Content area
The critical need to increase access to computer science education is highlighted by President Obama’ “CSforAll” initiative to provide CS education for all K-12 children in the United States (Smith 2016). Because of the central importance of Computer Science to innovation, it is increasingly important to expand equitable access to CS education. According to Russell and Norvig (2016), AI includes problem solving, representation and reasoning of certain/uncertain knowledge, machine learning, and communicating, perceiving and acting techniques for designing and developing intelligent agents. Rivers and Koedinger have tested this approach in the domain of Python, a programming language that supports different programming paradigms: object-oriented, aspect-oriented, and functional programming. [...]this approach seems to be promising. Gerdes, Heeren, Jeuring, and van Binsbergen propose a strategy-based model tracing and property-based testing approach to modeling the domain of Haskell, a functional programming language, in their paper “Ask-Elle: a teacher-adaptable programming tutor for Haskell giving automated feedback.”
Details
Teaching;
Programming languages;
Students;
Intelligent agents;
Computer science;
Artificial intelligence;
Error correction & detection;
Functional programming;
Science education;
Education;
Communication;
Educational technology;
Python;
Self-efficacy;
Machine learning;
Model tracing;
Learning;
Object oriented programming;
Skills
1 North Carolina State University, Raleigh, USA (GRID:grid.40803.3f) (ISNI:0000000121736074)
2 Arizona State University, Tempe, USA (GRID:grid.215654.1) (ISNI:0000000121512636)
3 Humboldt Universität zu Berlin, Berlin, Germany (GRID:grid.7468.d) (ISNI:0000000122487639)
4 German Research Center for Artificial Intelligence (DFKI), Saarbrücken, Germany (GRID:grid.17272.31) (ISNI:000000040621750X)