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sphereML

0.1.1Package record

Analyzing Students' Performance Dataset in Physics Education Research (SPHERE) using Machine Learning (ML)

0packages depend
2.1Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

A simple package facilitating ML based analysis for physics education research (PER) purposes. The implemented machine learning technique is random forest optimized by item response theory (IRT) for feature selection and genetic algorithm (GA) for hyperparameter tuning. The data analyzed here has been made available in the CRAN repository through the 'spheredata' package. The SPHERE stands for Students' Performance in Physics Education Research (PER). The students are the eleventh graders learning physics at the high school curriculum. We follow the stream of multidimensional students' assessment as probed by some research based assessments 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 predicting students' performance on physics are also demonstrated.

Install

Health

CRAN checks
13OK
Slowest check: 3.3 min · r-oldrel-windows-x86_64
Status changes
  • OK13 OK2026-08-04
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK13 OK2026-06-09
  • ERROR12 OK, 1 ERROR2026-06-08
  • OK12 OK2026-04-25
Show 1 earlier changeHide 1 earlier change
  • ERROR13 OK, 1 ERROR2026-03-10
Advisories

none known

Documentation

In release 0.1.1
READMENoVignettesNoNEWSNoCitation fileNoWebsitenot declared in DESCRIPTION
Help pages
1
Examples that run
0%1 never run
Exported functions with examples
100%
Documented parameters
not tracked
Return-value docs
100%
Help pages citing references
0%

Downloads

2.1K
CRAN downloads in the past year
Rank #19,521 · ~6/day · ~173/mo
Daily download trend is not available in this view yet.
29430 days
68090 days
2.1K1 year
Compare downloads with other packages →
Also on67 r2u1 autocran

Repository

0Stars
0Forks
0Open issues
0Open PRs
0Releases
Last activity 2024-11-20 · The default branch showed an older version (0.1.0) than CRAN on 2026-10-21
Responsiveness
not measured
PracticesBeta

1 development-tooling and community-health practice detected across 1 family in the upstream repository

Checks run against github.com/santosoph/sphereml on 2026-10-21.

Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v4 (2026-10-20)

Dependencies

Declared dependencies
15 external dependencies (excludes base and recommended)

Installing sphereML adds 164 packages (84 with compiled code, 123 MB of source tarballs). Heaviest: BH 14 MB, stringi 11 MB, ggplot2 6.0 MB.

Depends (1)
R >= 3.50
LinkingTo (0)
none
Suggests (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

People & History

People (3)
Author, Maintainer since 0.1.0 (2025)
Contributor
Releases (2)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • 0.1.1Latest
    record
    2025-05-09 · current release · diff ↗
  • R
    R 4.5.0 released · 2025-04-11
  • 0.1.0
    record
    2025-02-06
  • R
    R 4.4.0 released · 2024-04-24

Package metadata

First published
2025-02-06
Total releases
2 / 1 yrs
License
MIT + file LICENSE OSI
Minimum R
≥ 3.50
Download size
180 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("sphereML")
Santoso, P. H., Haryanto, H., & Istiyono, E. (2025). sphereML: Analyzing Students' Performance Dataset in Physics Education Research (SPHERE) using Machine Learning (ML) (Version 0.1.1) [Computer software]. https://doi.org/10.32614/CRAN.package.sphereML

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for sphereML version 0.1.1 [Data set]. HJJB, LLC. Data release v2026-10-25. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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