Secondary school students’ intentions to learn AI: testing moderation effects of readiness, social good and optimism

Chai, Ching Sing; Teo, Timothy; Huang, Fang; Chiu, Thomas K. F.; wei, Wang Xing

doi:10.1007/s11423-022-10111-1

Cited by 31 publications

(12 citation statements)

References 58 publications

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“…Previous studies have revealed that perceived Usefulness influences school teachers' intention to accept new technology (Antonietti et al, 2022;Bin et al, 2020;Xianhan et al, 2022). Concerning AI, even though limited, studies have also shown that perceived Usefulness could predict health specialists' intention to learn to use AI , learners' intention to learn AI (Chai et al, 2022), and teachers' intention to teach AI (Ayanwale et al, 2022). Based on these, we intend to validate previous findings and thus hypothesize that: H2: Perceived Usefulness will significantly influence behavioral intention to teach AI.…”

Section: Perceived Usefulnessmentioning

confidence: 62%

Investigating the moderating effects of social good and confidence on teachers' intention to prepare school students for artificial intelligence education

Sanusi,

Ayanwale,

Chiu

2023

Educ Inf Technol

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Artificial Intelligence (AI) has triggered profound reforms across industries, including education. These developments necessitate the inclusion of AI as a subject in K-12 classrooms. However, the need for students to learn AI demands that educators pay increasing attention, believe in its relevance and intend to promote it among their students and colleagues. This paper aimed to explore teachers' perceptions of and behavioral intention to teach AI. We specifically considered the association of AI anxiety, perceived usefulness, attitude towards AI, AI relevance, AI readiness, and behavioral intention factors. This research further aims to examine the moderator effect of AI for social good and confidence on the relationship in our hypothesized research model. To address this purpose, a quantitative methodology with the use of structural equation modeling was utilized. Data were retrieved through an online questionnaire from 320 lower and upper secondary school in-service teachers, mostly in STEM-related fields. Our findings reveal that teacher perceptions of AI for social good and confidence will affect most relationships in the model. Teacher professional programs should include the benefits and risks of AI and good practice sharing.

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Section: Perceived Usefulnessmentioning

confidence: 62%

Investigating the moderating effects of social good and confidence on teachers' intention to prepare school students for artificial intelligence education

Sanusi,

Ayanwale,

Chiu

2023

Educ Inf Technol

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“…As in many other sectors, artificial intelligence has been the subject of analysis in education. It was examined from different perspectives, whereas the attention was often dedicated to students' intention to learn AI [8,[31][32][33][34], as well as studies in which the emphasis was on teachers' intention to teach or prepare students for AI [35,36].…”

Section: Students' Intention Toward Aimentioning

confidence: 99%

“…AI can be defined as "systems that display intelligent behavior by analyzing their environment and taking action-with some degree of autonomy-to achieve specific goals" [7] (p. 1). It is being implemented in various organizations and sectors with the aim of optimizing their effectiveness and efficiency [8].…”

Section: Introductionmentioning

confidence: 99%

Students’ Intention toward Artificial Intelligence in the Context of Digital Transformation

Milicevic,

Kalas,

Djokic

et al. 2024

Sustainability

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The analysis of students’ attitudes and perceptions represents a basis for enhancing different types of activities, including teaching, learning, assessment, etc. Emphasis might be placed on the implementation of modern procedures and technologies, which play an important role in the process of digital transformation. Among them is artificial intelligence—a technology that has already been found to be applicable in various sectors. When it comes to education, several AI-based tools and platforms can be used by students and teachers. Besides offering customized learning experiences, AI may play a significant part in establishing the concept of sustainability, especially when concerning the achievement of sustainable development goal 4. This paper investigates students’ intention to use artificial intelligence in education, taking three predictors from the UTAUT model and AI awareness as the moderator. The analysis included students from the Autonomous Province of Vojvodina, Republic of Serbia. For the purpose of the research, the partial least squares structural equation modeling (PLS-SEM) method was applied. Hereby, two models (without and with a moderator) were tested to examine the main and moderating effects, respectively. Regarding the results, while interaction terms were non-significant, the impacts of performance expectancy, effort expectancy, and social influence on behavioral intention were significant and positive.

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“…Student-focused studies explore and analyze attitudes and previous knowledge to make didactic proposals adapted to the learner. Some of them measure their intention and interest in learning AI (Bollin et al, 2020;Chai et al, 2021Chai et al, , 2020aChai et al, , 2020bGao & Wang, 2019;Harris et al, 2004;Sing, et al, 2022;Suh & Ahn, 2022), whereas others discuss their views on the integration of technologies in the education system (Sorensen & Koefoed, 2018) and on teaching-learning support tools in AI (Holstein et al, 2019).…”

Section: Student Perspective On Ai Literacymentioning

confidence: 99%

AI literacy in K-12: a systematic literature review

et al. 2023

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The successful irruption of AI-based technology in our daily lives has led to a growing educational, social, and political interest in training citizens in AI. Education systems now need to train students at the K-12 level to live in a society where they must interact with AI. Thus, AI literacy is a pedagogical and cognitive challenge at the K-12 level. This study aimed to understand how AI is being integrated into K-12 education worldwide. We conducted a search process following the systematic literature review method using Scopus. 179 documents were reviewed, and two broad groups of AI literacy approaches were identified, namely learning experience and theoretical perspective. The first group covered experiences in learning technical, conceptual and applied skills in a particular domain of interest. The second group revealed that significant efforts are being made to design models that frame AI literacy proposals. There were hardly any experiences that assessed whether students understood AI concepts after the learning experience. Little attention has been paid to the undesirable consequences of an indiscriminate and insufficiently thought-out application of AI. A competency framework is required to guide the didactic proposals designed by educational institutions and define a curriculum reflecting the sequence and academic continuity, which should be modular, personalized and adjusted to the conditions of the schools. Finally, AI literacy can be leveraged to enhance the learning of disciplinary core subjects by integrating AI into the teaching process of those subjects, provided the curriculum is co-designed with teachers.

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Secondary school students’ intentions to learn AI: testing moderation effects of readiness, social good and optimism

Cited by 31 publications

References 58 publications

Investigating the moderating effects of social good and confidence on teachers' intention to prepare school students for artificial intelligence education

Investigating the moderating effects of social good and confidence on teachers' intention to prepare school students for artificial intelligence education

Students’ Intention toward Artificial Intelligence in the Context of Digital Transformation

AI literacy in K-12: a systematic literature review

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