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SOLVING MAZES AND PLOTTING BOX AND WHISKER GRAPHS AS TOOLS TO UNDERSTAND AND TO EVALUATE LEARNING
Universidad de Huelva (SPAIN)
About this paper:
Appears in: EDULEARN14 Proceedings
Publication year: 2014
Page: 153 (abstract only)
ISBN: 978-84-617-0557-3
ISSN: 2340-1117
Conference name: 6th International Conference on Education and New Learning Technologies
Dates: 7-9 July, 2014
Location: Barcelona, Spain
Abstract:
In their teacher training, students use permanently the concept of learning. However, the inquiry into students' ideas about this topic shows a dispersion of ideas and confusing answers, referred to the concept itself and the procedures to evaluate its progression.
Since solving mazes have been used long ago as a method to investigate learning as they “provide a situation previously unfamiliar to the learner”, a simple methodology using a standard maze has been designed to analyze what is learning and how it can be measured. As an instructional strategy, box and whisker plots were used to assess the progression of learning.

Method:
Students were not previously advised about the purpose nor the methodology used in these experiments, in order to not influence their answers or stimulate a competition among them.
Experiment no 1. During a typical class, students were going to solve a maze of moderate difficulty. They were previously grouped in pairs so that a member solved the maze and the other measured the time resolution. The timekeeper should not help his partner. The maze was partitioned face down to the different pairs and simultaneously all couples turn over the maze and began its resolution and timing. Once solved, the timekeeper wrote the name of his partner and the time of resolution and he delivered the data and used maze to the teacher.
Experiment no 2. It was as before, using the same maze, with the same couples in the same roles but a half an hour after the end of the first experiment.
Experiment no 3. One month later, the same maze was delivered to be solved by the couples formed in the first experiment. The procedure was as above.

Results and discussion:
The experiments were performed out by 10 paired students (n = 10). All obtained data for each experiment fit a normal distribution. In the experiment 1, the average time for solving maze was 112 s, while in the numbers 2 (a half an hour later) and 3 (one month later) the times were 31 and 38 s, respectively. The average time used in the experiment 1 was very significantly (p < .001) different from the mean times measured in the experiments 2 and 3, whereas both times did not differ significantly. The quartile 2 or median for each experiment was 103 (experiment no 1), 30 (no 2) and 20 (no 3) and the interquartile ranges (IQR) were 93, 15 and 34, respectively.
The boxplot graphs were drawn to understand how learning is evolved during the use of the maze and how learning cannot be isolated from the simultaneous memory processing of information. Learning occurs after the first attempt and was stable without any reinforcement even a month later.

The IQR in the experiment no 1 was the highest, probably because of genetic differences between students and also by the previous individual experience with labyrinths. However, IQR decreased very significantly in the experiment 2, showing that learning reduced individual differences. IQR was slightly higher in the experiment 3 than in the experiment 2, probably because the memory threshold depends on each individual and the time elapsed since the last experiment.

In summary, a simple experiment and a mathematical analysis were useful to define how learning is produced and how it can be measured. These experiments further support that “the functional architecture of the brain depends not only on genes but on epigenetic mechanisms based on the stabilization of connections among neurons for specific tasks” like the resolution of a maze.
Keywords:
Learning, box and whisker plot, maze, learning concept, learning evaluation, individual differences.