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Related Concept Videos

Inductive Reasoning00:59

Inductive Reasoning

Inductive reasoning is a form of logical thinking that uses related observations to arrive at a general conclusion. It is uncertain and operates in degrees to which the conclusions are credible. As such, inductive arguments can be weak or strong, rather than valid or invalid, and conclusions can be used to formulate testable, falsifiable hypotheses.
Inductive reasoning is common in descriptive science. A life scientist makes observations and records them. This data can be qualitative or...
Data Validation01:03

Data Validation

Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
Nursing assessment guides are generally based on holistic models rather than medical...
Confirmation Biases01:31

Confirmation Biases

The confirmation bias is the tendency to focus on information that confirms our existing beliefs and ignore information that is inconsistent with our expectations. For example, if you think that your professor is not very nice, you notice all of the instances of rude behavior exhibited by the professor while ignoring the countless pleasant interactions he is involved in on a daily basis. Have you ever fallen prey to the confirmation bias, either as the source or target of such bias?
Purposive Learning01:22

Purposive Learning

E. C. Tolman emphasized the purposiveness of behavior — the idea that much of our behavior is goal-directed. For instance, employees who aim for a promotion work diligently to meet their targets. Tolman argued that when classical conditioning and operant conditioning occur, the organism acquires certain expectations. In classical conditioning, a child might fear a dog because they expect it to bite. In operant conditioning, a person might consistently work overtime because they expect a bonus...
Deductive Reasoning01:16

Deductive Reasoning

Deductive reasoning, or deduction, is the type of logic used in hypothesis-based science. In deductive reasoning, the pattern of thinking moves in the opposite direction as compared to inductive reasoning, which means that it uses a general principle or law to predict specific results. From those general principles, a scientist can deduce and predict the specific results that would be valid as long as the general principles are valid.
For example, a researcher can deduce specific predictions...
Cognitive Learning01:21

Cognitive Learning

Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...

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Related Experiment Videos

An inductive learning intervention to improve news veracity discernment.

Ariana Modirrousta-Galian1, Tina Seabrooke2, Yaniv Hanoch3

  • 1Department of Experimental Psychology, University College London.

Journal of Experimental Psychology. Applied
|May 11, 2026
PubMed
Summary

Inductive learning (IL) training improved distinguishing true from false news. However, easy-to-hard training with a hard-to-easy approach was most effective for enhancing news veracity discernment.

Related Experiment Videos

Area of Science:

  • Cognitive Psychology
  • Media Psychology
  • Educational Psychology

Background:

  • Distinguishing true from false news is a critical skill in the digital age.
  • Inductive learning (IL) offers a potential method for improving news veracity discernment.
  • Previous research has not fully explored the optimal structure of IL interventions for this task.

Purpose of the Study:

  • To investigate the effectiveness of an inductive learning (IL) intervention on improving participants' ability to discern news veracity.
  • To examine the impact of training structure (easy-to-hard vs. hard-to-easy) and gamification on IL intervention efficacy.
  • To provide robust evidence for an effective IL strategy for enhancing news literacy.

Main Methods:

  • Three preregistered experiments (N=1,135) were conducted.
  • Participants engaged in inductive learning (IL) by classifying news headlines as true or false with feedback.
  • Interventions varied in training progression (easy-to-hard vs. hard-to-easy) and included gamified elements (badges).

Main Results:

  • Experiment 1 showed a significant but anecdotally supported improvement in news veracity discernment.
  • Experiment 2, with gamification and easy-to-hard training, unexpectedly showed a decreased effect, possibly due to performance awareness.
  • Experiment 3, using hard-to-easy training, demonstrated a significant improvement in news veracity discernment with strong Bayesian evidence.

Conclusions:

  • Inductive learning (IL) can effectively enhance news veracity discernment.
  • A hard-to-easy training structure is more effective than an easy-to-hard structure, especially when gamified.
  • Optimizing IL intervention design is crucial for improving digital news literacy and combating misinformation.