Digital Commons Network^™

Active Learning: Eight Models That Shape Instructional Practice, A.E. Dreyfuss, Ana Fraiman, Karmen T. Yu

Publications and Research

Developed since the mid-20^th century, several instructional models have provided practical means to shift the emphasis in learning from lecture to engagement by students. The snapshots of models presented in this paper include Cooperative Learning, Problem-Based Learning (PBL), Supplemental Instruction (SI) (also PALS, PASS), Team-Based Learning (TBL), Emerging Scholars Program (Mathematics Workshop, MathExcel), Peer-Led Team Learning (PLTL), Process Oriented Guided Inquiry Learning (POGIL), and Learning Assistants (LA). These models have been well-disseminated, widely adopted, and incorporated in disciplines beyond their origins. For purposes of exploration and consideration of implementation, these “snapshots” provide an overview. Features of each model are …

Tutoring Online During The Covid-19 Pandemic: Use Of Critical Incidents To Improve Practice, A.E. Dreyfuss, Jose Armando Sanchez Diaz, Barakat Adigun, Helen Baraki, Thalyia Thompson

Publications and Research

Developing expertise in the practice of online tutoring is presented by peer tutors who provided support to students with synchronous sessions with the onset of COVID-19. The experiences and learning of peer tutors were probed through the use of critical incidents (Flanagan, 1954), and how weekly training meetings provided support to them, creating a collaboration among the tutors and the training manager.

Art Forms: Born Out Of Necessity, Urmi Duttagupta

Publications and Research

This collection of artworks expresses the artist’s profound passion for mathematics and life’s complex balance. As a female mathematician, she uses artistic expression and intricate patterns to evoke mathematical beauty and feminine strength, celebrating the presence and resilience of women in mathematics.

Major, Trace And Rare Earth Element Concentrations In Nist Standard Reference Material® 1646a Analyzed By Als Global Using Method Me-Ms61r, Jane L. Alexander

Publications and Research

This technical note compares analytical results obtained from ALS Global Method ME-MS61r with the certified and previously published results for NIST Standard Reference Material® 1646a, Estuarine Sediment. The results are grouped into major, trace and rare earth elements, and focus on elements used by sedimentary geochemists, for example in studies of sediment provenance. The results from ALS Global Method ME-MS61r are internally consistent and generally robust when compared with published analyses. However, acid digestion may not completely dissolve resistant minerals, leading to under-reporting of some elements such as Ti, Cr, Zr, heavy REE and Y.

Advanced Robotic Multimodal Imaging With Real-Time Motion Compensation For Dynamic Structural Health Monitoring, George Papaioannou, Christos Mitrogiannis, Mark Schweitzer, Maria Pappa, Pegah Khosravi, Apostolos Karantanas, Chris Ruberg, Shawn Owens, Nikolaos Michailidis

Publications and Research

Modern composite materials promise superior performance and load-bearing capabilities, yet evaluating their structural integrity remains challenging. Current testing methods, such as visual, thermographic, ultrasonic, optical, electromagnetic, terahertz, shearography, X-ray, and neutron imaging, are hampered by long scan durations, limited field of view, suboptimal accuracy, and high costs, particularly when applied to large structures.

This paper addresses these issues by introducing a novel robotic multimodal imaging system that overcomes the limitations of traditional methods. This system dynamically captures both static and dynamic properties of materials using advanced motion compensation techniques. By integrating multiple radiographic modalities into a coordinated robotic platform, it …

Improved Rational Approximations Of Pi, Nelson Carella

Publications and Research

The irrationality exponent of a real number α is defined by maximal value μ(α) ≥ 1 such that the inequality |p/q − α| < 1/qμ(α) is true for finitely many rational approxi- mations by relatively prime pairs p/q. The earliest result introduced the upper bound μ(π) ≤ 42 for the irrationality exponent of π. Subsequently, it was improved by many authors. The more recent result introduced the improved upper bound μ(π) ≤ 7.6063. This note introduces an improved irrationality exponent μ(π) ≤ 3. The optimal value is expected to be μ(π) = 2.

"Chatgpt Told Me To Say It": Ai Chatbots And Class Participation Apprehension In University Students, Daisuke Akiba

Publications and Research

The growing prevalence of AI chatbots in everyday life has prompted educators to explore their potential applications in promoting student success, including support for classroom engagement and communication. This exploratory study emerged from semester-long observations of class participation apprehensions in an introductory educational psychology course, examining how chatbots might scaffold students toward active and independent classroom contribution. Four students experiencing situational participation anxiety voluntarily participated in a pilot intervention using AI chatbots as virtual peer partners. Following comprehensive training in AI use and prompt design given to the entire class, participants employed systematic consultation frameworks for managing classroom discourse trepidations. …

Can We Discover Physical Models Using Machine Learning? A Case Study Of Galaxy Sizes, Festa Buçinca-Çupallari, Ariyeh Maller, Viviana Acquaviva, Austen Gabrielpillai, Rachel S. Somerville

Publications and Research

We explore the ability of machine learning methods to discover underlying equations of physics by searching for the equations governing galaxy size in a semianalytic model. This case study allows us to evaluate the process as we know the ground truth. We find that we fail to find an equation to predict galaxy size on the entire data set, but are successful when we separate out disk galaxies where we expect the physics driving galaxy size to be different than in bulge-dominated systems. We are also able to find an equation for bulge size, but not without adding an additional …

Evidence-Based Shared Agendas For Scholarship On Teaching With Primary Sources: Reflections On A Bibliometric Analysis, Jen Hoyer, Anne Bahde

Publications and Research

This article explores how scholarship about teaching with primary sources (TPS) has evolved over time and what future directions past work might suggests. Using bibliometric analysis and visualization tools, we examined how TPS work has grown; what fields and disciplines focus on this work; key themes and issues; and what scholarship has been influential to the field. These insights led to reflections on disconnects across the field, considerations for publishing about TPS, and the potential of pedagogical standards and guidelines. Finally, this article concludes with recommendations on how this analysis points to possibilities for shared education, space, conversation, and products.

Kimball Hall, 1970: Collective Organizing Through Print Production, Jen Hoyer

Publications and Research

This article examines the May 1970 occupation of Kimball Hall, a university administrative building at New York University, and specifically of its basement printshop. The group that came together in this space referred to itself as the Kimball Commune; they used university equipment and resources to print material in support of the strike and related movements, and they invited students, activists, and the general public to come into the printshop and produce material with them. I demonstrate how the Kimball Commune provides a concrete example of how a collaborative radical printing project isn’t just about creating alternative media. It also …

Full-Stack Web Applications: Infrastructure, Development Pipelines & Devsecops, Yassine Chahid, Patrick Slattery

Publications and Research

This research explores emerging development methodologies and technologies which facilitate the deployment and maintenance of software applications. It evaluates architectural styles for the development of software such as monolithic (legacy) and microservice models, with a focus on their key differences such as scalability or project structure through to the development of an application. By examining methodologies such as Agile and continuous integration/continuous development pipelines along with the deployment tools Docker and Git for version/release control, the study analyzes how these innovations speed up development, improve existing practices, and serve as the foundation for development operations. Cloud solutions for tasks such …

Artificial Intelligence And Machine Learning For Composite Materials Design, Kazi Imran, Akm Rahman, Jiayue Shen, Md Zahidul Haque

Publications and Research

Artificial intelligence is becoming a powerful tool to design and develop new materials, especially in composite materials design. Fiber-reinforced polymer composites have an exceptional advantage over traditional materials for their superior or specific stiffness and strength, and resistance to corrosion and fatigue, which results in low total lifetime cost. One of the primary limitations of these composite materials is predicting mechanical, thermal, and electrical properties due to the anisotropy of the materials. Predicting mechanical, thermal, and electrical properties is important in utilizing these composite materials for multiple engineering applications. To address this issue requires a machine learning model trained from …

Board # 186: The Impact Of Virtual Reality On Learning In Engineering Materials Courses, Ozlem Yasar, Angran Xiao

Publications and Research

Virtual reality (VR), one of the leading technologies in immersive learning, has the potential to transform the teaching of mechanical engineering by providing interactive, 3D learning environments. Traditional teaching methods in mechanical engineering often rely heavily on theoretical concepts and offer limited practical demonstrations. However, giving students hands-on experience with advanced machinery, such as scanning probe microscopes (SPM) and transmission electron microscopes (TEM), poses significant challenges. These challenges arise from factors like cost constraints, limited availability, and safety concerns. These machines are prohibitively expensive to acquire and maintain, making it impractical for many educational institutions to provide widespread access. Even …

Board # 363: Effective Strategies To Support Student Success In An Nsf S-Stem Program, Diana Samaroo, Urmi Duttagupta, Nadia E. Stoyanova Kennedy, Armando R. Solis, Viviana Acquaviva

Publications and Research

This paper reports on the success of an NSF S-STEM grant, which builds on two successful previous programs at “our institution”. The initiative aims to improve retention and graduation rates, increasing the participation of minority and female students in STEM fields and the NYC workforce, thereby reducing socio-economic disparities.

From Spring 2020 to Spring 2024, the project awarded an average of 40 scholarships annually to academically strong and financially disadvantaged students in various STEM programs, benefiting 93 unique students. It also enhanced early research experiences, internships, and provided robust academic advisement and mentoring. Seminars and meetings with STEM professionals expanded …

Board # 414: Nsf S-Stem: Developing An Ecosystem Of Stem Success For Built Environment Scholars, Melanie Villatoro, Muhammad Ummy, Hamidreza E. Norouzi, Masato R. Nakamura, Daeho Kang

Publications and Research

The National Science Foundation S-STEM program, Developing an Ecosystem of STEM success for Built Environment Scholars (Award Number 2150432), focuses on supporting and developing scholars in the majors relating to the Built-Environment which include Civil Engineering Technology, Construction Engineering Technology, Electrical Engineering Technology, Mechanical Engineering Technology and Environmental Control Technology. The intent of the project is to implement evidence-based effective practices and assess the impact of these practices, degree attainment, and entry into the U.S. workforce or graduate programs in STEM. Students are provided faculty mentors and opportunities to engage in cohort building activities that include field trips, research, workforce …

Shaping Future Innovators: A Curriculum Comparison Of Data Science Programs In Leading U.S. And Chinese Institutions, Elizabeth Milonas, Qiping Zhang, Duo Li

Publications and Research

Background: In recent years, the data revolution has sparked widespread interest in Data Science (DS) across numerous fields and disciplines [1]. As society becomes more reliant on data-driven decisions, the demand for professionals equipped to handle data challenges is rising. The need for skilled workers in diverse roles and capacities continues to grow as these demands evolve [2,3]. To meet the demand for skilled workers, training in the latest data science technologies has become a priority in colleges across the US and China. These colleges have established comprehensive data science programs to ensure students graduate with the expertise required in …

Proceedings Of The Cuny Games Conference 11.0, Robert O. Duncan, Grace Axler-Diperte, Joe Bisz, Christina Boyle, Devorah Kletenik, Carolyn Stallard

Publications and Research

The CUNY Games Conference combines workshops, idea exchanges, interactive participant presentations, playtesting, and playing tabletop games into a one-day online event to promote and discuss game-based learning. The conference focuses on creative pedagogy, such as playful learning activities or games, that teachers can use in the classroom every day. The conference is online and features interactive presentations by attendees, informal idea exchange sessions, and workshops by the conference organizers.

Extended Abstract—Using Augmented Reality To Teach The History Of Classical Athens: A Presentation Of The Methodology And Preliminary Findings, Christopher Tripoulas, George Koutromanos

Publications and Research

In this extended abstract, the methodology for a study in progress regarding the design, development and evaluation of an Augmented Reality application for the teaching of the History of Classical Athens to students of Greek descent living abroad is presented. Following a review of the reasons necessitating the adoption of this technology for the teaching of History – and specifically relating to fifth-century B.C. Athens – the preliminary findings including a review of the literature and results of interviews with teachers, students, and parents are also shared. The detailed methodological framework of Design-Based Research guiding this study is detailed, as …

Charting Your Own Course: Diverse Paths To Occupational Health Psychology, Irvin Sam Schonfeld

Publications and Research

This piece describes my pathway, via stressful work experiences, into occupational health psychology (OHP). Those work experiences combined with my later training in epidemiology at Columbia led me to the study of work, stress, and health. I briefly describe key research experiences with Joe Mazzola of Meredith College (the role of qualitative research in theory development and hypothesis generation) and Renzo Bianchi of the Norwegian University of Science and Technology (research on burnout–depression overlap and the creation of scales to assess occupational depression, occupational anxiety, and pandemic-related anxiety). The piece concludes with ideas for newcomers to OHP for getting the …

Arts-Based Sustainability: From New York To Malawi, Martha B. Lerski

Publications and Research

Recognizing that libraries serve multiple constituencies and subject areas, this chapter documents and advocates for development of transdisciplinary arts-based research (ABR) and culture-related projects linked to environmental challenges. Libraries contribute collections and spaces, as well as the research of library and information scientists. Libraries are currently among invisible contributors to sustainability planning and services. The chapter will link this invisibility to the value of what visual arts refer to as negative space elements in subjects ranging from traditional ecological knowledge to environmental science. Library collections, projects, and research contribute to education for sustainable development (ESD) as required to achieve the …

Integrating Universal Generative Ai Platforms In Educational Labs To Foster Critical Thinking And Digital Literacy, Vasiliy S. Znamenskiy, Joel Hernandez, Rafael Niyazov

Publications and Research

This study investigates the educational potential of generative artificial intelligence (GenAI) platforms based on large language models (LLMs), such as ChatGPT, Claude, and Gemini, as tools for studentcentred learning. Recognizing the current limitations of GenAI, particularly its propensity for generating inaccurate or misleading information—the paper proposes a novel instructional strategy: an interdisciplinary laboratory designed to foster critical evaluation of GenAI-generated outputs. In this pedagogical model, students engage with GenAI systems by posing questions or solving problems drawn from topics they have already studied and understand. Equipped with correct answers, students are positioned to assess the accuracy and relevance of AI-generated …

Quantum-Enhanced Training Of Large Language Models: A Hybrid Approach, Nan Wu, Fangmin Song, Xiangdong Li

Publications and Research

The training of large language models (LLMs) presents significant computational challenges, particularly regarding efficient convergence. This paper presents a hybrid quantum-classical framework designed to address the significant computational challenges associated with training large language models (LLMs). By integrating quantum computing principles superposition, entanglement, and tunneling with classical deep learning methods, we propose an approach to accelerate convergence, enhance optimization efficiency, and improve model generalization. Specifically, quantum feature mapping is employed to project classical data into high-dimensional Hilbert spaces, facilitating more expressive data representations. Quantum-assisted optimization algorithms, such as Quantum Approximate Optimization Algorithm (QAOA) and Variational Quantum Eigensolver (VQE), efficiently navigate …

In The Quest For New Horizons: Evaluating Novel Therapeutic Approaches For Tuberculosis Treatment, Selassie Mawuko, Aminata Traore, Bibi-Sakeena Khemraj, Anna Steto, Richa Gupta

Publications and Research

Tuberculosis (TB) in humans, caused by Mycobacterium tuberculosis, is a significant global health concern, resulting in high disease burden and mortality each year which together make it the world’s topmost infectious killer. The emergence of multidrug-resistant tuberculosis (MDR-TB) in recent decades has further exacerbated the present situation and warrants an urgent need to develop and investigate innovative treatment regimes. This study aims to assess the therapeutic potential of newly identified drug candidates, namely Bedaquiline, Delamanid, and Linezolid, in treating MDR-TB. We adopted a consolidated and integrated approach encompassing a thorough literature review, empirical experimental studies, multiple sequence alignments, and …

Bayesian Statistics: Origins And Applications, Evelyn Pulla

Publications and Research

Bayesian Statistics applies Bayes' Theorem to update beliefs through new evidence. In this project, I explored how Bayesian Statistics applies into real supporting decision-making under uncertainty. By solving problems using data, I was able to realize how prior knowledge and evidence collaborate to make better conclusions. The project also demonstrates how Bayesian reasoning corrects our intuition to make decisions based on logical reasoning. Through this project, I was able to learn why using probability to make informed decisions matters both in science and real life.

Automation Of Javanese Shadow Puppets Using Machine Control, Kristian Rice, Yinson Tso, Mukhammadali Yuldoshev

Publications and Research

The virtualization of Javanese shadow puppetry (Wayang Kulit) offers a unique opportunity to preserve and revitalize traditional performance art through immersive digital platforms. This project explores the development of a virtual Wayang Kulit experience using real-time 3D engines like Unity/Unreal Engine while focusing on simulating the mechanics and aesthetics of shadow puppet performance. The puppets are designed using detailed 2D planes and rigged with skeletal systems to reflect the stylized motion of traditional puppetry. An aspect of this project is integrating an AI-driven control system that autonomously animates the puppets, learning from recorded puppeteer performances to replicate gesture, rhythm, and …

Symmetry Induced Pairing In Dark Excitonic Condensate At Finite Temperature, Adham Alkady, Anatoly Kuklov

Publications and Research

Bose Einstein condensate of dark intervalley excitons must be inherently multi-component because of crystalline symmetries. Since valleys hosting such excitons are separated by large quasi-momenta, a minimal inter-component Josephson-type coupling can only be established between pairs of excitons from the time-reversed valleys. As a result, a paired condensate can emerge at finite temperature, that is, the off-diagonal order exists for the pairs from the time-reversed valleys, while the individual valleys are disordered. This prediction follows from the elementary mean field analysis regardless of the dimensionality. However, as Monte Carlo simulations show, no such a phase exists in 3D crystals. Instead, …

Hybridize Functions: A Tool For Automatically Refactoring Imperative Deep Learning Programs To Graph Execution, Raffi Khatchadourian, Tatiana Castro Vélez, Mehdi Bagherzadeh, Nan Jia, Anita Raja

Publications and Research

Efficiency is essential to support responsiveness w.r.t. ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code—supporting symbolic, graph-based Deep Neural Network (DNN) computation. While scalable, such development is error-prone, non-intuitive, and difficult to debug. Consequently, more natural, imperative DL frameworks encouraging eager execution have emerged but at the expense of run-time performance. Though hybrid approaches aim for the “best of both worlds,” using them effectively requires subtle considerations to make code amenable to safe, accurate, and efficient graph execution—avoiding performance bottlenecks and semantically inequivalent results. We discuss the engineering aspects of a …

Hybridize Functions: A Tool For Automatically Refactoring Imperative Deep Learning Programs To Graph Execution, Raffi Khatchadourian, Tatiana Castro Vélez, Mehdi Bagherzadeh, Nan Jia, Anita Raja

Publications and Research

Efficiency is essential to support responsiveness w.r.t. ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code—supporting symbolic, graph-based Deep Neural Network (DNN) computation. While scalable, such development is error-prone, non-intuitive, and difficult to debug. Consequently, more natural, imperative DL frameworks encouraging eager execution have emerged but at the expense of run-time performance. Though hybrid approaches aim for the “best of both worlds,” using them effectively requires subtle considerations to make code amenable to safe, accurate, and efficient graph execution—avoiding performance bottlenecks and semantically inequivalent results. We discuss the engineering aspects of a …

Hybridize Functions: A Tool For Automatically Refactoring Imperative Deep Learning Programs To Graph Execution, Raffi Khatchadourian, Tatiana Castro Vélez, Mehdi Bagherzadeh, Nan Jia, Anita Raja

Publications and Research

Efficiency is essential to support responsiveness w.r.t. ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code—supporting symbolic, graph-based Deep Neural Network (DNN) computation. While scalable, such development is error-prone, non-intuitive, and difficult to debug. Consequently, more natural, imperative DL frameworks encouraging eager execution have emerged but at the expense of run-time performance. Though hybrid approaches aim for the "best of both worlds," using them effectively requires subtle considerations to make code amenable to safe, accurate, and efficient graph execution—avoiding performance bottlenecks and semantically inequivalent results. We discuss the engineering aspects of a …

Theoretical Proof Of And Proposed Experimental Search For The Ground Triplet State Of A Wigner-Regime Two-Electron ‘Artificial Atom’ In A Magnetic Field, Marlina Slamet, Viraht Sahni

Publications and Research

It is experimentally established that there is no ground triplet state of the natural He atom. There is also no exact analytical solution to the Schrödinger equation corresponding to this state. For a two-dimensional two-electron ‘artificial atom’ or a semiconductor quantum dot in a magnetic field, as described by the Schrödinger–Pauli equation, we provide theoretical proof of the existence of a ground triplet state by deriving an exact analytical correlated wave function solution to the equation. The state exists in the Wigner high-electron-correlation regime. We further explain that the solution satisfies all requisite symmetry and electron coalescence constraints of …