Journal Article
1 May 2026
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Volume 10, Issue 2 (2026)Read More
Featured Content
Journal Article1 May 2026AI-assisted Case Conceptualization: Enhancing Ethical Decision-making in Graduate Counseling Education
As artificial intelligence (AI) is increasingly integrated into counselor education, a significant gap exists between the rapid adoption of technology and the development of structured pedagogical frameworks for ethical decision-making. This article introduces a multi-component framework to support ethical AI integration in graduate counseling education, comprising three key elements: (1) a case conceptualization model with AI assistance, (2) Morgan (SC), an intentionally imperfect AI school counseling thought partner trained on ethical standards and decision-making models, and (3) structured protocols for ethical decision-making aligned with American Counseling Association and National Board for Certified Counselors guidance. The framework is designed to center human judgment, cultural responsiveness, and professional values, leveraging AI to prompt reflection, generate alternative perspectives, and highlight ethical and contextual considerations. The framework is conceptually situated within a graduate-level internship course and informs instructional design and reflective learning practices. This article presents a practice-informed model for ethical AI integration.
Current Articles
- Journal Article1 May 2026
A Friendly Welcome from the Guest Editors Dr. Jeanne Surface and Dr. Elliott Ostler:
- Journal Article1 May 2026
The Integrity Paradox: Reflections on Epistemic Substitution and the Ethical Failure of Plagiarism Detection Systems
This article critiques the ethical authority granted to AI plagiarism detection systems, using humor to expose a serious contradiction in these algorithms. Through a case in which an original ethics manuscript is labeled 40.7% “non-original,” the authors argue that similarity scores are mistaken for judgments of misconduct. They introduce the concept of “epistemic substitution” to describe how tools that both judge originality and offer AI rewrites replace human authorship while mandating human accountability. The paper contends that this collapse of roles undermines scholarly integrity, conflates disciplinary fluency with plagiarism, and shifts ethical responsibility from humans to procedures. The authors call for contextual, human-centered oversight of AI-assisted evaluation. - Journal Article1 May 2026
You Are Me, and I Am You: Bias, AI, and the Academic Self
Being black, brown, caramel, immigrant, French speaking, divorced, mother of six, economically disadvantaged, neurodivergent, foster care graduate, survivor of abuse, child of divorce, and health-impacted person, I’ve often examined the wheel of power and privilege with sadness and dismay. In contrast, being white, catholic, intellectually advantaged, athletic, American, Canadian, middle-class, mathematics mastermind, and Doctor of Education, I’ve needed to examine this wheel fiercely as I come face-to-face with my privilege. Through reflection and self-interrogation, I carefully and imperfectly consider how my bias informs me of my disposition towards others, my educational privileges, and my experience in the world of academia. In this paper, I offer reflections on a specific form of bias from a specific set of people: AI and academics. These reflections serve to vulnerably disclose how I continue to interrogate my bias towards AI and to offer opportunity for other academics to do the same. - Journal Article1 May 2026
Leading with Intentionality: A PreK-12th Grade Public School District's Initial Journey of Ethical Artificial Intelligence Integration
This article chronicles the intentional and evolving approach of Westside Community Schools in Omaha, Nebraska, toward integrating artificial intelligence (AI) into teaching and learning. Grounded in historical parallels to earlier technological shifts such as calculators, the Internet, and search engines, the district emphasizes ethical implementation, transparency, and ongoing professional learning rather than restriction or avoidance. Through the development of an AI Task Force, differentiated professional development, and community engagement initiatives, Westside seeks to promote AI literacy while preserving academic integrity and human-centered decision-making. The district’s framework prioritizes safety, equity, and responsible use, positioning AI as a tool to enhance—not replace—critical thinking and creativity. While challenges related to adoption, perception, and rapid technological change remain, Westside’s experience highlights the importance of adaptive leadership, cultural trust, and continuous learning in preparing students for an AI-driven future. - Journal Article1 May 2026
Leading Artificial Intelligence Integration: Trust, Tension, and Decision-Making
Artificial intelligence integration in education is advancing faster than shared trust and understanding are being established. Educational leaders are responding in real-time to questions of risk and efficacy while navigating conditions that are still forming. This article situates artificial intelligence integration within the paradox of educational leadership, identifying trust as the critical condition shaping leaders’ interpretations of the tensions. Leveraging paradox and trust theory, the article explores how competing demands are not problems to be solved, but tensions to be navigated. When trust is present, leaders respond to tension points through both/and sense-making; when trust is absent, decision-making collapses into either/or approaches. The article offers actionable practices for building shared understanding, establishing guardrails, and creating conditions for the integration of reflective, contextually responsive artificial intelligence. - Journal Article1 May 2026
Harnessing AI in Legal Education: Opportunities for Innovation, Leadership, and Student Success
Artificial Intelligence (AI) is increasingly transforming the practice of law, from predictive analytics in policing and algorithmic sentencing to generative AI-assisted drafting and research. Despite this technological shift, legal education remains predominantly doctrinal, inadequately preparing graduates to function effectively in an AI-mediated environment. This paper contends that law and legal studies programs must integrate AI literacy, applied AI skills, and ethical instruction into curricula. By leveraging experiential learning, interdisciplinary collaboration, AI-driven simulations, and critical inquiry, institutions can produce graduates who are both technically competent and ethically grounded, ready to navigate the evolving legal profession. - Journal Article1 May 2026
AI-assisted Case Conceptualization: Enhancing Ethical Decision-making in Graduate Counseling Education
As artificial intelligence (AI) is increasingly integrated into counselor education, a significant gap exists between the rapid adoption of technology and the development of structured pedagogical frameworks for ethical decision-making. This article introduces a multi-component framework to support ethical AI integration in graduate counseling education, comprising three key elements: (1) a case conceptualization model with AI assistance, (2) Morgan (SC), an intentionally imperfect AI school counseling thought partner trained on ethical standards and decision-making models, and (3) structured protocols for ethical decision-making aligned with American Counseling Association and National Board for Certified Counselors guidance. The framework is designed to center human judgment, cultural responsiveness, and professional values, leveraging AI to prompt reflection, generate alternative perspectives, and highlight ethical and contextual considerations. The framework is conceptually situated within a graduate-level internship course and informs instructional design and reflective learning practices. This article presents a practice-informed model for ethical AI integration. - Journal Article1 May 2026
Artificial Intelligence in Dental Education: A Literature Review of Global Adoption, Pedagogical Outcomes, and Ethical Implications
Background: Artificial intelligence (AI) is revolutionizing many fields by enabling machines to accomplish tasks that previously required human intelligence, such as learning, decision-making, and problem-solving. In dentistry, AI is increasingly applied to diagnostics, treatment planning, and clinical training. Its integration enhances educational experiences for students while supporting more accurate and efficient patient care. Objective: This review synthesizes recent research on AI in dental education, highlighting global adoption trends and key pedagogical, ethical, and practical considerations. Conclusion: AI has significant potential to enhance dental education through innovative teaching, clinical training, and data-driven decision-making. Effective integration depends on institutional readiness, ethical oversight, and stakeholder engagement. Evidence-based strategies, guided by theoretical frameworks, are crucial for supporting curriculum development, faculty training, and the responsible adoption of AI globally. - Journal Article1 May 2026
Artificial Intelligence Tools and Job Performance Among Secondary School Administrators
This study investigated the relationship between Artificial Intelligence (AI) tools and job performance among secondary school administrators in Egbedore and Osogbo Local Governments, Osun State, Nigeria. Specifically, the study assessed the extent of AI tools usage, the relationship between AI tools usage and administrators’ job performance and differences in AI tools usage between public and private secondary school administrators. The study was motivated by the growing expectation for school administrators to improve administrative effectiveness through digital technologies. A descriptive survey research design was adopted, involving 252 respondents comprising 162 administrators and 90 teachers drawn from 18 secondary schools (nine schools from each local government). Nine administrators were purposively selected from each school based on their administrative roles, while five teachers were randomly selected per school to assess the school administrative job performance in relation to AI-support practices. Data were collected using two validated instruments: the Artificial Intelligence Usage and Job Performance of Secondary School Administrators Questionnaire (AIJPSSAQ) and the Administrator Job Performance Scale (AJPS), with reliability coefficients of 0.82 and 0.87, respectively. Data were analyzed using descriptive statistics, linear regression, and an independent samples t-test at the 0.05 level of significance. Findings indicated that administrators reported a high level of AI tools usage (M=2.79), while teachers perceived AI-related administrative practices of schools positively (M=3.22). A significant positive relationship was found between AI tools usage and administrators’ job performance. In addition, private school administrators reported significantly higher AI tools usage than their public school counterparts, with a significant mean difference (MD = 0.67).The study concludes that AI tools usage is significantly associated with administrators’ job performance and recommends enhanced AI capacity building and infrastructural support, particularly in public secondary schools. - Journal Article1 May 2026
Assessing the Effectiveness of AI-Based Adaptive Learning Systems in Higher Education
The integration of artificial intelligence (AI) in education is transforming teaching and learning by enhancing outcomes and personalizing learning experiences. This study investigates the effectiveness of AI-based adaptive learning systems in higher education using a quantitative research design involving 500 students from five institutions. The primary goal is to assess the impact of these systems on academic performance, student engagement, and retention rates. Data were collected through surveys and academic records, comparing students using adaptive learning systems to those in traditional classroom environments. Academic performance of students utilizing AI systems demonstrated significant improvement in grades compared to peers in conventional setups. Engagement, increased participation, and motivation were reported among students using adaptive technologies. Retention rates institutions saw higher retention rates among students who engaged with AI-driven systems. Challenges include technical barriers, initial costs of implementation, and resistance to change among educators and students. Recommendations focus on training educators, ensuring equitable access to technology, and fostering institutional support for AI adoption. The findings underscore the potential of AI to revolutionize education by tailoring learning experiences to individual needs. These insights provide a roadmap for educators and policymakers to optimize the integration of AI in higher education.
Most Popular Articles
- Journal Article1 May 2026
- Journal Article1 May 2026
The Integrity Paradox: Reflections on Epistemic Substitution and the Ethical Failure of Plagiarism Detection Systems
This article critiques the ethical authority granted to AI plagiarism detection systems, using humor to expose a serious contradiction in these algorithms. Through a case in which an original ethics manuscript is labeled 40.7% “non-original,” the authors argue that similarity scores are mistaken for judgments of misconduct. They introduce the concept of “epistemic substitution” to describe how tools that both judge originality and offer AI rewrites replace human authorship while mandating human accountability. The paper contends that this collapse of roles undermines scholarly integrity, conflates disciplinary fluency with plagiarism, and shifts ethical responsibility from humans to procedures. The authors call for contextual, human-centered oversight of AI-assisted evaluation. - Journal Article1 May 2026
You Are Me, and I Am You: Bias, AI, and the Academic Self
Being black, brown, caramel, immigrant, French speaking, divorced, mother of six, economically disadvantaged, neurodivergent, foster care graduate, survivor of abuse, child of divorce, and health-impacted person, I’ve often examined the wheel of power and privilege with sadness and dismay. In contrast, being white, catholic, intellectually advantaged, athletic, American, Canadian, middle-class, mathematics mastermind, and Doctor of Education, I’ve needed to examine this wheel fiercely as I come face-to-face with my privilege. Through reflection and self-interrogation, I carefully and imperfectly consider how my bias informs me of my disposition towards others, my educational privileges, and my experience in the world of academia. In this paper, I offer reflections on a specific form of bias from a specific set of people: AI and academics. These reflections serve to vulnerably disclose how I continue to interrogate my bias towards AI and to offer opportunity for other academics to do the same. - Journal Article1 May 2026
Leading with Intentionality: A PreK-12th Grade Public School District's Initial Journey of Ethical Artificial Intelligence Integration
This article chronicles the intentional and evolving approach of Westside Community Schools in Omaha, Nebraska, toward integrating artificial intelligence (AI) into teaching and learning. Grounded in historical parallels to earlier technological shifts such as calculators, the Internet, and search engines, the district emphasizes ethical implementation, transparency, and ongoing professional learning rather than restriction or avoidance. Through the development of an AI Task Force, differentiated professional development, and community engagement initiatives, Westside seeks to promote AI literacy while preserving academic integrity and human-centered decision-making. The district’s framework prioritizes safety, equity, and responsible use, positioning AI as a tool to enhance—not replace—critical thinking and creativity. While challenges related to adoption, perception, and rapid technological change remain, Westside’s experience highlights the importance of adaptive leadership, cultural trust, and continuous learning in preparing students for an AI-driven future. - Journal Article1 May 2026
Leading Artificial Intelligence Integration: Trust, Tension, and Decision-Making
Artificial intelligence integration in education is advancing faster than shared trust and understanding are being established. Educational leaders are responding in real-time to questions of risk and efficacy while navigating conditions that are still forming. This article situates artificial intelligence integration within the paradox of educational leadership, identifying trust as the critical condition shaping leaders’ interpretations of the tensions. Leveraging paradox and trust theory, the article explores how competing demands are not problems to be solved, but tensions to be navigated. When trust is present, leaders respond to tension points through both/and sense-making; when trust is absent, decision-making collapses into either/or approaches. The article offers actionable practices for building shared understanding, establishing guardrails, and creating conditions for the integration of reflective, contextually responsive artificial intelligence. - Journal Article1 May 2026
Harnessing AI in Legal Education: Opportunities for Innovation, Leadership, and Student Success
Artificial Intelligence (AI) is increasingly transforming the practice of law, from predictive analytics in policing and algorithmic sentencing to generative AI-assisted drafting and research. Despite this technological shift, legal education remains predominantly doctrinal, inadequately preparing graduates to function effectively in an AI-mediated environment. This paper contends that law and legal studies programs must integrate AI literacy, applied AI skills, and ethical instruction into curricula. By leveraging experiential learning, interdisciplinary collaboration, AI-driven simulations, and critical inquiry, institutions can produce graduates who are both technically competent and ethically grounded, ready to navigate the evolving legal profession.