Empowering Scientific Argumentation through Best Practices in Science Education: What Lies Ahead?

Artificial Intelligence (AI)-based assessment is increasingly being adopted in educational contexts. One area that remains challenging is scientific reasoning in Science Education, which has been identified as a major constraint among secondary school students in mastering argumentation skills. The inability to systematically connect claims and evidence to scientific principles not only reduces the quality of arguments but also hinders the development of holistic scientific literacy. Therefore, this paper aims to discuss the best practices of the Strength-Based Science Education (SBSE) approach, a pedagogical approach that focuses on identifying, activating, and developing students’ cognitive and socio-emotional strengths to enhance their reasoning abilities. In addition, this paper discusses future directions, particularly in AI-based assessment. The implementation of best practices encompasses three main strategies: identifying students’ reasoning strengths, constructing Claim–Evidence–Reasoning (CER) strength profiles, and facilitating strength-based peer reasoning dialogues. These strategies enable students to understand their personal reasoning styles, utilize them in constructing arguments, and improve weaknesses through peer collaboration. Reflective observations indicate that integrating argumentation frameworks into teaching and learning activities enhances conceptual clarity, confidence in argumentation, and active student collaboration. These findings support the effectiveness of the CER model in improving scientific literacy and the quality of classroom discourse. To ensure the sustainability of these practices, a generic conceptual model is proposed as a practical reference for educators. This initiative not only promotes more holistic and inclusive Science learning but also empowers students’ potential in accordance with contemporary educational needs. Future studies should further explore effective adaptations of scientific reasoning in Science Education through contemporary AI-based assessment practices. The proposed framework provides a practical reference for educators and a conceptual foundation for future research on AI-enhanced scientific reasoning assessment in Science Education.

artificial intelligence (AI); cognitive; scientific argumentation; scientific reasoning; science education; students’ socio-emotional development

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