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2 Atkinson and Shiffrin memory model. (From Atkinson, R. C. and Shiffrin, R. M. The Psychology of Learning and Motivation, 2, 89-195, 1968.)
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Our knowledge is a collection of our experiences, which expands daily as we experience new things. The way we imbue our surroundings and ourselves with meaning depends on the knowledge and understanding we have, and this knowledge depends on our memorization of what we have learned. In daily life, we take in new information and store it in our brai...
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... Amin & Malik [28] and Khishfe [29], [30] presented an analysis of theories that contribute to our understanding of memory retention and the recall process. They raised five models: Atkinson and Shiffrin's Memory Model, the Dual-coding theory of memory, Baddeley's Model of Working Memory, Cognitive Load Theory, and the Cognitive Theory of Multimedia Learning. ...
... Among its merits are developing approaches to lessen superfluous cognitive burden in learning and launching research into successful instructional design tactics. When content is given in a manner that does not connect to actual performance, however, the transfer of learning will be more difficult [28], [31]. ...
... This research is also based on the significance of instructional materials in any teaching-learning process in order to provide intervention materials to improve students' low achievement in Science education [4], [42] Due to the limited involvement of students with the campus, the classroom is frequently the only location for academic and social integration that may be connected with academic participation in the school. As previously stated, neither grade retention nor social promotion will serve students' needs [28], [44]. ...
Using strategic intervention materials (SIM) in Science class is essential for achieving students' needed competencies, which they could have succeeded in regular classroom instruction. This study examines the retention of concepts among Grade 11 learners in Central Philippines after exposure to teacher-made Strategic Intervention Materials (SIMs). It utilized the Quasi-Experimental Research Design, Post-test Post-Post-Test, Experimental Group only design. To determin0e the significant difference in the level of proficiency right after and a semester after exposure to SIMs intervention Wilcoxon signed-rank test for paired samples was employed. Results showed that the SIMs helped students exceed the core knowledge, skills, and understanding requirements. Learning is best transferred through authentic performance tasks which made retention of Science concepts evident.0
... Using GeoGebra helps in enhanced learnability as compared to traditional learning certain factors that affect memory retention as shown in Fig. 2. All the duplicate entries were deleted while selecting the valid factors. The finalized retention factors after discussion and deleting the duplicate entries are motivation (Amin & Malik, 2014), relevance (Boyd et al., 2019), confidence (Amin & Malik, 2014), and satisfaction (Hou & Wang, 2013) as shown in Table 3. So while designing GLA, these four parameters have been kept in mind so that the content is provided in such a way that an enhanced rate of memory retention is achieved. ...
... Using GeoGebra helps in enhanced learnability as compared to traditional learning certain factors that affect memory retention as shown in Fig. 2. All the duplicate entries were deleted while selecting the valid factors. The finalized retention factors after discussion and deleting the duplicate entries are motivation (Amin & Malik, 2014), relevance (Boyd et al., 2019), confidence (Amin & Malik, 2014), and satisfaction (Hou & Wang, 2013) as shown in Table 3. So while designing GLA, these four parameters have been kept in mind so that the content is provided in such a way that an enhanced rate of memory retention is achieved. ...
The teaching of Mathematics – in particular, Geometry, through conventional methods has been a challenging task for tutors. Augmented Reality (AR) based applications available in commercial space, have not followed any structured pedagogical approach in the designing process, and also do not ensure that the learning time of students is spent prolifically. In this paper, we explore the use of AR in mathematics for geometry education, to aid visualization of multidimensional objects and long-term retention of concepts by the learners. For designing an appropriate AR application it is necessary to identify some principles which support better memory retention of the students. The application has been specifically designed on the basis of identified principles affecting memory retention. We further explain the development of an AR-based Geometry Learning Assistant (AR-GLA), using a structural approach to pedagogical-design for teaching 3-dimensional geometry to higher school students through improved visualization and enhance their memory retention for related concepts. A sample of 54 K-12 students and 2 teachers with expertise in mathematics were part of the experiment. The students were divided into two different groups; one of the groups was taught with AR-based content whereas the other group was given Interactive Simulation (IS) based learning. The results illustrated that AR-based learning provides better retention of memory as compared to IS-based learning were tested over a period of two months.
... In general, there are two types of memory: the short-term memory and long-term memory. Information is retained for a relatively short period of time in short-term memory, with an average person's capacity ranging from seven to nine items (Amin & Malik, 2014). Long-term memory stores information for longer periods of time, even up to a lifetime. ...
... By paying attention to that information, it is stored in short-term memory which after rehearsal, can be encoded and stored in the long-term memory store. Adapted from (Amin & Malik, 2014). ...
Procedural memory is the memory of habits, involved in the acquisition and maintenance of new motor skills. The neural substrates underlying this memory are the basal ganglia (BG), a group of structures involved in motor and cognitive functions. The input nucleus of the BG is the striatum, earning it a central role in relaying information between the cortex and other subcortical structures, thus ensuring the selection and integration of cortical information within parallel functional loops. Procedural learning first follows a goal-directed behavior mediated by the associative loops, including the dorsomedial striatum (DMS), which is then transferred to an automatic behavior where habit is formed and mediated by the sensorimotor loops including the dorsolateral striatum (DLS). The anatomy and the evolution of the dynamics of the striatal networks has been well described during procedural learning, and the involvement of each striatal territory in a specific phase of learning established. However, how procedural learning is encoded at the level of the corticostriatal networks remains unknown.During my PhD work, we were interested in characterizing the dynamics of the corticostriatal networks involved in motor skill learning and determining the neural correlates responsible for the formation of this memory. We first used two-photon ex vivo calcium imaging to monitor the activity of the networks during the different phases of procedural learning. First we extracted the calcium responses of only medium spiny neurons (MSNs), the striatal output neurons. To distinguish MSNs from other striatal neurons, we developed a cell-sorting classifier based on the calcium responses of neurons and their morphology. We showed a specific reorganization of the DMS networks during the early phase, and the DLS during the late phase of motor skill learning. In DMS, the activity of the networks decreased after early training and returned to a basal level after late training. The main activity of the DMS networks was held by a group of highly active (HA) cells. In DLS, the reorganization of the activity was gradual and localized in small clusters of activity after late training. We then examined the properties of the HA cells in DMS and clusters in DLS. The existence of HA cells and clusters are directly correlated to the performance of the animals. Whole-cell patch-clamp recordings allowed us to characterize electrophysiological properties of HA bells and determine an increase of the synaptic weight of cingulate cortex inputs to HA cells in DMS after early learning. Anatomical tracing showed more robust changes in the DLS with an increase of the number of somatosensory projections to the DLS after late training. Using an AAV cFos-TRAP strategy coupled to chemogenetics, we inhibited HA and cluster cells, leading to impaired motor learning. These experiments thus highlighted the necessity of these cells in early and late phases of motor skill learning respectively.Next we wanted to explore if deficits in motor skill learning occur in a premotor-symptomatic phase of a mouse model of Huntington’s disease (HD), and if they would be associated to dysfunctions in the corticostriatal networks. We first showed deficits in the late phase of motor skill learning in a mouse model of HD. Using ex vivo two-photon calcium imaging, we explored the DMS and DLS networks and we observed an alteration of both networks in naïve HD animals and in addition, an absence of reorganization upon motor skill learning. These results confirm the importance of the reorganization of the networks in motor skill learning.Altogether, this work provides a new insight on the role of the corticostriatal networks and their reorganization in motor skill learning. The necessity of HA and cluster cells opens the door of the ‘engram’ world to the striatal networks.
... 16 There are various factors that can affect one's memory including: age, stress, sleep, nutrition and physical activity. 17 The research that was conducted by Horiuchi et al 18 in Cambodia in 2018 on the differences of the nutritional status in urban and rural areas of schoolage children found that the children in rural areas had a higher prevalence of stunting than urban areas, this was highly associated with the differences of food intake between the two regions. Another research that was conducted by Addiniya et al 19 in 2014 on the comparison of intelligence based on short-term memory tests in urban and rural students in Jatinangor Region using digit span forward, digit span backward and symbol digit modality tests found that the digit span backward and symbol digit modality tests in children in urban areas were scored higher than those children in rural areas. ...
... Internal factors include the quality and quantity of nutrient intake, sleep quality and physical activities. 17,25 While the external factors are stimulation or training. 26 Based on the distribution of the data it can be seen that the daily consumption of fish in rural areas was higher than in urban areas. ...
... Regular physical activities often has positive impact on short-term memory but it must be followed by adequate food consumption to optimize the subject's short-term memory. 17 External factors such as stimulation / repetitive exercise will improve the ability of short-term memory of the subject. 27 A research conducted by Sadikin was also supported by the research conducted by Sokolovic et al 28 in India of 1040 elementary school students who were stunted after a nutritional intervention for six months found that the short-term memory abilities, retrieval abilities, and visuospatial abilities were not significantly different before and after the intervention with the p value > 0.1. ...
Background: Inadequate chronic nutrition can cause disruption of bone growth and brain development. Impaired bone growth can cause stunting in children, and a disruption of brain development will affect cognitive function, one of them is short-term memory. This study aimed to compare the short-term memory between stunting and non stunting in urban and rural elementary school students in Kupang.Methods: This research used analytic observational method with cross sectional design conducted on urban and rural elementary school students in Kupang City. One hundred and sixty students who met the inclusion and exclusion criteria were selected using consecutive sampling method. Characteristics data were collected by the interview, while the stunting data was known by measuring height and assessed by WHO anthroplus application, short-term memory data was obtained from digit span test. Stunting is a nominal data scale, while the short-term memory is an ordinal data scale. This study was analyzed bivariately using chi-square test with significant p value ≤ 0.05.Results: Chi-square test results of short-term memory between stunting and non stunting in urban and rural elementary school students obtained p = 0.144, which means there is no significant difference in short-term memory between stunting and non stunting in urban and rural elementary school children in Kupang.Conclusions: There is no significant difference in short-term memory between stunting and non stunting in elementary school children, both in urban and rural areas of Kupang.
This study combined the principles of multimedia message design with an enclosing-rectangle scaffold to facilitate instruction on deriving the area of basic geometric shapes. A pretest/posttest/delayed-posttest design was used to compare the effectiveness of the enclosing-rectangle scaffold with that of conventional dissection/rearrangement methods among low-achieving seventh-grade students. These fifty-six low-achieving students were averagely assigned to one of two teaching methods. In immediate and delayed testing, an enclosing-rectangle scaffold proved significantly more effective than the conventional approach (posttest: F (1,53) = 16.148, p = <.001, η² = .234; delayed posttest: F (1,53) = 13.502, p = <.001, η² = .203). These findings demonstrate the effectiveness of stepwise visualisation within a coherent context in facilitating the selection, organisation, and integration of mathematical concepts. Given the ongoing challenges that students face in comprehending the formula for calculating the area of a trapezoid, there is a need for further research in this area to identify effective instructional approaches and strategies.
Smart and efficient application of DL algorithms in IoT devices can improve operational efficiency in healthcare, including tracking, monitoring, controlling, and optimization. In this paper, an artificial neural network (ANN), a structure of deep learning model, is proposed to efficiently work with small datasets. The contribution of this paper is two-fold. First, we proposed a novel approach to build ANN architecture. Our proposed ANN structure comprises on subnets (the group of neurons) instead of layers, controlled by a central mechanism. Second, we outline a prediction algorithm for classification and regression. To evaluate our model experimentally, we consider an IoT device used in healthcare i.e., an insulin pump as a proof-of-concept. A comprehensive evaluation of experiments of proposed solution and other classical deep learning models are shown on three small scale publicly available benchmark datasets. Our proposed model leverages the accuracy of textual data, and our research results validate and confirm the effectiveness of our ANN model.
Emotion has a substantial influence on the cognitive processes in humans, including perception, attention, learning, memory, reasoning, and problem solving. Emotion has a particularly strong influence on attention, especially modulating the selectivity of attention as well as motivating action and behavior. This attentional and executive control is intimately linked to learning processes, as intrinsically limited attentional capacities are better focused on relevant information. Emotion also facilitates encoding and helps retrieval of information efficiently. However, the effects of emotion on learning and memory are not always univalent, as studies have reported that emotion either enhances or impairs learning and long-term memory (LTM) retention, depending on a range of factors. Recent neuroimaging findings have indicated that the amygdala and prefrontal cortex cooperate with the medial temporal lobe in an integrated manner that affords (i) the amygdala modulating memory consolidation; (ii) the prefrontal cortex mediating memory encoding and formation; and (iii) the hippocampus for successful learning and LTM retention. We also review the nested hierarchies of circular emotional control and cognitive regulation (bottom-up and top-down influences) within the brain to achieve optimal integration of emotional and cognitive processing. This review highlights a basic evolutionary approach to emotion to understand the effects of emotion on learning and memory and the functional roles played by various brain regions and their mutual interactions in relation to emotional processing. We also summarize the current state of knowledge on the impact of emotion on memory and map implications for educational settings. In addition to elucidating the memory-enhancing effects of emotion, neuroimaging findings extend our understanding of emotional influences on learning and memory processes; this knowledge may be useful for the design of effective educational curricula to provide a conducive learning environment for both traditional “live” learning in classrooms and “virtual” learning through online-based educational technologies.
