Project chunking involves breaking projects up into smaller deliverables and monitoring student progress throughout the project life-cycle.  

When chunking projects, consider the following:

1. Define the project: Describe the project’s objectives and explain what the final deliverable should look like. 
2. Break the project down into chunks: Divide the project into smaller, more manageable parts that can be completed in phases. Consider what skills and knowledge students will need to complete each part successfully.
3. Assign deadlines: Assign specific deadlines for each part of the project. This will help students stay on track and ensure that they are making steady progress towards the project’s completion.
4. Provide guidance and feedback: Monitor student work and provide appropriate supports as needed.
5. Incorporate reflection and revision: Encourage students to reflect on what they have learned and revise their work as they go. This will help them refine their understanding of the material and improve the quality of their final project.

The main premise of this model is that instructional delivery takes place outside the classroom allowing classroom time to be used for learning activities such as discussions, hands-on activities, group work, projects, monitored independent work, etc. 

When implementing the flipped classroom, keep in mind the following three key components:

1. Instructional delivery: Instruction in a flipped classroom is commonly delivered via video lectures created by the instructor, but it can also be delivered via readings, found videos, interactive tutorials, etc.
2. Instructional accountability: Because students are responsible for interacting with content outside the classroom, it is important that they are held accountable for reading and viewing assigned materials.  This can be done through online or in-person quizzes or other tasks that require students to interact with specific content.  Regardless of the task type, it should align closely with the instructional materials students are responsible for ingesting. 
3. In class activities: In class activities should build off of learning that takes place outside of class. By giving students opportunities to practice and demonstrate their learning during class, instructors are able to monitor student learning and provide feedback.

An oral assessment is an evaluation in which a student’s knowledge and skills are assessed through a verbal conversation. In an oral assessment, the student responds to questions, prompts, or scenarios presented by the instructor. Oral assessments do not necessarily need to be lengthy stand-alone events.  Adding an oral component to other assignment types can help ensure that students are able to stand behind the products they create by requiring them to demonstrate their knowledge in real time. For instance, facilitating a concise Q & A session following a presentation not only offers a chance to assess the knowledge beyond their pre-prepared materials, but also encourages a deeper understanding of the subject matter. 

A process-based assessment is an evaluation method where students are graded on their approach and methodology rather than just the final outcome. In this assessment style, the emphasis is on the journey students undertake, the strategies they employ, and the decisions they make along the way. Process-based assessments don't have to overshadow traditional grading methods. Incorporating them as a component of other assignments can ensure that students are genuinely engaging with the material and not just aiming for a polished end product. For instance, asking students to document and reflect on their interactions with generative AI tools can provide insights into their critical thinking abilities, fostering a deeper appreciation for the learning process itself.

There are a variety of tools that have been developed or updated to detect text written by ChatGPT and other AI tools. Because ChatGPT is so new and is constantly evolving, the effectiveness of these tools is not established. Most experts agree that there is no fail-proof method for reliably detecting AI-generated text. As AI is incorporated into standard writing tools, the line between human and AI-generated text will become increasingly indistinct. 

Although these tools are not guaranteed to accurately assess whether student submissions were written with AI, they can help determine whether a closer look is warranted. Indicating to students that detection tools will be used may also act as a deterrent for elicit use of generative AI. Please note that these tools have been found to report both false negatives and false positives.