Effects Of Eye Movement Modeling Examples In Video Learning

Digital transformation is driving sweeping changes in society,and education is no exception.For the burgeoning demand of education digitization,the construction of instructional videos deserves extra attention.However,recent researches found that the transient presentation of information on instructional videos imposed an excessive burden on learners’ information selection,organization,and integration.Therefore,some instructional aids should be considered in the original materials to help learners mitigate the risk of cognitive overloading.Eye movement modeling examples(EMME)is one such effective aid.It allows eye movement from individuals of high expertise to be superimposed on the learning material.This helps learners with low priori knowledge to locate useful information quickly,guiding them to use effective cognitive processing strategies and creating social learning contexts.However,the effects of eye movement modeling examples in video learning are inconsistent.This may be related to the level of model expertise and learner control.Based on the Cognitive Theory of Multimedia Learning,the Cognitive Load Theory,and the Information-reduction Hypothesis,this study explored the effects of model expertise and learner control on eye movement modeling examples.In Experiment 1,84 undergraduate and postgraduate students were used as participants to explore the effects of the model expertise to EMME(Expert model vs.Intermediate model vs.no model)on learners’ learning outcomes,cognitive load,learning experience,and attention allocation.The results revealed that:(1)The videos adding EMME reduced learners’ extrinsic cognitive load,increased relevant cognitive load,and led to a higher perception of teacher-student interaction and motivation.(2)Compared with no EMME or expert EMME,the video with intermediate EMME was more effective in enhancing learners’ learning outcomes and engagement.(3)The videos adding EMME caused learners to show the same attention processing patterns as the model.According to previous studies,the effectiveness of EMME may be related to learner control.Therefore,in Experiment 2,111 undergraduate and postgraduate students were used as participants to investigate the effects of learner control(learner control vs.system control)on learning outcomes,cognitive load,learning experience,and attention allocation during watching videos adding different expertise EMME(Expert model vs.Intermediate model).The results revealed that:(1)There was no difference in the effects of expert EMME and intermediate EMME on learning outcomes in the system control condition;The expert EMME was more effective in the learner control condition.(2)In the system control condition,learners showed the same attention processing patterns as the models;In the learner control condition,learners in the intermediate EMME group showed different attention processing patterns from the model,and they increased their attention to the picture area.(3)The model expertise and learner control did not significantly affect learners’ cognitive load and learning experience.In summary,the following conclusions were drawn:(1)Under the system control condition,instructional videos adding intermediate EMME reduced extrinsic cognitive load,increased relevant cognitive load,facilitated in-depth cognitive processing,and improved learning outcomes and learning experience.(2)Under the learner control condition,instructional videos adding expert EMME deepened learners’ memory and understanding.(3)The EMME had a significant effect on attention guidance,and learners showed the same attention processing patterns as the model.This study empirically investigated the effectiveness of EMME in video learning and the boundary conditions for use.These findings provide support for the application of EMME in video learning.And it broadens the research horizon for instructional videos and provides valuable references for the design and use of instructional videos.