Beyond Compliance: Creative Thinking as an Anchor for Academic Integrity in AI-Era Teacher Education

Brief synopsis - presentation

This presentation reports results from an empirical study of 1,450 Israeli preservice teachers examining how creative thinking and ethical sensitivity in AI use relate to academic integrity. Using Structural Equation Modeling, the study tests whether creative thinking mediates the relationship between emotional stability and integrity. Results inform teacher education curriculum design.

Title: Beyond Compliance: Creative Thinking as an Anchor for Academic Integrity in AI-Era Teacher Education.

Introduction and Background:

Teacher education is undergoing a profound transformation as artificial intelligence (AI) reshapes conceptions of teaching, learning, and professional judgment in contemporary educational contexts (Zhang et al., 2025). Within this evolving landscape, creative thinking has been increasingly discussed in literature as a key dimension of teachers’ professional competence, supporting the design of original and context-sensitive pedagogical responses rather than the uncritical implementation of standardized instructional approaches (Maor et al., 2024). However, despite its recognized importance, the integration of creative thinking into teacher education curricula remains uneven. In the Israeli context, only about 20% of academic institutions currently include dedicated coursework in creative thinking within teacher education programs.

Creative thinking is traditionally described as detecting previously unidentified relationships and producing original and novel experiences as a new pattern, including the skill to evaluate, improve, and generate novel solutions (Yang & Zhao, 2021). The theoretical framework is based on Torrance’s Tests of Creative Thinking, which conceptualize creative thinking through fluency, flexibility, elaboration, and originality.

(Torrance, 1966). Eshet & Margaliot (2022) found using the Torrance test that the higher a student`s level of creative thinking, the lower their level of dishonesty and the higher their level of academic integrity.

Recent research suggests that AI-supported learning environments can contribute to the development of students’ creativity and higher-order thinking by enabling more personalized, interactive, and learner-centered experiences; however, these potential benefits are contingent upon teachers’ capacity to integrate AI tools in pedagogically sound, ethically informed, and critically reflective ways (Walter, 2024). At the same time, systematic reviews of the literature indicate that the rapid diffusion of generative AI has intensified concerns regarding academic integrity in higher education, including AI-assisted plagiarism, the automation of student assignments, and the erosion of authentic assessment practices (Bittle & El-Gayar, 2025).

Taken together, these developments place new and complex demands on teacher education programs, which are increasingly called upon to cultivate not only innovative pedagogical design capabilities but also robust ethical awareness and professional responsibility in relation to AI use. Such preparation is essential for positioning future teachers as both creative and trustworthy professionals capable of integrating AI responsibly across instructional and assessment contexts (Daher, 2025).

Conference Theme: Education & training in the area of ethics and integrity

The main research question examines how creative thinking contributes to academic integrity among undergraduates in the AI era, with the following hypotheses: H1 states that creative thinking negatively correlates with academic dishonesty, H2 proposes that ethical sensitivity in AI use negatively correlates with academic misconduct, and H3 posits that creative thinking mediates the relationship between emotional stability and academic integrity.

Methods: Ethical approval for the study was obtained from the Institutional Review Board (Approval No. 2024/5). All participants provided informed consent. A paper and pen questionnaire was distributed to a Sample of a 1,450 undergraduate students, primarily in education programs (future teachers), studying in four academic colleges in Israel. Student grade point averages ranged from 20 to 100.

Instruments: Part one Torrance Tests of Creative Thinking (Runco et al., 2010), measuring dimensions of creative thinking: fluency (generating many ideas), flexibility (diverse thinking), elaboration (developing ideas), and originality (unusual, surprising ideas), (Cohen’s κ = .80). Part two the Academic Integrity Inventory (Eshet & Margaliot, 2022), a culturally adapted scale assessing academic integrity and dishonesty behaviors among students (α = .84) . Part three Ethical Sensitivity in AI Use Scale - measuring awareness of ethical implications in AI deployment (fairness, algorithmic bias, privacy, accountability, hallucinations), (α = .87). Part four the Big Five Personality Inventory (Gosling et al., 2003), assessing emotional stability and other personality dimensions, (α = .70).

Analysis was Correlation analysis using Pearson correlation and model building Structural Equation Modeling (SEM) to examine direct relationships, mediation effects, and model fit. Model fit was assessed using Chi-square, CFI (Comparative Fit Index), RMSEA (Root Mean Square Error of Approximation), and R² (explained variance). As the data are based on self-reported measures, the findings reflect participants’ reported behaviors and perceptions of academic integrity.

Findings: The structural equation modeling revealed that creative thinking, particularly the originality dimension, serves as a protective factor against academic dishonesty among education students. The study demonstrated that most students (71%) reported engaging in academic cheating at some point, yet students exhibiting higher levels of creative thinking, especially originality and flexibility, demonstrated significantly lower rates of unethical academic behavior. The model fits the data well, confirming both hypotheses H1 and H2. Additionally, ethical sensitivity regarding AI deployment emerged as an independent predictor of academic integrity, with students possessing high ethical awareness demonstrating substantially greater academic integrity regardless of AI tool usage frequency.

What Was Learnt: The interplay between personality traits, creative thinking, and ethical sensitivity creates a complex protective mechanism against academic misconduct in the AI era. Originality the capacity to generate unique, novel ideas proved to be the strongest dimension of creative thinking in predicting academic integrity. Students who naturally think creatively are less likely to resort to plagiarism or cheating because they are intrinsically motivated to develop their own original contributions. Furthermore, merely using AI tools does not necessarily lead to misconduct; rather, understanding the ethical implications and risks of AI deployment, including awareness of plagiarism generation, hallucinations, and algorithmic bias drives responsible, ethical use. These findings suggest that integrating creative thinking education and AI ethics training into teacher training programs can meaningfully enhance student academic integrity while preparing future educators to foster both innovation and ethical responsibility in their own classrooms.

Conclusion: Strengthening and systematizing the integration of creative thinking within existing teacher education programmes can enhance students’ integrity, innovation, and problem-solving abilities, particularly given that such components are currently implemented in a limited and uneven manner across institutions. To foster both, educators are encouraged to adopt pedagogical approaches that emphasise autonomy, collaboration, and engagement with real-world challenges. Considering the growing influence of artificial intelligence (AI) on education and employment, educators must also develop a robust understanding of AI to prepare students for future professional contexts adequately. Academic integrity remains a cornerstone of trust within educational systems and is typically reinforced through the promotion of positive values, among which creative thinking plays a vital role.

Keywords: Creative Thinking, Academic Integrity, Ethical Sensitivity, Artificial Intelligence; Teacher Education; Academic Misconduct.

Artificial intelligence tools were used solely to improve wording, proofreading, and alignment with the submission guidelines; responsibility for the content remains with the authors.

References

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