How to Provide Effective Feedback For Learning
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How to Provide Effective Feedback For Learning
Feedback is one of the most powerful tools educators have to enhance student learning. When done effectively, it not only clarifies what students are doing right and wrong but also motivates them to improve and grow.
However, providing meaningful feedback requires a thoughtful approach that balances encouragement, clarity, and sensitivity. Here’s a guide to delivering feedback that truly supports learning:
1. Focus on What’s Right and What’s Wrong
Effective feedback involves highlighting both the strengths and weaknesses in a student’s work. Start by acknowledging what they’ve done correctly—this reinforces positive behaviors and builds confidence. Then, gently address areas for improvement, ensuring your feedback is specific and actionable.
Example: Instead of saying, “Your essay needs work,” try, “Your introduction is clear and engaging, which is great! However, the argument in the second paragraph could be stronger if you include more evidence to support your point.” By emphasizing correct actions and providing clear examples, students can better understand how to improve.
2. Provide Immediate Feedback
Timing is critical when it comes to feedback. Immediate feedback, given right after a student demonstrates their learning, leads to better retention and more positive responses. When students receive feedback promptly, they can easily connect it to their actions and make adjustments while the material is still fresh in their minds.
Example: After a class presentation, offer quick verbal feedback on what went well and what could be improved. This helps students reflect on their performance while it’s still relevant. Delayed feedback, on the other hand, can create a disconnect between the feedback and the action, reducing its effectiveness.
3. Tailor Feedback to Individual Needs
Every student is unique, and a one-size-fits-all approach to feedback rarely works. In diverse classrooms, some students may need encouragement to push their boundaries, while others may require gentle handling to protect their self-esteem. Understanding each student’s personality, learning style, and emotional needs is key to providing feedback that resonates.
For confident students: Challenge them with constructive criticism and higher expectations.
For hesitant students: Focus on their progress and offer encouragement to build their confidence.
4. Balance Encouragement and Sensitivity
Feedback should inspire growth, not discourage effort. Striking the right balance between encouragement and constructive criticism is essential.
Encouragement: Celebrate successes, no matter how small. Phrases like “You’re on the right track!” or “I can see how much effort you put into this” can motivate students to keep trying.
Sensitivity: Be mindful of how you deliver criticism. Frame it in a way that focuses on improvement rather than failure. For example, instead of saying, “This is wrong,” try, “Let’s see how we can make this even better.”
Providing effective feedback is both an art and a science. It requires clarity, timeliness, and a deep understanding of each student’s needs. By focusing on what students are doing right, addressing areas for improvement with sensitivity, and tailoring feedback to individual learners, educators can create a supportive environment where students feel empowered to grow.
Pregrade AI helps teachers give timely, personalized feedback to students for quick and accurate assessments. This enhances the learning experience and allows educators to effectively address individual student needs. Check out Pregrade now!
Unpacking the Help-Seeking Process
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Unpacking the Help-Seeking Process: ChatGPT vs. Human Experts
With AI tools like ChatGPT popping up, things are changing in education. Students who used to depend on teachers and professors are now getting help from AI.
A recent study titled “Unpacking help-seeking process through multimodal learning analytics: A comparative study of ChatGPT vs Human expert” (Unpacking help-seeking process through multimodal learning analytics: A comparative study of ChatGPT vs Human expert – ScienceDirect) explored how learners interact with AI and human experts when seeking help. The study involved 38 university students divided into two groups: one seeking help from ChatGPT and the other from an experienced teacher. The researchers used multimodal data, including trace data, eye-tracking data, and conversational data, to analyze the help-seeking processes.
Here are some of the key findings from the study:
- Non-linear vs. Linear Processes: The study found that learners who asked AI for help didn’t follow the usual step-by-step process and often skipped the evaluation stages. On the other hand, those who turned to human experts for help followed a more straightforward process, which matches up with the traditional theories about how people seek help.
- Types of Questions and Activities: Learners who chatted with ChatGPT usually asked practical questions and looked for specific help. On the other hand, learners who asked human experts for help were more likely to think about their own thinking and assess the feedback they got.
- Social Pressure and Metacognitive Off-loading: Learners were more likely to ask for help when they weren’t feeling social pressure. This was especially true when they were interacting with AI, since they felt more comfortable asking questions without worrying about being judged.
- Scaffolding and Support: The research highlighted that we need scaffolding to learn better with AI. With effective scaffolding, learners can find help faster and improve their metacognitive skills.
AI is great for answering FAQs quickly, which means less waiting around. But for tricky or sensitive issues, you need a human touch – someone who can really understand and empathize.
So, the best approach is to combine AI and human support for a perfect balance of efficiency and empathy.
What is Synthetic Sycophancy and how does it hinder learning?
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What Is Synthetic Sycophancy and How Does It Hinder Learning?
Ever asked your chatbot a question you knew the answer to, deliberately argued your ‘wrong’ answer was ‘right’, and got a ‘you’re right!’ in return instead of a headstrong ‘No?’
AI models have a tendency to align with users' incorrect beliefs or statements, a phenomenon referred to as synthetic sycophancy.
This behavior arises from the AI’s goal to maintain user satisfaction. However, it can be detrimental, particularly in educational contexts, as it can reinforce misconceptions instead of rectifying them. What are some key patterns of sycophantic behavior?
1. Feedback Sycophancy: AI systems may evaluate the same output differently depending on how the user feels about it. For instance, a user who expresses pride in their answer to a math problem may receive positive feedback from an AI, even if the answer is wrong.
2. Answer Sycophancy: The AI would rather agree with you than be right, which makes it a lot less accurate. This happens because AI models change their initially correct answers when you tell them you’re unsure.
3. Mimicry Sycophancy: Instead of correcting user errors, the AI may adopt and expand upon incorrect information. For example, if a user incorrectly attributes a poem to the wrong author, an AI system used for literary analysis may accept this error and build upon it.
The way AI models are trained is closely linked to the behavior of synthetic sycophancy. Analysis shows that AI models are frequently trained to prioritize user satisfaction over accuracy, as “matching user beliefs” is a strong predictor of positive human ratings.
However, in education, this can pose significant risks. Effective education often requires challenging existing beliefs, but AI systems that prioritize agreement can reinforce misconceptions. This creates a dynamic where AI tools intended to support learning may instead hinder it.
To address the issue of AI-generated flattery, we need to change the technology and the culture surrounding it. AI systems should be designed to prioritize truthfulness while remaining helpful. We also need clear rules for using AI tools in education. Both educators and students need to understand the limitations and biases of these tools so that they can be used to support learning and discovering the truth.
Is AI a foe or friend to critical thinking? How can educators combat the potentially negative effects of AI on intellectual growth?
How has AI changed impact assessments?
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How has AI Changed Impact Assessments?
Learn more through our online program ‘Co-Design Engaging Courses with Generative AI,’ here.
In an era where technology is reshaping every facet of our lives, education is no exception.
Recognizing the potential of AI to revolutionize online learning, we at Pregrade have teamed up with esteemed partners—Learnmonade, Star-Kin, Actuator Media, UNESCO-ICHEI, and the IIOE Global Webinar—to co-create a groundbreaking course designed for higher education professionals. This initiative is not just about integrating AI; it’s about transforming the way educators engage, assess, and empower their students.
This course provides educators with the tools to harness generative AI, enabling them to craft engaging and interactive lecture experiences. Gone are the days of monotonous lectures. With AI, educators can create dynamic content that captivates students’ attention and fosters a deeper understanding of the material. Imagine virtual classrooms where AI-driven simulations and personalized learning paths cater to each student’s unique needs, making learning not just effective but also enjoyable.
Revolutionizing Assessment
Assessment methods have long been a challenge in online education. The rise of AI presents both a hurdle and an opportunity. This course guides educators on how to adapt their assessment techniques in an era where students have access to AI tools. By incorporating AI into their assessment strategies, educators can ensure academic integrity while also embracing the benefits of automated grading and feedback systems, which can save time and provide more detailed insights into student performance.
Reducing Workload with AI Tools
One of the significant advantages of AI in education is its ability to reduce the administrative burden on educators. Through the effective application of AI tools, such as Pregrade, educators can automate routine tasks, streamline administrative processes, and focus more on what truly matters—teaching and mentoring their students. This not only enhances productivity but also contributes to a healthier work-life balance for educators.
Click on the link below to try out our globally available online program now.
Navigating the Evolution of AI
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Navigating the Evolution of AI
As we stand at the crossroads of AI’s trajectory, let’s recognize that both our personal growth and AI’s evolution share common threads. So, here are some insights between my own development and Gen AI’s near term trajectory.
A Reflection from Joon Nak Choi
Just as we’ve learned to channel our intelligence more effectively, AI will also find its purpose, and we will learn to adapt.
In my 20’s my IQ was off the charts, but I didn’t really have the wisdom to use it correctly. I made poor decisions after poor decision and made poor use of my potential. As I near my 50’s my IQ is probably a bit more limited, but my decision quality is better. I am making much better use of the intelligence that I do have. Gen AI will be the same way. The performance of these foundational models isn’t going to grow rapidly. However, we are going to start learning to make better use of it.
The rapid advancements in Gen AI models, like GPT-4, have been impressive, but the pace of performance improvements is expected to stabilize. This means that while we might not see dramatic leaps in the core capabilities of these models, they will continue to evolve steadily. The real game-changer will be how we learn to use these models more effectively. This involves integrating Gen AI into various workflows, enhancing productivity, and expanding the range of tasks it can perform. For example, businesses are already leveraging GenAI to automate customer service, generate content, and even assist in complex decision-making processes.
In essence, while the foundational technology may not see exponential growth, out ability to harness its potential will significantly improve, leading to more innovative and efficient applications across different industries.
With Pregrade however, we start with the intelligence, and are adding more wisdom to the AI as we go along.
We utilise advanced AI models that already possess significant capabilities in language understanding, pattern recognition, and data processing. Over time, these models are refined and enriched with domain-specific knowledge, ethical considerations, and contextual awareness. This process involves continous learning from real-world appliations, use interactions, and feedback loops.
Pregrade’s AI systems are designed to adapt to evolve based on new information and changing environments. This user-centric approach helps in building trust and ensuring the AI’s outputs are meaningful and beneficial.