Skip to content

A Simple Technology of Thesaurus Design in Partnership with Artificial Intelligence. Part 1: A Practical Guide and Case Studies for Educators

Sep 2026 · Zenodo (CERN European Organization for Nuclear Research)

Abstract

This preprint describes a methodological framework IPRO-Dialogue (Integrated Pragmatic Regulation and Ontology of Dialogue) for integrating generative Artificial Intelligence into modern lesson planning and curriculum design. Moving away from passive use of AI, this article presents a structured methodology for collaborative "human-AI" design based on classic technologies for developing computer learning environments (1981–1994). The guide provides educators with a reliable, code-free "linguistic grounding" technique. As an example, this paper describes the creation of a thesaurus on the topic of "Ancient Egypt" for middle school students. By deploying a strictly controlled, 60-term educational thesaurus and limiting AI text generation to absolute zero (Temperature = 0), teachers can mitigate AI "hallucinations" and frame a secure, personalized Socratic learning environment for middle school students. Key practical assets included in this document: 1) Step-by-step technology for conceptual term extraction and ontological mapping; 2) Universal meta-prompt templates and complete system instructions for an AI expert-validator; 3) The Prompt Architecture Diagnostic Checklist (Identity, Boundary, and Safety dimensions) for stress-testing prompts before classroom use; 4) Text-based Mermaid.js visualization protocols and tabular data export formats (CSV/XLSX) for instant educational technology integration; 5) A ready-to-use registration template for securing teacher intellectual property via micro-publications with DOI assignments. This manual serves as an actionable blueprint for instructional designers, K-12 teachers, and educational technology researchers striving to maintain pedagogical control over generative tools. Keywords: IPRO-Dialogue, Educational Thesaurus, Conceptual Learning, Prompt Engineering, Educational Technology, Human-AI Co-creation in Curriculum Design, Teacher Agency.

View source

Similar papers

#artificial intelligence Open access May 2023

Evaluating the Performance of Large Language Models on GAOKAO Benchmark

GAOKAO-Bench is introduced, an intuitive benchmark that employs questions from the Chinese GAOKAO examination as test samples, including both subjective and objective questions that contribute a robust evaluation benchmark for future large language models and offers valuable insights into the advantages and limitations of such models.

Xiaotian Zhang, Chun-yan Li, Yi Zong et al. · 216 citations · ⚡17
#artificial intelligence Open access Jul 2024

Gender, Race, and Intersectional Bias in Resume Screening via Language Model Retrieval

This work investigates the possibilities of using LLMs in a resume screening setting via a document retrieval framework that simulates job candidate selection and finds that the MTEs are biased, significantly favoring White-associated names in 85% of cases and female-associated names in only 11.1% of cases.

Kyra Wilson, Aylin Caliskan · 131 citations · ⚡8

PRISM: Self-Pruning Intrinsic Selection Method for Training-Free Multimodal Data Selection

Empirically, PRISM reduces the end-to-end time for data selection and model tuning to just 30% of conventional pipelines, and achieves this efficiency while simultaneously enhancing performance, surpassing models fine-tuned on the full dataset across eight multimodal and three language understanding benchmarks.

Jinhe Bi, Yifan Wang, Danqi Yan et al. · 73 citations · ⚡4
#artificial intelligence Conference Open access Apr 2020

ECCOLA - a Method for Implementing Ethically Aligned AI Systems

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 · 64 citations · ⚡6
#computer vision Review Apr 2024

AI-powered Code Review with LLMs: Early Results

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. · 62 citations · ⚡3

Let the Flows Tell: Solving Graph Combinatorial Optimization Problems with GFlowNets

This paper designs Markov decision processes (MDPs) for different combinatorial problems and proposes to train conditional GFlowNets to sample from the solution space and demonstrates that GFlowNet policies can efficiently find high-quality solutions.

Dinghuai Zhang, H. Dai, Esmeralda S. Whitammer et al. · 59 citations · ⚡8

Related blog posts

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.