Kevin Waugh

A Classification of Object-Relational Impedance Mismatch

Object and relational technologies are grounded in different paradigms. Each technology mandates that those who use it take a particular view of a universe of discourse. Incompatibilities between these views manifest as problems of an object-relational impedance mismatch. In this paper we propose a conceptual framework for the problem space of object-relational impedance mismatch and consequently distinguish four kinds of impedance mismatch. We show that each kind of impedance mismatch needs to be addressed using a different object-relational mapping strategy. Our framework provides a mechanism to explore issues of fidelity, integrity and completeness in the design and implementation of existing and new strategy choices. Our framework will be of benefit to standards bodies, tool vendors, designers and programmers as it will provide them with new insights into how to address problems of an object-relational impedance mismatch both at the most appropriate levels of abstraction and in the most appropriate way.

Interpreting Imprecise Diagrams

Imprecise diagrams (those with malformed, missing, or extraneous features) occur in many situations. We propose a five-stage architecture for interpreting such diagrams and have implemented a tool, within this architecture, for automatically grading answers to examination questions. The approach is based on identifying (possibly malformed) minimal meaningful units and interpreting them to yield a meaningful result. Early indications are that the tool’s performance is similar to that of human markers.

Experiments in the automatic marking of ER-diagrams

In this paper we present an approach to the computer understanding of diagrams and show how it can be successfully applied to the automatic marking (grading) of student attempts at drawing entity-relationship (ER) diagrams. The automatic marker has been incorporated into a revision tool to enable students to practice diagramming and obtain feedback on their attempts.

Automatically Assessing Graph-Based Diagrams

To date there has been very little work on the machine understanding of imprecise diagrams, such as diagrams drawn by students in response to assessment questions. Imprecise diagrams exhibit faults such as missing, extraneous and incorrectly formed elements. The semantics of imprecise diagrams are difficult to determine. While there have been successful attempts at assessing text (essays) automatically, little success with diagrams has been reported. In this paper, we explain an approach to the automatic interpretation of graph‐based diagrams based on a five‐stage framework. The paper describes our approach to automatically grading graph‐based diagrams and reports on some experiments into the automatic grading of student diagrams. The diagrams were produced under examination conditions and the output of the automatic marker was compared with the original human marks across a large number of diagrams. The experiments show good agreement between the performance of the automatic marker and the human markers. The paper also describes how the automatic marking algorithm has been incorporated into a variety of software teaching and learning tools. One tool supports the human grading of entity‐relationship diagrams (ERDs). Another tool is for student use during the revision of ERDs. This tool automatically marks student answers in real‐time and provides dynamically created feedback to help guide the students progress.

Computer assisted assessment of diagrams

In this paper, we describe an approach to the grading (marking) of graph-based diagrams. The work is an application of a framework for the computer interpretation of imprecise diagrams (which students produce in response to assessment questions). We describe the interpretation framework and how it has been applied in the domain of entity-relationship diagrams used in data modeling. In our approach to grading, student diagrams are compared to specimen solutions representing correct solutions to an assessment question. The comparison between a student diagram and a specimen solution diagram results in a matching of the two diagrams from which a grade is computed. The comparison matching is used to provide graphical feedback on the correctness of the student diagram. The approach has been applied to a test corpus of 394 diagrams produced in answer to an examination question with some good results: 91% of all automatically produced grades were within 0.5 of a mark of the human graders. However, when supertype-subtype associations are present, the performance drops to around 87%. The paper concludes with a discussion of some applications of the marker.

Using patterns in the automatic marking of ER-diagrams

This paper illustrates how the notion of pattern can be used in the automatic analysis and synthesis of diagrams, applied particularly to the automatic marking of ER-diagrams. The paper describes how diagram patterns fit into a general framework for diagram interpretation and provides examples of how patterns can be exploited in other fields. Diagram patterns are defined and specified within the area of ER-diagrams. The paper also shows how patterns are being exploited in a revision tool for understanding ER-diagrams.

Teaching and Learning Applications Related to the Automated Interpretation of ERDs

In this paper we report ongoing work in the development of diagram interpretation and assessment applied to entity-relationship diagrams (ERDs). We report on our development of an automated marking tool and the results of two large-scale experiments with this tool. We give an overview and the results of some initial, informal, evaluation of a student revision tool that we developed as a result of our experiences working on the automated marking system.

An investigation into the automated assessment of the design-code interface

In this paper, we present an investigation into the development of a framework for the automatic grading (marking) of student submitted course work. We discuss this framework, its structure and its subsystems. Our framework has been developed in the context of the student submission consisting of two components: a design (using the UML methodology) and source code (using the Java programming language). The focus of our framework is upon the consistency between the student code and design. We discuss its context and development and highlight how we can infer structure from the student submission and use this to inform the assessment process. We describe the approach we are currently undertaking to instantiate this framework and apply it to work submitted for assessment by undergraduate computing students.

Generalised diagramming tools with automatic marking

Abstract We describe an approach to the generalisation of tools for teaching and learning the skills associated with modelling with diagrams. The paper briefly describes the existing revision tools and our approach to automatic marking of diagrams. We report on our work to generalise both the marking algorithm and the drawing editor in such a way that revision tools can be easily generated for new domains. We also report how we have incorporated our tools into our institution’s Moodle-based Virtual Learning Environment (VLE).

Diagram interpretation and e-learning systems

We describe a system capable of grading free-form diagrammatic answers. Our matches meaningful parts of a diagram with equivalents in a model solution. This is complicated by errors, omissions, and superfluous items in the student answer. The result of matching is used to calculate the grade and generate appropriate feedback; it performs at least as well as a human marker on a variety of diagram types. We describe tools that allow the easy creation of questions, marking schemes, and diagram editors suitable for embedding in a VLE quiz engine.