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Which Task Characteristics Do Students Rely on When They Evaluate Their Abilities to Solve Linear Function Tasks? - A Task-Specific Assessment of Self-Efficacy.


ABSTRACT: Self-efficacy is an important predictor of learning and achievement. By definition, self-efficacy requires a task-specific assessment, in which students are asked to evaluate whether they can solve concrete tasks. An underlying assumption in previous research into such assessments was that self-efficacy is a one-dimensional construct. However, empirical evidence for this assumption is lacking, and research on students' performance suggests that it depends on various task characteristics (e.g., the representational format). The present study explores the potential multi-dimensionality of self-efficacy in the topic of linear functions. More specifically, we investigate how three task characteristics - (1) the representational format, (2) embedding in a real-life context, or (3) the required operation - are related to students' self-efficacy. We asked 8th and 9th graders (N = 376) to evaluate their self-efficacy on specific linear function tasks which systematically varied along the three dimensions of task characteristics. Using confirmatory factor analysis, we found that a two-dimensional model which includes the task characteristic of real-life context (i.e., with vs. without a real-life context) fitted the data better than other two-dimensional models or a one-dimensional model. These results suggest that self-efficacy with linear functions is empirically separable with respect to tasks with vs. without a real-life context. This means that in their self-evaluation of linear function tasks students particularly rely on whether or not the linear function task is embedded in a real-life context. This study highlights the fact that even within a specific content domain students' self-efficacy can be considered a multi-dimensional construct.

SUBMITTER: Siefer K 

PROVIDER: S-EPMC7994344 | biostudies-literature |

REPOSITORIES: biostudies-literature

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