Lab Report- The Implicit Learning Experiment
Implicit learning differs from explicit learning in that the latter employs a more conscious approach, and the learner has to make and test a hypothesis to search for the structure. In implicit learning, an individual acquires knowledge of the structure of an environmental stimulus naturally or unconsciously. An example of a task learned via implicit knowledge is riding a bicycle. The learning process is gradual, and it is difficult for individuals to ascertain when they fully acquire the knowledge or skill (VanPatten & Smith, 2022). Explicit learning utilizes a more intentional approach to acquiring information. An example of explicit learning is memorizing a phrase. This paper is a lab report on implicit learning.
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Methods
The implicit learning experiment was conducted using the online cognitive laboratory. In each trial, a dot appeared in four locations, and the learner was asked to press a key on the keyboard that corresponded to the dot’s location on display. For most of the blocks in the trials, the sequence of the dots followed a specific pattern. The pattern was, however, varied in the tenth block. The learner was expected to register their results quickly, and the response time was recorded. There were 264 trials in 11 blocks. The response time was recorded in milliseconds.
Results
The mean response time for block number 1=1210.0435 milliseconds; block number 2=705.1739; block number 3= 559.875; block number 4=773.1818; block number 5=629.5; block number 6=644.1667; block number 7=720.2083; block number 8=646.2857.; block number 9=734.5; block number 10=952.63635; block number 11=660.4783. The pattern for accuracy of each trial revealed a higher accuracy with higher response times. Trial numbers 18, 35, 83, 92, 169,174, 187, 214, 215, 239,240, and 261 recorded inaccurate results. Most inaccurate findings coincided with shorter response times of not more than 700 milliseconds, indicative of the shortest response times.
Discussions
As the block number increases, the mean response time decreases. The overall trend in this experiment lacked consistency. The sharp rise in the mean response time observed in the tenth block is due to the variation in the pattern of the dots. It is expected that the response time increases as the learner readjusts. The decrease in response time from the first block onwards, as indicated in the results, is due to the mastery of key presses, better focus on display, and predictability of the location of the dots. As the trials begin, the learner tends to exhibit slower responses due to a lack or inadequate mastery of the key presses. During these initial phases, there is a high likelihood of making mistakes accustomed to wrong presses rather than inaccurate responses. As the trials continue and the response time shortens, the learners are likely to give inaccurate due to poor focus and lack of concentration (Ivanchei et al., 2019).
The results were not per my expectations. I expected to spend less time per block and yield higher accuracy with more attempts. This was not the case, as the pattern of my results indicates inconsistent findings not aligned with the theoretical provisions on the same. For a moment, I felt I had learned the pattern that was apparent in the experiment. I, however, made some mistakes that yielded inconsistency in the results. My reaction got faster with increasing attempts, as indicated in the results. The experiment was straightforward. I was surprised by how implicit learning occurs and my ability to learn the structure of the experiment unconsciously. Several factors can influence the result of implicit learning. These include mood and the individual’s cognitive style (Batterink et al., 2019). These factors will inform how well an individual’s results conform to the theoretical predictions.
References
Batterink, L., Paller, K., & Reber, P. (2019). Understanding the Neural Bases of Implicit and Statistical Learning. Topics In Cognitive Science. https://doi.org/10.1111/tops.12420
Ivanchei, I., Moroshkina, N., Tikhonov, R., & Ovchinnikova, I. (2019). Implicit learning in attractiveness evaluation: The role of conformity and analytical processing. Journal Of Experimental Psychology: General, 148(9), 1505-1516. https://doi.org/10.1037/xge0000633
VanPatten, B., & Smith, M. (2022). Explicit and Implicit Learning in Second Language Acquisition. Cambridge University Press. Retrieved 31 July 2022, from https://www.cambridge.org/core/elements/abs/explicit-and-implicit-learning-in-second-language-acquisition/EBABCB9129343210EB91B9198F17C4EB.a:link {text-decoration: none;}a:visited {text-decoration: none;
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Question 
The Implicit Learning Experiment
Using CogLab, perform the implicit learning experiment and create a report on the experiment.
In your report, write a brief introduction explaining the differences between implicit and explicit learning.
Next, in the Methods section, describe the process that you followed to complete the experiment, including a description of the material requirements and stimuli. Make sure to include enough information so that others can also perform the same experiment successfully. Finally, describe the experimental results. Summarize your report, including answers to the following questions:
Were the results in accordance with your expectations? Provide a rationale to support your answer.
Did you feel like you were learning the patterns that occurred? Did your reaction time get faster with each attempt?
Did anything about the experiment surprise you? If yes, what?
What factors can influence the results of the implicit learning experiment?