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Data Interpretation Project (AI-Assisted)

Benefits

  • Enhances critical thinking by allowing students to focus on interpretation rather than data crunching.
  • Provides real-world data interpretation experience.
  • Familiarizes students with cutting-edge AI tools used in professional settings.

Project Learning Outcomes & Alignment

Outcome Activity
Generate a relevant key question that connects with the course concepts and/or topics Blueprint Beacon (Project Plan)
Interrogate personal biases, unchecked assumptions, and ethical implications in relation to the key question Blueprint Beacon (Project Plan)
Examine the context of a key question using critical thinking strategies. Blueprint Beacon (Project Plan)
Collect and compare relevant real world data from credible sources Fact Foraging and Data Diving (i.e., Research & Data Quest)
Summarize and describe the data being used The Data Diary (i.e., Data Interpretation Brief)
Identify the main features, characteristics, and key highlights from data The Data Diary (i.e., Data Interpretation Brief)
Analyze patterns and trends in data The Data Diary (i.e., Data Interpretation Brief)Insight Ignition (i.e., Presentation of Findings)
Interpret the significance of the data in relation to the key question and topic Insight Ignition (i.e., Presentation of Findings)

Suggested Project Schedule

Note to instructors: Below is a suggested schedule and order for the project. Every course is unique, so choose a flow that works best for your course.

Week Activity Title Description
3 Blueprint Beacon Project plan
5 Data Diving and Fact Foraging Research and data quest
7 The Data Diary Data discussion and interpretation
10 Insight Ignition Presentation and findings

AI Collaboration

We recognize that students have a range of familiarity, experience, and feelings associated with the utilization of generative (AI) Artificial Intelligence tools in an academic context. You are not required to use AI tools for this project. Collaboration with AI tools will be limited as described in the reference table below and are articulated in activity instructions. You can choose to opt out if you prefer. If you haven’t had the opportunity to use AI tools, this is a safe space to experiment.

Activity AI Collaboration Type
Milestone 1 | Blueprint Beacon (Plan) topic exploration key question generation outline a project plan
Milestone 2 | Fact Foraging and Data Diving (Research) Generate a list of potential sources for finding relevant research, information, and data Conduct and compare CRAAP tests on sources
Milestone 3 | The Data Diary (Data Review and Interpretation) Create a data visualization
Milestone 4 | Insight Ignition(Presentation) Create a presentation

Which AI tool should I use?

A recommendation is to use the AI tool to which your institution subscribes to. Using technological tools that are supported by the university ensures that if you encounter technical issues or have questions the Academic Technologies department can provide assistance.

When considering the use of an AI tool, consider the following:

  • How can I use AI ethically and responsibly as a student?
    • Suggested actions:
      • Be transparent with how you use AI tools. This might include a brief description of the tasks you used it for. For example, “I used Microsoft Copilot to generate a list of potential titles for my project and an outline for the paper. This helped me to organize my projects, so I had a framework to start from.”
      • Cite which tools you used using the approved convention (e.g., APA, MLA) Refer to Citing AI Use section below.
  • Will using an AI tool in such a way violate the course and/or institution’s Academic Integrity policies?
    • Suggested action: Always reach out to your instructor and consult if you have any concerns. Seeking clarification proactively will help to mitigate unintentional academic integrity violations. Review your academic institution’s Academic Integrity policy / Student Code of Conduct for expectations around permitted, prohibited, and transparent (i.e., citations) use.
  • Will my data be secure or unsecure?
    • Suggested action: Review the Terms of Service and Privacy Policy. If you utilize a generative AI tool, other than your institution’s, a recommendation is to review the Privacy Policy and Terms of Use to familiarize yourself with how your data is used, stored, and shared. This is especially important with AI tools because of how they learn based on the prompts that are input into them. Some common generative AI tools also include ChatGPT and Claude. For additional information, review MIT’s Navigating Data Privacy article. When engaging with an AI tool, a recommendation is not to provide personal (e.g., name, address) or sensitive information.
  • Does this tool have known concerns around the generation of false information (i.e., hallucinations)? Review MIT’s When AI Gets it Wrong: Addressing AI Hallucinations and Bias article.
    • Suggested action: Maintain awareness that the tool may produce inaccurate information. Conduct your own research using diverse sources to identify gaps and confirm the relevance and reliability of the information produced.
  • Does this tool have known concerns related to perpetuating harmful biases and stereotypes? If so, how will I know? Review Edutopias Helping Students Check for Bias in AI Outputs article.
    • Suggested actions: Maintain awareness that the tool may reproduce and reinforce biases. Assess AI responses for lack of valid evidence, lack of reasoning/rationale, inaccurate connections, vague examples, missing perspectives, singular perspectives, assumptions, and/or exclusionary language.

Citing AI Use

The responsible use of generative AI tools enhances your learning experience while ensuring that you develop and demonstrate your understanding and skills. When you collaborate with AI, you will need to include the following:

  • Cite use of the tool usings the [insert citation] convention. Refer to the following library guide for format structure and examples.
  • Include the initial prompt
  • Identify the information used from the output.
  • Explain how you adapted the output and why

What are best practices to create prompts for generative AI tools?

To get started, you are now going to become an AI Prompt Engineer. Generative AI tools need an input (usually text but not always) to guide them to the correct and/or desired response that the user is requesting.

Here are a few best practices, according to Claude, to get you started:

  • Be specific and clear.
    • Do not be vague. The more specifics the tool can obtain the more likely it is to understand and fulfill your request.
  • Provide context
    • Provide the AI tool with relevant background information which will help with understanding the task at hand. E.g., subject, topics, intended audience, requirements/parameters
      • Share examples
        • Craft a sample of what you are looking for which aligns with your expectations for the output.
  • Break complex tasks down
    • If the task is complex, chunk it into smaller manageable steps. Similarly to what your instructor has done with this project (e.g., step 1, step 2).
  • Iterate and refine
    • Most likely the output from the tool will not be perfect on the first try. Continue to adjust and provide guidance to help refine the information you receive from the tool. You will need to keep ‘drilling down’ until you strike gold!

Purpose Statement

The purpose of this project is to identify a key question and use authentic real world research to examine and interpret key findings. There will be varied opportunities to collaborate with Artificial Intelligence (AI) tools on identified project elements. A culminating presentation of data interpretations will be shared with the class.

Overview | Setting the Stage

For this project, you will select a topic that personally resonates with you, within the context of the topics and/or concepts covered in this course.

Potential topics include but are not limited to:

  • TBD
  • TBD
  • TBD

If you have an idea that is not listed here, please contact the instructor to discuss the viability of your topic for this project. The instructor can help to assess how to focus the scope of your ideas, so that you can be successful in completing this project within the duration of the course.

Milestone Instructions

Milestone #1 | Blueprint Beacon (i.e., Project Plan)

Purpose

The project plan will serve as a roadmap by providing structure, clarity, and direction for your project. This helps to stay focused, manage the scope of your research, and ensure you have everything you need (e.g., sources, data) in place to complete the final deliverable (i.e., presentation). Information shared in this plan will also help the instructor focus and personalize feedback on each of the project deliverables.

Overview

For this activity, you will create a project plan which includes the following components

  • Topic
  • Key question (and possible alternatives)
  • Reflections: key questions, biases
  • Summary

Outcomes

  1. Generate a relevant key question that has the potential to address a challenge, problem, issue, gap, potential decision, concern etc.
  2. Interrogate personal biases, unchecked assumptions, and ethical implications in relation to the key question

Instructions

  1. Topic Exploration (AI collaboration optional)
    • To begin, identify topics of interest that relate to the concepts covered in this course. Reviewing the course description, learning outcomes, course schedule, etc. may be helpful to identify broad topic areas that you are personally interested in. Now do some research. Narrow down the options to one topic that you have the most interest in and have questions about. The topic is going to serve as the basis for the next step in the project which is to create a key question.
    • You have the option to use a generative AI tool for this activity, but it is not required.
    • Here is an example prompt to get you started:

      “Copilot, I am in [insert class] which is a college class. I have a project to complete that allows me to collaborate with an AI tool. I picked you! My task is to generate a list of potential topics to use for my project. The project will be to generate a key question related to a course specific topic. I will have to do research and locate data relevant to that question. Next I will analyze the data to identify patterns and trends in order to answer the key question. The class description is [insert description]. Here are the following course learning outcomes: [insert outcomes]. Here are a few high-level topics indicated in the course schedule: [insert topics]. When I initially took this class I was interested to learn about the following: [insert topic(s)]. Can you help me to explore potential topics that I can use for my project? Please format the list with bullet points, so it is easier for me to read. Please keep the list to 5 potential topics. Please note I may ask you additional questions to help refine the topics. Thank you for your assistance.”

    • Citing AI Use
      • Include the following:
        • Cite use of the tool usings the [insert citation] convention. Refer to the following library guide for format structure and examples.
          • Include the initial prompt
          • Identify the information used from the output.
          • Explain how you adapted the output from the tool
  2. Question Formation
    • For this assignment, you will generate a key question that relates to your chosen topic. The question should address a challenge, problem, issue, gap, potential decision, concern etc.
    • Characteristics of a SMART key question includes:
      • Specific: It relates to the field of study and addresses an issue, challenge, problem, concern, need, etc.
      • Measurable: The question can be examined using data. Is not answered with a yes or a no. Rather, research is needed to account for context.
      • Aligned: Situates the question within the academic context of this course and/or industry.
      • Relevant:
      • Time bound: The question can be addressed within the allotted time of this course.
    • As with step one, you may also collaborate with an AI tool for this portion of the assignment to formulate and refine the key question. You need to continue to follow best practices and AI citation guidelines. Refer to [insert reference] for requirements, guidelines, and support resources.

Example prompt: “Hello AI, I am working on a project for my [Course Name], and I need to generate a key question that will guide my research on a data interpretation project. My project focuses on [Topic], specifically addressing [Issue/Problem/Challenge] within the [chosen Industry]. The key question needs to have the following characteristics: feasibility, open ended, clear, specific, focused, and aligned. My objective is to find out [insert goal]. Please generate a bullet point list of 5-10 options. If you need more context regarding the key question characteristics please let me know. I also may ask you to refine the list depending on the initial outputs. Thank you!”

  1. Project Summary
    • Include the following reflections in the project summary:
      • Reflection | Key Question
        • Reflect and summarize the purpose of the question. Does the question reflect any of the following? If so, how?
          • describe potential impact of an action
          • articulate why something happened
          • predict if something will happen
          • compare the differences between two things
          • assess an issue, problem, or challenge
    • Explain why the question is relevant.
    • Explain how answering the question could be beneficial and/or valuable within real world contexts
    • Articulate what type of data could be helpful to answer the key question
    • Is there sufficient data accessible to complete an analysis? If not, why? Consult with the instructor in this case.
    • Reflection | Connecting to the Topic
      • Answer the following questions:
        • What has sparked your interest with this topic/question?
        • How does this topic and/or question relate to your personal experiences or professional field?
        • How do you think exploring this topic may change your current perspective?
        • What potential real world applications do you see for this type of research?
    • Reflection | Acknowledging Potential Biases
      • Next, you will critically interrogate your own biases and assumptions by answering the following questions:
        • How might your beliefs and initial understanding influence the way you have formed your question?
        • What may be some potential biases as it relates to this topic?
        • Am I making assumptions? If so, why?
        • Is my current thinking rooted in evidence, research, and or fact?
        • Ask yourself if your understanding is based upon stereotypes or unfounded generalizations.
    • After engaging in this mindfulness exercise, review the key questions again and revise based on your reflection (as applicable).

Instructor note:

  1. For this assignment, it may be beneficial to highlight what type of feedback students can expect to receive and how that information can be used and applied to the project. Additionally, if students may be required to revise and refine the questions iteratively based on instructor feedback, this may be valuable to share in the assignment instructions.
  2. Including a Muddiest Point discussion board, may be beneficial as a way to field questions about the project where all students can benefit and support one another.

Milestone #2 | Fact Foraging and Data Diving (i.e., Research & Data Quest)

Purpose

The purpose of conducting research is to situate the key question within context. Doing so ensures that meaning is associated with the information you find and the data you analyze. Through research you will uncover themes, patterns, and trends. Please note that data can be easily misinterpreted. The more context you have the less ambiguity there will be. Ideally, the research you conduct can mitigate incorrect assumptions and conclusions through continual checks (i.e., relevance, reliability, validity, and credibility) of sources and data. With all that said, let’s go on a data quest!

Outcomes

  • Source relevant data from credible sources
  • Identify data type, relevant characteristics, and variables

Instructions

  • After you have finalized your question, you will need to conduct a preliminary search for background information and data relevant to answering your key question. Before getting started, review the CRAAP test. You will be asked to review each source to ensure its relevance, reliability, validity, and credibility.
  • For this activity, you may collaborate with an AI tool to generate a list of potential sources for finding relevant research, information, and data. You need to continue to follow best practices and AI citation guidelines. Refer to [insert reference] for requirements, guidelines, and support resources.
    • Success tip! Include the following elements in your prompt input for the AI tool: topic overview, key question, objective, what types of information would be helpful, and type of sources (e.g., scholarly, government reports, peer reviewed articles, organizations).
  • Deliverables
    • Behind the Question: Exploring the Story
      • Identify [#] resources that you will use to research the context that aligns with your key question. Provide the following information for each source:
        • Write a brief summary of each source
          • Identify key points of information, data, theory, findings, discussion, etc. that highlights the relevance of the resource.
          • Identify at minimum 2-3 pieces of information that you can use for your project.
          • Explain the relevance of the source to the key question and topic.
          • You will need to cite using [insert preferred format] convention.
        • Conduct a CRAAP test on the sources. You do not have to answer every question. Rather, review each section and reflect on the questions. Make relevant notes a minimum five (one per element).
          • You may collaborate with AI, though not required, to compare sources and conduct a thorough CRAAP test. Success tip! Share the purpose of the project, objectives, the chosen resources (one by one) with summary, and the CRAAP test resource (linked above). You may find that you will have to iterate on your prompt to get the AI tool to help you conduct the CRAAP test.
    • Data Discovery
      • Identify the type of data needed (e.g., quantitative, qualitative)
      • Identify [#] potential databases or other sources where you can pull data from to help answer your key question. (e.g., Kaggle, Google Cloud Public Datasets). If you are considering using raw data versus an existing graph, chart, or diagram as one of your data sources, make sure that the data format available is compatible with Excel (i.e., .xls). This will help to simplify the data interpretation process that will be conducted in Milestone 3 | The Data Diary (i.e., Data Interpretation Brief).
    • Select at minimum two relevant data sources. Provide the following information for each source:
      • Write a brief summary of each source
      • What type of data is being captured
      • Where did the data come from
      • Who collected the data
      • What was the original purpose for collecting the data
      • What is the size of the data set? (e.g., sample size)
      • Identify the period of time that the data was collected
    • You will need to cite using [insert preferred format] convention.
    • Conduct a CRAAP test on the sources. You do not have to answer every question. Rather, review each section and reflect on the questions. Make relevant notes a minimum five (one per element).
  • Data Selection
    • Next, after you have conducted a thorough review of all the potential sources, identify two data sources that will work best for your project. Keep these handy as they will be used in Milestone 3 | The Data Diary.

Milestone 3 | The Data Diary (i.e., Data Interpretation Brief)

  • For this activity, you will be doing a deep dive into the data you have chosen which will ultimately aid you in generating a conclusion to the key question. You will be conducting a process called data interpretation on the two data sources you identified in Milestone 2 | Fact Foraging and Data Diving. Data interpretation will involve answering a series of questions that will help you to make observations about the data. The insights gleaned from this activity will help to inform your findings for this project.
  • To begin, first read the following article “Narrative visualization: Telling stories with data. Next, you will need to determine what type of data you are using. If you are using an existing visual representation of the data (e.g., graph, diagram), say from a report, you can proceed with answering the following questions. However, if you are using a raw dataset you may want to consider running the data through Excel to create a visual representation of the data. For guidance on creating a data visualization, review the section below entitled Data Demystified.
  • Data Demystified – Visualizing Data
  • Breaking Down The Bits – Interpreting the Data
    • Compare results within the data
      • Mean, media, mode, standard deviation
      • Review the outliers. What story do they tell?
      • Does the data show a consistent pattern? If so, explain. Articulate the significance of identified trends and patterns.
      • Is there a lack of pattern?
        • If so, how do you know?
        • What do you observe?
        • What story does a lack of pattern in the data communicate?
      • Do you observe any correlations? (e.g., as one variable goes up the other goes down)?
      • Is any of the data potentially misleading?
      • Identify at least two points of interest in the data that relate to the key question you are trying to answer. Explain how this information is helpful.
      • Compare results outside of the data
        • What differences or similarities do you note between both sources? Explain the relevance.
        • How does the data compare (i.e., similar, different) to other sources (e.g., municipal, state, or federal government reports?

Milestone 4 | Insight Ignition (i.e., Presentation of Findings)

You have officially made it to the grand finale of your project! This is an opportunity to share out and showcase the insights and interpretations from your data quest. For this final presentation, you have agency to choose how you would prefer to present. Feel free to get creative!

Here are a few ideas to get you started:

  • Insider news report
  • Storyteller
  • Detective solving a mystery
  • Boardroom meeting where you address a group of interested parties that do not have a data analysis background.
  • Committee briefing to local administrators
  • Interview (where someone asks you pre-planned questions)
  • Narrated PowerPoint presentation

Regardless of the way you choose to present, include the following in your presentation:

  • Provide a brief background on your topic of interest (refer to milestone #1)
  • Articulate the key question (refer to milestone #1)
  • Data summary (refer to milestone #2)
  • Discuss relevant trends that may highlight problems, issues, challenges, concerns, needs, etc. (refer to milestone #3)
  • Quality and relevance of conclusions drawn from the analysis (refer to milestone #3)
  • Share your understanding of the potential implications of the findings (refer to milestone #3)
  • Reflection
    • What insights did you gain from your data that you found most surprising or valuable?

As with other activities, collaboration with AI is allowed. If you choose to use AI, make sure to cite the tool, identify how the tool was used, and how you refined the output and applied it to the presentation. This should be a short summary that either accompanies the presentation, or the summary can be placed at the end of the presentation in the speaker notes.

Here are a few ways that AI can be used for:

  • Suggest logical presentation design and structure
  • Suggest layout and formatting ideas
  • Help to generate talking points outline
  • Review for clarity, consistency, and accuracy
  • Suggest areas that may need clarification
  • Help creating examples and scenarios
  • Taking a full summary that you generate and condensing it down

Evaluation

  • Criteria 1: Key Question Generation (Learning Outcome #1)
    • A SMART key question is generated that is contextualized and guides the data interpretation project by addressing a specific challenge, problem, issue, gap, decision, or concern within a chosen course topic.
  • Criteria 2: Kay Question Analysis (Learning Outcome #2)
    • Submission clearly articulates the analytical purpose the question serves, the relevance and value as a social good, data needs and access, and the examination of biases that may impact the research.
  • Criteria 3: Data Story & Interpretation (Learning Outcomes #3 and #4)
    • Submission includes a comprehensive examination of relevant and credible data by connecting key data points to the key question. The detailed and thorough examination includes the following elements: identifies data characteristics, interprets patterns and trends, compares data sources, and articulates insightful explanations of the significance of the data in relation to the key question and topic.

References

AI Use Disclosure

The following GenAI tools were used in the development of this assignment template.

AI assisted uses include:

  • generate engaging titles
  • create example prompts to submit to GenAI tools
  • list best practices for creating prompts to submit to GenAI tools
  • list of ways GenAI tools can assist with developing a presentation
  • generate a first draft of the evaluation rubric criteria #1 and #2
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