Exploring online authentic learning environment (OnALE) for inferential statistics: its efficacy and benefits to statistics learners

• Published in: Educational Technology Research and Development
• Main Author: Lau U.H.; Tasir Z.
• Format: Article
• Language: English
• Published: Springer 2024
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85176459740&doi=10.1007%2fs11423-023-10287-0&partnerID=40&md5=882f59c6877f258d3aa3419630962b4c

An online authentic learning environment (OnALE) is proposed in this study to facilitate students’ learning of inferential statistics in a real-life context. The efficacy of the OnALE, in comparison to the conventional approach relative to the students’ performance, was explored. Respondents from the experimental group were purposively selected to complete the Perception Questionnaire regarding the features of the OnALE. The Analysis of Covariance (ANCOVA) on the post-test scores using prior knowledge scores as covariate disclosed a significant variance in the post-test scores between control and experimental groups (F (1, 74) = 10.924, p < 0.05, partial η2 = 0.129), with the experimental group displaying a higher mean score. Outcomes from the Perception Questionnaire revealed that all respondents at least agreed that each authentic learning characteristic in the OnALE facilitated their learning. The highest and the lowest rated characteristics were Collaboration and Multiple Roles and Perspectives, respectively. The framework of the OnALE characteristics for varying levels of students’ performance unveiled the combinations of authentic learning characteristics beneficial to students from different performing groups. This framework functions as a guideline for statistics educators and learning designers to provide an effective online learning environment. © Association for Educational Communications and Technology 2023.