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Related Concept Videos

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Albert Bandura's theory of observational learning identifies four critical processes: attention, retention, motor reproduction, and reinforcement or motivation.
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Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...
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Updated: Aug 16, 2025

Mixed Reality for Education MRE Implementation and Results in Online Classes for Engineering
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Modeling with Real-Time Informative Feedback: Implementing and Evaluating a New Massive Open Online Course Component.

Niva Wengrowicz1, Rea Lavi2, Hanan Kohen1

  • 1Faculty of Industrial Engineering and Management, Technion - Israel Institute of Technology, Haifa, Israel.

Journal of Science Education and Technology
|December 27, 2022
PubMed
Summary
This summary is machine-generated.

A new feature called MORTIF (Modeling with Real-Time Informative Feedback) was developed for a model-based systems engineering MOOC. Students highly preferred MORTIF, demonstrating its effectiveness in active learning and providing valuable feedback for improved model submissions.

Keywords:
Engineering educationLearning styleMBSEMOOCOPCloudOPMPedagogical usability

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Area of Science:

  • Educational Technology
  • Systems Engineering Education
  • Online Learning

Background:

  • Massive Open Online Courses (MOOCs) require innovative pedagogical tools to enhance engagement and learning outcomes.
  • Model-based systems engineering (MBSE) presents unique challenges for online learners.
  • Effective feedback mechanisms are crucial for mastery in complex technical domains.

Purpose of the Study:

  • To introduce and evaluate the pedagogical usability of MORTIF (Modeling with Real-Time Informative Feedback), a novel learning feature for an MBSE MOOC.
  • To investigate learner characteristics, preferences, and learning styles associated with the MORTIF feature.
  • To assess the effectiveness of MORTIF in promoting meaningful learning through active engagement and immediate feedback.

Main Methods:

  • A mixed-methods approach was employed, combining MOOC server data analysis with online questionnaires.
  • 295 participants engaged with the MORTIF feature within the MOOC.
  • Analysis included 12,095 submissions to track feature usage and student feedback.

Main Results:

  • The study observed an increasing frequency of participants utilizing the model resubmission option within MORTIF.
  • Students ranked MORTIF highest among six question types for preference and perceived contribution.
  • Nine distinct learning style categories were identified based on student explanations of their MORTIF preference.

Conclusions:

  • MORTIF effectively promotes meaningful learning by combining active learning with real-time, informative feedback.
  • The MORTIF feature is highly embraced by students, offering benefits such as immediate feedback, iterative improvement opportunities, and adaptability to diverse learning styles.
  • The findings support the hypothesis that active learning coupled with immediate, actionable feedback is a highly effective educational mode.