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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 a Radek PELÁNEK. Visualization of Student-Item Interaction Matrix. Online. In Muhittin Sahin, Dirk Ifenthaler. \textit{Visualizations and Dashboards for Learning Analytics}. Cham: Springer, 2021, s.~439-456. Advances in Analytics for Learning and Teaching. ISBN~978-3-030-81221-8. Dostupné z: https://dx.doi.org/10.1007/978-3-030-81222-5\_{}20.
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