Learning
Overview
Learning (學習) is the process by which relatively lasting changes occur in knowledge, skills, attitudes, and behavioral patterns through experience, training, observation, and interaction. Beyond simple memorization or information storage, it is understood as an active process of construction in which new information is connected to existing cognitive structures and used for problem solving. It is a core concept jointly addressed by education, psychology, cognitive science, and neuroscience, and today it is widely used not only in the context of human learning but also in the context of machine learning.
Main Content
Definition and Scope
Learning is defined by three main conditions. First, it must be the result of experience or practice. Second, there must be a change in behavior or cognitive structure. Third, that change must not be temporary and must persist to some degree. Therefore, temporary declines in performance caused by fatigue or drugs are not regarded as learning. Learning encompasses not only formal education (school curricula) but also non-formal education (vocational training, lifelong education) and informal learning (incidental acquisition in everyday life).
The Flow of Learning Theories
- Behaviorism: Explains learning as the connection of stimulus-response-reinforcement, as in Pavlov's classical conditioning and Skinner's operant conditioning. It highlighted the importance of clear goals, immediate feedback, and repetitive training.
- Cognitivism: Views learning as an information-processing process. Piaget emphasized stages of cognitive development through assimilation and accommodation, while Vygotsky emphasized social interaction and the Zone of Proximal Development (ZPD).
- Constructivism: Holds that learners actively construct meaning. Problem-based learning (PBL), project-based learning, and inquiry-based learning were derived from this.
- Social learning theory: Bandura held that learning occurs through observation, modeling, and vicarious reinforcement.
- Experiential learning: Kolb proposed a cycle of concrete experience → reflective observation → abstract conceptualization → active experimentation.
- Self-regulated learning: Emphasizes the learner's ability to control the learning process on their own through goal setting, self-monitoring, and self-evaluation.
Cognitive and Neuroscientific Foundations
Neuroplasticity is the biological foundation of learning. Repeated use strengthens synaptic connections (long-term potentiation, LTP), and the hippocampus plays a key role in the formation and consolidation of new factual memories. Because memory reorganization and consolidation occur during sleep, sufficient sleep directly affects learning efficiency. Ebbinghaus's forgetting curve shows that memory declines rapidly over time, which supports the need for spaced review. Since the capacity of working memory is limited, instructional design that chunks information and manages cognitive load is important.
Types of Learning
- Concept learning: Forms concepts through categories, definitions, and examples.
- Procedural learning: Acquires step-by-step skills and algorithms.
- Motor skill learning: Characterized by automatization through repeated practice.
- Affective learning: Includes changes in values, attitudes, motivation, and self-efficacy.
- Metacognitive learning: The ability to monitor one's own state of understanding and adjust strategies.
- Transfer: The ability to apply what has been learned to new situations, regarded as the ultimate goal of learning.
Effective Learning Strategies
The representative strategies supported by cognitive psychology research are as follows.
1. Retrieval Practice: Rather than rereading the textbook, use the testing effect by asking oneself questions and recalling answers.
2. Spacing: Rather than cramming, repeat with time intervals.
3. Interleaving: Increase discrimination by mixing similar but different types of problems.
4. Elaboration and self-explanation: Expand meaning by explaining to oneself why something is the case and creating examples.
5. Dual coding: Use multiple representations together, such as text, pictures, and diagrams.
6. Pre-testing: Attempting before learning and recognizing incorrect answers promotes subsequent learning.
7. Metacognitive monitoring and rest: Periodically check comprehension and arrange cognitive rest.
Assessment and Feedback
Learning cannot be separated from assessment. Formative assessment that promotes learning provides specific and timely feedback during the process. Rubric-based assessment, peer assessment, and self-assessment help learners internalize the criteria. Feedback is more effective when it focuses on "what and how to improve next" rather than on result scores.
Latest Trends
The biggest change in the field of learning in 2024–2025 is the everyday adoption of generative AI. As conversational AI tutors provide explanations and immediate feedback tailored to individual levels, the teacher's role is shifting from information transmitter to learning designer and coach. Adaptive learning platforms and learning analytics diagnose weak points based on learning logs and personalize pathways. At the same time, issues such as AI usage ethics, plagiarism and copyright, learner data privacy, and the digital divide have emerged as major concerns. In educational settings, AI literacy has become a new basic competency, and in companies and universities, adult learning pathways such as reskilling, micro-credentials, and lifelong learning accounts are spreading. In addition, there is a trend emphasizing instructional design based on Learning Science, hybrid and micro-learning, and customized support that considers neurodiversity.
Related Topics
- [[Education]]
- [[Cognitive Science]]
- [[Memory]]
- [[Metacognition]]
- [[Self-Directed Learning]]
- [[Machine Learning]]