Context-Aware Recommender Systems for Learning: A Survey and Future Challenges <s> Computing <s> Abstract This paper sets out a framework for the design of a new genre of educational technology — personal (handheld or wearable) computer systems that support learning from any location throughout a lifetime. We set out a theory of lifelong learning mediated by technology and indicate how it can provide requirements for the software, hardware, communications and interface design of a handheld learning resource, or HandLeR. The paper concludes with a description and formative evaluation of a demonstrator system for children aged 7–11. <s> BIB001 </s> Context-Aware Recommender Systems for Learning: A Survey and Future Challenges <s> Computing <s> The access devices of today are becoming increasingly sophisticated. Thanks to multimedia, communication is much widespread and therefore more powerful. However, we face a serious problem of heterogeneity in our terminals, in our networks, and in the people who ultimately consume and interact with the information presented to them. In this article, we focus on Part 7 of the MPEG-21 standard (ISO/IEC 21000-7), which we refer to as Digital Item Adaptation (DIA). At the time of this writing, the DIA specification is at the penultimate stage of Final Committee Draft (2003); final approval is scheduled for December 2003. The general DIA concept is that Digital Item is subject to both a resource adaptation and a descriptor adaptation engine, which together produce the adapted Digital Item. Note that the standard specifies only the tools that assist with the adaptation process, not the adaptation engines themselves. Digital Item Adaptation (DIA) specifies the following natural environment description tools: location and time and audiovisual environment. The DIA offers a rich set of tools to assist with the adaptation of Digital Items. It offers standardized tools for the description of usage environments, tools to create high-level descriptions of the bitstream syntax to achieve format-independent adaptation, tools that assist in making tradeoffs between feasible adaptation operations and constraints, tools that enable low-complexity adaptation of metadata, and tools for session mobility. Moving forward, the MPEG-21 committee is considering amendments to the specification-for instance, tools that provide further assistance with modality conversion and tools that relate more specifically to the adaptation of audio and graphics media. Furthermore, also being actively considered is how to express the rights that a User has to perform adaptation and how this expression fits into a system that governs those rights. <s> BIB002 </s> Context-Aware Recommender Systems for Learning: A Survey and Future Challenges <s> Computing <s> Mobile learning is becoming an important research topic as people are increasingly connected through smart phones that combine telephony, computing, messaging, and multimedia. The process of designing, communicating and presenting learning resources for mobile learners poses new challenges to the research community. This is mainly due to the limited bandwidth of wireless networks, limited resource available on mobile devices, and the special requirements of mobile learners. In this paper, an attempt is made to solve some of these problems by proposing an ontology-based framework for context-aware mobile learning. The system consists mainly of a rule-based ontology and a search agent. The rule-based ontology component is driven by the learner profile to contextualize learning content accordingly. The goal is to extract from a source ontology a lightweight target ontology by firing a set of rules based on the learner profile. The extracted conceptual knowledge is then mapped to a set of learning objects that meet the technical requirements of the used mobile technology. The mapping is geared by a search agent that searches a set of distributed learning objects repositories for feasible lightweight learning objects. <s> BIB003
Computing context has been researched extensively by the pervasive and mobile research community  , including by researchers in the mobile learning area BIB001 , BIB003 . Computing characteristics can be classified in three areas. . Network includes static and dynamic properties of the network, such as maximum and available bandwidth. . Hardware comprises input and output capabilities of devices, storage or CPU capabilities, etc. . Software describes whether the delivery context supports certain APIs, document formats, operating systems, application-layer protocols, etc. The acquisition and use of computing context is necessary to support intelligent interfaces that can for instance select suitable learning resources for the device that is used. The prevalent standards for describing computing characteristics are W3C Composite Capabilities/ Preferences Profile (CC/PP)  , User Agent Profile (UAprofile)  , developed by OMA, and the Usage Environment Description (UED) standard which was standardized within MPEG-21 Digital Item Adaptation BIB002 . CC/PP defines only a basic structure of components and attributes without specifying a particular vocabulary of terms  . UAProfile adopts CC/PP and provides a concrete vocabulary mainly targeting mobile devices. UED defines both the structure and a comprehensive vocabulary. Device profiles can also be identified using the open source Wireless Universal Resource FiLe project (WURFL)  . WURFL is a community effort that collects a wide range of device descriptions.