Novice

A novice is someone who is just beginning to learn something new. This person has little or no experience and often needs clear, step-by-step instructions to complete a task.[1] For example, a student learning a new language may have to memorize words and repeat phrases before understanding how sentences work. A medical student learning to sew a wound (called suturing) must carefully follow each step because they do not yet know how to do it smoothly or automatically.[2] In education and psychology, being a novice means you are at the very first level of learning. One popular model that explains this is the Dreyfus Model of skill acquisition, which has five stages from beginner to expert. A novice is at the very bottom, and they usually follow rules exactly without fully understanding why. They may do okay in simple situations, but if something changes or becomes confusing, they may struggle because they do not know how to adjust yet.[3]

Novices are also in the cognitive stage of learning, according to another model by Fitts and Posner. At this stage, people must think hard about each part of the task, so their performance is slow and full of errors.[4] For example, a beginner driver might have to think carefully about every mirror check, gear change, and turn, while an experienced driver does it automatically. Because novices are still learning, they often do not know what is important and what is not. They may get overwhelmed if they are given too much information at once.[5] Teachers and trainers help novices by using things like worked examples, models, and lots of feedback.[6] In schools and workplaces, special training, mentors, and apprenticeships are used to guide beginners and help them avoid serious mistakes, especially in high-risk jobs like flying planes or caring for patients.[7]

Sometimes, beginners do not realize how much they still need to learn. This is called the Dunning-Kruger effect, which means people with low skills often think they are better than they really are.[8] That is why it is important for novices to get helpful feedback and learn how to reflect on their progress. In computer programming, novices may struggle because they look at the surface of the code without understanding the deeper logic.[9] That is why easy tools like Scratch are used to teach young or new coders, they simplify coding so learners can build confidence before moving on to more difficult programming languages.[10]

When novices get too much new information at once, it can cause something called cognitive overload. This makes learning harder.[5] To fix this, lessons should start simple and slowly become more complex over time. Teachers often use strategies like “chunking” information into smaller parts or showing examples that fade in detail as the learner gains skill.[11] Even though beginners may not have much experience, they can still offer fresh ideas. Because they have not yet learned all the usual ways of doing things, they might see problems in a new light. This is sometimes called having a “beginner’s mind,” and it is actually helpful in creative fields or when designing new products.[12]

In places like the military or emergency services, novices practice in simulations that are meant to be stressful. This helps them prepare for real-life situations where they will need to stay calm and make quick decisions, even before they become experts.[13] In many jobs or schools, beginners are called things like trainee, intern, or apprentice. These titles help define their role and what is expected of them.[14] Being a novice is not a bad thing, it is a natural and important step on the way to becoming skilled. With the right help and plenty of practice, novices gradually learn to handle harder tasks and grow into experts.[15]

References

  1. Chi, Michelene T. H.; Glaser, Robert; Farr, Marshall J. (2014). The Nature of Expertise. Hoboken: Taylor and Francis. ISBN 978-0-8058-0404-1.
  2. Ericsson, K. Anders; Krampe, Ralf T.; Tesch-Römer, Clemens (1993). "The role of deliberate practice in the acquisition of expert performance". Psychological Review. 100 (3): 363–406. doi:10.1037/0033-295X.100.3.363. ISSN 1939-1471.
  3. Dreyfus, Hubert L.; Dreyfus, Stuart E.; Athanasiou, Tom (1986). Mind over machine: the power of human intuition and expertise in the era of the computer. New York: Free Press. ISBN 978-0-02-908060-3.
  4. Fitts, Paul M.; Posner, Michael I., eds. (1973). Human performance. Basic concepts in psychology series Psychology. London: Prentice Hall. ISBN 978-0-13-445247-0.
  5. 5.0 5.1 Sweller, John (1988). "Cognitive Load During Problem Solving: Effects on Learning". Cognitive Science. 12 (2): 257–285. doi:10.1207/s15516709cog1202_4. ISSN 1551-6709.
  6. Sweller, John (2011-01-01), Mestre, Jose P.; Ross, Brian H. (eds.), "CHAPTER TWO - Cognitive Load Theory", Psychology of Learning and Motivation, vol. 55, Academic Press, pp. 37–76, doi:10.1016/b978-0-12-387691-1.00002-8, retrieved 2025-08-01
  7. Salas, Eduardo; Tannenbaum, Scott I.; Kraiger, Kurt; Smith-Jentsch, Kimberly A. (2012-06-01). "The Science of Training and Development in Organizations: What Matters in Practice". Psychological Science in the Public Interest. 13 (2): 74–101. doi:10.1177/1529100612436661. ISSN 1529-1006.
  8. Kruger, Justin; Dunning, David (1999). "Unskilled and unaware of it: How difficulties in recognizing one's own incompetence lead to inflated self-assessments". Journal of Personality and Social Psychology. 77 (6): 1121–1134. doi:10.1037/0022-3514.77.6.1121. ISSN 1939-1315.
  9. Robins, Anthony; Rountree, Janet; Rountree, Nathan (2003-06-01). "Learning and Teaching Programming: A Review and Discussion". Computer Science Education. 13 (2): 137–172. doi:10.1076/csed.13.2.137.14200. ISSN 0899-3408.
  10. Resnick, Mitchel; Maloney, John; Monroy-Hernández, Andrés; Rusk, Natalie; Eastmond, Evelyn; Brennan, Karen; Millner, Amon; Rosenbaum, Eric; Silver, Jay; Silverman, Brian; Kafai, Yasmin (2009-11-01). "Scratch: programming for all". Commun. ACM. 52 (11): 60–67. doi:10.1145/1592761.1592779. ISSN 0001-0782.
  11. Renkl, Alexander (2014). "Toward an Instructionally Oriented Theory of Example-Based Learning". Cognitive Science. 38 (1): 1–37. doi:10.1111/cogs.12086. ISSN 1551-6709.
  12. Sarasvathy, Saras D. (2001). "Causation and Effectuation: Toward a Theoretical Shift from Economic Inevitability to Entrepreneurial Contingency". The Academy of Management Review. 26 (2): 243–263. doi:10.2307/259121. ISSN 0363-7425.
  13. Klein, Gary (2001). Sources of power: how people make decisions (7th print ed.). Cambridge, Mass.: MIT Press. ISBN 978-0-262-61146-6.
  14. Lave, Jean; Wenger, Etienne (1991-09-27). "Situated Learning: Legitimate Peripheral Participation". Higher Education from Cambridge University Press. doi:10.1017/cbo9780511815355. Retrieved 2025-08-01.
  15. Ericsson, K. Anders; Nandagopal, Kiruthiga; Roring, Roy W. (2009). "Toward a Science of Exceptional Achievement". Annals of the New York Academy of Sciences. 1172 (1): 199–217. doi:10.1196/annals.1393.001. ISSN 1749-6632.