Эта страница была переведена автоматически, точность перевода не гарантируется. Пожалуйста, обратитесь к английской версии для исходного текста.

AI-Assisted Adaptive Simulation in Physiology Education (PBL)

20 мая 2026 г. обновлено: 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.

Обзор исследования

Статус

Завершенный

Условия

Вмешательство/лечение

Подробное описание

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.

Тип исследования

Интервенционный

Регистрация (Действительный)

672

Фаза

  • Непригодный

Контакты и местонахождение

В этом разделе приведены контактные данные лиц, проводящих исследование, и информация о том, где проводится это исследование.

Места учебы

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

Критерии участия

Исследователи ищут людей, которые соответствуют определенному описанию, называемому критериям приемлемости. Некоторыми примерами этих критериев являются общее состояние здоровья человека или предшествующее лечение.

Критерии приемлемости

Возраст, подходящий для обучения

  • Взрослый

Принимает здоровых добровольцев

Да

Описание

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

Учебный план

В этом разделе представлена ​​подробная информация о плане исследования, в том числе о том, как планируется исследование и что оно измеряет.

Как устроено исследование?

Детали дизайна

  • Основная цель: Фундаментальная наука
  • Распределение: Рандомизированный
  • Интервенционная модель: Параллельное назначение
  • Маскировка: Одинокий

Оружие и интервенции

Группа участников / Армия
Вмешательство/лечение
Экспериментальный: 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.
Поведенческий: 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.
Другие имена:
  • Adaptive Screen-Based Simulation
  • AI-Assisted Adaptive Simulation
  • Rule-Based Adaptive Simulation
  • Adaptive Physiology Simulation Platform
Активный компаратор: 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.
Поведенческий: 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.
Другие имена:
  • Standard Curriculum-Based Teaching
  • Conventional Teaching
  • Didactic Physiology Education
  • Traditional Physiology Instruction

Что измеряет исследование?

Первичные показатели результатов

Мера результата
Мера Описание
Временное ограничение
Physiological Reasoning Ability
Временное ограничение: 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
Временное ограничение: 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
Временное ограничение: 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)

Вторичные показатели результатов

Мера результата
Мера Описание
Временное ограничение
Student Engagement
Временное ограничение: 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
Временное ограничение: 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
Временное ограничение: 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)

Соавторы и исследователи

Здесь вы найдете людей и организации, участвующие в этом исследовании.

Спонсор

Saveetha University

Публикации и полезные ссылки

Лицо, ответственное за внесение сведений об исследовании, добровольно предоставляет эти публикации. Это может быть что угодно, связанное с исследованием.

Общие публикации

Даты записи исследования

Эти даты отслеживают ход отправки отчетов об исследованиях и сводных результатов на сайт ClinicalTrials.gov. Записи исследований и сообщаемые результаты проверяются Национальной медицинской библиотекой (NLM), чтобы убедиться, что они соответствуют определенным стандартам контроля качества, прежде чем публиковать их на общедоступном веб-сайте.

Изучение основных дат

Начало исследования (Действительный)

1 августа 2025 г.

Первичное завершение (Действительный)

31 января 2026 г.

Завершение исследования (Действительный)

31 января 2026 г.

Даты регистрации исследования

Первый отправленный

15 мая 2026 г.

Впервые представлено, что соответствует критериям контроля качества

20 мая 2026 г.

Первый опубликованный (Действительный)

27 мая 2026 г.

Обновления учебных записей

Последнее опубликованное обновление (Действительный)

27 мая 2026 г.

Последнее отправленное обновление, отвечающее критериям контроля качества

20 мая 2026 г.

Последняя проверка

1 мая 2026 г.

Дополнительная информация

Термины, связанные с этим исследованием

Ключевые слова

Другие идентификационные номера исследования

  • 24/032/2025/SR/SIBMS

Планирование данных отдельных участников (IPD)

Планируете делиться данными об отдельных участниках (IPD)?

НЕТ

Описание плана IPD

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.

Информация о лекарствах и устройствах, исследовательские документы

Изучает лекарственный продукт, регулируемый FDA США.

Нет

Изучает продукт устройства, регулируемый Управлением по санитарному надзору за качеством пищевых продуктов и медикаментов США.

Нет

Эта информация была получена непосредственно с веб-сайта clinicaltrials.gov без каких-либо изменений. Если у вас есть запросы на изменение, удаление или обновление сведений об исследовании, обращайтесь по адресу register@clinicaltrials.gov. Как только изменение будет реализовано на clinicaltrials.gov, оно будет автоматически обновлено и на нашем веб-сайте. .

Подписаться