Math in the Modern World

Students are asked to gather nutrition data regarding their favorite snacks and assess how well they contribute to their maintenance of a “healthy” diet, as defined through, articles, websites, and guidelines established by the US Department of Agriculture

EMBRACING CHANGE: UNVEILING TEACHERS’ EXPERIENCES IN THE DEPARTMENT OF EDUCATION “OPLAN BAKLAS” BARE CLASSROOM WALLS POLICY

This phenomenological study explored the lived experiences of 10 purposively selected teachers in implementing the Department of Education’s “Oplan Baklas” Bare Classroom Walls Policy. Using a qualitative research design, data were gathered through in-depth interviews and analyzed using Colaizzi’s method for phenomenological analysis. The findings revealed several challenges faced by teachers, including the absence of visual learning materials, reduced learner engagement, difficulty in introducing new concepts, restricted creativity, and a diminished sense of community within the classroom. Participants also expressed concerns about emotional and financial burdens, although some acknowledged that the policy helped reduce classroom decoration expenses. To overcome these challenges, teachers demonstrated resilience and adaptability by reassessing their teaching strategies, becoming more resourceful, and integrating computer-aided instruction. They creatively maximized their learning spaces, leading to improved learner attention and a more focused environment. Some teachers embraced the policy as an opportunity to rethink conventional classroom norms and practices. Ultimately, this study underscores the importance of teacher adaptability and innovation in navigating systemic educational reforms, highlighting that even in the face of limitations, educators can transform challenges into meaningful opportunities for growth, creativity, and professional development.  Article visualizations

The “Knapsack Problem” Workbook: An Exploration of Topics in Computer Science

This workbook provides discussions, programming assignments, projects, and class exercises revolving around the “Knapsack Problem” (KP), which is widely a recognized model that is taught within a typical Computer Science curriculum. Throughout these discussions, we use KP to introduce or review topics found in courses covering topics in Discrete Mathematics, Mathematical Programming, Data Structures, Algorithms, Computational Complexity, etc. Because of the broad range of subjects discussed, this workbook and the accompanying spreadsheet files might be used as part of some CS capstone experience. Otherwise, we recommend that individual sections be used, as needed, for exercises relevant to a course in the major sequence. Each section, save for the Introduction, is written so that it can be presented independently of any other

An Improved Upper Bound for the Ring Loading Problem

The Ring Loading Problem emerged in the 1990s to model an important special case of telecommunication networks (SONET rings) which gained attention from practitioners and theorists alike. Given an undirected cycle on $n$ nodes together with non-negative demands between any pair of nodes, the Ring Loading Problem asks for an unsplittable routing of the demands such that the maximum cumulated demand on any edge is minimized. Let $L$ be the value of such a solution. In the relaxed version of the problem, each demand can be split into two parts where the first part is routed clockwise while the second part is routed counter-clockwise. Denote with $L^*$ the maximum load of a minimum split routing solution. In a landmark paper, Schrijver, Seymour and Winkler [SSW98] showed that $L \leq L^* + 1.5D$, where $D$ is the maximum demand value. They also found (implicitly) an instance of the Ring Loading Problem with $L = L^* + 1.01D$. Recently, Skutella [Sku16] improved these bounds by showing that $L \leq L^* + \frac{19}{14}D$, and there exists an instance with $L = L^* + 1.1D$. We contribute to this line of research by showing that $L \leq L^* + 1.3D$. We also take a first step towards lower and upper bounds for small instances

Models for Decision-Making - Second Edition

Decision-Making often refers to a multi-stage process that starts with some form of introspection or reflection about a situation in which a person or group of people find themselves. These ruminations usually lead to series of questions that need to be answered, or to a set of data that needs to be collected and analyzed, or to some calculations that need to be performed before someone can be in a position to make informed decisions and take appropriate actions.We provide some simple examples of Quantitative Models, which are often found in a decision-making situation. We focus on the use of algebraic equations, probability models, the “Payoff Table” and “Decision Tree” models, to represent situations involving a sequence one or more of decisions over time. Concepts are illustrated with a large set of examples that can be presented during classroom instruction and can be practiced by the students, either individually or in groups, through homework or lab exercises

Lab Exercises for Statistics Using Excel

This document contains the text associated with a series of computer-based lab exercises to help students apply the concepts usually included in a first course in Statistics. A compressed file has been included that contains a separate folder for each lab. In each folder is an excel spreadsheet file and an editable word document providing the instructions for students to complete the exercise. The exercises are not numbered in the folders, so you can select any subset of these exercises to assign to your students. You are free to modify the instructions in any way you see fit, e.g., to add activities or to articulate the format of the lab-reports that will be completed by the student or the student groups as part of the exercise