensional students' assessment as probed
  by some research based assessments (RBAs) in PER. The goal is to predict the students'
  performance at the end of the learning process. Three learning domains are measured
  including conceptual understanding, scientific ability, and scientific attitude.
  Furthermore, demographic backgrounds and potential variables influencing students'
  performance on physics are also demonstrated. We provide teachers' judgment data
  as our baseline to compare the predictive results of students' performance between
  machine learning (ML) based analysis and teacher (human) based judgment. Click on
  the Tab below to explore the detail of each data further.
authors:
- family-names: Santoso
  given-names: Purwoko Haryadi
  email: purwokoharyadisantoso@unsulbar.ac.id
  orcid: https://orcid.org/<0000-0002-7093-5309>
repository: https://santosoph.r-universe.dev
repository-code: https://github.com/santosoph/sphereML
commit: 24c951b25bfbe70b68384baea9efab0f7115bab8
url: https://github.com/santosoph/sphereML
contact:
- family-names: Santoso
  given-names: Purwoko Haryadi
  email: purwokoharyadisantoso@unsulbar.ac.id
  orcid: https://orcid.org/<0000-0002-7093-5309>