PhD Candidate · Information Systems · Universiti Utara Malaysia

Mohammed Moghazi Ezzeldein Ahmed

I study why academics keep using generative AI — and I build the digital products that put research into people’s hands.

Explore my research See what I’ve built

Each light behind me is one of the 183 studies my thesis stands on. Drag to turn the galaxy.

Mohammed Moghazi Ezzeldein Ahmed
Generative AI in higher education PLS-SEM · Survey research Product builder
0studies reviewed & cited
0hypotheses in one model
0faculty in the study population
0digital products built
—visitors to this site

About me

Hi, I’m Mohammed Moghazi Ezzeldein Ahmed.

I am a PhD candidate in Information Systems at Universiti Utara Malaysia (UUM). My doctoral research asks why university faculty keep using generative AI tools after adopting them, and how the quality of those tools, academics’ cognitive trust and their AI self-efficacy shape that decision — with a survey of faculty in Egyptian higher education.

My background is Management Information Systems: a bachelor’s degree in Mansoura, Egypt, where I graduated first in my class with first-class honours, and a master’s degree from Amman Arab University, Jordan, completed with a perfect 4.00 / 4.00 GPA.

Alongside research, I design and build digital products in Arabic — from a study-abroad guide covering more than 740 universities to a research-collaboration platform and the system I use to write my own thesis. I believe a good research question deserves a good tool.

Information systems adoptionGenerative AI in higher educationTrust in AI PLS-SEMSurvey designProduct design & engineeringDigital transformationAI in businessBusiness model innovation
  1. 2014

    Bachelor of Management Information Systems

    Misr Higher Institute for Commerce & Computers, Mansoura, Egypt

    Ranked 1st · First-class honours
  2. 2015–21

    Teaching Assistant, Management Information Systems

    Misr Higher Institute for Commerce & Computers, Mansoura, Egypt

    • Taught across the full range of MIS courses
    • Supervised graduation projects
    • Served on the examinations control committee
  3. 2024

    Master of Management Information Systems (Thesis track)

    Amman Arab University, Jordan

    GPA 4.00 / 4.00 · ExcellentHonoured by Jordan’s Minister of Higher Education — first among international students
  4. Now

    PhD candidate, Information Systems

    Universiti Utara Malaysia (UUM)

    Chapters 1–3 complete

Doctoral research

Why do academics keep using generative AI?

Thesis · in progress

The Impact of Perceived Generative AI Quality on Continuance Intention Among University Faculty in Egypt: The Mediating Role of Cognitive Trust and the Moderating Effect of AI Self-Efficacy

University
Othman Yeop Abdullah Graduate School of Business, Universiti Utara Malaysia
Population
146,995 faculty members, Egyptian higher education
Method
Proportionate stratified survey · PLS-SEM
Theories
IS Success Model · Expectation–Confirmation Model · Social Cognitive Theory
01

Do the information, system and service quality of GenAI tools build academics’ cognitive trust?

02

Does that trust carry academics from trying GenAI to continuing to use it?

03

Does AI self-efficacy strengthen the step from trust to continued use?

Most evidence on GenAI comes from students. Academics decide what students learn, yet they are rarely studied — and no previous study combines all six constructs of this model.

Conceptual framework

Eleven hypotheses, one model

Hover or tap a path to read its hypothesis.

Research model: three quality dimensions lead to cognitive trust and continuance intention, moderated by AI self-efficacy. Informationquality Systemquality Servicequality Cognitivetrust Continuanceintention AIself-efficacy Perceived GenAI quality

Evidence map

Fifty years of theory, three years of explosion

The studies behind the thesis, by year of publication and by theme.

71% of the cited studies were published in 2024–2026 — the generative AI era.
183studies
    71%of prior studies focus on students
    17%on university teachers — the gap this thesis fills
    Share of prior GenAI-acceptance studies by sample, as reported in the literature reviewed in Chapter Two.

    Publications

    Research in numbers

    Counted from the records below. Work under review is listed separately and never counted as published.

    Academic services

    How I can help

    Research support, collaboration and guidance — grounded in my own doctoral work and the products I build.

    Digital products

    Research that ships

    Platforms and apps I designed and built — live, in use, and in Arabic first.

    How I work

    From question to product

    1. 1

      Ask a precise question

      Theory first: every construct defined, every path argued from evidence.

    2. 2

      Trace every claim to its source

      Each sentence of the thesis links to the exact passage it rests on.

    3. 3

      Build the tool that was missing

      When the workflow does not exist, I build it — then put it in other people’s hands.

    Get in touch

    Open to research collaboration

    For collaboration on generative AI in higher education, survey research and PLS-SEM, or building a digital product for research, write to me.

    Research profiles