The Influence Of Instructor-generated Drawings On Video Learning Performance:The Role Of Learners ’ Prior Knowledge And Generative Learning Strategies

With the rapid development of information technology,great changes have taken place in the platforms and ways for people to accept knowledge.Whether it is a traditional classroom or flipped classroom in full swing,online learning with video as the main learning resource carrier is a crucial link.Instructional design based on video learning has become a concern of researchers.According to the cognitive theory of multimedia learning,the use of different content presentation modes for the same knowledge point will have a great impact on the learning effect of learners.As a novel content presentation mode,instructor-generated drawing shows many advantages compared with traditional static presentation and animation presentation,which has been widely concerned by many researchers and educational practitioners.And some of learners’ characteristics will affect the effectiveness of instructor-generated drawings.In addition,for different types of learners,what learning strategies should be adopted to maximize the role of instructor-generated drawings is also a question worth exploring.Therefore,this study carried out two experiments to explore the promoting effect of instructor-generated drawings on video learning and its influencing factors.In Experiment 1,144 participants were selected,and a 3(content presentation mode:instructor-generated drawings vs animation vs static picture)× 2(learner’s prior knowledge : high vs low)between-subjects design was used to explore the effect of different content presentation mode on video learning effect,and to explore the effect of learner prior knowledge on the effectiveness of instructor-generated drawings.The results of Experiment 1 showed that compared with static picture group,learners in instructor-generated drawings and animation group had lower external cognitive load,higher learning interest and motivation,and higher scores in retention test and transfer test.In addition,compared with the animation group,the learners in the instructor-generated drawings group have higher interest in learning.Compared with low prior knowledge learners,high prior knowledge learners have lower external cognitive load and perceived task difficulty,higher learning interest and motivation,and better performance in retention test and transfer test.In addition,for learners with low prior knowledge,instructor-generated drawings can significantly reduce their external cognitive load,improve their learning interest and motivation,and improve their retention test and transfer test scores.For learners with high prior knowledge,there is no significant improvement.In Experiment 2,107 participants with low prior knowledge were selected,and a 2(content presentation mode: instructor-generated drawings vs animation)× 2(generative learning strategy : self-explanation vs repeated watching)between-subjects design was used to verify the promotion effect of instructor-generated drawings and explore the influence of different learning strategies on the effectiveness of instructor-generated drawings,and then explore the predictive effect of self-explanation quality on learning effect based on the prognostic explaining hypotheses.Experiment 2verified the promoting effect of instructor-generated drawings on video learning effect,and found that for learners with low prior knowledge,self-explanation strategy could not significantly improve their learning effect.In addition,under the condition of self-explanation,there was no significant difference in the learning effect between instructor-generated drawings group and animation group.Under the condition of repeated watching,compared with animation,instructor-generated drawings can significantly reduce the learners ’ perceived tasks difficulty and improve their retention test scores.On the whole,the learners in the instructor-generated drawings repeated watching group had the best test scores and the lowest difficulty of the perceptual task.There was no significant difference between the learners in the instructor-generated drawings self-explanation group and the animation self-explanation group,while the learners in the animation repeated watching group were the worst.Finally,through the coding analysis of self-explanatory texts generated by learners,the experiment verifies the prognostic explaining hypotheses,and the quality of self-explanation can significantly predict learners ’ retention test and transfer test scores.The research shows that:(1)In video learning,dynamic presentation of teaching content can improve learners ’ enthusiasm and promote learning.Among them,instructor-generated drawings has the best effect on learning,which is better than animation presentation and static picture presentation.(2)In video learning,learners with high prior knowledge have better learning effect.Learners’ prior knowledge and experience will affect the positive role of instructor-generated drawings.Instructor-generated drawings can only improve the learning effect of learners with low prior knowledge,but does not affect learners with high prior knowledge.(3)For learners with low prior knowledge,self-explanation strategy cannot significantly improve their learning effect compared with repeated watching.(4)For learners with low prior knowledge,the combination of instructor-generated drawings and repeated watching has the best promotion effect on learning effect,followed by the combination of instructor-generated drawings and self-explanation and the combination of animation and self-explanation,and there is no significant difference.(5)Learners’ self-explanatory quality can significantly predict their retention and transfer test scores.