Studies on Effective Educational Programs for Elementary School Students: Using Generative AI to Build Academic Resilience and Self-Regulation Through Soft Skills for Learning

Dear Colleagues,

The quality of early educational experiences is vital to a child’s developmental trajectory. Educational programs play an important role in a child’s academic success and their overall future choices.  In the era of Artificial Intelligence (AI), the opportunities for technology-infused educational programs continue to grow, pertaining to whole-life learning. However, very few studies report on the impact of such efforts on children’s academic success at the elementary grade level. With AI technology as the modus operandi for the future, it is important to examine the role that AI plays in the development of children’s self-regulation and academic resilience as pertains to the teaching and learning of soft skills, attitudes, behaviors, and relationships that children will need to navigate in their academic success. Studies focused on what can be done with AI in elementary grades may shed light on the discourse and scientific dialog to guide future educational programming. Several questions may be explored. For example, what AI tools are developmentally appropriate for children at different grade levels? What is the impact of these tools as they are infused with theory-based practices related to teaching and learning? What are the challenges to the integration of AI-infused educational programs in particular settings (e.g., context)? What is the role of the home environment in the support of such AI-infused educational programming? This is an important discourse as we continue to build on the scientific knowledge for future applications of AI for teaching and learning in elementary school classrooms across the world.

The aim of this Special Issue on “Studies on Effective Educational Programs for Elementary School Students: Using Generative AI to Build Academic Resilience and Self-Regulation Through Soft Skills for Learning” is two-fold; (1) to provide the field of education with a compendium of studies that can serve to advance theories on AI uses for learning that are cross-cultural and relevant across contexts, and (2) to provide schools and educational systems across the world with studies that exemplify best practices for teaching and learning as well as effective programs that are AI-infused. We welcome studies that exemplify theory-based practices using AI (e.g., Vygotsky’s Zone of Proximal Development, Bloom’s Taxonomy, Bandura’s self-efficacy, etc.) with a focus on either intra-psychological factors (e.g., behaviors, attitudes, etc.), inter-psychological factors (e.g., relations, dynamics for learning, etc.), and social factors (e.g., role of the home environment, community, etc.) as contributors that may serve to advance theory and practice among diverse learners. 

Potential topics include, but are not limited to, the following:

1. Studies focused on second language learning, building resilience, and socio-emotional development of children in elementary grades are welcomed. These studies can be part of a project that uses a quantitative design (e.g., experimental, quasi-experimental, etc.), a qualitative design (e.g., case study, ethnography, etc.), or a mixed-methods design to answer research questions of theory, practice, or both relevant to the use of AI in teaching and learning.
2. Studies focused on indigenous communities with a focus on capacity building, culture, and L1 maintenance (e.g., bilingual education) to answer research questions of theory, practice, or both through AI-infused programs in elementary classrooms.
3. Studies focused on the teaching and learning of immigrant children (e.g., newcomers, refugees, asylum seekers, etc.) learning the language of the host country with a focus on either theory, practice, or both in elementary classrooms.
4. Studies focused on classroom practices that address the interplay of culture, identity, socio-emotional development, resilience, and/or the learning environment in teaching and learning among diverse populations in elementary classrooms.
5. Studies focused on either the application(s) of a new or adapted research method/approach or novel AI application(s) of an existing research method to advance theories and/or research practices for elementary-grade levels.
6. Studies focused on the assessment of effective teaching and learning practices that address various validity and/or fairness issues concerning culture, diversity, socio-emotional development, and/or the learning environment as they pertain to the use of AI in elementary classrooms.

Dr. Héctor Rivera
Dr. Eun Hye (Grace) Ko
Guest Editors

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