芬兰小学生对机器学习的概念理解
Finnish primary school students' conceptions of machine learning
AI总结：
本研究调查了197名芬兰小学生在无概念引导下对机器学习的理解，发现其概念可分为教导机器、编程及通过机器学习三类，强调了计算机科学教育中清晰使用关键概念的重要性。
摘要：
目的：本研究调查小学生在没有概念“引导”（即认为在机器学习（ML）中是人类教计算机）的情况下，对ML会有什么样的概念理解。方法：采用外推法分析了197名芬兰小学生的定性调查回复。发现：我们识别出三个部分重叠的ML概念类别，从最准确到最不准确依次为：ML是关于教机器（34%），ML是关于编程（7.6%），以及ML是关于通过机器学习或了解机器（37.1%）。启示：研究结果表明，在没有概念提示的情况下，儿童对ML的理解是多样的，可能包含诸如ML是关于通过机器学习或了解机器这样的误解。研究结果强调了在计算机科学教育中清晰系统地使用关键概念的重要性。除了研究人员外，本研究还为教师、教师教育者、课程开发者和政策制定者提供了见解。方法：采用外推法分析了197名芬兰小学生的定性调查回复。发现：我们识别出三个部分重叠的ML概念类别，从最准确到最不准确依次为：ML是关于教机器（34%），ML是关于编程（7.6%），以及ML是关于通过机器学习或了解机器（37.1%）。启示：研究结果表明，在没有概念提示的情况下，儿童对ML的理解是多样的，可能包含诸如ML是关于通过机器学习或了解机器这样的误解。研究结果强调了在计算机科学教育中清晰系统地使用关键概念的重要性。除了研究人员外，本研究还为教师、教师教育者、课程开发者和政策制定者提供了见解。
英文摘要：
Objective This study investigates what kind of conceptions primary school students have about ML if they are not conceptually "primed" with the idea that in ML, humans teach computers. Method Qualitative survey responses from 197 Finnish primary schoolers were analyzed via an abductive method. Findings We identified three partly overlapping ML conception categories, starting from the most accurate one: ML is about teaching machines (34%), ML is about coding (7.6%), and ML is about learning via or about machines (37.1%). Implications The findings suggest that without conceptual clues, children's conceptions of ML are varied and may include misconceptions such as ML is about learning via or about machines. The findings underline the importance of clear and systematic use of key concepts in computer science education. Besides researchers, this study offers insights for teachers, teacher educators, curriculum developers, and policymakers. Method Qualitative survey responses from 197 Finnish primary schoolers were analyzed via an abductive method. Findings We identified three partly overlapping ML conception categories, starting from the most accurate one: ML is about teaching machines (34%), ML is about coding (7.6%), and ML is about learning via or about machines (37.1%). Implications The findings suggest that without conceptual clues, children's conceptions of ML are varied and may include misconceptions such as ML is about learning via or about machines. The findings underline the importance of clear and systematic use of key concepts in computer science education. Besides researchers, this study offers insights for teachers, teacher educators, curriculum developers, and policymakers.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
