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Objective <p>This study compared the efficacy of Popular Science (PS) and Research-Based (RS) curriculum extensions in a Histology and Embryology course, and explored how artificial intelligence (AI) tools can be designed as differentiated cognitive partners to support distinct pedagogical goals.</p> Methods <p>Two parallel first-year clinical medicine classes (<i>N</i> = 118) were non-randomly assigned to PS (<i>n</i> = 60) and RS (<i>n</i> = 58) arms. The PS group completed narrative, clinically connected tasks supported by the Intelligent Quiz Platform (IQP). The RS group undertook inquiry-driven literature analysis supported by the Literature Analysis Assistant (LAA). Outcomes included examination scores, validated questionnaire ratings, AI usage logs, and semi-structured interview themes.</p> Results <p>The RS group was associated with higher comprehensive application (16.8 ± 2.6 vs. 14.2 ± 2.9, <i>p</i> &lt; 0.01) and innovative thinking scores (9.0 ± 1.6 vs. 7.6 ± 1.8, <i>p</i> &lt; 0.01). The PS group reported significantly higher learning interest and satisfaction (<i>p</i> &lt; 0.01). The PS group used IQP more frequently (8.5 ± 2.1 vs. 5.2 ± 1.8, <i>p</i> &lt; 0.001), while the RS group engaged more deeply with LAA (4.8 ± 1.5 vs. 1.2 ± 0.9, <i>p</i> &lt; 0.001). IQP use correlated with basic knowledge (<i>r</i> = 0.42, <i>p</i> &lt; 0.01); LAA use correlated with comprehensive application (<i>r</i> = 0.51, <i>p</i> &lt; 0.001) and innovative thinking (<i>r</i> = 0.46, <i>p</i> &lt; 0.01). Interviews confirmed AI acted as a “tutor” for PS and a “research assistant” for RS.</p> Conclusion <p>PS and RS extensions are associated with complementary competencies. A tiered, AI-differentiated model may support personalized learning to cultivate clinically engaged communicators and critically thinking physician-scientists.</p>

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AI as a differentiated cognitive partner in medical education: a comparative study of popular science versus research-based curriculum extensions in histology and embryology

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月9日

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  • Dejian Chen,
  • Lin Ma,
  • Shengbing Liu,
  • Yaling Zhang

摘要

Objective

This study compared the efficacy of Popular Science (PS) and Research-Based (RS) curriculum extensions in a Histology and Embryology course, and explored how artificial intelligence (AI) tools can be designed as differentiated cognitive partners to support distinct pedagogical goals.

Methods

Two parallel first-year clinical medicine classes (N = 118) were non-randomly assigned to PS (n = 60) and RS (n = 58) arms. The PS group completed narrative, clinically connected tasks supported by the Intelligent Quiz Platform (IQP). The RS group undertook inquiry-driven literature analysis supported by the Literature Analysis Assistant (LAA). Outcomes included examination scores, validated questionnaire ratings, AI usage logs, and semi-structured interview themes.

Results

The RS group was associated with higher comprehensive application (16.8 ± 2.6 vs. 14.2 ± 2.9, p < 0.01) and innovative thinking scores (9.0 ± 1.6 vs. 7.6 ± 1.8, p < 0.01). The PS group reported significantly higher learning interest and satisfaction (p < 0.01). The PS group used IQP more frequently (8.5 ± 2.1 vs. 5.2 ± 1.8, p < 0.001), while the RS group engaged more deeply with LAA (4.8 ± 1.5 vs. 1.2 ± 0.9, p < 0.001). IQP use correlated with basic knowledge (r = 0.42, p < 0.01); LAA use correlated with comprehensive application (r = 0.51, p < 0.001) and innovative thinking (r = 0.46, p < 0.01). Interviews confirmed AI acted as a “tutor” for PS and a “research assistant” for RS.

Conclusion

PS and RS extensions are associated with complementary competencies. A tiered, AI-differentiated model may support personalized learning to cultivate clinically engaged communicators and critically thinking physician-scientists.