| Title: | Students' Performance Dataset in Physics Education Research (SPHERE) |
| Version: | 0.1.3 |
| Maintainer: | Purwoko Haryadi Santoso <purwokoharyadisantoso@unsulbar.ac.id> |
| Description: | A multidimensional dataset of students' performance assessment in high school physics. The SPHERE dataset was collected from 497 students in four public high schools specifically measuring their conceptual understanding, scientific ability, and attitude toward physics [see Santoso et al. (2024) <doi:10.17632/88d7m2fv7p.1>]. The data collection was conducted using some research based assessments established by the physics education research community. They include the Force Concept Inventory, the Force and Motion Conceptual Evaluation, the Rotational and Rolling Motion Conceptual Survey, the Fluid Mechanics Concept Inventory, the Mechanical Waves Conceptual Survey, the Thermal Concept Evaluation, the Survey of Thermodynamic Processes and First and Second Laws, the Scientific Abilities Assessment Rubrics, and the Colorado Learning Attitudes about Science Survey. Students' attributes related to gender, age, socioeconomic status, domicile, literacy, physics identity, and test results administered using teachers' developed items are also reported in this dataset. |
| BugReports: | https://github.com/santosoph/spheredata/issues |
| URL: | https://github.com/santosoph/spheredata |
| License: | CC BY 4.0 |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.3.2 |
| Depends: | R (≥ 3.50) |
| LazyData: | true |
| NeedsCompilation: | no |
| Packaged: | 2025-05-09 16:49:13 UTC; ASUS |
| Author: | Purwoko Haryadi Santoso
 [aut, cre],
Edi Istiyono [ctb],
Haryanto Haryanto [ctb] |
| Repository: | CRAN |
| Date/Publication: | 2025-05-09 17:10:02 UTC |
The Colorado Learning Attitudes about Science Survey (CLASS) dataset
Description
The CLASS originally includes 42 attitudinal items measuring students' attitude toward physics learning within five categories of Likert scale ranging from strongly disagree (1) to strongly agree (5). In this package, thirty-six CLASS items have been preprocessed based on the scoring rule as suggested by Adams et al. (2006).
Usage
data(CLASS)Format
A data frame of students' responses on the following 36 CLASS items (after preprocessed using the scoring rule).
CLASS1A student's response on the CLASS item number 1.
CLASS2A student's response on the CLASS item number 2.
CLASS3A student's response on the CLASS item number 3.
CLASS5A student's response on the CLASS item number 5.
CLASS6A student's response on the CLASS item number 6.
CLASS8A student's response on the CLASS item number 8.
CLASS10A student's response on the CLASS item number 10.
CLASS11A student's response on the CLASS item number 11.
CLASS12A student's response on the CLASS item number 12.
CLASS13A student's response on the CLASS item number 13.
CLASS14A student's response on the CLASS item number 14.
CLASS15A student's response on the CLASS item number 15.
CLASS16A student's response on the CLASS item number 16.
CLASS17A student's response on the CLASS item number 17.
CLASS18A student's response on the CLASS item number 18.
CLASS19A student's response on the CLASS item number 19.
CLASS20A student's response on the CLASS item number 20.
CLASS21A student's response on the CLASS item number 21.
CLASS22A student's response on the CLASS item number 22.
CLASS23A student's response on the CLASS item number 23.
CLASS24A student's response on the CLASS item number 24.
CLASS25A student's response on the CLASS item number 25.
CLASS26A student's response on the CLASS item number 26.
CLASS27A student's response on the CLASS item number 27.
CLASS28A student's response on the CLASS item number 28.
CLASS29A student's response on the CLASS item number 29.
CLASS30A student's response on the CLASS item number 30.
CLASS32A student's response on the CLASS item number 32.
CLASS34A student's response on the CLASS item number 34.
CLASS35A student's response on the CLASS item number 35.
CLASS36A student's response on the CLASS item number 36.
CLASS37A student's response on the CLASS item number 37.
CLASS38A student's response on the CLASS item number 38.
CLASS39A student's response on the CLASS item number 39.
CLASS40A student's response on the CLASS item number 40.
CLASS42A student's response on the CLASS item number 42.
Source
Santoso, P. H. et al. SPHERE: Students' performance dataset of conceptual understanding, scientific ability, and learning attitude in physics education research (PER). Mendeley Data, V1, (2024). doi: 10.17632/88d7m2fv7p.1
References
Adams, W. K. et al. New instrument for measuring student beliefs about physics and learning physics: The Colorado Learning Attitudes about Science Survey. Physical Review Special Topics - Physics Education Research 2, 010101 (2006).
Examples
library(spheredata)
# Call the data from spheredata package
get("CLASS")
# Open the data
CLASS
The Colorado Learning Attitudes about Science Survey (CLASS) content validity dataset
Description
In this data, five PER experts rated the content validity of the CLASS.
Usage
data(CLASScontentvalidity)Format
A data frame of expert ratings on the content validity of 36 CLASS items (after preprocessed using the scoring rule).
IDAn anonymized expert identity.
CLASS1A numeric of expert rating to the CLASS item 1.
CLASS2A numeric of expert rating to the CLASS item 2.
CLASS3A numeric of expert rating to the CLASS item 3.
CLASS5A numeric of expert rating to the CLASS item 5.
CLASS6A numeric of expert rating to the CLASS item 6.
CLASS8A numeric of expert rating to the CLASS item 8.
CLASS10A numeric of expert rating to the CLASS item 10.
CLASS11A numeric of expert rating to the CLASS item 11.
CLASS12A numeric of expert rating to the CLASS item 12.
CLASS13A numeric of expert rating to the CLASS item 13.
CLASS14A numeric of expert rating to the CLASS item 14.
CLASS15A numeric of expert rating to the CLASS item 15.
CLASS16A numeric of expert rating to the CLASS item 16.
CLASS17A numeric of expert rating to the CLASS item 17.
CLASS18A numeric of expert rating to the CLASS item 18.
CLASS19A numeric of expert rating to the CLASS item 19.
CLASS20A numeric of expert rating to the CLASS item 20.
CLASS21A numeric of expert rating to the CLASS item 21.
CLASS22A numeric of expert rating to the CLASS item 22.
CLASS23A numeric of expert rating to the CLASS item 23.
CLASS24A numeric of expert rating to the CLASS item 24.
CLASS25A numeric of expert rating to the CLASS item 25.
CLASS26A numeric of expert rating to the CLASS item 26.
CLASS27A numeric of expert rating to the CLASS item 27.
CLASS28A numeric of expert rating to the CLASS item 28.
CLASS29A numeric of expert rating to the CLASS item 29.
CLASS30A numeric of expert rating to the CLASS item 30.
CLASS32A numeric of expert rating to the CLASS item 32.
CLASS34A numeric of expert rating to the CLASS item 34.
CLASS35A numeric of expert rating to the CLASS item 35.
CLASS36A numeric of expert rating to the CLASS item 36.
CLASS37A numeric of expert rating to the CLASS item 37.
CLASS38A numeric of expert rating to the CLASS item 38.
CLASS39A numeric of expert rating to the CLASS item 39.
CLASS40A numeric of expert rating to the CLASS item 40.
CLASS42A numeric of expert rating to the CLASS item 42.
Examples
library(spheredata)
# Call the data from spheredata package
get("CLASScontentvalidity")
# Open the data
CLASScontentvalidity
The Force Concept Inventory (FCI) dataset
Description
The focus of the FCI is intended to measure students’ conceptual understanding of Newtonian mechanics. It comprises of 30 multiple-choice items with five possible responses (a key and four distractors).
Usage
data(FCI)Format
A data frame of students' responses on the following 30 FCI multiple choice items.
FCI1A student's response on the FCI item number 1.
FCI2A student's response on the FCI item number 2.
FCI3A student's response on the FCI item number 3.
FCI4A student's response on the FCI item number 4.
FCI5A student's response on the FCI item number 5.
FCI6A student's response on the FCI item number 6.
FCI7A student's response on the FCI item number 7.
FCI8A student's response on the FCI item number 8.
FCI9A student's response on the FCI item number 9.
FCI10A student's response on the FCI item number 10.
FCI11A student's response on the FCI item number 11.
FCI12A student's response on the FCI item number 12.
FCI13A student's response on the FCI item number 13.
FCI14A student's response on the FCI item number 14.
FCI15A student's response on the FCI item number 15.
FCI16A student's response on the FCI item number 16.
FCI17A student's response on the FCI item number 17.
FCI18A student's response on the FCI item number 18.
FCI19A student's response on the FCI item number 19.
FCI20A student's response on the FCI item number 20.
FCI21A student's response on the FCI item number 21.
FCI22A student's response on the FCI item number 22.
FCI23A student's response on the FCI item number 23.
FCI24A student's response on the FCI item number 24.
FCI25A student's response on the FCI item number 25.
FCI26A student's response on the FCI item number 26.
FCI27A student's response on the FCI item number 27.
FCI28A student's response on the FCI item number 28.
FCI29A student's response on the FCI item number 29.
FCI30A student's response on the FCI item number 30.
Source
Santoso, P. H. et al. SPHERE: Students' performance dataset of conceptual understanding, scientific ability, and learning attitude in physics education research (PER). Mendeley Data, V1, (2024). doi: 10.17632/88d7m2fv7p.1.
References
Hestenes, D., Wells, M. & Swackhamer, G. Force concept inventory. Phys Teach 30, 141–158 (1992).
Examples
library(spheredata)
# Call the data from spheredata package
get("FCI")
# Open the data
FCI
The Force Concept Inventory (FCI) content validity dataset
Description
In this data, five PER experts rated the content validity of the FCI.
Usage
data(FCIcontentvalidity)Format
A data frame of expert ratings on the content validity of 30 FCI items.
IDAn anonymized expert identity.
FCI1A numeric value of expert rating to the FCI item number 1.
FCI2A numeric value of expert rating to the FCI item number 2.
FCI3A numeric value of expert rating to the FCI item number 3.
FCI4A numeric value of expert rating to the FCI item number 4.
FCI5A numeric value of expert rating to the FCI item number 5.
FCI6A numeric value of expert rating to the FCI item number 6.
FCI7A numeric value of expert rating to the FCI item number 7.
FCI8A numeric value of expert rating to the FCI item number 8.
FCI9A numeric value of expert rating to the FCI item number 9.
FCI10A numeric value of expert rating to the FCI item number 10.
FCI11A numeric value of expert rating to the FCI item number 11.
FCI12A numeric value of expert rating to the FCI item number 12.
FCI13A numeric value of expert rating to the FCI item number 13.
FCI14A numeric value of expert rating to the FCI item number 14.
FCI15A numeric value of expert rating to the FCI item number 15.
FCI16A numeric value of expert rating to the FCI item number 16.
FCI17A numeric value of expert rating to the FCI item number 17.
FCI18A numeric value of expert rating to the FCI item number 18.
FCI19A numeric value of expert rating to the FCI item number 19.
FCI20A numeric value of expert rating to the FCI item number 20.
FCI21A numeric value of expert rating to the FCI item number 21.
FCI22A numeric value of expert rating to the FCI item number 22.
FCI23A numeric value of expert rating to the FCI item number 23.
FCI24A numeric value of expert rating to the FCI item number 24.
FCI25A numeric value of expert rating to the FCI item number 25.
FCI26A numeric value of expert rating to the FCI item number 26.
FCI27A numeric value of expert rating to the FCI item number 27.
FCI28A numeric value of expert rating to the FCI item number 28.
FCI29A numeric value of expert rating to the FCI item number 29.
FCI30A numeric value of expert rating to the FCI item number 30.
Examples
library(spheredata)
# Call the data from spheredata package
get("FCIcontentvalidity")
# Open the data
FCIcontentvalidity
The Force Concept Inventory (FCI) key dataset
Description
The answers key to analyze the students' obtained score on the FCI.
Usage
data(FCIkey)Format
A data frame of answer keys on the following 30 FCI items.
FCI1A key of the FCI item number 1.
FCI2A key of the FCI item number 2.
FCI3A key of the FCI item number 3.
FCI4A key of the FCI item number 4.
FCI5A key of the FCI item number 5.
FCI6A key of the FCI item number 6.
FCI7A key of the FCI item number 7.
FCI8A key of the FCI item number 8.
FCI9A key of the FCI item number 9.
FCI10A key of the FCI item number 10.
FCI11A key of the FCI item number 11.
FCI12A key of the FCI item number 12.
FCI13A key of the FCI item number 13.
FCI14A key of the FCI item number 14.
FCI15A key of the FCI item number 15.
FCI16A key of the FCI item number 16.
FCI17A key of the FCI item number 17.
FCI18A key of the FCI item number 18.
FCI19A key of the FCI item number 19.
FCI20A key of the FCI item number 20.
FCI21A key of the FCI item number 21.
FCI22A key of the FCI item number 22.
FCI23A key of the FCI item number 23.
FCI24A key of the FCI item number 24.
FCI25A key of the FCI item number 25.
FCI26A key of the FCI item number 26.
FCI27A key of the FCI item number 27.
FCI28A key of the FCI item number 28.
FCI29A key of the FCI item number 29.
FCI30A key of the FCI item number 30.
Examples
library(spheredata)
# Call the data from spheredata package
get("FCIkey")
# Open the data
FCIkey
The Force and Motion Conceptual Evaluation (FMCE) dataset
Description
Similar with the FCI, the goal of the FMCE is also intended to measure students’ conceptual understanding of Newtonian mechanics. It comprises of 47 multiple-choice items.
Usage
data(FMCE)Format
A data frame of students' responses on the following 47 FMCE multiple choice items.
FMCE1A student's response on the FMCE item number 1.
FMCE2A student's response on the FMCE item number 2.
FMCE3A student's response on the FMCE item number 3.
FMCE4A student's response on the FMCE item number 4.
FMCE5A student's response on the FMCE item number 5.
FMCE6A student's response on the FMCE item number 6.
FMCE7A student's response on the FMCE item number 7.
FMCE8A student's response on the FMCE item number 8.
FMCE9A student's response on the FMCE item number 9.
FMCE10A student's response on the FMCE item number 10.
FMCE11A student's response on the FMCE item number 11.
FMCE12A student's response on the FMCE item number 12.
FMCE13A student's response on the FMCE item number 13.
FMCE14A student's response on the FMCE item number 14.
FMCE15A student's response on the FMCE item number 15.
FMCE16A student's response on the FMCE item number 16.
FMCE17A student's response on the FMCE item number 17.
FMCE18A student's response on the FMCE item number 18.
FMCE19A student's response on the FMCE item number 19.
FMCE20A student's response on the FMCE item number 20.
FMCE21A student's response on the FMCE item number 21.
FMCE22A student's response on the FMCE item number 22.
FMCE23A student's response on the FMCE item number 23.
FMCE24A student's response on the FMCE item number 24.
FMCE25A student's response on the FMCE item number 25.
FMCE26A student's response on the FMCE item number 26.
FMCE27A student's response on the FMCE item number 27.
FMCE28A student's response on the FMCE item number 28.
FMCE29A student's response on the FMCE item number 29.
FMCE30A student's response on the FMCE item number 30.
FMCE31A student's response on the FMCE item number 31.
FMCE32A student's response on the FMCE item number 32.
FMCE33A student's response on the FMCE item number 33.
FMCE34A student's response on the FMCE item number 34.
FMCE35A student's response on the FMCE item number 35.
FMCE36A student's response on the FMCE item number 36.
FMCE37A student's response on the FMCE item number 37.
FMCE38A student's response on the FMCE item number 38.
FMCE39A student's response on the FMCE item number 39.
FMCE40A student's response on the FMCE item number 40.
FMCE41A student's response on the FMCE item number 41.
FMCE42A student's response on the FMCE item number 42.
FMCE43A student's response on the FMCE item number 43.
FMCE44A student's response on the FMCE item number 44.
FMCE45A student's response on the FMCE item number 45.
FMCE46A student's response on the FMCE item number 46.
FMCE47A student's response on the FMCE item number 47.
Source
Santoso, P. H. et al. SPHERE: Students' performance dataset of conceptual understanding, scientific ability, and learning attitude in physics education research (PER). Mendeley Data, V1, (2024). doi: 10.17632/88d7m2fv7p.1.
References
Thornton, R. K. & Sokoloff, D. R. Assessing student learning of Newton’s laws: The Force and Motion Conceptual Evaluation and the Evaluation of Active Learning Laboratory and Lecture Curricula. Am J Phys 66, 338–352 (1998).
Examples
library(spheredata)
# Call the data from spheredata package
get("FMCE")
# Open the data
FMCE
The Force and Motion Conceptual Evaluation (FMCE) content validity dataset
Description
In this data, five PER experts rated the content validity of the FMCE.
Usage
data(FMCEcontentvalidity)Format
A data frame of expert ratings on the content validity of 47 FMCE items.
IDAn anonymized expert identity.
FMCE1A numeric value of expert rating to the FMCE item number 1.
FMCE2A numeric value of expert rating to the FMCE item number 2.
FMCE3A numeric value of expert rating to the FMCE item number 3.
FMCE4A numeric value of expert rating to the FMCE item number 4.
FMCE5A numeric value of expert rating to the FMCE item number 5.
FMCE6A numeric value of expert rating to the FMCE item number 6.
FMCE7A numeric value of expert rating to the FMCE item number 7.
FMCE8A numeric value of expert rating to the FMCE item number 8.
FMCE9A numeric value of expert rating to the FMCE item number 9.
FMCE10A numeric value of expert rating to the FMCE item number 10.
FMCE11A numeric value of expert rating to the FMCE item number 11.
FMCE12A numeric value of expert rating to the FMCE item number 12.
FMCE13A numeric value of expert rating to the FMCE item number 13.
FMCE14A numeric value of expert rating to the FMCE item number 14.
FMCE15A numeric value of expert rating to the FMCE item number 15.
FMCE16A numeric value of expert rating to the FMCE item number 16.
FMCE17A numeric value of expert rating to the FMCE item number 17.
FMCE18A numeric value of expert rating to the FMCE item number 18.
FMCE19A numeric value of expert rating to the FMCE item number 19.
FMCE20A numeric value of expert rating to the FMCE item number 20.
FMCE21A numeric value of expert rating to the FMCE item number 21.
FMCE22A numeric value of expert rating to the FMCE item number 22.
FMCE23A numeric value of expert rating to the FMCE item number 23.
FMCE24A numeric value of expert rating to the FMCE item number 24.
FMCE25A numeric value of expert rating to the FMCE item number 25.
FMCE26A numeric value of expert rating to the FMCE item number 26.
FMCE27A numeric value of expert rating to the FMCE item number 27.
FMCE28A numeric value of expert rating to the FMCE item number 28.
FMCE29A numeric value of expert rating to the FMCE item number 29.
FMCE30A numeric value of expert rating to the FMCE item number 30.
FMCE31A numeric value of expert rating to the FMCE item number 31.
FMCE32A numeric value of expert rating to the FMCE item number 32.
FMCE33A numeric value of expert rating to the FMCE item number 33.
FMCE34A numeric value of expert rating to the FMCE item number 34.
FMCE35A numeric value of expert rating to the FMCE item number 35.
FMCE36A numeric value of expert rating to the FMCE item number 36.
FMCE37A numeric value of expert rating to the FMCE item number 37.
FMCE38A numeric value of expert rating to the FMCE item number 38.
FMCE39A numeric value of expert rating to the FMCE item number 39.
FMCE40A numeric value of expert rating to the FMCE item number 40.
FMCE41A numeric value of expert rating to the FMCE item number 41.
FMCE42A numeric value of expert rating to the FMCE item number 42.
FMCE43A numeric value of expert rating to the FMCE item number 43.
FMCE44A numeric value of expert rating to the FMCE item number 44.
FMCE45A numeric value of expert rating to the FMCE item number 45.
FMCE46A numeric value of expert rating to the FMCE item number 46.
FMCE47A numeric value of expert rating to the FMCE item number 47.
Examples
library(spheredata)
# Call the data from spheredata package
get("FMCEcontentvalidity")
# Open the data
FMCEcontentvalidity
The Force and Motion Conceptual Evaluation (FMCE) key dataset
Description
The answers key to analyze the students' obtained score on the FMCE.
Usage
data(FMCEkey)Format
A data frame of answer keys on the following 47 FMCE items.
FMCE1A key of the FMCE item number 1.
FMCE2A key of the FMCE item number 2.
FMCE3A key of the FMCE item number 3.
FMCE4A key of the FMCE item number 4.
FMCE5A key of the FMCE item number 5.
FMCE6A key of the FMCE item number 6.
FMCE7A key of the FMCE item number 7.
FMCE8A key of the FMCE item number 8.
FMCE9A key of the FMCE item number 9.
FMCE10A key of the FMCE item number 10.
FMCE11A key of the FMCE item number 11.
FMCE12A key of the FMCE item number 12.
FMCE13A key of the FMCE item number 13.
FMCE14A key of the FMCE item number 14.
FMCE15A key of the FMCE item number 15.
FMCE16A key of the FMCE item number 16.
FMCE17A key of the FMCE item number 17.
FMCE18A key of the FMCE item number 18.
FMCE19A key of the FMCE item number 19.
FMCE20A key of the FMCE item number 20.
FMCE21A key of the FMCE item number 21.
FMCE22A key of the FMCE item number 22.
FMCE23A key of the FMCE item number 23.
FMCE24A key of the FMCE item number 24.
FMCE25A key of the FMCE item number 25.
FMCE26A key of the FMCE item number 26.
FMCE27A key of the FMCE item number 27.
FMCE28A key of the FMCE item number 28.
FMCE29A key of the FMCE item number 29.
FMCE30A key of the FMCE item number 30.
FMCE31A key of the FMCE item number 31.
FMCE32A key of the FMCE item number 32.
FMCE33A key of the FMCE item number 33.
FMCE34A key of the FMCE item number 34.
FMCE35A key of the FMCE item number 35.
FMCE36A key of the FMCE item number 36.
FMCE37A key of the FMCE item number 37.
FMCE38A key of the FMCE item number 38.
FMCE39A key of the FMCE item number 39.
FMCE40A key of the FMCE item number 40.
FMCE41A key of the FMCE item number 41.
FMCE42A key of the FMCE item number 42.
FMCE43A key of the FMCE item number 43.
FMCE44A key of the FMCE item number 44.
FMCE45A key of the FMCE item number 45.
FMCE46A key of the FMCE item number 46.
FMCE47A key of the FMCE item number 47.
Examples
library(spheredata)
# Call the data from spheredata package
get("FMCEkey")
# Open the data
FMCEkey
The Fluid Mechanics Concept Inventory (FMCI) dataset
Description
The Fluid Mechanics Concept Inventory (FMCI) is developed in 2003 as a conceptual inventory to explore students' ideas of fluid mechanics concepts [see Martin et al. (2003)]. The FMCI administers 30 multiple choice items.
Usage
data(FMCI)Format
A data frame of students' responses on the following 30 FMCI multiple choice items. The FMCI numbering system starts from the item 3.
FMCI3A student's response on the FMCI item number 3.
FMCI4A student's response on the FMCI item number 4.
FMCI5A student's response on the FMCI item number 5.
FMCI6A student's response on the FMCI item number 6.
FMCI7A student's response on the FMCI item number 7.
FMCI8A student's response on the FMCI item number 8.
FMCI9A student's response on the FMCI item number 9.
FMCI10A student's response on the FMCI item number 10.
FMCI11A student's response on the FMCI item number 11.
FMCI12A student's response on the FMCI item number 12.
FMCI13A student's response on the FMCI item number 13.
FMCI14A student's response on the FMCI item number 14.
FMCI15A student's response on the FMCI item number 15.
FMCI16A student's response on the FMCI item number 16.
FMCI17A student's response on the FMCI item number 17.
FMCI18A student's response on the FMCI item number 18.
FMCI19A student's response on the FMCI item number 19.
FMCI20A student's response on the FMCI item number 20.
FMCI21A student's response on the FMCI item number 21.
FMCI22A student's response on the FMCI item number 22.
FMCI23A student's response on the FMCI item number 23.
FMCI24A student's response on the FMCI item number 24.
FMCI25A student's response on the FMCI item number 25.
FMCI26A student's response on the FMCI item number 26.
FMCI27A student's response on the FMCI item number 27.
FMCI28A student's response on the FMCI item number 28.
FMCI29A student's response on the FMCI item number 29.
FMCI30A student's response on the FMCI item number 30.
FMCI31A student's response on the FMCI item number 31.
FMCI32A student's response on the FMCI item number 32.
Source
Santoso, P. H. et al. SPHERE: Students' performance dataset of conceptual understanding, scientific ability, and learning attitude in physics education research (PER). Mendeley Data, V1, (2024). doi: 10.17632/88d7m2fv7p.1.
References
Martin, J., Mitchell, J. & Newell, T. Development of a concept inventory for fluid mechanics. in Proceedings of the 33rd Annual Frontiers in Education 2003 vol. 1 T3D (IEEE, 2003).
Examples
library(spheredata)
# Call the data from spheredata package
get("FMCI")
# Open the data
FMCI
The Fluid Mechanics Concept Inventory (FMCI) content validity dataset
Description
In this data, five PER experts rated the content validity of the FMCI.
Usage
data(FMCIcontentvalidity)Format
A data frame of expert ratings on the content validity of 30 FMCI items.
IDAn anonymized expert identity.
FMCI3A numeric value of expert rating to the FMCI item number 3.
FMCI4A numeric value of expert rating to the FMCI item number 4.
FMCI5A numeric value of expert rating to the FMCI item number 5.
FMCI6A numeric value of expert rating to the FMCI item number 6.
FMCI7A numeric value of expert rating to the FMCI item number 7.
FMCI8A numeric value of expert rating to the FMCI item number 8.
FMCI9A numeric value of expert rating to the FMCI item number 9.
FMCI10A numeric value of expert rating to the FMCI item number 10.
FMCI11A numeric value of expert rating to the FMCI item number 11.
FMCI12A numeric value of expert rating to the FMCI item number 12.
FMCI13A numeric value of expert rating to the FMCI item number 13.
FMCI14A numeric value of expert rating to the FMCI item number 14.
FMCI15A numeric value of expert rating to the FMCI item number 15.
FMCI16A numeric value of expert rating to the FMCI item number 16.
FMCI17A numeric value of expert rating to the FMCI item number 17.
FMCI18A numeric value of expert rating to the FMCI item number 18.
FMCI19A numeric value of expert rating to the FMCI item number 19.
FMCI20A numeric value of expert rating to the FMCI item number 20.
FMCI21A numeric value of expert rating to the FMCI item number 21.
FMCI22A numeric value of expert rating to the FMCI item number 22.
FMCI23A numeric value of expert rating to the FMCI item number 23.
FMCI24A numeric value of expert rating to the FMCI item number 24.
FMCI25A numeric value of expert rating to the FMCI item number 25.
FMCI26A numeric value of expert rating to the FMCI item number 26.
FMCI27A numeric value of expert rating to the FMCI item number 27.
FMCI28A numeric value of expert rating to the FMCI item number 28.
FMCI29A numeric value of expert rating to the FMCI item number 29.
FMCI30A numeric value of expert rating to the FMCI item number 30.
FMCI31A numeric value of expert rating to the FMCI item number 31.
FMCI32A numeric value of expert rating to the FMCI item number 32.
Examples
library(spheredata)
# Call the data from spheredata package
get("FMCIcontentvalidity")
# Open the data
FMCIcontentvalidity
The Fluid Mechanics Concept Inventory (FMCI) key dataset
Description
The answers key to analyze the students' obtained score on the FMCI.
Usage
data(FMCIkey)Format
A data frame of a key record on the following 30 FMCI items. The FMCI numbering system starts from the item 3.
FMCI3A key of the FMCI item number 3.
FMCI4A key of the FMCI item number 4.
FMCI5A key of the FMCI item number 5.
FMCI6A key of the FMCI item number 6.
FMCI7A key of the FMCI item number 7.
FMCI8A key of the FMCI item number 8.
FMCI9A key of the FMCI item number 9.
FMCI10A key of the FMCI item number 10.
FMCI11A key of the FMCI item number 11.
FMCI12A key of the FMCI item number 12.
FMCI13A key of the FMCI item number 13.
FMCI14A key of the FMCI item number 14.
FMCI15A key of the FMCI item number 15.
FMCI16A key of the FMCI item number 16.
FMCI17A key of the FMCI item number 17.
FMCI18A key of the FMCI item number 18.
FMCI19A key of the FMCI item number 19.
FMCI20A key of the FMCI item number 20.
FMCI21A key of the FMCI item number 21.
FMCI22A key of the FMCI item number 22.
FMCI23A key of the FMCI item number 23.
FMCI24A key of the FMCI item number 24.
FMCI25A key of the FMCI item number 25.
FMCI26A key of the FMCI item number 26.
FMCI27A key of the FMCI item number 27.
FMCI28A key of the FMCI item number 28.
FMCI29A key of the FMCI item number 29.
FMCI30A key of the FMCI item number 30.
FMCI31A key of the FMCI item number 31.
FMCI32A key of the FMCI item number 32.
Examples
library(spheredata)
# Call the data from spheredata package
get("FMCIkey")
# Open the data
FMCIkey
The Mechanical Waves Conceptual Survey (MWCS) dataset
Description
The MWCS is the most important test to date that has been designed to evaluate students’ understanding of four main topics in mechanical waves. It encompasses some concepts surrounding propagation, superposition, reflection, and standing waves within 22 multiple choice items.
Usage
data(MWCS)Format
A data frame of students' responses on the following 22 MWCS multiple choice items.
MWCS1A student's response on the MWCS item number 1.
MWCS2A student's response on the MWCS item number 2.
MWCS3A student's response on the MWCS item number 3.
MWCS4A student's response on the MWCS item number 4.
MWCS5A student's response on the MWCS item number 5.
MWCS6A student's response on the MWCS item number 6.
MWCS7A student's response on the MWCS item number 7.
MWCS8A student's response on the MWCS item number 8.
MWCS9A student's response on the MWCS item number 9.
MWCS10A student's response on the MWCS item number 10.
MWCS11A student's response on the MWCS item number 11.
MWCS12A student's response on the MWCS item number 12.
MWCS13A student's response on the MWCS item number 13.
MWCS14A student's response on the MWCS item number 14.
MWCS15A student's response on the MWCS item number 15.
MWCS16A student's response on the MWCS item number 16.
MWCS17A student's response on the MWCS item number 17.
MWCS18A student's response on the MWCS item number 18.
MWCS19A student's response on the MWCS item number 19.
MWCS20A student's response on the MWCS item number 20.
MWCS21A student's response on the MWCS item number 21.
MWCS22A student's response on the MWCS item number 22.
Source
Santoso, P. H. et al. SPHERE: Students' performance dataset of conceptual understanding, scientific ability, and learning attitude in physics education research (PER). Mendeley Data, V1, (2024). doi: 10.17632/88d7m2fv7p.1.
References
Barniol, P. & Zavala, G. Mechanical waves conceptual survey: Its modification and conversion to a standard multiple-choice test. Phys Rev Phys Educ Res 12, 010107 (2016).
Examples
library(spheredata)
# Call the data from spheredata package
get("MWCS")
# Open the data
MWCS
The Mechanical Waves Conceptual Survey (MWCS) content validity dataset
Description
In this data, five PER experts rated the content validity of the MWCS.
Usage
data(MWCScontentvalidity)Format
A data frame of expert ratings on the content validity of 22 MWCS items.
IDAn anonymized expert identity.
MWCS1A numeric value of expert rating to the MWCS item number 1.
MWCS2A numeric value of expert rating to the MWCS item number 2.
MWCS3A numeric value of expert rating to the MWCS item number 3.
MWCS4A numeric value of expert rating to the MWCS item number 4.
MWCS5A numeric value of expert rating to the MWCS item number 5.
MWCS6A numeric value of expert rating to the MWCS item number 6.
MWCS7A numeric value of expert rating to the MWCS item number 7.
MWCS8A numeric value of expert rating to the MWCS item number 8.
MWCS9A numeric value of expert rating to the MWCS item number 9.
MWCS10A numeric value of expert rating to the MWCS item number 10.
MWCS11A numeric value of expert rating to the MWCS item number 11.
MWCS12A numeric value of expert rating to the MWCS item number 12.
MWCS13A numeric value of expert rating to the MWCS item number 13.
MWCS14A numeric value of expert rating to the MWCS item number 14.
MWCS15A numeric value of expert rating to the MWCS item number 15.
MWCS16A numeric value of expert rating to the MWCS item number 16.
MWCS17A numeric value of expert rating to the MWCS item number 17.
MWCS18A numeric value of expert rating to the MWCS item number 18.
MWCS19A numeric value of expert rating to the MWCS item number 19.
MWCS20A numeric value of expert rating to the MWCS item number 20.
MWCS21A numeric value of expert rating to the MWCS item number 21.
MWCS22A numeric value of expert rating to the MWCS item number 22.
Examples
library(spheredata)
# Call the data from spheredata package
get("MWCScontentvalidity")
# Open the data
MWCScontentvalidity
The Mechanical Waves Conceptual Survey (MWCS) key dataset
Description
The answers key to analyze the students' obtained score on the MWCS.
Usage
data(MWCSkey)Format
A data frame of a key record on the following 22 MWCS items.
MWCS1A key of the MWCS item number 1.
MWCS2A key of the MWCS item number 2.
MWCS3A key of the MWCS item number 3.
MWCS4A key of the MWCS item number 4.
MWCS5A key of the MWCS item number 5.
MWCS6A key of the MWCS item number 6.
MWCS7A key of the MWCS item number 7.
MWCS8A key of the MWCS item number 8.
MWCS9A key of the MWCS item number 9.
MWCS10A key of the MWCS item number 10.
MWCS11A key of the MWCS item number 11.
MWCS12A key of the MWCS item number 12.
MWCS13A key of the MWCS item number 13.
MWCS14A key of the MWCS item number 14.
MWCS15A key of the MWCS item number 15.
MWCS16A key of the MWCS item number 16.
MWCS17A key of the MWCS item number 17.
MWCS18A key of the MWCS item number 18.
MWCS19A key of the MWCS item number 19.
MWCS20A key of the MWCS item number 20.
MWCS21A key of the MWCS item number 21.
MWCS22A key of the MWCS item number 22.
Examples
library(spheredata)
# Call the data from spheredata package
get("MWCSkey")
# Open the data
MWCSkey
The Rotational and Rolling Motion Conceptual Survey (RRMCS) dataset
Description
The RRMCS could be given to explore students’ ideas in various education levels starting in high school to introductory college. It examines students' understanding of rotational motion and notions associated with it through 30 multiple choice items.
Usage
data(RRMCS)Format
A data frame of students' responses on the following 30 RRMCS multiple choice items.
RRMCS1A student's response on the RRMCS item number 1.
RRMCS2A student's response on the RRMCS item number 2.
RRMCS3A student's response on the RRMCS item number 3.
RRMCS4A student's response on the RRMCS item number 4.
RRMCS5A student's response on the RRMCS item number 5.
RRMCS6A student's response on the RRMCS item number 6.
RRMCS7A student's response on the RRMCS item number 7.
RRMCS8A student's response on the RRMCS item number 8.
RRMCS9A student's response on the RRMCS item number 9.
RRMCS10A student's response on the RRMCS item number 10.
RRMCS11A student's response on the RRMCS item number 11.
RRMCS12A student's response on the RRMCS item number 12.
RRMCS13A student's response on the RRMCS item number 13.
RRMCS14A student's response on the RRMCS item number 14.
RRMCS15A student's response on the RRMCS item number 15.
RRMCS16A student's response on the RRMCS item number 16.
RRMCS17A student's response on the RRMCS item number 17.
RRMCS18A student's response on the RRMCS item number 18.
RRMCS19A student's response on the RRMCS item number 19.
RRMCS20A student's response on the RRMCS item number 20.
RRMCS21A student's response on the RRMCS item number 21.
RRMCS22A student's response on the RRMCS item number 22.
RRMCS23A student's response on the RRMCS item number 23.
RRMCS24A student's response on the RRMCS item number 24.
RRMCS25A student's response on the RRMCS item number 25.
RRMCS26A student's response on the RRMCS item number 26.
RRMCS27A student's response on the RRMCS item number 27.
RRMCS28A student's response on the RRMCS item number 28.
RRMCS29A student's response on the RRMCS item number 29.
RRMCS30A student's response on the RRMCS item number 30.
Source
Santoso, P. H. et al. SPHERE: Students' performance dataset of conceptual understanding, scientific ability, and learning attitude in physics education research (PER). Mendeley Data, V1, (2024). doi: 10.17632/88d7m2fv7p.1.
References
Rimoldini, L. G. & Singh, C. Student understanding of rotational and rolling motion concepts. Physical Review Special Topics - Physics Education Research 1, 010102 (2005).
Examples
library(spheredata)
# Call the data from spheredata package
get("RRMCS")
# Open the data
RRMCS
The Rotational and Rolling Motion Conceptual Survey (RRMCS) content validity dataset
Description
In this data, five PER experts rated the content validity of the RRMCS.
Usage
data(RRMCScontentvalidity)Format
A data frame of expert ratings on the content validity of 30 RRMCS items.
IDAn anonymized expert identity.
RRMCS1A numeric value of expert rating to the RRMCS item number 1.
RRMCS2A numeric value of expert rating to the RRMCS item number 2.
RRMCS3A numeric value of expert rating to the RRMCS item number 3.
RRMCS4A numeric value of expert rating to the RRMCS item number 4.
RRMCS5A numeric value of expert rating to the RRMCS item number 5.
RRMCS6A numeric value of expert rating to the RRMCS item number 6.
RRMCS7A numeric value of expert rating to the RRMCS item number 7.
RRMCS8A numeric value of expert rating to the RRMCS item number 8.
RRMCS9A numeric value of expert rating to the RRMCS item number 9.
RRMCS10A numeric value of expert rating to the RRMCS item number 10.
RRMCS11A numeric value of expert rating to the RRMCS item number 11.
RRMCS12A numeric value of expert rating to the RRMCS item number 12.
RRMCS13A numeric value of expert rating to the RRMCS item number 13.
RRMCS14A numeric value of expert rating to the RRMCS item number 14.
RRMCS15A numeric value of expert rating to the RRMCS item number 15.
RRMCS16A numeric value of expert rating to the RRMCS item number 16.
RRMCS17A numeric value of expert rating to the RRMCS item number 17.
RRMCS18A numeric value of expert rating to the RRMCS item number 18.
RRMCS19A numeric value of expert rating to the RRMCS item number 19.
RRMCS20A numeric value of expert rating to the RRMCS item number 20.
RRMCS21A numeric value of expert rating to the RRMCS item number 21.
RRMCS22A numeric value of expert rating to the RRMCS item number 22.
RRMCS23A numeric value of expert rating to the RRMCS item number 23.
RRMCS24A numeric value of expert rating to the RRMCS item number 24.
RRMCS25A numeric value of expert rating to the RRMCS item number 25.
RRMCS26A numeric value of expert rating to the RRMCS item number 26.
RRMCS27A numeric value of expert rating to the RRMCS item number 27.
RRMCS28A numeric value of expert rating to the RRMCS item number 28.
RRMCS29A numeric value of expert rating to the RRMCS item number 29.
RRMCS30A numeric value of expert rating to the RRMCS item number 30.
Source
Santoso, P. H. et al. SPHERE: Students' performance dataset of conceptual understanding, scientific ability, and learning attitude in physics education research (PER). Mendeley Data, V1, (2024). doi: 10.17632/88d7m2fv7p.1.
Examples
library(spheredata)
# Call the data from spheredata package
get("RRMCScontentvalidity")
# Open the data
RRMCScontentvalidity
The Rotational and Rolling Motion Conceptual Survey (RRMCS) key dataset
Description
The answers key to analyze the students' obtained score on the RRMCS.
Usage
data(RRMCSkey)Format
A data frame of answer keys on the following 30 RRMCS items.
RRMCS1A key of the RRMCS item number 1.
RRMCS2A key of the RRMCS item number 2.
RRMCS3A key of the RRMCS item number 3.
RRMCS4A key of the RRMCS item number 4.
RRMCS5A key of the RRMCS item number 5.
RRMCS6A key of the RRMCS item number 6.
RRMCS7A key of the RRMCS item number 7.
RRMCS8A key of the RRMCS item number 8.
RRMCS9A key of the RRMCS item number 9.
RRMCS10A key of the RRMCS item number 10.
RRMCS11A key of the RRMCS item number 11.
RRMCS12A key of the RRMCS item number 12.
RRMCS13A key of the RRMCS item number 13.
RRMCS14A key of the RRMCS item number 14.
RRMCS15A key of the RRMCS item number 15.
RRMCS16A key of the RRMCS item number 16.
RRMCS17A key of the RRMCS item number 17.
RRMCS18A key of the RRMCS item number 18.
RRMCS19A key of the RRMCS item number 19.
RRMCS20A key of the RRMCS item number 20.
RRMCS21A key of the RRMCS item number 21.
RRMCS22A key of the RRMCS item number 22.
RRMCS23A key of the RRMCS item number 23.
RRMCS24A key of the RRMCS item number 24.
RRMCS25A key of the RRMCS item number 25.
RRMCS26A key of the RRMCS item number 26.
RRMCS27A key of the RRMCS item number 27.
RRMCS28A key of the RRMCS item number 28.
RRMCS29A key of the RRMCS item number 29.
RRMCS30A key of the RRMCS item number 30.
Examples
library(spheredata)
# Call the data from spheredata package
get("RRMCSkey")
# Open the data
RRMCSkey
The Scientific Abilities Assessment Rubrics (SAAR) dataset
Description
The SAAR is developed as a qualitative scoring rubric intended to measure students’ scientific abilities within the environment of physics laboratory. A rating scale with four categories (1–4) is used in this dataset to describe the students’ work in the laboratory (1, missing; 2, inadequate; 3, needs some improvement; and 4, adequate) and devised descriptions of student work that could merit a particular score. In this package, we merely measure some abilities from the SAAR since they could be more relevant and important for the high school physics laboratory. They are the ability to design & conduct an observational experiment (Rubric B),the ability to communicate scientific ideas (Rubric F), and the ability to collect and analyze experimental data (Rubric G).
Usage
data(SAAR)Format
A data frame of students' performance in the physics laboratory measured by the following 16 SAAR observation items.
SAARB1An observation using SAAR on the Rubric B item 1.
SAARB2An observation using SAAR on the Rubric B item 2.
SAARB3An observation using SAAR on the Rubric B item 3.
SAARB4An observation using SAAR on the Rubric B item 4.
SAARB5An observation using SAAR on the Rubric B item 5.
SAARB6An observation using SAAR on the Rubric B item 6.
SAARB7An observation using SAAR on the Rubric B item 7.
SAARB8An observation using SAAR on the Rubric B item 8.
SAARB9An observation using SAAR on the Rubric B item 9.
SAARF10An observation using SAAR on the Rubric F item 1 (SAAR item 10).
SAARF11An observation using SAAR on the Rubric F item 2 (SAAR item 11).
SAARG12An observation using SAAR on the Rubric G item 1 (SAAR item 12).
SAARG13An observation using SAAR on the Rubric G item 2 (SAAR item 13).
SAARG14An observation using SAAR on the Rubric G item 3 (SAAR item 14).
SAARG15An observation using SAAR on the Rubric G item 4 (SAAR item 15).
SAARG16An observation using SAAR on the Rubric G item 5 (SAAR item 16).
Source
Santoso, P. H. et al. SPHERE: Students' performance dataset of conceptual understanding, scientific ability, and learning attitude in physics education research (PER). Mendeley Data, V1, (2024). doi: 10.17632/88d7m2fv7p.1
References
Etkina, E. et al. Scientific abilities and their assessment. Physical Review Special Topics - Physics Education Research 2, 020103 (2006).
Examples
library(spheredata)
# Call the data from spheredata package
get("SAAR")
# Open the data
SAAR
The Scientific Abilities Assessment Rubrics (SAAR) content validity dataset
Description
In this data, five PER experts rated the content validity of the STPFASL.
Usage
data(SAARcontentvalidity)Format
A data frame of expert ratings on the content validity of 16 SAAR observation items.
IDAn anonymized expert identity.
SAARB1A numeric of expert rating on the SAAR Rubric B item 1.
SAARB2A numeric of expert rating on the SAAR Rubric B item 2.
SAARB3A numeric of expert rating on the SAAR Rubric B item 3.
SAARB4A numeric of expert rating on the SAAR Rubric B item 4.
SAARB5A numeric of expert rating on the SAAR Rubric B item 5.
SAARB6A numeric of expert rating on the SAAR Rubric B item 6.
SAARB7A numeric of expert rating on the SAAR Rubric B item 7.
SAARB8A numeric of expert rating on the SAAR Rubric B item 8.
SAARB9A numeric of expert rating on the SAAR Rubric B item 9.
SAARF10A numeric of expert rating on the SAAR Rubric F item 1.
SAARF11A numeric of expert rating on the SAAR Rubric F item 2.
SAARG12A numeric of expert rating on the SAAR Rubric G item 1.
SAARG13A numeric of expert rating on the SAAR Rubric G item 2.
SAARG14A numeric of expert rating on the SAAR Rubric G item 3.
SAARG15A numeric of expert rating on the SAAR Rubric G item 4.
SAARG16A numeric of expert rating on the SAAR Rubric G item 5.
Examples
library(spheredata)
# Call the data from spheredata package
get("SAARcontentvalidity")
# Open the data
SAARcontentvalidity
The Survey of Thermodynamic Processes and First and Second Laws (STPFASL) dataset
Description
The STPFASL instrument demonstrates 33 items in multiple-choice format that are written based on common student difficulties of thermodynamics as resources in that the incorrect answers to the multiple-choice questions were guided by them.
Usage
data(STPFASL)Format
A data frame of students' responses on the following 47 STPFASL multiple choice items.
STPFASL1A student's response on the STPFASL item number 1.
STPFASL2A student's response on the STPFASL item number 2.
STPFASL3A student's response on the STPFASL item number 3.
STPFASL4A student's response on the STPFASL item number 4.
STPFASL5A student's response on the STPFASL item number 5.
STPFASL6A student's response on the STPFASL item number 6.
STPFASL7A student's response on the STPFASL item number 7.
STPFASL8A student's response on the STPFASL item number 8.
STPFASL9A student's response on the STPFASL item number 9.
STPFASL10A student's response on the STPFASL item number 10.
STPFASL11A student's response on the STPFASL item number 11.
STPFASL12A student's response on the STPFASL item number 12.
STPFASL13A student's response on the STPFASL item number 13.
STPFASL14A student's response on the STPFASL item number 14.
STPFASL15A student's response on the STPFASL item number 15.
STPFASL16A student's response on the STPFASL item number 16.
STPFASL17A student's response on the STPFASL item number 17.
STPFASL18A student's response on the STPFASL item number 18.
STPFASL19A student's response on the STPFASL item number 19.
STPFASL20A student's response on the STPFASL item number 20.
STPFASL21A student's response on the STPFASL item number 21.
STPFASL22A student's response on the STPFASL item number 22.
STPFASL23A student's response on the STPFASL item number 23.
STPFASL24A student's response on the STPFASL item number 24.
STPFASL25A student's response on the STPFASL item number 25.
STPFASL26A student's response on the STPFASL item number 26.
STPFASL27A student's response on the STPFASL item number 27.
STPFASL28A student's response on the STPFASL item number 28.
STPFASL29A student's response on the STPFASL item number 29.
STPFASL30A student's response on the STPFASL item number 30.
STPFASL31A student's response on the STPFASL item number 31.
STPFASL32A student's response on the STPFASL item number 32.
STPFASL33A student's response on the STPFASL item number 33.
Source
Santoso, P. H. et al. SPHERE: Students' performance dataset of conceptual understanding, scientific ability, and learning attitude in physics education research (PER). Mendeley Data, V1, (2024). doi: 10.17632/88d7m2fv7p.1.
References
Brown, B. & Singh, C. Development and validation of a conceptual survey instrument to evaluate students’ understanding of thermodynamics. Phys Rev Phys Educ Res 17, 010104 (2021).
Examples
library(spheredata)
# Call the data from spheredata package
get("STPFASL")
# Open the data
STPFASL
The Survey of Thermodynamic Processes and First and Second Laws (STPFASL) content validity dataset
Description
In this data, five PER experts rated the content validity of the STPFASL.
Usage
data(STPFASLcontentvalidity)Format
A data frame of expert ratings on the content validity of 33 STPFASL items.
IDAn anonymized expert identity.
STPFASL1A numeric value of expert rating to the STPFASL item number 1.
STPFASL2A numeric value of expert rating to the STPFASL item number 2.
STPFASL3A numeric value of expert rating to the STPFASL item number 3.
STPFASL4A numeric value of expert rating to the STPFASL item number 4.
STPFASL5A numeric value of expert rating to the STPFASL item number 5.
STPFASL6A numeric value of expert rating to the STPFASL item number 6.
STPFASL7A numeric value of expert rating to the STPFASL item number 7.
STPFASL8A numeric value of expert rating to the STPFASL item number 8.
STPFASL9A numeric value of expert rating to the STPFASL item number 9.
STPFASL10A numeric value of expert rating to the STPFASL item number 10.
STPFASL11A numeric value of expert rating to the STPFASL item number 11.
STPFASL12A numeric value of expert rating to the STPFASL item number 12.
STPFASL13A numeric value of expert rating to the STPFASL item number 13.
STPFASL14A numeric value of expert rating to the STPFASL item number 14.
STPFASL15A numeric value of expert rating to the STPFASL item number 15.
STPFASL16A numeric value of expert rating to the STPFASL item number 16.
STPFASL17A numeric value of expert rating to the STPFASL item number 17.
STPFASL18A numeric value of expert rating to the STPFASL item number 18.
STPFASL19A numeric value of expert rating to the STPFASL item number 19.
STPFASL20A numeric value of expert rating to the STPFASL item number 20.
STPFASL21A numeric value of expert rating to the STPFASL item number 21.
STPFASL22A numeric value of expert rating to the STPFASL item number 22.
STPFASL23A numeric value of expert rating to the STPFASL item number 23.
STPFASL24A numeric value of expert rating to the STPFASL item number 24.
STPFASL25A numeric value of expert rating to the STPFASL item number 25.
STPFASL26A numeric value of expert rating to the STPFASL item number 26.
STPFASL27A numeric value of expert rating to the STPFASL item number 27.
STPFASL28A numeric value of expert rating to the STPFASL item number 28.
STPFASL29A numeric value of expert rating to the STPFASL item number 29.
STPFASL30A numeric value of expert rating to the STPFASL item number 30.
STPFASL31A numeric value of expert rating to the STPFASL item number 31.
STPFASL32A numeric value of expert rating to the STPFASL item number 32.
STPFASL33A numeric value of expert rating to the STPFASL item number 33.
Examples
library(spheredata)
# Call the data from spheredata package
get("STPFASLcontentvalidity")
# Open the data
STPFASLcontentvalidity
The Survey of Thermodynamic Processes and First and Second Laws (STPFASL) key dataset
Description
The answers key to analyze the students' obtained score on the STPFASL.
Usage
data(STPFASLkey)Format
A data frame of answer keys on the following 33 STPFASL items.
STPFASL1A key of the STPFASL item number 1.
STPFASL2A key of the STPFASL item number 2.
STPFASL3A key of the STPFASL item number 3.
STPFASL4A key of the STPFASL item number 4.
STPFASL5A key of the STPFASL item number 5.
STPFASL6A key of the STPFASL item number 6.
STPFASL7A key of the STPFASL item number 7.
STPFASL8A key of the STPFASL item number 8.
STPFASL9A key of the STPFASL item number 9.
STPFASL10A key of the STPFASL item number 10.
STPFASL11A key of the STPFASL item number 11.
STPFASL12A key of the STPFASL item number 12.
STPFASL13A key of the STPFASL item number 13.
STPFASL14A key of the STPFASL item number 14.
STPFASL15A key of the STPFASL item number 15.
STPFASL16A key of the STPFASL item number 16.
STPFASL17A key of the STPFASL item number 17.
STPFASL18A key of the STPFASL item number 18.
STPFASL19A key of the STPFASL item number 19.
STPFASL20A key of the STPFASL item number 20.
STPFASL21A key of the STPFASL item number 21.
STPFASL22A key of the STPFASL item number 22.
STPFASL23A key of the STPFASL item number 23.
STPFASL24A key of the STPFASL item number 24.
STPFASL25A key of the STPFASL item number 25.
STPFASL26A key of the STPFASL item number 26.
STPFASL27A key of the STPFASL item number 27.
STPFASL28A key of the STPFASL item number 28.
STPFASL29A key of the STPFASL item number 29.
STPFASL30A key of the STPFASL item number 30.
STPFASL31A key of the STPFASL item number 31.
STPFASL32A key of the STPFASL item number 32.
STPFASL33A key of the STPFASL item number 33.
Examples
library(spheredata)
# Call the data from spheredata package
get("STPFASLkey")
# Open the data
STPFASLkey
The Thermal Concept Evaluation (TCE) dataset
Description
There are 26 multiple-choice items in the TCE examining students’ alternative concepts on heat, temperature, heat transfer and temperature change, and thermal properties. The alternative concepts are discovered based on former studies, and they are used as a researcher basis to construct the TCE distractors.
Usage
data(TCE)Format
A data frame of students' responses on the following 26 TCE multiple choice items.
TCE1A student's response on the TCE item number 1.
TCE2A student's response on the TCE item number 2.
TCE3A student's response on the TCE item number 3.
TCE4A student's response on the TCE item number 4.
TCE5A student's response on the TCE item number 5.
TCE6A student's response on the TCE item number 6.
TCE7A student's response on the TCE item number 7.
TCE8A student's response on the TCE item number 8.
TCE9A student's response on the TCE item number 9.
TCE10A student's response on the TCE item number 10.
TCE11A student's response on the TCE item number 11.
TCE12A student's response on the TCE item number 12.
TCE13A student's response on the TCE item number 13.
TCE14A student's response on the TCE item number 14.
TCE15A student's response on the TCE item number 15.
TCE16A student's response on the TCE item number 16.
TCE17A student's response on the TCE item number 17.
TCE18A student's response on the TCE item number 18.
TCE19A student's response on the TCE item number 19.
TCE20A student's response on the TCE item number 20.
TCE21A student's response on the TCE item number 21.
TCE22A student's response on the TCE item number 22.
TCE23A student's response on the TCE item number 23.
TCE24A student's response on the TCE item number 24.
TCE25A student's response on the TCE item number 25.
TCE26A student's response on the TCE item number 26.
Examples
library(spheredata)
# Call the data from spheredata package
get("TCE")
# Open the data
TCE
The Thermal Concept Evaluation (TCE) content validity dataset
Description
In this data, five PER experts rated the content validity of the TCE.
Usage
data(TCEcontentvalidity)Format
A data frame of expert ratings on the content validity of 26 TCE items.
IDAn anonymized expert identity.
TCE1A numeric value of expert rating to the TCE item number 1.
TCE2A numeric value of expert rating to the TCE item number 2.
TCE3A numeric value of expert rating to the TCE item number 3.
TCE4A numeric value of expert rating to the TCE item number 4.
TCE5A numeric value of expert rating to the TCE item number 5.
TCE6A numeric value of expert rating to the TCE item number 6.
TCE7A numeric value of expert rating to the TCE item number 7.
TCE8A numeric value of expert rating to the TCE item number 8.
TCE9A numeric value of expert rating to the TCE item number 9.
TCE10A numeric value of expert rating to the TCE item number 10.
TCE11A numeric value of expert rating to the TCE item number 11.
TCE12A numeric value of expert rating to the TCE item number 12.
TCE13A numeric value of expert rating to the TCE item number 13.
TCE14A numeric value of expert rating to the TCE item number 14.
TCE15A numeric value of expert rating to the TCE item number 15.
TCE16A numeric value of expert rating to the TCE item number 16.
TCE17A numeric value of expert rating to the TCE item number 17.
TCE18A numeric value of expert rating to the TCE item number 18.
TCE19A numeric value of expert rating to the TCE item number 19.
TCE20A numeric value of expert rating to the TCE item number 20.
TCE21A numeric value of expert rating to the TCE item number 21.
TCE22A numeric value of expert rating to the TCE item number 22.
TCE23A numeric value of expert rating to the TCE item number 23.
TCE24A numeric value of expert rating to the TCE item number 24.
TCE25A numeric value of expert rating to the TCE item number 25.
TCE26A numeric value of expert rating to the TCE item number 26.
Examples
library(spheredata)
# Call the data from spheredata package
get("TCEcontentvalidity")
# Open the data
TCEcontentvalidity
The Thermal Concept Evaluation (TCE) key dataset
Description
The answers key to analyze the students' obtained score on the TCE.
Usage
data(TCEkey)Format
A data frame of answer keys on the following 26 TCE items.
TCE1A key of the TCE item number 1.
TCE2A key of the TCE item number 2.
TCE3A key of the TCE item number 3.
TCE4A key of the TCE item number 4.
TCE5A key of the TCE item number 5.
TCE6A key of the TCE item number 6.
TCE7A key of the TCE item number 7.
TCE8A key of the TCE item number 8.
TCE9A key of the TCE item number 9.
TCE10A key of the TCE item number 10.
TCE11A key of the TCE item number 11.
TCE12A key of the TCE item number 12.
TCE13A key of the TCE item number 13.
TCE14A key of the TCE item number 14.
TCE15A key of the TCE item number 15.
TCE16A key of the TCE item number 16.
TCE17A key of the TCE item number 17.
TCE18A key of the TCE item number 18.
TCE19A key of the TCE item number 19.
TCE20A key of the TCE item number 20.
TCE21A key of the TCE item number 21.
TCE22A key of the TCE item number 22.
TCE23A key of the TCE item number 23.
TCE24A key of the TCE item number 24.
TCE25A key of the TCE item number 25.
TCE26A key of the TCE item number 26.
Examples
library(spheredata)
# Call the data from spheredata package
get("TCEkey")
# Open the data
TCEkey
Compute the Aiken's V index of content validity
Description
Aiken's V is a statistical measure of content validity index on a single
item (Aiken, 1980). This measure could be defined as follow.
\displaystyle V=\frac{\bar{X}-l}{k}
where \bar{X} represents the sample mean of the judges’ ratings,
l represents the lowest possible rating, and k represents the
range of possible values of the rating scale used (e.g., a scale having
possible values extending from 1 to 5 has l=1 and k = 5-1 = 4).
Then, Penfield and Giacobbi (2004) suggest a method to compute the confidence
interval of Aiken's V index using the formula below.
\displaystyle L=\frac{2nkV+z^2-z\sqrt{4nkV(1-V)+z^2}}{2(nk+z^2)}
\displaystyle U=\frac{2nkV+z^2+z\sqrt{4nkV(1-V)+z^2}}{2(nk+z^2)}
where L and U are the lower and upper limit of Aiken's V
index within a C\% confidence interval, and the z is a critical
value of a standard normal distribution such that C\% of the area of
the distribution lies between -z and z (e.g., for a 95%
confidence interval z = 1.96).
Usage
aikenV(data, max_cat = 4, min_cat = 1, CI = 0.95)
Arguments
data |
a dataframe of categorical value from expert judgment to the item content validity. |
max_cat |
a maximum category point of used rating scale (the default value is 4). |
min_cat |
a minimum category point of used rating scale (the default value is 1). |
CI |
the default value of confidence interval is 0.95. It can be set to preferred confidence interval. |
Value
a dataframe of content validity index of each item as calculated using the Aiken's formula
References
Aiken, L.R. Content Validity and Reliability of Single Items or Questionnaires. Educational and Psychological Measurement 40, 955-959 (1980).
Penfield, R.D. & Giacobbi, P.R. Applying a Score Confidence Interval to Aiken’s Item Content-Relevance Index. Measurement in Physical Education and Exercise Science 8, 4, 213-225 (2004).
Examples
# In this example, we define a dataframe describing the rating of ten
# imaginary items as assessed by seven artificial experts. The minimum point
# of the rating scale is 1, and the maximum point that could be given by
# those experts is 4.
df <- data.frame(item1 = c(3,3,3,4,4,4,3),
item2 = c(2,4,3,2,4,4,4),
item3 = c(4,3,3,2,4,4,3),
item4 = c(3,2,3,3,4,3,3),
item5 = c(4,4,4,3,3,3,3),
item6 = c(3,3,3,4,3,3,4),
item7 = c(4,4,4,3,4,4,4),
item8 = c(3,3,4,4,4,4,4),
item9 = c(4,4,4,3,4,4,4),
item10 = c(4,3,4,4,3,3,4))
# Compute the Aiken's V
aikenV(df)
Compute the students' score of spheredata package
Description
Compute the students' score as binary/ dichotomous value. The calculation method is based on a classical test theory prespective.
Usage
binary(raw, key)
Arguments
raw |
a dataframe of raw response data |
key |
a dataframe of answer key |
Value
a dataframe of dichotomous format of students' response data
Examples
# Import the FCI score and key data
library(spheredata)
data("FCI")
data("FCIkey")
# Processing the Force Concept Inventory (FCI) data as dichotomous
binary(FCI, FCIkey)
Students' demographic of the SPHERE dataset
Description
This dataset is used to describe the students' contexts of this study.
Usage
data(demographic)Format
A data frame with 497 observations on the following 8 demographic variables.
STUDIDStudents' identity. The first letter denotes the school code. The second one coins the students' cohort within schools. Three last numbers for their alphabetical orders.
SCHSchool sample participated in the study.
COHStudents' class within schools. 1 = Group A, 2 = Group B, 3 = Group C, 4 = Group D
GDRStudents' gender. 1 = Male, 2 = Female
AGEStudents' age. 1 = 13-14 years, 2 = 15-16 years, 3 = 17-18 years, 4 = 19-20 years
FATHOCCFather's occupation. 1 = Entrepreneur, 2 = Farmer, 3 = Armed force, 4 = Private employee, 5 = Educator, 6 = Medicine, 7 = Civil servant, 8 = Unemployed, 9 = Others
MOTHOCCMother’s occupation. 1 = Entrepreneur, 2 = Farmer, 3 = Armed force, 4 = Private employee, 5 = Educator, 6 = Medicine, 7 = Civil servant, 8 = Unemployed, 9 = Others
FATHEDUFather's education. 1 = Graduate, 2 = Undergraduate, 3 = Vocational, 4 = High school, 5 = Junior high school, 6 = Elementary, 7 = Unfinished education, 8 = Out of formal education
MOTHEDUMother's education. 1 = Graduate, 2 = Undergraduate, 3 = Vocational, 4 = High school, 5 = Junior high school, 6 = Elementary, 7 = Unfinished education, 8 = Out of formal education
FATHINCFather's monthly income. 1 = More than IDR10.000.000, 2 = IDR9.000.000-IDR10.000.000, 3 = IDR8.000.000-IDR9.000.000, 4 = IDR7.000.000-IDR8.000.000, 5 = IDR6.000.000-IDR7.000.000, 6 = IDR5.000.000-IDR6.000.000, 7 = IDR4.000.000-IDR5.000.000, 8 = IDR3.000.000-IDR4.000.000, 9 = IDR2.000.000-IDR3.000.000, 10 = IDR1.000.000-IDR2.000.000, 11= Less than IDR1.000.000, 12 = No income
MOTHINCMother's monthly income. 1 = More than IDR10.000.000, 2 = IDR9.000.000-IDR10.000.000, 3 = IDR8.000.000-IDR9.000.000, 4 = IDR7.000.000-IDR8.000.000, 5 = IDR6.000.000-IDR7.000.000, 6 = IDR5.000.000-IDR6.000.000, 7 = IDR4.000.000-IDR5.000.000, 8 = IDR3.000.000-IDR4.000.000, 9 = IDR2.000.000-IDR3.000.000, 10 = IDR1.000.000-IDR2.000.000, 11= Less than IDR1.000.000, 12 = No income
SIBLNumber of siblings belonged to the student. Zero means student as an only child.
DOMStudent's domicile from the school location. 1 = Inside the zoning area of the school. 2 = Outside the zoning area of the school.
Source
Santoso, P. H. et al. SPHERE: Students' performance dataset of conceptual understanding, scientific ability, and learning attitude in physics education research (PER). Mendeley Data, V1, (2024). doi: 10.17632/88d7m2fv7p.1
Examples
library(spheredata)
# Call the data from spheredata package
get("demographic")
# Open the data
demographic
Compute the Lawshe's content validity ratio (CVR)
Description
Lawshe (1975) proposed an index to quantify content validity of items as
assessed by experts. He coined the index as content validity ratio
(CVR) that can be calculated using the following formula.
\displaystyle CVR=\frac{n_e - \frac{N}{2}}{\frac{N}{2}}
where n_e is the number of experts identifying an item as essential.
In this function, we define a cutoff value using two methods. The first is
"max" calculated by searching the maximum value of the used rating scale
("max_cat") and then divide it by two. The second method is "min" by using
the minimum value of the used rating scale ("min_cat") as the cutoff
criteria.
Usage
lawsheCVR(data, max_cat = 4, min_cat = 1, method = "max")
Arguments
data |
a dataframe of categorical value from expert judgment to the item content validity. |
max_cat |
a maximum category point of used rating scale (the default value is 4). |
min_cat |
a minimum category point of used rating scale (the default value is 1). |
method |
a method to determine cutoff value between essential and non-essential items |
Value
a dataframe of CVR of each item as calculated using the Lawshe's formula
References
Gilbert, G.E. & Prion, S. Making Sense of Methods and Measurement: Lawshe's Content Validity Index. Clinical Simulation in Nursing 12, 530-531 (2016).
Lawshe, C.H. A Quantitative Approach of Content Validity. Personnel Psychology 28, 563-575 (1975).
Examples
# In this example, we define a dataframe describing the rating of ten
# imaginary items as assessed by seven artificial experts. The minimum point
# of the rating scale is 1, and the maximum point that could be given by
# those experts is 4.
df <- data.frame(item1 = c(3,3,3,4,4,4,3),
item2 = c(2,4,3,2,4,4,4),
item3 = c(4,3,3,2,4,4,3),
item4 = c(3,2,3,3,4,3,3),
item5 = c(4,4,4,3,3,3,3),
item6 = c(3,3,3,4,3,3,4),
item7 = c(4,4,4,3,4,4,4),
item8 = c(3,3,4,4,4,4,4),
item9 = c(4,4,4,3,4,4,4),
item10 = c(4,3,4,4,3,3,4))
# Compute the Lawshe's CVR
lawsheCVR(df)
Students' literacy dataset
Description
In this package, students' literacy was defined based on two close-ended items asking the accessibility to available books in their home and digital facilities belong to the students.
Usage
data(literacy)Format
A data frame with 497 observations on the following 2 literacy items.
LIT1Do you read books in your home? 1 = Yes, 2 = No
LIT2Do you access gadgets and the internet in your home? 1 = Yes, 2 = No
Source
Santoso, P. H. et al. SPHERE: Students' performance dataset of conceptual understanding, scientific ability, and learning attitude in physics education research (PER). Mendeley Data, V1, (2024). doi: 10.17632/88d7m2fv7p.1.
Examples
library(spheredata)
# Call the data from spheredata package
get("literacy")
# Open the data
literacy
Students' physics identity dataset
Description
In this study, students' physics identity was defined based on two close-ended items asking the students' study time for physics and the experienced family recognition when they are studying physics.
Usage
data(physicsidentity)Format
A data frame with 497 observations on the following 2 physics identity items.
PHYIDE1When did you study physics outside schools? 1 = Most of the time, 2 = Night before the physics schedule, 3 = Night before exam, 4 = Never
PHYIDE2Did your parents support you while studying physics? 1 = Yes, 2 = Lack of parental support, 3 = Extremely no
Source
Santoso, P. H. et al. SPHERE: Students' performance dataset of conceptual understanding, scientific ability, and learning attitude in physics education research (PER). Mendeley Data, V1, (2024). doi: 10.17632/88d7m2fv7p.1.
References
Hazari, Z., Sonnert, G., Sadler, P. M. & Shanahan, M. C. Connecting high school physics experiences, outcome expectations, physics identity, and physics career choice: A gender study. J Res Sci Teach 47, 978–1003 (2010).
Examples
library(spheredata)
# Call the data from spheredata package
get("physicsidentity")
# Open the data
physicsidentity
Teachers' judgment dataset
Description
In this study, physics teachers are studied to predict the binary state of their students' performance at the final second semester.
Usage
data(teachersjudgment)Format
A data frame with 497 rows of final test assessments and prediction reported by physics teachers.
FINTEST1Students' score on the final test at the first semester using teachers developed items.
FINTEST2Students' score on the final test at the second semester using teachers developed items.
TEACHPREDStudents' performance state as predicted by physics teachers intuitively. 1 = higher ability, 0 = lower ability.
Source
Santoso, P. H. et al. SPHERE: Students' performance dataset of conceptual understanding, scientific ability, and learning attitude in physics education research (PER). Mendeley Data, V1, (2024). doi: 10.17632/88d7m2fv7p.1.
References
Zhu, C. & Urhahne, D. Temporal stability of teachers’ judgment accuracy of students’ motivation, emotion, and achievement. European Journal of Psychology of Education 36, 319–337 (2021).
Examples
library(spheredata)
# Call the data from spheredata package
get("teachersjudgment")
# Open the data
teachersjudgment