智能技术支持的科学论证

… As a critical indicator of scientific literacy, scientific argumentation encompasses not only … In scientific argumentation instruction, several persistent challenges have been identified. …

… This study combines scientific argumentation, … AI-interactive learning environment. Through the synergy created by these three dimensions, it aims to promote scientific argumentation …

Abstract Writing academic arguments is a complex and demanding task, even for proficient tertiary students. At the same time, providing prompt support for individual students working on discipline-specific arguments is often challenging for instructors. Artificial Intelligence (AI) techniques enable automated and adaptive educational scaffolding. In this study, we leveraged Natural Language Processing (NLP) AI techniques in an AI-Supported Scaffolding (AISS) system to evaluate written arguments and present alternative writing examples that human experts might write. To evaluate a pilot version of AISS, we gathered mixed-method data from 14 students enrolled in two sections of the same graduate-level online course (6 students in Cohort 1 and 8 students in Cohort 2). We used the Tool for the Automatic Analysis of Cohesion (TAACO) to track revisions in written arguments. TAACO indices demonstrated that the students used AI-generated scaffolding to build stronger claims with more elaborate and cohesive ideas. In written reflections, students revealed the perceived value of AISS, and visual inspection of their writing indicates that students used AISS feedback to improve their arguments. The findings demonstrate the potential of AI to provide personalised scaffolding for academic argument composition.

This article reports the outcome of a community service program aimed to improve the capability of biology teachers’ in using artificial intelligence to support learning in building scientific argumentation. As a respond to the teachers’ need, this program integrated digital technology into learning activities, promoting evidence-based reasoning for students. The activity introduced teachers to the Adaptive Interactive Study Interface for Next-Generation Learning (AISI) and train them to use it to build scientific argumentation in biology classrooms. The participants were 36 biology teachers from the local Biology Teachers’ Association (MGMP Biologi) across Purwakarta Regency, West Java, Indonesia. The program was conducted through online instructional sessions, hands-on training, and guided practice. The results were evaluated using a pre-test and post-test design, supplemented by a perception questionnaire. Based on the results, teachers responded positively and were actively engaged throughout the training. AISI was perceived as easy to use, relevant to learning in biology, and effective in helping students construct, evaluate, and revise scientific arguments. The program improved teachers’ pedagogical and technological capability in designing AI-supported argumentation building. These findings imply that AI-based community service programs can support teacher professional development and promote more interactive, evidence-based science learning in schools.

This study addresses the limitations of traditional STEM education by integrating socio-scientific issues within the STEM-5E instructional framework, using generative AI-driven …

… from AI-assisted argumentative writing, identifying two types: a regulatory gap (misalignment between awareness and enactment) and a critical-AI … argumentation, metacognition, and AI …