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Cognitive Spacetime

  • The raise of so-called artificial intelligence has made people believe that computers may some day be congenial with human beings. In the past computers were regarded as effective but soulless and unintelligent assistants to free humans from routine tasks. Computers were supposed to perform time-consuming but mechanical calculations. Today's computers are universal machines that can execute an almost unlimited variety of software. The increase of processing speed allows us to implement complex software which does not seem to have much in common with past computing machinery. In the field of education this awakened the desire to build algorithms which didactically support learners or even emulate human-like tutors. However, despite the apparent complexity of today's software, algorithms are step-by-step procedures which in their core are purely mechanical. So before introducing just another approach for technology-enhanced learning let me reconsider a seemingly naive but fundamental question. Given the nature of how computers work on the machine-level, can we emulate human-like tutors with computers? I believe that we can not because human beings are in possession of abilities which can not be implemented with algorithms due to their mechanical kernel and the formal systems on which algorithms are built. However, there exists a concept with which we can implement a mutual human-machine interaction that enables computers to at least adapt themselves to a learner. The result of this is what we call "adaptive systems". In this work, I present a method based on spatio-temporal data structures and algorithms which enable us to build technically simple but artificially intelligent self-adapting systems. Such systems can be utilized for technology enhanced learning but also for other fields related to human-machine interaction.

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Author:Kevin FuchsGND
Subtitle (English):a Contribution to Human-Centered Adaptivity in E-Learning
Referee:Mutfried HartmannGND, Peter A. HenningGND, Gerd GidionGND
Advisor:Mutfried HartmannGND, Peter A. HenningGND
Document Type:Doctoral Thesis
Year of Completion:2019
Date of first Publication:2019/05/09
Granting Institution:Pädagogische Hochschule Karlsruhe, Fakultät III
Date of final exam:2019/04/10
Release Date:2019/05/09
Tag:Algorithmus; Datenbank; E-Learning; Informatik; Intelligenz; Kognition; Künstliche Intelligenz
Adaptive Systems; Algorithm; Artificial Intelligence; Cognition; Computer Science; E-Learning; Spatio-Temporal Databases
GND Keyword:Künstliche Intelligenz; E-Learning; Mensch-Maschine-Kommunikation; Intelligentes Tutorsystem
Pagenumber:vi, 156
Identifier Union Catalogue:1666818585
Institutes:Fakultät III / Institut für Mathematik und Informatik
DDC class:000 Allgemeines, Informatik, Informationswissenschaft / 000 Allgemeines, Wissenschaft / 004 Informatik
Licence (German):License LogoVeröffentlichungsvertrag für Dissertationen