Author: swoyam

EDCI335 Post 4

Blog Post #4

EDCI335 Post 3

Blog Post #2

EDCI335 Post 1

Overview:

Wearable devices like smartwatches, fitness trackers, and medical monitoring devices are revolutionizing personal healthcare, where one can collect data and monitor health continuously. Those devices are equipped with different types of sensors and technologies, which can make them measure various types of health indicators. Moreover, it can also provide users and healthcare professionals with valuable data about their health status. For example, Vini Vijayan mentions in the paper, “Review of Wearable Devices and data collection considerations for Connected Health. Sensors” regarding data gloves and balls with sensors that have been used to track the movement of the fingers in hand rehabilitation therapy for stroke patients. “Those sensors can evaluate the nerve conduction and activation frequency and quantify and monitor electrical activity associated with muscle contraction and muscle response in injured tissue. It can make treatments like MRI screens affordable for more people.” (Vini Vijayan ,etc2021).

However, wearable devices can also be overrated if they can not balance estimates of Interoperability. Stefano Canali has mentioned that wearable devices often make it difficult to distinguish between COVID-19 and seasonal flu, as well as standard flu cases—elevated heart rates more commonly can be interpreted as symptoms of respiratory illness, and as a result, wearables have incorrectly detected, and COVID-19 infections predicted.(Stefano Canali etc, 2022)

Misconceptions of Wearable Health Devices:

1. Wearable Health Monitors Are Not as Accurate as Medical-Grade Devices:

 One popular misconception is that wearable health monitors are as accurate as medical-grade devices. Although they assist in tracking overall health patterns and motivating positive, healthy practices, do not expect clinical instruments’ accuracy from these devices. They may not always be accurate since sensor quality, device placement, and user movement can affect measurements. Consequently, while these wearable devices can be helpful for daily health status monitoring, they should not replace professional medical assessment and diagnosis.

2. Wearable Devices Can Diagnose Diseases:

Another common misunderstanding is that wearable devices can diagnose diseases. In truth, most wearable technologies are meant to follow up on various aspects such as heart rate, steps taken in a day, sleep pattern or physical activity level, which saves time and helps the patient get the help needed more quickly by healthcare professionals (e.g., arrhythmia detection). However, diagnosis of medical conditions often necessitates comprehensive clinical evaluations and tests beyond what current wearable technologies provide.

A rationale for developing your learning resource based on this topic. What is it about this topic in particular that is of interest to you?

The need for medical care is a continuous, broad, and expanding project. Developing a learning resource on wearable devices in healthcare showcases its significant potential to monitor and help in treatments easily. Educating users on wearable devices can help raise awareness and correct misconceptions, along with promoting an easy tool to monitor one’s health. A few of us have some interest in the computer science and technology field, so looking into a topic that we could be working on in the near future is intriguing. Recently one of our friends just developed a motion tracking program that allows someone with a physical impairment be able to use and maneuver around a computer without needing to hold a mouse. This is not exactly in relation to a wearable device, but it’s one of the many inspiring ideas we could tackle in the technologically advancing medical field.

Learning Design Plan

Concept 1:

Big Idea

Workings of wearable devices in healthcare:

Wearable technology can provide reliable data on an individual’s health.

Learners will understand how wearable devices work in healthcare, including the technology they use, their uses, and their limitations.

Essential Questions

1. What are the different types of wearable devices currently used in healthcare, and how are they different from each other (Technology)?

2. What types of sensors are commonly used in wearable healthcare devices, and how do these sensors work?

Learning Outcomes

By the end of this lesson, learners will be able to:

1. Identify and describe different types of wearable devices used in healthcare.
2. Explain the technology and sensors used in these devices.
3. Analyze the functionality and data processing methods of wearable health devices.
4. Evaluate the accuracy and reliability of wearable device data.

Evidence of Learning

The learners can provide the following evidence for their learning:

1. Learners will describe how various wearable devices work and their uses.
2. Learners will use correct terms when explaining the technology and sensors in these devices.
3. Learners will analyze the functionality and data accuracy of these devices, using examples from technical sources.
4. Learners will evaluate the reliability of data produced by wearable devices through technical case studies.

Assessments

1. Quiz: Multiple-choice and short-answer questions about the types, technology, and uses of wearable devices.
2. Peer Review and Feedback: Learners evaluate each other’s case study reports, providing written feedback based on a rubric.
3. Case Study Analysis: Learners will analyze a technical case study involving wearable devices, focusing on the accuracy, reliability, and data processing methods of these devices, followed by group presentations on their findings.

Learning Activities

1. Interactive Lecture: A presentation on wearable health devices, including videos and demonstrations of different devices.
2. Reading Assignments: Academic articles on the technology and uses of wearable devices.
3. Hands-On Activity: A virtual lab where learners can simulate using wearable devices and understand the data they collect.
4. Group Discussion: Small group discussions about common technical misconceptions about wearable devices and their real-world implications.

This plan will help create an engaging and informative learning resource about wearable devices in healthcare.

Concept 2:

Big Idea

Usage and Case Studies of Wearable Devices in the Medical Field:

The data from wearable technology can be useful for both diagnostic and health promotion purposes. 

Learners will gain a comprehensive understanding of the significance, applications, and impact of wearable devices in the medical field, emphasizing how these technologies enhance patient care, diagnosis, and treatment.

Essential Questions:

1. How do various types of wearable medical devices function to monitor and improve patient health, and what criteria can be used to categorize these devices in the medical field?

2. What are the real-world impacts of wearable medical devices on healthcare outcomes, and how do the benefits and challenges of these devices influence their adoption and effectiveness in medical practice?

Learning Outcomes

By the end of this lesson, learners will be able to:

1. Categorize various wearable medical devices and explain their primary functions in the medical field.
2. Determine the criteria for selecting appropriate wearable devices for different medical conditions and patient needs based on functionality, data accuracy, and usability.
3. Assess the benefits and challenges associated with using wearable devices in healthcare.

Evidence of Learning

The learners can provide the following evidence for their learning:

1. Learners will correctly identify and describe different wearable devices and their uses in the medical field.
2. Learners will present a detailed analysis of a case study, demonstrating an understanding of the device’s application, and its reliability.
3. Learners will articulate the advantages and potential issues of using wearable devices in medical scenarios, supported by examples.

Assessments

1. Quiz: A quiz covering the different types of wearable devices and their usage in the medical field.
2. Case Study Report: A written report analyzing a selected case study, including an assessment of the device’s impact on patient care.
3. Presentation: Learners present their research on a specific wearable device, highlighting its medical applications and impact, followed by a Q&A session.

Learning Activities

1. Interactive Lecture and Videos: An introductory lecture supplemented by videos demonstrating various wearable medical devices and their applications in real-world scenarios.
2. Hands-on Exploration: Small group activities where learners interact with sample devices (or simulations) to understand their functionalities and use cases.
3. Case Study Review: Guided analysis of selected case studies where wearable devices were implemented in healthcare, including group discussions and critical thinking exercises to explore the outcomes.
4. Research and Presentation: Learners work in pairs or small groups to research a specific wearable device and present their findings to the class, focusing on the device’s medical applications and impact.
5. Peer Review and Feedback: A peer review session where learners critique each other’s case study reports, providing constructive feedback to improve their analyses.

By integrating these activities, learners will engage deeply with the topic, preparing them to demonstrate their understanding through the assessments.

References:

Canali, S., Schiaffonati, V., & Aliverti, A. (2022, October 13). Challenges and recommendations for wearable devices in Digital Health: Data Quality, interoperability, health equity, fairness. PLOS digital health. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9931360/

Vijayan, V., Connolly, J. P., Condell, J., McKelvey, N., & Gardiner, P. (2021, August 19). Review of Wearable Devices and data collection considerations for Connected Health. Sensors (Basel, Switzerland). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8402237/ 

Responsibilities:

Marco Lai: Wrote the Overview and the Misconceptions of Wearable Health Devices.

Brandon Chiem: Wrote the rationale for developing our learning resource and why we chose it.

JungJoo Yoon:  I wrote Big Idea 1 for the learning design plan along with the associated content.

Swoyam Rajbhandari: Wrote Big Idea 2 for the learning design plan and its corresponding content.

Based on the course outline and the reading for Week 2, the following assessment strategies are being used in the course:

Strategies Being Used:

1. Assessing Learning:
   • The course includes various learning outcomes and objectives that will be evaluated, such as identifying prominent learning theories, comparing learning design approaches, understanding learning design components, and developing an interactive learning resource.
   • These objectives suggest that the course will have assessments to gauge the student’s understanding and application of the material.
2. Feedback:
   • While specific methods of providing feedback are not explicitly detailed in the outline, it is reasonable to infer that feedback will be a part of the course, especially given the focus on developing and refining interactive learning environments. Constructive feedback is essential in such a process to guide students in improving their designs.
3. Reliability and Validity:
   • The course explicitly includes an outcome related to examining the reliability and validity of assessments. This indicates that students will engage in activities that ensure the assessments they design are both reliable and valid.

Strategies Not Explicitly Detailed:

1. Measuring Learning:
   • The outline does not explicitly describe how the measurement of learning will be conducted. While it can be inferred that learning will be measured through assignments and projects, the specific methods and tools for measuring learning are not detailed.
2. Alignment and the Assessment Triangle:
   • There is no explicit mention of the assessment triangle (alignment between learning objectives, instructional activities, and assessments) in the course outline. Although the course covers components of learning design, including assessment, and aims to help students construct well-aligned learning design strategies, the direct use of the assessment triangle as a framework is not specified.

The Week 2 assessment-related questions connect to several learning theories from Week 1. Here’s how they align:

Learning Theories and Week 2 Assessment Strategies

1. Behaviorism:
   • Assessment of/for/as Learning: Behaviorism focuses on observable behaviors and the responses to stimuli. In assessment, this can translate to evaluating specific, measurable outcomes through clear criteria. The concept of “assessment of learning” aligns with behaviorist principles, where learning is assessed through observable changes in behavior or performance.
   • Formative and Summative Assessment: Behaviorism supports the use of both formative (ongoing, during learning) and summative (final, after learning) assessments to reinforce desired behaviors and skills through repetition and reinforcement.
2. Constructivism:
   • Assessment of/for/as Learning: Constructivism emphasizes the learner’s active role in constructing knowledge based on their experiences. “Assessment for learning” aligns well with this theory as it focuses on using assessment as a tool to guide and improve the learning process, encouraging reflection and deeper understanding.
   • Formative and Summative Assessment: Formative assessments are particularly important in constructivist learning environments, as they provide continuous feedback and opportunities for learners to reflect, adapt, and build upon their understanding.
3. Connectivism:
   • Feedback: Connectivism highlights the importance of networks and connections in the learning process. Feedback within a networked environment can help learners understand how their knowledge and skills are connected and how they can apply them in different contexts.
   • Reliability and Validity: In a connective approach, ensuring that assessments are reliable and valid is crucial, as learners often gather and synthesize information from diverse sources. This helps maintain the integrity of the learning process and the accuracy of assessments.

As an undergraduate computer science student, this learning design course presents both similarities and differences when compared to typical computer science courses. Here’s a detailed comparison, emphasizing specific examples and the relevant learning theories and strategies:

Similarities:

1. Structured Learning Outcomes:
   • Both courses provide clear learning outcomes. In computer science courses, they might include specific programming skills, understanding algorithms, or mastering data structures. Similarly, this learning design course outlines objectives such as identifying learning theories and developing interactive learning environments.
   • Theoretical Connection: The clear learning outcomes in both courses align with behaviorist principles, which emphasize setting specific, measurable goals and assessing learning through observable outcomes.
2. Project-Based Learning:
   • In computer science courses, I often engaged in project-based learning, such as developing software or working on group projects. This learning design course also involves planning, designing, and developing an interactive learning environment.
   • Theoretical Connection: Project-based learning is grounded in constructivist theory, which posits that learners construct knowledge through active engagement and practical application.

Differences:

1. Focus on Learning Theories:
   • Computer science courses typically emphasize technical skills and theoretical knowledge specific to computing, such as algorithmic thinking and software engineering principles. In contrast, this learning design course places significant emphasis on understanding learning theories (behaviorism, constructivism, connectivism) and applying them to educational contexts.
   • Strategy: While computer science focuses on problem-solving and analytical thinking, the learning design course emphasizes metacognitive strategies—reflecting on how learning happens and how it can be facilitated.
2. Assessment Types and Feedback:
   • In computer science, assessments often include coding assignments, exams, and practical projects, with feedback focused on correctness, efficiency, and coding practices. The learning design course, however, includes a broader range of assessment strategies like formative assessments (ongoing feedback), summative assessments (final evaluations), and reflective assessments.
   • Theoretical Connection: The comprehensive approach to assessment in the learning design course aligns with constructivist and connectivist principles, which advocate for ongoing feedback and reflection to deepen understanding and adapt learning processes.
3. Technology Integration:
   • Both courses incorporate technology, but in different ways. Computer science courses use technology primarily as a subject of study (e.g., learning programming languages, software tools). In the learning design course, technology is a medium to enhance teaching and learning (e.g., using digital tools to create interactive learning environments).
   • Strategy: This aligns with connectivism, which emphasizes the role of technology and networks in learning, highlighting how digital tools can facilitate connections and access to information.

Specific Examples:

• Algorithms and Data Structures vs. Learning Theories:
  • In a typical computer science course on algorithms, I might learn about sorting algorithms, their efficiency, and their implementation in various programming languages. This involves understanding theoretical concepts and applying them to solve specific problems.
  • In the learning design course, I might study behaviorism, constructivism, and connectivism, understanding how each theory informs different teaching strategies and designing learning activities that reflect these theories.
• Software Development Projects vs. Interactive Learning Environments:
  • In a software development course, I might work on a project to develop a web application, focusing on user requirements, system design, coding, testing, and deployment.
  • In the learning design course, I would develop an interactive learning environment, focusing on learning objectives, engagement strategies, assessment methods, and the use of educational technology tools.

Comments:

Blog Post #1

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.

What is your preferred mode of remote communication?

I prefer using discord or instagram

What are your communication strengths?

I can speak English clear and concisely

What are your communication weaknesses? Where would you like to grow?

Although I have no problem with speaking and understanding English, as it’s not my first language, I sometimes do mess up pronunciations.

I would love to increase my proficiency in word pronunciations.

Do you consider yourself an introvert or extrovert?

Somewhere in between. I don’t like to be too active or take initiative for activities but I do like to make friends

What time zone are you in?

I’m in the Pacific Daylight Saving Time zone

What time of day do you prefer doing academic work?

During the evening or before midnight

When you are upset do you tend to share this with others or keep it to yourself?

If it will affect my health or thinking ability too much, then I would refer to others. Otherwise no.

What do you like about group work?

Having the chance to exchange ideas and recieve feedback

What don’t you like about group work?

I dont like it when any of the groupmates can’t complete their work before the due dates (i.e if they dont have any relevent excuses).

What else would you like your team to know?

I’m excited about working with all of you and I hope we can communicate and co-ordinate well during assignments.