- Use AI to enhance creativity, brainstorm ideas, and design lesson/unit plans.
- Integrate AI tools to support differentiated instruction and inclusion for diverse learners.
- Apply ethical and responsible practices when using AI in lesson planning.
- Create effective prompts for accurate, relevant, and curriculum-aligned content.
- Evaluate and adapt AI-generated materials for accuracy, bias, and alignment with learning goals.
- Confidently integrate digital tools into the teaching workflow.
Category: EDCI-335 (Page 2 of 3)
We chose ChatGPT, Diffit, and Gemini for their accessibility, adaptability, and ability to support teachers with different levels of tech skills. ChatGPT offers quick, customizable lesson ideas; Diffit adjusts reading materials to meet diverse learning needs; and Gemini provides a comparative AI experience to develop evaluation skills. These tools align with our constructivist approach by promoting experimentation, critical thinking, and differentiated instruction, while remaining free or low-cost so teachers can continue using them beyond the course.
Learning Context: HOW TO AI COURSE
Accessibility & Inclusive Design. This course is built to be inclusive and easy to use. It is important to recognize that teachers come with a wide range of technology skills and comfort. Following the principles of Universal Design for Learning (UDL), which encourages proactive planning to reduce barriers for all learners (CAST, 2018).
- Training videos can include closed captions (CC).
- Teachers can create lesson plans using technology or by writing on a hand-made template.
- Videos can be slowed down or sped up as needed.
- Navigation is simple and text is clearly labeled.
The learning design we chose is experiential. Experiential learning engages learners âintellectually, emotionally, socially, soulfully and/or physically and creates a learning task that is authentic.â (Association for Experiential Education, n.d.). The AEE further explains that experiential learning is personal and forms the basis for future experience and learning.
This is reflected in our learning resource because our activities are an active process of exploration and application. Rather than being shown or told about how generative AI can be used to lesson plan, our tool provides an opportunity for teachers to be guided through a series of interactive activities that require them to experiment with AI prompts in a relevant context. For example, activity 2 involves prompting AI with a series of questions, each time becoming more specific, and then comparing results to one another.
Our design templates also involve direct instruction as some of them provide teachers with exact formulas for prompting AI. According to Main (2021) direct instruction âemphasizes explicit teaching, carefully sequenced lessons, and small learning incrementsâ because clear instruction reduces the chance of misinterpretation. In our resource, this approach is reflected in the use of pre-laid-out templates that guide teachers step by step. Activity 1 for example, involves little inquiry or open-ended exploration, as they are designed to build foundational understanding and ensure clarity before teachers move on to more creative, exploratory tasks.
Our rationale for a combination of these approaches is to build teacher confidence while encouraging creativity. The use of direct instruction provides a clear framework proven to be successful when lesson planning. This structure reduces confusion and is a strong starting point, especially for those new to AI. Once this foundational understanding is set, experiential learning allows teachers to experiment with what they learned, deepening their understanding of genAI.
Our interactive learning resource is based on constructivist learning theory, which suggests that learners build knowledge through active participation, reflection, and linking new ideas to previous experiences (Piaget, 1973; Vygotsky, 1978). In this resource, teachers actively explore AI tools, assess AI-generated lesson plans, and modify them to align with curriculum objectives and student needs.
Constructivism aligns with our topic because effective AI use in education requires critical thinking, problem-solving, and personalization rather than rote memorization. Teachers learn by experimenting with prompts, comparing outputs, and refining lessons, reflecting real classroom practice where design is iterative and guided by student needs.
We incorporate social constructivist principles through peer discussions, sharing of lesson plans, and reflection activities, enabling participants to learn from each other’s strategies and feedback. By framing AI as a tool that supports teacher creativity, we empower educators to actively create knowledge and integrate AI into their practice thoughtfully, ethically, and effectively.
This professional development opportunity is designed for teachers who want to learn how to use AI (Artificial Intelligence) to support their lesson planning. With AI becoming more user friendly and available, many teachers are curious but unsure. This course aims to help a teacher who is new with AI to try out an online support tool to try and test their skills around using AI to generate lesson plans. It is suitable for educators across all levels of experience, whether you are new to teaching, have been in the classroom for 25 years, or are working as a teacher on call. This resource is designed to be used to meet a variety of needs.
It is especially useful for those who are new to genAI and may feel hesitant about using it in the classroom, curious of its potential, or need guidance with getting started. Although prior experience with AI could be beneficial, no prior experience with AI is necessary as our learning resource serves as a straightforward guide to using genAI when lesson planning, making the process more efficient. Our learning resource is ideal for new teachers who may feel overwhelmed with the amount of lesson planning required in the first couple years of teaching, as well as for experienced teachers looking for fresh ideas and innovative ways to engage their students.
It is designed to give teachers the skills and confidence to move beyond our templates and create their own AI prompts based on their individual teaching situations and needs.
This course aims to support elementary school teachers in learning simple strategies for using generative artificial intelligence (AI) in lesson planning. In education, AI involves using algorithms to assist or automate parts of teaching and learning, such as generating lesson ideas, personalizing content, and providing adaptive learning supports (Holmes et al., 2022). When used carefully, AI can help teachers in planning, addressing diverse learning needs, and enhancing creativity without replacing professional judgment (Kasepalu et al., 2022). This learning resource provides step-by-step guidance, examples, and templates for using accessible AI tools, like ChatGPT, Diffit, and Gemini, to design engaging, inclusive, and curriculum-aligned lessons.
Audience: Kâ7 teachers Total time: 60â90 min Tools: ChatGPT, Diffit, Gemini
Course Map
- Overview (5 min)
- Learning Context & Learners (5â10 min)
- Learning Theory (Constructivism) (5â10 min)
- Learning Design (Experiential + Direct Instruction) (5â10 min)
- Accessibility & UDL (5 min)
- Rationale for Selected AI Tools (5 min)
- Learning Outcomes (2 min)
- Course Outline
- Resources & Prep (5 min)
- Interactive Activities
- Activity 1A & 1B Get Comfortable with AI (10 min)
- Activity 2: The Power of Specificity (10 min)
- Activity 3: Inclusive Student Profiles (No PII) (10 min)
- Activity 4: Plan with Profiles (10â15 min)
- Activity 5: Compare Prompt Templates (10â15 min)
- Assessment Plan & Rubric (5 min)
- References (browse)
Downloads & Templates
Assessment
- Formative Check-in (H5P/Google Form)
- Summative: Publish AI-supported Lesson
- Rubric
- Peer Feedback Protocol (TAG)
Ethics & Safety: Donât paste any personal/identifiable student data into AI tools. Use profiles/pseudonyms, verify outputs, check bias, and align to school/district privacy policies.
Progress Checklist
- Overview read
- Watched PB&J âExact Instructionsâ video
- Completed Activities 1â5
- Submitted formative check-in
- Posted summative lesson + rubric
Why Assessment Matters
When I began my journey in the B.Ed program at UVic, I honestly didnât think much about the purpose of assessment. Like many students, I saw grades as simply a way to measure how well I âdidâ on an assignment. However, through my coursework, practicums, and conversations with instructors, Iâve come to realize that assessment is much more than just a letter on a transcript, itâs about fostering learning in a thoughtful, purposeful, and meaningful manner.
At UVic, every syllabus includes clear grading standards for a good reason. Academic rigor involves ensuring our work meets established expectations, and this canât happen without precise alignment between learning outcomes and the activities we engage in.
I realized how often Iâd previously completed assignments without thinking about the purpose behind them. Now, I try to ask myself, âWhat outcome am I showing evidence for?â This shift in mindset has helped me take more ownership of my learning.
My Experience with Formative and Summative Assessment
One of the most powerful things Iâve experienced in university is formative assessment. Whether itâs feedback on a blog post, a peer review, or a chance to revise a lesson plan draft, these moments have been where real learning has taken place.
I remember a moment during our EDCI course when I received feedback on a digital resource I had designed. At first, I felt frustrated because I thought I had done well, but when I stepped back, I realised the suggestions were helping me refine and sharpen my work. I made the revisions, and the final product was much stronger.
Summative assessment still plays a role; of course, itâs essential to see where we land after a unit or project. But Iâve come to appreciate that the final grade isnât the whole story.
The Role of Self-Assessment in My Learning
This year, I was asked to self-assess one of my teaching units using a competency-based rubric. At first, it felt awkward to evaluate myself; shouldnât that be the instructorâs job? But as I reflected on my goals, strengths, and challenges, I began to see how valuable this process was.I ended up recognizing pieces of work I felt proud of, not necessarily because they were perfect, but because they demonstrated growth. I also noticed patterns in where I struggled (for me, time management in group settings) and was able to discuss these openly in a follow-up meeting with my instructor. The experience reminded me that assessment isnât something that happens to us. When done properly, itâs something we are actively part of.
Designing for Learning
As a future educator, I am increasingly considering how I will design assessments in my classroom. I donât want students to fear feedback or view grades as the final goal. I want them to feel supported, guided, and empowered to reflect on their learning along the way.
Assessment isnât just a checkbox on a rubric. Itâs a tool for growth for both learners and instructors. Itâs feedback, reflection, and iteration. When done thoughtfully and transparently, assessment builds trust, deepens understanding, and helps learners see how far theyâve come.
As I continue in my B.Ed. program and enter the classroom, I carry these lessons with me. I want my students to understand that learning can be messy, that feedback is a valuable gift, and that they have the power to show what they know.
BLOG POST #2
Cooperative Learning
Cooperative learning is a structured method of group work where students rely on one another to achieve shared academic goals. It highlights intentional interaction that promotes positive interdependence, mutual support, and genuine collaboration, rather than merely parallel work on the same task (Herrmann, 2013; Davidson & Major, 2014). Each student contributes individually while being accountable to the group, encouraging both academic achievement and the development of social skills through face-to-face interaction and group reflection (Gillies, 2016).
The one that is doing the learning is doing the talking.
CAndy Olandt
Example of Cooperative Learning
Jigsaw Learning: Students are divided into groups, assigned a topic, and learn and teach each other, like the jigsaw activity we did in class with the approaches to learning. It’s also cool how we used Zoom to complete this.
Think-Pair-Share: Students first think about questions individually, then share their thoughts with a partner, and finally, share with the whole class.
Structured heterogeneous grouping: Students are intentionally placed in diverse groups based on their abilities, personalities, and learning styles. Each student has a role, ensuring balanced participation and peer learning.
The Limits of AI in Cooperative Learning
While AI can support learning, it doesn’t always align well with cooperative learning. Cooperative learning relies on peer interaction, shared responsibility, and face-to-face collaboration. Many AI tools are designed for individual use, which can reduce meaningful group dialogue and lead to uneven participation. When students rely on AI for quick answers instead of discussing and solving problems together, it limits critical thinking and weakens social skill development. Without careful guidance, AI use can unintentionally replace rather than support the human connections that make cooperative learning effective.
In the video, “The Pros and Cons of AI in Education: What Every Educator Should Know,” educators emphasise that while AI tools are very effective for personalising learning, they can sometimes hinder collaborative learning. By promoting isolated engagement, AI might reduce meaningful student dialogue and restrict the development of critical thinking and interpersonal skills.
These concerns are growing that when students rely too heavily on automated responses, they miss out on opportunities for peer discussion and shared problem-solving, core components of cooperative learning.
Challenges and Risks of Using AI in the Classroom
- Privacy concerns around student data
- Ethical considerations, including fairness and transparency
- Reduced social adaptability due to less face-to-face interaction
- Overdependence on technology which can weaken problem-solving skills
Educators play a vital role in ensuring that AI is used fairly, transparently, and with student autonomy and dignity in mind. As Gillies (2016) reminds us, cooperative learning thrives on structured, real-world interaction, something AI alone cannot replicate.
Shalan’s Blog Post #2 Reflection
When discussing cooperative learning, I agree that it creates space for students to feel more open and comfortable sharing, especially when the class is divided into smaller groups. It also encourages full participation, and group roles tend to form naturally.
Having a peer who is confident with the topic can be helpful, but I also see it as an opportunity for the group to discover the answer together as a team.
I agree that the best approach depends on the learners, as everyone learns in a unique way. My ongoing challenge has been figuring out how to accommodate all learning styles, but I really like the idea of blending strategies to meet a variety of needs.
For our topic, do you think AI tools in education can support or hinder cooperative learning? In what ways might they enhance collaboration or unintentionally replace it?