Memory for task-action mappings: mnemonics, regularity and consistency

Much of the knowledge required to use modern computing systems takes the form of mappings or associations. These associations occur between user goals and the functions that accomplish those goals, between functions and the user actions that activate a desired function, and between a menu item or a button label and the function associated with that item or label. The question we explore in this paper is: when is it worthwhile, if ever, to make a user pay the price of learning a new set of task-action mappings? In other words, how much interference is there when the new set is inconsistent with the original set of task-action mappings of the previously known system? We consider three factors that determine the ease of learning and retention of task-action mappings: mnemonics, regularity within a set of mappings, and consistency of mapping across different system contexts. In two experiments, we found that Irregular-Non-Mnemonic mappings take much longer to master than Regular-Mnemonic mappings and that Irregular-Non-Mnemonic mappings are more rapidly forgotten and subject to interference effects due to inconsistency. Regular-Non-Mnemonic mappings fall between the two groups. They are easier to learn and retain than Irregular-Non-Mnemonic but harder than Regular-Mnemonic mappings. We conclude that transferring from a well-learned set of old task-action mappings is simple when the new set is regular (completely consistent) and mnemonic.