Application of Artificial Intelligence (AI) to enhance the design and application of Open Educational Practices (OEP)
This collection begins with a paper titled “The evolution of sustainability models for Open Educational Resources: Insights from the literature and experts”, discussing how emerging technologies have changed the sustainability models for OER. In this context, Tlili et al. (2020) applied the triangulation method, where they start first by collecting the available sustainability models for OER via a systematic review. They then validated these models through a two-round Delphi method with thirty OER experts. The obtained findings identified and analyzed ten OER sustainability models, where public and internal funding are the most established ones. The next paper titled “Impact of cultural diversity on students’ learning behavioral patterns in open and online courses: A lag sequential analysis approach” highlighted the potential conflicts that could be raised in open courses due to learners being from different cultures. In this context, Tlili et al. (2021b) applied Lag Sequential Analysis (LSA) to investigate how students from China, Tunisia and Serbia behave in an open course on Moodle based on the theoretical framework of Hofstede’s National Cultural Dimensions (NCD). The obtained results highlighted that students from each culture behave differently due to several interconnecting factors, such as educational traditions. The results also pointed out that culture is a complex dimension, and further investigation is needed to understand the other dimensions that may affect online and open learning behaviors. In the paper titled “Understanding user behavioral patterns in open knowledge communities”, Yang et al. (2018) also applied LSA to investigate how users collaboratively create and share knowledge in Open knowledge communities (OKCs). The obtained findings revealed that content editing and commenting were the most frequently occurred behaviors. On the other hand, uploading material, inviting collaborators, and credibility voting were the least occurred behaviors
Edited by
Ahmed Tlili, [email protected](Smart Learning Institute of Beijing Normal University (SLIBNU), China)
Daniel Burgos, [email protected](2. Daniel Burgos, [email protected], Universidad Internacional de La Rioja (UNIR), Spain)