Sep 2026· Educational technology research and development· 0 citations· 50 references
AI in Service Interactions
Abstract
The increasing accessibility of Artificial Intelligence (AI), particularly Generative AI (GenAI) and chatbots, highlights the need for users to develop critical thinking skills to evaluate information and understand these systems. While critical thinking is essential for interacting with such technologies, current AI literacy efforts lack robust empirical validation, and effective educational methodologies have yet to be explored. This study explores the potential of the Socratic Method, a structured dialogue-based approach that fosters reflection and critical questioning, to support the development of critical thinking within a GenAI environment. Recognizing that many technology-enhanced and Socratic learning environments often overlook the role of learners’ domain expertise and prior knowledge in shaping effective questioning strategies, the study further compares within-domain and outside-domain Socratic dialogues to evaluate the pedagogical effectiveness of both conditions. Eighty participants, comprising higher education students and teachers, took part in workshops where they interacted with GenAI using two Socratic-style prompts, one within-domain and one outside-domain, and completed questionnaires assessing critical thinking, technical competence, and trust in technology after each interaction. Findings highlight the value of guiding GenAI interactions through Socratic reasoning within domain-relevant contexts to enhance perceived critical thinking, while also stressing the challenges of influencing user trust and perceived competence in technology.
The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.
Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson· EUROMICRO Conference on Soft...· 64 citations· ⚡6
The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.
Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al.· arXiv.org· 62 citations· ⚡3
A comprehensive overview of how enhanced sampling methods are reshaping the field, with a particular focus on the data-driven construction of collective variables, is provided.
Kai Zhu, Enrico Trizio, Jintu Zhang et al.· Chemical Reviews· 58 citations
The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.
Zheying Zhang, M. Rayhan, Tomas Herda et al.· International Conference on...· 48 citations· ⚡4
This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.
Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al.· arXiv.org· 44 citations· ⚡2
The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.
Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al.· arXiv.org· 41 citations
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