Enabling the Creation of Intelligent Things: Bringing Artificial Intelligence and Robotics to Schools

Kandlhofer, Martin; Steinbauer, Gerald; Lasnig, Julia P.; Baumann, Wilfried; Plomer, Sandra; Ballagi, Áron; Alföldi, István

doi:10.1109/fie43999.2019.9028537

Cited by 24 publications

(14 citation statements)

References 20 publications

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“…Additionally, an advisory board, comprising representatives of industry, public bodies and educational institutions was established and ensures a broad, international acceptance of the entire program. Finally, a certification system proves trainers' and trainees' understanding of fundamental topics of AI and Robotics [41,49].…”

Section: Discussionmentioning

confidence: 99%

“…In general, the project comprises four stages [41]: Stage 1-foundation: The EDLRIS project consortium is composed of two technical universities in Austria (AT) and Hungary (HU) which have a strong research background in AI and Robotics ensuring sound technological preparation, one university of teacher education (AT) ensuring the sound didactical preparation as well as two computer societies (AT, HU) with long-term experience in conducting computer certifications across Europe. As a first step, the educational needs of society and economy as well as the expected Robotics and AI skills of graduates were assessed by conducting a survey among various stakeholders from educational institutions and industry.…”

Section: Project Approachmentioning

confidence: 99%

“…It turned out that certain teaching methods, and teaching materials/ tools had to be adapted, and the complexity and extend of certain contents had to be reduced in order to impart AI/ Robotics topics in a target group specific manner. Based on the insights of this pilot implementation, the further AI and Robotics modules were developed and adapted accordingly [41]. The thesis of Lassnig [44] describes in detail the development, realization, and evaluation as well as results and conclusions of this first pilot implementation.…”

Section: Pilot Implementationmentioning

confidence: 99%

“…In order to meet these challenges, the European Driving License for Robots and Intelligent Systems (EDLRIS) was developed [39,41,49] 1 . This novel educational project aimed at the development and implementation of a professional, standardized, and internationally accepted system for training and certifying teachers and educators (in this context referred to as trainers) and school students, apprentices and young people (referred to as trainees, learners respectively) in AI and Robotics.…”

Section: Introductionmentioning

confidence: 99%

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EDLRIS: A European Driving License for Robots and Intelligent Systems

Kandlhofer¹,

Steinbauer

Lassnig

et al. 2021

Künstl Intell

Self Cite

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This 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.

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Section: Discussionmentioning

confidence: 99%

Section: Project Approachmentioning

confidence: 99%

Section: Pilot Implementationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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EDLRIS: A European Driving License for Robots and Intelligent Systems

Kandlhofer¹,

Steinbauer

Lassnig

et al. 2021

Künstl Intell

Self Cite

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“…While many effective AI curricula have been made for K-12 [Estevez, Garate, and Graña 2019;Sabuncuoglu 2020;Williams et al 2019], few of them go beyond the concepts involved in machine learning. Examples of such curricula for high-school students are mentioned in [Burgsteiner, Kandlhofer, and Steinbauer 2016;Kandlhofer et al 2019]. In this work, we present a curricular module that teaches a core AI idea, search, with the goal of expanding our curriculum to encompass other crucial AI ideas and techniques that are through students' engagement with authentic problem-solving scenarios.…”

Section: Related Workmentioning

confidence: 99%

Towards an AI-Infused Interdisciplinary Curriculum for Middle-Grade Classrooms

Akram

Yoder

Tatar

et al. 2022

AAAI

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As AI becomes more widely used across a variety of disciplines, it is increasingly important to teach AI concepts to K-12 students in order to prepare them for an AI-driven future workforce. Hence, educators and researchers have been working to develop curricula that make these concepts accessible to K-12 students. We are designing and developing a comprehensive AI curriculum delivered through a series of carefully crafted activities in an adapted \emph{Snap!} environment for middle-grade students. In this work, we lay out the proposed content of our curriculum and present the design, development, and implementation results of the first unit of our curriculum that focuses on teaching the breadth-first search algorithm. The activities in this unit have been revised after being piloted with a single high-school student. These activities were further refined after a group of K-12 teachers examined and critiqued them during a two-week professional development workshop. Our teachers created a lesson plan around the activities and implemented that lesson in a summer workshop with 14 middle school students. Our results demonstrated that our activities were successful in helping many of the students in understanding and implementing the algorithm through block-based programming while extra supplementary material was needed to assist some other students. In this paper, we explain our curriculum and technology, the results of implementing the first unit of our curriculum in a summer camp, and lessons learned for future developments.

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Collaborative construction of artificial intelligence curriculum in primary schools

Dai

Liu

Jian-jun

et al. 2022

J of Engineering Edu

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Background: The recent discussion of introducing artificial intelligence (AI) knowledge to K-12 students, like many engineering and technology education topics, has attracted a wide range of stakeholders and resources for school curriculum development. While teachers often have to directly interact with external stakeholders out of the public schooling system, few studies have scrutinized their negotiation process, especially teachers' responses to external influences, in such complex environments. Purpose: Guided by an integrated theoretical framework of social constructionism, this research examined the process of how a teacher-initiated AI curriculum was constructed with external influences. The research focused on teachers' perspectives and responses in mediating external influences into local schools and classrooms.Methods: A 3-year ethnographic study was conducted in relation to an AI curriculum project among 23 Computer Science (CS) teachers from primary schools. Data collected from ethnographic observation, teacher interviews, and artifacts, were analyzed using open coding and triangulation rooted in the ethnographic, interpretivist approach.Results: Three sets of external influences were found salient for teachers' curriculum decisions, including the orientation of state-level educational policies, AI faculty at a partner university, and students' media and technology environments. The teachers' situational logics and strategic actions were reconstructed with thick descriptions to uncover how they navigated and negotiated the external influences to fulfill local challenges and expectations in classrooms and schools. Conclusions:The ethnographic study uncovered the dynamic and multifaceted negotiation involved in the collaborative curriculum development, and offers insights to inform policymaking, teacher education, and student support in engineering education.

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Enabling the Creation of Intelligent Things: Bringing Artificial Intelligence and Robotics to Schools

Cited by 24 publications

References 20 publications

EDLRIS: A European Driving License for Robots and Intelligent Systems

EDLRIS: A European Driving License for Robots and Intelligent Systems

Towards an AI-Infused Interdisciplinary Curriculum for Middle-Grade Classrooms

Collaborative construction of artificial intelligence curriculum in primary schools

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