The Effect of Age on Memory

Al-Qahtani, Abdulkhaleq A.

doi:10.5220/0008682601730177

Cited by 2 publications

(4 citation statements)

References 3 publications

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“…This study shows that generally, improving one's memory will require improving the processes through which one encodes information into the memory and using techniques that facilitate effective retrieval of the information. Faculty should internalize the practice of relating any new information they encounter and wish to keep to what they already know so that they can form mental images about the information (Al-Qahtani, 2018; Asperholm et al , 2020). This study showed that difficulty in classifying or grouping documents for storage (CP1) is as much a PIM challenge for faculty just as difficulty in naming files properly for storage (CP2).…”

Section: Discussionmentioning

confidence: 99%

“…Personal factors of age and gender relate to subfunctions of memory, and memory relates to refinding of certain types of information. There is sufficient evidence in the literature that human memory varies in human life course; it also differs in capacity and performance across gender, age, interest, motivation and training and other factors (Al-Qahtani, 2018; Asperholm et al , 2020).…”

Section: Literature Reviewmentioning

confidence: 99%

“…In many studies, age is often found to be negatively related to information processing, capacity to learn new things and ability to perform more than one task at a time, as well as shifting focus between different tasks. In a study, Al-Qahtani (2018) concluded that memory is not affected by age as a whole system, but that age can affect certain functions of the memory subcategories.…”

Section: Introductionmentioning

confidence: 99%

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Personal factors and the role of memory in faculty refinding of stored information

Nwagwu

Donkor

2022

LHT

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PurposeThe study examined the personal information management (PIM) challenges encountered by faculty in six universities in Ghana, their information refinding experiences and the perceived role of memory. The study tested the hypothesis that faculty PIM performance will significantly differ when the differences in the influence of personal factors (age, gender and rank) on their memory are considered.Design/methodology/approachThe study was guided by a sample survey design. A questionnaire designed based on themes extracted from earlier interviews was used to collect quantitative data from 235 faculty members from six universities in Ghana. Data analysis was undertaken with a discrete multivariate Generalized Linear Model to investigate how memory intermediates in the relationship between age, gender and rank, and, refinding of stored information.FindingsThe paper identified two subfunctions of refinding (Refinding 1 and Refinding 2) associated with self-confidence in information re-finding, and, memory (Memory 1 and Memory 2), associated with the use of complimentary frames to locate previously found and stored information. There were no significant multivariate effects for gender as a stand-alone variable. Males who were aged less than 39 could refind stored information irrespective of the memory class. Older faculty aged 40–49 who possess Memory 1 and senior lecturers who possess Memory 2 performed well in refinding information. There was a statistically significant effect of age and memory; and rank and memory.Research limitations/implicationsThis study was limited to faculty in Ghana, whereas the study itself has implications for demographic differences in PIM.Practical implicationsIdentifying how memory mediates the role of personal factors in faculty refinding of stored information will be necessary for the efforts to understand and design systems and technologies for enhancing faculty capacity to find/refind stored information.Social implicationsUnderstanding how human memory can be augmented by technology is a great PIM strategy, but understanding how human memory and personal factors interplay to affect PIM is more important.Originality/valuePIM of faculty has been extensively examined in the literature, and limitations of memory has always been identified as a constraint. Human memory has been augmented with technology, although the outcome has been very minimal. This study shows that in addition to technology augmentation, personal factors interplay with human memory to affect PIM. Discrete multivariate Generalized Linear Model applied in this study is an innovative way of addressing the challenges of assimilating statistical methodologies in psychosocial disciplines.

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Section: Discussionmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Personal factors and the role of memory in faculty refinding of stored information

Nwagwu

Donkor

2022

LHT

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“…There is a significant relationship between short-term and long-term memory performance in age range [14]. Short-term memory is affected by age as a result of slowing down the process of receiving and sending information to long-term memory [15]. There is a relationship between age differences in the accuracy of short and long-term memory [16].…”

Section: Introductionmentioning

confidence: 99%

The Effect of Age, Sleep Duration, Learning Duration, and Coffee Intake on Short-Term Memory

Chandra,

Istiqomah,

Rinda Wahyu Purnama

et al. 2023

JEMIS

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In the reality of life, learning requires a process of remembering. In the process of teaching and learning, memory is crucial. Sleep deprivation affects the process of remembering in learning. Memory is one of the important aspects that affect student performance in learning. In addition to sleep duration, the age factor can also affect short-term memory. This study wants to find out if age, sleep duration, and learning duration have an impact on short-term memory. This study incorporates elements of cognitive ergonomics because it measures short-term memory performance to assess how people process information and how they maintain it in their memory. Based on the results of multiple linear regression tests, the R Square value was 0.328 and the Adjusted R Square was 0.272. The age variable has a significance value of 0.001. The coefficient value on the age variable is 0.303 and is positive. This positive value indicates that increasing student age will increase the value of short-term memory. This shows that the higher the age of the student, the higher the ability in short-term memory. The sleep duration variable has no significant effect on short-term memory. The learning duration variable has no significant effect on short-term memory.

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The Effect of Age on Memory

Cited by 2 publications

References 3 publications

Personal factors and the role of memory in faculty refinding of stored information

Personal factors and the role of memory in faculty refinding of stored information

The Effect of Age, Sleep Duration, Learning Duration, and Coffee Intake on Short-Term Memory

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