✨Tutorial: Easy Student Consent Management in Google Workspace

A simple way to gather and tabulate informed student consent (or the lack thereof) for your use of recordings, AI tools, and more.

[image created with Dall-E 3 via ChatGPT Plus]

Welcome to AutomatED: the newsletter on how to teach better with tech.

Each week, I share what I have learned — and am learning — about AI and tech in the university classroom. What works, what doesn't, and why.

In this fortnight’s Premium edition, I present a Tutorial for efficiently managing student consent in Google Workspace. This is an easy-to-implement, effective, and generalizable way to gather and tabulate your students’ consent (or lack thereof) for your use of recording software in class or in professor-student meetings or for your use of AI tools with their work.

In my recent ✨Guide to Ethically Using AI with Student Data, I present seven options:

  • 🛑 Option 1: Don’t Run Student Data Through AI

  • 🦺 Option 2: Limit to “Completely Safe” Categories

  • 🏰 Option 3: Stay Within Your Ecosystem

  • 🗣️ Option 4: Change the Consent Paradigm

  • 🥷 Option 5: Pseudonymize or Anonymize

  • 💻 Option 6: Use Local LLMs

  • 🔀 Option 7: A Combination of the Above

In this Tutorial, I explain how to reduce the cost and inconvenience of recording student consent in the Google ecosystem while improving transparency and communication with your students. This sort of solution is needed if you take Option 4 in the aforementioned Guide.

But why might you take Option 4 and attempt to change the consent paradigm with your students?

Here is an extended excerpt from the Guide of some of the considerations:

Another option would be to get explicit written consent from students in order to use any of their data with AI tools.

In my experiences discussing with students whether they consent to me using their data, they always appreciate being asked, even if the data and use case are completely safe (and not covered by FERPA). Why? They tell me that they know that the university and their professors have access to so much of their data, but that they wish it were more transparent how it is being used. They appreciate being respected and included in the process of teaching them and assessing their work.

Given that I think that this general desire amongst students for greater data transparency is more than reasonable, it is my view that it is worth trying to respect. In general, professors should be honest and they should be in the position to convince (reasonable) students that their uses of student data are worthwhile and worth consenting to.

[…]

My view is that relying completely on consent — whether the data in question is completely safe, personally identifiable, or whatever — is too extreme.

For me, the clearest exception cases to such a broad blanket policy are uses of student data that are completely safe (not even in principle personally identifiable) where it is costly or inconvenient to get consent and there are serious benefits of me running such data through AI tools.

The next clearest are cases where the data is personally identifiable in principle, but where I can take reliable steps to make it not personally identifiable in actuality (e.g., anonymize it, per Option 5) and where it is stored in an ecosystem I am already relying on to protect personally identifiable student data like sensitive emails. And I would even go so far as to suggest that consent is not morally required or needed in cases where I am using AI tools in such an ecosystem on data that is personally identifiable.

The less clear cases are cases where the AI tools are third-party like Fireflies.ai, Otter.ai, Zapier, or Make. Even if the relevant data is not personally identifiable in actuality, these are cases where consent should be sought because of the increased risk, the expectation of students to not have their data used this way (or their lack of expectation that it would be used this way), and so on. I will discuss this sort of mixed or combination strategy below in the discussion of Option 7…

(This is to set aside the question of conformity to my university’s data classification and usage policies, which are somewhat idiosyncratic. Professors should be aware of those institutional policies with which they must be compliant.)

With these considerations and alternative Options in mind, let’s consider one simple way to make large scale consent acquisition, management, and recording much simpler, at least within the Google ecosystem.

📝 Step 1 - Create Form(s)
for Collecting Consent

The first step in simplifying the process of acquiring student consent is to create a structured and clear method for gathering their permissions. Utilizing Google Forms provides an efficient and user-friendly way to achieve this. With Google Forms, you can design customized forms that specifically cater to your needs, ensuring that all necessary information is collected in an organized manner. This not only streamlines the process but also enhances transparency and trust with your students by clearly communicating what they are consenting to.

Creating these forms involves setting up fields to capture essential details, such as the student's name and email address, and presenting the consent options in a straightforward format. By using Google Forms' features, you can ensure that all responses are validated, reducing the chances of errors or incomplete submissions. Additionally, as I will show below in the subsequent Steps, the responses can be easily managed and recorded within the Google ecosystem, making it convenient for future reference and compliance purposes.

Let’s get started! Here is how to proceed:

  1. Open Google Forms with your institutional account

  2. Click the "+" button to create a new form

  3. Title the form (e.g., "Class 123: Professor-Student Meetings Consent Form").

  4. Add a description at the top that discloses what you are planning to do with the relevant student data. In short, this description should outline what you are requesting that the student consent to.

Obviously, the form that your description ought to take is complicated and context-sensitive. In this Tutorial, my focus isn’t on the details of a good and legally compliant description. However, I will flag a few of the complications here, using an excerpt from my ✨Guide to Ethically Using AI with Student Data. Note that this is an excerpt focused on the specific case of using student data with AI tools, but the points generalize to recordings and other cases where student consent is needed:

When seeking student consent for using their data with AI tools, we must recognize and address the challenges of ensuring genuinely informed consent. The complexity of AI technologies, coupled with the intricate implications of data usage, may not be readily understood by all students. I have found this to be true in my own experimentation with consent-based solutions at my institution.

For instance, a student might consent to their data being used for 'enhancing learning algorithms,' not fully realizing this could entail detailed analysis of their interaction patterns and potentially sensitive performance metrics.

To tackle this, educators should provide clear, comprehensive explanations of what data is being used, how it is being processed, and what the outcomes might be. This could involve simplified briefings, examples of data use cases, or even Q&A sessions where students can express concerns and request further information. Ensuring that consent is truly informed not only respects student autonomy but also fortifies trust in educational uses of technology, making it crucial to invest time and resources in educational initiatives that enhance understanding of AI's role and impact in the learning environment.

  1. Add the first question to capture the student's name

    • Click "Add question" (the plus sign).

    • Choose "Short answer" as the question type.

    • Label it "Name".

    • Make it a required question.

  2. Add the second question to capture the student's email address

    • Click "Add question".

    • Choose "Short answer" as the question type.

    • Label it "Email Address".

    • Make it a required question.

    • Click on the three dots in the bottom right and select "Response validation".

    • Choose "Text" -> "Email address" to ensure the input is in email format.

  3. Add the third question for consent

    • Click "Add question".

    • Choose "Multiple choice" as the question type.

    • Label it as you like (e.g. "Do you consent to the above?".

    • Provide three options: "Consent", "Do not consent", and "Not sure".

    • Make it a required question.

Here is what you will end up with:

  1. Repeat this process for all the cases where you expect to need to acquire student consent for this class

The second step in our process involves linking the responses from the Google Forms created in Step 1 to Google Sheets for easier management and analysis. We will create "follower" Sheets for each form to store individual responses and then consolidate these into a single "leader" Sheet. By linking each form’s responses to a dedicated "follower" Sheet, you ensure that all data is organized and accessible in a structured manner. Subsequently, the "leader" Sheet will aggregate these responses, allowing you to see at a glance which students have given consent and which have not. For instance, in my toy example, we end up with a Sheet that looks like this, dynamically filled based on student responses:

This method not only simplifies the process of tracking consent but also helps in maintaining a high level of organization and clarity, crucial for both compliance and communication purposes.

Let’s continue. Here are the sub-steps:

  1. Create a "follower" Sheet

    • In the Google Form, click on the "Responses" tab.

    • Click the green Sheets icon to create a new Google Sheet (this will be your "follower" Sheet).

    • Name the "follower" Sheet appropriately (e.g., "Professor-Student Meetings Consent Form").

  2. Repeat for each of the Forms you created in Step 1

The next step is to create a “leader” Sheet that gathers all of the responses from the “follower” Sheet.

  1. Create a new “leader” Sheet from scratch (blank for now)

  2. Go back to each of the Forms and link their Sheets to the “leader” Sheet

    • In the Form, click on the "Responses" tab.

    • Next to the green Sheets icon you used before, click on the three dots.

    • Click “Select destination for responses” and select the “leader” Sheet you just created

    • Do this for each of the Forms

The result will look something like this in your “leader” Sheet (visible at the bottom, with as many secondary “follower” Sheets next to the “leader” Sheet as you have Forms):

  1. Format the “follower” Sheets in an organized and consistent manner

    • In the Sheet, order the columns to reflect the order of the questions, if they aren’t in the appropriate order already

    • Bold their names if you like

Here is how mine looks:

Now you need to connect the Sheets’ contents. You need a formula that draws the Form responses from the “follower” Sheet(s) into the “leader” Sheet. In particular, you need a formula that can handle the fact that students will respond to the consent Form(s) in an unpredictable order. However, you know who your students are — what their names are and what their email addresses are — and you can use this knowledge with a formula to “look” for their names when they appear in the “follower” Sheet(s). Here’s how…

Subscribe to Premium to read the rest.

Become a paying subscriber of Premium to get access to this post and other subscriber-only content.

Already a paying subscriber? Sign In

A subscription gets you:
New Premium Pieces Every 2 Weeks
Access to AI Tutorials, like our Tutorial on Building (Better) Custom GPTs
Access to AI Pedagogy Guides, like our Guide on Designing Assignments in the AI Era
Access to Exclusive AI Tools
Discounts on Events