Critical Thinking (CT) is recognized as a foundational competency for professional readiness, innovation, and ethical reasoning in higher education, enabling students to analyze information, evaluate evidence, and make reasoned decisions in complex environments. The rapid integration of Generative Artificial Intelligence (GenAI) tools, such as large language models, presents new opportunities and risks for CT development. This study conducts a systematic literature review to synthesize empirical evidence on the pedagogical implications and cognitive impact of GenAI on students’ CT. Following PRISMA guidelines, and search terms around GenAI Tools, Critical Thinking And Higher Education, on five major education research databases—Web of Science; Scopus; EBSCOhost (Education Source, ERIC, and APA PsycInfo); and Compendex and Inspec (Elsevier)—63 empirical studies published between January 2023 and April 2025 were analyzed across higher education contexts, disciplines, and intervention designs. Results indicate that GenAI offers notable cognitive affordances, including scaffolding reflective reasoning, promoting self-regulation, and facilitating iterative dialogue and argument evaluation. Pedagogical strategies clustered into four primary integration typologies: AI-based feedback prompts, dialogue simulation and reflection, AI-supported peer review, and critical engagement with AI-generated content. Nearly half of the studies reported statistically significant CT improvements, particularly when GenAI use was guided by structured prompts, reflective activities, and performance-based assessment. However, multiple risks persist, including cognitive offloading, uncritical acceptance of AI outputs, and diminished intellectual autonomy, especially in unguided or surface-level usage. This review highlights the need for intentional pedagogical design, validated CT assessment tools, and longitudinal studies to ensure GenAI acts as a catalyst rather than a substitute for human reasoning. By identifying effective integration strategies and outlining potential pitfalls, this study provides evidence-informed guidance for educators and institutions aiming to responsibly leverage GenAI to strengthen students’ CT skills.

The rapid diffusion of generative artificial intelligence (GenAI) tools such as ChatGPT has unsettled established academic practices related to assessment, authorship, integrity, and disciplinary knowledge production. This qualitative repeated cross-sectional study examines how faculty and staff at a large public research university understood these changes in 2023 and 2024. The analysis draws on responses to the same open-ended survey question collected from independent respondent groups in 2023 (n = 104) and 2024 (n = 313). Responses were analyzed inductively through thematic analysis and subsequently interpreted using Disruptive Innovation Theory and Complex Adaptive Systems Theory. The analysis identified both continuity and change across the two datasets. Responses in 2023 emphasized uncertainty, threats to academic integrity, and defensive assessment redesign. Responses in 2024 more frequently described pedagogical experimentation, process-oriented assessment, and AI literacy as emerging academic and professional competencies. Concerns about authorship, equity, reliability, and inconsistent institutional guidance persisted across both years. The findings suggest that faculty and staff discourse shifted from primarily containing GenAI-related risks toward selectively integrating the technology into teaching and professional practice. However, because the study used independent cross-sectional samples, it does not establish individual change over time. The study contributes a theoretically informed account of institutional sensemaking during the first two years following ChatGPT’s public release and identifies strategies for balancing innovation, integrity, equity, and the human purposes of higher education.

Generative artificial intelligence (GenAI) tools such as ChatGPT have rapidly entered higher education, challenging longstanding norms around authorship, assessment, and disciplinary expertise. While early GenAI scholarship has largely emphasized student outcomes, adoption trends, and academic integrity, comparatively little empirical work has examined how faculty and staff make sense of this disruption over time. Guided by Transformative Learning Theory (TLT) as an interpretive lens for faculty discourse, this qualitative study examines how educators interpret GenAI as a “disorienting dilemma” and how patterns in faculty discourse differ across two cross-sectional cohorts during the first year of widespread adoption. We analyzed open-ended survey responses to the question, “How do you think AI tools like ChatGPT will impact the future of your discipline?” collected at a large U.S. R1 Hispanic-serving public research university. Two cohorts were examined: an early-adoption dataset gathered in 2023 (n = 104) and a follow-up dataset collected in 2024 (n = 313). Using Braun and Clarke’s reflexive thematic analysis procedures, we identified persistent themes and qualitative differences in how participants described GenAI-related concerns and opportunities. No educator-navigation theme differed significantly in proportional prevalence between cohorts. Accordingly, interpretations of cross-cohort differences rest on variations in thematic framing, tone, and illustrative detail rather than on statistically demonstrated temporal change. The 2023 responses more often foregrounded academic-integrity concerns and defensive assessment redesign, whereas the 2024 responses included more concrete descriptions of pedagogical experimentation and potential uses of GenAI to support faculty productivity and professional practice. Across both years, persistent anxieties regarding student dependency, erosion of foundational skills, and the potential dehumanization and homogenization of academic discourse remained salient. These results highlight faculty as active agents engaged in reflection and adaptation and show how aggregate patterns of faculty sensemaking are compatible with early processes described by Transformative Learning Theory. TLT is used here as an interpretive lens for cohort-level faculty discourse, not as evidence that individual instructors underwent internal perspective transformation. This underscores the need for institutionally supported, human-centered approaches to GenAI integration, including policy clarity, sustained faculty development, and communities of practice that enable ethical, reflective experimentation.

With the growing demand for flexible learning environments in higher education, asynchronous online courses have become increasingly popular, particularly among graduate students. This study investigates student preferences and the perceived effectiveness of various learning tools in an asynchronous graduate-level Engineering Economy course. We surveyed students and collected data across different demographics, including age, employment status, and degree level, to understand why they enrolled in asynchronous learning formats and their preferred methods for accessing course materials. Students rated the effectiveness of key learning tools, such as recorded video lectures, online discussion forums, virtual office hours, and interactive assignments, using a Likert scale. Additionally, they provided feedback on challenges faced during the course, including time management, peer interaction, and technical issues. The survey also explored students' overall satisfaction with the flexibility provided by the asynchronous format and their confidence in mastering the course material. The findings aim to offer educators actionable insights into which tools students indicated most effectively enhanced their learning and how the unique challenges of asynchronous education might be addressed. By better understanding student needs and preferences, this research contributes to improving the design and delivery of asynchronous courses, ensuring a learning experience that is both flexible and of high quality. These insights will be crucial for educators seeking to develop more inclusive and effective online learning environments for graduate students, balancing the demands of professional and academic commitments.