Exploratory factor analysis of 384 learners' log data identifies four factors in usage of UDL-guided elements, indicating learners remain consistent in decisions such as video vs. text and tasks with or without help¶

Claim · All claims
Evidence · 1 study (2 entries) · associational r1–r2 · q2
Currency · newest study 2024 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? EFA on usage durations of UDL-guided elements (texts, videos, tasks with/without help, self-assessments) yielded a four-factor solution in which tasks with help and tasks without help separate into distinct factors, and videos separate from texts, suggesting learners stay consistent in these decisions throughout the platform. → Marvin Roski 2024

Evidence¶

Marvin Roski 2024¶

Marvin Roski, Ratan Sebastian, Ralph Ewerth, Anett Hoppe, Andreas Nehring. (2024). Learning analytics and the Universal Design for Learning (UDL): A clustering approach. Computers & Education 214 (2024) 105028. https://doi.org/10.1016/j.compedu.2024.105028

q2 · i? · associational · r2

Exploratory factor analysis of log-file-derived usage durations from 384 learners on the I3Learn platform. Suitability was supported by the Bartlett test (chi-square = 5389.13, p < 0.001) and a "KMO value = 0.677". The authors reduced a five-factor elbow solution to four factors for interpretability.

"The results of both the Bartlett test (chi-square = 5389.13, p < 0.001) and the Kaiser-Mayer-Olkin coefficient (KMO value = 0.677) indicate the general feasibility of EFA with the data set"

Marvin Roski 2024 (2)¶

Marvin Roski, Ratan Sebastian, Ralph Ewerth, Anett Hoppe, Andreas Nehring. (2024). Learning analytics and the Universal Design for Learning (UDL): A clustering approach. Computers & Education 214 (2024) 105028. https://doi.org/10.1016/j.compedu.2024.105028

q2 · i? · associational · r1

The authors' interpretation of the EFA factor structure: Factor 1 captured tasks with help and Factor 3 tasks without help, while Factor 2 captured videos and Factor 4 texts, implying that "learners remain consistent in decision-making behavior throughout using I3Learn". This is an interpretation of factor content, not a tested comparison.

"Factor 1 mainly contains tasks with help, Factor 3 mainly without help. This implies that learners remain consistent in decision-making behavior throughout using I3Learn: They tend to choose the tasks with or without help, regardless of where the tasks are located on their learning journey."

Discussion¶

Related Claims¶

• The six clusters differ substantially in usage duration of UDL-guided elements, with the small Cluster 2 investing particularly more time than Cluster 1 — related
• K-means clustering on EFA-derived features yields six learner groups with distinct usage patterns of UDL-guided elements — related
• All UDL-guided elements were used voluntarily, supporting the inference that offering several UDL-guided elements in a web-based platform diversifies learning opportunities and supports self-regulated learning — related