The working memory is the portion of the brain responsible for short term memorization and the allocation of information to its necessary stores. It has been found there is a correlation between working memory capacity and multisensory presentation, which is the combination of multiple senses. Students are faced daily with tasks and assessments requiring memorization, but the current methods of studying they utilize do not result in the maximum possible recall. Research has been conducted on the effects of multisensory learning retention rates among students with learning disabilities, but a study focused on healthy teenagers has yet to be conducted. This led me to develop my research question which considers the relationship between multisensory study methods and recall rates among healthy teenagers. The method consisted of an inclusive survey with over 400 responses, a design-based methodology study with 40 participants, and a matched pairs t-test statistical analysis. The results showed that there was a statistically significant increase in retention of terms from a singular sense to the use of multisensory integration.
I chose the methodology of design-based research since the groups of tested students would be undergoing researcher-imposed learning strategies followed by observations in performance and retention. In determining what combinations of sensory modalities to test, I considered the most common strategies currently utilized by the high schoolers surveyed. The most prevalent method, with a 45.11% use rate, was found to be writing as well as reading, as in flash cards, written notes, study guides, etc. Based on these results I chose to focus on using visual presentation as a benchmark, measuring the improvement to audiovisual as well as visual, auditory, and kinesthetic (VAK) techniques.
I began by preparing the words that would be presented to the students by utilizing a randomizer with Charles Kay Ogden’s 850 basic English word list. Then, I proceeded to select the first 36 of the random words. Ogden, an English linguist, philosopher, and writer, advocated for the widespread employment of these basic words, as they could be used for practically all necessary language in day-to-day life (The Editors of Encyclopaedia Britannica, 2018). This ensured that the words would not come as shocking, foreign, or confusing to the students, eliminating a possible variable for error.
Zhijian Chen and Nelson Cowan, a biochemist and a professor specializing in working memory, respectively, conducted an experiment in 2005 to determine working memory capacity, with an experimental design of word lists ranging from 4 words to 12 words. I separated Ogden’s words into three lists of 12, based on Chen and Cowan’s findings about the average maximum number of words recalled, in order to provide the opportunity for maximum recall. These three lists were placed into Quizlet, a regularly used flashcard website.
With my subject group chosen, students aged 13-18, I further focused on those without learning disabilities, to address the gap in current research. Four groups of 10 individuals, grades 7-12, were randomly selected for separate study sessions in order to properly control the large number of participants. In a study session, the students were brought into a classroom and asked whether or not they had been diagnosed with a learning disability, in order to ensure the study group met the criteria. Then, they were given a writing utensil and four sheets of paper labeled Set 1, Set 2, Set 3 Practice, and Set 3. Each paper had 12 lines for presented words and lines for their name and grade level. Students were asked to sit in a position so that they could see the board clearly.
The main computer was connected to the classroom projector and sound system to aid in clarity. With the first study group, Set 1 was presented first. The order of set presentation was switched for each study group in order to eliminate a possible conflict of disengagement over the course of the study session. I explained the instructions and then we began. The students were given approximately 1.7 seconds per word. Once all 12 words had been shown they were told to flip over their Set 1 sheet and begin writing as many as they could remember. Then, once all students finished writing, I enabled the audio function and pulled Set 2 up on the screen, starting with the blank side of the flashcard. I used the same process as Set 1 for Set 2 to maintain consistency in reading time. Then, once finished with Set 2, the students were instructed to lay out the Set 3 practice and Set 3 sheets. With the audio function remaining on, the Set 3 words were shown, and students simultaneously wrote each down on the practice sheet. Then, once all 12 had been displayed, the participants were instructed to flip the practice sheet over and write the words they recalled on the Set 3 sheet. These handouts were collected and organized by participants.
In a synthesis of studies written by George A. Miller, an American psychologist known for founding the cognitive psychology field, subjects were presented with a series of digits, terms, and other testable variables, in order to determine the capacity of the working memory. The span of immediate memory, “the amount of information that an observer can retain,” was concluded to hold seven ‘chunks’ at one time (Miller, 1994). Chunks are a combination of digits or letters, such as words, and “therefore contain much more information per item” (Chen & Cowan, 2009). This study has become the cornerstone in working memory research, as “the lengths of word and digit lists that can be reproduced in immediate recall tasks are very similar” across multiple studies (Chen & Cowan, 2009). Miller accurately provided the ‘magic number’ for memorization of chunks, seven.
The average recall of all 40 students presented with the unisensory visual technique was found to be 6.825 words. This value is consistent with Miller’s findings, providing a baseline for the number of words these participants could recall without additional stimulus. The average number of terms retained utilizing the audiovisual technique was 7.925, which is approximately 1.1 more words than the unisensory set, and the average words recalled with the VAK technique was 7.65, around 0.825 more words than the visual technique. These final results demonstrate the increase in retention among healthy teenagers, bringing the average number of words recalled above the baseline number provided by Set 1 and George A. Miller.
The p values were calculated with a TI-84 plus graphing calculator with the matched pairs t-test function, in which I found p = 0.0000469 and p = 0.0147 for audiovisual and VAK respectively. Since both of these values are below α = 0.05, we have sufficient evidence that the average difference in audiovisual and VAK presentation with visual presentation is greater than zero. This means the evidence suggests that recall will improve with the use of cross-modal memorization techniques. We can also conclude that recall with audiovisual processes will improve word recall by between 0.589 and 1.611 words, and with VAK techniques, between 0.087 and 1.563 terms, compared to visual. From the confidence interval conducted, “we would expect the true population parameter to fall within [the previously stated] interval estimates 95% of the time” (“Statistics Dictionary,” n.d.).
The p value determined for the audiovisual set is significantly lower than that of the VAK set. This could be due to a variety of factors, but the most prevalent response noticed from the students, once the study was completed, was they had trouble remembering words in Set 3 (VAK) due to the multitasking aspect of reading and writing. They found that they did not have enough time to comprehend the words presented, as they were too focused on writing them down correctly. Though the length of time words remained on the screen had to be consistent for this particular study, this could be improved at home with more time to study the words. If given an adjustable time frame, I hypothesize that VAK retention would be as effective, if not more effective, than with the audiovisual presentation, as it would allow students to truly interpret their study materials.
The results from my study are consistent with those found in Quak et al.’s study in which they found “...recall is better for cross-modal objects compared to modality-specific objects (Delogu, Raffone, & Belardinelli, 2009; Goolkasian & Foos, 2005; Thompson & Paivio, 1994)” as well as the heightened working memory capacity when comparing cross-modal objects to unimodal objects (Saults & Cowan, 2007; Fougnie & Marois, 2011; Quak et al., 2015). The p-values, which are significantly lower than α = 0.05, demonstrate the proven improvement between visual presentation and audiovisual as well as VAK processes, which is why it can be concluded that multisensory learning techniques improve retention among healthy teenagers.
When conducting a study related to neuroscience there are a variety of limitations concerning uncontrollable aspects of thought processing. Were the students distracted by the art in the teachers’ classrooms? Did certain students pay closer attention or feel the need to try more than others? Many of these questions remain unanswered due to the lack of a controllable environment or the resources to eliminate outside variables. If conducting this study again, future researchers should implement a post-study survey to gauge the personality of the students and accuracy of their answers. This information would be helpful in determining which results should be disregarded and which can be confidently utilized in the researcher’s findings.
Along with the uncontrollable limitations, there are also variables that could have affected the results but were not tested. The varying attention spans of participants could have influenced the length of time focused as well as the depth of processing students exerted. In Xiaoyu Tang, Jinglong Wu, and Yong Shen’s study on the interactions between multisensory integration and attention they found that “endogenous attentional selectivity acts on multiple levels of multisensory processing and determines the extent to which simultaneous stimuli from different modalities can be integrated” (Tang et al., 2016). The important effect of attention on multisensory integration shows the necessity of considering this variable when analyzing results from future studies, though it was beyond the scope of my particular study.
Students may have also found that a different combination of sensory modalities would have had a more significant effect on their recall, due to their specific learning style. Since the most common and accessible techniques were tested—audiovisual and VAK—this could have left out certain individuals who learn best with a different combination of senses. Future research could incorporate a pre-test to determine the learning styles of students and organize their study design by groups of like learners.
This research study addresses improvement in students learning in an experimental environment with instructed and required focus. This aspect of my methodology may not maintain its validity in a home setting. When students leave school and study for tests, there are a variety of factors that can contribute to a lack of retention, besides just the memorization techniques. Though these processes may help teenagers retain information, they may be unmotivated to study, lack the necessary resources, or not have the time to provide the essential attention required. These implications are similar to the limitations, as they address factors that were not able to be controlled. Though it is up to the adolescents to motivate themselves to study, these multisensory techniques will improve the information they do recall when the time is found.
About the Author
Alma Russell is a freshman at Harvard College concentrating in Neuroscience and Mathematics.
References
Chen, Z., & Cowan, N. (2009). Core verbal working-memory capacity: The limit in words retained without covert articulation.
Quarterly Journal of Experimental Psychology, 62(7), 1420-1429. doi:10.1080/17470210802453977
Delogu, F., Raffone, A., & Belardinelli, M. O. (2009). Semantic encoding in working memory: Is there a (multi)modality effect?
Memory, 17(6), 655-663. doi:10.1080/09658210902998054
Fougnie, D., & Marois, R. (2011). What limits working memory capacity? Evidence for modality-specific sources to the
simultaneous storage of visual and auditory arrays. Journal of Experimental Psychology: Learning, Memory, and Cognition, 37(6), 1329-1341. doi:10.1037/a0024834
Miller, G. A. (1994). The magical number seven, plus or minus two: Some limits on our capacity for processing information.
Psychological Review, 101( 2), 343-352. doi:10.1037//0033-295x.101.2. 343
Saults, J. S., & Cowan, N. (2007). A central capacity limit to the simultaneous storage of visual and auditory arrays in working
memory. Journal of Experimental Psychology: General, 136( 4), 663-684. doi:10.1037/0096-3445.136.4.663
Statistics Dictionary. (n.d.). Retrieved February 26, 2019, from https://stattrek.com/statistics/dictionary.aspx?definition
=alternative hypothesis
Tang, X., Wu, J., & Shen, Y. (2016). The interactions of multisensory integration with endogenous and exogenous attention.
Neuroscience & Biobehavioral Reviews, 61, 208-224. doi:10.1016/j.neubi orev.2015.11.002
The Editors of Encyclopaedia Britannica. (2018, May 28). C.K. Ogden. Retrieved February 23, 2019, from
https://www.britannica.com/biography/C-K-Ogden
Quak, M., London, R. E., & Talsma, D. (2015, April 21). A multisensory perspective of working memory. Retrieved 2018,
October 25 from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC440 4829/
Research Advisor
Elise Ballinger
I chose the methodology of design-based research since the groups of tested students would be undergoing researcher-imposed learning strategies followed by observations in performance and retention. In determining what combinations of sensory modalities to test, I considered the most common strategies currently utilized by the high schoolers surveyed. The most prevalent method, with a 45.11% use rate, was found to be writing as well as reading, as in flash cards, written notes, study guides, etc. Based on these results I chose to focus on using visual presentation as a benchmark, measuring the improvement to audiovisual as well as visual, auditory, and kinesthetic (VAK) techniques.
I began by preparing the words that would be presented to the students by utilizing a randomizer with Charles Kay Ogden’s 850 basic English word list. Then, I proceeded to select the first 36 of the random words. Ogden, an English linguist, philosopher, and writer, advocated for the widespread employment of these basic words, as they could be used for practically all necessary language in day-to-day life (The Editors of Encyclopaedia Britannica, 2018). This ensured that the words would not come as shocking, foreign, or confusing to the students, eliminating a possible variable for error.
Zhijian Chen and Nelson Cowan, a biochemist and a professor specializing in working memory, respectively, conducted an experiment in 2005 to determine working memory capacity, with an experimental design of word lists ranging from 4 words to 12 words. I separated Ogden’s words into three lists of 12, based on Chen and Cowan’s findings about the average maximum number of words recalled, in order to provide the opportunity for maximum recall. These three lists were placed into Quizlet, a regularly used flashcard website.
With my subject group chosen, students aged 13-18, I further focused on those without learning disabilities, to address the gap in current research. Four groups of 10 individuals, grades 7-12, were randomly selected for separate study sessions in order to properly control the large number of participants. In a study session, the students were brought into a classroom and asked whether or not they had been diagnosed with a learning disability, in order to ensure the study group met the criteria. Then, they were given a writing utensil and four sheets of paper labeled Set 1, Set 2, Set 3 Practice, and Set 3. Each paper had 12 lines for presented words and lines for their name and grade level. Students were asked to sit in a position so that they could see the board clearly.
The main computer was connected to the classroom projector and sound system to aid in clarity. With the first study group, Set 1 was presented first. The order of set presentation was switched for each study group in order to eliminate a possible conflict of disengagement over the course of the study session. I explained the instructions and then we began. The students were given approximately 1.7 seconds per word. Once all 12 words had been shown they were told to flip over their Set 1 sheet and begin writing as many as they could remember. Then, once all students finished writing, I enabled the audio function and pulled Set 2 up on the screen, starting with the blank side of the flashcard. I used the same process as Set 1 for Set 2 to maintain consistency in reading time. Then, once finished with Set 2, the students were instructed to lay out the Set 3 practice and Set 3 sheets. With the audio function remaining on, the Set 3 words were shown, and students simultaneously wrote each down on the practice sheet. Then, once all 12 had been displayed, the participants were instructed to flip the practice sheet over and write the words they recalled on the Set 3 sheet. These handouts were collected and organized by participants.
In a synthesis of studies written by George A. Miller, an American psychologist known for founding the cognitive psychology field, subjects were presented with a series of digits, terms, and other testable variables, in order to determine the capacity of the working memory. The span of immediate memory, “the amount of information that an observer can retain,” was concluded to hold seven ‘chunks’ at one time (Miller, 1994). Chunks are a combination of digits or letters, such as words, and “therefore contain much more information per item” (Chen & Cowan, 2009). This study has become the cornerstone in working memory research, as “the lengths of word and digit lists that can be reproduced in immediate recall tasks are very similar” across multiple studies (Chen & Cowan, 2009). Miller accurately provided the ‘magic number’ for memorization of chunks, seven.
The average recall of all 40 students presented with the unisensory visual technique was found to be 6.825 words. This value is consistent with Miller’s findings, providing a baseline for the number of words these participants could recall without additional stimulus. The average number of terms retained utilizing the audiovisual technique was 7.925, which is approximately 1.1 more words than the unisensory set, and the average words recalled with the VAK technique was 7.65, around 0.825 more words than the visual technique. These final results demonstrate the increase in retention among healthy teenagers, bringing the average number of words recalled above the baseline number provided by Set 1 and George A. Miller.
The p values were calculated with a TI-84 plus graphing calculator with the matched pairs t-test function, in which I found p = 0.0000469 and p = 0.0147 for audiovisual and VAK respectively. Since both of these values are below α = 0.05, we have sufficient evidence that the average difference in audiovisual and VAK presentation with visual presentation is greater than zero. This means the evidence suggests that recall will improve with the use of cross-modal memorization techniques. We can also conclude that recall with audiovisual processes will improve word recall by between 0.589 and 1.611 words, and with VAK techniques, between 0.087 and 1.563 terms, compared to visual. From the confidence interval conducted, “we would expect the true population parameter to fall within [the previously stated] interval estimates 95% of the time” (“Statistics Dictionary,” n.d.).
The p value determined for the audiovisual set is significantly lower than that of the VAK set. This could be due to a variety of factors, but the most prevalent response noticed from the students, once the study was completed, was they had trouble remembering words in Set 3 (VAK) due to the multitasking aspect of reading and writing. They found that they did not have enough time to comprehend the words presented, as they were too focused on writing them down correctly. Though the length of time words remained on the screen had to be consistent for this particular study, this could be improved at home with more time to study the words. If given an adjustable time frame, I hypothesize that VAK retention would be as effective, if not more effective, than with the audiovisual presentation, as it would allow students to truly interpret their study materials.
The results from my study are consistent with those found in Quak et al.’s study in which they found “...recall is better for cross-modal objects compared to modality-specific objects (Delogu, Raffone, & Belardinelli, 2009; Goolkasian & Foos, 2005; Thompson & Paivio, 1994)” as well as the heightened working memory capacity when comparing cross-modal objects to unimodal objects (Saults & Cowan, 2007; Fougnie & Marois, 2011; Quak et al., 2015). The p-values, which are significantly lower than α = 0.05, demonstrate the proven improvement between visual presentation and audiovisual as well as VAK processes, which is why it can be concluded that multisensory learning techniques improve retention among healthy teenagers.
When conducting a study related to neuroscience there are a variety of limitations concerning uncontrollable aspects of thought processing. Were the students distracted by the art in the teachers’ classrooms? Did certain students pay closer attention or feel the need to try more than others? Many of these questions remain unanswered due to the lack of a controllable environment or the resources to eliminate outside variables. If conducting this study again, future researchers should implement a post-study survey to gauge the personality of the students and accuracy of their answers. This information would be helpful in determining which results should be disregarded and which can be confidently utilized in the researcher’s findings.
Along with the uncontrollable limitations, there are also variables that could have affected the results but were not tested. The varying attention spans of participants could have influenced the length of time focused as well as the depth of processing students exerted. In Xiaoyu Tang, Jinglong Wu, and Yong Shen’s study on the interactions between multisensory integration and attention they found that “endogenous attentional selectivity acts on multiple levels of multisensory processing and determines the extent to which simultaneous stimuli from different modalities can be integrated” (Tang et al., 2016). The important effect of attention on multisensory integration shows the necessity of considering this variable when analyzing results from future studies, though it was beyond the scope of my particular study.
Students may have also found that a different combination of sensory modalities would have had a more significant effect on their recall, due to their specific learning style. Since the most common and accessible techniques were tested—audiovisual and VAK—this could have left out certain individuals who learn best with a different combination of senses. Future research could incorporate a pre-test to determine the learning styles of students and organize their study design by groups of like learners.
This research study addresses improvement in students learning in an experimental environment with instructed and required focus. This aspect of my methodology may not maintain its validity in a home setting. When students leave school and study for tests, there are a variety of factors that can contribute to a lack of retention, besides just the memorization techniques. Though these processes may help teenagers retain information, they may be unmotivated to study, lack the necessary resources, or not have the time to provide the essential attention required. These implications are similar to the limitations, as they address factors that were not able to be controlled. Though it is up to the adolescents to motivate themselves to study, these multisensory techniques will improve the information they do recall when the time is found.
About the Author
Alma Russell is a freshman at Harvard College concentrating in Neuroscience and Mathematics.
References
Chen, Z., & Cowan, N. (2009). Core verbal working-memory capacity: The limit in words retained without covert articulation.
Quarterly Journal of Experimental Psychology, 62(7), 1420-1429. doi:10.1080/17470210802453977
Delogu, F., Raffone, A., & Belardinelli, M. O. (2009). Semantic encoding in working memory: Is there a (multi)modality effect?
Memory, 17(6), 655-663. doi:10.1080/09658210902998054
Fougnie, D., & Marois, R. (2011). What limits working memory capacity? Evidence for modality-specific sources to the
simultaneous storage of visual and auditory arrays. Journal of Experimental Psychology: Learning, Memory, and Cognition, 37(6), 1329-1341. doi:10.1037/a0024834
Miller, G. A. (1994). The magical number seven, plus or minus two: Some limits on our capacity for processing information.
Psychological Review, 101( 2), 343-352. doi:10.1037//0033-295x.101.2. 343
Saults, J. S., & Cowan, N. (2007). A central capacity limit to the simultaneous storage of visual and auditory arrays in working
memory. Journal of Experimental Psychology: General, 136( 4), 663-684. doi:10.1037/0096-3445.136.4.663
Statistics Dictionary. (n.d.). Retrieved February 26, 2019, from https://stattrek.com/statistics/dictionary.aspx?definition
=alternative hypothesis
Tang, X., Wu, J., & Shen, Y. (2016). The interactions of multisensory integration with endogenous and exogenous attention.
Neuroscience & Biobehavioral Reviews, 61, 208-224. doi:10.1016/j.neubi orev.2015.11.002
The Editors of Encyclopaedia Britannica. (2018, May 28). C.K. Ogden. Retrieved February 23, 2019, from
https://www.britannica.com/biography/C-K-Ogden
Quak, M., London, R. E., & Talsma, D. (2015, April 21). A multisensory perspective of working memory. Retrieved 2018,
October 25 from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC440 4829/
Research Advisor
Elise Ballinger
