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Atmospheric Water Generation: Bacterial And Inorganic Chemical Quality, Garrett E. Stanley
Atmospheric Water Generation: Bacterial And Inorganic Chemical Quality, Garrett E. Stanley
Theses and Dissertations
This study investigated the quality of untreated water collected from a vapor compression-based atmospheric water generator (AWG) operated outdoors in Dayton, Ohio. The concentrations of bacterial and chemical constituents were determined. The concentration of culturable bacteria was between 200 and 2300 CFU/mL, significantly higher than the reference levels described in recreational and drinking water quality guidance. Three discrete bacteria phenotypes were visually identified; two were yellow in color, rod-shaped and gram-negative while the third was milky white, circular, and gram-positive. Chemical analysis on 15 randomly selected samples revealed the presence of Barium (average = 0.16 mg/L), Magnesium (0.08 = mg/L), …
Material Classification With Spectropolarimetric Lidar, Alexander J. Watson
Material Classification With Spectropolarimetric Lidar, Alexander J. Watson
Theses and Dissertations
A method for characterizing unknown targets using a hyperspectral polarimetric light detection and ranging (LiDAR) system is presented. Light reflected from manmade objects tends to be more polarized than light reflected from objects in the natural world. As such, polarization measurements can be used in remote sensing applications to differentiate artificial and natural objects. Previous works have attempted to characterize objects through passive polarimetric imagery. Methods developed by Cain and Lemaster and Cunningham facilitate reconstruction of the Stokes Vector from returning light. Martin used multispectral polarimetry to classify targets when the angle of incidence (AOI) is close to 0º. Here, …
Evaluating The Performance Of Conformal Prediction Generated Uncertainty Sets In Robust Optimization, Zion C. Johnson
Evaluating The Performance Of Conformal Prediction Generated Uncertainty Sets In Robust Optimization, Zion C. Johnson
Theses and Dissertations
Uncertainty is a major challenge in optimization, especially in problems where unpredictable costs impact decision-making. Robust optimization addresses this by modeling uncertainty via uncertainty sets. These sets are then used such that solutions hold under worst-case scenarios, with success depending on the accuracy of the uncertainty sets. This research examines the use of conformal prediction to construct uncertainty sets for RO, an approach that has not been widely explored. We test split and full conformal prediction in a robust optimization minimum cost flow problem, and comparing them to interval-based and normal-based ellipsoidal uncertainty sets. Experiments run across different network structures …
A Reinforcement Learning Approach For Maneuvering And Firing Decisions In Sead Operations, Nathaniel Garcia
A Reinforcement Learning Approach For Maneuvering And Firing Decisions In Sead Operations, Nathaniel Garcia
Theses and Dissertations
The integration of automated processes in defense continues to expand, enhancing the lethality of military forces. Artificial intelligence accelerates decision-making cycles, removes the constraints of human-operated hardware, and improves coordination by enabling seamless integration across multiple systems. Suppression of Enemy Air Defenses (SEAD) missions are critical to the United States (U.S.) military, as they neutralize hostile air defense systems, ensuring air superiority and enabling safe and effective operations for aircraft in contested environments. Therefore, it is necessary to pair emerging autonomous capabilities with an important mission set in defense. This research investigates the Autonomous Unmanned Air-to-Ground Strike (AUAGS) problem, modeling …
Machine Learning Techniques To Predict Solar Particle Events And Radiation Of Aircrew, Haley Traub
Machine Learning Techniques To Predict Solar Particle Events And Radiation Of Aircrew, Haley Traub
Theses and Dissertations
Solar Particle Events (SPEs) are high-energy phenomena from the Sun that pose risks to technology, human health, and Air Force operations. Accurate prediction of SPEs exceeding 100 MeV is crucial for mitigating these risks. This thesis explores using Bayesian statistical models to predict such events, integrating prior knowledge from solar physics with the ability to update predictions based on new data. The research uses a dataset spanning three solar cycles (21–23) and incorporates attributes like flare fluence, peak flux, latitude, longitude, and class. Four Bayesian models (PyMC, Bnlearn, and two Dredge models) were compared to machine learning models. The Bayesian …
Symbology Detection And Numerical Recognition For T-38 Heads-Up Display Recordings, Ben T. Hepner
Symbology Detection And Numerical Recognition For T-38 Heads-Up Display Recordings, Ben T. Hepner
Theses and Dissertations
The extraction of symbology and numerical data from the T-38 Heads-Up Display (HUD) enhances post-flight analysis and supports real-time decision-making. This research develops a deep learning pipeline using YOLO-based object detection and Optical Character Recognition (OCR) to analyze HUD video data. Model evaluations showed mAP0.5:0.95 ranging from 0.422 (YOLOv11m, hard test set) to 0.696 (YOLOv8m, medium test set), demonstrating robust symbology detection. Numeric detection performed well (mAP0.5:0.95 = 0.764), but OCR struggled with glare and resolution limitations, achieving a recognition accuracy of 17.35%. These results validate deep learning for HUD data extraction but highlight the need for improved robustness …
Air-Based Chemical Patient Decontamination Methodologies For Arctic Regions Using Methly Salicylate As A Chemical Agent Surrogate On A Litter-Bound Manikin, Marcus D. Shadd
Theses and Dissertations
This study evaluated a mobile air shower for patient decontamination without disrobing or rinsing, an alternative for Arctic conditions where water is scarce. A manikin in extreme cold weather gear was exposed to 10 µL of methyl salicylate (MeS), a sulfur mustard surrogate, and placed in a horizontal chamber on a military litter. Airborne MeS was measured using a ppbRAE 3000 detector to assess inhalation risk for the patient and decontamination team. Three methods were tested: an air-knife system, paper towels, and no decontamination, with 10 trials each (30 total). ANOVA analysis showed significant reductions in airborne MeS with air-knife …
Transfer Efficiencies Of Surface-To-Surface Transport Of Micron-Sized Actinide Surrogate Particles, Austin R. Powell
Transfer Efficiencies Of Surface-To-Surface Transport Of Micron-Sized Actinide Surrogate Particles, Austin R. Powell
Theses and Dissertations
Particle effluent of varying sizes is released during routine activities within laboratory environments and these particles can come in contact with a wide range of surfaces. Particles of micron size or smaller can be especially pervasive and can transfer between multiple subsequent surfaces, leading to the progressive contamination of a laboratory. Understanding the transport dynamics of micron sized particles will help inform facility personnel of the possibility of contamination by these potentially hazardous materials of interest. In this research, the transfer efficiency of micron sized surrogate actinide particles (Europium-doped Gadolinium Oxysulfide (EGOS)) is measured for multiple materials, between two particle …
Implications Of Magnetic Evolution On Coronal Loop Thermal Variation Prior To Solar Flares, Kara L. Kniezewski
Implications Of Magnetic Evolution On Coronal Loop Thermal Variation Prior To Solar Flares, Kara L. Kniezewski
Theses and Dissertations
Solar flares are intense bursts of electromagnetic radiation, which occur due to a rapid destabilization and reconnection of the magnetic field. While flares are a magnetic phenomena, very little attention has been paid to thermal conditions in the corona prior to flare onset. This study serves as a follow-on to Kniezewski et al., 2024, where the EUV emission from coronal loops was observed to vary substantially and without any coherence between channels before 53 off-limb flares. These variations suggest multiple mechanisms within the coronal magnetic field are responsible for heating fluctuations. Here, the 3D magnetic field is modeled using a …
Reflected Laser Light As A Diagnostic Insight For Femtosecond Laser-Plasma Coupling, David S. Stiles
Reflected Laser Light As A Diagnostic Insight For Femtosecond Laser-Plasma Coupling, David S. Stiles
Theses and Dissertations
High-energy laser technology is critical for military, scientific, and industrial applications, but traditional mixed-radiation facilities are hindered by cost, scheduling constraints, and lack of portability. A high-repetition-rate, cost-effective alternative is needed to meet evolving application needs and timelines. This study investigates changes in reflected laser intensity to diagnose coupling efficiency and optimize energetic particle generation in ultraintense laser-target interactions. Using an ultraintense 35 femtosecond, 9 - 12 mJ laser and a deuterated water target, reflected laser light was captured via high-resolution imaging, while energetic electron and X-ray data were collected using a custom spectrometer and ion chamber, respectively. Statistical analysis …
Universal Model Based Systems Engineering Rendezvous And Proximity Operations Mission Planner, Thomas J. Kelly
Universal Model Based Systems Engineering Rendezvous And Proximity Operations Mission Planner, Thomas J. Kelly
Theses and Dissertations
This thesis addresses the fragmentation and inefficiencies in current Rendezvous and Proximity Operations (RPO) mission planning by developing an integrated Model-Based Systems Engineering (MBSE) framework. The research explores the design and implementation of RPO missions using System Modeling Language (SysML) and Matlab-based physics simulation to improve mission planning processes. Key objectives include the standardization of mission requirement characterization, the development of evaluation criteria for mission plans, and the implementation of iterative design methods to refine RPO strategies. The study leverages the Hill-Clohessy-Wiltshire (HCW) equations for initial mission planning, incorporating rigid-body attitude control with properties generated from the physical description, and …
Learning To Dogfight: Proximal Policy Optimization Vs. Double Deep Q Network For 2v2 Air Combat With Directed Energy Weapons In Afsim, Caden W. Wilson
Learning To Dogfight: Proximal Policy Optimization Vs. Double Deep Q Network For 2v2 Air Combat With Directed Energy Weapons In Afsim, Caden W. Wilson
Theses and Dissertations
This research utilizes reinforcement learning (RL) to train two blue agents each imbued with a directed energy weapon (DEW) in a 2v2 within visual range air combat maneuvering problem. A phased solution approach is employed to repeatedly tune and train several RL algorithm implementations: Proximal Policy Optimization (PPO) and Double Deep Q Network (DDQN). Phase I of training includes reward shaping for basic flight elements such as altitude, airspeed, and target proximity. Phase II of training builds off policies developed in Phase I, but rewards emphasize winning the aerial engagement by any means necessary. DDQN significantly outperforms PPO in Phase …
Numerical Studies Of Semiclassical Light Storage Using The Coherent Atomic Transfer Function, Zachary T. Johnson
Numerical Studies Of Semiclassical Light Storage Using The Coherent Atomic Transfer Function, Zachary T. Johnson
Theses and Dissertations
Quantum communication through photons relies on photonic storage to preserve quantum states. However, when photons interact with matter, quantum information becomes distorted. A recently developed semi-classical analytical model predicts output light pulses from an electromagnetically induced transparency (EIT) system. Using the predictions, the model known as the Coherent Atomic Transfer (CAT) Function, is capable of predicting the stored pulse or reconstructing the original pulse. Using numerical convolution and deconvolution with the CAT function as an analog of the point spread function of Fourier optics can provide insights on the effects of EIT storage on the retrieved pulse. Blind deconvolution is …
Correlating Aerosol Morphology And Optical Properties With Image Blur: An Investigation Of Aerosol-Induced Image Degradation, Patricia A. Byrd
Correlating Aerosol Morphology And Optical Properties With Image Blur: An Investigation Of Aerosol-Induced Image Degradation, Patricia A. Byrd
Theses and Dissertations
Small-angle scattering by relatively large cloud/fog droplets and ice crystals is known to degrade imagery. However, it is not well investigated how much of an impact aerosols, especially the prevalent anthropogenic fine/ultra-fine/coarse particles, have in image degradation. This thesis explores the contribution of aerosols to image blur but focuses on collecting field data with a relatively large variety of ambient aerosol characterization and optical instrumentation. Field experiments were conducted over six days, correlating aerosol measurements (particle counters and nephelometer) with image quality from a visible camera along a 450m path. Image blur was quantified using the Modulation Transfer Function (MTF), …
Event-Based Camera Simulation And Neural Network Processing For Autonomous Aerial Refueling, Stephanie C. Hanson
Event-Based Camera Simulation And Neural Network Processing For Autonomous Aerial Refueling, Stephanie C. Hanson
Theses and Dissertations
Event-based cameras excel in dynamic environments, and do not face challenges like washout and motion blur, like a frame-based camera. This work describes the process used to collect the first EBS data collect for use in AAR, and develops an event simulator to generate synthetic training data for evaluating CNN architectures on asynchronous data. The three models compared are a traditional CNN, a YOLO-based CNN, and an asynchronous sparse CNN. The YOLO-based model achieved the best accuracy, while the sparse CNN, despite being less optimized, maintained an average IoU of 0.9. These results highlight the potential of asynchronous approaches for …
Grassmannian Codes From Stratified Frames, William J. Brinkley
Grassmannian Codes From Stratified Frames, William J. Brinkley
Theses and Dissertations
An equichordal tight fusion frame (ECTFF) is a finite sequence of equi-dimensional subspaces of a Euclidean space that achieves equality in Conway, Hardin and Sloane's simplex bound. Every ECTFF is an optimal Grassmannian code with respect to the chordal distance. We introduce a method for constructing an ECTFF from any finite sequence of unit norm tight frames that happen to be stratified in a certain sense. We moreover show how to construct stratified unit norm tight frames from a difference family for a finite abelian group, as well as from a suitable combination of a resolvable balanced incomplete block design …
Heterogeneous Boid Swarm Performance Under Environmental And Neighbor Communication Link Variability, Jonathan C. Oxborrow
Heterogeneous Boid Swarm Performance Under Environmental And Neighbor Communication Link Variability, Jonathan C. Oxborrow
Theses and Dissertations
Artificial swarms are of growing interest in numerous fields and use cases. As their utilization increases drones and robots with different capabilities will be required to coordinate for task completion thus creating heterogeneous swarms. Swarm individuals generally communicate with all neighbors inside their sensor range generating a significant amount of message traffic. Previous research of a heterogeneous group in a non-physical environment has shown that restricting communication to only one neighbor of each different capability maintained performance. This work applies that finding to a heterogeneous boid swarm with the addition of varied environmental conditions. The swarm is comprised of three …
Quantum Ghost Imaging Through An Atmospheric Turbulence Simulator, Mikaela R. Morris
Quantum Ghost Imaging Through An Atmospheric Turbulence Simulator, Mikaela R. Morris
Theses and Dissertations
The use of single photons and photon pairs has become a cornerstone for new developments in the sensing and imaging community for their ability to improve image resolution and signal to noise readings in low light environments and large standoff distances. Quantum imaging techniques have an ability to overcome the fundamental limits of classical imaging, like diffraction. Quantum ghost imaging, a specific type of quantum imaging, uses a bi-photon pair produced during the process of spontaneous parametric down conversion to produce an image. The pair is split using a beam splitter, the signal photon is transmitted through an aperture and …
Adiabatic And Overall Effectiveness Superposition Theory For Upstream Phantom Cooling On A Film Cooled Leading Edge, Nathaniel J. Stout
Adiabatic And Overall Effectiveness Superposition Theory For Upstream Phantom Cooling On A Film Cooled Leading Edge, Nathaniel J. Stout
Theses and Dissertations
Film cooling experimentation aims to improve the cooling performance while minimizing the amount of coolant flow redirected from the compressor. The coolant flow that is used for film cooling reduces the maximum thrust any gas turbine engine can produce. Finding creative ways to improve cooling performance without increasing the amount of coolant used, like phantom cooling, is essential for the gas turbine industry to improve engine performance while increasing turbine components’ lifespan. Phantom cooling refers to any secondary cooling effect that propagates downstream from its original cooling application to cool subsequent turbine components. Phantom cooling is actively gaining more attention …
Approximating Three-Body Trajectories With A Knot Theory Inspired Model For Orbit Generation And Determination, Mason R. Mill
Approximating Three-Body Trajectories With A Knot Theory Inspired Model For Orbit Generation And Determination, Mason R. Mill
Theses and Dissertations
This thesis explores a novel approach to approximating three-body trajectories using a knot theory-inspired model for orbit generation and determination. Traditional methods for solving the Circular Restricted Three-Body Problem (CR3BP) rely on numerical integration and correction schemes to generate trajectories, often requiring iterative refinements. This research investigates the application of knot theory principles—such as torus knots, Alexander polynomials, and Reidemeister moves—to categorize and model complex orbital trajectories in the CR3BP. By leveraging these mathematical tools, the study aims to enhance trajectory prediction, orbit determination, and mission planning for spacecraft operating in the cislunar environment. The results demonstrate that knot theory …
Misalignment Uncertainty In Near-Field Thz Scattering Experiments, Philip Patterson
Misalignment Uncertainty In Near-Field Thz Scattering Experiments, Philip Patterson
Theses and Dissertations
This research investigates the effect of misalignment on the near-field scattering of cylinders in the 550-700 GHz frequency band. A Type-1 calibration is performed on previously collected data, using a near-field physical optics solution to simulate scattering at various positions and orientations. The alignment of the cylinders at the time of measurement is predicted by comparing the range profiles of the theoretical and calibrated responses. The data with the most similar range profiles had a mean calibration difference metric of -2.78 dB and a standard deviation of -0.57 dB, demonstrating the presence of sources of error that are dominant over …
An Analytical Approach In Solving A Two-On-One Pursuit Evasion Differential Game With Fast Evader And No-Point Capture, Nathan T. Morrow
An Analytical Approach In Solving A Two-On-One Pursuit Evasion Differential Game With Fast Evader And No-Point Capture, Nathan T. Morrow
Theses and Dissertations
This paper is concerned with a co-planar pursuit-evasion scenario where two Pursuers (P) are after an Evader (E). The players are holonomic/can turn on a dime and their speeds, VP and VE, are constant, but the evader is faster than the pursuers, that is, the speed ratio parameter μ = VE/VP > 1. The Pursuers are endowed with a circular capture disc whose radius l > 0. A differential game (DG) with three states and one parameter is addressed through geometric and analytical methods where a partial solution is outlined and visualized. The game is split …
Analyzing Lf/Vlf Lightning Waveforms To Estimate D-Region Electron Density Profiles: Process, Application, And Comparison, William R. Smith
Analyzing Lf/Vlf Lightning Waveforms To Estimate D-Region Electron Density Profiles: Process, Application, And Comparison, William R. Smith
Theses and Dissertations
Lightning waveforms in the low frequency (LF; 30-300 kHz) and the very low frequency (VLF; 3-30 kHz) can be exploited to produce data-driven ionospheric Dregion electron density profile (EDP) estimates with significantly higher spatial and temporal coverage than previously available. The lightning waveforms used in this paper are signals detected in the LF/VLF of negative cloud-to-ground lightning by the Earth Networks Total Lightning Detection Network. Each waveform contains a ground wave and a time-delayed ionospheric reflection. The time delay between the ground wave and ionospheric reflection has previously been used to estimate a single specular reflection altitude, where LF/VLF emissions …
A Standardized Methodology For Evaluating A Digital Badging System [ Data Package ], Benjamin T. Pederson, Mark G. Reith, Ralucca Gera, David S. Long, Edward D. White, Jonathan Zemmer
A Standardized Methodology For Evaluating A Digital Badging System [ Data Package ], Benjamin T. Pederson, Mark G. Reith, Ralucca Gera, David S. Long, Edward D. White, Jonathan Zemmer
Faculty Publications
Digital badges, a form of micro-credentials, have grown in popularity over the past decade. However, few standard processes exist to assess the potential of digital badging systems within an organization. This study proposes a generalizable methodology for comparing a badging system with other methods of recording skills and competencies. The experimental design is tested using the military's cyber operations community as the target organization. Finally, mixed-method data from thirty-six participants is analyzed in accordance with the methodology. Based on the results, digital badging systems are perceived to be more valuable and usable than a current method of military talent management. …
Convergent Close-Coupling Approach To Electron Scattering On H3+ : Scattering Dynamics And Dissociative Processes, Reese K. Horton, Michael V. Pak, Igor Bray, Dmitry V. Fursa
Convergent Close-Coupling Approach To Electron Scattering On H3+ : Scattering Dynamics And Dissociative Processes, Reese K. Horton, Michael V. Pak, Igor Bray, Dmitry V. Fursa
Faculty Publications
Cross sections for electron impact dissociative excitation and ionization in scattering on vibrationally excited levels of the ground electronic state of H3+, D3+, and T3+ are reported in the energy range of 8–1000 eV. Calculations have been performed using a newly developed version of the molecular convergent close-coupling code. Convergence of the cross sections with the size of the projectile partial-wave and close-coupling expansions is examined. Branching ratios and cross sections for the yields of D2+ and D+ from dissociative excitation of D3+ are presented and isotope …
Convergent Close-Coupling Approach To Electron Impact Dissociation Of The Polyatomic Molecule H 3 + And Its Isotopologues, Reese K. Horton, Michael V. Pak, Igor Bray, Dmitry V. Fursa
Convergent Close-Coupling Approach To Electron Impact Dissociation Of The Polyatomic Molecule H 3 + And Its Isotopologues, Reese K. Horton, Michael V. Pak, Igor Bray, Dmitry V. Fursa
Faculty Publications
Cross sections for electron impact dissociative excitation and ionization in scattering on vibrationally excited levels of the ground electronic state of H3+ and its isotopologues are reported in the energy range of 8 to 1000 eV. Calculations have been performed using a newly developed version of the molecular convergent close-coupling code. Cross sections for total dissociative excitation, ionization yielding atomic fragments such as D+, and the total inelastic cross section are presented. Good agreement with available experiments has been demonstrated.
Accelerated Multiobjective Calibration Of Fused Deposition Modeling 3d Printers Using Multitask Bayesian Optimization And Computer Vision, Craig S. Ganitano, Benji Maruyama, Gilbert L. Peterson
Accelerated Multiobjective Calibration Of Fused Deposition Modeling 3d Printers Using Multitask Bayesian Optimization And Computer Vision, Craig S. Ganitano, Benji Maruyama, Gilbert L. Peterson
Faculty Publications
Proper process parameter calibration is critical to the success of fused deposition modeling (FDM) three-dimensional (3D) printing, but is time-consuming and requires expertise. While existing systems for autonomous calibration have demonstrated success in calibrating for a single objective, users may need to balance multiple conflicting objectives. Herein, an easily deployable, camera-based system for autonomous calibration of FDM printers that optimizes for both part quality and completion time is presented. Autonomous calibration is achieved through a novel, multifaceted computer vision characterization and a multitask learning extension to Bayesian optimization. The system is demonstrated on four popular filament types using two distinct …
Display System Interface Using Visually-Evoked Cortical Potentials, Michael E. Miller, Brett J. Borghetti, Kellie D. Kennedy, Chad L. Stephens, Alan T. Pope
Display System Interface Using Visually-Evoked Cortical Potentials, Michael E. Miller, Brett J. Borghetti, Kellie D. Kennedy, Chad L. Stephens, Alan T. Pope
AFIT Patents
A brain-computer interface system includes a video processor for producing a display signal, a temporal controller for producing a plurality of repetitive visual stimulus (RVS) signals with different respective temporal aspects, a display device that receives the display signal and displays a corresponding image on a plurality of different display regions and receives the RVS signals and displays corresponding RVS in respective ones of the display regions, an electroencephalographic (EEG) sensor for sensing a visually-evoked cortical potential (VECP) signal in a user with eyes fixated on a viewed one of the display regions, and a VECP processor for processing the …
Afit Generative Ai Teaching Guidebook, Afit Faculty Learning Community, Mark G. Bateman, Brett J. Borghetti, Allen W. Dukes, Nicholas C. Francis, Mike Frick, Bobbie Oh, Kevin Patterson, Hiren J. Patel, Mark G. Reith, Erick S. Tyndall, Teresa M. Walton, Torrey J. Wagner, Timothy S. Wolfe, Jonathan Zemmer
Afit Generative Ai Teaching Guidebook, Afit Faculty Learning Community, Mark G. Bateman, Brett J. Borghetti, Allen W. Dukes, Nicholas C. Francis, Mike Frick, Bobbie Oh, Kevin Patterson, Hiren J. Patel, Mark G. Reith, Erick S. Tyndall, Teresa M. Walton, Torrey J. Wagner, Timothy S. Wolfe, Jonathan Zemmer
AFIT Documents
AFIT is proud to highlight the Generative AI Teaching Guidebook, a resource designed to provide military educators with practical insights, strategies, and use cases for integrating Generative AI (Gen AI) into their teaching practices. Developed through a collaborative effort involving AFIT faculty across various departments within the Graduate School of Engineering and Management and the School of Systems and Logistics, this digital resource serves as a starting point for educators exploring how to leverage Gen AI in their classrooms. It offers accessible examples and best practices, ensuring utility for instructors of all technical backgrounds. The guidebook provides a comprehensive overview …
Afit Generative Ai Teaching Guidebook Synopsis, Afit Faculty Learning Community, Mark G. Bateman, Brett J. Borghetti, Allen W. Dukes, Nicholas C. Francis, Mike Frick, Bobbie Oh, Kevin Patterson, Hiren J. Patel, Mark G. Reith, Erick S. Tyndall, Teresa M. Walton, Torrey J. Wagner, Timothy S. Wolfe, Jonathan Zemmer
Afit Generative Ai Teaching Guidebook Synopsis, Afit Faculty Learning Community, Mark G. Bateman, Brett J. Borghetti, Allen W. Dukes, Nicholas C. Francis, Mike Frick, Bobbie Oh, Kevin Patterson, Hiren J. Patel, Mark G. Reith, Erick S. Tyndall, Teresa M. Walton, Torrey J. Wagner, Timothy S. Wolfe, Jonathan Zemmer
AFIT Documents
The main objective of this work was to bring together various perspectives on how to envision incorporating Gen AI capabilities into the learning environment and identify some best practices for their implementation. Any instructor who is interested in these capabilities but does not necessarily have a technical background can find pragmatic use of the examples provided. While the examples have a wide range of applicability, they are meant to serve as a starting point for educators to explore what would be beneficial to their educational environment, from traditional classroom settings to online continuing education courses.