Machine learning for middle-schoolers: Children as designers of machine-learning apps

Vartiainen, Henriikka; Suhonen, Jarkko; Jormanainen, Ilkka; Kahila, Juho; Tedre, Matti; Valtonen, Teemu

doi:10.1109/fie44824.2020.9273981

Cited by 24 publications

(15 citation statements)

References 24 publications

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“…Most of the reported teaching units involve in-person and extracurricular activities (Figure 7) that are conducted in lab settings or in workshops or after-school lessons, suggesting that AI education is still not typically included in regular classrooms, even being absent in technology and computing-related courses. However, three teaching units in five of the included studies are applied in regular classrooms [40][41][42][43][44]. One teaching unit in Finland is implemented as a part of regular curricular activities [40][41][42]; one teaching unit in Spain involves AI education in regular middle school classes [44]; and one teaching unit in Denmark critically emphasizes the social impact of AI and is taught in regular social studies classes [43].…”

Section: Settingmentioning

confidence: 99%

“…However, three teaching units in five of the included studies are applied in regular classrooms [40][41][42][43][44]. One teaching unit in Finland is implemented as a part of regular curricular activities [40][41][42]; one teaching unit in Spain involves AI education in regular middle school classes [44]; and one teaching unit in Denmark critically emphasizes the social impact of AI and is taught in regular social studies classes [43]. Five studies involved AI education conducted wholly online or in a blended mode in response to the COVID-19 pandemic [34,36,[45][46][47].…”

Section: Settingmentioning

confidence: 99%

“…In artifact construction, the typical approaches are project-based learning and design-oriented learning. Despite sharing common features with the artifact creation approach, the design-oriented approach, which emphasized design elements, e.g., [40,41,49], merits some discussion. This approach involves open-ended goals, with children being prompted to design their own projects according to their own interests and experience.…”

Section: Experiential Learningmentioning

confidence: 99%

“…Another unplugged example is "Be the machine" [34], a team role-playing game that taught how ML works; in this game, each team member assumed a different role to manually train an ML model. Second, brainstorming involving pictures can be included when a design-oriented approach is used [40,41]. Here, children first visually represented their understanding of AI and what they were going to design.…”

Section: Experiential Learningmentioning

confidence: 99%

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Pedagogical Design of K-12 Artificial Intelligence Education: A Systematic Review

2022

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In response to the growing popularity of artificial intelligence (AI) usage in daily life, AI education is increasingly being provided at the K-12 level, with relevant initiatives being launched worldwide. Examining how these programs have been implemented and summarizing useful experiences is thus imperative. Although prior reviews have described the characteristics of AI education programs in publications, the papers reviewed were mostly nonempirical reports, and the analysis typically only involved a descriptive summary. The current review focuses on the most recent empirical studies on AI teaching programs in K-12 contexts through a systematic search of the Web of Science database from 2010 to 2022. To provide a comprehensive overview of the status of AI teaching and learning (T&L), 32 empirical studies were analyzed both descriptively and thematically. We analyzed (1) the research status, (2) the pedagogical design, and (3) the assessments and outcomes of the AI teaching programs. An increasing number of studies have focused on AI education at the K-12 stage, but most of them have a small sample size. Moreover, the data were mostly collected through interviews and self-reports. We reviewed the pedagogical design of AI teaching programs by using Gerlach and Ely’s pedagogical design model. The results comprehensively delineated current AI teaching programs through nine dimensions: learning theory, pedagogical approach, T&L activities, learning content, scale, teaching resources, prior knowledge prerequisite, aims and objectives, assessment, and learning outcome. The results highlighted the positive impact of current AI teaching programs on students’ motivation, engagement, and attitude. However, we observed a lack of sufficient research objectively measuring students’ knowledge acquisition as learning outcomes. Overall, in this paper, we discussed relevant findings in terms of research trends, learning content, teaching units, characteristics of the pedagogical design, and assessment and evaluation by providing illustrations of exemplary designs; we also discussed future directions for research and practice in AI education in the K-12 context.

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Section: Settingmentioning

confidence: 99%

Section: Settingmentioning

confidence: 99%

Section: Experiential Learningmentioning

confidence: 99%

Section: Experiential Learningmentioning

confidence: 99%

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Pedagogical Design of K-12 Artificial Intelligence Education: A Systematic Review

2022

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“…The fourth industrial revolution (4IR) is here with the cutting edge and emerging technologies in areas such as robotics and it is shaping societies and industries across the world [ 1 , 2 ]. It is therefore about time that belts are tightened and to ensure the present and future generations in Namibia, Africa and the world at large understand and apply the robotics technologies that revolve around the 4IR.…”

Section: Introductionmentioning

confidence: 99%

Co-Learning Computational and Design Thinking Using Educational Robotics: A Case of Primary School Learners in Namibia

Shipepe

Uwu-Khaeb

Villiers³

et al. 2022

Sensors

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In a two-day educational robotics workshop in a Namibian primary boarding school, learners with no programming skills managed to apply both computational and design thinking skills with the aid of educational robotics. Educational robotics has proved to be an area which enhances learning both computational thinking and design thinking. An educational robotics (ER) workshop focusing on Arduino robotics technologies was conducted with primary school learners at Nakayale Private Academy. Observation methods through watching, listening and video recordings were used to observe and analyze how the learners were interacting throughout the workshop. Based on the results, it was concluded that this approach could be applied in classrooms to enable the primary school learners apply computational and design thinking in preparation of becoming the producers and not only the consumers of the 4IR technologies.

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Tangible interfaces in early years’ education: a systematic review

Rodić

Granić

2021

Pers Ubiquit Comput

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Machine learning for middle-schoolers: Children as designers of machine-learning apps

Cited by 24 publications

References 24 publications

Pedagogical Design of K-12 Artificial Intelligence Education: A Systematic Review

Pedagogical Design of K-12 Artificial Intelligence Education: A Systematic Review

Co-Learning Computational and Design Thinking Using Educational Robotics: A Case of Primary School Learners in Namibia

Tangible interfaces in early years’ education: a systematic review

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