Teaching Machine Learning in K-12 Education

被引：13
|
作者：
Sanusi, Ismaila Temitayo [1 ]
机构：
[1] Univ Eastern Finland, Sch Comp, Kuopio, Finland
来源：
ICER 2021: PROCEEDINGS OF THE 17TH ACM CONFERENCE ON INTERNATIONAL COMPUTING EDUCATION RESEARCH | 2021年
关键词：
Teaching machine learning; K-12; Pedagogy; Machine Learning Education; Machine Learning Tools; ARTIFICIAL-INTELLIGENCE;
D O I：
10.1145/3446871.3469769
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
This research is interested in how to teach machine learning concepts to K-12 learners. There is limited evidence to support the teaching, learning, and usefulness of machine learning in K-12 settings, hence addressing the evident gap. This research aims to specifically identify pedagogical approaches with the underlying theories and methods in teaching K-12 machine learning as well as design, assess, and determine the impact of machine learning on student outcomes in K-12.
引用
收藏
页码：395 / 397
页数：3
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