Skip to content

No-Code RAG Ecosystems as an Alternative to Linear English Learning in Higher Education

· 0 citations · 20 references

TL;DR

This research provides a fully replicable methodology to democratize advanced, hallucination-free educational technology in university settings without requiring custom software engineering.

View source

Similar papers

#natural language process... Preprint Sep 2026

SLATE: Are AI-Generated Slides Educationally Effective? A Benchmark for Language Teaching Quality and Learner Knowledge Acquisition

SLATE (Slide-based Learning Assessment for Teaching Effectiveness), the first benchmark that evaluates AI-generated language teaching slides through instructional effectiveness and learner knowledge acquisition, reveals a dissociation between artifact quality and instructional effectiveness.

Jing-Zhuo Wu, Jia-Jun Zhang, Liu Yi et al. · 0 citations
#generative ai Open access Sep 2026

Large language models for teaching and learning in higher education: opportunities, challenges, and future directions

Five contributions that examine LLM-enhanced course recommendation, real-time prompting support, automated essay scoring, verifiable online education, and knowledge-augmented automation for higher-education services illustrate how LLMs are increasingly being used as components of educational systems rather than as stan...

Zheng-Dao Li, Jordi Conesa, Moncef Gabbouj et al. · 0 citations
Open access 2026

A TextGrad-Inspired Optimization Pipeline for AI-Assisted Generation of Lecture Notes and Problem Sets

Large language models (LLMs) hold substantial promise for AI-assisted education, yet challenges such as hallucinations and pedagogical misalignment hinder their direct application. This article introduces a pipeline adapting textual gradient-based optimization for the automated generation and iterative refinement of le...

Chi-Chiu So, C. Lee, Dan Yang et al. · 0 citations
#artificial intelligence Review Open access Oct 2026

Artificial Intelligence in Language Education: Pedagogical Applications, Representative Platforms, and Human Oversight

Artificial intelligence is reshaping language education through automated feedback, speech recognition, adaptive practice, dialogue systems, machine translation, learning analytics, and generative language models. This article critically reviews the principal pedagogical uses of these technologies and examines represen...

Sema Mehdi, Türkan İsmayıllı · 0 citations
Conference Aug 2026

Large Language Models: A Review with its Role, Applications and Challenges & Future Directions

The use of Large Language Models (LLM) has become a key to transforming the educational landscapes and enabling intelligent, adaptive learning through the help of GPT-4 and Llama series. This paper gives an in-depth discussion of the contribution of LLMs in the field of education starting with the initial work done usi...

Chintan Chatterjee, Umang Patel, Jaydeep Vala et al. · 0 citations
Open access Aug 2026

Clause Encounters of the Third Kind: Can LLMs Replace Language Teachers?

While various organizations now actively encourage LLM use in classrooms, we still lack rigorous, systematic evaluations of how well these models actually perform the fundamental tasks of language pedagogy. This paper examines whether state-of-the-art LLMs can deliver the kind of corrective feedback and methodological...

Kristina Šekrst, A. Kovačič · 0 citations

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