satisfaction {rrcov3way} | R Documentation |
Student satisfaction data
Description
The primary assessment tool for analyzing student satisfaction is an
annual questionnaire organized into five categories: degree program, course
characteristics, teaching, equipment, and overall satisfaction.
Each questionnaire comprises 18 standardized questions rated on a ten-point
Likert scale (1 = "Strongly Disagree" to 10 = "Strongly Agree"). The
original microdata were aggregated by 10 faculties and six academic years.
Thus, we have a threeway array with dimensions 10 x 18 x 6
.
Usage
data(satisfaction)
Format
A three-way array with dimension 10 x 18 x 6
.
The first dimension refers to the 10 faculties. The second dimension
refers to 18 standardized questions rated on a ten-point Likert scale
(1 = "Strongly Disagree" to 10 = "Strongly Agree").
The third dimension refers to six consequtive academic years (2012–2017).
Source
Italian universities are mandated by Law No. 370/99 to evaluate teaching quality through student opinion surveys. The National Agency for the Evaluation of Universities and Research (ANVUR), established in 2006, supervises the periodic assessment of academic quality. Following Presidential Decree 76/2010, ANVUR standardized methodologies for evaluating institutions and degree programs, with a strong focus on student involvement. The University of Florence provided microdata, which were later aggregated into data for 10 faculties, 18 questions and 6 academic years.
Simonacci V, Gallo M (2017) Statistical tools for student evaluation of academic educational quality. Quality & Quantity 51(2):565–579
References
Gallo M, Simonacci V, Todorov V (2021) A compositional three-way approach for student satisfaction analysis. In: Filzmoser P, Hron K, Martin–Fernandez JA, Palarea-Albaladejo J (eds) Advances in Compositional Data Analysis, Springer, Cham, pp 143–162
Todorov, V., Simonacci, V., Gallo, M., and Di Palma, M. (2025). Robust tools for three-way component analysis of compositional data: The R package rrcov3way. Behaviormetrika. In press.
Examples
data(satisfaction)
t3 <- Tucker3(satisfaction, P=2, Q=2, R=1, coda.transform="clr")
t3
t3$A
t3$B
t3$C
t3$G
plot(t3)
plot(t3, which="jbplot", xlim=c(-1, 1))