The Importance Of Regulatory Fit & Early Success In A Human-Machine Game

In this paper, we explore the potential of regulatory focus theory as a framework for personalizing human-machine interactions. We manipulate framing (gain or loss) of a collaborative word-guessing game where a fully-automated virtual human gives clues. Consistent with previous work on regulatory focus, we find evidence of significantly higher perceived task-success when participants have regulatory fit. Inconsistent with previous work, however, fit did not increase task-enjoyment (nor performance). Participants with gain framing had marginally higher enjoyment, regardless of their regulatory focus. We operationalize motivation by number of optional rounds played but failed to find a "fit" effect. Instead, players who achieved early success (scoring more points in initial rounds) were more motivated. Early success was significantly correlated with number of optional rounds played. This finding calls to attention the need for the literature to more thoroughly investigate the relationship between success-timing and total player playtime in the game.