Flipping STEM Education with Enhanced Pre-Lecture Videos and Integrated Transfer Questions
Project Lead: N. Weliweriya
In STEM education, encouraging students to engage with course material prior to class is a common strategy. However, this approach often falls short in terms of effectiveness. This proposal aims to address this challenge by enhancing pre-lecture videos with integrated near and far transfer questions. These improvements will provide students with active learning opportunities and promote deeper understanding of concepts.
Current Limitations and Issues: The conventional approach of requiring students to read the textbook before class has limitations. Students may lack time or motivation, struggle with comprehension, and miss interactive discussions. Similarly, relying solely on pre-lecture videos faces challenges due to passive viewing and absence of practical applications. These limitations result in surface-level understanding and hinder effective learning.
Objectives: The primary objective of this proposal is to enhance the pre-lecture preparation process through the integration of near and far transfer questions. The proposed approach seeks to:
- Promote Active Engagement: Encourage students to actively engage with pre-lecture videos by solving integrated multiple-choice questions (MCQs) that assess their understanding.
- Enhance Comprehension: Shift in-class focus to practical applications and examples, enabling deeper understanding and concept retention.
- Improve Problem-Solving Skills: Provide opportunities for students to apply learned concepts through quizzes and worksheets, fostering problem-solving proficiency.
Measures of Success:
- Engagement Metrics: Monitor student interaction with pre-lecture quizzes, tracking completion rates and accuracy of near transfer MCQs.
- Classroom Performance: Evaluate student performance in class discussions, problem-solving activities, and application-based worksheets.
- Exam Performance: Analyze exam scores and problem-solving approaches, correlating these with pre-lecture engagement and worksheet completion.
- Education Research Data: Utilize data collected from iPads to explore student voice and pen movements, assessing their problem-solving strategies and learning patterns.
- Algorithm Development: Work towards developing an algorithm that predicts student grades based on pre-lecture engagement and performance in transfer questions.
Implementation and Data Collection:
- Enhanced Pre-Lecture Videos: Develop 8–10-minute pre-lecture videos with integrated near transfer MCQs, encouraging active engagement and concept application.
- Classroom Application: Implement the flipped classroom approach, utilizing pre-lecture quizzes as a basis for in-class discussions and problem-solving activities.
- Data Collection Platform: Utilize iPads with Kyle's platform to collect student voice and pen movement data during pre-lecture engagement and in-class activities.
- Performance Analysis: Analyze data to assess the effectiveness of enhanced pre-lecture videos, correlations between engagement and performance, and potential algorithm development.
Education Research and Long-Term Impact:
This project not only seeks to enhance student engagement and understanding but also contribute to education research. The data collected will provide insights into student learning behaviors and problem-solving approaches. By integrating this approach across multiple courses, we can track knowledge transfer and develop a coaching system for application-based learning.
Incorporating near and far transfer questions into pre-lecture videos holds the potential to transform STEM education, bridging the gap between theoretical concepts and practical applications. Through this initiative, we aim to create a more engaged, proficient, and confident generation of STEM learners.
Involving Courses:
studio physics 1 for engineers' class (PHYS 1251) and Engineering statics course
Current Funding:
- EETI College of Engineering 2021,
- CTL’s learning technologies grant (LTG) 2021
- Affordable Materials Grant, University System of Georgia, 2022
Future Funding opportunities:
Will apply for the next round of USG’s Affordable Materials Grant (fall 2023) as an improvement for the current pre-lecture approach, and we will work with Sid to apply for next rounds of EETI (fall 2023), CTL’s LTG grants (Spring 2024).