Behaviour Analysis: AI & I – Part 1

Curriculum Integration Statement / Values Statement

Value Statement: Creating learning environments where every student, regardless of background, ability, or prior experience, has equitable access to knowledge, support, and opportunities for success. Alignment with GenAI: Integrating AI helps dismantle barriers by giving students individualized explanations, study aids, and alternative ways to engage with content. In terms of impact to the student, the hope is to provide more inclusive support, increased confidence, and reduced stigma around help-seeking.

Value Statement: Teaching students to engage with emerging technologies, especially GenAI, ethically, critically, and responsibly, ensuring they develop the judgment needed for academic and professional integrity. Alignment with GenAI: AI is a tool that must be understood, not blindly used. Embedding discussions of data ethics, bias, transparency, and authorship is a must.

Value Statement: Fostering a culture of curiosity, continuous learning, and innovation and adapting to a rapidly changing world. Alignment with GenAI: GenAI encourages exploration, experimentation, and problem-solving. Integrating AI into teaching models supports iterative learning, rapid prototyping, data analysis, and creativity.

Setting the Context/Curriculum Integration Goals

PSY355 is a required course for the General Arts Program (GAP) and a general education course elective in the sciences and social sciences.

Assessment Details

Title: AI & I – Behaviour Analysis (Part 1 of 2)

Note: This activity/assignment/kernel can be paired with another kernel “AI & I: Behaviour Analysis Part 2.” This kernel introduces AI capabilities, limitations, and uses in a more basic sense, whereas “AI & I: Behaviour Analysis Part 2” focuses on more intermediate AI skills and applications. If an instructor decides to use both kernels, it is recommended to start with “AI & I – Behaviour Analysis Part 1” as the foundational kernel, then assign “AI & I: Behaviour Analysis Part 2” to build upon these skills.

Deliverables/Objectives:

• Students will record a journal entry of a personal, heightened emotional response that they have recently experienced (one that they are comfortable with recording); to write down as many thoughts, feelings, and facts as possible in their entry.
• Students will diagnosis their journal entry by determining traits, emotions, and behaviours that were experienced at the time, according to material provided within the course.
• Students will submit their journal entry into an AI tool and utilize their prompt engineering skills to generate an AI generated behavioural analysis.
• Students will write a comparative analysis report that critically examines both their human behaviour analysis and the AI generated one.
• Students will also write a reflection that discusses the AI responses and the ethical implications of using AI to analyze human behaviour.

Learning Objectives:

• Students will identify and document their own emotional responses and associated behavioural traits using reflective journaling.
• Students will apply prompt engineering techniques to analyze emotional responses using AI platforms such as Copilot and Goblin Tools.
• Students will compare AI-generated emotional analyses with their own interpretations, evaluating the strengths and limitations of AI in understanding human emotions.
• Students will develop AI literacy and critical thinking skills by assessing the usefulness and accuracy of AI outputs in behavioural analysis.
• Students will reflect on the importance of human emotional intelligence and the interplay between human skills and AI analysis in behavioural science.

Materials Required:

• Paper or digital journaling tools for students to record personal emotional experiences.
• Access to AI platforms such as Microsoft Copilot and Goblin Tools (The Judge) for emotional analysis.
• Course materials on emotional traits, diagnoses, and behavioural analysis frameworks.

Part 1: Personal Emotional Reflection and Journaling

Students are expected to recall and select a recent personal experience where they experienced a heightened emotional response. Students will write a detailed journal entry, capturing their thoughts, feelings, physical reactions, and contextual facts about the event, preferably using a pen and paper to encourage mindfulness. Students should ensure they write their journal entry in a way that does not identify them personally; this is to ensure privacy and emotional safety.

Part 2: Personal Behavioural Analysis

Students will use their journal entry and reference course materials to self-identify emotional traits and possible behavioural diagnoses present during the experience, using definitions such as 'emotional triggers' and 'coping mechanisms.'

Part 3: AI Behavioural Analysis

Students will input their journal entries into Microsoft Copilot and/or, if available, Goblin Tools (The Judge), experimenting with different prompt structures to optimize AI output. Students are expected to use their AI literacy and prompt engineering skills to craft effective prompts to elicit meaningful emotional analysis from AI platforms. Students will document the AI-generated emotional and behavioural assessments, noting key terms, diagnoses, and any patterns in the AI's analysis.

Part 4: Comparative Analysis: Human vs. AI

Students will systematically compare their self-identified emotional traits and diagnoses with those generated by the AI platforms. Students will identify and discuss areas of agreement and divergence between human and AI interpretations, considering possible reasons for discrepancies such as lack of nuance or contextual understanding in AI.

Part 5: Reflection

Students will write a brief reflective essay, summarizing what they learned about the intersection of AI and human emotional intelligence. Students will reflect on AI's capacity for emotional intelligence. Students are encouraged to answer questions like 'Can AI understand empathy?' and 'What are AI’s limitations in behavioural analysis?'. Students will be encouraged to set personal goals for further developing both their human and AI literacy skills in future behavioural analysis work.

Summary

Students record and assess a heightened emotional response they have recently experienced and compare their own analytic interpretation of the experience with AI’s interpretation.