Early Introduction of AI in Spanish Middle Schools. A Motivational Study

Fernández-Martínez, Carmen; Hernán-Losada, Isidoro; Fernández, Alberto

doi:10.1007/s13218-021-00735-5

Cited by 18 publications

(9 citation statements)

References 6 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 addition, two studies mentioned that students' general abilities, such as higher-order thinking [55] and collaboration skills [43], are improved. Notably, there are also potential barriers to learning AI, such as students being easily distracted [67] or relatively low motivation [44]. Table 5.…”

Section: Assessments and Learning Outcomes Of The Reported Teaching U...mentioning

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: Assessments and Learning Outcomes Of The Reported Teaching U...mentioning

confidence: 99%

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

2022

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“…According to Rus et al, ITS uses evidence-based or empirical evidence-backed practises, such as the extensive use of cognition and learning models, to achieve optimal learning for students. In fact, programmes like DeepTutor and AutoTutor put the learner at the centre of the process, allowing for the creation of content that is tailored to the individual's specific abilities and interests (Fernández-Martínez et al, 2021;Popenici & Kerr, 2017). Artificial Intelligence (AI) has improved instructional quality and effectiveness, as Pokrivcakova argues, because modern systems are technologybased adaptive systems, the materials or content presented are determined by the learners' needs, which ensures an optimal learning experience.…”

Section: Instructionmentioning

confidence: 99%

The Impact of AI on Teaching and Learning in Higher Education Technology

2022

JHETP

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Thanks to AI, students may now study whenever and wherever they like. Personalized feedback on assignments, quizzes, and other assessments can be generated using AI algorithms and utilised as a teaching tool to help students succeed. This study examined the impact of artificial intelligence in higher education teaching and learning. This study focuses on the impact of new technologies on student learning and educational institutions. With the rapid adoption of new technologies in higher education, as well as recent technological advancements, it is possible to forecast the future of higher education in a world where artificial intelligence is ubiquitous. Administration, student support, teaching, and learning can all benefit from the use of these technologies; we identify some challenges that higher education institutions and students may face, and we consider potential research directions.

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“…Due to its widespread influence, the incorporation of AI in K-12 education has been observed in several countries, such as China (Jing, 2018), Singapore (AI-Singapore, 2018), South Korea (Walch, 2018), India (Central Board of Secondary Education. Ministry of Education, Government of Indian, 2019), European Union (Ilkka, 2018), Hong Kong (Curriculum Development Council, Hong Kong, 2020), Japan (Eguchi et al, 2021), and Spain (Fernández-Martínez et al, 2021). Eguchi et al (2021) admitted that today's learners have been growing up with AI assistants or AI-assisted smart devices in their homes, such as Google enhanced smart speaker, and devices equipped with Siri or Alexa.…”

Section: Introductionmentioning

confidence: 99%

Potential Risks of Artificial Intelligence Integration into School Education: A Systematic Review

Karan,

Angadi

2023

Bulletin of Science, Technology & Society

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Currently, artificial intelligence (AI) is being rapidly incorporated into K-12 education because of its increasing social and pedagogical importance. The integration of AI in K-12 education is likely to have a profound influence on the lives and learning styles of learners, teaching approaches of teachers, and the whole mechanism of school management systems. As AI technologies are new to K-12 school curriculum, the research on AI for K-12 classrooms is under explored. In this study, the current state of AI integration in school education and risks associated with it were explored. The study using a systematic review method attempted to explore the findings, observations, and results of recent research regarding the possible risk factors of AI integration in K-12 education. At initial search using predefined key terms, 390 articles were recorded. Using inclusion and exclusion criteria, 71 articles covering 34 journals and other publications were selected for final analysis. Selected 71 articles reported that AI innovation incorporation into K-12 education is associated with certain risks and challenges. Through a systematic review technique, we categorized them into major 6 risk areas namely Privacy and Autonomy Risks, AI Biases, Accuracy and Functional Risks, Deepfakes and FATE Risks, Social Knowledge and Skill Building Risks, and Risk in Shifting Teacher's Role. The study also explored these risk areas to provide an overview of how these are connected with teaching and learning process of K-12 education.

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Early Introduction of AI in Spanish Middle Schools. A Motivational Study

Cited by 18 publications

References 6 publications

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

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

The Impact of AI on Teaching and Learning in Higher Education Technology

Potential Risks of Artificial Intelligence Integration into School Education: A Systematic Review

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