The effect of background environment on the learning and recognition of Chinese numeric characters
Abstract
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Previous researches on human memory found that the context present at learning and testing can have a significant impact on how well information is remembered, suggesting that information learned in one context is better recalled when the same context is reinstated during testing (McGeoch, 1932; Godden &Baddeley, 1975; Schwabe& Wolf, 2009). The purpose of this study was to investigate the effects of classical background music on learning and recognition of Chinese numeric characters. Participants (N=60) were randomly exposed to four different situations over an established period of time while given a sheet consisting of nine Chinese numeric characters to remember. After remembering the list of numbers they were tested on their recall of the numbers either in the same environment they were learnt or in the alternative environment. Using a 2?2 between-subject designs analysis it was found that recall was better in the matching conditions. Additionally, numbers learned in a quiet condition produced more errors during recall in a noisy condition, suggesting that performance is worse when the environmental contexts are mismatched. These results suggest that the effects of background noise on memory retrieval can be eliminated when a dissimilar learning context is reinstated at test. These findings have important implications for educational concerns.
Introduction
The theory of working memory model considers the mind to have strictly limited attention resources in processing parallel steams of information, and can become overloaded when exposed to excessive amount of information. Early investigations of memory discovered that the context at learning and recall can have an impact on how well information is remembered, suggesting that information learned in one context is better remembered when similar context is reinstated during recall. Accordingly, in this context it has been established by prior studies that external stimuli such as background music would possibly interfere with cognitive processing. Previous researches that have tested recognition memory in an environmental context that is different from the learning context have produced inconsistent results. (Davidson, Powell, 1986; Banburry& Berry, 1998) observed that background music enhance task performance on a variety of tasks. However, (Saufley, Otaka&Bavaresco, 1985; Klatte, Bergstrom &Lachmann, 2013) found that students’ exam performance were not significantly better when learning and testing took place in the same environmental context, compare to a different context.
This aspect of memory has been known as context-dependent memory (CDM). The CDM has been extended to different context and have received some previous attentions in the literature, including; olfactory stimuli (Pointer & Bond, 1998; Cann& Ross, 1989), alcohol states (Eich, 1980), and testing environment (Godden &Baddeley, 1975), among many other context. Background music has been shown to be another potential context under which CDM seems to occur. In a number of studies changes in context between learning and testing have produced a significant affect during recall,whereas, in other studies this effects has not been shown (Geiselman&Glenny, 1977; Geiselman& Bjork, 1980; Russo, Ward, Geurts&Scheres, 1999; Smith, Glenberg& Bjork, 1978; Smith & Vela, 2001; Godden &Baddeley, 1975; Smith, 1985; Fernandez & Alonso, 2001). Nevertheless while external stimulus (such as music) appears to enhance individuals’ learning, it could be distracting to others. For instance, (Smith, 1985) examined the effect of background music on CDM. In which subjects were asked to learn a list of words under one of three background music conditions (Mozart piece, jazz selection or quiet condition). He concluded that participants who were exposed to the same musical context recalled significantly more words during testing. This provides evidence that the idea of background music can serve as an effective retrieval cue for earlier learned material and does produce CDM effects.
According to the literature cited above, individuals tend to recall information better when the environmental context matches from encoding to retrieval. This was supportedin a study conducted by (Grant, Bredahl, Clay, Ferrie, McDorman& Dark, 1998). In this study, the participants were instructed to study meaningful information under either noisy or quiet conditions. Then, they were asked multiple-choice and short-answer questions on the previously learned material. A reduction in recall was noticed in participants whose noise level was mismatched during learning and testing compare to those whose noise-level was matched. This suggests if the music played throughoutthe administration of the test and learning is the same, this will improves memory because similar background cues promote memory retrieval.
Researches have also demonstrated the effects of background noise on task performance (Hygge, Evans &Bullinger, 2002; Ylias and Heaven, 2003), underlining the harmful effects of noise as a distractoron an individual’s performance. Banbury and Berry (1998) found that performance was lower in the presence of background noise (taped office noise) compare to quiet conditions during recall. Also greater disruption was noticed when both learning and recall occurred in the same noisy environment. However, there has also been research contradicting these findings. Avila,Furnham and McClelland (2011) found no significant difference in task performance in the presence background noise.
The present study considers the effects of background environment on learning and recognition of Chinese numeric characters. Three research questions are addressed. The first question is whether learning context affect recall. The second research question is whether testing context affect recall. And finally, the third research question that was addressed is to see whether there is an interaction between learning contexts and testing context. Also, in line with previous studies (Grant, Bredahl, Clay, Ferrie, McDorman& Dark, 1998; Cann& Ross, 1989; Smith, 1985), it was predicted that there would be an effect of context. It was expected that tasks performed in learn quiet-test quiet conditions would yield better results during recall than tasks performed in learn noisy-test noisy conditions, indicating that the background environment(Classical music) is a distracter to performance. The rationale for these predictions would be that background music could prevent full concentration on memory task; this could be because extra information during testing could be distracting to participants.
Additionally, percentage error scores were expected to be significantly higher in the quiet-noisy condition during learning and recall, suggesting that background noise contribute to lower performance in memory. Perhaps this could be due to the fact that attention will be drawn to the background music while learning, therefore, leading to poorer recall during testing. Finally, performance was predicted to be significantly higherin no background noise condition. The rationale for these results would be that according to prior studies the presence of background noiseand changed environment during recall could impair performance, potentially through distraction.
Method
Design
The first research question used a 2?2 between-subjects design to analyse the collected data. This was chosen to determine whether differences exist between different background situations (quiet and noisy) and whether one is more effective than the other. The independent variable was context at learning, with two levels; quiet and noisy. This addresses whether background music affects learning. The second research questions also used a between-subjects design. The independent variable was the context at testing, with two levels; quiet and noisy. This addresses whether background music affects recall at testing. The third research question addresses whether there this a interaction between context at learning and testing. For all the research questions the dependent variable was the number of errors. This was measured by counting the numbers of incorrect answers given by each participant.
Participants
Sixty participants (22 Males, 38 Females), ranging in age from 18 to 65 years old (M=29, SD=12. 1) participated in the study. The groups were randomly allocated from personal contacts of the researchers. Participants were divided into four groups each assigned to four different conditions. However, it is important to note that any Chinese participants or anyone with a previous knowledge of Chinese language were excluded from the study, due to the nature of the task.
Materials (or Measures)
The stimuli were the ‘noise’,which was played via Youtube throughout the study for a specific condition. Since classical music may cover a wide range of stylistic variances, the present study used Vivaldi – The Four Seasonsthis was chosen as classical music is frequently heard in the radio and thus musical style would be familiar to the participants (VanWeelden, 2012). The test consisted of nine Chinese numeric characters,which were selected for the purpose of the study (appendix). In order to avoid practice destruction sheet (word search) was used, which was randomly selected on the Internet (appendix 7).
Procedure
The experiment was conducted in a room assigned by the researchers. Participants were given consent forms to fill out at the beginning of the study and were informed of their right to withdraw at any point (appendix 3,4). They were also given an instruction sheet, detailing what they were required to do (appendix 2). The study was an independent-measure design. All sixty participants were assigned to four different conditions. Each condition consisted of 15 participants and depending on their groups they were exposed to either a quiet or a noisy room with classical music being played in the background. Also, depending on the conditions the researchers explained to the participants that music would be played while they were given a sheet with nine Chinese numeric characters to remember the meaning of (appendix 1). The participants were then given five minutes to remember the meaning of each numeric character. Then, in order to redirect participant’s attention and to avoid practice subjects were given a distraction task of a word search to complete under three minutes. Then, they were asked to return to their respective room, depending on their conditions (quiet or noisy) and were allowed five minutes to identify the meanings of the same nine Chinese characters on a separate testing sheet presenting with symbols but no meanings (appendix 6). At the end of the experiment participants were debriefed (appendix 5) and instructed in the same verbal and written manner throughout the experiment.
Result
The analysis conducted a 2?2 ANOVA with learn (quiet, noisy) and test (quiet, noisy) conditions as between-subject variables were conducted on the percentage error recall. This was done In order to determine whether recall would be higher when the learning and testing context were quiet in comparison to noisy, and whether recall would be better when learning and testing context matched compared to mismatched. The mean and standard deviation for recall scores are reported in table 1.
The results of the ANOVA confirmed that as predicted there was a significant main effect of context at learningF(1,56)=6. 287, P=0. 015, such that participants made significantly more errors in a noisycondition than in a quiet condition (M=22. 96 and M=11. 85 respectively). (See graph 1, figure 1). In addition, along with the prediction, there was not a significant main effect of context at test (p>0. 05),noisy condition produced more error compare to quiet condition (M= 21. 48 and M=13. 33 respectively).
And finally, There was not a statistically significant interaction effect between learning and testing context, F(1,56)=3. 381, P=0. 071. This means that context at learning had the same effect at both levels of the other IV, context at test.
Table 1. Percentage memory recall during quiet and noisy test conditions following quiet and noisy learning conditions.
Learning Condition
Quite Noisy Total
Mean SD Mean SD
Test condition Quite 11. 85 15. 97 11. 85 15. 9713. 33
Noisy 31. 11 21. 4914. 813 16. 08 21. 48
Total 11. 85 14. 85 22. 96 20. 41
Figure 1: Estimated mean log of errors scores in Chinese numeric character recall task of context at learning.
Discussion
Our primary goal in this experiment was to examine the effect of background music on learning and recall. It was predicted that the detrimental influence of background music on memory retrieval would be lessened if the learning and retrieval environments matched. The present findings confirmed this prediction. The participants performed worse when the learning and testing context were dissimilar. This is in line with previous studies of impaired memory retrieval following background noise (Dalton &Behm, 2007; Dobbs, Furnham& McClelland, 2011). If, however, the learning and testing context were matched, this detrimental effect of stress disappeared. But, in confliction with some studies, the results provide no evidence for an interaction of background music and context effects in memory processes. Participants learned better in learn quiet-test quiet condition (M=11. 85), but did not necessarily recall higher when they were tested in a noisy condition (M=31. 11). Also, participants produced more errors in learn noisy-test noisy (M=14. 81) as opposed to learn noisy-test quiet condition (M=11. 85), suggesting that participants performed poorly when the learning and test context were mismatched. This can be supported by many studies (Fernandez & Alonso, 2001; Schwabe& Wolf, 2009).
Although we focused mainly on the manipulation of the environmental (i. e. , external) context, it is important to note that the presence or absence of other stimuli can also be conceptualised as a change in internal context. In this study internal stimulus such as personality trait, emotional state and mood were not assessed during learning and recall. Also, mood, which can be affected by emotions and feelings, can improve or hinder with successful learning model of the engaged individual. Additionally, as mentioned before personality trait could be a factor that needs to be considered. The influence of music on memory performance has also been linked to personality types. A study piloted by Furnham and Bradley (1997) demonstratedthat pop music could be a distracter on the performance of introverts and extraverts. It was proposed that in the presence of music extravert would perform better than introverts. The findings determined that when pop music was played recall was severely lessened for both introverts and extraverts. Also, it was shown that introverts recalled significantly lower than extraverts in the presence of pop music condition as well as introverts in the silent condition. Overall, introverts seemed to be easily distracted in the presence of background noise. This researchexposed evidence that overall background noise, such as music, TV and background conversation could improve performance in complicated cognitive tasks for extraverts, while it will considerably impair introverts’ task performance (Furnham& Bradley, 1997; Dobbs, Furnham & McClelland, 2011).
A possible confounding variable in between-subjects designs in this experiment could have been related to individual differences, in which the participants’ characteristic differed one group to another, for instance the participants in one group may be older, smarter, then the participants in another group. This was somehow controlled by giving the exact same information to every participant and treated equally. Also, environmental variables may have affected the findings in which characteristics of the environment differed between groups, for example the groups were tested in different rooms, one group may be tested in a larger room and another group in a smaller room. However, we had no control over assignment of individuals to groups, as the groups were randomly allocated. It is important to note that the Chinese numeric characters where unfamiliar to the participants, these may have affected their recall regardless the condition their were set in, however, this needs to be taken into further consideration.
A group of different ages were exposed to one task that had been designed to assess the participants’ ability ton how well they canremember unfamiliar Chinese characters. As Fernandez & Alonso (2001) found that older participants recall better when they were tested in the same context, but no effects was shown for the younger participants. However, this had no impact on the direction of the data, but it makes the sample less reliable.
In summary, the results of the present experiment indicate that the detrimental effects of background music on memory retrieval can be prevented when the environmental context at learning and testing match. These findings have important implications for educational concerns, to find out whether the negative impact of background music on learning or testing will be reduced if students are tested in the same room/context, instead of in an unfamiliar room.
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