Project Proposal for Rebuilding Lives: An E-learning Course on Social Responsibility and Big Data

Introduction: The issue of houselessness and mental health support in society is a complex challenge, influenced by the lack of accessible resources, educational gaps, and insufficient public understanding. Rebuilding Lives aims to bridge the gap between existing misconceptions and actionable solutions by introducing an engaging e-learning course through the Canvas LMS.

This project addresses a significant educational gap: community college students often lack opportunities to develop social responsibility and apply data-driven solutions in real-world contexts. Current learning outcomes focus heavily on theoretical knowledge, with limited applications for developing empathy, problem-solving, and decision-making using Big Data insights. This course will introduce students to essential community-building strategies, equipping them with skills in critical data interpretation and ethical resource allocation. The course will also integrate real-world data sources, ensuring students can access and navigate important public data repositories.

A case study approach will be used to support students as they translate their ideas into action. To enhance realism, students will participate in a “Call for Proposals” activity that walks them through the process of applying for funding to address a real-world problem in their community. The proposal will include identifying a real-world need, developing a comprehensive plan, budgeting and allocating resources, and identifying potential community partners.

Instructional Goal: Learners will demonstrate their ability to analyze community data and create sustainable, evidence-based action plans for addressing houselessness and advocating for mental health services.

Sub Goal 1: Understanding the Issue: Learners will identify key community issues, such as housing instability and mental health service disparities, using case studies and statistical data.

After completing this module, the learner will:

  • Objective 1.1: Identify relevant social service entities in a given community case study.
  • Objective 1.2: Analyze the causes and impacts of housing instability using real-world scenarios.
  • Objective 1.3: Evaluate gaps in services for vulnerable populations and identify potential areas for improvement.

Sub Goal 2: Introduction to Data-Driven Solutions: Learners will interpret community health data and recognize patterns that influence policymaking and resource allocation.

After completing this module, the learner will:

  • Objective 2.1: Interpret visualizations of key community data, such as bar graphs and maps.
  • Objective 2.2: Apply basic data mining principles to simulate decision-making in resource distribution.
  • Objective 2.3: Explain how Big Data insights influence local policy decisions and resource allocation.

Sub Goal 3: Advocacy in Action: Learners will develop persuasive communication strategies to advocate for solutions using storytelling and data visualizations.

After completing this module, the learner will:

  • Objective 3.1: Develop a narrative that combines data insights with personal testimonies.
  • Objective 3.2: Design effective visualizations that simplify complex data for community stakeholders.
  • Objective 3.3: Role-play advocacy efforts by presenting findings in a mock proposal to peers and receiving feedback.

Sub Goal 4: Crafting the Plan: Learners will create and present a detailed resource allocation plan that balances housing, mental health services, and community trust.

After completing this module, the learner will:

  • Objective 4.1: Synthesize data from multiple sources to propose a balanced resource allocation model.
  • Objective 4.2: Justify decisions using both qualitative and quantitative evidence.
  • Objective 4.3: Create a multimedia presentation that communicates the resource plan to a public audience, simulating a real-world funding pitch.

Intended Audience: The intended audience for this course comprises high school students and first-year community college students, primarily aged 16–22, with a class size of 27.

  1. Diverse Academic Backgrounds: Many students may have limited experience with data analysis but a strong interest in community advocacy. Instruction will include foundational data literacy tutorials.
  2. Technology-Driven Learning Preferences: Students are comfortable with digital interfaces but may need assistance navigating data dashboards and accessing online data sources. Interactive video guides, step-by-step tutorials, and user-friendly LMS layouts will support this.
  3. Varied Socio-Cultural Contexts: A culturally inclusive approach, incorporating local and global examples, will ensure the content resonates with students’ lived experiences.

Learning Context: The course will be delivered fully online via Canvas, incorporating multimedia resources, discussion boards, and interactive modules.

Characteristics:

  • Asynchronous Participation: Students will engage in self-paced assignments with structured deadlines.
  • Multimedia Content: Lessons will feature video presentations, case simulations, and interactive graphs to enhance engagement.
  • Collaborative Spaces: Virtual discussion boards will facilitate peer learning, reflection, and personalized feedback.

Resources:

  • Online access to real-world data sets (e.g., housing reports, mental health statistics).
  • Canvas-integrated assessment tools (quizzes, peer-reviewed projects).
  • Tools such as Padlet for collaborative brainstorming, Kahoot for interactive quizzes, and Power BI dashboards for data exploration.

Constraints:

  • Some students may face challenges with internet access or balancing external commitments. Solutions will include downloadable resources, mobile-friendly course design, and offline assignment options.

Summary: This instructional solution leverages e-learning to bridge the gap between theoretical knowledge and practical action. Each module offers an integrated approach to understanding houselessness and mental health, developing learners’ data literacy and communication skills through an immersive, accessible platform.

Rebuilding Lives will foster critical thinking and promote meaningful contributions to community advocacy by engaging students with real-world simulations, storytelling, and resource management tasks. The “Call for Proposals” activity will personalize the learning experience and provide students with actionable tools for making a difference. Additionally, comprehensive tutorials will ensure students can effectively access and query real-world data, empowering them to develop informed, impactful plans.