Personalized Knowledge Awareness Map in Computer Supported Ubiquitous Learning

El-Bishouty, Moushir M.; Ogata, Hiroaki; Yano, Yoneo

doi:10.1109/icalt.2006.1652566

Cited by 59 publications

(61 citation statements)

References 11 publications

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“…Visualisations can help to explain recommendation results by explicitly exposing relationships among content and people. El-Bishouty et al [28], for instance, researched the use of visualisation techniques to present the relationship between recommended peer-learners. Visualisation techniques can increase understanding of in-and output for a recommender system.…”

Section: Analysis According To the Frameworkmentioning

confidence: 99%

Panorama of Recommender Systems to Support Learning

Drachsler

Verbert

Santos

et al. 2015

Recommender Systems Handbook

175

106

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Section: Analysis According To the Frameworkmentioning

confidence: 99%

Panorama of Recommender Systems to Support Learning

Drachsler

Verbert

Santos

et al. 2015

Recommender Systems Handbook

175

106

View full text Add to dashboard Cite

“…Specific services may encourage social interactions, for example the PERKAM prototype that enables learners to find relevant peer learner-helpers [20].…”

Section: Social Interactionsmentioning

confidence: 99%

“…Recommendations for learning resources that aim to support daily living, rather than the completion of a structured curriculum need to take into account personal goals and interests as well as providing resources appropriate to the learner's current level of learning competency and progress through materials. The PERKAM system, for example, identifies personal interests through a learner profile: on registration, learners are asked to enter their personal information and topics of interest, and as they engage with the system, their actions are also recorded to the profile [20].…”

Section: Learning Goals and Personal Interestsmentioning

confidence: 99%

Challenges in Context-Aware Mobile Language Learning: The MASELTOV Approach

Gaved

Luley

Efremidis

et al. 2014

Mobile as a Mainstream – Towards Future Challenges in Mobile Learning

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Abstract. Smartphones, as highly portable networked computing devices with embedded sensors including GPS receivers, are ideal platforms to support context-aware language learning. They can enable learning when the user is engaged in everyday activities while out and about, complementing formal language classes. A significant challenge, however, has been the practical implementation of services that can accurately identify and make use of context, particularly location, to offer meaningful language learning recommendations to users. In this paper we review a range of approaches to identifying context to support mobile language learning. We consider how dynamically changing aspects of context may influence the quality of recommendations presented to a user. We introduce the MASELTOV project's use of context awareness combined with a rules-based recommendation engine to present suitable learning content to recent immigrants in urban areas; a group that may benefit from contextual support and can use the city as a learning environment.

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“…We asked the new computer science students from the introductory course if they wanted to join an orientation rally to see the campus. 49 Students participated in the field test, of whom 12.24% were female. 53.19% were new students in the first semester.…”

Section: Field Testsmentioning

confidence: 99%

“…Orientation Area-wide P. Technique Ambient Wood [22] X FM Pingers Bird Watching Learning System [26] BodyLearning [27] Butterfly Watching Learning System [3] Caerus [28] X X GPS Clls [21] X RFID CLUE [29] RFID CropViewer [30] X X GPS Electronic Guidebook [4] RFID Environmental Detectives [31] X X GPS eSchoolbag [32] X X GPS Exploratorium [5] X RFID Garden Explorer [33] X X GPS Genius Loci [27] X Ekahau Gipsy [30] X X GPS ImagiProbe [34] Hypertag Magus Guide system [35] Infrared M-Eco-Learn [36] x Digital Map ME-Learning Experience [37] x Digital Map Milk [2] X SMS Mobile cinematic presentations [38] X Infrared Mobile Learning Passport [39] X Fotos Mobile Lessons [40] X GPS Moles [41] Moop [42] X GPS Motus2 [43] MoULe [44] X GPS Museum Outside Walls [45] Musex [46] X RFID MyArtSpace [47] periLearn [48] X X GPS and CELL ID PerkamII [49] X RFID RAFT [50] TANGO [51] RFID Tate Modern Multimedia Tour Pilots [19] WIFI The Lost Worlds of Somers Town [52] X Virtual Exhibitions [53] RFID Table 1: Orientation support in mobile learning projects…”

Section: Projectmentioning

confidence: 99%