Towards Intelligent Databases

This article is a presentation of the objectives and techniques of deductive databases. The deductive approach to databases aims at extending with intensional definitions other database paradigms that describe applications extensionaUy. We first show how constructive specifications can be expressed with deduction rules, and how normative conditions can be defined using integrity constraints. We outline the principles of bottom-up and top-down query answering procedures and present the techniques used for integrity checking. We then argue that it is often desirable to manage with a database system not only database applications, but also specifications of system components. We present such meta-level specifications and discuss their advantages over conventional approaches

Problem-Solving Knowledge Mining from Users’\ud Actions in an Intelligent Tutoring System

In an intelligent tutoring system (ITS), the domain expert should provide\ud relevant domain knowledge to the tutor so that it will be able to guide the\ud learner during problem solving. However, in several domains, this knowledge is\ud not predetermined and should be captured or learned from expert users as well as\ud intermediate and novice users. Our hypothesis is that, knowledge discovery (KD)\ud techniques can help to build this domain intelligence in ITS. This paper proposes\ud a framework to capture problem-solving knowledge using a promising approach\ud of data and knowledge discovery based on a combination of sequential pattern\ud mining and association rules discovery techniques. The framework has been implemented\ud and is used to discover new meta knowledge and rules in a given domain\ud which then extend domain knowledge and serve as problem space allowing\ud the intelligent tutoring system to guide learners in problem-solving situations.\ud Preliminary experiments have been conducted using the framework as an alternative\ud to a path-planning problem solver in CanadarmTutor

Continual Evolution: The Experience Over Three Semesters of a Librarian Embedded in an Online Evidence-Based Medicine Course for Physician Assistant Students

This column examines the experience, over three years, of a librarian embedded in an online Epidemiology and Evidence-based Medicine course, which is a requirement for students pursing a Master of Science in Physician Assistant Studies at Pace University. Student learning outcomes were determined, a video lecture was created, and student learning was assessed via a five-point test during year one. For years two and three, the course instructor asked the librarian to be responsible for two weeks of the course instruction and a total of 15 out of 100 possible points for the course. This gave the librarian flexibility to measure additional outcomes and gather more in-depth assessment data. The librarian then used the assessment data to target areas for improvement in the lessons and Blackboard tests. Revisions made by the librarian positively affected student achievement of learning outcomes, as measured by the assessment conducted the subsequent semester. Plans for further changes are also discussed

A design recording framework to facilitate knowledge sharing in collaborative software engineering

This paper describes an environment that allows a development team to share knowledge about software artefacts by recording decisions and rationales as well as supporting the team in formulating and maintaining design constraints. It explores the use of multi-dimensional design spaces for capturing various issues arising during development and presenting this meta-information using a network of views. It describes a framework to underlie the collaborative environment and shows the supporting architecture and its implementation. It addresses how the artefacts and their meta-information are captured in a non-invasive way and shows how an artefact repository is embedded to store and manage the artefacts