Universität zu Köln

Olari, Viktoriya ORCID: 0000-0002-5113-6624 (2020). Introducing Machine Learning Using Robots – Design and Integration of Simple Neural Networks and the Q-learning Algorithm in the Robot Simulation Environment of Open Roberta Lab, Accompanied by the Development, Testing, and Evaluation of Complementary Teaching Materials. Masters thesis, Universität zu Köln.

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Abstract

The following master’s thesis provides an approach to introducing machine learning to students using the block-based programming language NEPO in combination with educational robotics. The target group of the research study are students from primary to high school, representing beginners without any previous knowledge of machine learning. After analysing the guidelines and methods for the introduction of machine learning in schools, as well as concrete proposals for artificial intelligence school curricula, the author identified a large discrepancy between the requirements for introducing the topics of supervised, unsupervised, and reinforcement learning in schools and the solutions currently available on the educational landscape to do so. Most of the approaches which are currently available either remain a black box or are inaccessible to young students. In order to close this discrepancy, and following the ideas of constructionism, the author developed three approaches to introduce machine learning using robots: (1) The Neural Network Playground which allows the user to experiment with simple neural networks, (2) The Q-learning Playground which enables the student to tinker with the Q-learning algorithm, (3) An unplugged activity introducing the k-means algorithm that makes the unsupervised learning tangible. The author accompanied all approaches with a curriculum and a series of learning materials. She then conducted and evaluated a user study with 24 children from primary, middle, and high school. The results underline the practical feasibility of the approaches: the children of all age groups perceived the topics as interesting and ranging from very easy to moderately hard to grasp. Thus, the research study proposes a solid concept for the introduction of machine learning to beginners which fundamentally differs from the currently available approaches and enriches the educational landscape.

Item Type:	Thesis (Masters thesis)
Translated title:	Title Language Einführung in das maschinelle Lernen mit Robotern - Entwurf und Integration einfacher neuronaler Netze und des Q-Learning-Algorithmus in die Robotersimulationsumgebung von Open Roberta Lab, begleitet von der Entwicklung, Erprobung und Evaluation ergänzender Lehrmaterialien German Introduction de l'apprentissage automatique à l'aide de robots - Conception et intégration de réseaux neuronaux simples et de l'algorithme d'apprentissage en ligne dans l'environnement de simulation de robots d'Open Roberta Lab, accompagnée du développement, de l'essai et de l'évaluation de matériels pédagogiques complémentaires French Introducción al aprendizaje automático mediante robots - Diseño e integración de redes neuronales simples y el algoritmo Q-learning en el entorno de simulación de robots de Open Roberta Lab, acompañado del desarrollo, prueba y evaluación de materiales didácticos complementarios Spanish Introduzione all'apprendimento automatico tramite robot - Progettazione e integrazione di reti neurali semplici e dell'algoritmo di apprendimento Q nell'ambiente di simulazione dei robot dell'Open Roberta Lab, accompagnato da sviluppo, test e valutazione di materiali didattici complementari Italian Представление машинного обучения с использованием роботов - проектирование и интеграция простых нейронных сетей и алгоритма Q-обучения в среду моделирования роботов Open Roberta Lab, в сопровождении разработки, тестирования и оценки дополнительных учебных материалов Russian 介绍使用机器人进行机器学习--简单神经网络和Q-learning算法在开放Roberta实验室机器人仿真环境中的设计和集成，并伴随着配套教材的开发、测试和评价。 Chinese ロボットを用いた機械学習の導入 - オープンロバータラボのロボットシミュレーション環境における単純なニューラルネットワークとQ-learningアルゴリズムの設計と統合、補完教材の開発・テスト・評価を伴う Japanese
Creators:	Creators Email ORCID ORCID Put Code Olari, Viktoriya viktoriya.olari@gmail.com orcid.org/0000-0002-5113-6624 UNSPECIFIED
URN:	urn:nbn:de:hbz:38-307273
Date:	13 October 2020
Language:	English
Faculty:	Faculty of Arts and Humanities
Divisions:	Faculty of Arts and Humanities > Fächergruppe 1: Kunstgeschichte, Musikwissenschaft, Medienkultur und Theater, Linguistik, IDH > Institut für Digital Humanities (IDH)
Subjects:	Data processing Computer science Education Technology (Applied sciences)
Uncontrolled Keywords:	Keywords Language AI Education; AI Teaching; AI Learning; ML Education; ML Teaching; Artificial Intelligence; Machine Learning; Robotics; Playful Learning; Neural Networks; Q-Learning; Clustering; K-means Algorithm; Open Roberta Lab; Constructionism; English KI Bildung; KI Lehre; KI Lernen; Künstliche Intelligenz; Maschinelles Lernen; Robotik; Spielerisches Lernen; Neuronale Netze; Q-Learning; Clustering; K-means Algorithmus; Open Roberta Lab; Konstruktivismus; German Apprentissage de l'IA; Enseignement de l'IA; Intelligence artificielle; Apprentissage machine; Robotique; Réseaux neuronaux; Q-Learning; Apprentissage ludique; Clustering; Algorithme K-means; Open Roberta Lab; Constructionisme; French Обучение ИИ; Преподавание искусственного интеллекта; Игровое обучение; Обучение ИИ; Искусственный интеллект; Машинное обучение; Робототехника; Нейронные сети; Q-обучение; Кластеризация; Алгоритм К-средних; Open Roberta Lab; Конструктивизм; Russian AI教育; AI教育; AI学習; ML教育; ML教育; 人工知能; 機械学習; ロボット工学; ニューラルネットワーク; Qラーニング; 遊び心のある学習; クラスタリング; Kmeansアルゴリズム; オープンロバータラボ; コンストラクショニズム Japanese AI教育;AI教学;AI学习;ML教育;ML教学;人工智能;机器学习;机器人;神经网络;Q-Learning;玩乐学习;聚类;K-means算法;开放罗伯塔实验室;构造主义。 Chinese
Date of oral exam:	2020
Referee:	Name Academic Title Eide, Øyvind Prof. Dr.
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/30727