Analysis of article using Artificial Intelligence tools
|Author||Hafour M.F.; Alwaleedi M.|
|Title||Students’ Emotional and Behavioral Engagement: Cloud-based Collaborative Writing and Learning Analytics|
Hafour M.F.; Alwaleedi M. Students’ Emotional and Behavioral Engagement: Cloud-based Collaborative Writing and Learning Analytics,CALL-EJ 23 1
|Link to article|| https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126962102&partnerID=40&md5=a8e858ad1092d0ec0ed0406b8c85b6b7
|Abstract||Collaboration on, around, and through written text has been facilitated with the integration of cloud tools and platforms. Thanks to the learning analytics tools available on these platforms, large educational datasets on learners’ logs and online learning behavior are now at the instructors’ fingertips. Consequently, affective factors (like learning engagement), that have long been thought of as difficult and labor-intensive to observe and assess, can now be easily and objectively measured. In response, the current study examined the influence of cloud-based collaborative writing on EFL learners’ emotional and behavioral engagement using cloud learning analytics tools. A cohort of 27 junior EFL college students was selected and exposed to the eight-week intervention practicing collaborative writing and feedback on Google Docs. The quasi-experimental mixed-method design was followed. Quantitative data about behavioral engagement were collected using 4 indices: number of self-edits, frequency of learner logs, number of comments, and time spent per task. A pre-post emotional engagement scale was also administered. Quantitative results of the study revealed that, generally, students’ behavioral engagement did not change after the intervention, whereas their overall emotional engagement did. Qualitative data collected from the open-ended perceptions survey were generally in line with the quantitative ones. © 2022, CALL-EJ. All rights reserved.