Category: Uncategorised (Page 2 of 2)

As we finalize our interactive learning resource on cybersecurity for high school students, applying both inclusive learning design and universal design for learning (UDL) has become central to our approach. We want to ensure every learner—regardless of their background, ability, or context—can access and engage with our module meaningfully.

Meeting All Learners’ Needs
Our resource includes short videos, interactive quizzes, infographics, and a project-based activity. Following UDL principles, we offer multiple means of representation (e.g., audio + visuals in videos, transcripts, bilingual captions), engagement (gamified quizzes and real-life privacy case studies), and expression (students can submit a mind map, a written summary, or a video reflection for their final activity). This allows learners to choose how they take in information and demonstrate their understanding, which reduces anxiety and supports different learning styles.

Responding to Unexpected Events
If an unexpected event like a pandemic forces students to learn from home, we’re prepared. All resources will be accessible online with mobile-friendly design. We plan to include a short onboarding tutorial—a step-by-step guide (with visuals and voice-over) showing students how to navigate the platform, submit tasks, and ask questions via our forum. We’ll also provide teachers with a facilitation toolkit to support asynchronous learning.

Barriers and Adjustments
In our Blueprint, one interactive activity involves students analyzing a mock social media profile for privacy risks. However, this could be a barrier for students with visual impairments or limited internet. To address this, we’ll offer an alternative: an audio-based scenario and a text transcript version with the same learning outcomes.

Engineering Inspiration: The Oxo Good Grips Example
One example of universal design in engineering that inspires us is the Oxo Good Grips kitchen tools—originally made for people with arthritis, but now appreciated by everyone for their comfort and ease. Similarly, we aim to design our module so that it’s better for all, not just accessible to a few.

I’ve really appreciated seeing how others are applying these ideas too. For instance, [Peer Name]’s post on adjusting science lab activities for remote learning gave me new ideas for flexibility. Also loved how [Another Peer]’s module design makes space for student voice—definitely a principle we want to amplify as well.

Our Group: Group C

Feedback For: Group A

Alzheimer’s Disease

Overall Impression
The learning resource presents valuable and accessible information on Alzheimer’s disease. It appears to be designed with clarity and empathy, aiming to raise awareness and understanding among a general audience. That said, there are a few areas where the structure, interactivity, and alignment with instructional design principles could be strengthened.

Clarity of the Lesson
Strengths: The tone is approachable, and the language is generally clear and accessible. The topic is introduced in a simple and inviting way.
Suggestions:
You might consider adding clear learning objectives or outcomes at the beginning of the lesson. This would help users understand what they should gain from the resource.
Is there a way to segment the content more visually? Currently, most of the material is presented in long paragraphs—perhaps subheadings or bullet points could improve readability.

Learning Outcomes & Alignment
Observations:
I might have missed them, but I didn’t see any explicit learning outcomes listed.
Suggestions:
You might consider framing your outcomes using action verbs like “Describe,” “Identify,” or “Explain.”
E.g., “By the end of this module, learners will be able to describe the early symptoms of Alzheimer’s disease.”
Once outcomes are added, it would be helpful to ensure that each section aligns with those stated goals. For example, if one outcome is about understanding risk factors, make sure there’s a section clearly dedicated to that.

Interactivity
Observations:
Most of the content is static text with some videos embedded.
Suggestions:
In what way is this activity interactive? Consider adding knowledge check questions, drag-and-drop activities, or even a simple poll or reflection prompt.
You might consider using tools like H5P to add interactive elements that reinforce key concepts.

Inclusivity
Strengths: The tone is respectful and avoids jargon, which is great for accessibility.
Suggestions:
Consider whether there are multiple perspectives represented in the content—e.g., voices of caregivers, or cultural views on aging and dementia.
Are the videos captioned for accessibility? Ensuring closed captions or transcripts are available would enhance inclusivity.

Technology Use & Rationale
Observations: The website is functional and mobile-friendly, with multimedia elements included.
Suggestions:
Could you briefly explain your rationale for using video versus other tools? For example: “Videos were selected to provide visual context and emotional connection…”
You might also consider adding a short tutorial or guiding question before a video to help learners focus.

Presentation
Strengths: The use of images and white space is helpful.
Suggestions:
There are a few areas where the font size and contrast could be more readable.
Could the visual flow be improved with section headers or icons?

Final Thoughts
This resource offers great potential and conveys information in a compassionate way. To further improve it, I suggest:
Adding explicit outcomes and aligning content with them.
Increasing interactivity for deeper engagement.
Enhancing accessibility and inclusivity.
Including citations for key claims or statistics.
Keep up the great work—this is a meaningful topic, and the resource already shows a strong foundation!

1. Big Idea & Learning Outcomes

Overview

Artificial intelligence, or AI, is about creating systems that can handle tasks we usually associate with human thinking, like learning from experience, solving problems, or making decisions (Russell & Norvig, 2021). It’s all around us, from the voice assistants on our phones to self-driving cars on the road. John McCarthy, one of the early minds behind AI, saw it as a way to mimic how humans think, letting machines adapt to the world they’re in (McCarthy, 2007). This learning plan is here to pull back the curtain on AI. It’ll help students figure out how it works, where it pops up in their lives, and what it means for the world. With hands-on projects and group discussions, they’ll not only get the basics but also start thinking hard about where AI might take us next.

We’re designing this for high school students, ages 15 to 18, in a regular classroom setting. These kids are already at home with tech. They’re streaming music, scrolling social media, and gaming with friends. They’re curious about how stuff works and often dream of futures in science, tech, or engineering. Sure, they use AI tools every day, like Netflix suggestions or Siri, but most haven’t peeked under the hood or thought about its bigger impact. They’ve got a good foundation in math and science from school. Still, we’ll need to break down tricky ideas, like algorithms or ethics, into examples they can connect with. Our aim is to spark their interest and get them wrestling with big questions, even if they’re new to all this.

Learning Theory and Rationale

We’re building this around constructivism, the idea that people learn best by piecing things together themselves through experience and reflection (Piaget, 1970). It’s a great fit for AI because it’s not just facts to memorize. It’s a living, changing thing that touches everything from TikTok to hospitals. Students will connect what they already know, like how their phone works, to bigger ideas, like how AI learns. They’ll figure it out as they go. Talking it over with friends and tackling real examples helps them make sense of it all. This way, they’re not just taking in info. They’re ready to question and shape the AI world they’re growing into.

Learning Design and Rationale

We’re going with project-based learning. Think of it as learning by doing. Students will dig into AI examples, like how YouTube picks videos, and even build something of their own, like a simple chatbot. It’s perfect for high schoolers because it turns big ideas into stuff they can touch and play with. It ties back to their own lives. Working on projects together gets them solving problems and dreaming up new ideas. Those are skills they’ll need down the road. Plus, wrestling with questions like “Is AI fair?” keeps their minds sharp and engaged.

Technology Choices and Rationale

We’re bringing in some cool tools to make this work:

• AI Platforms (e.g., ChatGPT, Google’s Teachable Machine): These let students mess around with AI themselves. They’ll see how it thinks and what it can do.
• Simulation Tools: Things like TensorFlow give them a sandbox to test ideas without breaking anything.
• Teamwork Tech (e.g., Google Colab, Canva AI): These help them collaborate and show off what they’ve made, just like pros do.
  These picks keep things fun and familiar. Students already live online. The tools let them explore in a way that sticks. It’s all about giving them what they need to learn by doing and think ahead.

Big Idea 1: How is Artificial Intelligence Changing Everyday Life?

• Smart Assistants & Language Models (e.g., Siri, ChatGPT): These handy tools help with everything from setting reminders to writing a story. They make life smoother and more creative.
• Personalized Recommendation Systems (e.g., Netflix, YouTube, Spotify): They dig into what we like, using tons of data to suggest the next show or song we’ll enjoy.
• Smart Homes & Automation (e.g., Robot Vacuums, Smart Locks): From cleaning the floor to locking the door, these gadgets make home life easier and safer.

Key Considerations:
How does AI make our days better by learning what we need? What happens when we lean on it too much? Could we be giving up more than we gain, like our privacy?

Big Idea 2: The Role of AI in Key Industries

• Healthcare: Picture AI spotting diseases in X-rays or tailoring treatments to someone’s DNA. It’s changing how doctors keep us healthy.
• Education: Tools like Duolingo adjust to how each student learns. They make school feel more personal.
• Transportation: Self-driving cars and smart traffic lights are shaking up how we get around. They aim for safer, faster trips.

Key Considerations:
Could AI ever take over from doctors, teachers, or drivers completely? As it speeds things up, what tough questions do we need to face, like fairness or job losses?

Learning Outcomes

By the time we wrap up, students will:

• Get a grip on what makes AI tick, like machine learning or neural networks, and point to examples they see every day.
• Break down how AI’s shaking up fields like healthcare or transportation, with real stories to back it up.
• Weigh the good and the tricky sides of AI, from privacy worries to job shifts to ethical debates, and sharpen their thinking along the way.
• Dream up their own AI idea and bounce it around with classmates, building on what they’ve learned.

2.Evidence of Learning & Reference

Artificial intelligence (AI) is transforming daily life by enhancing automation, decision-making, and efficiency. It powers virtual assistants, smart homes, healthcare diagnostics, self-driving cars, and personalized recommendations. AI improves industries like finance, education, and entertainment through data analysis and predictive algorithms. While it boosts convenience and innovation, ethical concerns such as privacy, bias, and job displacement remain challenges. AI continues to evolve, shaping the future of human interactions and technology.

Evidence of Learning: Learning will be demonstrated through various forms of assessment and participation

• Perform tasks accurately: students will successfully use artificial intelligence tools such as chatbots or machine learning models in practical exercises.
• Use terminology correctly: learners will use ai-related vocabulary correctly in discussions, written assignments, and presentations.
• Critical analysis and applications: students will analyze case studies and provide strong supporting arguments for Ethics of artificial intelligence and social impact.
• Problem solving and innovation: Learners will demonstrate creativity and applied knowledge by proposing ai-driven solutions to industry-specific challenges.
• Collaboration and communication: participation in panel discussions, debates and presentations will demonstrate the ability to present and defend ideas based on research.

1. Perform Tasks Accurately

Engage students in practical exercises using AI tools such as chatbots and machine learning models. Hands-on activities could include:

• Training a chatbot to answer FAQs using tools like ChatGPT, IBM Watson, or Dialogflow.
• Developing an image recognition model using platforms like Google’s Teachable Machine or TensorFlow.
• Implementing AI-powered recommendation systems to personalize learning content for students.
• Exploring AI-based sentiment analysis to analyze social media trends and opinions.

These exercises reinforce AI applications by bridging theory with practice and preparing students for real-world AI problem-solving.

Resource:

https://ditchthattextbook.com/ai-tools/

2. Use Terminology Correctly

Encouraging students to accurately use AI-related vocabulary in discussions, written work, and presentations is essential for building confidence and technical fluency. To strengthen their understanding, this section combines vocabulary-focused strategies with real-world case studies and project-based learning.

Strategies to Reinforce Vocabulary:

• Build an AI Glossary: Students collaboratively define key terms such as neural networks, supervised learning, deep learning, and natural language processing.
• Peer Teaching: Learners take turns explaining AI terms and concepts to classmates in simplified language or with real-life examples.
• Contextual Usage: Vocabulary is embedded in class debates, essays, presentations, and responses to ethical dilemmas involving AI.
• Interactive Reinforcement: Use flashcards, quizzes, or vocabulary games to support retention and engagement.

Project-Based Learning & Real-World Application:

To apply terminology in meaningful contexts, students will also:

• Analyze real-world AI case studies, such as facial recognition in public surveillance, AI in healthcare diagnostics, or recommendation algorithms on social media platforms.
• Develop small-scale AI projects (e.g., building a sentiment analysis app or chatbot), where students must document and present their process using accurate AI terminology.
• Reflect on current events related to AI by writing blog posts or opinion pieces using appropriate technical language.

By combining vocabulary learning with applied, real-world tasks, students will develop both fluency and confidence in discussing and implementing AI concepts.

Resource: https://www.educationalinnovation360.com/blogs/empowering-students-in-the-digital-age-the-role-of-ai-in-developing-essential-skills

3. Critical Analysis and Applications

Assign students to analyze case studies on AI ethics and social impact. Activities may include:

• Investigating algorithmic biases in AI-powered hiring systems and facial recognition technology.
• Evaluating the ethical implications of AI surveillance systems and privacy concerns.
• Studying the impact of AI on employment and the future of work.
• Discussing AI-driven misinformation and the spread of fake news.
• Assessing the fairness of AI decision-making in criminal justice and credit scoring.

A useful case study is Dr. Joy Buolamwini’s research on biases in facial recognition technology, which sheds light on ethical considerations in AI.

Resource: https://en.wikipedia.org/wiki/Joy_Buolamwini

4. Problem Solving and Innovation

Encourage students to propose AI-driven solutions to real-world challenges. For example:

• Developing AI applications for healthcare, finance, or education.
• Addressing ethical and accessibility concerns in AI development.

Resource: https://www.eklavvya.com/blog/ai-edtech-tools/

5. Collaboration and Communication

Facilitate participation in panel discussions, debates, and presentations. AI tools can enhance engagement through:

• AI-generated interactive presentations using tools like Canva AI or PowerPoint Designer.
• AI-assisted research on discussion topics using platforms like Elicit and Perplexity AI.
• Hosting AI-driven debates where students defend ethical positions based on AI research.
• Collaborative AI coding projects using platforms like Google Colab.

Encouraging discussion and teamwork ensures students develop strong communication skills and a deeper understanding of AI applications.

By incorporating these strategies, students will demonstrate their understanding of AI through practical applications, accurate terminology use, critical thinking, innovative problem-solving, and effective communication. AI education not only prepares learners for future careers but also fosters ethical and responsible AI development.

3. Assessments （misunderstanding and mistakes）

With the continuous development of science and technology, artificial intelligence (AI) has penetrated into our daily lives—from mobile assistants to voice control to intelligent driving. These technologies surround us and affect how we live and work. However, many people still hold some misunderstandings about AI and often make avoidable mistakes in how they use or view it.

Common Misunderstandings

1. AI is completely objective
AI’s decisions rely on the data it is trained on. If the training data is biased—intentionally or unintentionally—then the AI’s output will also reflect that bias. Therefore, AI is not absolutely objective, as people often assume. This is crucial to understand because people may be misled by AI-generated conclusions that appear neutral but are actually biased.

2. AI will replace all human jobs
While AI may replace some repetitive or simple jobs, it is more accurately a tool to assist humans and improve their efficiency. Many movies depict AI developing emotions or attacking humans to take over the world, which has led to the false belief that AI is a threat. In reality, current AI is still at the stage of “weak” artificial intelligence—it can simulate human behavior but has no true consciousness or emotions. It is not capable of autonomous action or decision-making in the way that people fear.

Common Mistake

Over-reliance on AI
Although AI can be highly accurate and convenient, relying on it too much may weaken our own ability to think critically and make decisions independently. We must remember that AI is created by humans, and it is only through human innovation and independent learning that AI can continue to improve. If we stop thinking for ourselves and let AI do everything, technological and societal progress may stagnate.

Test

Quiz 1 （50%）

Quiz 2 （50%）

Complete all quizzes

Calculate Grades example

• Quiz 1 （4/5）=80% /2 40%
• Quiz 2 （3/5）=60%/2 30%

Total grade ： 40% + 30% = 70%

Quiz 1

Test 1

Quiz 2

Test 2

Notes

There is only one chance to take the exam and there is no chance to retake it. Please plan your trip in advance.

To pass the course, you need an average score of 50% on both exams.

4. Learning Activities (Learning Activity Design)

Reasons for Developing Learning Resources

Artificial intelligence is changing our lives, and it involves a wide range of areas that only humans can imagine. There is nothing that artificial intelligence cannot cover. Learning AI can help us better understand and adapt to this rapidly developing world.

Activity 1: Case Study Analysis (Exploring Recommendation Systems)

Activity Description:

• Students form groups to select a common AI recommendation system (such as Netflix, TikTok, or Douyin) and investigate the underlying algorithm logic.
• Each group collects authentic data, examines algorithmic personalization and its influence on user behavior, and assesses its societal impacts and ethical implications.

Example:

• Students analyze YouTube’s recommendation patterns, observing how different users’ interest tags and viewing history influence recommended video results.

Implementation Methods:

• Data collection and compilation.
• Writing a report (including algorithm overview, societal impacts, and ethical considerations).
• Group presentations and discussions.

Learning Objectives:

• Enhance understanding of AI recommendation algorithms and their societal impact.
• Improve skills in analytical thinking, data interpretation, and academic writing.

Activity 2: Simulation and Comparative Analysis (AI Capabilities and Limitations)

Activity Description:

• Students utilize AI tools such as ChatGPT or Google Translate to perform tasks involving complex text translation, summarization, or creative content generation.
• Parallel tasks are completed by students themselves, allowing comparison of the quality and efficiency between AI and human performances.

Example:

• Translating literary works (e.g., Shakespearean poetry) and comparing the translation quality produced by AI tools versus human translators.

Implementation Methods:

• Task setup and distribution.
• Comparative analysis and evaluation of outcomes.
• Summarizing findings in a comprehensive report (including performance comparisons and analysis of AI limitations and capabilities).

Learning Objectives:

• Provide students with a clear understanding of AI capabilities and limitations.
• Stimulate deeper reflections on practical scenarios for AI applications.

Activity 3: Interactive Group Discussions (Debating Ethical Issues in AI)

Activity Description:

• Students engage in structured debates around ethical and regulatory issues related to artificial intelligence.

Discussion Topics Include:

• Should artificial intelligence technology be fully regulated by the government, or is it better for companies to self-regulate?
• Will the widespread application of artificial intelligence technology lead to large-scale unemployment for the majority of people?

Implementation Methods:

• Pre-read relevant literature and materials.
• Clearly define positions and arguments within groups (pro vs. con).
• Conduct debates and instructor-led evaluations during class.

Learning Objectives:

• Develop critical thinking and public speaking skills.
• Encourage profound contemplation on ethical implications related to AI technologies.

Activity 4: Practical Project (Chatting with AI Tools and Presentation)
Activity Description:
• Students collaborate in small groups to explore and interact with artificial intelligence tools. Students will use existing AI platforms (such as ChatGPT, Google Teachable Machine, or other available tools) to engage with AI through conversations or image recognition experiments.
• The goal is to help students understand how AI behaves, what it can and cannot do, and reflect on its potential real-world applications.

Example:
• Use a conversational AI chatbot like ChatGPT to simulate a virtual “campus assistant” that answers common student questions (e.g., “Where is the library?”, “How can I join a club?”).
• Try out an AI image recognition tool to test how accurately it can identify objects, animals, or hand gestures, and discuss its limitations or errors.

Implementation Methods:
• Project Planning and Identification of Objectives:
  Students decide on a theme or purpose for their AI interaction project (e.g., exploring how well AI understands daily language or how reliable AI is in identifying objects).
  Each group sets a clear goal for what they want to learn or demonstrate.

• Exploration of AI Tools and Teamwork:
Students select one or more AI tools to use.
Each team member takes on a specific role (e.g., prompt designer, tester, presenter).
Teams interact with the AI tools, document the process, and analyze the outcomes (e.g., when the chatbot made mistakes or gave helpful answers).

• Presentation and Defense of Project Outcomes:
Each group presents their project to the class, showcasing their findings and reflecting on what surprised them, what worked well, and what challenges they encountered.
They will also answer questions from peers or teachers, encouraging critical thinking about AI’s capabilities and limitations.

Learning Objectives:
• Develop hands-on skills in using AI technologies and evaluating their behavior in realistic scenarios.
• Enhance students’ ability to work in teams, communicate findings clearly, and solve problems collaboratively.
• Foster awareness of how AI tools are used in everyday contexts and promote critical thinking about their ethical and practical implications.

Project Plan:

• Yixuan Lu: Big Idea & Learning Outcome(s) Part 1
• Minyuan Ye: Evidence of Learning & Reference Part 2
• Tianxiang Wang: Assessments Part 3
• Diyuxie: Learning Activities Part 4

References

• McCarthy, J. (2007). What is Artificial Intelligence? Stanford University.
• Piaget, J. (1970). Science of Education and the Psychology of the Child. Orion Press.
• Russell, S., & Norvig, P. (2021). Artificial Intelligence: A Modern Approach (4th ed.). Pearson.
• 1.Artificial Intelligence and the Future of Teaching and Learning
• This report from the U.S. Department of Education discusses the integration of AI in educational settings, emphasizing the importance of minimizing bias in AI systems, promoting fairness, and ensuring that AI tools are explainable and support educators’ professional judgment.
• U.S. Department of Education. (2023). Artificial Intelligence and the Future of Teaching and Learning. Retrieved from https://www.ed.gov/sites/ed/files/documents/ai-report/ai-report.pdf
• 2.A Scoping Review on How Generative Artificial Intelligence Transforms Assessment in Higher Education
• This scoping review investigates the transformative impact of generative AI on assessment practices in higher education, providing insights into the evolving landscape of AI applications in educational assessments.
• Zawacki-Richter, O., & Jung, I. (2023). A scoping review on how generative artificial intelligence transforms assessment in higher education. International Journal of Educational Technology in Higher Education, 20(1), 1-27. https://doi.org/10.1186/s41239-024-00468-z

1.Big Ideas and Learning Outcomes

Big Idea 1: How is Artificial Intelligence Changing Everyday Life?

• Smart Assistants & Language Models (e.g., Siri, ChatGPT): Help people access information, manage tasks, assist with creative writing, and support programming.
• Personalized Recommendation Systems (e.g., Netflix, YouTube, Spotify): Analyze user behavior through big data to improve content recommendation accuracy.
• Smart Homes & Automation (e.g., Robot Vacuums, Smart Locks): Enhance convenience and security in daily life.

Key Considerations:

How does AI improve human life through learning and data analysis? Could increasing reliance on AI bring new challenges?

Big Idea 2: The Role of AI in Key Industries

• Healthcare: AI-assisted diagnosis (e.g., IBM Watson), intelligent medical imaging analysis, and personalized treatment plans (e.g., genetic analysis).
• Education: AI-driven personalized learning systems (e.g., Duolingo, Socratic).
• Transportation: Self-driving cars (e.g., Tesla), smart traffic lights, and AI-optimized public transportation systems.

Key Considerations:

Can AI completely replace human roles in these fields? While improving efficiency, what ethical and social issues might AI introduce?

Learning Outcomes

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

• Understand the fundamental concepts and core technologies of AI (such as machine learning, neural networks, and natural language processing) and explain their applications in daily life.
• Analyze how AI impacts various fields, including healthcare, education, and transportation, and provide specific examples.
• Discuss the pros and cons of AI, including issues related to privacy, employment, and ethical issues, while developing critical thinking skills.
• Engage in innovative thinking by proposing an AI-based application concept and sharing their ideas in group discussions.

This learning resource will enhance the learning experience through interactive case studies, simulation exercises, and discussion activities, such as:

• Allowing learners to experience how AI recommendation systems adjust results based on data.
• Analyzing real-world cases (e.g., Tesla’s autonomous driving accidents) to discuss AI safety.

2.Evidence of Learning & Reference

Artificial intelligence (AI) is transforming daily life by enhancing automation, decision-making, and efficiency. It powers virtual assistants, smart homes, healthcare diagnostics, self-driving cars, and personalized recommendations. AI improves industries like finance, education, and entertainment through data analysis and predictive algorithms. While it boosts convenience and innovation, ethical concerns such as privacy, bias, and job displacement remain challenges. AI continues to evolve, shaping the future of human interactions and technology.

Evidence of Learning: Learning will be demonstrated through various forms of assessment and participation

• Perform tasks accurately: students will successfully use artificial intelligence tools such as chatbots or machine learning models in practical exercises.
• Use terminology correctly: learners will use ai-related vocabulary correctly in discussions, written assignments, and presentations.
• Critical analysis and applications: students will analyze case studies and provide strong supporting arguments for Ethics of artificial intelligence and social impact.
• Problem solving and innovation: Learners will demonstrate creativity and applied knowledge by proposing ai-driven solutions to industry-specific challenges.
• Collaboration and communication: participation in panel discussions, debates and presentations will demonstrate the ability to present and defend ideas based on research.

References:

1.Artificial Intelligence and the Future of Teaching and Learning

This report from the U.S. Department of Education discusses the integration of AI in educational settings, emphasizing the importance of minimizing bias in AI systems, promoting fairness, and ensuring that AI tools are explainable and support educators’ professional judgment.

U.S. Department of Education. (2023). Artificial Intelligence and the Future of Teaching and Learning. Retrieved from https://www.ed.gov/sites/ed/files/documents/ai-report/ai-report.pdf

2.A Scoping Review on How Generative Artificial Intelligence Transforms Assessment in Higher Education

This scoping review investigates the transformative impact of generative AI on assessment practices in higher education, providing insights into the evolving landscape of AI applications in educational assessments.

Zawacki-Richter, O., & Jung, I. (2023). A scoping review on how generative artificial intelligence transforms assessment in higher education. International Journal of Educational Technology in Higher Education, 20(1), 1-27. https://doi.org/10.1186/s41239-024-00468-z

3. Assessments （misunderstanding and mistakes）

With the continuous development of science and technology, artificial intelligence(AI) has penetrated into our daily lives. From mobile assistants to voice control to intelligent driving. They are around us and affect our lives. However, many people still have some misunderstandings about artificial intelligence and often make some mistakes.

• Misunderstanding
• AI is completely objective: AI’s decisions rely on training data. If the person who sets the data is biased, then the data will be biased, and the output of AI may also be biased. Therefore, AI is not absolutely objective as people usually understand. This is very important to understand, because many people will be misled by AI’s conclusions.
• AI will replace all human jobs: Although AI may replace some repetitive and simple jobs, it is more of a tool to assist humans and help them improve their efficiency, rather than completely replacing human jobs. Many movies are about AI developing emotions and attacking humans to rule the world. This has caused people to misunderstand AI, that it can only simulate human behavior and has no real consciousness and emotions. Currently, AI is in the stage of weak artificial intelligence and does not have autonomous consciousness, so it will not pose a threat to us like in the movies.

• Mistake

Over-reliance on AI: Although AI can provide convenience and is very accurate, over-reliance on it may cause humans to lose their ability to think and judge independently. We must know that AI is also created by humans, but if people rely on AI instead of thinking and learning independently. AI will not be able to be improved and our own technology and life will not develop and innovate.

AI is changing our lives, but we need to view its capabilities and limitations rationally. By correctly understanding AI and avoiding misunderstandings and mistakes, we can better utilize this technology to promote social progress and development.

4. Learning Activities (Learning Activity Design)

Reasons for Developing Learning Resources

Artificial intelligence is changing our lives, and it involves a wide range of areas that only humans can imagine. There is nothing that artificial intelligence cannot cover. Learning AI can help us better understand and adapt to this rapidly developing world.

The main reasons include:

AI is everywhere, affecting life 🏠📱

AI exists in everyday tools such as intelligent assistants (Siri, ChatGPT), recommendation systems (Netflix, YouTube), and smart homes (robotic vacuum cleaners, smart locks).

Understanding AI can better utilize these technologies and improve efficiency in daily life.

AI provides more career opportunities 💼📊

Many industries, such as healthcare, factories, restaurants, and transportation, are using artificial intelligence to improve efficiency and create revenue.

Understanding artificial intelligence can help with future career development and make oneself more competitive.

AI can help solve real-world problems 🌍🔬

AI can be used for medical diagnosis, intelligent education, and self-driving technology to help society solve complex problems.

Learning AI can explore how to use technology to create a better world.

Case Study Analysis

Activity content: Learners analyze the operation of AI recommendation systems (such as YouTube or Netflix) and explore their impact on user behavior.

Objective: To understand how AI optimizes user experience through data analysis and discuss data privacy issues.

Simulation Exercise

Activity content: Conduct task testing using AI tools such as ChatGPT or Google Translate, and compare the performance of AI and humans in understanding complex texts or creative writing.

Objective: To explore the capabilities and limitations of AI and understand its applications in the work environment.

Group Discussion

Discussion topic:

Will AI lead to mass unemployment?

How should we regulate AI to ensure fairness?

What is the best application of AI in education?

Objective: To cultivate critical thinking and stimulate in-depth reflection on the ethical and social impact of AI.          

Ethics&AI Governance for the Future of AI

However, with advancements in technology and AIs, it is clear there is a need for stricter regulation and ethical rules to be enforced concerning the progress of its development.

AI Regulation: The EU’s Artificial Intelligence Act seeks to cover the gap in the legal frameworks that deal with AI in an attempt to control its usage and prevent misuse.

Deepfakes and false information: AI generated false content may affect elections, business competition, and even personal reputation.

AI and Privacy Concerns: How do companies like Google and Facebook use AI to process user data? Do people have the right to demand that AI not store their information?

These issues will determine the future direction of AI development and are of particular interest to me.  

Project Plan:

• Yixuan Lu: Big Idea & Learning Outcome(s) Part 1
• Minyuan Ye: Evidence of Learning & Reference Part 2
• Tianxiang Wang: Assessments Part 3
• Diyuxie: Learning Activities Part 4

Applying Constructivism to Adult Professional Development: A Personal Approach

Designing a learning environment rooted in constructivism requires more than disseminating information—it demands fostering active engagement. As someone developing online courses for adult professionals, I aim to create experiences where learners construct knowledge through meaningful interaction and reflection.

1. Aligning Outcomes with Active Learning
For a course on leadership, instead of lecturing on theories, I’d set outcomes like “Apply adaptive leadership strategies in workplace scenarios.” Activities might involve collaborative case studies where learners navigate real-world challenges, followed by peer discussions to dissect their choices. Assessments would shift from quizzes to project portfolios, where learners document iterative problem-solving processes. This mirrors constructive alignment, ensuring activities and evaluations directly support skill application.

2. Embracing Social Learning
Constructivism thrives on social interaction. I’d integrate discussion forums where learners share workplace experiences and critique solutions. In a project management course, teams could simulate managing a virtual project, encountering “roadblocks” (e.g., budget cuts) requiring adaptive thinking. Peer feedback sessions would encourage reflection, helping learners refine their mental models.

3. Challenges and Adaptations
Balancing structure with exploration is tricky. Clear rubrics outlining expectations for critical thinking (e.g., “Demonstrates analysis of stakeholder impact”) can guide without stifling creativity. Additionally, fostering a safe environment for experimentation is key—adults may resist ambiguity, so framing mistakes as learning opportunities is essential.

4. Reflection as a Tool
Journals or video diaries could prompt learners to articulate how new strategies intersect with their existing practices. For instance, after a module on conflict resolution, learners might reflect on adapting techniques to their team dynamics.

By prioritizing active participation, social discourse, and reflection, I aim to move beyond passive consumption, empowering professionals to build adaptable, personalized expertise. Constructivism isn’t just theory—it’s a pathway to lifelong, self-driven growth.

Learning theories like behaviorism, cognitivism, and constructivism are all different in their approaches towards education, and reflecting on them has helped me understand how to learn and teach better in my own context.

For example, in my own learning, I’ve come to understand that behaviorism works best for me at the most basic levels, where It’s primary focus is on the repetition and reinforcement of a task. When I was new to a language, learning apps like Duolingo had gamified rewards that motivated me to memorize vocabulary, but the same method isn’t effective for conversation. For more complex, skill-elevating tasks like engaging in conversations, I now practice cognitivist and constructivist approaches.

A concept that I was able to apply to my teaching style is cognitivism’s focus on the value of information organization. I had a friend who was preparing for a professional certification and so, to aid him, I used detailed structured outlines, flowcharts, and visual aids. By addressing the difficult topics in parts, I was not only able to help him understand everything effectively, but it also improved my skills on how to articulate my ideas clearly.

The most transformative approach for me has been constructivism, especially while working on group projects. When I was leading a team at work, I was assigned a project to develop a new community initiative and I started with encouraging brainstorming sessions and practical experimentation, followed by discussions on what everyone contributed and how their ideas connected to the larger goal. This approach not only allowed everyone to feel valued and involved but also fostered creativity and deeper understanding.

If I were designing a lesson on climate change in my context, I’d blend these approaches. I’d start with a behaviorist method like short quizzes to reinforce foundational knowledge, use cognitivist tools like concept maps to explain climate systems, and finish with constructivist projects where participants create local solutions. In my own teaching and learning, I find the best outcomes come from tailoring methods to the situation. By combining these theories, I can create engaging and effective learning experiences.