We’re coming up on a ton of political campaigns, and it was those that spurred me to take a look again at SIFT, which others have mentioned, but I had only briefly explored. After studying up on it, I realized how valuable it can be for the classroom as a tool for critical thinking.
Photo by TUAN ANH TRAN on Unsplash
But I also would want to combine it with something Melanie Trecek-King (ThinkingIsPower.com called, Systematic Disconfirmation.
The process of systematic disconfirmation involves actively seeking out and considering evidence or cases that contradict or challenge existing beliefs, theories, or findings. Disconfirmation bias, for example, refers to the tendency of individuals to more readily accept information that supports their pre-existing beliefs and dismiss information that contradicts them. This bias can lead to a lack of fair evaluation of arguments that deviate from one’s own beliefs, hindering true collaboration and compromise. Disconfirmation bias is linked to cognitive dissonance, where conflicting thoughts or information can lead to discomfort or mental distress, prompting individuals to dismiss disconfirming evidence to maintain their beliefs or identity (source).
I can definitely see a lot of that when holding up what I believe or hold true, only to discover it’s not. Melanie mentions the terms in passing in one of her published writings, and its evident its not a new term. That said, I had never heard of it described in that way. Learning about it is great, though. How do you go about systematically disconfirming what hold as gospel or think is true?
A Systematic Disconfirmation Process
One process suggested is this one:
- Identify: Determine the existing belief or theory that needs to be tested.
- Hypothesize: Formulate expectations based on the identified belief or theory.
- Collect: Gather data or evidence relevant to the belief or theory.
- Compare: Contrast the collected evidence against the initial expectations.
- Disconfirm: Identify evidence that contradicts or challenges the initial belief or theory.
- Analyze: Examine the disconfirming evidence to understand its implications.
- Adjust: Modify the original belief or theory based on the analysis of disconfirming evidence.
- Repeat: Continue the process iteratively to refine the belief or theory further.
However, a simplification might be helpful. I mean, that’s pretty simple, but if teaching it to middle school students, simpler language may be called for, such as:
- Find: Look for what you think is true.
- Guess: Make a guess about what you expect based on what you think.
- Get: Collect information or facts related to your guess.
- Check: Look at the information to see if it matches your guess.
- Spot: Notice any information that doesn’t match what you thought.
- Think: Think about what the mismatching information means.
- Change: Make changes to your original thought based on new insights.
- Go again: Keep doing this process to refine your thoughts.
You could even shorten or collapse the steps further, although I’m not sure how useful that is:
Step | Description | Example: Plant Growth |
---|---|---|
Hypothesize | Form an idea or belief based on what you think is true. | Students think plants need sunlight to grow. |
Test | Collect and compare information to see if it supports or contradicts your idea. | Grow two plants, one in sunlight and one in darkness, and observe the differences. |
Revise | Based on the test results, adjust your idea or belief. | If the plant in darkness doesn’t grow well, conclude that sunlight is important for plant growth and update the belief. |
Digging Deeper into Systematic Disconfirmation with an Example
In simple words, systematic disconfirmation means “actively testing and challenging existing assumptions and theories” (Source: Perplexity.ai gathered information). An example of systematic disconfirmation with a middle school science topic of “force and motion” looks like this according to AI:
Step | Description | Example: Force and Motion |
---|---|---|
Find | Look for what you think is true. | Students believe heavier objects fall faster than lighter ones. |
Guess | Make a guess about what you expect based on what you think. | Predict that when dropped from the same height, a textbook will hit the ground before a sheet of paper. |
Get | Collect information or facts related to your guess. | Perform an experiment by dropping objects of different masses from the same height. |
Check | Look at the information to see if it matches your guess. | Observe that all objects hit the ground at the same time when air resistance is negligible. |
Spot | Notice any information that doesn’t match what you thought. | Notice that the sheet of paper and the textbook hit the ground simultaneously in a vacuum. |
Think | Think about what the mismatching information means. | Conclude that mass does not affect the falling speed in the absence of air resistance. |
Change | Make changes to your original thought based on new insights. | Update the belief to understand that gravity accelerates all objects equally when air resistance is not a factor. |
Go again | Keep doing this process to refine your thoughts. | Test with different shapes and sizes of objects to further explore the concept of air resistance and motion. |
Aside: What a time-saver to have an AI (learn more) put that table together. Just doing that would have been the whole time I have to write a blog entry.
Here’s what the 3-step version would look like: Using the 3-step process of systematic disconfirmation to analyze the belief that “students believe heavier objects fall faster than lighter ones,” we can structure the analysis as follows:
Step | Description | Example: Heavier vs. Lighter Objects Falling |
---|---|---|
Hypothesize | Form an idea or belief based on what you think is true. | Students think heavier objects, like a textbook, fall faster than lighter ones, like a feather. |
Test | Collect and compare information to see if it supports or contradicts your idea. | Conduct an experiment dropping two objects of different masses but similar shapes from the same height in a vacuum to eliminate air resistance. Reference[2] and[19] provide insights into experiments and theoretical explanations showing that without air resistance, all objects fall at the same rate due to gravity. |
Revise | Based on the test results, adjust your idea or belief. | If the experiment shows that both objects hit the ground at the same time, conclude that the initial belief was incorrect. Update the belief to understand that in the absence of air resistance, all objects fall at the same rate, regardless of their mass, as explained by the universal law of gravitation[12][19]. |
It’s a process worth reflecting about when you encounter anything, no matter which version you use like the 8 step or 3 step approach.
SIFT LESSON PLAN Blog Entry
Be sure to check out my latest blog effort:
Discover the SIFT lesson plan— designed to equip learners with critical skills for navigating media overwhelm. Explore this practical guide.
For fun, here’s the 3-step process of systematic disconfirmation applied to the same bit of DOGOnews in the blog entry:
Applying the 3-step process of systematic disconfirmation to the project of completing Beethoven’s unfinished 10th Symphony using artificial intelligence (AI) can be outlined as follows:
Step | Description | Example: Completing Beethoven’s 10th Symphony |
---|---|---|
Hypothesize | Form an idea or belief based on what you think is true. | The team believes AI can successfully complete Beethoven’s unfinished 10th Symphony in a way that aligns with his style and intentions. |
Test | Collect and compare information to see if it supports or contradicts your idea. | AI software is trained on Beethoven’s existing works and the unfinished sketches of the 10th Symphony. The AI then generates music based on this training, which is reviewed by music experts to determine if it aligns with Beethoven’s style. |
Revise | Based on the test results, adjust your idea or belief. | If the AI-generated music is deemed consistent with Beethoven’s style and intentions by experts, the hypothesis is supported. If not, the approach or AI model may need to be adjusted to better capture Beethoven’s musical language. |
Quite fun.