Instructional designers aim at providing learning material that is attractive to learners, thereby fostering motivational processes. However, sometimes, learners themselves also decide to enrich their learning setting to raise motivation, for example, by listening to background music while learning. Such attractive but—in terms of information processing—irrelevant aspects are called seductive details (Garner, Gillingham, & White, 1989 ; Mayer & Fiorella, 2014 ). Research indicates that seductive details generally have a negative impact on learning (Rey, 2012 ). However, whether music can be helpful for learning or hinders learning might be individual and dependent from learners' characteristics. One of these individual mechanisms might be that listening to background music influences the learner's arousal level (e.g., Pelletier, 2004 ). For example, people with different levels of extraversion prefer different levels of induced arousal: The higher the extraversion level, the greater the preferred induced arousal (Eysenck, 1967 , 1994 ; Eysenck & Eysenck, 1985 ) and vice versa. This is why the learner's extraversion level might be an important variable to be considered while analyzing the effects of background music.

Another important variable for explaining the different effects of music on learning outcomes might be the music's potential to induce arousal: There is broad evidence that listening to music has an impact on the listener's arousal level (for a meta‐analysis about the arousal decreasing effect of music, see Pelletier, 2004 ; for an arousal increasing effect, see Holbrook & Anand, 1990 ; Rickard, 2004 ; Salimpoor, Benovoy, Longo, Cooperstock, & Zatorre, 2009 ). The tempo of the song is primarily important for the amount of induced arousal (Husain, Thompson, & Schellenberg, 2002 ): The higher the tempo, the higher the induced arousal. The relation between arousal and learning follows a reversed u‐shaped curve (e.g., Eysenck, 1976 ; Heuer & Reisberg, 2014 ). The peak of this curve does not only depend on the task (Yerkes & Dodson, 1908 ) but also on the learner's extraversion level (Eysenck, 1967 , 1994 ; Eysenck & Eysenck, 1985 ).

For example, it would be helpful to also analyze the effects of music on cognitive load in a differentiated way. Based on cognitive load theory (Chandler & Sweller, 1991 ), seductive details are inherent to an inadequate instructional design and should therefore cause extraneous load. The studies that revealed beneficial effects of background music might nevertheless indicate that learners also increased germane processes of schema acquisition when listening to music (de Groot, 2006 ; Hallam et al., 2002 ). To analyze both effects of music, it is necessary to use differentiated measures of cognitive load (e.g., Leppink, Paas, van der Vleuten, van Gog, & van Merriënboer, 2013 ; Klepsch, Schmitz, & Seufert, 2017 ). Only then, one can disentangle whether an increase in load caused by background music is due to unproductive (extraneous) processes like distraction or due to an increase in germane processes (Kalyuga, 2011 ).

Previous research revealed different results concerning the impact of background music on learning. While some studies found that background music impedes learning (for a meta‐analysis, which reports a negative impact, see Kämpfe, Sedlmeier, & Renkewitz, 2010 ), another study found no impact (Grice & Hughes, 2009 ). However, there is also some evidence for a beneficial effect of background music on learning (e.g., de Groot, 2006 ; Hallam, Price, & Katsarou, 2002 [Study 1]). Thus, to understand these different effects of background music on learning outcomes, it is worth taking a closer look at the variables that might explain these differences.

However, in his meta‐analysis, Rey ( 2012 ) summarizes four main argumentations why seductive details impede learning: First, he argues that seductive details can lead to a cognitive overload. Second, seductive details distract the learner and draw their attention away from the actual learning content. Third, the presentation of seductive details may lead to inadequate schema acquisition. Fourth, seductive details hinder the construction of a coherent mental model. These explanations can be applied when explaining the influence of background music on learning: First, background music needs to be processed in addition to the actual learning content and thus, poses additional load on learner's working memory. Second, it is plausible that learners focus on the background music rather than on the learning content, as auditive stimuli are always processed first (Salamé & Baddeley, 1989 ). Thus, background music might split the learner's attention. Previous studies (e.g., Mayer & Moreno, 1998 ) have already shown that split attention generally impedes learning. And third, background music may activate schemata, which are not important for the learning content, as, for example, schemata about the musician. These schemata then might interfere with the processing of the learning content. Problems in constructing a coherent mental model should especially affect higher levels of processing, like comprehension and transfer. Thus, it might be especially interesting to analyze the effects of background music on different levels of learning outcomes.

As outlined above, seductive details are potentially attractive pieces of information added to the learning material, which are unnecessary for understanding the learning content (Garner et al., 1989 ; Mayer & Fiorella, 2014 ). In this paper, we refer to Mayer and Fiorella's work (Mayer & Fiorella, 2014 ) and his broader understanding of seductive details: We consider all unnecessary but attractive information as seductive details, which need to be processed by the learner and are part of the learning environment, but not necessarily of the learning material. Seductive details can be visual stimuli such as pictures (e.g., Harp & Mayer, 1998 ) or additional texts (e.g., Garner et al., 1989 ; Harp & Mayer, 1998 ; Park, Flowerday, & Brünken, 2015 ), as well as auditive information such as sounds or background music (Lehmann & Seufert, 2017 ; Grice & Hughes, 2009 ; Mayer & Fiorella, 2014 ; Moreno & Mayer, 2000 ). The idea behind adding seductive details is to raise the learner's interest and enjoyment, thereby fostering learning (cf. Harp & Mayer, 1998 ). Specifically, in regard to background music, it might motivate the learner to adopt a general state of positive attitude toward the overall learning environment, which transfers to the learning content itself, for example, by an increased willingness to invest effort.

A basic assumption of the arousal theory is that people seek to attain an optimal level of cortical arousal (Eysenck, 1967 ). Eysenck ( 1967 ) states that there is an inverted u‐shaped relationship between the level of external stimulation and the hedonic tone, which is determined by the level of arousal. The maximum hedonic tone is only reached at a medium level of stimulation and thereby at moderate levels of arousal (Eysenck, 1967 , 1994 ; Eysenck & Eysenck, 1985 ). Thus, Eysenck ( 1967 , 1994 ) and Eysenck and Eysenck ( 1985 ) describe the physiological differences between introverts and extraverts and their ensuing need for external stimulation: Introverts are naturally more aroused and more vulnerable to become over‐aroused by external stimulations. Therefore, they try to avoid intense stimulation like noisy settings, exciting situations, or social stimulation. On the contrary, the arousal system of extraverts requires more stimulation to attain the optimal level of arousal and maximum hedonic tone. Therefore, they engage in arousing situations and seek out stimulating environments (Eysenck, 1967 , 1994 ; Eysenck & Eysenck, 1985 ).

Eysenck ( 1967 ) postulates that differences between extraverts and introverts are caused by differences in their cortical activity. In general, introverts tend to have higher cortical activity and are more aroused compared with extraverts (Eysenck, 1967 , 1994 ; Eysenck & Eysenck, 1985 ). Cortical activity is influenced by external stimulations, and under too high levels of stimulation, the brain protects itself by de‐arousal (Eysenck, 1994 ).

In recent years, researchers became increasingly interested in extraversion as a learner's characteristic that might be able to predict learning performance (Chamorro‐Premuzic & Furnham, 2008 ). Studies investigating the relationship between the level of extraversion and cognitive ability show varying results. For example, Ackerman and Heggestad ( 1997 ) determined that the level of extraversion correlates positively with cognitive abilities, whereas another study of Moutafi, Furnham, and Crump ( 2003 ) reported this correlation as negative. These heterogeneous results are considered to be a consequence of using different intelligence tests for measuring cognitive abilities (Moutafi, Furnham, & Paltiel, 2004 ). For example, the study of Rawlings and Carnie ( 1989 ) indicates that extraverts show superior outcomes on intelligence tests with time–pressure. Introverts, however, perform better in written tests such as in reading comprehension tasks in a foreign language (Robinson, Gabriel, & Katchan, 1993 ).

The interaction effect of background music on learning outcomes of introverts and extraverts has been investigated for many years (Avila, Furnham, & McClelland, 2011 ; Cassidy & MacDonald, 2007 ; Chamorro‐Premuzic, Swami, Terrado, & Furnham, 2009 ; Dobbs, Furnham, & McClelland, 2011 ; Furnham & Bradley, 1997 ; Furnham & Strbac, 2002 ). Most of these studies actually support the assumption, that background music in general raises the cortical arousal level: They report that extraverts showed better learning outcomes than introverts without using specifically fast, arousing background music. This does not automatically mean that extraverts always profit from background music. While there is only one study reporting a stimulating effect of music on extraverts (Furnham, Trew, & Sneade, 1999 ), there is broader evidence suggesting that the outcomes of extraverts can also remain unaffected (Dobbs et al., 2011 ; Furnham & Bradley, 1997 ) or even be impaired by background music (Cassidy & MacDonald, 2007 ). Interestingly, Cassidy and MacDonald ( 2007 ) found that extraverts were more negatively affected by music with high arousal potential than by music with low arousal potential, pointing out that also extraverts may become over aroused. Furthermore, Furnham and Strbac ( 2002 ) demonstrated that complex background music and noises have equally distracting effects on learning outcomes. Thus, the reduced or unaffected outcomes of extraverts in the presence of background music observed in many studies might be explained by an unappealing choice of music. All in all, especially the music's potential to influence arousal should be considered while setting up hypotheses about the influence of background music on learning.

Listening to background music while learning represents an external stimulation that has an impact on cortical arousal (Rickard, 2004 ; Sweeney & Wyber, 2002 ). In general, fast music seems to lead to an increased arousal, whereas slow music was found to reduce arousal (Thompson, Schellenberg, & Letnic, 2011 ). Thus, on the one hand, it can be expected that fast background music has a beneficial effect on the arousal level of high extraverts and therefore, positively influences their learning outcomes. In contrast, listening to fast music while learning would over‐arouse introverted individuals. Slow background music, on the other hand, should be beneficial for the cortical arousal level of introverts by decreasing it. However, such a decreased arousal level should be harmful for high extraverts.

With respect to the overall effect of background music irrespective of the learner's extraversion level, the first research question (Q1) is whether listening to background music influences recall, comprehension, and transfer. Based on the seductive detail assumption (Rey,) and the results of Kämpfe et al.'s (Kämpfe et al.,) meta‐analysis, we assume that:The second research question (Q2) is whether background music has a different effect on recall, comprehension, and transfer depending on the level of extraversion of the participants. According to Eysenck's arousal theory (Eysenck,), introverts are more vulnerable to become over‐aroused by external stimulation, whereas extraverts require external stimulation to attain the optimal level of arousal. If background music has an impact on the learner's arousal, we would assume that:Given that background music can theoretically increase or decrease the learner's arousal level, one could assume the following competing hypotheses:Moreover, we raise the third research question (Q3) of whether background music has an impact on cognitive load. Based on the argumentation of the seductive detail assumption (Rey,) and empirical findings (Park, Moreno, Seufert, & Brünken,; Park et al.,), we assume that:However, as there are also studies, which show better learning outcomes for learners who learn with background music, there seem to be germane processes taking place while learning with background music. Therefore, we assume that:

Based on the theoretical and empirical background, we want to investigate the effect of background music on different levels of learning outcomes. We differentiate between performance in recall, comprehension, and transfer tasks. Moreover, we are especially interested in analyzing whether the learner's level of extraversion or introversion moderates the effects of background music.

Before the data collection took place, parents of all students received an information letter including all relevant information about the study, such as the involved tasks, duration of the experiment, anonymous use of all collected data, and the freedom to quit the experiment at any time. Permission was sought for all students under the age of 18, while students over the age of 18 were allowed to sign the informed consent themselves. During data collection, all participants first filled out the demographical questionnaire, followed by a prior knowledge test and the pretest for arousal. Then, the learning phase began. Participants were instructed to wear their headphones and to listen to the recorded instructions, and were then asked to start reading. Learning time was limited to 15 min. And at the end, participants completed the arousal questionnaire again as well as the test on learning outcomes and cognitive load. Students were tested with their classes in their classrooms, and the experiment took about 60 min.

Cognitive load was measured differentiated with the cognitive load questionnaire (Klepsch et al., 2017 ). Based on our hypotheses, we used the subscale for extraneous cognitive load with three items (e.g., “The design of this task was very inconvenient for learning.”) and the subscale for germane cognitive load, also including three items (e.g., “For this task, I had to highly engage myself.”) on a seven‐point Likert scale from 1 ( not at all ) to 7 ( completely ). Validity of this questionnaire has been shown by a comprehensive predictive validity test. Reliability was reported by Klepsch et al. ( 2017 ) to be between α = 0.80 and α = 0.86 for all subscales.

To measure arousal before and after learning, a subscale of the self‐assessment manikin (Bradley & Lang, 1994 ) was used. The construct was measured with one nine‐point Likert scale that ranged from 1 ( highly aroused ) to 9 ( not at all aroused ). The item is additionally illustrated by a stick figure with a smaller (little arousal) or bigger (higher arousal) explosion in its belly and was already used successfully in other studies (Sloan, Marx, Epstein, & Lexington, 2007 ).

Extraversion was measured with the corresponding subscale of the Big Five Inventory 10 (BFI‐10; Rammstedt & John, 2007 ; Muck, Hell, & Gosling, 2007 ). This subscale consists of two items to be scored on a seven‐point Likert scale that ranged from 1 ( strongly agree ) to 7 ( strongly disagree ). The BFI‐10 is a time‐economic questionnaire, which showed sufficient levels of validity and reliability (Rammstedt & John, 2007 ). In their study, the BFI‐10 shows only a small decrease in its effect sizes compared with its longer version. This is acceptable when considering the saving time. The BFI‐10 was validated especially for school students (Rammstedt & John, 2007 ).

The learning material was a visual text about two musicians (Michael Jackson und Justin Bieber) and consisted of 1,223 words presented on three pages. The text describes the life of both musicians, including information about their families, religion, and scandals. Learning time was limited to 15 min. Prior knowledge was measured with 20 self‐developed open‐ended questions (e.g., “How many siblings did Michael Jackson have?”). The posttest for learning outcomes included open‐ended questions, seven for recall (e.g., “How many Grammys did Michael Jackson win?”), four for comprehension (e.g., “What are the differences between Michael Jackson and Justin Bieber? Name three.”), and also four for transfer (e.g., “Explain two difficulties that single parents have to deal with and discuss them with reference to one of the two biographies.”). For recall tasks, the learner had to simply recall information, which were provided in den learning material. To solve comprehension tasks, the learner had to understand the given information and had to be able to compare them, for example, by finding similarities or differences. To answer transfer tasks, the learner needed to discuss learned contents in regard to common knowledge. All answers were compared with predefined solutions. Participants could reach a maximum of 28 points.

Data were collected from 167 students from a German gymnasium. Participants were aged between 13 and 18 years ( M age = 14.38, SD age = 1.00), and the sample included 143 (85.6%) females. The first factor was the presence or absence of background music. While the participants were learning a visual text, randomly half of them listened to background music (experimental group), and the other half learned in silence (control group). Extraversion was the second factor and was measured as a continuous organism variable. Moreover, we measured recall, comprehension, and transfer as dependent variables and arousal before and after learning as a potential mediator. Furthermore, age, gender, and prior knowledge were considered as a potential confounding variables.

For transfer, the regression model again showed significant results, F (5, 166) = 6.47, p < 0.001, R 2 adj = 0.14 (see Figure 3 ). Background music was a significant predictor for transfer, β = 0.184, t (166) = 2.52, p = 0.013, and the presence of background music led to higher transfer scores. The interaction between background music and extraversion was no significant predictor for transfer, β = 0.036, t < 1, ns. Extraversion did not influence transfer, neither in the group without background music, β = 0.097, t < 1, ns, nor in the group with background music, β = 0.142, t (166) = 1.55, ns.

For comprehension, the regression model was significant as well, F (5, 166) = 3.49, p = 0.005, R 2 adj = 0.07 (see Figure 2 ). Again, we found no significant influence of background music on comprehension, β = 0.072, t < 1, ns. The interaction between background music and extraversion was no significant predictor for comprehension, β = 0.057, t < 1, ns. Extraversion was neither a significant predictor in the group without background music, β = 0.208, t (166) = 1.65, ns, nor in the group with background music, β = 0.136, t (166) = 1.43, ns.

For recall, the regression model showed significant results, F (5, 166) = 4.52, p < 0.001, R 2 adj = 0.10 (see Figure 1 ). Background music was not a significant predictor for recall, β = 0.079, t (166) = 1.06, ns. Moreover, the interaction between background music and extraversion was no significant predictor for recall, β = 0.151, t (166) = 1.22, ns. However, extraversion predicted recall significantly in the group without background music, β = 0.325, t (166) = 2.61, p = 0.010, but not in the group with background music, β = 0.135, t (166) = 1.44, ns.

To further analyze the influence of background music and extraversion on recall, comprehension, and transfer, we set up regression analyses as proposed by Aiken and West ( 1991 ). We included the predictors condition (learning with background music, learning without background music), extraversion (z‐standardized), the interaction term between condition and extraversion, and the covariates prior knowledge and age.

We analyzed whether the control variables (prior knowledge, age, gender) have an influence on the dependent variables (recall, comprehension, transfer). For prior knowledge, we found significant correlations with recall ( r = 0.196, p = 0.005), comprehension ( r = 0.215, p = 0.003), and transfer ( r = 0.233, p = 0.001). Moreover, we found that age also correlated significantly with recall ( r = 0.198, p = 0.005), comprehension ( r = 0.166, p = 0.016), and transfer ( r = 0.280, p < 0.001). Therefore, we included prior knowledge and age in all further calculations analyzing the influence on recall, comprehension, or transfer. None of the covariates correlated with the cognitive load subscales.

8 DISCUSSION

In this study, we addressed the questions of whether music affects learning and cognitive load (Research Questions 1 and 3). We were especially interested in analyzing whether effects of music depend on learners' level of extraversion (Research Question 2).

Concerning the first research question, the results are not consistent for all levels of learning outcomes. Interestingly, we found no effects of music on recall and comprehension, but a beneficial effect of music for transfer. This was especially unexpected, as our learning material dealt with musicians, and the music we presented was composed from a different musician. We would have expected that this might lead to interferences and thus, especially to problems in the construction of a coherent mental model, resulting in lower transfer performance. Results did not support this assumption, as learners in the group with background music outperformed those in the group without background music in their transfer outcomes. Transfer tasks are more complex than comprehension or recall tasks and thus, require more mental effort. Therefore, a higher engagement of the learner and an appropriate schema acquisition become especially important while answering transfer questions compared with easier recall or comprehension tasks. But how can we explain the improved schema construction process?

Considering the results of the third research question regarding cognitive load might help to answer this question. One possible explanation could be the increase in germane cognitive load, which we found in the music condition. Learners, in fact, seemed to have engaged more intensively in learning when music was given. However, this engagement did not influence recall or comprehension performance. As recall tasks are comparably easy to answer, an additional engagement might not have been needed. Considering the comprehension scores, a rather high variance becomes visible. Some participants might have had problems in understanding the task, overshadowing the effect of background music.

The question of whether the increase in germane processes could be due to motivational aspects needs to be analyzed in further studies. It would also be interesting to find out which aspect of listening to background music fosters germane load and thereby learning. One possible important variable could be mood (Husain et al., 2002): There is empirical evidence, that music can influence mood (e.g., Schmidt & Trainor, 2010). In turn, positive mood seems to influence learning outcomes positively (Goetz & Hall, 2013), whereas negative mood hinders learning (O'Hanlon, 1981). Besides mood, there might also be other motivational variables, which play an important role and should be investigated in further studies.

In contrast to germane load, listening to background music had no influence on the reported extraneous cognitive load. This was against our expectations, as we thought that listening to background music poses an unnecessary burden on working memory and distracts the learner, leading to a higher extraneous cognitive load. One explanation might be that our participants were used to learning with music, so that they did not score music as an additional burden. This is in keeping with the argument of Kou, McClelland, and Furnham (2017) who discuss that there might be a habituation effect for background music for people who are used to noisy environments. Another important point would be that we used instrumental music, which is less disturbing for the learner than music with lyrics (Iwanaga & Ito, 2002). As music did not cause extraneous load, learners had sufficient capacity left to invest in germane processes.

In conclusion, background music is one kind of seductive detail, which had a positive influence on transfer performance, probably explained through an increased germane cognitive load. This is in contrast to the results of Rey's (2012) meta‐analysis, which showed an overall negative effect of seductive details on learning. Most seductive details are presented visually, such as decorative pictures, thereby burdening the visual channel in working memory (Mayer, 2014). Background music, however, is presented auditorily, thereby relying on additional capacity provided through the auditive channel (Mayer, 2014). Thus, cognitive overload is prevented. This might be one reason why the presentation of background music in contrast to other seductive details did not raise extraneous cognitive load, thereby leading to a different impact on learning.

Regarding the second research question concerning the interaction between background music and extraversion, we only found differences in the recall scores of the two experimental groups: Extraversion predicted recall in the group without music, but not in the group with music. However, the overall interaction reached no significant level. Thus, one needs to be cautions when interpreting these results. The higher scores for more extraverted learners in the condition without music might be explained by the testing conditions: The students had to learn a text with limited time. Rawlings and Carnie (1989) showed in their experiment that extraverts perform better under time pressure than introverts. Moreover, we assume that the whole data collection might have been special and arousing for our participants. Taking part in a study is definitely not an everyday routine for high school students and might have particularly benefited students with higher levels of extraversion.

Interestingly, this effect disappears in the group with background music: In contrast to the group without background music, extraversion no longer predicted recall. Based on the argumentation above, this could be a hint for an arousal decreasing effect of background music, which however, was not found statistically. This might be an issue of a problematic measurement: To evaluate one's own arousal one needs interoceptive sensitivity. Interoception skills differ largely between learners (Herbert & Pollatos, 2012), and high extraverts tend to have less interoceptive sensitivity than introverts (Garfinkel & Critchley, 2013). One solution would have been to measure arousal physiologically, such as the heart rate or temperature (e.g., Burns et al., 2002). Moreover, not only the quantity of arousal but also the quality of arousal, that is, how pleasant the participants rate the arousal might be interesting. Due to the higher cortical activity of introverts (Eysenck, 1967, 1994), extraverts might judge the same amount of induced arousal more pleasant than introverts. One further problem is that arousal was measured with a seven‐point‐Likert scale, which means that 14% of variance is between two points of the scale. This might have been too insensitive to detect possible differences between the experimental groups on a statistically significant level.

Finally, we would like to point out the advantages of our sample and setting: We tested high school students in their classes, which leads to a higher generalizability than controlled laboratory studies. As most recent research about the influence of seductive details took place in more controlled settings, our study extends the knowledge of how seductive details and particularly background music influence student's learning outcomes.