Adapting the Turing Test for Embodied Neurocognitive Evaluation of Biologically-Inspired Cognitive Agents. - Shane T. Mueller; Brandon S. Minnery (AAAI Fall Symposium: Biologically Inspired Cognitive Architectures, 2008)

Preface: Toward a Growing Computational Replica of the Human Mind. - Alexei V. Samsonovich; Shane T. Mueller (AAAI Fall Symposium: Biologically Inspired Cognitive Architectures, 2008)

Preface. - Alexei V. Samsonovich; David C. Noelle; Shane T. Mueller (AAAI Fall Symposium: Biologically Inspired Cognitive Architectures, 2009)

Cultural variations in collaborative decision making: driven by beliefs or social norms? - Winston R. Sieck; Shane T. Mueller (IWIC, 2009)

The calibration of trust in an automated system: A sensemaking process. - Corey K. Fallon; Anne K. G. Murphy; Laura Zimmerman; Shane T. Mueller (CTS, 2010)

Tutorial on using the Psychology Experiment Building Language (PEBL) in the laboratory, the field, and the classroom. - Shane T. Mueller (CogSci, 2011)

Adapting the task-taxon-task methodology to model the impact of chemical protective gear. - Shane T. Mueller; Benjamin Simpkins; George Anno; Corey K. Fallon; Owen Price; Gene E. McClellan (Comput. Math. Organ. Theory, 2011)

Improving Users' Mental Models of Intelligent Software Tools. - Shane T. Mueller; Gary Klein (IEEE Intell. Syst., 2011)

An Exploration of Crossword Skill. - Kejkaew Thanasuan; Shane T. Mueller (CogSci, 2012)

Improving Lexical Memory Access and Decision Making Processes Using Cognitive Word Games. - Kejkaew Thanasuan; Shane T. Mueller (CogSci, 2015)

Development of the PEBL Traveling Salesman Problem Computerized Testbed. - Shane T. Mueller; Brandon S. Perelman; Yin-Yin Tan 001; Kejkaew Thanasuan (J. Probl. Solving, 2015)

Evaluating path planning in human-robot teams: Quantifying path agreement and mental model congruency. - Brandon S. Perelman; Shane T. Mueller; Kristin E. Schaefer (CogSIMA, 2017)

Explaining Explanation, Part 2: Empirical Foundations. - Robert R. Hoffman; Shane T. Mueller; Gary Klein (IEEE Intell. Syst., 2017)

The Tracer Method: The Dynamic Duo Combining Cognitive Task Analysis and Eye Tracking. - Kaitlyn M. Roose; Elizabeth S. Veinott; Shane T. Mueller (CHI PLAY (Companion), 2018)

Testing the effectiveness of crossword games on immediate and delayed memory for scientific vocabulary and concepts. - Shane T. Mueller; Elizabeth S. Veinott (CogSci, 2018)

Equality in Dictator Games: Methodological Concerns in Interpreting Default-Mode Strategies and Norms for Equity. - Caden Sumner; Samantha Verran; Shane T. Mueller (CogSci, 2018)

Metrics for Explainable AI: Challenges and Prospects. - Robert R. Hoffman; Shane T. Mueller; Gary Klein; Jordan Litman (CoRR, 2018)

Explaining Explanation, Part 4: A Deep Dive on Deep Nets. - Robert R. Hoffman; Tim Miller 001; Shane T. Mueller; Gary Klein; William J. Clancey (IEEE Intell. Syst., 2018)

Cognitive perspectives on opinion dynamics: the role of knowledge in consensus formation, opinion divergence, and group polarization. - Shane T. Mueller; Yin-Yin (Sarah) Tan (J. Comput. Soc. Sci., 2018)

What makes a good explanation? Cognitive dimensions of explaining intelligent machines. - Roberto Confalonieri 001; Tarek R. Besold; Tillman Weyde; Kathleen Creel; Tania Lombrozo; Shane T. Mueller; Patrick Shafto (CogSci, 2019)

Development and Evaluation of a Model of Human Comfort and Cognitive Ability for Moderate Differences in Thermal Environment. - Shane T. Mueller; Yin-Yin (Sarah) Tan; Isaac Flint (HCI (LBP), 2019)

Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of Key Ideas and Publications, and Bibliography for Explainable AI. - Shane T. Mueller; Robert R. Hoffman; William J. Clancey; Abigail Emrey; Gary Klein (CoRR, 2019)

Cognitive Anthropomorphism of AI: How Humans and Computers Classify Images. - Shane T. Mueller (CoRR, 2020)

Explaining AI as an Exploratory Process: The Peircean Abduction Model. - Robert R. Hoffman; William J. Clancey; Shane T. Mueller (CoRR, 2020)

Assessing Clustering Methods to Establish Reliability and Consensus in Card Sorting Tasks. - Lamia Alam; Shane T. Mueller (AHFE (17), 2021)

Collaborative Explainable AI: A Non-algorithmic Approach to Generating Explanations of AI. - Tauseef Ibne Mamun; Robert R. Hoffman; Shane T. Mueller (HCI (44), 2021)

Developing an Adaptive Framework to Support Intelligence Analysis. - Ashley F. McDermott; Elizabeth S. Veinott; Leonard Eusebi; Elizabeth T. Whitaker; Ethan Brantley Trewhitt; Shane T. Mueller; David A. Illingworth; Rick Thomas; Michael R. Dougherty; Sean L. Guarino (HCI (31), 2021)

Principles of Explanation in Human-AI Systems. - Shane T. Mueller; Elizabeth S. Veinott; Robert R. Hoffman; Gary Klein; Lamia Alam; Tauseef Mamun; William J. Clancey (CoRR, 2021)

Examining the effect of explanation on satisfaction and trust in AI diagnostic systems. - Lamia Alam; Shane T. Mueller (BMC Medical Informatics Decis. Mak., 2021)

Examining the Effectiveness of Different Assessments and Forecasts for Accurate Judgments of Learning in Engineering Classes. - Christopher Cischke; Shane T. Mueller (CSEDU (1), 2022)

When Self-Driving Fails: Evaluating Social Media Posts Regarding Problems and Misconceptions about Tesla's FSD Mode. - Anne Linja; Tauseef Ibne Mamun; Shane T. Mueller (Multimodal Technol. Interact., 2022)

Evaluating machine-generated explanations: a "Scorecard" method for XAI measurement science. - Robert R. Hoffman; Mohammadreza Jalaeian; Connor Tate; Gary Klein; Shane T. Mueller (Frontiers Comput. Sci., 2023)

Explainable AI: roles and stakeholders, desirements and challenges. - Robert R. Hoffman; Shane T. Mueller; Gary Klein; Mohammadreza Jalaeian; Connor Tate (Frontiers Comput. Sci., 2023)

Measures for explainable AI: Explanation goodness, user satisfaction, mental models, curiosity, trust, and human-AI performance. - Robert R. Hoffman; Shane T. Mueller; Gary Klein; Jordan Litman (Frontiers Comput. Sci., 2023)

"Minimum Necessary Rigor" in empirically evaluating human-AI work systems. - Gary Klein; Robert R. Hoffman; William J. Clancey; Shane T. Mueller; Florian Jentsch; Mohammadreza Jalaeian (AI Mag., 2023)

Increasing the Value of XAI for Users: A Psychological Perspective. - Robert R. Hoffman; Tim Miller 001; Gary Klein; Shane T. Mueller; William J. Clancey (Künstliche Intell., 2023)

Using LLMs, Knowledge Space Representations and Worked Examples to Support Adaptive Cybertraining in Construction Education. - Shane T. Mueller; Katrina Carlson; Yifan Wang; Xiaoyu Hou; Zaid Alwashah; Hexu Liu; Bo Xiao (HCI (48), 2025)