Typologies for learning patterns for mathematical games: Introduction

The recent years have seen a growing acknowledgment of the educational potential of computer and video games among researchers, developers and practicioners. In spite of this, the design and deployment of pedagogically sound mathematics games with a wide appeal has proved illusive. There are many potential reasons for this but it is generally agreed that the process of designing and deploying a game for mathematical learning is a difficult task.

This project Learning patterns for the design and deployment of mathematical games aims to investigate this problem. We work from the premise that designing games for mathematical learning is a difficult task because it requires the assimilation and integration of deep knowledge from diverse domains of expertise including mathematics, games development, software engineering, learning and teaching. We see all these aspects of knowledge as various facets of design knowledge.

Our first outcome, a review of the literature, set out to identify and elucidate the key issues in this realm. We now wish to take a first step towards addressing those issues.
In order to facilitate communication and knowledge sharing between potential contributors to the design and deployment of games, we need to start by establishing a common language. We propose this set of typologies as a tool\ntowards that end. This set includes six typologies, each aiming to capture one aspect of design knowledge related to games for mathematical learning. Each typology is presented in two forms: a topic map (using FreeMind) and a browseable glossary.

Our typologies were developed by a group of domain experts through an iterative process of construction, testing, negotiation and refinement. We initiated this process by a brainstorming session conducted during a project meeting. Following this session, each domain expert published an initial draft of their respective typology. These drafts were scrutinised by the other project members. Using an on-line discussion mechanism, we queried each other for clarifications and illuminated possible gaps and overlaps. The next iteration explored the potential capacity of the typologies, by using them in the process of drafting case studies and learning patterns. The rationale was that, in order to make the typologies a productive tool, they need to be refined through productive use.

These typologies are not fixed - they will be constantly refined as our knowledge grows. We will offer stable versions of the typologies in the outcomes section, and at the same time continue to develop them in the workspace area. They will provide the semantic strata for the case studies and patterns, and in turn will be informed by those. Thus, we see a continuing iterative process in which typologies, case studies and patterns evolve in tandem.

A note for our guests:

Please feel welcome to browse this section, and comment on\nany typology you find interesting. Please note:

1. All content on this site is licensed. You may use these typologies in any way which conforms with the terms of that license.
2. All content in this section is perpetual work in progress. Please do not quote, cite or refer to it without consulting the authors. Stable outcomes will be presented in the outcomes section.

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