Ahmet's PhD

This study aims to critically examine how the integration of artificial intelligence (AI) in education impacts teachers, particularly in relation to their autonomy, professional identity, and relationships. Using Marx’s theory of alienation as a framework, the study seeks to explore the broader implications of AI on the teaching profession and its alignment with humanistic teaching values.

Research Questions

1

How does AI contribute to teachers' alienation from the products of their labour?

2

How does AI affect the teaching process, leading to alienation from the act of teaching itself?

3

How does AI contribute to teachers' alienation from their species-being?

4

How does AI reshape social relations in education, causing alienation from colleagues and students?

Relevance of AI in Education

AI’s integration in education is transforming teaching practices globally. Tools like automated grading systems, adaptive learning platforms, and virtual teaching assistants promise efficiency and personalised learning. However, these developments also pose challenges:

Reducing teacher autonomy in decision-making.
Risking job satisfaction by automating traditionally human-centric tasks.
Impacting relational and empathetic aspects of teaching

This research is timely, as it addresses the critical need to balance AI’s potential benefits with preserving the essence of the teaching profession. It aims to contribute to ethical and practical frameworks guiding AI adoption in education.

Theoretical Framework

This research is rooted in Karl Marx’s theory of alienation, which describes the estrangement workers experience under conditions that separate them from the following.

The Product

Teachers might feel disconnected from student learning outcomes as AI takes on grading and feedback tasks.

The Production

The use of AI in lesson planning and curriculum delivery may reduce teachers' decision-making freedom and creative input.

Species-Being

AI’s automation of meaningful teaching tasks may limit teachers' ability to express their human potential through their work.

Others

AI-mediated teaching could diminish relational engagement, isolating teachers from colleagues and students.

The purpose of this study is to critically investigate the extent to which AI technologies contribute to labour alienation among teachers.

1. To explore how AI affects teachers' autonomy, professional identity, and their relationships with students.
This objective seeks to understand the complex ways AI technologies influence teachers’ professional autonomy—their ability to make independent decisions regarding instructional practices, curriculum implementation, and classroom management (Pearson & Moomaw, 2005). It also examines how AI impacts teachers' professional identity and the relational dimensions of teaching.

2. To examine how AI technologies might contribute to alienation among teachers.
This objective focuses on analysing the potential alienation of teachers from their work as a consequence of AI integration, based on Marxist theory.

3. To explore the broader implications of AI integration in education through the lens of alienation.
This objective aims to assess the systemic changes introduced by AI-driven technologies, with a focus on how these changes may contribute to or alleviate feelings of alienation among teachers.

This study is significant as it applies Marx’s theory of labour alienation to the integration of AI in education, bridging historical frameworks with modern technological challenges. It expands on Marx’s concepts to address how AI impacts teaching, offering insights into autonomy, professional identity, and social relations.

By exploring AI’s effects on teachers’ work, this research provides valuable data to guide policies and practices that enhance educators’ well-being. It informs strategies for teacher training and AI implementation, ensuring technological benefits support human-centric teaching environments. Empirical findings from surveys and interviews reveal how AI influences control, meaningfulness, and interpersonal dynamics in the profession.

As AI increasingly shapes education, this study offers timely contributions to debates on its ethical and practical implications, advocating for teacher fulfillment alongside technological progress.

SURVEY DESIGN

The data collection process employs a bilingual questionnaire (in English and Turkish) designed to capture teachers’ perceptions of AI’s impact on their professional experiences. The survey is structured around Marx’s theory of alienation, with sections exploring:

Alienation from the product of labour,
Alienation from the labour process,
Alienation from species-being, and
Alienation from interpersonal relationships.

Each section contains statements rated on a 5-point Likert scale, ranging from "Strongly Disagree" to "Strongly Agree," enabling the quantification of teachers’ experiences. The survey is distributed both online (via a QR code link) and in print to ensure accessibility for participants with varying technological proficiency.