Anticipatory saccades as an implicit measure of self-evaluations of own knowledge and corresponding test performance

Student self-assessment is an essential component of effective learning (Black & Wiliam, 1998) and accurate self-assessment (realistic subjective self-evaluations) can lead to more proactive learning (Karaman, 2021), arguably resulting in better exam performance. It is not clear, whether self-assessment has to be accurate to yield positive effects, since positively-biased self-assessment of students has also been found to have positive effects on performance, but inaccurate, negatively-biased self-assessment seems to be detrimental to performance (Butler, 2011). One way to measure how much self-evaluations align with actual performance (from now on denoted as self-evaluation accuracy as we will only focus on this aspect of self-assessment) is to compare the self-reported competence of a participant to the performance in a corresponding test (e.g., Narciss, Koerndle, & Dresel, 2011). However, in such studies explicit measures of self-evaluation are used, which are prone to self-report biases such as the tendency to be unrealistically optimistic about one`s abilities and the belief to be above average (Brown & Harris, 2014). Moreover, studies using such explicit measures of self-evaluation typically ask for global evaluations (e.g., course grade) rather than evaluations on the level of individual tasks or questions. Information on a learner’s self-evaluation and its accuracy could be beneficial to systematically guide the learning process, for instance, in e-learning by providing corresponding feedback. Yet frequent self-reports of subjective self-evaluation are not very practical and, as mentioned before, a subject to answer biases. Here, we will try to establish an alternative means of assessing self-evaluation (implicit and on the level of individual questions). Thus, we will test anticipatory saccades (e.g., Gouret & Pfeuffer, 2021; Pfeuffer et al., 2016, 2022) as a potential implicit measure of self-evaluations in the context of learning. Ideally, such anticipatory saccades could, in the future, be simultaneously assessed when learners complete, for instance, quizzes and should not be affected by answer biases. When an action contingently yields a consequence at a certain location (e.g., right key press > visual effect on the right), participants anticipatorily move their eyes in the direction of the future consequence/effect before it appears (e.g., Pfeuffer et al., 2016, 2022). Importantly, such anticipatory saccades already emerge after 1-2 learning trials (Gouret & Pfeuffer, 2021). We will test whether such anticipatory saccades also emerge when learning is tested in quizzes. Quiz questions will be presented in the central part of the screen and feedback will appear after a short delay. Crucially, correct feedback will appear on one side of the screen (e.g., left) and incorrect feedback will appear on the other side of the screen (e.g., right). We will assess whether participants’ anticipatory saccades (frequency of saccades in the direction of the future corresponding correct/incorrect feedback) can be used to assess participants’ expectations regarding the correctness of their respective responses and hence provide an implicit measure of their self-evaluation derived from the self-evaluation of individual answers. We will assess relations between implicit self-evaluation accuracy (I-SE-A; difference between anticipated and actual answer correctness across questions, sensitivity index according to signal detection theory) and implicit self-evaluation bias (I-SE-B; deviations of anticipated answer correctness from actual answer correctness in self-report questions in the positive or negative direction, response bias according to signal detection theory; both as inferred from such anticipatory saccades), quiz performance (multiple quizzes), accuracy and bias of self-reported explicit self-evaluations (E-SE-A and E-SE-B), and corresponding exam success. List of Abbreviations I-SE-A: Implicit Self-Evaluation Accuracy I-SE-B: Implicit Self-Evaluation Bias E-SE-A: Explicit Self-Evaluation Accuracy E-SE-B: Explicit Self-Evaluation Bias I-SE-A-X: Implicit Self-Evaluation Accuracy in Session X