Effects of prior knowledge and joint attention on learning from eye movement modelling examples

Abstract

Eye movement modelling examples (EMMEs) are instructional videos of a model's demonstration and explanation of a task that also show where the model is looking. EMMEs are expected to synchronize students' visual attention with the model's, leading to better learning than regular video modelling examples (MEs). However, synchronization is seldom directly tested. Moreover, recent research suggests that EMMEs might be more effective than ME for low prior knowledge learners. We therefore used a 2 × 2 between‐subjects design to investigate if the effectiveness of EMMEs (EMMEs/ME) is moderated by prior knowledge (high/low, manipulated by pretraining), applying eye tracking to assess synchronization. Contrary to expectations, EMMEs did not lead to higher learning outcomes than ME, and no interaction with prior knowledge was found. Structural equation modelling shows the mechanism through which EMMEs affect learning: Seeing the model's eye movements helped learners to look faster at referenced information, which was associated with higher learning outcomes.

Using eye movement modelling examples to guide visual attention and foster cognitive performance: A meta‐analysis

“…expertise reversal effect , Kalyuga, 2007; Kalyuga et al, 2003). Even so, there are studies in which no moderating role of prior knowledge in the effect of EMME on cognitive performance was found (Chisari et al, 2020; Wang et al, 2020).…”

Do prior knowledge, model-observer similarity and social comparison influence the effectiveness of eye movement modeling examples for supporting multimedia learning?

“…Accordingly, EMME are supposed to support learners in selecting relevant information more quickly. In line with this assumption, Chisari et al (2020), for example, recently demonstrated that learners with EMME-guidance looked faster at referenced information, which was associated with higher learning outcomes.…”

“…In contrast, there is research by Van Marlen et al (2018) showing that a sample of low prior knowledge learners benefited from EMME (Experiment 2), whereas a sample of high prior knowledge learners did not benefit from any instructional support (Experiment 1). Furthermore, in a recent study, Chisari et al (2020) observed no influence of prior knowledge (high vs. low) on the effectiveness of EMME.…”

“…Against this background, when investigating (alleged) similarity with regard to competence/expertise, it is important that the participants do not receive any information about other model characteristics. A closer look at other studies in the EMME context show that participants often receive not only explicit information about the model's competence/expertise, but also implicit or explicit information about other model characteristics such as gender or status (e.g., Chisari et al, 2020;Jarodzka et al, 2013;Van Marlen et al, 2018). To investigate only the effect of (alleged) similarity in terms of competence/expertise, in our previous experiments as well as in the present one we provided no further information about other model characteristics in the introductory text or in the EMME-videos (cf.…”

“…Thus, it can be assumed that gaze cues follow the same mechanisms. Moreover, it is presumed that synchronization processes are triggered by observing the model's eye movements (Jarodzka et al, 2013;Van Marlen et al, 2016), which establishes a form of joint attention and allows learners to infer which information is task relevant (e.g., Chisari et al, 2020;Van Gog et al, 2009). Accordingly, EMME are supposed to support learners in selecting relevant information more quickly.…”