Survey of Personalized Learning Software Systems: A Taxonomy of Environments, Learning Content, and User Models
| dc.contributor.author | Ismail,by Heba | |
| dc.contributor.author | Hussein , Nada | |
| dc.contributor.author | Harous,Saad | |
| dc.contributor.author | Khalil,Ashraf | |
| dc.date.accessioned | 2024-02-23T07:32:49Z | |
| dc.date.available | 2024-02-23T07:32:49Z | |
| dc.date.issued | 2023-07-20 | |
| dc.description | The human brain comprehends and perceives concepts uniquely. However, teaching has invariably followed a one-size-fits-all approach. Educators conventionally follow a learning model called the cohort-based model, which is characterized by relatively large numbers of students moving through the same curriculum at the same rate [1]. A significant disadvantage of the cohort-based method is that individual learning needs can never be fully addressed, compromising the effectiveness and efficiency of education [1]. Therefore, considerable efforts have been directed toward personalizing the educational process. However, personalized learning could never occur at scale without leveraging advanced technologies [2]. | |
| dc.description.abstract | This paper presents a comprehensive systematic review of personalized learning software systems. All the systems under review are designed to aid educational stakeholders by personalizing one or more facets of the learning process. This is achieved by exploring and analyzing the common architectural attributes among personalized learning software systems. A literature-driven taxonomy is recognized and built to categorize and analyze the reviewed literature. Relevant papers are filtered to produce a final set of full systems to be reviewed and analyzed. In this meta-review, a set of 72 selected personalized learning software systems have been reviewed and categorized based on the proposed personalized learning taxonomy. The proposed taxonomy outlines the three main architectural components of any personalized learning software system: learning environment, learner model, and content. It further defines the different realizations and attributions of each component. Surveyed systems have been analyzed under the proposed taxonomy according to their architectural components, usage, strengths, and weaknesses. Then, the role of these systems in the development of the field of personalized learning systems is discussed. This review sheds light on the field’s current challenges that need to be resolved in the upcoming years. Keywords: Personalized Learning Software Systems, Learner Models, Learning Content, Learning Environments, Taxonomy, Glossary, Personalized Learning Software Systems Architecture. | |
| dc.identifier.citation | Ismail, H., Hussein, N., Harous, S., & Khalil, A. (2023). Survey of personalized learning software systems: A taxonomy of environments, learning content, and user models. Education Sciences, 13(7), 741. | |
| dc.identifier.doi | https://doi.org/10.3390/educsci13070741 | |
| dc.identifier.uri | https://dspace.adu.ac.ae/handle/1/1281 | |
| dc.language.iso | en | |
| dc.publisher | MDPI | |
| dc.title | Survey of Personalized Learning Software Systems: A Taxonomy of Environments, Learning Content, and User Models | |
| dc.type | Article |