Diana Rahmasari
State University of Surabaya

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Preparing Future-Ready Teachers through Artificial Intelligence Literacy and Sustainability Competencies: A Systematic Literature Review Annas Solihin; Suryanti; Neni Mariana; Wiryanto; Ganes Gunansyah; Ika Rahmawati; Diana Rahmasari
Proceeding International Conference on Education Volume 04, Agustus Tahun 2026: International Conference on Education
Publisher : Fakultas Tarbiyah dan Ilmu Keguruan, Universitas Islam Negeri (UIN) Syekh Wasil Kediri, Indonesia

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Abstract

The rapid integration of artificial intelligence (AI) into education, alongside global demands for sustainable development, has created an urgent need for teacher education programs to cultivate both AI literacy and sustainability competencies among future teachers. This study aims to systematically review and synthesize existing literature on the integration of AI literacy and sustainability competencies in teacher education. A systematic literature review guided by the PRISMA 2020 Statement was conducted across Scopus, Web of Science, ERIC, ScienceDirect, SpringerLink, Taylor and Francis, and Wiley Online Library, using a structured search string combining terms related to AI literacy, teacher education, and sustainability competencies. Twenty peer-reviewed studies published between 2018 and 2026 met the inclusion criteria and were analyzed through descriptive, thematic, and narrative synthesis. The results indicate a marked increase in AI literacy research following the widespread adoption of generative AI, a comparatively slower growth pattern in sustainability competency research, and very limited integration between the two domains within existing teacher education literature. The review proposes a conceptual framework in which AI literacy strengthens digital pedagogical competence, which in turn supports the development of sustainability competencies necessary for future-ready teachers. These findings offer theoretical grounding for bridging the UNESCO AI Competency Framework for Teachers with the GreenComp Framework and provide practical direction for curriculum design in teacher education institutions.
Neurocognitive Foundations of Abstract Reasoning in Middle Childhood Juvinália Antónia de Fátima Ribeiro; Devinalia da Silva; Salvador Magno Ximenes; Mochamad Nursalim; Diana Rahmasari; Annas Solihin
Jurnal Review Pendidikan Dasar : Jurnal Kajian Pendidikan dan Hasil Penelitian Vol. 12 No. 3 (2026): Vol. 12 No. 3 Oktober 2026
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jrpd.v12n3.p347-366

Abstract

Limited research has jointly examined how error monitoring, multidimensional inhibition, white matter pathways, and daily biological rhythms relate to abstract reasoning during middle childhood, the period in which children aged 7 to 12 years move from concrete to abstract thinking. This systematic review followed PRISMA 2020, searched Scopus, Web of Science, and PubMed between January and March 2026 for neuroscience and cognitive studies published from 2020 to 2026, identified 485 records, and appraised 23 included studies with the Joanna Briggs Institute checklists. Narrative synthesis produced six coded themes showing that children in a task-switching study made more consecutive errors and showed smaller post-error slowing than adults while recruiting the dorsal anterior cingulate cortex and anterior insula, that white matter microstructure was related to age and arithmetic performance, that response inhibition was related to visuospatial working memory in young adults, that far transfer from executive function training was limited, that cognitively engaging physical activity and guided play showed small to moderate benefits, and that sleep and class timing were related to cognitive performance. These findings indicate that abstract reasoning in middle childhood is supported by interacting neural and biological conditions, and the proposed neuropedagogical framework should be treated as a set of hypotheses that require classroom-based experimental testing.