Constitution of Meaning Using Contexts

An Empirical Study of a Project on Reinforcement Learning Using the Example of Q-Learning

Abstract

The article discusses an approach for learners to AI algorithms by means of context. This approach should enable the constitution of meaning by linking context and content. Q-learning is used as an example for this. In the study, students were videotaped as they explored the Q-learning algorithm and the transcripts were analysed using qualitative content analysis. The results indicate that the students use the context to solve comprehension problems and suggest that they are used for the purpose of constituting meaning. This clearly shows the potential of relevant contexts for constituting meaning when working with AI algorithms.