Winslow Burleson - US grants

Game As Life / Life As Game (GALLAG) is a research agenda exploring the boundary of physical and virtual lives. Gaming is becoming an increasing popular phenomenon that is having a profound effect on individuals and society. The GALLAG system will use sensors as the interface between digital and physical life. These sensors will detect the everyday physical activities that a person engages in. These activities will then be linked to games and game scenarios. Sensing aspects of individuals'' emotions and their interactions will be used, first, as a way to measure the impact of the GALLAG system and its scenarios on participants and, second, as an information channel to create a real-time feedback that enables the system to attend to and tailor itself to how participants'' emotional states. GALLAG will use ubiquitous computing and personally tailored game scenarios to integrate activities across the virtual and physical domains, holistically throughout everyday life, focusing on: meditation, sleep, and exercise. Influences and activities in the game scenarios will affect real life and vice versa influences and activities in life will affect the game. It is not known how people will respond to the GALLAG experience, if these synergies will be sufficiently engaging to users or if there are more fundamental barriers to the creation of long-term hybrid virtual/physical experience that must be addressed to make them compelling and beneficial. To address these unknowns, several methods of experience and behavioral assessment, and environmental, contextual and physiological sensors will be used in conjunction with participatory design approaches that include end-user-programming, and iterative design and testing. The GALLAG approach can be used to become quickly aware of other people''s lives, as well. The status of another game player (perhaps a family member) can be observed through their profile and information. For example, elderly parent''s activities - even if the parents are not involved in the gaming activities - might be represented in a readily interpretable manner so that their children can better understand their wellbeing. This elderly parent might not know how to explain tell her doctor that she has been feeling fatigued or ill. GALLAG may enable her physician to better understand her condition by reviewing with her brief game-clips of her activities. It is not known how people will respond to the GALLAG experience, if these synergies will be sufficiently engaging to participants or if there are more fundamental barriers to the creation of long-term hybrid virtual/physical experience that must be addressed to make them compelling and beneficial. As gaming becomes more of an important part of life, new opportunities arise to use emerging technologies to benefit individuals in their daily activities and life long aspirations. This agenda seeks to empower users to create their own synergies between their on-line activities and to help them achieve their personal real world aspirations.

Gaming is becoming an increasing popular phenomenon that is having a profound effect on individuals and society. Further, online role-playing games and interactive gaming interfaces are becoming more social and starting to engage participants in physical activity. This exploratory research has the potential to further extend the emerging avant garde ''real life games'' that are coordinated by digital means to further blur digital-physical-social barriers. Specifically, GALLAG seeks to study the coordination of digital life with real life to link real life behaviors with no immediate tangible reward with more immediate intrinsic reward in the virtual environments. An example of the potential of this strategy is the diabetics support software called DiaBetNet (http://www.dimagi.com/case-studies-diabetnet.php). The game leads the child to a better understanding of diabetes and thereby increases his or her ownership of long-term health. As gaming becomes more of an important part of life, fantastic opportunities arise to use emerging technologies to benefit individuals in their daily activities and life long aspirations. This agenda seeks to empower users to create their own synergies between their on-line activities and to help them achieve their personal real world aspirations. Ultimately work from this GALLAG project may lead to ''Life Long Games'' that provide persistent, supportive, and actualizing experiences.

Emotion and motivation are fundamental to learning; students with high intrinsic motivation often outperform students with low motivation. Yet affect and emotion are often ignored or marginalized with respect to classroom practice. This project will help redress the emotion versus cognition imbalance. The researchers will develop Affective Learning Companions, real-time computational agents that infer emotions and leverage this knowledge to increase student performance. The goal is to determine the affective state of a student, at any point in time, and to provide appropriate support to improve student learning in the long term. Emotion recognition methods include using hardware sensors and machine learning software to identify a student's state. Five independent affective variables are targeted (frustration, motivation, self-confidence, boredom and fatigue) within a research platform consisting of four sensors (skin conductance glove, pressure mouse, face recognition camera and posture sensing devices). Emotion feedback methods include using a variety of interventions (encouraging comments, graphics of past performance) varied according to type (explanation, hints, worked examples) and timing (immediately following an answer, after some elapsed time). The interventions will be evaluated as to which best increase performance and in which contexts. Machine learning optimization algorithms search for policies that further engage individual students who are involved in different affective and cognitive states. Animated agents are enhanced with appropriate gestures and empathetic feedback in relation to student achievement level and task complexity. Approximately 500 ethnically and economically diverse students in Massachusetts and Arizona will participate.

The broader impact of this research is its potential for developing computer-based tutors that better address student diversity, including underrepresented minorities and disabled students. The solution proposed here provides alternative representations of scientific content, alternative paths through material and alternative means of interaction; thus, potentially leading to highly individualized science learning. Further, the project has the potential to advance our understanding of emotion as a predictor of individual differences in learning, unveiling the extent to which emotion, cognitive ability and gender impact different forms of learning.

This project includes the development and evaluation of pilot studies of creativity in an IT research organization with three primary objectives: (1) combine IT and social science methodologies; (2) extend our understanding of individual and team creative processes; (3) develop and evaluate new types of interventions and interfaces that incorporate affect, context, and social interaction to leverage opportunities to promote creativity. The intellectual merit lies in the development of hybrid methodologies, combining social science and computer science approaches to multiple behavioral and affective elements for creativity in an IT research organization. The research will improve our understanding of organizational creativity and advance the development a new generation of integrated Creativity Support Tools that are applicable within teams and organizations. Broader Impacts: Creativity is required for advances in all areas of human endeavor. The methods and frameworks developed are broadly applicable throughout academic and industrial IT research organizations, and they are also adaptable to a broad spectrum of organizations that increasingly need guidance and support to foster creative practices and innovation. The methods and tools will also apply to people performing a wide range of personal endeavors as they engage in their own creative pursuits. The findings and systems will advance academic and industry collaborations and will be broadly disseminated throughout multiple research communities, IT organizations, and on-line communities.

Going beyond in-person conference and symposium events this workshop develops and evaluates new types of Creative-IT community events that incorporate IT and IT artifacts of the Creative-IT community and leverage these in distributed online events. The events will focus on Creative IT community and knowledge development through participant engagement, generative activities, and reflective critique. Initially the distributed will be developed by curating (i.e., selecting, facilitating, and hosting the events) three events. The initial events will focus on three themes of this community, including: (1) Creativity Support Tools, (2) Multifaceted Creative Experiences with IT, (3) Creativity-IT Theories and Methodologies: An Evolving Canon. This project effectively defines a workshop that is distributed in time and space. The 2 major goals are to bring the CreativeIT community together using the technologies that are claimed to enable creativity, and to provide an opportunity to develop and evaluate the application of these technologies with a group of researchers that tend to be both creative and early adopters. The long term impact of the proposed work is to create, a series of interactive creative experiences that would become a self-motivated process of self-definition and growth that is owned by the Creative-IT community as a whole, or a rotating facilitating group of members.

The studies address through investigation of students in Arizona High School summer programs how students learn, understand and manipulate scientific models of the carbon cycle and the water cycle. The investigators of this project have identified problems that on-line tutors have with creating conditions for students to regulate their own behavior. Instead of taking advantage of the available learning opportunities, some students ask for hints until the tutor gives them the correct answer.

The investigators hypothesize that lasting benefits require changing students beliefs about shallow compared with deep modeling practices and breaking their modeling habits and instilling new ones. They intend to add affective learning companions to the on-line tutors. The modules use the teachable agent metaphor called Betty's Brain.
The study analysis will be conducted in high school summer schools in Arizona for students that are mostly Native Americans. The students are self-selected for attending the summer school. Data collection will include student logs, verbal protocols and affect sensor data from the summer school participants (approximately 30 students). Three studies will be conducted: 1. to develop a meta tutoring tool, 2. to develop an affective learning agent with verbal and physical gestures, and 3. a measure of whether the new tool results in increases in learning. The analysis will involve causal inference and data mining of student records of their activities. The third phase of the learning will compare students who use one agent with the teachable agent; a second group will compare two agents, the teachable agent and the meta-tutor; and a third group will compare three agents. The outcome of the study is a developed and tested tool to increase student learning and statistical analysis of records maintained by the investigators of student activities with the teachable agent. The study should help indicate whether computer tutors are more effective if they have integrated features that mimic human performance.

The Preparing for College: Using Technology to Support Achievement for Students with Learning Disabilities in Mathematics project will advance knowledge about improved learning, motivation and achievement of undergraduate students with mathematics learning disabilities when using digital interventions. This demonstration research project will result in pilot-tested interventions, which will serve as the basis for more advanced studies of how students with learning disabilities learn math in a cyber-enabled environment.

The primary intervention tool for this project is a cyber-enabled mathematics tutor, "Wayang Outpost," that helps students solve challenging test problems, teaches explicitly, and uses visual representations to help students learn. Modifications to the tutoring system will be piloted that address cognitive, metacognitive, and affective dimensions of the system, corresponding to the representation/expression and engagement strands underlying universal design for learning.

This demonstration research pilot project will include testing a series of interventions with undergraduates in developmental mathematics classes at the University of Massachusetts and at Arizona State University. The project will target approximately 200 undergraduates, with and without learning disabilities, across four classrooms in experimental and control conditions.

The purpose of this proposal is to explore the extent to which timely emotional, cognitive, and metacognitive interventions in tutoring software will have positive effects on students' emotions, attitudes, and achievements in mathematics. The intelligent tutor, Wayang Outpost, a high school mathematics tutoring system, is being enhanced to leverage automatic detection of emotions to guide cognitive, metacognitive, and affective forms of learning support.

The PIs are conducting a set of experiments to understand the interplay of observed emotional states, emotion assessments, student behavior within tutors, and student achievement. In particular, the experiments are testing the effects of the tutoring system when it assesses the emotions of a student and then responds with instructional support appropriate to that student's affect and content knowledge.

In this project, an interdisciplinary team of researchers in learning technologies and mathematics education are working together to investigate issues related to motivation in learning mathematics. They are taking the results of lab-based studies into classrooms. The novel technology and approaches developed in the lab were tested with a small population of learners; in their classroom-based investigations, they are testing feasibility of the approach with a more diverse population and refining the technology for use in a broad range of classroom learning environments. This translational research project will not only make significant contributions to the field of learning technologies, but will also contribute to our understanding of issues related to motivation in mathematics learning.

In robotics activities, students are theorized to benefit from "learning-by-doing" activities where they set their own goals, but in practice, these activities have failed to produce the expected effects on STEM outcomes. To improve learning from robotics, this project will leverage teachable agent technologies, where students learn about a domain by teaching a computer agent. The agent interacts with students to expose misconceptions and encourage them to persist in the face of failure. By integrating the structure of teachable agents with the exploratory and engaging features of learning from robotics, the project will enhance the benefits of both approaches. The investigators will implement a robot that students can teach about the concepts they are learning in their middle school mathematics class. They will engage in design exercises with teachers and students to identify features of the robot that might be particularly important for improving student motivation and learning. Finally, they will conduct two studies, one in the laboratory and one in the classroom, to explore how students react to the robot in a realistic setting.

Intellectual merit: The project will improve understanding of what features students respond to in a teachable robot for mathematics, and of the potential educational benefits such a robot might have. The project will make a technological contribution by inventing methods for integrating teachable agents and robotic learning environments.

Broader impacts: The project will impact middle school students from underrepresented groups who will help design and test the teachable robot, exposing them to new technologies and engaging aspects of STEM careers. The project will also lead to a better understanding of the impact of teachable robots in the classroom and pave the way for these technologies to be adopted more widely in education.

A major factor influencing learning is students' emotions and their general affective state. Given the pivotal role that affect plays in learning activities it is not surprising that there has been a good deal of interest in developing affect-aware technologies. The overwhelming majority of this work, however, has focused on modeling affect, i.e., designing computational models capable of inferring how students are feeling while interacting with an Intelligent Tutoring System (ITS). While modeling of affect is a critical first step in providing adaptive support tailored to students' affective needs, very little work exists on systematically exploring the impact of affective interventions on students' performance, learning, affect and attitudes, i.e., how to respond to students' emotions such as frustration, anxiety, boredom, and hopelessness as they arise. The research fills this gap by analyzing the value of tailoring different types of interventions to negative affective states for individual students and groups of students.

The project has two main goals. First, it addresses how to respond to negative student emotion (e.g., frustration, anxiety, boredom) in computer-based learning environments through a variety of interventions. Some correspond to specially-designed digital characters, integrated into the learning environment, which are intended to act like students' learning companions. These agents support students through (a) non-verbal behaviors (e.g., having the characters express empathy in response to student frustration), (b) messages targeting students' cognitive and meta-cognitive skills, as well as motivation and affect. Other interventions involve supporting collaboration between students to mitigate negative emotional states when detected. The impact of these interventions are investigated through a series of eight experiments with a total of 800 students. These experiments help to unveil general prescriptive principles to address student affect.

The second goal accomplished by this research is that the experiments provide valuable data to continue to extend and validate existing models of emotion. Specifically, the project triangulates and integrates a complex space of partially overlapping models and constructs of affect in learning (i.e. emotions, attitudes, incoming moods, motivation, engaged use or misuse of software). The project refines several well-established models, in particular the control-value theory of emotions to provide a more stable theoretical framework for the field of emotions in educational software.

This research is unique and ground breaking, as few researchers have targeted students' emotion in classrooms, gathered fine grained data on emotions during learning, or assessed the impact of specific affective treatments on a moment-to-moment basis. Students using the tutoring systems have already shown statistically significant gains and learning outcomes, as well as increased positive affect and attitudes. The new affective interventions will greatly increase the broad impact of these systems.
This research is developing: (1) prescriptive principles about how to respond to student affect; (2) new understanding about the impact of cognitive, affective, and meta-cognitive interventions on emotions and learning; (3) new understanding about individual differences in learning, unveiling the extent to which emotion, cognitive abilities, and gender impact learning; (4) instruction that is sensitive to individual differences; and (5) refined theories of student emotion.

This research is also: (1) increasing participation in mathematics of underrepresented populations (women and minorities) who often avoid STEM careers; (2) creating broad access to web-based technologies that help to engage more students by addressing their affective and social needs; and (3) addressing the one-size-fits-all approach to education, by responding to individual student needs with alternative representations of content and pathways through which material is presented.

This research will advance a novel technological approach that relies on machine learning techniques in general and Natural Language Processing (NLP) in particular to develop models and support for creativity during collaborative science, technology, engineering, and mathematics (STEM) educational activities. We will extend existing educational software with NLP capabilities to automatically assess and subsequently support creativity during collaborative tasks. The research questions are: (1) Which factors influence moment-by-moment creativity during collaborative problem solving activities? (2) How can NLP be used to build student models that detect those factors? (3) How can an ITS use this information to create personalized interventions to support creativity?

The first phase in this research will collect data from students solving problems in pairs with an educational application to identify factors that are relevant to creativity processes and outcomes. These data will be used to derive computational student models for automatically assessing student creativity in terms of both moment-to-moment processes and outcomes through machine learning methodologies focusing on an NLP approach. In addition to providing automatic assessment, the models will also inform factors that influence creativity during collaboration through educational data mining techniques. The final phase of the work will design and test a set of interventions to foster creativity during collaborative activities.

Using data corresponding to pairs of students solving open-ended STEM-based problems, this research will develop a rich and nuanced understanding of creativity processes and outcomes in collaborative contexts, and how these relate to knowledge, affect and creative thinking styles. Relying on that understanding, it will develop and evaluate novel student models that recognize salient, creativity-related events through NLP techniques, as well as personalized support for creativity during collaborative activities and evaluating that support through an experiment with university students. This project will pave the way for a new class of collaborative cyberlearning technologies to both assess and foster creativity, through just-in-time personalized support based on easily deployed NLP-based student models.

This project, developing a distributed instrument to physically integrate seamlessly the physical with the virtual, aims to create a unique experiential supercomputer, an immersive, collaborative, virtual/physical research environment with unparalleled tools for intellectual and creative output, a Holodeck that scientifically exceeds Star Trek science fiction. The work should advance the next-generation experiences in human interaction and deep integration of virtual and physical settings, creating rich actualizing environments to support research and discovery of new paradigms. The flexible, modular, reconfigurable infrastructure will connect researchers, research, and educational facilities across the university, the NYU Global Network University (GNU), and external researchers, communities, and industry partners worldwide. The instrument will enable exploration of a myriad of research questions involving virtual environments, telepresence, collaborative engagement, and remote interaction and create a strong foundation for extended collaborations. The project integrates qualitative and quantitative assessment of affect and motivation, with foundations of learning science, motion science, acoustics, modeling and simulation, robotics and fabrication to improve research effectiveness and scalability to address real world challenges.

The work is accomplished by integrating 3-D printing to physically realize simulated forms, robots to allow virtual models to impact the physical world and interact with it, haptics to provide to human collaborators a sense of tactile feel of virtual objects, and physiological state monitors to try to get "inside" the human experience. This "experiential supercomputing" serves as a paradigm for human collaboration that translates to all disciplines spanning computer science, engineering, music, psychology, nursing, radiology, applied math, biology, and medicine. The effort transcends visualization to approach human collaboration in its totality and has the potential to transform our fundamental understanding of collaboration, learning, creativity, discovery, and innovation. The NYU Holodeck will be a well-integrated software/hardware instrument incorporating visual, audio, and physical components and novel technologies to enhance social interactions (human-human, human-agent, and human-robot). In its incorporation of rapid prototyping and fabrication tools, this unique instrument fosters creative capacity, and tight coupling of interactive visual, audio, and physical experience. Its research capabilities support comprehensive capture of behavioral, physiological, affective, and cognitive data, and visualization and analysis of the data in real time. Creating innovative environments that bridge simulation, cyber learning, scientific visualization, human-computer interaction, and applied physical science research; the effort enables new types of science where researchers from diverse disciplines can interact with theoretical models, real objects, robots, and agents, engendering insights not possible using 2D, 3D, or other currently available representations.

This proposal investigates robotic teachable agents, a type of cyberlearning technology that provides cognitive and affective feedback to support students' learning. The Tangible Activities for Geometry system (TAG) is a robotic teachable agent platform for middle school mathematics and computational thinking. Students physically engage within a projected coordinate space with an interactive teachable robot named Quinn. Students teach Quinn how to solve challenges involving plotting points on a graph, translating points, rotating points, and plotting lines by giving procedural and conditional instructions to Quinn. There appear to be at least two primary advantages to using a robotic learning platform to investigate how to design teachable agents. First, a physical presence, provided by a robotic agent, strengthens users' perceptions of having a social partner that is more than a virtual agent. Second, students receive cognitive benefits from learning through embodied, physical interactions. This research investigates the unique affordances of a teachable robot for supporting students' cognitive and social interactions within a learning environment as it enhances our understanding of how cyberlearning can support STEM learning (mathematics and computational thinking). The study will be conducted in a school system having high percentages of underrepresented minorities who will learn to design features of the robots, exposing them to STEM careers and increasing the likelihood of acceptance and scalability. The investigative team will also disseminate findings and Do-It-Yourself (DIY) instructions for integrating cyberlearning environments and pedagogical approaches.

This proposal advances an empirical investigation that uses a teachable robot learning environment built with prior NSF support, integrated within the NYU Holodeck, a state-of-the-art immersive collaborative cyberlearning research environment, to improve understanding of how adaptive cognitive and social support can facilitate embodied interactions with teachable agents. This project investigates the teachable agent phenomenon within the context of the Tangible Activities for Geometry system (TAG), a robotic teachable agent platform for middle school mathematics and computational thinking. The project has three phases. First, the research team will explore two factors related to cognitive support: (1) how the teachable agent can give adaptive feedback representative of a learner (questions, self-explanations) rather than a tutor (hints, instructional explanations), and (2) how cognitive prompts can leverage the physical properties of the environment. Second, the team will explore two factors related to social support: (a) how a teachable agent can make adaptive attributions to effort or ability for its success or failure to motivate students, and (b) how the robot can use its embodied presence (physical or tactile) to contribute social information to enhance student learning. Third, to assess the efficacy of the interventions, the project incorporates a study comparing cognitive and social support to a condition with only cognitive support, only social support, and with no support. The project will make substantial contributions toward better understanding how to design and effectively incorporate support, provided by a teachable robot, to adaptively provide cognitive and social support to improve student outcomes. The robot framework will be tested in schools, including high percentages of underrepresented minorities, developing new ways of using technology to learn mathematics and computational thinking.

Abstract: Persons living with dementia (PWD) often require assistance with routine activities and daily tasks. Workloads placed on caregivers often results in high levels of physical and emotional stress, and depression, and higher overall morbidity and mortality rates. Focus group of caregivers for individuals with mild to moderate dementia, identified dressing the PWD as the most pressing and stressful daily concern. We have developed a prototype computerized Dressing Assistant (DA), designed to reduce caregiver burden and independence. The system, employing advanced smart home technologies embedded within a set of dresser drawers, uniquely tailors assistance to the cognitive and affective states and abilities of PWD, using prompts and feedback. Our interdisciplinary team which combines human-computer interaction, gerontological nursing and dementia, will conduct translational research, bringing DA from laboratory to home settings. AIM 1: Optimize the Dressing Assistant installation procedures for PWD home settings. To understand how effectively the DA system can be installed in a home, we will consider: 1) the initial system installation, including length of installation visit, number of component adjustments, and caregiver and PWD training time required; and 2) opportunities for system optimization and durability through ongoing DA system monitoring, alert notices generated by the performance log, and caregiver feedback to the study team. AIM 2: Assess Dressing Assistant system reliability and accuracy in PWD home settings. We will use an adaptive support model, performance log, error rate, and caregiver feedback, to determine how accurately the DA system functions in a home setting. Data includes: 1) system switches and sensor logs (i.e. which drawers were opened, when, for how long, and in what sequence), and doorway motion sensor; 2) validated Pearlin?s Caregiver Mastery and Mahoney?s Caregiver Vigilance scales will determine trend effects; and 3) mobile device caregiver feedback. AIM 3: Maximize utility through identification of barriers and facilitators, usage, acceptability, effectiveness, and perceptions and refining system accordingly. We will identify barriers and facilitators that enable/impede frequent, long-term Dressing Assistant system use and compare performance log usage frequency data and accuracy measures (AIM 2) to consider how DA system accuracy affects usage. The DA system-generated data, and qualitative open-ended structured caregivers and PWD interviews will be used to determine acceptability. We will consider whether the PWD/caregiver dyad effectively uses the technology, frequency and duration of use based on the performance logs, and user interviews to identify reasons for using/not using the DA system. Interviews will identify barriers and facilitators influencing usage and obtain information about how positive and negative perceptions of the interaction experience affect use. Key Words: Alzheimer's, caregiver, dementia, smart home, assistive technology, Activities of Daily Living.

Cyberlearning technologies that incorporate robust personalized support and motivational engagement with co-robotic teachable agents present compelling high risk-high payoff opportunities for advancement and broad dissemination of collaborative-robotics STEM education. The project will create robotic teachable agent technologies that provide personalized social, affective, and cognitive support to improve students' STEM learning and motivation. The project will engage at least 10 teachers and 250 middle school students including many underrepresented minority middle school students in the study of collaborative robotics and STEM cyberlearning. The researchers will involve students and teachers in the design and integration of ChalkTalk (a Mixed Reality gesture-based storytelling and simulation tool-kit) with Robotic-Teachable Agents for middle school Geometry (R-TAG) to create an open-source tool-kit for formal and informal STEM learning. The researchers will conduct empirical studies to develop rich models of student cognitive and social interactions, and improve understanding of how to design personalized cognitive, social, and affective support using physical and virtual teachable robotic agents. The project will create a low-cost opportunity for students and teachers to engage in collaborative robotics and STEM cyberlearning. The project will contribute to development and testing of education strategies for broadening participation of students from groups underrepresented in education pathways to careers in robotics.

This research will advance the state-of-the-art of co-robotic cyberlearning, engaging hundreds of underrepresented minority middle school students in personalized Ubiquitous Cyberlearning with Collaborative Robotic Experiences (UCCRE). The project will (1) investigate how UCCRE can develop perceptual and cognitive support through collaborative embodied personalized interaction that generates exploratory insight, adaptive feedback, and self-explanation - going beyond typical tutoring support (offering hints, instructional explanations); (2) investigate how UCCRE can develop social support, through embodied personalized interaction with robotic teachable agents that engage and motivate students and (3) evaluate UCCRE through a series of pilot studies using design-based research methods, affective and physiological measures, and Natural Language Processing (NLP) tools. The researchers will use these methods, measures, and tools to sense and adapt to learners' affective states in ways that promote learning and creativity. Students and teachers will iteratively advance the capacity of UCCRE to provide personalized adaptive cognitive and social support, and facilitate collaborative embodied interactions between robotic teachable agents, students and teachers, within formal classroom and informal after-school settings. The findings on participatory design of ubiquitous co-robotics will likely generalize across domains and improve students' interest and motivation in learning robotics.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.