learning_motivation: Learning Motivation Data
In SDT: Self-Determination Theory Measures
Description
Usage
Format
Details
Source
See Also
Description
A dataset containing the aggregate learning motivation scores for the
subscales of intrinsic regulation, identified regulation, introjected
regulation, and external regulation of a total number of 1,150 students.
Usage
1
Format
A data frame with 1,150 rows and 6 variables:
sexinteger vector, female (= 1) and male (= 2)
ageinteger vector, years
intrinsicnumeric vector, aggregate intrinsic regulation subscale
motivation scores
identifiednumeric vector, aggregate identified regulation subscale
motivation scores
introjectednumeric vector, aggregate introjected regulation
subscale motivation scores
externalnumeric vector, aggregate external regulation subscale
motivation scores
Details
The variables intrinsic, identified, introjected, and
external of the data frame learning_motivation contain
aggregate subscale scores in the sense that the scores are the means taken
over all raw-data test items that make up a respective subscale.
Source
Mueller, F. H. and Hanfstingl, B. and Andreitz, I. (2007) Skalen zur
motivationalen Regulation beim Lernen von Schuelerinnen und Schuelern:
adaptierte und ergaenzte Version des Academic Self-Regulation Questionnaire
(SRQ-A) nach Ryan & Connell [Scales of motivational regulation for student
learning: adapted and supplemented version of the Academic Self-Regulation
Questionnaire (SRQ-A) by Ryan & Connell] (Transl. A. Uenlue). In Institut
fuer Unterrichts- und Schulentwicklung (Ed.), Wissenschaftliche
Beitraege [Scientific Contributions] (Transl. A. Uenlue) (pp. 1–17).
Klagenfurt, Austria: Alpen-Adria-Universitaet.
See Also
The three main functions of the package:
internalization for motivation internalization analysis of the
data; sdi for the orginal and adjusted SDI or RAI index of the
data; and simplex for motivation simplex structure analysis of
the data. See also SDT-package for general information about
this package.
SDT documentation built on May 2, 2019, 6:08 a.m.
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Description Usage Format Details Source See Also
Description
A dataset containing the aggregate learning motivation scores for the subscales of intrinsic regulation, identified regulation, introjected regulation, and external regulation of a total number of 1,150 students.
Usage
1 |
Format
A data frame with 1,150 rows and 6 variables:
sexinteger vector, female (= 1) and male (= 2)
ageinteger vector, years
intrinsicnumeric vector, aggregate intrinsic regulation subscale motivation scores
identifiednumeric vector, aggregate identified regulation subscale motivation scores
introjectednumeric vector, aggregate introjected regulation subscale motivation scores
externalnumeric vector, aggregate external regulation subscale motivation scores
Details
The variables intrinsic, identified, introjected, and
external of the data frame learning_motivation contain
aggregate subscale scores in the sense that the scores are the means taken
over all raw-data test items that make up a respective subscale.
Source
Mueller, F. H. and Hanfstingl, B. and Andreitz, I. (2007) Skalen zur motivationalen Regulation beim Lernen von Schuelerinnen und Schuelern: adaptierte und ergaenzte Version des Academic Self-Regulation Questionnaire (SRQ-A) nach Ryan & Connell [Scales of motivational regulation for student learning: adapted and supplemented version of the Academic Self-Regulation Questionnaire (SRQ-A) by Ryan & Connell] (Transl. A. Uenlue). In Institut fuer Unterrichts- und Schulentwicklung (Ed.), Wissenschaftliche Beitraege [Scientific Contributions] (Transl. A. Uenlue) (pp. 1–17). Klagenfurt, Austria: Alpen-Adria-Universitaet.
See Also
The three main functions of the package:
internalization for motivation internalization analysis of the
data; sdi for the orginal and adjusted SDI or RAI index of the
data; and simplex for motivation simplex structure analysis of
the data. See also SDT-package for general information about
this package.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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