Context-Aware Recommendation Algorithms for the PERCEPOLIS Personalized Education Platform


This paper describes Pervasive Cyberinfrastructure for Personalized Learning and Instructional Support (PERCEPOLIS), where context-aware recommendation algorithms facilitate personalized learning and instruction. Fundamental to PERCEPOLIS are (a) modular course development and offering, which increase the resolution of the curriculum and allow for finer-grained personalization of learning artifacts and associated data collection; (b) blended learning, which allows class time to be used for active learning, interactive problem solving and reflective instructional tasks; and (c) networked curricula, in which the components form a cohesive and strongly interconnected whole where learning in one area reinforces and supports learning in other areas. Intelligent software agents customize the content of a course for each learner, based on his or her academic profile and interests, aided by context-based recommendation algorithms. This paper provides an introduction to the PERCEPOLIS platform, with focus on these algorithms; and describes the educational research that underpins its design.

Meeting Name

41st Annual Frontiers in Education Conference (2011: Oct. 12-15, Rapid City, SD)


Electrical and Computer Engineering

Second Department

Computer Science


National Science Foundation (U.S.)


The research presented in this paper was supported in part by the National Science Foundation, under contract IIS-0324835.

Keywords and Phrases

Active Learning; Blended Learning; Context-Aware; Context-Based Recommendations; Course Development; Cyber Infrastructures; Data Collection; Educational Research; Instructional Support; Intelligent Software Agent; Interactive Problem Solving; Learning Artifacts; Personalizations; Personalized Learning; Recommendation Algorithms; Algorithms; Teaching; Ubiquitous Computing; Curricula; Context-Aware Recommendation; Multi-Agent Software; Pervasive Computing

International Standard Book Number (ISBN)

978-1612844695; 978-1612844688

International Standard Serial Number (ISSN)

0190-5848; 2377-634X

Document Type

Article - Conference proceedings

Document Version


File Type





© 2011 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

01 Oct 2011