What Students Should Learn and Teachers Must Know About Artificial Intelligence

被引：0

作者：

Opel, Simone ^{[1
]}

Linxen, Andrea ^{[1
]}

Beecks, Christian ^{[1
]}

机构：

[1] Fern Univ Hagen, D-58097 Hagen, Germany

来源：

INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING - IDEAL 2024, PT II | 2025年 / 15347卷

关键词：

Curriculum; AI; Secondary School; Teacher Education; Learning; Students; Further Education; Curriculum Analysis;

D O I：

10.1007/978-3-031-77738-7_40

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Systems based on artificial intelligence have become prominent in nearly all domains. However, knowledge of the inner workings of these intelligent systems is not as widespread, partly because the associated issues have been discussed only to a limited extent in computer science education. In order to gain an overview of AI in curricula and to see what competencies teachers need to teach this content, the AIrelated content of the computer science curricula of the German federal states was analysed and compared with existing approaches. Proposals for further training courses are derived from this to enable teachers to teach AI competently.

引用

页码：488 / 494

页数：7

共 16 条

[1]

Abedjan Z., 2021, Gesellschaft f ur Informatik e.V.

[2]

Anderson L., 2001, TAXONOMY LEARNING TE, DOI DOI 10.7771/1541-5015.1355

[3]

Anderson P, 2014, PROCEEDINGS OF THE 45TH ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION (SIGCSE'14), P145

[4] Deep Machine Learning-A New Frontier in Artificial Intelligence Research [J].

Arel, Itamar ;

Rose, Derek C. ;

Karnowski, Thomas P. .

IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE, 2010, 5 (04) :13-18

[5] Enhancing teaching through constructive alignment [J].

Biggs, J .

HIGHER EDUCATION, 1996, 32 (03) :347-364

[6]

Brinda T., 2016, Gesellschaft f ur Informatik e.V.

[7]

Clear Alison, 2020, Technical Report

[8] Distributed data source verification in wireless sensor networks [J].

Conti, Mauro ;

Di Pietro, Roberto ;

Mancini, Luigi V. ;

Mei, Alessandro .

INFORMATION FUSION, 2009, 10 (04) :342-353

[9] Curriculum Guidelines for Undergraduate Programs in Data Science [J].

De Veaux, Richard D. ;

Agarwal, Mahesh ;

Averett, Maia ;

Baumer, Benjamin S. ;

Bray, Andrew ;

Bressoud, Thomas C. ;

Bryant, Lance ;

Cheng, Lei Z. ;

Francis, Amanda ;

Gould, Robert ;

Kim, Albert Y. ;

Kretchmar, Matt ;

Lu, Qin ;

Moskol, Ann ;

Nolan, Deborah ;

Pelayo, Roberto ;

Raleigh, Sean ;

Sethi, Ricky J. ;

Sondjaja, Mutiara ;

Tiruviluamala, Neelesh ;

Uhlig, Paul X. ;

Washington, Talitha M. ;

Wesley, Curtis L. ;

White, David ;

Ye, Ping .

ANNUAL REVIEW OF STATISTICS AND ITS APPLICATION, VOL 4, 2017, 4 :15-30

[10]

EDISON Project, 2023, Edison: Building the data science profession

← 1 2 →