دورية أكاديمية
Assessing the Learning of Machine Learning in K-12: A Ten-Year Systematic Mapping
| العنوان: | Assessing the Learning of Machine Learning in K-12: A Ten-Year Systematic Mapping |
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| اللغة: | English |
| المؤلفون: | Rauber, Marcelo Fernando, Gresse Von Wangenheim, Christiane |
| المصدر: | Informatics in Education. 2023 22(2):295-328. |
| الإتاحة: | Vilnius University Institute of Mathematics and Informatics, Lithuanian Academy of Sciences. Akademjos str. 4, Vilnius LT 08663 Lithuania. Tel: +37-5-21-09300; Fax: +37-5-27-29209; e-mail: info@mii.vu.lt; Web site: https://infedu.vu.lt/journal/INFEDU |
| Peer Reviewed: | Y |
| Page Count: | 34 |
| تاريخ النشر: | 2023 |
| نوع الوثيقة: | Journal Articles Reports - Evaluative |
| Education Level: | Elementary Secondary Education |
| Descriptors: | Artificial Intelligence, Technology Education, Elementary Secondary Education, Educational Strategies, Evaluation Methods, Instructional Design, Student Evaluation, Feedback (Response), Automation, Test Construction |
| تدمد: | 1648-5831 2335-8971 |
| مستخلص: | Although Machine Learning (ML) has already become part of our daily lives, few are familiar with this technology. Thus, in order to help students to understand ML, its potential, and limitations and to empower them to become creators of intelligent solutions, diverse courses for teaching ML in K-12 have emerged. Yet, a question less considered is how to assess the learning of ML. Therefore, we performed a systematic mapping identifying 27 instructional units, which also present a quantitative assessment of the students' learning. The simplest assessments range from quizzes to performance-based assessments assessing the learning of basic ML concepts, approaches, and in some cases ethical issues and the impact of ML on lower cognitive levels. Feedback is mostly limited to the indication of the correctness of the answers and only a few assessments are automated. These results indicate a need for more rigorous and comprehensive research in this area. |
| Abstractor: | As Provided |
| Entry Date: | 2023 |
| رقم الأكسشن: | EJ1392994 |
| قاعدة البيانات: | ERIC |
| تدمد: | 1648-5831 2335-8971 |
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