| Title: | Course-Dependent Skill Structures |
|---|---|
| Description: | Deriving skill structures from skill assignment data for courses (sets of learning objects). |
| Authors: | Cord Hockemeyer [aut, cre] |
| Maintainer: | Cord Hockemeyer <cord.hockemeyer@uni-graz.at> |
| License: | GPL-3 |
| Version: | 1.0-0 |
| Built: | 2026-10-07 13:06:56 UTC |
| Source: | https://github.com/cran/CDSS |
The CDSS package provides functions for a complete workflow from
skill assignment tables to surmise mappings on the sets of skills and
learning objects, respectively.
Read the skill assignment using one of the read_skill_assignments_xxx() functions.
Check the compliance to the definition for skill assignments using cdss_sa_compliance().
Determine the attribution function on skills and on learning objects
applying the cdss_skill_sa2af() and cdss_lo_sa2af() functions, respectievely.
Close the attribution functions to surmise functions using kstMatrix::kmclosure().
Check if the skill assignment leads to a quasi-ordinal space using cdss_sa_describes_sr().
If TRUE, determine attribution relations on skills and learning objects using
cdss_skill_sa2ar() and cdss_lo_sa2ar(), respectively.
Close the attribution relations to surmise relations applying kstMatrix::kmclosure().
Continue with functions from the kstMatrix package, e.g., to obtain a basis and further on a skill space.
Read the skill assignment using one of the read_skill_assignments_xxx() functions.
Check whether the skill assignment allows for the derivation of a surmise relation using cdss_sa_describes_sr().
If yes, derive an attribution relation from the skill assignment using cdss_skill_sa2ar().
Close the attribution relation to a surmise relation using kstMatrix::kmclosure().
Continue with functions from the kstMatrix package, e.g., to obtain a basis and further on a skill space.
The installation of this package includes several data files as examples in the
extdata sub directory (see the Examples below for how to access the files there).
There are four data sets, KST, KST-Intro, SkillAssignment, and
ErroneousSkillAssignment. The SkillAssignment data set is available in
three formats, ODS, XLSX, and CSV (in CSV format, there are two files each,
SkillAssignment-R.csv and SkillAssignment-T.csv, for required and taught skills, respectively).
The other three data sets are available in ODS format only.
SkillAssignment and ErroneousSkillAssignment are small example data sets
where the latter fails for cdss_sa_compliance(). KST contains a skill
assignment for the course on knowledge space theory under https://moodle.qhelp.eu/.
KST-Intro contains the reduction of KST to the first chapter of
that course.
Hockemeyer, C. (2022). Building Course-Dependent Skill Structures - Applying Competence based Knowledge Space Theory to Itself. Manuscript in preparation.
The creation of this R package was financially supported by the Erasmus+ Programme of the European Commission through the QHELP project (https://qhelp.eu/).
library(readODS) fpath <- system.file("extdata", "SkillAssignment.ods", package="CDSS") sa <- cdss_read_skill_assignment_ods(fpath) sa ssf <- kstMatrix::kmclosure(cdss_skill_sa2af(sa)) ssf lsf <- kstMatrix::kmclosure(cdss_lo_sa2af(sa)) lsflibrary(readODS) fpath <- system.file("extdata", "SkillAssignment.ods", package="CDSS") sa <- cdss_read_skill_assignment_ods(fpath) sa ssf <- kstMatrix::kmclosure(cdss_skill_sa2af(sa)) ssf lsf <- kstMatrix::kmclosure(cdss_lo_sa2af(sa)) lsf
cdss_circular_requirements expects skill assignment and returns
a vector of learning objects which require a skill that they teach.
cdss_circular_requirements(sa)cdss_circular_requirements(sa)
sa |
Skill assignment |
Vector of learning objects
Other Functions testing validity of skill assignments:
cdss_missing_los(),
cdss_nonteaching_los(),
cdss_sa_compliance()
cdss_lo_sa2af expects a skill assignment and derives an attribution
function on the set of learning objects.
cdss_lo_sa2af(sa)cdss_lo_sa2af(sa)
sa |
Skill assignment object |
Object of class cdss_af (attribution function).
Other functions building skill (multi) assignment matrices:
cdss_skill_sa2af(),
cdss_tables2sa()
cdss_lo_sa2ar expects a skill assignment and derives an attribution relation
on learning objects if the skill assignment fulfills the necessary conditions, i.e. if
there is only one teaching LO per skill.
cdss_lo_sa2ar(sa)cdss_lo_sa2ar(sa)
sa |
Skill assignment object |
attribution relation or NULL
Other functions deriving skill structures from skill assignments:
cdss_sa_describes_sr(),
cdss_skill_sa2ar()
cdss_missing_los expects a skill assignment and returns a vector
of skills which are not taught by any learning object.
cdss_missing_los(sa)cdss_missing_los(sa)
sa |
SKill assignment |
Vector of skills
Other Functions testing validity of skill assignments:
cdss_circular_requirements(),
cdss_nonteaching_los(),
cdss_sa_compliance()
cdss_nonteaching_los expects a skill assignment and returns a vector
of learning objects which do not teach any skill.
cdss_nonteaching_los(sa)cdss_nonteaching_los(sa)
sa |
SKill assignment |
Vector of learning objects
Other Functions testing validity of skill assignments:
cdss_circular_requirements(),
cdss_missing_los(),
cdss_sa_compliance()
Read a skill assignment from file
cdss_read_skill_assignment( filename = NULL, taught = "Taught", required = "Required", sep = ",", warnonly = FALSE, verbose = FALSE )cdss_read_skill_assignment( filename = NULL, taught = "Taught", required = "Required", sep = ",", warnonly = FALSE, verbose = FALSE )
filename |
Name of the file for ODS or XLSX files |
taught |
Name of the sheet/file for taught skill assignments |
required |
Name of the sheet/file for required skil assignments |
sep |
Cell-separating character for CSV files |
warnonly |
Are non-compliant SAs allowed? (default FALSE) |
verbose |
Verbosity (default TRUE) |
Skill assignment ('cdss_sa' object)
Skill assignments are stored in a pair of tables, 'taught' and 'required'. For ODS and XLSX files, these must be sheets of **one** file; CSV does not support multi-sheet file and, therefore, two files must be specified there.
For CSV files, the 'filename' parameter must be 'NULL', and the two filenames are specified in the 'taught' and 'required' parameters. For ODS and XLSX, the 'filename' must be specified, and teh 'taught' and 'required' parameters specify the names of the respective sheets within that file.
cdss_read_skill_assignment expects two CSV-files with two columns each. The first
column contains the IDs of learning objects and the second row the IDs of single skills
required or taught, respectively, by this learning object.
It returns a list of two binary matrices, "taught" and "required". Each matrix has one
row per learning object and one column per skill. The cells contain a "1" if the skill
is taught or required, respectively, by the learning object and a "0" otherwise,
cdss_read_skill_assignment_csv( taught, required, header = TRUE, sep = ",", dec = ".", warnonly = FALSE, verbose = TRUE )cdss_read_skill_assignment_csv( taught, required, header = TRUE, sep = ",", dec = ".", warnonly = FALSE, verbose = TRUE )
taught |
CSV-file with assignments of taught competencies to learning objects |
required |
CSV-file with assignments of required competencies to learning objects |
header |
Boolean specifying whether the CSV-files contain a header line (default = TRUE) |
sep |
Column separator (default ",") |
dec |
Decimal point character (default ".") |
warnonly |
Are non-compliant SAs allowed? (default = FALSE) |
verbose |
Verbosity of compliance test (default = TRUE) |
List of two binary matrices, "taught" and "required".
Other functions reading skill assignments:
cdss_read_skill_assignment_ods(),
cdss_read_skill_assignment_xlsx()
cdss_read_skill_assignment_ods expects an ODS-file with two sheets assigning taught and
required, respectively, skills to learning objects with two columns each. The first
column contains the IDs of learning objects and the second row the IDs of single skills
required or taught, respectively, by this learning object.
It returns a list of two binary matrices, "taught" and "required". Each matrix has one
row per learning object and one column per skill. The cells contain a "1" if the skill
is taught or required, respectively, by the learning object and a "0" otherwise,
cdss_read_skill_assignment_ods( filename, taughtname = "Taught", requiredname = "Required", warnonly = FALSE, verbose = TRUE )cdss_read_skill_assignment_ods( filename, taughtname = "Taught", requiredname = "Required", warnonly = FALSE, verbose = TRUE )
filename |
Name of the ODS-file |
taughtname |
Name of the sheet with required assignment (default = "Taught") |
requiredname |
Name of the sheet with required assignment (default = "Required") |
warnonly |
Are non-compliant SAs allowed? (default = FALSE) |
verbose |
Verbosity (default = TRUE) |
List of two binary matrices, "taught" and "required".
Other functions reading skill assignments:
cdss_read_skill_assignment_csv(),
cdss_read_skill_assignment_xlsx()
cdss_read_skill_assignment_xlsx expects an XLSX-file with two sheets assigning taught and
required, respectively, skills to learning objects with two columns each. The first
column contains the IDs of learning objects and the second row the IDs of single skills
required or taught, respectively, by this learning object.
It returns a list of two binary matrices, "taught" and "required". Each matrix has one
row per learning object and one column per skill. The cells contain a "1" if the skill
is taught or required, respectively, by the learning object and a "0" otherwise,
cdss_read_skill_assignment_xlsx( filename, taughtname = "Taught", requiredname = "Required", warnonly = FALSE, verbose = TRUE )cdss_read_skill_assignment_xlsx( filename, taughtname = "Taught", requiredname = "Required", warnonly = FALSE, verbose = TRUE )
filename |
Name of the XLSX-file |
taughtname |
Name of the sheet with required assignment (default = "Taught") |
requiredname |
Name of the sheet with required assignment (default = "Required") |
warnonly |
Are non-compliant SAs allowed? (default = FALSE) |
verbose |
Verbosity of compliance test (default = TRUE) |
List of two binary matrices, "taught" and "required".
Other functions reading skill assignments:
cdss_read_skill_assignment_csv(),
cdss_read_skill_assignment_ods()
cdss_sa_compliance expects a skill assignment and checks whether
it is compliant to the conditions for CDCS.
cdss_sa_compliance(sa, verbose = FALSE)cdss_sa_compliance(sa, verbose = FALSE)
sa |
Skill assignment |
verbose |
Verbosity (default = FALSE) |
Boolean
Other Functions testing validity of skill assignments:
cdss_circular_requirements(),
cdss_missing_los(),
cdss_nonteaching_los()
cdss_sa_describes_sr expects a list of two matrices (taught and required) of a skill
assignment. It returns TRUE if the skill assignment describes a surmise relation (i.e. there is
only one teaching LO per skill) and FALSE.
cdss_sa_describes_sr(sa, verbose = FALSE)cdss_sa_describes_sr(sa, verbose = FALSE)
sa |
Skill assignment object |
verbose |
Flag, default is FALSE |
Logical value
Other functions deriving skill structures from skill assignments:
cdss_lo_sa2ar(),
cdss_skill_sa2ar()
Derive a skill map from a skill assignment
cdss_sa2mu(sa)cdss_sa2mu(sa)
sa |
Skill assignment |
Skill multi map (cbkst_skillmultimap object); if sa
describes a surmise relation, the result is also a
cbkst_skillmap.
cdss_skill_sa2af expects a skill assignment and derives an attribution
function on the set of learning objects.
cdss_skill_sa2af(sa)cdss_skill_sa2af(sa)
sa |
Skill assignment object |
Object of class kmattributionfunction
Other functions building skill (multi) assignment matrices:
cdss_lo_sa2af(),
cdss_tables2sa()
cdss_skill_sa2ar expects a skill assignment and derives an attribution relation
on skills if the skill assignment fulfills the necessary conditions, i.e. if there
is only one teaching LO per skill.
cdss_skill_sa2ar(sa)cdss_skill_sa2ar(sa)
sa |
Skill assignment object |
attribution relation or NULL
Other functions deriving skill structures from skill assignments:
cdss_lo_sa2ar(),
cdss_sa_describes_sr()
cdss_tables2sa expects two data frames with two columns each. The first
column contains the IDs of learning objects and the second row the IDs of single skills
required or taught, respectively, by this learning object.
It returns a list of two binary matrices, "taught" and "required". Each matrix has one
row per learning object and one column per skill. The cells contain a "1" if the skill
is taught or required, respectively, by the learning object and a "0" otherwise.
cdss_tables2sa(taught, required)cdss_tables2sa(taught, required)
taught |
Data table containing the assignment of taught skills to learning objects |
required |
Data table containing the assignment of required skills to learning objects |
List of two binary matrices, "taught" and "required".
Other functions building skill (multi) assignment matrices:
cdss_lo_sa2af(),
cdss_skill_sa2af()