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Auflistung Künstliche Intelligenz 35(2) - Juni 2021 nach Titel
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- ZeitschriftenartikelA Differentiated Discussion About AI Education K-12(KI - Künstliche Intelligenz: Vol. 35, No. 2, 2021) Steinbauer, Gerald; Kandlhofer, Martin; Chklovski, Tara; Heintz, Fredrik; Koenig, SvenAI Education for K-12 and in particular AI literacy gained huge interest recently due to the significantly influence in daily life, society, and economy. In this paper we discuss this topic of early AI education along four dimensions: (1) formal versus informal education, (2) cooperation of researchers in AI and education, (3) the level of education, and (4) concepts and tools.
- ZeitschriftenartikelAI K–12 Education Service(KI - Künstliche Intelligenz: Vol. 35, No. 2, 2021) Kandlhofer, Martin; Steinbauer, GeraldThis article provides an overview of relevant scientific venues, journals, projects and resources in the context of AI K-12 education.
- ZeitschriftenartikelAnalyzing Teacher Competency with TPACK for K-12 AI Education(KI - Künstliche Intelligenz: Vol. 35, No. 2, 2021) Kim, Seonghun; Jang, Yeonju; Choi, Seongyune; Kim, Woojin; Jung, Heeseok; Kim, Soohwan; Kim, HyeoncheolAs the need for teaching Artificial Intelligence (AI) for K-12 is increasing, discussions on what competencies teacher should have for effective teaching of AI is overlooked. In this work, we determine what teacher competencies are necessary for improving the teaching and learning of AI for K-12 with Technological Pedagogical Content Knowledge (TPACK) framework. First, we identify current AI education resources and investigate the core foundations of AI taught to K-12. Based on the findings, we propose teacher competency for K-12 AI education by analyzing AI curricula and resources using the TPACK framework. We conclude that teachers who teach AI to K-12 students require TPACK to construct, prepare an environment, and facilitate project-based classes that solve problems using AI technologies.
- ZeitschriftenartikelComparing 2 Years of Empowering Families to Solve Real-World Problems with AI(KI - Künstliche Intelligenz: Vol. 35, No. 2, 2021) Chklovski, Tara; Jung, Richard; Anderson, Rebecca; Young, KathrynOver the course of 2 years a global technology education nonprofit engaged ~ 20,000 under-resourced 3rd-8th grade students, parents and educators from 13 countries in a multi-week AI competition. Families worked together with the help of educators to identify meaningful problems in their communities and developed AI-prototypes to address them. Key findings included: (1) Identifying a high level of interest in underserved communities to develop and apply AI-literacy skills; (2) Determining curricular and program implementation elements that enable families to apply AI knowledge and skills to real problems; (3) Identifying effective methods of engaging industry mentors to support participants; (4) Measuring and identifying changes in self-efficacy and ability to apply AI-based tools to real-world problems; (5) Determining effective curricula around value-sensitive design and ethical innovation.
- ZeitschriftenartikelContextualizing AI Education for K-12 Students to Enhance Their Learning of AI Literacy Through Culturally Responsive Approaches(KI - Künstliche Intelligenz: Vol. 35, No. 2, 2021) Eguchi, Amy; Okada, Hiroyuki; Muto, YumikoAI has become ubiquitous in our society, accelerated by the speed of the development of machine learning algorithms and voice and facial recognition technologies used in our everyday lives. Furthermore, AI-enhanced technologies and tools are no strangers in the field of education. It is more evident that it is important to prepare K-12 population of students for their future professions as well as citizens capable of understanding and utilizing AI-enhanced technologies in the future. In response to such needs, the authors started a collaborative project aiming to provide a K-12 AI curriculum for Japanese students. However, the authors soon realized that it is important to contextualize the learning experience for the targeted K-12 students. The paper aims at introducing the idea of contextualizing AI education and learning experience of K-12 students with examples and tips using the work-in-progress version of the contextualized curriculum using culturally responsive approaches to promote the awareness and understanding of AI ethics among middle school students.
- ZeitschriftenartikelCooperative Human Artificial Intelligence(KI - Künstliche Intelligenz: Vol. 35, No. 2, 2021) Ragni, Marco
- ZeitschriftenartikelEarly Introduction of AI in Spanish Middle Schools. A Motivational Study(KI - Künstliche Intelligenz: Vol. 35, No. 2, 2021) Fernández-Martínez, Carmen; Hernán-Losada, Isidoro; Fernández, AlbertoThis paper describes the practical initiative to include Artificial Intelligence (AI) in the Spanish educational system’s curriculum at an early age. This proposal is in line with the current trend of introducing AI in school curricula all over the world. To this end, we propose an Artificial Intelligence workshop for middle schools within the existing subject, Technology, Programming and Robotics. In order to test the suitability of introducing AI at an early age, we conducted the activities at a bilingual middle school in Madrid. As evaluation tools, a quiz and motivational study of the students concerning AI was carried out using Situational Motivational Scale (SIMS) before and after introducing the activities. Responses of 84 students were analysed and the conclusion was reached that it is slightly better to introduce AI at an early age.
- ZeitschriftenartikelEDLRIS: A European Driving License for Robots and Intelligent Systems(KI - Künstliche Intelligenz: Vol. 35, No. 2, 2021) Kandlhofer, Martin; Steinbauer, Gerald; Lassnig, Julia; Menzinger, Manuel; Baumann, Wilfried; Ehardt-Schmiederer, Margit; Bieber, Ronald; Winkler, Thomas; Plomer, Sandra; Strobl-Zuchtriegl, Inge; Miglbauer, Marlene; Ballagi, Aron; Pozna, Claudiu; Miltenyi, Gabor; Alfoldi, Istvan; Szalay, ImreThis article presents a novel educational project aiming at the development and implementation of a professional, standardized, internationally accepted system for training and certifying teachers, school students and young people in Artificial Intelligence (AI) and Robotics. In recent years, AI and Robotics have become major topics with a huge impact not only on our everyday life but also on the working environment. Hence, sound knowledge about principles and concepts of AI and Robotics are key skills for this century. Nonetheless, hardly any systematic approaches exist that focus on teaching principles of intelligent systems at K-12 level, addressing students as well as teachers who act as multipliers. In order to meet this challenge, the European Driving License for Robots and Intelligent Systems—EDLRIS was developed. It is based on a number of previously implemented and evaluated projects and comprises teaching curricula and training modules for AI and Robotics, following a competency-based, blended learning approach. Additionally, a certification system proves peoples’ acquired competencies. After developing the training and certification system, the first 32 trainer and trainee courses with a total of 445 participants have been implemented and evaluated. By applying this innovative approach—a standardized and widely recognized training and certification system for AI and Robotics at K-12 level for both high school teachers and students—we envision to foster AI/Robotics literacy on a broad basis.
- ZeitschriftenartikelEducation in Artificial Intelligence K-12(KI - Künstliche Intelligenz: Vol. 35, No. 2, 2021) Steinbauer, Gerald; Kandlhofer, Martin; Chklovski, Tara; Heintz, Fredrik; Koenig, Sven
- ZeitschriftenartikelLearning by Enhancing Half-Baked AI Projects(KI - Künstliche Intelligenz: Vol. 35, No. 2, 2021) Kahn, Ken; Winters, NiallWe have developed thirty sample artificial intelligence (AI) programs in a form suitable for enhancement by non-expert programmers. The projects are implemented in the Snap! blocks language and can be run in modern web browsers. These projects have been designed to be modifiable by school students and have been iteratively developed with over 100 students. The projects involve speech synthesis, speech and image recognition, natural language processing, and deep machine learning. They illustrate a variety of AI capabilities, concepts, and techniques. The intent is to provide students with hands-on experience with AI programming so they come to understand the possibilities, problems, strengths, and weaknesses of AI today.