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Fuchs, K. (2020). Cognitive Spacetime. eleed, Iss. 13. (urn:nbn:de:0009-5-50181)
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%0 Journal Article %T Cognitive Spacetime %A Fuchs, Kevin %J eleed %D 2020 %V 13 %N 1 %@ 1860-7470 %F fuchs2020 %X 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. %L 370 %K Algorithmus %K Datenbank %K Informatik %K Intelligentes Tutorsystem %K Intelligenz %K Kognition %K Künstliche Intelligenz %K Mensch-Maschine-Kommunikation %K adaptive Systems %K algorithm %K artificial intelligence %K cognition %K computer science %K e-learning %K spatio-temporal databases %U http://nbn-resolving.de/urn:nbn:de:0009-5-50181Download
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@Article{fuchs2020,
author = "Fuchs, Kevin",
title = "Cognitive Spacetime",
journal = "eleed",
year = "2020",
volume = "13",
number = "1",
keywords = "Algorithmus; Datenbank; Informatik; Intelligentes Tutorsystem; Intelligenz; Kognition; K{\"u}nstliche Intelligenz; Mensch-Maschine-Kommunikation; adaptive Systems; algorithm; artificial intelligence; cognition; computer science; e-learning; spatio-temporal databases",
abstract = "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.",
issn = "1860-7470",
url = "http://nbn-resolving.de/urn:nbn:de:0009-5-50181"
}
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TY - JOUR AU - Fuchs, Kevin PY - 2020 DA - 2020// TI - Cognitive Spacetime JO - eleed VL - 13 IS - 1 KW - Algorithmus KW - Datenbank KW - Informatik KW - Intelligentes Tutorsystem KW - Intelligenz KW - Kognition KW - Künstliche Intelligenz KW - Mensch-Maschine-Kommunikation KW - adaptive Systems KW - algorithm KW - artificial intelligence KW - cognition KW - computer science KW - e-learning KW - spatio-temporal databases AB - 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. SN - 1860-7470 UR - http://nbn-resolving.de/urn:nbn:de:0009-5-50181 ID - fuchs2020 ER -Download
Wordbib
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ISI
PT Journal AU Fuchs, K TI Cognitive Spacetime SO eleed PY 2020 VL 13 IS 1 DE Algorithmus; Datenbank; Informatik; Intelligentes Tutorsystem; Intelligenz; Kognition; Künstliche Intelligenz; Mensch-Maschine-Kommunikation; adaptive Systems; algorithm; artificial intelligence; cognition; computer science; e-learning; spatio-temporal databases AB 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. ERDownload
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<abstract>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.</abstract>
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Full Metadata
| Bibliographic Citation | e-learning and education, Iss. 13 |
|---|---|
| Title |
Cognitive Spacetime (eng) |
| Author | Kevin Fuchs |
| Language | eng |
| Abstract | 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. Das Aufkommen sogenannter künstlicher Intelligenz hat Menschen glauben lassen, dass uns Computer eines Tages geistig ebenbürtig sein könnten. In der Vergangenheit sah man in Computern vorrangig effektive, aber letztlich unintelligente, seelenlose Helfer, deren Zweck allein darin lag, Menschen von lästigen Routineaufgaben zu befreien. Computer sollten lediglich zeitraubende, mechanische Berechnungen durchführen. Heutige Computer sind universelle Maschinen, die im Stande sind, eine beinahe unbegrenzte Vielfalt an Software auszuführen. Der stete Zuwachs an Verarbeitungsgeschwindigkeit erlaubt uns die Implementierung überaus komplexer Systeme, die augenscheinlich wenig mit früheren Computersystemen gemein haben. Im Bildungsbereich erweckte dies den Wunsch nach Algorithmen, die den Lernenden didaktisch unterstützen oder sogar in menschenähnlicher Weise einen Lehrer emulieren. Trotz der scheinbaren Komplexität heutiger Software sind und bleiben Algorithmen jedoch im Kern rein mechanische Prozeduren. Bevor ich also wiederum einen weiteren Ansatz für technologiegestütztes Lernen einführe, möchte ich eine scheinbar naive, aber grundlegende Fragestellung noch einmal neu denken: können wir angesichts der Art und Weise, wie Computer auf der maschinellen Ebene arbeiten, einen menschlichen Lehrer nachahmen? Menschen verfügen über Fähigkeiten, die mit Algorithmen, beziehungsweise mit den formalen Systemen, innerhalb derer Algorithmen operieren, nicht umsetzbar sind. Dennoch ist die Implementierung einer reziproken Mensch-Maschine-Interaktion dergestalt möglich, dass eine Maschine sich einem Lernenden hinreichend anzupassen vermag. Im Ergebnis erhalten wir das, was wir „adaptive Systeme“ nennen. In der vorliegenden Arbeit stelle ich eine auf raumzeitlichen Datenstrukturen und Algorithmen basierende Methode vor, die es uns ermöglicht, technisch einfache, aber dennoch künstlich intelligente, sich selbst adaptierende Systeme zu entwickeln, welche sowohl für technologiegestütztes Lernen, als auch für andere Bereiche der Mensch-Maschine-Interaktion eingesetzt werden können. |
| Subject | Algorithmus, Datenbank, Informatik, Intelligentes Tutorsystem, Intelligenz, Kognition, Künstliche Intelligenz, Mensch-Maschine-Kommunikation, adaptive Systems, algorithm, artificial intelligence, cognition, computer science, e-learning, spatio-temporal databases |
| Classified Subjects |
|
| DDC | 370 |
| Rights | fDPPL |
| URN: | urn:nbn:de:0009-5-50181 |
