# Dissociations between data-driven and goal-driven effort reports: Performance, metacognition, and affect

## TL;DR

This study shows that how people report their effort depends on whether they focus on the task's demands or their own goals, and this affects their performance and emotions.

## Contribution

The paper introduces a distinction between data-driven and goal-driven effort and shows how they uniquely relate to learning outcomes.

## Key findings

- Data-driven effort was negatively linked to performance estimates.
- Goal-driven effort showed the opposite pattern, being positively linked to performance estimates.
- The framing of effort reports significantly influences their relationship with learning outcomes.

## Abstract

Measuring effort has long been a challenge and this seems particularly true in the case of subjective effort. Koriat et al. compared two types of effort frames, what they call data-driven effort, the amount of effort perceived to be required by a task, and goal-driven effort, the amount of effort one chooses to invest in a task. This study investigates whether self-reports of data- and goal-driven effort are differentially associated with test performance, metacognition, and affect in a complex learning task. Results demonstrate that data- and goal-driven effort have qualitatively different relations with many of these variables. For example, partial correlations revealed data-driven effort was negatively associated with prospective and retrospective performance estimates, but the opposite pattern emerged for goal-driven effort. These results demonstrate that how subjective measures of effort are framed (and interpreted by the respondent) can drastically influence how they relate to other variables of interest.