Digital Commons Network^™

Promoting Critical Ai Literacy Through Online Video-Based Discussion, Mazid Ul Hasan, Janet Mannheimer Zydney

Teaching Online Pedagogical Repository

Video-based discussions can foster critical AI literacy by focusing on the potential benefits, challenges, and ethical considerations of using AI in education. The discussion may include video presentations with real-world examples about AI's advantages and pitfalls, synchronous discussions on video platforms, and asynchronous discussions that allow students to post answers through video. Prompts such as whether AI's benefits outweigh its costs or vice versa may bring in nuanced discourse, promoting a critical outlook toward AI among students.

Ucf Pegasus Plan - 5th Grade - Spilled Tea And Signed Freedoms, Sarah Gaudiosi, Milka Lucas-Dominguez, Maya Lopez, Natalie Ferguson, Destineebrittney Selby

Pegasus Plans: Social Studies Unit Plans for Florida Teachers

During this unit, students will explore the causes, key events, influential figures, and significant documents of the American Revolution through hands-on activities, interactive timelines, primary sources, and multimedia tools. Students will deepen their understanding of American Independence by examining the contributions of African Americans and women during the Revolutionary War, analyzing the terms and impact of the Treaty of Paris, and reflecting on how the Revolution continues to influence American government and society today.

Meeting Minutes 06-18-2025, Staff Advisory Council

Staff Advisory Council Meeting Documents

No abstract provided.

Susan Stanford Friedman, Christine Froula

James Joyce Literary Supplement

No abstract provided.

Irish Environmental Humanities, Emily Reiff

James Joyce Literary Supplement

No abstract provided.

Joyce’S Genealogy, Ryan Kerr

James Joyce Literary Supplement

No abstract provided.

Modern/Traditional/Radical, Shantam Goyal

James Joyce Literary Supplement

No abstract provided.

Radio Empire, Alex Fabrizio

James Joyce Literary Supplement

No abstract provided.

House, Richard C. Crepeau

On Sport and Society

With the settlement in the House Case finally being accepted by U.S. District Judge Claudia Wilken, five years of litigation has come to a close. It might be tempting to say, “the other shoe has dropped.” Unfortunately, College Athletics is not a biped, but rather a centipede. It is likely then that hundreds of more shoes are yet to drop.

Comparative Analysis Of Matrix Factorization And Neural Collaborative Filtering For Movie Recommendation Systems, Mahyar Alinejad

Data Science and Data Mining

This paper presents a comparative study of two recommendation system approaches for predicting movie ratings: Matrix Factorization with Stochastic Gradient Descent (SGD) optimization and Neural Collaborative Filtering (NCF) using Tensor Flow. The study aims to evaluate the effectiveness of these methods in recommending movies to users based on the MovieLens 100K dataset. The Matrix Factorization approach utilizes latent features to model user preferences and item characteristics, optimizing parameters through SGD. On the other hand, NCF integrates traditional collaborative filtering with neural networks to capture complex user-item interactions. Experimental results demonstrate the performance of both models in terms of Root Mean …

Detecting Physical Activity Using Wearable Sensor Data, Dipok Deb

Data Science and Data Mining

This study focuses on detecting physical activity using wearable sensor data, specifically distinguishing between walking and running. A dataset comprising accelerometer and gyroscope readings is used to train and evaluate various machine learning models, including logistic regression, random forest, k-nearest neighbors, naïve Bayes, and XGBoost. Extensive preprocessing, such as creating lag features and rolling statistics, is performed to enhance temporal data representation. The models are evaluated using metrics like accuracy, precision, recall, and F1 score. Incorporating lag and rolling features significantly improves model performance, with logistic regression achieving perfect scores across all metrics. These findings demonstrate the effectiveness of enhanced …

Public Health Simulation Infused Program (Pship) Toolkit, Desiree A. Díaz, Mindi Anderson, Francisco Guido-Sanz, Peggy Hill, Samantha Stephenson, Heather Peralta, Syretta Spears, Geraldine Luzincourt

Faculty Scholarship and Creative Works

Project Narrative

PURPOSE AND NEED

Purpose: Priorities set forth by the Health Resources & Services Administration (HRSA) are addressed in the proposed simulation program in an effort to meet curricular needs and foster care to the medically underserved in Florida, further exposing students to public healthcare needs. Interprofessional (nursing and social work) and intraprofessional (undergraduate nurse and Nurse Practitioner [NP]) instruction is essential in the simulation-based education (SBE) program, promoting important content on identifying risk factors and health assessment of the medically underserved community (MUC) (Education Priority 2, §831). Coordination of medical care is a vicarious learning opportunity for all …

Agenda 2025-06, Staff Council

Staff Advisory Council Meeting Agendas

A meeting agenda is a list of the topics that will be discussed during a meeting, along with other details. The agenda is usually shared with participants before the meeting so they can prepare. The agenda's purpose is to give participants a clear outline of what should happen in the meeting, who will lead each task, and how long each step should take.

Meeting Minutes 05-21-2025, Staff Advisory Council

Staff Advisory Council Meeting Documents

No abstract provided.

Rose, The Commissioner, And The Hall, Richard C. Crepeau

On Sport and Society

It seems that the biggest news in baseball this week is off the field. Usually, that is not a good thing. Yesterday, the Commissioner of Baseball, Rob Manfred, announced that Pete Rose and sixteen other players have been re-instated from baseball’s “permanently ineligible” list. Among the sixteen others are several players caught up in the Black Sox scandal of 1919.

The Power Of Preference: How Assignment Choice Shapes Learning In Statistics, Joshua Guillemette, Charlotte A. Jones-Roberts

Research Data and Datasets

Assignment choice is an increasingly explored instructional strategy in undergraduate education, particularly in courses where students often struggle to find personal relevance or maintain motivation. In statistics education, where conceptual abstraction and perceived difficulty are common barriers, offering structured choices in group formation and dataset selection may enhance engagement and learning outcomes. This study investigates the effects of assignment choice on student self-efficacy, performance, and group behavior within a large introductory statistics course. Using a one-way ANOVA design, the study compared academic outcomes across three conditions: randomly assigned groups, self-selected groups, and independent work. Students completed six scaffolded projects over …

Performance Of Lasso And Ridge Regression For Variable Selection In Genome-Wide Association Studies Of Maize Flowering Time, Dipok Deb

Data Science and Data Mining

Genome-Wide Association Studies (GWAS) are instrumental in identifying genetic variants linked to complex traits, providing valuable insights into trait heritability and biological mechanisms. This study applies GWAS to investigate flowering time in maize, a critical adaptive trait, using a diverse dataset of 5,000 recombinant inbred lines across eight environments. Traditional GWAS methods often encounter challenges in high-dimensional datasets due to the presence of multiple small-effect genetic loci. To address this, we compared two penalized regression methods—LASSO and Ridge regression—to perform variable selection and regression analysis within a GWAS framework. LASSO effectively reduced the number of predictors by selecting the most …

Data Science Job Salary Prediction Using Linear Regression, Dipok Deb

Data Science and Data Mining

In the evolving landscape of data science, accurate salary prediction plays a crucial role in shaping career expectations, informing educational strategies, and guiding organizational hiring decisions. This study investigates the key factors influencing entry-level data science salaries in the United States by applying a multiple linear regression model to a recent dataset spanning from 2020 to 2024. Through data preprocessing, transformation, and diagnostic evaluation, we identify how job roles, experience levels, employment types, work arrangements, residency status, and company size impact compensation. Despite challenges such as outliers, heteroscedasticity, and non-normal residuals, model refinements like the Box-Cox transformation and variable selection …

Handwritten Digit Recognition Using Machine Learning, Dipok Deb

Data Science and Data Mining

Handwritten Digit Recognition (HDR) remains a fundamental benchmark in pattern recognition and machine learning due to its practical applications and inherent classification challenges posed by diverse handwriting styles. This study investigates and compares two classical statistical classifiers—Gaussian Naive Bayes (GNB) and Linear Discriminant Analysis (LDA)—to recognize the digits from the MNIST dataset. Both models assume underlying normality in feature distributions and offer computational efficiency, making them suitable for high-dimensional input such as image pixels. Using 60,000 training and 10,000 test samples, we evaluate model performance through accuracy, precision, recall, F1 score, and confusion matrices. The results reveal that while GNB …

Clustering Dataset Using K-Mean Clustering, Dipok Deb

Data Science and Data Mining

Clustering is a fundamental technique in unsupervised machine learning, widely applied in various domains such as pattern recognition, data segmentation, and anomaly detection. This study evaluates the performance of the K-Means clustering algorithm on multiple benchmark datasets, including low-dimensional, high-dimensional, and imbalanced datasets. The clustering results are assessed using four key evaluation metrics: Mean Squared Error (MSE), Adjusted Rand Index (ARI), Normalized Mutual Information (NMI), and Silhouette Score. Experimental results demonstrate that K-Means performs effectively on datasets with well-separated clusters, particularly in high-dimensional spaces, where it achieves near-perfect clustering accuracy. However, its performance deteriorates in datasets with overlapping clusters and …

Using Genai To Develop A Peer-To-Peer Feedback Assignment That Fosters Online Student Interaction, Karen Edwards

Teaching Online Pedagogical Repository

This TOPR strategy demonstrates that with the help of generative Artificial Intelligence (GenAI) tools (e.g., ChatGPT40; Claude3.5 Sonnet), online instructors can quickly develop interactive student feedback activities that foster critical thinking skills while building a community of learners (Fowlin, et al., 2025).

Creating Smaller, Stable Discussion Communities Within Larger Online Courses, Mary Adler

Teaching Online Pedagogical Repository

Given the adverse effects of large online discussions for student engagement and learning, the entry offers a strategy to establish smaller communities of learners by utilizing stable group sets for a series of learning logs. Steps include soliciting student input on their interests; grouping sets to join together students with common interests; using community-building prompts that include icebreakers, connection to lived experience, and soliciting thoughtful responses; and providing faculty feedback and modeling. Students were enthusiastic about the approach in survey data, with 100% recommending continued use, either as is (76%) or with minor changes (24%).

Meeting Minutes 04-16-2025, Staff Advisory Council

Staff Advisory Council Meeting Documents

No abstract provided.

March Madness Plus, Richard C. Crepeau

On Sport and Society

March Madness, the NCAA marketing term, often is anything but. This year in both the women’s and men’s rendition, March Madness spilled over, as it often does into April. The final weekend, featuring the men’s and women’s semi-finals and finals, offered more madness than could have been hoped for.

Agenda 2025-04, Staff Council

Staff Advisory Council Meeting Agendas

A meeting agenda is a list of the topics that will be discussed during a meeting, along with other details. The agenda is usually shared with participants before the meeting so they can prepare. The agenda's purpose is to give participants a clear outline of what should happen in the meeting, who will lead each task, and how long each step should take.

Injury Prevention Research In Athletes, Maura Tangney

UN SDG Open Pedagogy Faculty Fellowship: Renewable Assignments

No abstract provided.

March Is Full Of Madness, Richard C. Crepeau

On Sport and Society

Today is the first day of the Men’s Sweet Sixteen in the Moveable Feast called March Madness. It comes in an extended weekend of what might be the maddest March in history. No, I am not talking politics. I am talking about sports in America and a television schedule that could burn out the circuitry on TV sets across the country.

Meeting Minutes 03-19-2025, Staff Advisory Council

Staff Advisory Council Meeting Documents

No abstract provided.

Comparative Evaluation Of Linear Regression, Cross Validation And Regularization Approaches In Multivariate Data Analysis, Ransford Owusu, Felix Yeboah, Francis Effah Boateng

Data Science and Data Mining

This study evaluates linear regression and its enhanced variants incorporating cross-validation and regularization techniques for high-dimensional, multivariate datasets. We address challenges such as multicollinearity and overfitting. Methods including Ridge, LASSO, and Elastic Net are compared against ordinary least squares regression. Empirical analysis using an automobile dataset for fuel efficiency prediction shows that while OLS regression captures basic relationships, its limitations are mitigated through regularization and cross-validation, resulting in improved model interpretability. The findings provide a comprehensive framework for predictive modeling in complex data environments and offer insights into statistical methodology and practical applications in the automobile industry.

Meeting Minutes 02-19-2025, Staff Advisory Council

Staff Advisory Council Meeting Documents

No abstract provided.