Delivering processing instruction in classroom and virtual contexts

Processing Instruction (PI) is an approach to grammar instruction for second language learning. It derives its name from the fact that the instruction (both the explicit explanation as well as the practices) attempt to influence, alter, and/or improve the way learners process input. PI contrasts with traditional grammar instruction in many ways, most principally in its focus on input whereas traditional grammar instruction focuses on learners' output. The greatest contribution of PI to both theory and practice is the concept of "structured input", a form of comprehensible input that has been manipulated to maximize learners' benefit of exposure to input. This volume focuses on a new issue for PI, the role of technology in language learning. It examines empirically the differential effects of delivering PI in classrooms with an instructor and students interacting (with each other and with the instructor) versus on computers to students working individually. It also contributes to the growing body of research on the effects of PI on different languages as well as different linguistic items: preterite/imperfect aspectual contrast and negative informal commands in Spanish, the subjunctive of doubt and opinion in Italian, and the subjunctive of doubt in French. Further research contributions are made by comparing PI with other types of instruction, specifically, with meaning-oriented output instruction.

Engineering design knowledge management in de-centralised virtual enterprises

The problems of collaborative engineering design and knowledge management at the conceptual stage in a network of dissimilar enterprises was investigated. This issue in engineering design is a result of the supply chain and virtual enterprise (VE) oriented industry that demands faster time to market and accurate cost/manufacturing analysis from conception. The solution consisted of a de-centralised super-peer net architecture to establish and maintain communications between enterprises in a VE. In the solution outlined below, the enterprises are able to share knowledge in a common format and nomenclature via the building-block shareable super-ontology that can be tailored on a project by project basis, whilst maintaining the common nomenclature of the ‘super-ontology’ eliminating knowledge interpretation issues. The two-tier architecture layout of the solution glues together the peer-peer and super-ontologies to form a coherent system for both internal and virtual enterprise knowledge management and product development.