Epistemic Insights as Design Principles for a Teaching-Learning Module on Artificial Intelligence Epistemic Insights as Design Principles for a Teaching-Learning Module on Artificial Intelligence

In a historical moment in which Artificial Intelligence and machine learning have become within everyone’s reach, science education needs to find new ways to foster “AI literacy.” Since the AI revolution is not only a matter of having introduced extremely performant tools but has been determining a...

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Vydáno v:Science & education Ročník 34; číslo 2; s. 671 - 706
Hlavní autoři: Barelli, Eleonora, Lodi, Michael, Branchetti, Laura, Levrini, Olivia
Médium: Journal Article
Jazyk:angličtina
Vydáno: Dordrecht Springer Netherlands 01.04.2025
Springer Nature B.V
Témata:
Algorithms
Artificial intelligence
Chatbots
Cognitive Processes
Computer Science Education
Deep learning
Education
Educational Change
Educational Principles
Educational Research
Educational Technology
Elementary Secondary Education
Emotional Response
Epistemology
History
Influence of Technology
Information Processing
Instructional Materials
Language Processing
Learning algorithms
Learning Modules
Learning Objectives
Literature Reviews
Machine learning
Modules
Networks
Neural networks
Opacity
Philosophy of Science
Problem Solving
Programming
Scaffolding
Science Education
Science Instruction
Secondary Education
Secondary School Students
SI: Epistemic Insight & Artificial Intelligence
Students
Teaching
ISSN:0926-7220, 1573-1901
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Shrnutí:In a historical moment in which Artificial Intelligence and machine learning have become within everyone’s reach, science education needs to find new ways to foster “AI literacy.” Since the AI revolution is not only a matter of having introduced extremely performant tools but has been determining a radical change in how we conceive and produce knowledge, not only technical skills are needed but instruments to engage, cognitively, and culturally, with the epistemological challenges that this revolution poses. In this paper, we argue that epistemic insights can be introduced in AI teaching to highlight the differences between three paradigms: the imperative procedural, the declarative logic, and the machine learning based on neural networks (in particular, deep learning). To do this, we analyze a teaching-learning activity designed and implemented within a module on AI for upper secondary school students in which the game of tic-tac-toe is addressed from these three alternative perspectives. We show how the epistemic issues of opacity, uncertainty, and emergence, which the philosophical literature highlights as characterizing the novelty of deep learning with respect to other approaches, allow us to build the scaffolding for establishing a dialogue between the three different paradigms.
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ISSN:0926-7220
1573-1901
DOI:10.1007/s11191-024-00504-4