A comparative survey of integrated learning systems

This paper presents the duction framework for unifying the three basic forms of inference - deduction, abduction, and induction - by specifying the possible relationships and influences among them in the context of integrated learning. Special assumptive forms of inference are defined that extend the use of these inference methods, and the properties of these forms are explored. A comparison to a related inference-based learning frame work is made. Finally several existing integrated learning programs are examined in the perspective of the duction framework

Strange bedfellows? Keyword and conceptual search unite to make sense of relevant ESI in electronic discovery

In the brief history of electronic discovery, the latter part of the twentieth century witnessed the demise of paper by a digital hero that emancipated the content of paper documents with OCR and TIFF. This technology added a third dimension to the realm of 2D paper document review and production that lead to a sea change in discovery methods. By many accounts what we have before us is a three-stage evolution from paper to digital to clustering in order to overcome the problems of volume and complexity of ESI. The intent of this position paper is to describe the development of the digital hero and methodology that is emancipating the content and context of ESI – conceptual search that spans file formats, languages and technique, and includes keyword search on a common, shared index

Pleading as Information-Forcing

This study has been conducted in the context of the master program in Outdoor Environmental Education and Outdoor Life, of Linköping University. It aspires to investigate a specific part of outdoor environments: the schoolyards. Particularly, the aim of the study is to investigate how the use of the school grounds as an educational resource is influenced by their environments -rural or urban. The research compares the school communities’ (principals’, teachers’ and students’) perceptions about the use of their school grounds during the educational process. The research sample consists of 10 Swedish elementary schools, from which the five are in rural and five are in urban environments. The participants are in total 10 principals, 51 teachers and 295 students. Alongside, an observation recorded in a list and photographs enhance the comparison between the rural and urban schools’ infrastructures. From the 1268 photos taken, a selection is included in the study and constitutes the observation part. The study negotiates four controversial issues about school grounds’ capacities: space or place; good or bad; rural or urban; grounds of a school or grounds of a curriculum. The results, after all, reject the contradictions and the sections become respectively: a place for all seasons; neither good nor bad, just unique! ; Ideality stands for ideas; grounds for cooperation. It also becomes visible that even though the analysis of the responses confirms that the urban teachers hold the stereotypical idea that there are differences between rural and urban environments; the infrastructures of both environments do not appear different. However, the teachers’ different opinions and beliefs have a significant impact on the students’ responses. Specifically, significant differences are reported by students which align with the teachers’ differences. The rural and urban principals do not report significant differences, and in the great majority their opinions also align with their teachers’ opinions. Finally, a model which is unfolded through this study has central role, namely the schoolyard circle. This model aims to facilitate a process that I introduce as schoolisization, in which school grounds are used to extend the stereotypical learning environment by adapting the curriculum to a school’s needs. Consequently, the schoolyards’ transformation from a space to our place can be finally proved an outdoor education approach that “bridges contradictions” and promises better educational results

Pleading as Information-Forcing

Academics, judges, and practitioners have devoted much attention to the potential impact of the federal pleading standards announced in Ashcroft v. Iqbal, 556 U.S. 662 (2009), and Bell Atlantic Corp. v. Twombly, 550 U.S. 544 (2007). Many have criticized Iqbal and Twombly on procedural, substantive, and policy grounds. And although most everyone agrees that the cases mark a break with past liberal pleading rules and have changed pleading practice, there is little agreement about precisely how the cases have affected ultimate outcomes. Indeed, there is much confusion about what exactly the new rules require of a pleader. In this Article, I argue that the confusion can be traced in large part to two related errors, unrecognized to date by commentators. The first error is simple but subtle: when the Court announced Iqbal and Twombly, it used old language in new ways and in a new context. The Court rested its decisions on a particular understanding of the words “conclusory” and “plausible,” but did not acknowledge that before Iqbal and Twombly those words each had specific meanings in procedural jurisprudence. The old meanings did not jibe with how the Court used them in its new decisions; overnight the words “conclusory” and “plausible” meant something new in pleading and lower courts were left to sift through the rubble. Second, and relatedly, Iqbal and Twombly implicitly make pleading something of an information-forcing regime. Yet the Court did not rest its shift in emphasis on any of the justifications that the law typically relies upon for information-forcing rules. Here, I provide a taxonomy of some of the classic justifications for information-forcing rules and show that they do not map easily onto pleading. There are dangers inherent to both of these types of errors. When the Court uses legal terms with established meaning in a new way without any acknowledgment, it forces lower courts to attempt to reconcile apparently conflicting Supreme Court precedent with little guidance. It should be no surprise, then, that many judges at the district court and appellate level express frustration at applying the Court’s new decisions. And when the Court blindly imports an information-forcing regime into a context that calls for more nuanced evaluation, it increases the risk that governing doctrine will become even less coherent. I conclude, therefore, with modest suggestions for adhering to Iqbal and Twombly while minimizing this risk of incoherenc

Strategies for adding adaptive learning mechanisms to rule-based diagnostic expert systems

Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base