AJSM OPEN ACCESS

Academic Journal of Sociology and Management

ISSN:3005-5040 (print) | ISSN:3005-5059 (online) | Publication Frequency: Bimonthly

OPEN ACCESS|Research Article||15 May 2025

Design of Persona-Based Interactive Interfaces and Their Impact on Human Self-Perception

* Corresponding Author1: Xinzhu Li, E-Mail: xinzhuli642@gmail.com

Publication

Accepted 2025 May 12 ; Published 2025 May 15

Academic Journal of Sociology and Management, 2025, 3(3), 3005-5040.

Abstract

Grounded in the frameworks of affective computing and large-language-model technology, this paper systematically sorts out the conceptual evolution and core techniques of persona-based interactive interfaces (PBIIs) and, by means of a randomized controlled experiment, verifies their comprehensive effect on users’ self-perception. The study first constructs a four-level closed-loop architecture of “Perception – Understanding – Generation – Feedback.” Sixty university students are then recruited for a 14-day intervention; pre- and post-tests using a Self-Efficacy Scale and an Emotion-Awareness Test are compared. Results show a significant rise in self-efficacy for the experimental group (ΔM = +0.70, p < 0.01) and a 12 % increase in emotion-recognition accuracy, validating the synergistic mechanism of affective mirroring and verbal persuasion. Qualitative interviews further reveal potential risks such as emotional dependence and cognitive dissonance. In view of these findings, this paper proposes PBII design principles centred on uncertainty management and user-agency cues, offering theoretical and practical reference for responsible application in education and mental-health fields.

Keywords

Persona-based Interactive Interface , Self-perception , Artificial Intelligence , User Experience , Affective Computing , Human–computer Interaction .

Metadata

Pages: 30-35

References: 22

Disciplines: Psychology

Subjects: Cognitive Psychology

Cite This Article

APA Style

Li, X. (2025). Design of persona-based interactive interfaces and their impact on human self-perception. Academic Journal of Sociology and Management, 3(3), 30-35. https://doi.org/10.70393/616a736d.323936

Acknowledgments

The authors thank the editor and anonymous reviewers for their helpful comments and valuable suggestions.

FUNDING

Not applicable.

INSTITUTIONAL REVIEW BOARD STATEMENT

Not applicable.

DATA AVAILABILITY STATEMENT

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

INFORMED CONSENT STATEMENT

Not applicable.

CONFLICT OF INTEREST

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

AUTHOR CONTRIBUTIONS

Not applicable.

References

1.
Zhou, Y., Zhang, J., Chen, G., Shen, J., & Cheng, Y. (2024). Less is more: Vision representation compression for efficient video generation with large language models.

2.
Lin, W. (2024). A Systematic Review of Computer Vision-Based Virtual Conference Assistants and Gesture Recognition. Journal of Computer Technology and Applied Mathematics, 1(4), 28–35.

3.
Zhang, T. (2025). Combining Blockchain and AI to Optimize the Intelligent Risk Control Mechanism in Decentralized Finance. Journal of Industrial Engineering and Applied Science, 3(2), 26–32.

4.
Wu, S., Fu, L., Chang, R., Wei, Y., Zhang, Y., Wang, Z., ... & Li, K. (2025). Warehouse Robot Task Scheduling Based on Reinforcement Learning to Maximize Operational Efficiency. Authorea Preprints.

5.
Lyu, S. (2024). The Application of Generative AI in Virtual Reality and Augmented Reality. Journal of Industrial Engineering and Applied Science, 2(6), 1–9.

6.
Zhou, Z. (2025). Research on the Application of Intelligent Robots and Software in Multiple Segmentation Scenarios Based on Machine Learning. Available at SSRN 5236930.

7.
Zhou, Y., Shen, J., & Cheng, Y. (2025). Weak to strong generalization for large language models with multi-capabilities. In The Thirteenth International Conference on Learning Representations.

8.
Sun, J., Zhang, S., Lian, J., Fu, L., Zhou, Z., Fan, Y., & Xu, K. (2024, December). Research on Deep Learning of Convolutional Neural Network for Action Recognition of Intelligent Terminals in the Big Data Environment and its Intelligent Software Application. In 2024 IEEE 7th International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) (pp. 996–1004). IEEE.

9.
Ke, Z., & Yin, Y. (2024, November). Tail risk alert based on conditional autoregressive var by regression quantiles and machine learning algorithms. In 2024 5th International Conference on Artificial Intelligence and Computer Engineering (ICAICE) (pp. 527–532). IEEE.

10.
Wang, B. (2025). Big Data-Driven ESG Quantitative Investment Strategy. Journal of Economic Theory and Business Management, 2(2), 8–13.

11.
Zuo, Q., Tao, D., Qi, T., Xie, J., Zhou, Z., Tian, Z., & Mingyu, Y. (2025). Industrial Internet Robot Collaboration System and Edge Computing Optimization. arXiv preprint arXiv:2504.02492.

12.
Lyu, S. (2024). Machine Vision-Based Automatic Detection for Electromechanical Equipment. Journal of Computer Technology and Applied Mathematics, 1(4), 12–20.

13.
Mao, Y., Tao, D., Zhang, S., Qi, T., & Li, K. (2025). Research and Design on Intelligent Recognition of Unordered Targets for Robots Based on Reinforcement Learning. arXiv preprint arXiv:2503.07340.

14.
Wang, J., Zhang, Z., He, Y., Song, Y., Shi, T., Li, Y., ... & He, L. (2024). Enhancing Code LLMs with Reinforcement Learning in Code Generation. arXiv preprint arXiv:2412.20367.

15.
Lyu, S. (2024). The Technology of Face Synthesis and Editing Based on Generative Models. Journal of Computer Technology and Applied Mathematics, 1(4), 21–27.

16.
Yi, Q., He, Y., Wang, J., Song, X., Qian, S., Zhang, M., ... & Shi, T. (2025). SCORE: Story Coherence and Retrieval Enhancement for AI Narratives. arXiv preprint arXiv:2503.23512.

17.
Yu, Q., Yin, Y., Zhou, S., Mu, H., & Hu, Z. (2025). Detecting Financial Fraud in Listed Companies via a CNN-Transformer Framework.

18.
Yu, X. (2022). Research on elder-friendly design of entertainment smart-home product interfaces [Master’s thesis, East China Normal University]. (Supervisor: Liu Fei).

19.
Qiu, S., Wang, Y., Ke, Z., Shen, Q., Li, Z., Zhang, R., & Ouyang, K. (2025). A Generative Adversarial Network-Based Investor Sentiment Indicator: Superior Predictability for the Stock Market. Mathematics, 13(9), 1476.

20.
Ke, Z., Zhou, S., Zhou, Y., Chang, C. H., & Zhang, R. (2025). Detection of AI deepfake and fraud in online payments using GAN-based models. arXiv preprint arXiv:2501.07033.

21.
Lin, W. (2024). A Review of Multimodal Interaction Technologies in Virtual Meetings. Journal of Computer Technology and Applied Mathematics, 1(4), 60–68.

22.
Zhao, P., Fan, R., Wang, S., Shen, L., Zhang, Q., Ke, Z., & Zheng, T. (2024). Contextual Bandits for Unbounded Context Distributions. arXiv preprint arXiv:2408.09655.

PUBLISHER'S NOTE

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cc Copyright © 2025 The Author(s). Published by Southern United Academy of Sciences.
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