Skip to content
#explainable ai Book Open access

Foundations of Morphology: For EFL University Students

Oct 2026 · Zenodo (CERN European Organization for Nuclear Research)
Syntax, Semantics, Linguistic Variation

Abstract

Foundations of Morphology: For EFL University Students is a free introductory textbook on words, their internal structure, and the ways languages express grammatical meanings. It is written for international undergraduates studying through English as a foreign language and belongs to the Theoretical Linguistics branch of English Language Studies for EFL University Students. Necessary background is introduced within the book, with no previous university course in morphology assumed. Fifteen chapters cover wordhood, lexemes, and word classes; morphemes, morphs, and allomorphs; segmentation, glossing, and word-structure analysis; derivation; compounding and other word-formation processes; inflection and grammatical categories; paradigms, inflection classes, and exponence; nonconcatenative morphology; root-and-pattern morphology, including Arabic; relationships with phonology and syntax; productivity, lexicalization, and the lexicon; morphological typology; and major approaches to morphological explanation. Students compare forms across languages, solve data problems, interpret glosses and word trees, and explain the evidence behind their analyses. The complete digital textbook supports approximately 35–45 classroom contact hours, flexible teaching, and independent study. Central questions, learning outcomes, chapter roadmaps, worked examples, figures and tables, guided activities, five final practice tasks per chapter, review infographics, key terms, short quizzes, and complete explained answers help learners progress from recognition to analysis. All essential content is included without a paid access code or subscription. First Edition, Version 1. Directed by Munassir Alhamami of King Khalid University, with assistance from ChatGPT, Claude, Gemini, and NotebookLM. Original content is licensed under CC BY 4.0 except where otherwise stated; credited third-party material retains its stated terms. Series website: https://sites.google.com/view/els4efl/home AI-use disclosure: ChatGPT, Claude, Gemini, and NotebookLM assisted with research, drafting, revision, visual development, and production of this textbook. The cover illustration and the 32 chapter and whole-book learning visuals were generated with ChatGPT image assistance; exact cover typography and QR codes were prepared separately, and technical diagrams retain their original source attributions. The Project Director, Munassir Alhamami, is responsible for the final editorial decisions and released version.

View source

Similar papers

#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
#computer vision Open access Mar 2024

LLM-based agents for automating the enhancement of user story quality: An early report

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. · 48 citations · ⚡4
#computer vision Review Mar 2024

System for systematic literature review using multiple AI agents: Concept and an empirical evaluation

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. · 44 citations · ⚡2
#computer vision Feb 2024

Can Large Language Models Serve as Data Analysts? A Multi-Agent Assisted Approach for Qualitative Data Analysis

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. · 41 citations
#artificial intelligence Conference Open access Jun 2018

The Key Concepts of Ethics of Artificial Intelligence

It is suggested that the focus on finding keywords is the first step in guiding and providing direction for future research in the AI ethics field.

Ville Vakkuri, P. Abrahamsson · 39 citations · ⚡2

Related blog posts

Microsoft Research Blog Oct 12, 2026

Simulating student learning for better AI tutoring

StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.

GPT-Lab Oct 12, 2026

AI Has Grown Up. Have We?

AI is moving beyond impressive demos. After World Summit AI 2026 in Amsterdam, GPT-Lab's Muhammad Waseem reflects on what organizations need to make AI agents reliable, responsible and genuinely useful in everyday work. The post AI Has Grown Up. Have We? appeared first on GPT-Lab.

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