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@inbook{1820093,
author = {Effenberger, Tomáš and Pelánek, Radek},
address = {Cham},
booktitle = {Visualizations and Dashboards for Learning Analytics},
doi = {http://dx.doi.org/10.1007/978-3-030-81222-5_20},
editor = {Muhittin Sahin, Dirk Ifenthaler},
keywords = {exploratory data analysis; learning environment; heat map; dotted chart},
howpublished = {elektronická verze "online"},
language = {eng},
location = {Cham},
isbn = {978-3-030-81221-8},
pages = {439-456},
publisher = {Springer},
title = {Visualization of Student-Item Interaction Matrix},
url = {https://link.springer.com/chapter/10.1007/978-3-030-81222-5_20},
year = {2021}
}
TY - CHAP
ID - 1820093
AU - Effenberger, Tomáš - Pelánek, Radek
PY - 2021
TI - Visualization of Student-Item Interaction Matrix
VL - Advances in Analytics for Learning and Teaching
PB - Springer
CY - Cham
SN - 9783030812218
KW - exploratory data analysis
KW - learning environment
KW - heat map
KW - dotted chart
UR - https://link.springer.com/chapter/10.1007/978-3-030-81222-5_20
N2 - One type of visualization of data from digital learning environments focuses on students’ interaction with the educational content. Students may, for example, answer questions, read texts, or solve problems. We can represent these interactions as a matrix, where rows correspond to students, columns to educational items, and values to some aspect of student activity (e.g., the correctness of answers, response times, the order of actions). Visualizing this matrix is useful for several purposes. For teachers, it can provide an understanding of the skill and behavior of their students. For system developers, it can provide insight into the behavior of both students and adaptive algorithms, and it can also help detect suspicious activity. For researchers, it can provide an understanding of the properties of datasets used in experiments and valuable warnings about biases that are present in data. However, suitable visualization of the student-item interactions is nontrivial. To facilitate the design of the visualization, we provide a systematic discussion of approaches to student-item matrix visualization. Using data from an introductory programming exercise, we also provide specific illustrations of different visualization designs.
ER -
EFFENBERGER, Tomáš and Radek PELÁNEK. Visualization of Student-Item Interaction Matrix. Online. In Muhittin Sahin, Dirk Ifenthaler. \textit{Visualizations and Dashboards for Learning Analytics}. Cham: Springer, 2021, p.~439-456. Advances in Analytics for Learning and Teaching. ISBN~978-3-030-81221-8. Available from: https://dx.doi.org/10.1007/978-3-030-81222-5\_{}20.
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