Research Publications

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  Learning, Efficacy, and Achievement Framework for Older Adults: A Technology Acceptance Model Approach

  (Georgia Institute of Technology, 2024-08) Gleaton, Emily C.

  Smart Assistive Technologies (SMATS) have the potential to improve the lives of older adults by helping them age in place. Many of these emerging technologies provide a range of benefits that assist older adults with activities of daily living, including improved health management, enhanced safety, and increased social connectivity. For instance, smartphone applications can assist elderly individuals with managing their medications independently, or conversational agent technologies can be used to contact emergency services if a telephone cannot be reached. By leveraging these technologies, older adults can enjoy greater autonomy, maintain their daily routines, and engage more actively in their communities. Despite the potential benefits of SMATS, many older adults struggle to adopt and use them. One potential method to improve the adoption and use of SMATS among older adults is improving the associated instruction and training. From a macroscopic perspective, effective instructional design and training methods could prompt a behavior change that leads to technology adoption, an idea that is supported by the Health Belief Model (HBM; Rosenstock, 1966). This model stands out as one of the foundational health psychology models because it was developed to understand practical problems, such as why people fail to adopt disease prevention measures like tuberculosis screenings (Rosenstock, 1974a). The systems approach to training (W. Rogers et al., 2001) can be applied to develop instructions and training to meet the needs of older adults. The systems approach to developing instructions and training involves identifying the problem domain, the specific tasks, the trainee population, the cost (in terms of time and money), and the resources available (S. Czaja & Sharit, 2013). The systems approach also involves identifying the best modality of instruction to be employed, given the details and context of an application. However, this approach does not integrate technology adoption literature, leaving a critical research gap. To address this gap constructs from the Unified Theory of Acceptance and Use of Technology 2 (UTAUT 2) and the Health Belief Model (HBM) were integrated into the Learning, Efficacy, and Achievement Framework (LEAF). The LEAF was then integrated within the systems approach to developing instructions and training, supplementing it to improve outcomes by addressing the unique challenges and barriers older adults face when adopting and using SMATS. Older adults often encounter specific barriers that younger adults do not experience. Therefore, incorporating insights from technology adoption literature, the LEAF provides a comprehensive framework for developing tailored instructions and training targeting these potential problems. This paper focuses on integrating technology acceptance literature into a framework that can be applied within the systems approach to developing training for older adults. The end goal of using the LEAF within the systems approach is to create an improved instruction and training program that can prompt behavior change, leading to the successful adoption and use of SMATS among older adults. The LEAF has three major components: 1) Learning, 2) Efficacy, and 3) Achievement. Learning incorporates two main principles: providing purpose and meeting learner needs. Providing purpose emphasizes the importance of users understanding their individual health-related needs and how adopting SMATS can address them. By offering clear, balanced information, users can develop outcome expectations crucial for the adoption and sustained use of SMATS. This involves understanding the health-related needs that SMATS can address and fostering a belief in users’ abilities to engage with new technology successfully. Meeting learner needs on reducing the effort required to adopt and use SMATS. It highlights the importance of integrating SMATS into daily life and addresses users’ abilities to engage effectively with new technology. Efficacy within the LEAF aims to increase older adults’ confidence in using technology by providing hands-on experience. These experiences demonstrate the specific benefits of SMATS and allow the learner to understand the amount of effort necessary to adopt and use the technology successfully. This approach ultimately enhances older adults’ readiness to adopt and use technology effectively. Additionally, it focuses on reducing anxiety associated with using a new technology by providing assistance and training appropriate for the user’s needs. Lastly, Efficacy in the LEAF emphasizes the role of social support networks. These networks are crucial in shaping attitudes toward technology adoption among older adults. Positive support from family and friends influences attitudes toward technology adoption, while negative influences can hinder adoption efforts. Lastly, Achievement in the LEAF underlines the importance of reducing cognitive load and breaking tasks into sub-goals to reduce barriers to adoption. Setting clear, achievable goals and celebrating accomplishments can enhance older adults’ self-efficacy, encouraging habitual use of SMATS. Moreover, breaking down larger learning goals into smaller, manageable tasks improves learning and self-efficacy by fostering problem-solving skills. Researchers and educators can utilize these strategies to foster greater confidence and proficiency in using technology. In conclusion, the LEAF represents a pivotal strategy for addressing some of the challenges older adults face that hinder their adoption and use of SMATS. By leveraging insights from technology adoption literature, the LEAF, within the systems approach, enables the development of tailored training programs that cater to older adults’ unique needs and circumstances. This, in turn, lowers barriers to adopting and using SMATS in their daily lives. Further research and application of the LEAF framework can continue to refine our understanding and implementation of effective technology training strategies for older adults. If applied, this framework, grounded in both theory and empirical research, has the potential to foster the ability of older adults to age in place using SMATS.
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  Software Supply Chain Risk Management Framework

  (Georgia Institute of Technology, 2021-08) Onu, Kelly

  Software supply chain risk management framework is a systematic process for managing software supply chain risk exposures, threats, and vulnerabilities throughout the supply chain and developing response strategies to the supply chain risks presented by third-party software. The purpose of this paper is to provide a risk management framework for organizations that use or apply open source or third-party components within their SDLC. The proposed RMF will provide guidance for how to Frame, Assess, Respond and Monitor (FARM) the security risks associated with the use of third-party software or components. This RMF will also help organizations to understand these security risks and provide recommendations to manage them.
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  Transforming LibGuides: A Case Study

  (Georgia Institute of Technology, 2024-09) Givens, Marlee ; Holdsworth, Liz ; Jeffcoat, Heather

  This presentation delves into the comprehensive overhaul and streamlining of Georgia Tech Library's LibGuides and A-Z database list. Through detailed case studies, we illustrate the development of new workflows, the establishment of a template, rubric, and style guide for content creators, and the formation of a dedicated team to redefine database links, update descriptions, and ensure consistency. We highlight the strategic decisions and collaborative efforts, including cognitive load principles and accessibility standards, that optimized the user experience. Our approach underscores the importance of simplicity and organizational buy-in in effectively sharing expertise with an online audience.
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  Technical Services Training Top Ten

  (Georgia Institute of Technology, 2024-10) Givens, Marlee

  In today’s technical services organization, staff development plays a pivotal role in enhancing service delivery. Librarians, as lifelong learners, recognize how a strong learning culture can lead to organizational success. This interactive session explores a variety approaches to integrating formal and informal training into daily workflows, fostering a culture of continuous improvement, strengthening participant buy-in and peer collaboration, and increasing job satisfaction. Come hear a top ten and leave with a plus-one idea for your own workplace.
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  We’re Nowhere near the End, the Best Is Ready to Begin: Lessons Learned Making Canvas Modules

  (Georgia Institute of Technology, 2021-10) Givens, Marlee ; Holdsworth, Liz

  A campus-wide shift to the Canvas LMS seemed like an ideal opportunity for the library to reach new audiences. Two librarians organized a team to make LMS modules for instructors to import into their courses. Faculty librarians chose the topics, each team member volunteered for the work they could feasibly accomplish, deadlines were well in advance of launch date with padding, there was a rigorous editorial process, and the campus IT was a willing and engaged partner. The Georgia Tech Library was able to meet students where they were in a new learning environment. The library is inspired to further develop its suite of asynchronous offerings as a complement to live instruction, post-pandemic.
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  Assessing library instruction: Lessons learned from a pilot evaluation survey for non-credit instruction in academic libraries

  (Georgia Institute of Technology, 2024-11) Frizell, Matt ; Givens, Marlee

  The Georgia Tech Library developed and piloted a mixed-methods survey to evaluate non-credit instruction by librarians and archivists, aiming to complement existing campus-level evaluation tools and support promotion processes. The short survey, designed to maximize student response rates and avoid survey fatigue, did not provide deep or actionable feedback, prompting the use of alternative methods like peer observations for more meaningful insights. Purpose & Goals Can we create an evaluation survey for course integrated instruction and drop-in workshops that complements for-credit course evaluation tools used at the campus level? Many librarians and archivists at this institution teach, but most of this instruction is not for course credit. The few who teach courses for credit benefit from evaluation at the campus level through the Course-Instructor Opinion Survey (CIOS) from the Office of Academic Effectiveness. CIOS results are attached to librarian and archivist promotion dossiers. Our library has piloted a survey for non-credit library instruction. When this project started, changes to our department's promotion process and integration with promotion review processes at the campus level motivated us to show instruction effectiveness in some way. The pilot survey is similarly meant to offer meaningful feedback for individual instructors, their supervisors (annual review), the library review committee (promotion and cumulative reviews), library leadership, and our non-tenure-track faculty peers (promotion reviews). Design & Methodology The non-credit instruction evaluation survey is a mixed methods approach utilizing Qualtrics software. The survey was designed in two parts: 1) The survey itself which consists of 5 Likert scale questions and one open ended essay response field and, 2) a URL generator which embeds metadata, allowing for consistent formatting and easier categorization. In designing this project and creating a methodology, one goal was to develop a consistent vocabulary and approach to evaluating instruction. Part of the design process included creating a shared glossary which helped determine the scope of instructional types. A working group developed the questions and refined survey focus, gathered feedback from library faculty colleagues, and launched a pilot program with training. Findings After launching the pilot project in spring of 2023, we analyzed the first round of results and feedback from the pilot participants. The focus of this initial debrief was to understand the experience of administering the survey and any issues. Following the debrief, we made changes to the tool itself, editing the questions based on instructor feedback and attendee responses. At the time of this proposal, one year into the pilot, we have data from 12 instructors across 85 classes. We have collected over 1000 responses and over 250 open-ended comments. The poster will show average scores, the estimated response rate, a selection of typical comments, and any differences noted between responses for course-integrated instruction and drop-in library workshops. A finding of the project was that the nature of the short survey did not lend itself to deep or actionable criticism of the instructors or courses. This was purposeful – the survey designers sought to maximize student response rates in an environment where students suffer from survey fatigue. In reviewing the literature during survey design, we found that students are not motivated to complete a long survey (Hoel & Dahl, 2019), and that low response rates can indicate lower validity of the results (Chapman & Joines, 2017). Moreover, librarians and archivists can use other means to solicit more meaningful feedback, such as peer teaching observations, or surveying the professors in whose courses we provide instruction. Chapman, D. D., & Joines, J. A. (2017). Strategies for increasing response rates for online end-of-course evaluations. International Journal of Teaching and Learning in Higher Education, 29(1), 47-60. Hoel, A., & Dahl, T. I. (2019). Why bother? Student motivation to participate in student evaluations of teaching. Assessment & Evaluation in Higher Education, 44(3), 361-378. Action & Impact The Georgia Tech Library now has a tool which we can use to show quality, impact, and value of Library non-credit instruction for both workshops and course integrated instruction. At the time of this proposal, we have presented the first years’ worth of findings to library faculty and leadership, and general results will be included in the Library’s 2023 impact report. In the coming year or two, we will be able to test whether the survey results are meaningful additions to annual or promotion review dossiers. This will be evaluated by gathering feedback from the librarian or archivist using the tool, their managers, and the library and Institute faculty review committees. Another area of focus will be on whether the comments and scores create actionable feedback to improve instruction or lead to follow-up processes such as peer or campus led teaching observations. We hope that the tool and those resulting critiques will improve instruction and therefore student success. Practical Implications & Value Student success is a nationwide concern. The extent to which improvements to library instruction contribute to better student outcomes is a question we hope to shed light on. A review of the literature indicates ongoing efforts at assessing student learning in library instruction sessions, but fewer examples of student evaluations of library teaching. We hope our poster will add valuable feedback and contribute to the body of research and librarianship. Additionally, there seems to be a trend toward data-based decision making within libraries, mirroring trends across the academy. Our project looks at a potential model for applying student evaluations of teaching to non-credit instruction formats, that complements existing evaluations of credit-bearing courses.
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  Optimisation of Categorical Choices in Exploration Mission Concepts of Operations Using Column Generation Method

  ( 2024-10) Gollins, Nicholas ; Isaji, Masafumi ; Ho, Koki

  Space missions, particularly complex, large-scale exploration campaigns, can often involve a large number of discrete decisions or events in their concepts of operations. Whilst a variety of methods exist for the optimisation of continuous variables in mission design, the inherent presence of discrete events in mission ConOps disrupts the possibility of using methods that are dependent on having well-defined, continuous mathematical expressions to define the systems and instead creates a categorical mixed-integer problem. Typically, mission architects will circumvent this problem by solving the system optimisation for every permutation of the categorical decisions if practical, or use metaheuristic solvers if not. However, this can be prohibitively expensive in terms of computation time. Alternatively, categorical decisions in optimisation problems can be expressed using binary variables that indicate if the decision was taken or not. If implemented naively, commercially available mixed integer linear optimisation solvers are still slow to solve such a problem, in some cases not performing much better than combinatorially testing every permutation of the ConOps. Problems of this class can be solved more efficiently using "column generation" methods. Here, smaller, simpler restricted problems are created by removing significant numbers of variables. The restricted problem is solved, and the unused variables are priced by examining the dual linear program in order to test which, if any, could improve the objective of the restricted problem if they were to be added. Column generation methods are problem-specific, and so there is no guaranteed solution to these categorical problems. As such, the following paper proposes guidelines for defining restricted problems representing space exploration mission concepts of operations featuring common categories of decisions. First, the column generation process is described and then applied to two case studies. Firstly, it is applied to the NASA Marshall Advanced Concepts Office (ACO) ConOps for a crewed Mars mission, in which the design, assembly, and staging of the trans-Martian spacecraft are modelled using discrete decisions. Secondly, the process is applied to the payload delivery scheduling of translunar logistics in the context of an extended Artemis surface exploration campaign model.
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  Operational Development of Rotating Propulsive Maneuvers for NASA’s Lunar Flashlight Mission

  (Georgia Institute of Technology, 2024-05) Jordan, Graham ; Lightsey, E. Glenn

  This paper details the processes used for developing rotating propulsive maneuvers for JPL’s Lunar Flashlight cubesat mission as told from the perspective of the mission operations team. The timeline of the Lunar Flashlight mission after launch as well as the early anomalies that spurred work on the rotating maneuver concept are detailed first. An overview of the cumulative progression of implementing the rotating maneuver concept on the spacecraft is further explored. Finally, the operational software, hardware, and procedural tools that were created and utilized to make this development possible are described in-depth, concluding with a detailed description of the implementation of ground-in-the-loop maneuvers.
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  Socially Persuading Prosocial Behavior in Humans Using Automation: A Design Framework and Theoretical Model

  (Georgia Institute of Technology, 2024) Scott-Sharoni, Sidney

  Investigating methods to improve prosocial behavior has been a recent topic of interest for researchers studying human-automation and human-robot interaction. However, scientists have yet to uncover how and why certain features of technology enhance and encourage prosocial behavior in humans. By studying and facilitating prosocial actions between people, agents, and robots, not only will society benefit, but also personal factors such as psychological, social, and physical well-being will improve. The following preliminary examination paper reviews literature on automation, agent, and robot interaction with humans, focusing on their existence as social actors. Decades of work built from the media equation (Reeves & Nass, 1996) suggest that humans transfer social expectations, norms, and biases to non-human agents. This social existence affords non-human agents new possibilities to shape and persuade humans to increase prosocial behavior. To contextualize prosocial behavior in human-to-automation (H-A) interactions, definitions, motivations, and benefits of prosocial behavior within human-human (H-H) interactions and H-A contexts are discussed. The review highlights the lack of comparison researchers have made between the two domains. Additionally, it provides the first encompassing and comprehensive definition of H-A prosocial behavior, including core components necessary for its study. Throughout the review, there is an emphasis on understanding how social influences, that are paramount to H-H prosocial behavior, transfer to H-A contexts. While researchers assume, based on the media equation (Reeves & Nass, 1996), that social influences remain consistent across domains, the review discuses differences in H-A social influence. The theoretical role of social influence in prosocial behavior is detailed, as understanding conformity and persuasion is necessary to build agents and robots that encourage prosocial behavior in humans. Models of human to robot and agent social influence are examined with an exploration into how the Robot Social Influence model (Erel et al., 2024) can explain findings in prosocial behavior and persuasive social computing. The review presents and justifies a novel design framework and model that examines how and why specific characteristics in robots and virtual agents can promote prosocial behavior in human users. The framework, Robots and Agents as Persuasive Prosocial Actors (RAPPA), combines principles from persuasive social computing, social influence, and findings from the limited work within H-A prosocial behavior research. The theoretical model argues that anthropomorphism, social intelligence, and adaptiveness increase a human’s relatability, or sense of belonging, to the technology, which strengthens the automation’s influence on a human. This social influence can then persuade humans to behave prosocially. This is based on multiple theories that assert that close group identity increases social influence and prosocial behavior. Definitions and empirical evidence for each element of the RAPPA framework are provided, along with recommendations for its implementation into agent and robot design. The framework is then connected back to theories of human behavior such as the theory of planned behavior (Ajzen, 1991) and social learning theory (Bandura, 1971). RAPPA serves to enhance the understanding of how H-A prosocial behavior develops and provide scientists with a valuable reference for future work. The paper culminates in a series of applications and research topics that encourage researchers to include the framework in the study of in-vehicle agents.
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  Investigation of Weather Considerations for Battery Electric Regional Air Mobility Flights

  (Georgia Institute of Technology, 2024-07) Kim, Seulki ; Justin, Cedric Y. ; Mavris, Dmitri N.

  Recent advancements in battery electric aircraft technology have elevated their potential as a sustainable and efficient transportation solution for regional air mobility, particularly in enhancing connectivity for under-served communities. However, the lower energy density of onboard batteries presents a notable operational challenge, limiting the usable ranges for flights. This limitation could potentially impede the consistent and reliable deployment of these aircraft in regional flight networks, especially under unfavorable weather conditions. In response, this research proposes a comprehensive methodology to assess the operational impacts on electric aircraft under diverse meteorological scenarios in regional flight network. The proposed framework evaluates critical operational factors for Part 121 (scheduled air carriers) and Part 135 (commuter and on-demand operations), including flight cancellations, flight rules, wind-induced extended distances, and required alternate airport distances. To demonstrate the efficacy of this weather impact methodology, network-level analyses are conducted in two distinct regions of the United States: the Northeast Corridor and Colorado. The results offer information on the operational capabilities and limitations of electric aircraft under different regulatory frameworks. It is expected that these findings will support decision-making processes for regional fight operators and policymakers, facilitating the informed integration of electric aircraft into U.S. regional air mobility networks.