Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
PERCEPTIONS AND EXPERIENCES OF PRE-SERVICE AND IN-SERVICE CHEMISTRY TEACHERS ON THE INTEGRATION OF ARTIFICIAL INTELLIGENCE
Download
Cansu_Erol_Thesis_2296465.pdf
CANSU EROL.pdf
Date
2026-8-14
Author
Erol, Cansu
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
116
views
0
downloads
Cite This
This study aims to explore the perceptions, experiences, and recommendations of Turkish pre-service and in-service chemistry teachers regarding the use of AI-based tools in chemistry education. A qualitative design and purposive sampling were used to recruit nine senior pre-service chemistry teachers at a university and ten in-service chemistry teachers from private colleges in Ankara. Semi-structured interviews were performed from October 2025 to January 2026, analysed by means of inductive qualitative content analysis and the constant comparative method. Three themes were identified: Teachers’ Perceptions Towards AI in Chemistry Education, Experiences with AI-Based Tools in Chemistry Education, and Recommendations for Effective AI Integration in Education. Participants conceptualised AI as digital applications/information systems supporting rather than replacing teachers. In-service teachers mentioned generative AI tools; pre-service teachers mentioned simulations and animations. Uses included lesson planning, assessment/question generation, experiment/activity/material design, addressing misconceptions/learning difficulties, supporting teacher learning, and producing level-appropriate explanations, examples, analogies and visualisations. Participants agreed AI outputs required scientific-community verification, revision and contextualisation. Concerns included accuracy, reliability, misunderstanding user intent, classroom integration, student reliance, reduced critical thinking, academic integrity, confidentiality and ethical use. Pre-service teachers focused on simulations, misconceptions, prompting, personal learning and university AI education, while in-service teachers focused on classroom applications, teacher responsibility, professional development, policies, infrastructure and monitoring. Recommendations included Practitioner-Oriented Teacher Training, Responsible Use by Students, Institutional Policies, Curriculum Arrangements, Infrastructure and Equitable Access. Accessing technology, professional experience, ethical awareness, contextual adaptation, responsible student use and institutional readiness were essential to integration, informing teacher education, professional development and institutional planning.
Subject Keywords
Artificial intelligence, Chemistry education, Pre-service chemistry teachers, In-service chemistry teachers, Basic qualitative research
URI
https://hdl.handle.net/11511/120651
Collections
Graduate School of Natural and Applied Sciences, Thesis
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
C. Erol, “PERCEPTIONS AND EXPERIENCES OF PRE-SERVICE AND IN-SERVICE CHEMISTRY TEACHERS ON THE INTEGRATION OF ARTIFICIAL INTELLIGENCE,” M.S. - Master of Science, Middle East Technical University, 2026.