Abstract
The teaching of artificial intelligence (AI) topics in school curricula is an important global strategic initiative in educating the next generation. As AI technologies are new to K-12 schools, there is a lack of studies that inform schools’ teachers about AI curriculum design. How to prepare and engage teachers, and which approaches are suitable for planning the curriculum for sustainable development, are unclear. Therefore, this case study aimed to explore the views of teachers with and without AI teaching experience on key considerations for the preparation, implementation, and continuous refinement of a formal AI curriculum for K-12 schools. It drew on the self-determination theory (SDT) and four basic curriculum planning approaches—content, product, process, and praxis—as theoretical frameworks to explain the research problems and findings. We conducted semi-structured interviews with 24 teachers—twelve with and twelve without experience in teaching AI—and used thematic analysis to analyze the interview data. Our findings revealed that genuine curriculum creation should encompass all four forms of a curriculum design approach that are coordinated by teachers’ self-determination to be orchestrators of student learning experiences. This study also proposed a curriculum development cycle for teachers and curriculum officers.
Keywords
artificial intelligence education, curriculum planning, curriculum design, teacher education, self-determination theory, teacher belief, K-12 education
Introduction
Artificial intelligence (AI) has emerged as a ubiquitous form of technology in our everyday lives. Many educators and education authorities have begun considering including AI topics in K-12 curricula to prepare school students to learn about these emerging technologies. Such initiatives inevitably involve curriculum planning. As AI is an emerging field undergoing rapid changes, and considering that teachers are most likely not familiar with its content, understanding how existing theoretical frameworks of curriculum planning and teachers’ perspective can be invoked to respond to the situation would be of interest to the refinement of curriculum theories and teacher development. While innovators among teachers are creating AI curricula, a recent review of AI in education has highlighted the lack of study on teachers’ perspectives [1]. It is important for researchers to document the teachers’ perspective, as it undergirds their sense-making of the emerging AI technology for curriculum planning [2]. This study thus attempts to understand the teachers’ choice of action in planning AI curricula and the personal reasoning behind the teachers’ effort.
On the sociopolitical front, both China and the United States announced relevant AI education initiatives in 2018. The Ministry of Education of China announced the “Artificial Intelligence Innovation Action Plan for Institutions of Higher Education” to encourage and support young people to participate in AI work, and school teachers to teach their students AI knowledge. In response, the Association for the Advancement of Artificial Intelligence (AAAI) and the Computer Science Teachers Association (CSTA) formed a joint working group to develop national guidelines for the teaching of AI to K-12 students. These projects aimed to contribute to the development of AI-related school curricula. Including AI topics in school curriculum is an important global strategic initiative in educating the next generation [3]. AI education in schools not only helps children understand what the AI technologies are and how they work, but it also inspires future AI researchers, ethical designers and software developers [3]. However, curriculum design for K-12 schools is more complex compared to higher education. It involves considerations of how the new initiative or policy translates into practice, and considerable variation in implementation can be expected from school to school [4].
Schools often have fixed and inflexible timetables and subjects, and limited resources with regard to classroom equipment. In addition, while AI is an established field in higher education, school teachers are not formally trained for AI education. Integrating technology is still currently viewed as problematic and it is important to understand teachers’ value-driven and feasibility assessment processes embedded within dynamically evolving school environments [2]. Building on their work, integrating AI has unique challenges in that it is totally new to schools, with the AI content not defined and the teachers having to figure out where it fits in a crowded curriculum. Therefore, designing AI-related school curricula is very challenging for school teachers, school leaders, education officers, policy-makers, and AI experts, and it is important to raise the challenges teachers face to facilitate curricula planning work.
Most recent studies related to AI curricula focused on what content knowledge and skills should be included [5] and what AI tools are more effective for student learning [6]. These studies viewed teaching as the transmission of knowledge and used the syllabus and assessment methods to plan their curriculum by identifying appropriate content and effective delivery methods and enhancing students’ competencies. They focused on predefined content and outcomes, rather than how teachers, students, and knowledge interact [7]. In other words, the current approach to AI curriculum planning may neglect teachers’ perspective and sense-making, and also students’ agency in their learning [7,8]. Accordingly, these recent AI curriculum studies do not inform us well about the overall design of a formal curriculum and its planning approach for this emerging subject. Besides, school curriculum planning is fundamentally a political process [4], one which involves arguments about questions of value. Therefore, teachers’ beliefs and views will decide what the curriculum looks like [9]. Teachers’ intrinsic motivation is critical in the planning of curricula for sustainability [10] because AI curriculum design requires an iterative development cycle. This motivational process can be explained by the self-determination theory (SDT), which provides a theoretical framework to explain the teachers’ fundamental psychological needs—autonomy, relatedness, and competence—for educational innovation [11,12].
As such, we used a qualitative study to explore the views of teachers with (AI teachers) and without (non-AI Teachers) AI teaching experience on key considerations for the design, implementation, and revision of a formal AI curriculum for K-12 schools. AI teachers’ views were sought on developing, implementing, and redeveloping the school-based curriculum, and non-AI and AI teachers’ views were sought on teachers’ preparation issues (e.g., teacher feelings and perceived needs). In others words, this study is concerned with (1) curriculum preparation—how to prepare and motivate teachers to design and teach the curriculum, (2) curriculum development—what to include in content knowledge and what effective learning designs should be adopted and (3) curriculum renewal—how to motivate teachers and what teachers need to renew the curriculum. Situating the case on the nexus of theory and practice, we attempt to use the four basic curriculum planning approaches and the self-determination theory (SDT) to explain the research problem and findings in this paper.
Limitations and Future Directions
There are four limitations in this study. First, this study investigated AI perception among experienced and inexperienced teachers; hence, we need more work to understand how best to support teachers as they attempt to plan and design AI teaching and integrate AI technologies into their practice. An examination of the confidence levels of these two groups of teachers within their classrooms would yield useful data for future professional development. The second limitation is that the study did not evaluate the effectiveness of the AI school curriculum. Research into effective curricula needs to be conducted. Effective ways to enhance students’ AI identity and interest would yield more effective AI learning [36]. Students with stronger identity and interest are more likely to have greater persistence, which will be reflected in how successful and for how long they pursue AI studies and careers [36]. Therefore, we suggest that more studies should be conducted on what content knowledge should be included and which instructional design should be adopted for enhancing AI identity and interest. Thirdly, while this study proposes a new curriculum development cycle to support the promotion of AI K-12 education, more studies are needed to validate, enrich, and refine the cycle. We suggest that this study could also be extended by additional studies on other emerging subjects and curriculum innovations. Finally, given the richness of lived experience, this study portrayed two important themes based on the data we obtained. For the participants we interviewed, there are indications of theoretical saturation, but the research was conducted in a case setting. Future research may explicate more nuanced understandings about teachers’ experiences in designing curricula for AI, especially from other cultural settings.
About KSRA
The Kavian Scientific Research Association (KSRA) is a non-profit research organization to provide research / educational services in December 2013. The members of the community had formed a virtual group on the Viber social network. The core of the Kavian Scientific Association was formed with these members as founders. These individuals, led by Professor Siavosh Kaviani, decided to launch a scientific / research association with an emphasis on education.
KSRA research association, as a non-profit research firm, is committed to providing research services in the field of knowledge. The main beneficiaries of this association are public or private knowledge-based companies, students, researchers, researchers, professors, universities, and industrial and semi-industrial centers around the world.
Our main services Based on Education for all Spectrum people in the world. We want to make an integration between researches and educations. We believe education is the main right of Human beings. So our services should be concentrated on inclusive education.
The KSRA team partners with local under-served communities around the world to improve the access to and quality of knowledge based on education, amplify and augment learning programs where they exist, and create new opportunities for e-learning where traditional education systems are lacking or non-existent.
FULL Paper PDF file:
Sustainable Curriculum Planning for Artificial Intelligence Education: A Self-determination Theory Perspective
Bibliography
author
Year
2020
Title
Sustainable Curriculum Planning for Artificial Intelligence Education: A Self-determination Theory Perspective
Publish in
Sustainability 2020, 12, 5568
Doi
https://doi.org/10.3390/su12145568
PDF reference and original file: Click here
Nasim Gazerani was born in 1983 in Arak. She holds a Master's degree in Software Engineering from UM University of Malaysia.
Professor Siavosh Kaviani was born in 1961 in Tehran. He had a professorship. He holds a Ph.D. in Software Engineering from the QL University of Software Development Methodology and an honorary Ph.D. from the University of Chelsea.
Somayeh Nosrati was born in 1982 in Tehran. She holds a Master's degree in artificial intelligence from Khatam University of Tehran.
