Treffer: Development and Validation of the AI-Driven Pedagogical Leadership Agility Scale (AIDPLA): Exploring Ethical and Spiritual Dimensions of Educational Leadership in Jordan.
Title:
Development and Validation of the AI-Driven Pedagogical Leadership Agility Scale (AIDPLA): Exploring Ethical and Spiritual Dimensions of Educational Leadership in Jordan.
Authors:
Khasawneh NAS; Faculty of Educational Sciences, Classroom Teacher Department, Specialization in Arabic Language Curricula and Teaching Methods, Irbid National University, Irbid, Jordan., Khasawneh YJA; Faculty of Educational Sciences, Department of Educational Administration, Ajloun National University, Ajloun, Jordan., Khasawneh MAS; Special Education Department, King Khalid University, Abha, Saudi Arabia. mkhasawneh@kku.edu.sa.
Source:
Journal of religion and health [J Relig Health] 2025 Oct 10. Date of Electronic Publication: 2025 Oct 10.
Publication Model:
Ahead of Print
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Springer Country of Publication: United States NLM ID: 2985199R Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1573-6571 (Electronic) Linking ISSN: 00224197 NLM ISO Abbreviation: J Relig Health Subsets: MEDLINE
Imprint Name(s):
Publication: New York, NY : Springer
Original Publication: New York : Academy of Religion and Mental Health.
Original Publication: New York : Academy of Religion and Mental Health.
References:
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Almahasees, Z., Al-Harahsheh, A., & Albudairi, Y. (2024). AI-powered education: Revolutionizing teaching and learning through artificial intelligence in Jordan. Research Journal in Advanced Humanities. https://doi.org/10.58256/dqpagd83. (PMID: 10.58256/dqpagd83)
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Educational leadership and artificial intelligence for sustainable development. OP Avurakoghene & AO Oredein, Educational Leadership and Artificial Intelligence for Sustainable Development, Shodh Sari-An International Multidisciplinary Journal, 2(3),211-223. https://doi.org/10.59231/SARI7600.
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Blancia, G. V. V., Fetalvero, E. G., Baldera, P. R., & Mani, M. C. (2024). The mediating effects of artificial intelligence literacy on the association between computational thinking skills and organizational agility among secondary school teachers. Problems of Education in the 21st Century, 82(5), 616–629. (PMID: 10.33225/pec/24.82.616)
Boateng, G. O., Neilands, T. B., Frongillo, E. A., Melgar-Quiñonez, H. R., & Young, S. L. (2018). Best practices for developing and validating scales for health, social, and behavioral research: A primer. Frontiers in Public Health, 6, 149. (PMID: 29942800600451010.3389/fpubh.2018.00149)
Bouland-van Dam, S. I., Oostrom, J. K., & Jansen, P. G. (2022). Development and validation of the leadership learning agility scale. Frontiers in Psychology, 13, 991299. https://doi.org/10.3389/fpsyg.2022.991299. (PMID: 10.3389/fpsyg.2022.991299366191039817000)
Bush, T., & Glover, D. (2014). School leadership models: What do we know? School Leadership & Management, 34(5), 553–571. (PMID: 10.1080/13632434.2014.928680)
Byrne, B. M. (2016). Structural equation modeling with AMOS: Basic concepts, applications, and programming (3rd ed.). Routledge. https://doi.org/10.4324/9781315757421 .
Charbonnier-Voirin, A. (2011). The development and partial testing of the psychometric properties of a measurement scale of organizational agility. M@n@gement, 14(2), 119–156. (PMID: 10.3917/mana.142.0119)
Costello, A. B., & Osborne, J. (2005). Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Practical Assessment, Research, and Evaluation, 10(7). https://doi.org/10.7275/jyj1-4868 .
Crispín, R. L., Huayta-Franco, Y. J., Pimentel, J. F. F., Arenas, R. D., & Flores, E. (2022). Management performance, pedagogical leadership and school management in the learning. MOJEM: Malaysian Online Journal of Educational Management, 10(2).
Day, C., Gu, Q., & Sammons, P. (2016). The impact of leadership on student outcomes: How successful school leaders use transformational and instructional strategies to make a difference. Educational Administration Quarterly, 52(2), 221–258. (PMID: 10.1177/0013161X15616863)
De Meuse, K. P., Dai, G., & Hallenbeck, G. S. (2010). Learning agility: A construct whose time has come. Consulting Psychology Journal: Practice and Research, 62(2), 119. (PMID: 10.1037/a0019988)
DeVellis, R. F., & Thorpe, C. T. (2021). Scale development: Theory and applications. Sage Publications.
Dunn, T. J., Baguley, T., & Brunsden, V. (2014). From alpha to omega: A practical solution to the pervasive problem of internal consistency estimation. British Journal of Psychology, 105(3), 399–412. (PMID: 2484411510.1111/bjop.12046)
Elo, S., & Kyngäs, H. (2008). The qualitative content analysis process. Journal of Advanced Nursing, 62(1), 107–115. (PMID: 1835296910.1111/j.1365-2648.2007.04569.x)
Floridi, L. (2018). Soft ethics, the governance of the digital and the General Data Protection Regulation. Philosophical Transactions of the Royal Society a: Mathematical, Physical and Engineering Sciences, 376(2133), 20180081. (PMID: 10.1098/rsta.2018.0081)
Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., Luetge, C., Madelin, R., Pagallo, U., & Rossi, F. (2018). AI4People—An ethical framework for a good AI society: Opportunities, risks, principles, and recommendations. Minds and Machines, 28, 689–707. (PMID: 30930541640462610.1007/s11023-018-9482-5)
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. (PMID: 10.1177/002224378101800104)
Fry, L. W. (2003). Toward a theory of spiritual leadership. The Leadership Quarterly, 14(6), 693–727. (PMID: 10.1016/j.leaqua.2003.09.001)
Fullan, M. (2014). Three keys to maximizing impact. In Jossey-Bass and Ontario Principal’s Council, Toronto.
Fullan, M., Azorín, C., Harris, A., & Jones, M. (2024). Artificial intelligence and school leadership: Challenges, opportunities and implications. School Leadership & Management, 44(4), 339–346. https://doi.org/10.1080/13632434.2023.2246856. (PMID: 10.1080/13632434.2023.2246856)
Golino, H., Christensen, A. P., & Moulder, R. (2020). EGAnet: Exploratory graph analysis: A framework for estimating the number of dimensions in multivariate data using network psychometrics. R package version 0.9, 5.
Golino, H. F., & Epskamp, S. (2017). Exploratory graph analysis: A new approach for estimating the number of dimensions in psychological research. PLoS ONE, 12(6), e0174035. https://doi.org/10.1371/journal.pone.0174035. (PMID: 10.1371/journal.pone.0174035285948395465941)
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis. In Cengage Learning EMEA.
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Grant Information:
RGP.2 /68 /46 Deanship of Scientific Research, King Khalid University
Contributed Indexing:
Keywords: Artificial Intelligence in Education; Ethical AI Leadership; Pedagogical leadership; Psychometrics; Spiritual Visionary Leadership
Entry Date(s):
Date Created: 20251010 Latest Revision: 20251010
Update Code:
20251011
DOI:
10.1007/s10943-025-02478-1
PMID:
41073808
Database:
MEDLINE
Weitere Informationen
The purpose of this study was twofold: first, to design a novel scale for measuring AI-driven pedagogical leadership agility, with a particular focus on its ethical and spiritual dimensions within educational leadership, and second, to evaluate the psychometric properties of this scale among secondary school administrators in Jordan. The primary aim was to provide a reliable and valid instrument to support leaders in navigating AI integration while maintaining ethical accountability and fostering spiritually informed leadership practices. The study proceeded in two main phases. Initially, the conceptual framework and item pool were developed based on a systematic literature review and semi-structured interviews with educational experts. Subsequently, data were collected from a stratified random sample of 740 secondary school principals in Jordan, and construct validity was examined using exploratory factor analysis (EFA), exploratory graph analysis (EGA), and confirmatory factor analysis (CFA). Reliability was assessed through Cronbach's alpha, McDonald's omega, composite reliability, and test-retest stability, while convergent validity, discriminant validity, and measurement invariance across gender were also evaluated. The analyses revealed a robust five-factor structure underpinning the scale, consisting of 33 items distributed across Algorithmic Vision in Educational Leadership, Spiritual Visionary Leadership, Ethics and Algorithmic Transparency in AI-Enabled School Leadership, AI-Enabled Innovative Educational Leadership, and AI-Responsive Crisis Management Leadership. CFA confirmed excellent model fit, and reliability indices demonstrated strong internal consistency and stability. Among the dimensions, Spiritual Visionary Leadership and Ethics and Algorithmic Transparency showed the highest reliability and predictive importance. Overall, findings suggest that the AI-Driven Pedagogical Leadership Agility Scale (AIDPLA) is a valid and reliable tool for assessing leadership agility infused with ethical and spiritual considerations in the context of AI integration in Jordanian secondary education.
(© 2025. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)
Declarations. Conflict of interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Ethics Approval: The current study avoids the need for publication consent by not sharing private information, carrying out experiments, or working with sensitive data. Also, all methods followed relevant guidelines and regulations or the Declaration of Helsinki 1964. Informed Consent: Informed consent was obtained from all individual participants included in the study.