Learning about causal relations that change over time: primacy and recency over long timeframes in causal judgments...

Area of Science:

• Cognitive Psychology
• Causal Learning

Background:

• Adapting to environmental changes requires detecting shifts in cause-effect relationships.
• Understanding how humans track these dynamic contingencies is fundamental to causal learning theories.

Purpose of the Study:

• To investigate participants' ability to detect changes in cause-effect contingency over time.
• To compare causal learning in a rapid, artificial timeframe versus a prolonged, realistic timeframe.
• To examine memory recall and judgment biases (primacy/recency effects) in different learning durations.

Main Methods:

• An experiment comparing rapid, short-term learning with a 24-day mobile phone-based long-term learning procedure.
• Participants learned about cause-effect relationships that strengthened or weakened over time.
• Analysis of contingency detection, summary judgments, and episodic memory recall.

Main Results:

• Participants successfully detected changes in contingency across both short and long timeframes, performing better in the short-term task.
• A recency effect was observed in summary judgments during long-term learning, but not in the short-term task.
• Episodic memory recall was generally poor but showed primacy and recency effects in the short-term, which were reduced in the long-term.

Conclusions:

• Humans can automatically detect and represent changes in causal contingencies, even over extended periods.
• Existing causal learning theories may not fully account for the dynamic tracking of contingency changes.
• The findings suggest distinct learning and memory processes operate across different timescales.