Enterprise AI Analysis
PracticeDAPR: An AI-based Education-Supported System for Art Therapy
This paper introduces PracticeDAPR, an AI-based education-supported system designed for beginners in DAPR assessment practice in art therapy. Recognizing professional identity development as a core educational goal, the system aims to enhance performance, reduce anxiety, and improve self-efficacy among beginners. It achieves this through online peer-to-peer learning augmented by an AI mentor. The system provides diverse cases for practice, including sketch replays and post-survey results, enabling users to perform quantitative (DAPR score) and qualitative (question formulation) assessments. Users can compare their results with peers and AI, fostering a collaborative learning environment. A user study with graduate art therapy students demonstrated positive experiences, significant improvements in perceived usefulness, and a strong intention to use, suggesting its effectiveness in supporting professional identity formation.
Executive Impact
Art therapy education faces challenges in developing professional identity among beginners, often leading to difficulties in assessment skills, anxiety, and low self-efficacy. This paper proposes PracticeDAPR, an AI-based system that integrates online peer-to-peer learning with an AI mentor to address these issues. By providing diverse practice cases and interactive feedback mechanisms, PracticeDAPR aims to significantly improve beginners' performance, reduce anxiety, and enhance self-efficacy. Quantitative and qualitative studies confirm its positive impact, highlighting its potential as a supplementary tool in art therapy training to foster robust professional identity.
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DAPR Assessment Accuracy Increase
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Time Efficiency Gain per Assessment
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Users Reporting Performance Improvement
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Users Intending to Continue Use
Deep Analysis & Enterprise Applications
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AI as a Mentor
The AI mentor provides quantitative DAPR score evaluations through object detection and scoring models, offering objective benchmarks. It generates comparative question tables, highlighting expert-like inquiries, and provides feedback on user-generated questions to boost self-efficacy and guide learning. AI comments also encourage peer interaction and help validate/rectify AI errors in discussions.
Online Peer-to-Peer Learning
The platform fosters a collaborative environment where users compare their assessments with peers, access DAPR score distributions (including expert scores), and engage in discussion forums. This interaction facilitates knowledge sharing, reduces anxiety by normalizing experiences, and enhances self-efficacy through peer feedback and support, especially in qualitative assessment.
Professional Identity Support
PracticeDAPR directly addresses three key factors for professional identity formation: performance improvement (through repeated practice and AI/peer feedback), anxiety reduction (by exposure to diverse cases and peer support), and self-efficacy enhancement (via positive feedback and comparison with experts/AI). The system's usefulness is a significant predictor for these factors, and performance improvement strongly drives intention to use.
Enterprise Process Flow
Select Sketch (To-do)
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Practice DAPR Assessment (Manual Score & Questions)
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Review AI Results (AI Score & Feedback)
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Engage with Community (Peer & Expert Insights)
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Track Progress (Done Page)
86%
Post-training DAPR Score Correlation with Experts
After using PracticeDAPR, participants' DAPR score evaluations showed a significantly higher correlation (0.86) with expert assessments, up from 0.78 pre-training. This indicates a marked improvement in assessment accuracy for beginners.
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| Anxiety & Self-Efficacy |
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User Experience Spotlight: Building Confidence with AI & Peers
"I am usually nervous about whether my questions are adequate or not, as I am not familiar with the DAPR assessment. However, I felt confident when I discovered similar questions in the table (AI-based comparative question table)."
– Participant L
Participant L's experience highlights how PracticeDAPR directly addresses beginner anxiety and boosts self-efficacy. The AI-based comparative question table provides a crucial benchmark, allowing users to validate their qualitative assessment skills against expert-like examples. This immediate, reassuring feedback, combined with peer comparison, builds confidence—a key component of professional identity.
121.65s
Average Time per DAPR Assessment (Post-Training)
The average time taken by participants to complete a DAPR assessment significantly decreased from 199.29 seconds in the pre-test to 121.65 seconds post-training, demonstrating a substantial improvement in assessment efficiency.
Calculate Your Potential ROI
Estimate the impact PracticeDAPR could have on your organization's training efficiency and professional development.
Estimated Annual Savings
$0
Hours Reclaimed Annually
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Implementation Roadmap
A typical timeline for integrating PracticeDAPR into your art therapy education program.
Phase 1: Pilot & Customization (1-2 Months)
Initial deployment of PracticeDAPR with a pilot group of beginners. Customize DAPR case sets, integrate with existing LMS, and gather feedback for initial refinements.
Phase 2: Full Integration & Training (2-3 Months)
Roll out to all beginner art therapy students. Conduct comprehensive training for educators and supervisors on leveraging AI mentor insights and facilitating peer interaction.
Phase 3: Ongoing Optimization & Expansion (3-6 Months)
Continuous monitoring of performance metrics and user engagement. Expand case libraries, enhance AI models with new data, and explore integration with other assessment types.
Ready to Transform Art Therapy Education?
Empower your beginners with AI-supported, peer-driven practice to build strong professional identities and assessment skills.
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