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Related Concept Videos

Hindsight Biases01:12

Hindsight Biases

Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Can you relate this to the phrase "Hindsight is 20/20" now?
Accuracy and Errors in Hypothesis Testing01:13

Accuracy and Errors in Hypothesis Testing

Hypothesis testing is a fundamental statistical tool that begins with the assumption that the null hypothesis H0 is true. During this process, two types of errors can occur: Type I and Type II. A Type I error refers to the incorrect rejection of a true null hypothesis, while a Type II error involves the failure to reject a false null hypothesis.
In hypothesis testing, the probability of making a Type I error, denoted as α, is commonly set at 0.05. This significance level indicates a 5% chance...
The Availability Heuristic01:08

The Availability Heuristic

A heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. Different types of heuristics are used in different types of situations, and the impulse to use a heuristic occurs when one of five conditions is met (Pratkanis, 1989):
Accuracy, limits, and approximation01:28

Accuracy, limits, and approximation

Accuracy, limits, and approximations are common in many fields, especially in engineering calculations. These concepts are imperative for ensuring that a given value is as close as possible to its true value.
Accuracy is defined as the closeness of the measured value to the true or actual value. In engineering mechanics, repeated measurements are taken during theoretical or experimental analyses to ensure that the result is precise and accurate.
The accuracy of any solution is based on the...
Propagation of Uncertainty from Systematic Error01:10

Propagation of Uncertainty from Systematic Error

The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this particular...
Fundamental Attribution Error01:14

Fundamental Attribution Error

According to some social psychologists, people tend to overemphasize internal factors as explanations—or attributions—for the behavior of other people. They tend to assume that the behavior of another person is a trait of that person, and to underestimate the power of the situation on the behavior of others. They tend to fail to recognize when the behavior of another is due to situational variables, and thus to the person’s state. This erroneous assumption is called the fundamental attribution...

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Related Experiment Video

Updated: Jun 13, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

Usable knowledge, hazardous ignorance - beyond the percentage correct score.

Valerie Dory1, Jan Degryse, Ann Roex

  • 1Centre Academique de Medecine Generale, Université Catholique de Louvain, Brussels, Belgium. valerie.dory@uclouvain.be

Medical Teacher
|April 29, 2010
PubMed
Summary

Medical trainees demonstrate significant hazardous ignorance, with a sixth of their unknown information posing risks. Confidence marking can improve medical education assessments by identifying knowledge gaps and uncertainties.

Related Experiment Videos

Last Updated: Jun 13, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

Area of Science:

  • Medical Education
  • Metacognition
  • Health Professions Education

Background:

  • Metacognitive ability in medical students remains under-explored.
  • Understanding student certainty is crucial for effective learning.

Purpose of the Study:

  • To investigate medical students' knowledge certainty and ignorance using confidence marking.
  • To quantify usable knowledge and hazardous ignorance among trainees.

Main Methods:

  • 127 general practice trainees completed a multiple-choice question (MCQ) test with confidence judgments for each answer.
  • Calculated usable knowledge and hazardous ignorance based on certainty levels.
  • Analyzed results by MCQ score, training year, and gender.

Main Results:

  • Group-level analysis showed 21.13% usable knowledge and 5.21% hazardous ignorance.
  • 36.57% of knowledge was partial, and 14.32% of ignorance was hazardous.
  • Men exhibited higher levels of hazardous ignorance; no significant differences were found based on MCQ score or training year.

Conclusions:

  • A substantial portion of trainees' knowledge is partial, and a significant fraction of their ignorance is hazardous.
  • Confidence marking offers a valuable tool for formative assessment in medical education.
  • The method holds potential for integration into summative assessment strategies.