The Effect Of Double Sample Variability On Computational Thinking Ability Of High School Students

Worked-example learning has a long history,and its effectiveness has been confirmed.At the same time,it is found that the effect of worked-example learning is affected by the presentation of worked-examples.According to different teaching objectives,the design of worked-examples should also be changed.The double workedexamples refer to an original example and the varied example.It makes variation on the basis of the original example,which inspires students to think deeply about the materials,so as to draw inferences from other worked-examples.Most of the experiments on the influence of double worked-examples on students are focused on mathematics,the programming learning is not widely involved,and there are few researches on the promotion of computational thinking.Computational Thinking is a series of thinking activities involved in solving complex problems,which is reflected in all aspects of learning and life,and can be well cultivated in programming learning.However,the time when computational thinking has been formally incorporated into the curriculum standard is still relatively short.How to influence students' Computational Thinking through the variation of worked-examples needs to be studied.Therefore,in this experiment,Python examples are used as learning materials to explore the influence of worked-example design on students' Computational Thinking scores.Three experiments are designed with the senior two students of Yu Hua Tai middle school affiliated to Nanjing Normal University as the research object.In Experiment 1,the type of variation and the level of prior knowledge were used as independent variables,and the score of Computational Thinking was taken as the dependent variable.An experiment of 2(structural feature variation and surface feature variation)× 3(high prior knowledge level,medium prior knowledge level and low prior knowledge level)was designed to explore the influence of variation type on Computational Thinking performance.In Experiment 2,we chose the variation of structural characteristics to explore,and divided it into two types of variation degree:high and low.In Experiment 2,taking the degree of structural feature variation and prior knowledge level as independent variables and Computational Thinking performance as dependent variables,an experiment of 2(high variation of structural characteristics and low variation of structural characteristics)× 3(high prior knowledge level,medium prior knowledge level and low prior knowledge level)was designed to explore the influence of structural feature variation degree on Computational Thinking performance.In Experiment 3,taking the variation degree of surface features and prior knowledge level as independent variables and Computational Thinking performance as dependent variables,an experiment of 2(high variation of surface features and low variation of surface features)× 3(high prior knowledge level,medium prior knowledge level and low prior knowledge level)was designed to explore the influence of variation degree of surface features on Computational Thinking performance.According to the experimental results,the following conclusions are drawn:(1)No matter what the students' prior knowledge level is,the structural feature variation examples and the surface feature variation examples can improve the computational thinking ability,but they are not significant;However,for the students with low prior knowledge level,structural feature variation examples can significantly improve their computational thinking ability.(2)No matter what the prior knowledge level of students is,the high variability and low variability of structural features can significantly improve students' computational thinking ability,but there is no significant difference between the two groups.(3)For the students with medium and high prior knowledge level,the use of highly variable examples of structural features can significantly improve the students' computational thinking ability;For the students with low and medium prior knowledge level,the use of low variation examples of structural features can significantly improve the students' computational thinking ability.(4)No matter what the students' prior knowledge level is,the examples with high variation of surface features and the examples with low variation of surface features can not significantly improve the students' computational thinking ability,and there is no significant difference between the two groups of examples in the post test of computational thinking.(5)For students with low level of prior knowledge,examples with high variation of surface features can significantly improve students' computational thinking ability.