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If feedback is considered as a criterion for automated support in learning, the

device presented by Pressey in 1923 was the first teaching machine (Ludy 88). Skinner picked up Pressey’s design as well as the foundation in the theory of Thorndike. Based on Skinners concept machines and systems for programmed instruction (PI) were developed. Extended computational power and general problem solving theories lead to the idea of intelligent tutoring systems (ITS) and adaptive learning environments (ALE).

n the last years, the successful application of recommender systems in marketing led to the idea of transferring those systems in the didactical field in the form of educational recommender systems (ERS) (Duwal 2011).

With systems for programmed instruction, intelligent tutoring systems, adaptive

learning environments, and pedagogical recommender systems concepts for automatic educational reasoning (AER) have been developed. Despite the effort invested in AER systems there are hardly actually working systems available or real world applications reported. AER systems seem to have failed due to the high effort necessary to develop such systems and the lack of theoretical foundations (Schulmeister 2007). This might be connected to one concept all the systems developed so far share: Learning is considered as a formally describable and controllable process.