Ā¶ Use Case (Instructional)
| Author(s): | Caleigh Heenan |
|---|---|
| Role / Position: | Dean of Students |
| School(s): | National Park Elementary School (Gateway Group) |
| Contact Info: | [email protected] (856) 845-6876 ext. 116 |
Abstract
AI can improve student behavior in the classroom by generating personalized behavior trackers tailored to each studentās needs, goals, and patterns. These trackers can provide real-time feedback, identify behavior trends, and suggest targeted interventions based on data analysis. When shared regularly with parents, they foster consistent communication and reinforce expectations at home.
AI Integration
- AI Tool(s) Used: ChatGPT
- Intended Outcome of AI Use: AI is helpful for improving student behaviors because it can efficiently analyze large amounts of data to detect patterns, predict challenges, and recommend timely, individualized supports.
- AI Literacy or Skill Developed:
- AI helps develop personalized behavior plans by analyzing data from various sourcesāsuch as classroom management systems, behavior logs, attendance, and academic performanceāto identify trends and patterns in student behavior. It can detect early warning signs, such as increased off-task behavior or sudden changes in participation, and recommend targeted strategies to address them. By automating data collection and analysis, AI makes the process more efficient, accurate, and responsive to each student's unique behavioral needs.
- Standards Addressed:
- ISTE Coach Standard 3: Collaborator
- 3d: Personalize support for educators by planning and modeling the effective use of technology to improve student learning.
- ISTE Coach Standard 4: Learning Designer
- 4a: Collaborate with educators to develop authentic, active learning experiences that foster student agency and self-directed learning.
- ISTE Education Leader Standard 1: Equity and Citizenship Advocate
- 1b: Ensure all students have skilled teachers who actively use technology to meet student learning needs.
- ISTE Coach Standard 3: Collaborator
Implementation Details:
- Team:
- Grade-Level Team (3rd Grade teachers)
- I&RS Team (Administration, BSI teachers, Special Area and Special Education Teachers, Classroom Teachers/Case Managers)
- Frequency: Monthly (Team Meetings), On-Going As Needed (Specific Student Needs)
- How AI Was Used:
- Teachers brought a specific student issued to light at monthly grade-level meetings. One student was having difficulty focusing and paying attention to key information in lessons, and the gaps in their achievement were growing. While the teachers had several conversations with the studentās family about the issues with attention, they felt as though the parents werenāt understanding the severity of the students issue.
- The teachers created an I&RS referral for the student, and the team discussed the concerns at their next meeting.
- It was determined that there was a need for data collection in the following areas:
- The frequency of on-task behavior during lessons.
- The frequency of requested breaks by the student.
- The frequency of requested āescapeā behaviors; specifically- visits to the bathroom and nurse.
- Through discussion, it was determined that the best way to do this would be for the teachers to check-in on the student in 15 minute increments and note whether the student was on or off task. There also needed to be a space for teachers to note when the student requested breaks, to go to the bathroom, or to go to the nurse.
- Due to the age of the student and the need for objective data, it was decided that the student would not participate in the data collection or know that data was being collected. However, the data would be analyzed and presented to the parents at the next meeting so they could have a better picture of their childās performance.
- It was decided that data analysis would also help to show trends in behavior, such as time of day, subject, day of the week, etc.
- ChatGPT was used to generate data tracking sheets for the 3rd Grade Teachers.
- Prompt: Create a data collection sheet for a student. The top should have a space to record a date. The data collection sections should be broken into three sections: ELA, Math, and Other. In each section, show time in 15 minute increments (9:00, 9:15, etc). Under ELA, the times should start at 9:00 and end at 12:15. Under Math, the times should start at 12:45 and end at 2:30. Under Other, there should be sections for Nurse, Bathroom, Other Requested, and Guidance Counselor/Social Worker. Add a checkbox next to each time slot. In the other category, remove time/in and time out and add a box to record tally marks.
- The teachers utilized the tracking sheet to collect data for three weeks.
- ChatGPT was used to generate a Google Sheet to enter the data collected.
- Prompt: Create a Google Sheet to collect student data. There should be two sections: one for ELA and one for Math. Each section should have a column for the date/day of the week, a column for on-task, a column for off-task, and a percentage On-Task. Add a third section to the bottom called "Additional Data Points" with rows for trips to the nurse, trips to Social Worker, bathroom, and other breaks. Add a column to the far right for "Daily On-Task".
- ChatGPT was used to generate the formulas for the sheet to make it auto-calculate (given from prompt)
- Date was entered, a screenshot of the data was entered, and ChatGPT was used to analyze the trends.
- Prompt**
* Analyze this data set for trends and patterns.
- Prompt**
- Results were communicated to the parents at our next meeting to help them get a better understanding of daily performance. It allowed the I&RS team to create SMART goals for intervention, as well as provide the parents with insights they could use to speak with their childās healthcare provider.
- Evidence of Outcomes
- This process allowed us to have quantitative data to use to drive our discussions and assist us in the creation of SMART goals for the student.
- Changes to Workflow, Instruction, or Student Outcomes:
- This use case helped us develop a more targeted plan to support students struggling with attention and focus in the classroom. It prompted us to reflect on both the supports we provide for students and our instructional strategies. Additionally, it strengthened our communication with families. The artifacts we created during this process have since been used to support other students across multiple grade levels in our school.
Lessons Learned:
- What went well?:
- Teachers monitored progress well across the assigned days.
- Anonymity of the student was maintained.
- All stakeholders were able to get a clearer understanding of the studentās daily performance.
- Challenges Encountered:
- Unexpected scheduling changes (assemblies, drills, etc.)
- The student being absent or leaving early during data collection days.
- Assessments or Basic Skills lessons (pulling out of student during periods
- Recommendations for others replicating this use case:
- Utilize a longer data collection window to get a clearer picture (minimum one month).
- Hold a brief kick-off meeting or send a summary of instructions via email at the start, middle, and end of the data collection window.
- Use ChatGPT to generate a handout of the information to provide to parents ahead of the parent meeting. This will facilitate the discussion and provide them with key information to share with their childās healthcare provider.
Supporting Materials: