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AI-Assisted Adaptive Simulation in Physiology Education (PBL)

2026年5月20日 更新者：Jeevarathinam Thirumalai、Saveetha University

Effect of Adaptive AI-Supported Simulation on Physiology Learning Outcomes Among Medical Students: A Randomized Controlled Trial

This randomized controlled trial evaluated whether an AI-assisted, rule-based adaptive screen-based simulation module could improve physiology learning outcomes among undergraduate health science students compared with conventional instruction. A total of 672 students from Physiotherapy, Occupational Therapy, Nursing, and Allied Health Sciences were randomly assigned in a 1:1 ratio to either the adaptive simulation group or the conventional teaching group. The intervention used web-based clinical physiology cases with algorithm-supported case sequencing, automated formative feedback, and structured faculty-led debriefing, while the control group received standard lectures, textbook reading, tutorial sessions, and laboratory practicals. The primary outcomes were physiological knowledge and reasoning ability, and the secondary outcomes were conceptual understanding, engagement, cognitive load, and academic self-efficacy. Assessments were performed at baseline, immediately after the 12-week intervention, and again at four-week follow-up.

調査の概要

状態

完了

条件

介入・治療

詳細な説明

This study was designed as a prospective, two-arm, parallel-group randomized controlled trial with repeated-measures assessment at three time points: baseline, immediately post-intervention, and four weeks after the intervention. It was conducted at Saveetha Institute of Basic Medical Sciences, India, between August 2025 and January 2026, and received institutional ethical approval before enrollment. Participants were undergraduate health science students aged 18 to 25 years who were enrolled in a Human Physiology course and had access to an internet-enabled personal device. Students with prior formal exposure to simulation-based physiology instruction or adaptive digital learning platforms were excluded. After baseline assessment, participants were randomized in a 1:1 ratio to the intervention or control group, with allocation concealment and blinded outcome assessment.

The intervention group received physiology instruction through a screen-based adaptive simulation environment over 12 weeks. The module was intentionally designed as a bundled educational strategy integrating adaptive case sequencing, automated formative feedback, and faculty-led debriefing. The adaptive component used predefined rule-based logic to personalize learning by adjusting case difficulty and feedback pathways according to learner performance; it did not use autonomous generative artificial intelligence or clinical decision-making. Participants completed structured simulation sessions for two hours per week, including pre-briefing, individual case-based simulation, and facilitated debriefing. The control group received conventional curriculum-based physiology instruction over the same 12-week period, including didactic lectures, prescribed textbook readings, tutorial sessions, and laboratory practicals.

The study prioritized objective learning outcomes. Physiological knowledge was measured using a 40-item multiple-choice test, physiological reasoning ability using a scenario-based rubric-scored assessment, and conceptual understanding using a physiology concept inventory. Secondary outcomes included student engagement measured with the USEI, cognitive load measured with NASA-TLX, and academic self-efficacy measured with an adapted CASES scale. Outcomes were collected at baseline, post-intervention, and follow-up using the same instruments across all time points.

研究の種類

介入

入学 (実際)

672

段階

  • 適用できない

連絡先と場所

このセクションには、調査を実施する担当者の連絡先の詳細と、この調査が実施されている場所に関する情報が記載されています。

研究場所

  • インド
    • Tamil Nadu
      • Chennai、Tamil Nadu、インド、602105
        • Saveetha Institute of Basic Medical Sciences (SIBMS), Saveetha Institute of Medical and Technical Sciences (SIMATS)

参加基準

研究者は、適格基準と呼ばれる特定の説明に適合する人を探します。これらの基準のいくつかの例は、人の一般的な健康状態または以前の治療です。

適格基準

就学可能な年齢

  • 大人

健康ボランティアの受け入れ

はい

説明

Inclusion Criteria:

  • Undergraduate students enrolled in Health Science programs including Physiotherapy, Occupational Therapy, Nursing, and Allied Health Sciences
  • Registered for a Human Physiology course during the study period
  • Age between 18 and 25 years
  • Proficiency in English language
  • Access to an internet-enabled personal device capable of supporting web-based educational applications
  • Willingness to provide written informed consent for participation

Exclusion Criteria:

  • Prior formal exposure to structured simulation-based physiology instruction
  • Prior exposure to adaptive digital learning platforms related to physiology education
  • Inability to access or use internet-enabled educational applications required for the intervention
  • Declined or withdrew informed consent for participation

研究計画

このセクションでは、研究がどのように設計され、研究が何を測定しているかなど、研究計画の詳細を提供します。

研究はどのように設計されていますか？

デザインの詳細

  • 主な目的：基礎科学
  • 割り当て：ランダム化
  • 介入モデル：並列代入
  • マスキング：独身

武器と介入

参加者グループ / アーム
介入・治療
実験的：I-Assisted Adaptive Simulation Group
Participants received AI-assisted algorithm-supported adaptive screen-based physiology simulation over a 12-week period. The intervention included adaptive case sequencing, automated formative feedback, interactive clinical reasoning activities, animated physiological visualization, and structured faculty-led debriefing sessions aligned with physiology curriculum objectives.
行動：AI-Assisted Algorithm-Supported Adaptive Simulation
The intervention consisted of an AI-assisted algorithm-supported adaptive screen-based physiology simulation delivered over 12 weeks. Participants engaged in structured web-based simulation sessions involving interactive clinical case scenarios, animated physiological visualizations, adaptive case sequencing, automated formative feedback, and faculty-led debriefing. The adaptive instructional system operated through predefined rule-based educational algorithms that adjusted case difficulty, feedback pathways, and learning progression according to participant performance within faculty-defined parameters. Sessions included pre-briefing, individual simulation-based clinical reasoning activities, adaptive feedback, and reflective debriefing. The intervention was implemented in alignment with the INACSL Healthcare Simulation Standards of Best Practice and focused on improving physiological knowledge, conceptual understanding, and clinical reasoning skills.
他の名前：
  • Adaptive Screen-Based Simulation
  • AI-Assisted Adaptive Simulation
  • Rule-Based Adaptive Simulation
  • Adaptive Physiology Simulation Platform
アクティブコンパレータ：Conventional Instruction Group
Participants received standard curriculum-based physiology instruction over a 12-week period, including didactic lectures, prescribed textbook readings, faculty-guided tutorial sessions, and scheduled laboratory practicals covering core physiological systems.
行動：Conventional Physiology Instruction
Participants received standard curriculum-based physiology instruction over a 12-week period according to institutional teaching guidelines. Conventional instruction included didactic lectures, prescribed textbook readings, faculty-guided tutorial sessions, and scheduled laboratory practicals covering cardiovascular, respiratory, renal, neurological, endocrine, gastrointestinal, musculoskeletal, and integumentary physiology. Tutorial sessions focused on instructor-led clarification of physiological concepts, small-group discussion, and question-and-answer interactions. Laboratory practicals included supervised physiological measurements, observation of physiological demonstrations, interpretation of experimental findings, and guided analysis of physiological responses. The control condition did not include adaptive simulation, automated formative feedback, algorithm-supported instructional adaptation, or structured simulation-based clinical reasoning activities.
他の名前：
  • Standard Curriculum-Based Teaching
  • Conventional Teaching
  • Didactic Physiology Education
  • Traditional Physiology Instruction

この研究は何を測定していますか？

主要な結果の測定

結果測定
メジャーの説明
時間枠
Physiological Reasoning Ability
時間枠：Baseline (Week 1), post-intervention (Week 13), and follow-up (Week 17)
Physiological reasoning ability was assessed using a scenario-based assessment requiring hypothesis generation, interpretation of physiological data, and application of physiological mechanisms to management decisions. Responses were scored using a standardized four-point analytic rubric assessing reasoning and clinical interpretation skills. Higher scores indicate better physiological reasoning ability.
Baseline (Week 1), post-intervention (Week 13), and follow-up (Week 17)
Physiological Knowledge
時間枠：Baseline (Week 1), post-intervention (Week 13), and follow-up (Week 17)
Physiological knowledge was assessed using a faculty-developed 40-item multiple-choice assessment designed to evaluate conceptual understanding and applied physiological reasoning across eight core physiological systems, including cardiovascular, respiratory, renal, neurological, endocrine, gastrointestinal, musculoskeletal, and integumentary physiology. Higher scores indicate better physiology knowledge performance.
Baseline (Week 1), post-intervention (Week 13), and follow-up (Week 17)
Conceptual Understanding
時間枠：Baseline (Week 1), post-intervention (Week 13), and follow-up (Week 17)
Conceptual understanding was assessed using a faculty-developed Physiology Concept Inventory designed to evaluate deep conceptual understanding, integration of physiological mechanisms across systems, and identification of common physiological misconceptions. Higher scores indicate better conceptual understanding of physiology concepts.
Baseline (Week 1), post-intervention (Week 13), and follow-up (Week 17)

二次結果の測定

結果測定
メジャーの説明
時間枠
Student Engagement
時間枠：Baseline (Week 1), post-intervention (Week 13), and follow-up (Week 17)
Student engagement was assessed using the University Student Engagement Inventory (USEI), which evaluates behavioral, emotional, and cognitive dimensions of learner engagement. Higher scores indicate greater learner engagement during physiology learning activities.
Baseline (Week 1), post-intervention (Week 13), and follow-up (Week 17)
Cognitive Load
時間枠：Baseline (Week 1), post-intervention (Week 13), and follow-up (Week 17)
Cognitive load was assessed using the NASA Task Load Index (NASA-TLX), a multidimensional measure evaluating perceived cognitive workload and task demand during learning activities. Higher scores indicate greater perceived cognitive workload.
Baseline (Week 1), post-intervention (Week 13), and follow-up (Week 17)
Academic Self-Efficacy
時間枠：Baseline (Week 1), post-intervention (Week 13), and follow-up (Week 17)
Academic self-efficacy was measured using an adapted version of the College Academic Self-Efficacy Scale (CASES) to evaluate learner confidence in physiology-related academic tasks and simulation-based learning activities. Higher scores indicate greater academic self-efficacy.
Baseline (Week 1), post-intervention (Week 13), and follow-up (Week 17)

協力者と研究者

ここでは、この調査に関係する人々や組織を見つけることができます。

スポンサー

Saveetha University

出版物と役立つリンク

研究に関する情報を入力する責任者は、自発的にこれらの出版物を提供します。これらは、研究に関連するあらゆるものに関するものである可能性があります。

一般刊行物

研究記録日

これらの日付は、ClinicalTrials.gov への研究記録と要約結果の提出の進捗状況を追跡します。研究記録と報告された結果は、国立医学図書館 (NLM) によって審査され、公開 Web サイトに掲載される前に、特定の品質管理基準を満たしていることが確認されます。

主要日程の研究

研究開始 (実際)

2025年8月1日

一次修了 (実際)

2026年1月31日

研究の完了 (実際)

2026年1月31日

試験登録日

最初に提出

2026年5月15日

QC基準を満たした最初の提出物

2026年5月20日

最初の投稿 (実際)

2026年5月27日

学習記録の更新

投稿された最後の更新 (実際)

2026年5月27日

QC基準を満たした最後の更新が送信されました

2026年5月20日

最終確認日

2026年5月1日

詳しくは

本研究に関する用語

キーワード

その他の研究ID番号

  • 24/032/2025/SR/SIBMS

個々の参加者データ (IPD) の計画

個々の参加者データ (IPD) を共有する予定はありますか?

いいえ

IPD プランの説明

Individual participant data (IPD) will not be publicly shared because the dataset contains institution-linked educational performance information and participant-level academic assessment data. De-identified data may be considered for academic collaboration upon reasonable request to the corresponding author, subject to institutional ethical approval and data-sharing regulations.

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いいえ

米国FDA規制機器製品の研究

いいえ

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