Exploring middle school students’ common naive conceptions of Artificial Intelligence concepts, and the evolution of these ideas

Kim, Keun-Jae; Kwon, Kyungbin; Ottenbreit-Leftwich, Anne; Bae, Haesol; Glazewski, Krista

doi:10.1007/s10639-023-11600-3

Cited by 27 publications

(15 citation statements)

References 82 publications

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“…On the other hand, anthropomorphism can also signal a conceptual misconception that draws from limited (conscious) experiences of and narrow focus on AI. Children often name voice assistants like Apple's Siri and Amazon's Alexa as an AI application they are familiar with (Kim et al, 2023;Kreisens & Schultz, 2021;Mertala et al, 2022)a theme that was echoed in our data as well: "There are many types of AIs, for example Apple phones have an AI called Siri" (Student 24*).…”

Section: Anthropomorphic Aimentioning

confidence: 78%

“…Such a view can be further conceptualized as an anthropomorphic misconception, which refers to the attribution of distinctively human-like feelings, mental states, or behavioral characteristics to inanimate objects (Airenti, 2015;Epley et al, 2007). This is a common finding in research on children's (mis)conceptions of AI (Kim et al, 2023;Kreinsen & Schultz, 2021;Mertala et al, 2022) and digital technology in general (Rucker & Pinkwart, 2016;Robertson et al, 2018).…”

Section: Background: Misconceptions (About Ai)mentioning

confidence: 99%

“…On the other hand, anthropomorphic misconception could be a conceptual misconception (Davis, 1997) that arises from limited experience and narrow focus (Harlen & Qualter, 2018) on specific features of AI. Children commonly name personal voice assistants like Siri and Alexa as an example of an AI they are aware or have experience of (Kim et al, 2023;Kreinsen & Schultz, 2021;Mertala et al, 2022). They most likely encounter numerous other AI solutions in their daily life (e.g., smart phones camera) but are not aware of the presence of AI in these applicationsa common finding in studies done with adults (Selwyn et al, 2022;Zhang & Dafoe, 2020).…”

Section: Background: Misconceptions (About Ai)mentioning

confidence: 99%

“…As a result, it has been argued that agentic subjectivity in an age of AI requires AIliteracy (e.g., Lee et al, 2021), one dimension of which is to understand what AI is (Long & Magerko, 2020;Nq et al, 2021). Recently, AI-literacy has been introduced in educational curricula and white papers in various countries (e.g., Su et al, 2022) and scholars have begun to create methods and materials on how children could be taught about AI (e.g., Kim et al, 2023;Lee et al, 2021;Su et al, 2022;Vartiainen et al, 2021). That said, without knowledge about children's initial conceptions, the design of relevant curricula has less than solid footing.…”

Section: Introductionmentioning

confidence: 99%

“…Mertala et al, 2022) and sometimes with no data excerpts that would shed light on the rationales underlying children's thinking (Kreinsen & Schultz, 2021;Ottenbreit-Leftwich et al, 2021). Additionally, some studies were conducted within AI-themed summer camps, and the participating children were reported to have prior experience with programming and were interested in computer science (Kim et al, 2023), which -alongside with a small sample-limits the transferability of the findings.…”

Section: Introductionmentioning

confidence: 99%

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Finnish 5th and 6th graders’ misconceptions about Artificial Intelligence

Mertala¹,

Fagerlund²

2023

Preprint

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Research on children’s initial conceptions of AI is in an emerging state, which, from a constructivist viewpoint, challenges the development of pedagogically sound AI-literacy curricula, methods, and materials. To contribute in resolving this need in the present paper, qualitative survey data from 195 children were analyzed abductively to answer the following three research questions: What kind of misconceptions do Finnish 5th and 6th graders’ have about AI?; 2) How do these misconceptions relate to common misconception types?; and 3) How profound are these misconceptions? As a result, three misconception categories were identified: 1) Non-technological AI, in which AI was conceptualized as peoples’ cognitive processes (factual misconception); 2) Anthropomorphic AI, in which AI was conceptualized as a human-like entity (vernacular, non-scientific, and conceptual misconception); and 3) AI as a machine with a pre-installed intelligence or knowledge (factual misconception). Majority of the children evaluated their AI-knowledge low, which implies that the misconceptions are more superficial than profound. The findings suggest that context-specific linguistic features can contribute to students' AI misconceptions. Implications for future research and AI literacy education are discussed.

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Section: Anthropomorphic Aimentioning

confidence: 78%

Section: Background: Misconceptions (About Ai)mentioning

confidence: 99%

Section: Background: Misconceptions (About Ai)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Finnish 5th and 6th graders’ misconceptions about Artificial Intelligence

Mertala¹,

Fagerlund²

2023

Preprint

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Game-Based Learning Can Enhance Students’ Understanding of AI Ethics

Koskinen,

Lindstedt,

Kiili

2024

Lecture Notes in Computer Science

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Artificial intelligence in compulsory level of education: perspectives from Namibian in-service teachers

Jatileni,

Sanusi,

Olaleye

et al. 2023

Educ Inf Technol

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With the push to integrate Artificial Intelligence (AI) from kindergarten to twelfth-grade levels comes a need for equipped teachers. However, there needs to be more initiative in professional learning opportunities, which demands the required effort to ensure teachers learn the AI content they will be teaching. To design an effective professional development program, understanding teachers' existing knowledge, interest and disposition towards AI is crucial to devise strategies that could best support the teachers. As a result, this study aims to investigate in-service teachers' perspectives of teaching AI in schools from the perspective of planned behavior theory. Using a 7-factor scale of AI Anxiety, AI Readiness, AI Relevance, Attitude towards using AI, AI for Social Good, Confidence in AI and Behavioral Intention. This study sampled 159 in-service teachers in Namibia. The teachers' responses were analyzed with SmartPLS using Structural Equation Modelling and various Multigroup Analysis techniques. This study found that teachers' behavioral intention to teach AI depends on a combination of factors, including the relevance of AI, attitude towards using AI, the use of AI for social good and confidence. Meanwhile, AI Anxiety and readiness could not be linked to the intention to teach AI. We discussed our findings, highlighted the study implication, and suggested future directions.

show abstract

Exploring middle school students’ common naive conceptions of Artificial Intelligence concepts, and the evolution of these ideas

Cited by 27 publications

References 82 publications

Finnish 5th and 6th graders’ misconceptions about Artificial Intelligence

Finnish 5th and 6th graders’ misconceptions about Artificial Intelligence

Game-Based Learning Can Enhance Students’ Understanding of AI Ethics

Artificial intelligence in compulsory level of education: perspectives from Namibian in-service teachers

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