About

Kristi Shryock is an Associate Professor in the Department of Multidisciplinary Engineering at Texas A&M University. She serves as the Director of the Craig and Galen Brown Engineering Honors Program. She is also affiliated with the Aerospace Engineering faculty. Her contact information includes a phone number (979-458-6842), email (kshryock@tamu.edu), and office location in HRBB 309B. Her professional profile is available on Google Scholar. She is involved in the College of Engineering at Texas A&M University, located in College Station, TX.

Research topics

• Computer Science
• Psychology
• Applied psychology
• Social Science
• Political Science
• Artificial Intelligence
• Medicine
• Data Mining
• Engineering management
• Medical education
• Virology
• Management
• Clinical psychology
• Geography
• Engineering
• Mathematics
• Knowledge management
• Social psychology
• Psychiatry
• Pedagogy
• Operations management

Selected publications

• A Systematic Literature Review on the Pedagogical Implications and Impact of GenAI on Students’ Critical Thinking

  Algorithms · 2026-02-27

  articleOpen accessSenior author

  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.

  PublisherOA PDFDOI

• Engineering the Unexpected: Faculty Strategies for Navigating Academic Disruptions

  2025-11-02

  article

  This research full paper explores how engineering faculty navigate disruptions in academia, focusing on challenges posed by global events, technological shifts, and institutional changes. Using a qualitative design, focus groups were conducted with faculty at a southwestern U.S. R1 university, revealing key themes around resilience, adaptability, and communication. Faculty identified major disruptions such as the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$9 / 11$</tex> terrorist attacks, COVID-19, and technological advances like ChatGPT as pivotal in reshaping student attitudes, instructional practices, and institutional structures. They also cited student-level challenges including mental health and visa issues, as direct reflections of broader societal upheavals. Strategies to address disruptions included fostering open communication, building trust, using technology responsibly, and incorporating leadership training. The study emphasizes embedding these practices into routine operations to create a more agile and future-proof academic environment. Findings offer insights for faculty development and institutional policy making, with future research aimed at broader disciplinary and institutional contexts.

  PublisherDOI

• Applying Generative AI for Thematic Analysis: A Model for Researchers Exploring Qualitative Methods

  SSRN Electronic Journal · 2025-01-01 · 2 citations

  preprintOpen accessSenior author
  PublisherDOI

• Exploring the Role of Generative AI in Developing Durable Skills: An Exploratory Literature Review

  2025-08-21

  articleSenior author
  PublisherDOI

• An Assessment of ChatGPT 4o's Performance on Mechanical Engineering Concept Inventories

  2025-08-21

  article
  PublisherDOI

• Critical Thinking (Mis)conceptions of First-Year Engineering Students

  2025-08-21

  articleSenior author
  PublisherDOI

• Work in progress: Scaffolding faculty success and retention through a learner’s approach to faculty development

  2025-08-21

  article
  PublisherDOI

• Visualizing the Engineering Design Process: Analyzing Visual Representations from K-12 Educators

  2025-08-21

  articleSenior author
  PublisherDOI

• Impact of Generative AI Technologies on Blind and Visually Impaired Students: A Case Study

  2025-04-09 · 1 citations

  articleOpen accessSenior author

  She is also a fellow of the American Society for Engineering Education.She is an experienced educator specializing in student engagement and development of innovative educational practices

  PublisherOA PDFDOI

• Pre-Conference Workshop: Artificial General Intelligence Integration into Engineering Education, a Framework That Balances Technology with Human-Centered Skill Development

  2025-11-02

  articleSenior author

  As engineering education advances in alignment with Industry 5.0, institutions face increasing pressure to adapt their curricula to emerging technologies without compromising foundational competencies such as creativity, ethical reasoning, and adaptability. This workshop introduces the Artificial General Intelligence Integration into Engineering Education (AGIIEE) Framework, a structured approach to support educators in effectively incorporating AI-driven tools while preserving and enhancing human-centered skills. The workshop equips participants with actionable strategies, ethical frameworks, and practical tools for leveraging AI to personalize learning, support interdisciplinary collaboration, and maintain inclusive, human-centric pedagogies. Through interactive activities, case-based discussions, and structured feedback sessions, attendees will co-develop innovative approaches to AI integration.

  PublisherDOI

Frequent coauthors

• Jacques Richard

  Texas A&M University

  94 shared

• John Whitcomb

  Mitchell Institute

  82 shared

• John E. Angarita

  Virginia Tech

  81 shared

• L. Collins

  Mitchell Institute

  81 shared

• Trini Balart

  34 shared

• Jeffrey E. Froyd

  Texas A&M University

  33 shared

• Tracy Hammond

  Mitchell Institute

  28 shared

• Arun R. Srinivasa

  26 shared