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Direct Instruction: Characteristics and Application to Wearable Devices in Healthcare
Direct instruction is a teacher-centered approach that emphasizes clear and systematic teaching of knowledge and skills. This method includes structured lessons, clear goal setting, teacher demonstrations, guided practice, and frequent assessment and feedback. The teacher plays a central role in delivering content and ensuring that students fully understand the subject.
In contexts where learners need to acquire skills for specific tasks, direct instruction can be particularly effective. For example, learning to use wearable devices like smartwatches and fitness trackers for health monitoring requires understanding specific functions and technologies. Direct instruction helps learners efficiently acquire these skills.
Characteristics of Direct Instruction:
- Clear Goals: Setting specific learning goals for students. For example, “By the end of this lesson, learners will be able to set up and use their fitness tracker to monitor daily activity.”
- Structured Lessons: Following a set plan that includes an introduction, demonstration, guided practice, independent practice, and assessment.
- Teacher Demonstration: The teacher shows how to perform tasks, such as setting up a fitness tracker or using its features.
- Guided Practice: Students practice with the teacher’s help, receiving immediate feedback.
- Independent Practice: Students use the devices on their own, applying what they’ve learned.
- Regular Assessment: Frequent checks to ensure students understand the material, using quizzes, practical tests, and discussions.
Application to Wearable Devices in Healthcare:
Wearable devices like smartwatches and fitness trackers help monitor health by tracking metrics such as steps, heart rate, and sleep patterns. Direct instruction can teach users how to use these devices effectively, ensuring they understand how to set them up, interpret the data, and use the information to monitor their health.
How Direct Instruction Fits with Wearable Devices:
- Clear Goals: For instance, “Learners will set up their fitness tracker and monitor daily activity.”
- Structured Lesson Plan: Begin with an overview of wearable health devices, followed by step-by-step instructions on setting up and using the device.
- Teacher Demonstration: Show how to navigate device features like step counting and heart rate monitoring.
- Guided Practice: Learners set up their devices with the teacher’s guidance, practicing in a controlled environment.
- Independent Practice: Learners use the device independently to track health metrics over a week.
- Assessment and Feedback: Assess learners’ understanding through quizzes, practical demonstrations, and discussions.
Example Lesson Plan:
- Introduction: Explain the importance of wearable devices in personal healthcare.
- Demonstration: Teacher sets up a fitness tracker, showing its features and functions.
- Guided Practice: Learners set up their own devices with teacher assistance.
- Independent Practice: Learners use the device for a specified period, tracking their health data.
- Assessment: Quizzes, practical tests, and discussions to ensure understanding.
Conclusion:
Direct instruction is effective for teaching the technical skills needed to use wearable health devices. It ensures learners acquire the necessary skills systematically, with ample opportunities for practice and feedback. Combining direct instruction with real-world application enhances the learning experience and prepares learners to use wearable devices confidently and effectively in their daily lives.
Assessment Strategies Used
- Formative Assessment:
- Peer Feedback: Students give feedback to each other to help improve their work continuously.
- Self-Assessment: Students reflect on their own learning and progress.
- Ongoing Feedback: Students get feedback on drafts and assignments before the final submission.
- Connection to Learning Theories:
- Constructivism: This theory suggests learning happens through interactions and feedback, which matches well with these strategies.
- Cognitivism: This theory focuses on how we process information, and getting regular feedback helps with this process.
- Summative Assessment:
- Final Projects: Students complete a big project at the end of the course to show what they’ve learned.
- Connection to Learning Theories:
- Behaviorism: This theory focuses on observable behaviors, like how well you perform on a final project.
Assessment Strategies Not Used
- Multiple-Choice Tests:
- This course doesn’t use tests with multiple-choice questions, which are common in other courses.
- Connection to Learning Theories:
- Behaviorism: These tests check if you can choose the correct answer, fitting well with behaviorist ideas.
- Automated Grading Systems:
- This course doesn’t use systems that automatically grade your work, which are often used in computer science courses.
- Connection to Learning Theories:
- Behaviorism: Automated grading provides instant feedback on right or wrong answers.
Comparison to Computer Science Courses
- Typical Computer Science Course Assessments:
- Automated Coding Assignments: These are graded by computers based on whether the code works correctly.
- Exams and Quizzes: Use multiple-choice questions and coding problems to test knowledge.
- Project-Based Assessments: Students work on projects, but they often don’t get as much feedback during the process.
- Differences:
- Peer Feedback and Self-Assessment: These are used more in this course but not as much in computer science courses.
- Emphasis on Formative Assessment: This course focuses more on continuous feedback rather than just final grades.
Specific Examples
- Formative Feedback:
- In this course, students might submit a draft and get feedback from classmates and instructors, similar to a code review in some advanced computer science courses.
- Learning Theory Connection: Constructivism, which suggests that feedback helps build understanding.
- Summative Projects:
- Both types of courses might have final projects. In computer science, it could be a big coding project. In this course, it might be designing a learning plan.
- Learning Theory Connection: Behaviorism, focusing on the final performance to show what’s been learned.
Conclusion
The course “Learning Design for Technology-Mediated Environments” uses many different ways to assess learning, especially focusing on continuous feedback and reflection. This approach matches theories that say we learn best through interaction and feedback. In contrast, computer science courses often use automated grading and tests, which fit with theories that focus on right and wrong answers. This course’s approach can help students think more deeply about their learning compared to the more straightforward methods used in computer science.
- Learning Pod Self Reflection
Please answer the following questions in this document for your first introductory blog post in preparation for your initial team meeting with your Learning Pod. This information will allow your team members to get to know how you work best so that the group can make team agreements that work for all.
Preferred Mode of Remote Communication:
I prefer using Discord.Communication Strengths:
I can speak Korean very fluently.Communication Weaknesses and Growth Areas:
I’m an international student, so English is not my first language. Therefore, my English skills are not as strong as those of other local students. I’m trying to speak with other students at UVIC to improve my English skills.Introvert or Extrovert:
I’m an extrovert.Time Zone:
I’m in the Pacific Time Zone.Preferred Time for Academic Work:
I prefer to do academic work at night.When Upset:
When I feel upset, I usually keep it to myself.Likes About Group Work:
I like to share my ideas.Dislikes About Group Work:
I don’t like it when someone doesn’t respect other teammates.Additional Information for the Team:
My English skills are not very good, so I want to let everyone know to please be patient when I share my ideas.