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Effectiveness of Story-based Visual and Agile Teaching Method for Non-technical Adult Learners Who Want to Understand Artificial Intelligence

机译:基于故事的视觉和敏捷教学方法对想了解人工智能的非技术成人学习者的有效性

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This study proposes and evaluates an effective teaching method for non-technical adults who want to understand artificial intelligence (AI). As the number of non-technical business professionals who want to improve their participation in technical discussions is increasing, it becomes important to find effective teaching methods for non-technical adults who need to understand core technical concepts in which they are involved reasonably. The proposed teaching method utilizes the active use of visual feedback and agile practices to overcome the challenges the adult learners face. In this study, we evaluated the effectiveness of the proposed teaching method by the open coding method to analyze the free-form responses and by the paired t-test over the responses to the questions asked to the participants before and after the lecture. We found that this teaching method effectively supported the learners to understand the basic technical concepts of AI within one or two-day time frame. We also confirmed the non-technical adult learners had significantly changed their attitude toward understanding AI from initially negative to positive with a good expectation of success in understanding AI, which is one of the important outcomes for the learners as the expectancy-value theory predicts their future performance on understanding AI.
机译:这项研究为想要了解人工智能(AI)的非技术成人提出并评估了一种有效的教学方法。随着希望提高他们对技术讨论的参与度的非技术业务专业人员的数量不断增加,为需要理解其合理参与的核心技术概念的非技术成人找到有效的教学方法变得很重要。所提出的教学方法充分利用了视觉反馈和敏捷实践,以克服成人学习者面临的挑战。在本研究中,我们通过开放编码方法分析自由形式的回答,并通过配对t检验对讲课前后向参与者提出的问题的回答进行评估,从而评估了所提出的教学方法的有效性。我们发现,这种教学方法有效地支持了学习者在一两天内了解AI的基本技术概念。我们还确认,非技术成人学习者已将他们对AI的理解态度从最初的消极转变为积极,对成功理解AI的期望很高,这是学习者的重要成果之一,因为期望值理论预测他们了解AI的未来表现。

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