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Research Article
Open Access Peer-reviewed

Cognitive Strategies, Visual-Spatial Abilities, and Memorization Efficacy among Stem Senior High School Students

Doloritos Mico B, Rosario Vincent P , Torrejos Chrestine B
American Journal of Educational Research. 2025, 13(4), 184-232. DOI: 10.12691/education-13-4-5
Received March 18, 2025; Revised April 20, 2025; Accepted April 27, 2025

Abstract

This study explores cognitive strategies, visual-spatial abilities, and memorization efficacy among 95 senior high school STEM students at the University of Mindanao, Matina Campus. The study employs meticulous quantitative analysis, utilizing Spearman correlation analysis and multiple linear regression models. The investigation revealed a moderate utilization of cognitive strategies among participants, favoring rehearsal over organization strategies. Meanwhile, visual-spatial abilities are found to be at an average proficiency level, with a strong inclination towards interpretation. Participants exhibit high level of memorization efficacy, with retrieval accuracy and retention rate outperforming recall speed. Contrary to previous studies, there was no significant relationship found between cognitive strategies and memorization efficacy, while a strong correlation was found between visual-spatial abilities and memorization efficacy, which underscores the importance of incorporating more visual-spatial learning experiences into educational curricula to enhance memory retention and foster academic success among senior high school STEM students.

1. Introduction

In the realm of education and cognitive psychology, one enduring issue has remained at the forefront: the effectiveness of memorization, particularly its impact on learning outcomes, garnering substantial attention in educational research. Recent data from standardized testing and assessments have shown a concerning decline in individuals’ memorization efficacy across various subjects 1, 2, 3, raising questions about the factors contributing to the diminishing effectiveness of memorization strategies in contemporary education. Building upon this concern, effective memorization is crucial. It forms the basis for developing higher-order thinking, critical analysis, and problem-solving skills necessary for navigating the complexities of science education 4. A prior investigation into learning strategies among East Asian students using PISA 2012 data revealed the multifaceted nature of memorization. Among the four identified learning strategy types, 'metacognitive strategies with memorization' predominated (50.70%), highlighting the intricate cognitive processes employed by East Asian students who integrate metacognition with memorization for higher academic achievement 5. This underscores the significance of exploring factors influencing memorization efficacy, not merely as an academic pursuit but as a means to unlock the potential of future scientists and innovators.

Notwithstanding the importance of memorization, educators and students alike grapple with persistent difficulties in efficiently memorizing complex scientific concepts. Recent statistical data show that despite the increasing emphasis on STEM education, students often need help with the intricate memorization demands of these subjects (National Center for Education Statistics, 2022). The expanding volume and complexity of scientific information necessitate innovative strategies to enhance memorization efficacy 6, 7. Additionally, the rise of digital learning tools and the shift to online education have transformed the learning landscape, demanding a nuanced exploration of the factors underlying effective memorization in the digital age 8, 9, 10. This study explores the intricate interplay of cognitive strategies, visual-spatial abilities, and memorization efficacy among senior high school STEM students. While existing literature suggests potential connections between these factors 11, 12, 13, the specific nature of their correlation with memorization efficacy remains unclear. By investigating these variables, this study aims to shed light on their potential influences and implications for instructional practices, contributing to the holistic development of future scientists and thinkers.

For the effectiveness of educational instruction, it is imperative to consider the constraints of the working memory, which has a limited capacity for retaining information, and therefore, instructional methods should be designed to mitigate the risk of cognitive overload 14. Access to solution steps allows learners to concentrate their finite working memory resources on learning about the deep structural features of the problems presented to them 15. Importantly, this knowledge can be applied to solve similar classes of problems. Notably, the worked example effect has become the most widely studied effect in Cognitive Load Theory research 16, 17. Cognitive strategies come into play as they enable individuals to manage and optimize cognitive load by selecting appropriate encoding methods 18, 19, 20. Visual-spatial abilities become paramount within this framework, as they provide a means to simplify complex concepts through visual representation, ultimately leading to a reduction in the cognitive load associated with memorization tasks 21, 22, aligning with the Dual Coding Theory proposed by Allan Paivio (1971) that combining verbal and non-verbal (visual) encoding enhances learning and memory retention.

This study scrutinizes two pivotal independent variables: cognitive strategies and visual-spatial abilities. The Levels of Processing Theory, proposed by Craik and Lockhart (1972), highlights the significance of engaging students in meaningful activities like elaboration and organization, emphasizing the cognitive strategies variable encompassing three crucial indicators: rehearsal, elaboration, and organization. Rehearsal involves repeating and practicing information and has been widely used as an indicator for various cognitive processes by previous researchers 23, 24, 25. Elaboration delves into deep information processing, wherein individuals link and connect new knowledge to existing schemas 26, 27 and has been a widely adopted gauge as well 27. Organization is another pivotal cognitive strategy that revolves around structuring information into meaningful frameworks 28 and has served as a marker for diverse cognitive processes in prior studies 29, 30, 31. These indicators have garnered recognition in prior research, validating their efficacy in assessing cognitive strategies in various educational contexts 32.

Following cognitive strategies are visual-spatial abilities encompassing a broad spectrum of skills essential for effectively comprehending and maneuvering spatial information. Rooted in the Environmental Enrichment Theory by Rosenzweig (1996), visual-spatial abilities are integral to cognitive functioning, playing a crucial role in tasks involving spatial reasoning and problem-solving. Within this study, visual-spatial abilities are discerned through three distinct indicators: spatial visualization, interpretation, and manipulation. Spatial visualization pertains to an individual's ability to mentally represent and manipulate spatial objects and structures 33 and has been a widely adopted gauge for assessing visual-spatial abilities 34, 35, 36. Interpretation emphasizes one's capacity to understand and extract meaning from visual-spatial information 37 and has been employed by numerous studies as an indicator as well 38, 39, 40. Manipulation delves into an individual's proficiency in mentally rotating and transforming spatial objects 41 and has also served as a standard metric 42, 43, 44. These indicators have received acclaim in academic literature, firmly establishing their status as valid and reliable measures of visual-spatial abilities 45.

Furthermore, memorization efficacy will assess the effectiveness of learning and cognitive performance. Memorization, a fundamental cognitive process involving the encoding and retrieval of information, serves as a cornerstone of learning and daily functioning 46 and is supported by established cognitive psychology and education research such as spaced repetition 47 and metacognition 48. Its efficacy plays a substantial role in influencing students’ academic performance, and three distinct indicators have been chosen to evaluate memorization efficacy comprehensively: retrieval accuracy, retention rate, and recall speed. Retrieval Accuracy examines an individual’s capacity to accurately recall and retrieve previously learned information 49 and has been a widely adopted gauge for assessing memorization efficacy in previous research 50, 51, 52, 53. Retention Rate focuses on an individual’s ability to retain information over time, reflecting the durability of memorized content 47 and has also found an extensive application as an indicator 54, 55, 56. Lastly, Recall Speed measures the swiftness with which an individual can retrieve memorized information, indicating the efficiency of memory recall processes 57 and has been frequently employed as a marker for memorization efficacy 58, 59. These carefully selected indicators provide a robust framework for comprehensively evaluating memorization efficacy among senior high school STEM students. By employing these indicators and their respective validated assessments, this study aims to advance the understanding of memorization processes and their implications for instructional practices in senior high school STEM education.

In recent years, several studies have delved into the factors influencing memorization efficacy among senior high school STEM students, shedding light on the complex interplay between cognitive strategies and visual-spatial abilities in the efficacy of memory. Almarzouki, Khan, Al-Mansour, Al-free, Abuznadah, and Althubaiti 60 conducted an experimental investigation targeting short-term information retention and examined the effectiveness of various cognitive strategies. Despite implementing approaches such as frequent quizzes and summarization during lectures, the study found no improvements in memorization efficacy. Similarly, Pilotti, Alkuhayli, and Ghazo 61 provided substantial evidence about the absence of a relationship between cognitive strategies and memorization, challenging traditional assumptions about the effectiveness of strategies like rote learning in attaining superior memory skills.

Concurrently, studies have explored the association between visual-spatial abilities and memorization efficacy. Macchitella, Romano, Iaia, Vizzi, Mammarella, and Angelelli 62 proposed a limited connection between visual-spatial abilities and memorization, while Badmus and Jita 63 suggested a significant correlation, especially in domains such as physics. Furthermore, findings by Zhang and Jerkinson 64 indicated the critical role of visual-spatial abilities in improving memory efficiency, particularly in specialized subjects such as biology, and the research conducted by Babu and Kalaiyarasan 65 provides additional evidence for this idea, showing that fostering visual-spatial skills lays the groundwork for executive functions and boosts the retention of information over time, especially within scientific fields.

However, despite these valuable insights, there remains a critical research gap in educational psychology, particularly in the context of senior high school STEM education. While these studies have explored the factors influencing memorization efficacy, they did not specifically investigate the relative influence of cognitive strategies, encompassing rehearsal, elaboration, and organization, along with visual-spatial abilities, including spatial visualization, interpretation, and manipulation, on memorization efficacy. This gap is significant as it hinders the extensive understanding of the complex interplay between these variables, making it urgent to investigate how these cognitive factors uniquely contribute to memorization efficacy among this demographic 66. Moreover, this study contributes to new knowledge by providing insights into the specific dynamics between cognitive strategies and visual-spatial abilities in predicting memorization efficacy. By discerning the relative strength of their predictive power, this research offers a nuanced understanding of the underlying cognitive processes involved in effective memorization among senior high school STEM students. The decision to conduct this study is justified by the need to move beyond the general examination of memorization efficacy and delve into the distinct contributions of cognitive strategies and visual-spatial abilities, ensuring that this research is not a repetition of prior studies but a targeted exploration of the unique factors impacting memorization in the context of senior high school STEM education.

Furthermore, this study holds significant importance in education and cognitive psychology by shedding light on the interplay between cognitive strategies, visual-spatial abilities, and memorization efficacy. Memorization, a foundational process in learning, directly impacts students’ academic performance and daily functioning. Understanding the relative influence of cognitive strategies and visual-spatial abilities on memorization efficacy is academically relevant and socially valuable. The findings of this research have the potential to revolutionize instructional practices, particularly in senior high school STEM education, by offering insights into tailored strategies that enhance students’ memorization skills. By linking the gap between theory and practice, this study aligns with the United Nations Sustainable Development Goals (Quality Education and Good Health and Well-being), as it contributes to the promotion of effective and equitable education, thus fostering cognitive development and overall well-being among students. The implications of this research extend beyond the classroom, with practical applications in cognitive enhancement programs that can positively impact people across different areas of their lives, thereby addressing the broader societal need for lifelong learning and cognitive well-being.

In light of these considerations, this study aims to assess how cognitive strategies and visual-spatial abilities influence the memorization skills of senior high school STEM students, potentially informing changes in educational practices. It will measure the cognitive strategies of respondents (rehearsal, elaboration, and organization), their visual-spatial abilities (visualization, interpretation, and spatial manipulation), and memorization efficacy (retrieval accuracy, retention rate, and recall speed). Additionally, it will investigate the link between cognitive strategies and memorization effectiveness and the correlation between visual-spatial abilities and memorization outcomes.

2. Method

Research Participants

The research respondents for this study consisted of 95 STEM students currently enrolled at the University of Mindanao Matina Campus in Davao City. This specific selection of respondents aligns with the methodology suggested by Davis (2020), which emphasizes the importance of considering the context and characteristics of the study population. By focusing on senior high school STEM students, the researchers examined the relevance of cognitive strategies and visual-spatial abilities in the educational context of science, technology, engineering, and mathematics disciplines. This approach is supported by the work of Johnson and Brown (2018), who highlight the importance of studying cognitive processes within domain-specific contexts.

In selecting research respondents, explicit inclusion and exclusion criteria were set. Only the senior high school STEM students currently enrolled at the University of Mindanao Matina Campus in Davao City participated in this study. This criterion ensured that the research sample was homogeneous in terms of academic level and field of study, enhancing the internal validity. Exclusion criteria will encompass undergraduate students, postgraduate students, and those pursuing non-STEM disciplines, as their experiences and cognitive processes may differ significantly from the STEM population under investigation. By delineating these criteria, the study adheres to rigorous standards and ensures that the selected respondents are the most relevant for addressing the research questions.

Research Instrument

This quantitative research employed a comprehensive set of questionnaires to measure cognitive strategies, visual-spatial abilities, and memorization efficacy among senior high school STEM students. Cognitive strategies were assessed using the Motivated Strategies for Learning Questionnaire (MLSQ) for rehearsal, elaboration, and organization, comprising 15 items that will prompt respondents to indicate the frequency with which they engage in specific cognitive strategies using a 5-point Likert scale, ranging from "1 = Not at all true of me" to "5 = Very true of me." In interpreting data, the responses were analyzed using the mean scores of each indicator of the variable cognitive strategy (rehearsal, elaboration, organization). The mean scores of each indicator were calculated by summing the responses to the relevant items and dividing them by the total number of items. Higher mean scores indicate a greater frequency of utilization in the respective cognitive strategy. A mean score ranging from 1.00 - 1.99 indicates low utilization, 2.00 - 3.99 indicates moderate utilization and 4.00 - 5.00 indicates high utilization in the cognitive strategy.

Visual-spatial abilities were evaluated through the Trail Making Test (TMT) for visualization, the Raven's Standard Progressive Matrices (RSPM) for interpretation, and the Mental Rotations Test (MRT) for manipulation. The TMT consists of two parts, Parts A and B, each comprising 25 circles distributed on a sheet of paper. In Part A, participants are instructed to connect numbered circles in ascending order (1-25), and Part B involves connecting circles alternating between numbers (1-13) and letters (A) in an ascending pattern. Completion times for both parts were recorded in seconds. To compute the mean score, the total completion times for each Part were summed across all participants and divided by the total number of participants. The interpretation of results followed established guidelines: Completion times around 29 seconds for Part A was considered average, while completion times exceeding 78 seconds suggested deficiency. Similarly, completion times around 75 seconds for Part B were considered average, with over 273 seconds indicating deficiency. Additionally, if most participants took around 90 seconds for Part A or 3 minutes for Part B, further evaluation may be warranted.

Meanwhile, the results were further assessed using RSPM, wherein participants were presented with a series of 24 matrices, each containing a missing piece or pattern. They were instructed to identify the missing piece or the pattern that logically completes each matrix. To respond, participants encircled the number (1-8) corresponding to the option they believed best completed the pattern. Interpretation of RSPM results was based on the number of correct responses and the complexity of the matrices completed. To calculate the mean score of the RSPM responses, the number of correct responses for each participant was converted into a percentage. Then, the total percentage scores across all participants were summed up and divided by the total number of participants.

Furthermore, for the MRT, students were presented with a series of 20 items, each containing a target shape and four options on the right. Participants were instructed to identify and encircle two boxes from the four choices corresponding to the two rotated versions of the target shape. Thus, each item had two correct answers. MRT results were interpreted based on the number of correct responses, reflecting participants' accuracy in manipulating spatial information. Higher scores indicated better performance, suggesting stronger spatial cognition and manipulation skills. To calculate the mean score, the total number of correct responses for each participant was converted into percentages, then summed across all participants, and divided by the total number of participants. A mean score ranging from 0 to 33 indicates low manipulation skills, a mean score between 34 to 66 represents average manipulation skills, while a mean score between 67 to 100 suggests high proficiency, demonstrating strong mental rotation abilities.

Memorization efficacy was gauged using the Rey Auditory Verbal Learning Test (RAVLT) for retrieval accuracy and retention rate with five trials and 15 items each, along with the Digit Symbol Substitution Test (DSST) for recall speed of 90 items. To conduct the RAVLT, the facilitator read the list of 15 words aloud, ensuring a consistent pace across each reading. This process was repeated five times, with each trial allowing the student to recall the words in any order. The scoring was based on the total number of correct words recalled across all five trials, providing insight into the students' retrieval accuracy and retention rate. Each student's score was converted into percentage to calculate the mean score for the RAVLT. Subsequently, these percentage scores were summed across all students and then divided by the total number of participants. A high mean score for RAVLT is 67 to 100, indicating strong retrieval accuracy and retention rate, suggesting that students can memorize and recall information effectively. An average mean score, typically in the range of 34 to 66, signifies moderate proficiency in verbal learning and memory skills. A low mean score, typically 0 to 33, points to challenges in retaining verbal information, indicating potential areas for improvement in memorization skills. This comprehensive interpretation offers insights into the broader learning capabilities within the study cohort and helps identify areas for further research or educational support.

Meanwhile, to conduct the DSST, students were given a worksheet containing symbols for each number. The facilitator administered a timer for 90 seconds, and students were instructed to draw the appropriate symbol for each number as quickly as possible. This time constraint was intended to test recall speed and memory processing under pressure. Scoring for the DSST was based on the total number of correct symbols drawn by the students, corresponding to 1 point each. This score measured the student's recall speed and accuracy in completing the task within the given time limit. To calculate the mean score for the DSST, the total scores of each student were converted into a percentage, summed up across all students, and divided by the total number of participants. A high mean score for the DSST ranging from 67 to 100 indicates that students, on average, are quick and accurate in recalling and drawing the correct symbols, demonstrating effective memorization and cognitive processing speed. An average mean score, typically in the range of 34 to 66, reflects moderate proficiency in recalling and drawing symbols, suggesting adequate cognitive processing speed with room for improvement in accuracy or speed. A low mean score, typically in the range of 0 to 33, suggests slower recall or higher error rates, indicating a need for additional support or practice in these areas. This comprehensive interpretation of the DSST scores provides insight into the overall recall speed and efficiency among the student group, allowing educators to identify strengths and weaknesses in memorization skills.

Content validity was established through an expert review of the questionnaires to confirm the validity of the research instruments and their alignment with the intended constructs of cognitive strategies, visual-spatial abilities, and memorization efficacy. Construct validity was assessed through factor analysis to confirm the underlying structure of the questionnaires. Internal consistency reliability was determined using Cronbach's alpha. This ensures that the items consistently measure the intended variables. Additionally, test-retest reliability was conducted with a subsample of 30 respondents over a two-week interval to assess the stability of the measurements over time, further enhancing the reliability of the data collected. These validity and reliability assessments upheld the integrity of the research instruments and the quality of the data gathered in this study.

Design and Procedure

The research design employed in this study was a quantitative cross-sectional correlational design. This design allowed for assessing the relationships between cognitive strategies, visual-spatial abilities, and memorization efficacy among senior high school STEM students at the University of Mindanao Matina Campus in Davao City. Data were collected over a specified timeframe without introducing any experimental interventions, enabling the examination of these relationships as they naturally occurred within the selected sample of respondents. This research design was consistent with the guidelines suggested by Smith (2019) for studying predictors of academic performance among student populations.

The data-gathering process began with obtaining official permission from the University of Mindanao Matina Campus administration. Subsequently, informed consent was sought from the selected senior high school STEM student respondents in accordance with ethical guidelines (APA, 2022). Once respondents provided consent, they were administered the set of questionnaires, which includes the Motivated Strategies for Learning Questionnaire (MLSQ), Raven’s Standard Progressive Matrices (RSPM), Trail Making Test (TMT), Mental Rotations Test (MRT), Rey Auditory Verbal Learning Test (RAVLT), and the Digit Symbol Substitution Test (DSST).

In alignment with ethical considerations outlined by the American Psychological Association (APA, 2022), strict measures were implemented to protect respondents’ rights and data privacy. Every participant was asked for informed consent to ensure they willingly participated in the study, and respondents were assured of their right to withdraw from the study at any point without facing any adverse consequences. The preservation of anonymity and confidentiality was ensured by providing individualized identifiers to respondents instead of relying on their personal data. Data was stored securely and used solely for research purposes. Statistical tools, including regression analysis, were applied to analyze the data, with a significance level set at .05. Through regression analysis, the study assessed the strength and direction of these relationships, offering valuable insights into the research questions posed by providing a rigorous examination of the relationships under investigation.

3. Results and Discussions

Cognitive Strategies of Senior High School STEM Students

Table 1 presents the mean scores and standard deviations delineating rehearsal, elaboration, and organization strategies among senior high school STEM students, as gauged by the provided questionnaire items. These mean scores elucidate the average level of involvement with each cognitive strategy, while standard deviations unveil the dispersion within the sample, offering insights into the diversity of cognitive approaches adopted by the participants in their learning endeavors. An overall mean score for cognitive strategies standing at 3.99 (SD = 0.60) suggests a moderate degree of utilization of various cognitive techniques among senior high school STEM students.

This consistent cognitive approach among senior high school STEM students extends notably to rehearsal strategies, as evidenced by a mean score of 4.28 (SD = 0.70), which is higher than the overall mean. This score indicates a high inclination towards practices like repeated recitation, which correspond well with statements extracted from the questionnaire. On the other hand, organization strategies received comparatively lower engagement among senior high school STEM students, as indicated by a mean score of 3.79 (SD = 0.77), which is lower than the overall mean. Although students demonstrate some propensity for techniques like outlining and using mnemonic devices, there is potential for systematic improvement in organizing course material.

In exploring the cognitive strategies employed by senior high school STEM students, the investigation revealed intriguing disparities among rehearsal, elaboration, and organization indicators. Notably, rehearsal emerged as the most prominently utilized strategy, with scholars like Tan, Eak, Ooi, and Abdullah 67 as well as Osarumwense and Omorogiuwa 68 affirming its prevalence in student study habits, particularly in content-heavy subjects like STEM. However, while rehearsal garners widespread adoption, the findings also unveiled a contrasting trend regarding organization strategies. Despite being acknowledged as beneficial for effective learning, as observed from the findings by Selvina, Fitrianawati, and Awae 69, organization strategies receive notably lower utilization among senior high STEM students, reflecting a lack of emphasis on these skills and in organizing course materials systematically, as noted by Wael, Asnur, and Ibrahim 70. Nonetheless, it is essential to recognize that contextual factors and individual differences may influence cognitive strategies, as highlighted by Abbasi, Tariverdizadeh, and Younesi 71, warranting a more focused investigation into the underlying determinants shaping students' learning approaches.

These results generally confirm the prevailing trends observed in prior research regarding the predominant use of rehearsal strategies and the comparatively lower utilization of organization techniques among students. The findings suggest that while students are adept at recitation, there is a need to enhance their skills in organizing and structuring information. This underscores the importance of adopting diverse instructional approaches to address the multifaceted cognitive strategy preferences observed among senior high school STEM students. From a policy perspective, these findings could inform the development of curriculum and teaching methods that promote a more balanced use of cognitive strategies, thereby enhancing students' learning outcomes in STEM subjects.

Visual-spatial Abilities of Senior High School STEM Students

Table 2 provides a detailed analysis of the performance of senior high school STEM students across three crucial indicators: visualization, interpretation, and manipulation, along with the overall mean score and standard deviation of visual-spatial abilities. The visual-spatial abilities demonstrate an average mean score of 57.99 (SD = 10.25), indicating the average proficiency level among senior high school STEM students in this domain.

To begin with, among the indicators, interpretation has the highest mean score of 76.97 (SD = 18.58), which is higher than the overall mean. This indicates a high proficiency level among senior high school STEM students in terms of their capability to comprehend and analyze complex data. On the contrary, the manipulation indicates a notably lower mean score of 28.24 (SD = 12.14), which is lower than the overall mean, indicating a deficiency among senior high school STEM students in terms of their ability to rotate and transform spatial objects mentally. However, it is essential to note that despite this clustering of scores around the mean, there remains a notable range of abilities among the students. Some may excel in manipulation tasks, while others may struggle somewhat.

Notably, the high mean scores in interpretation (x̄ = 76.97, SD = 18.58) align with previous research findings by Abas et al. 38 on visual-spatial abilities among students, indicating that students often exhibit strengths in analytical thinking and the ability to interpret visual information effectively. Meanwhile, the manipulation indicator presents a contrasting picture with its low mean scores (x̄ = 28.24, SD = 12.14), affirming the research study of Rahmawati, Dianhar, and Arifin 44, which suggests a prominent need for improvement in practical manipulation skills among students.

In brief, this research underscores the significance of visual-spatial abilities among senior high school STEM students. The research reveals that while these students demonstrate commendable strengths in interpretation, a notable area for improvement in manipulation exists. This finding can advocate for targeted interventions to nurture visual-spatial abilities to optimize the educational experience and outcomes for senior high school STEM students. Addressing this aspect holds potential for students' practical problem-solving capabilities and spatial awareness, thereby fostering a more well-rounded skill set crucial for success in STEM disciplines.

Memorization Efficacy of Senior High School STEM Students

Table 3 illustrates an in-depth exploration of memorization efficacy within the senior high school STEM student demographic, focusing on three vital indicators: recall speed, retention rate, and retrieval accuracy. The overall mean score of 83.78 (SD = 9.68) suggests a high level of memorization efficacy, reflecting the students' ability to retain and recall information effectively. These metrics serve as illuminating markers, offering nuanced insights into the students' adeptness in swiftly recalling, diligently retaining, and precisely retrieving information.

Based on the findings among senior high school STEM students, the retention rate and retrieval accuracy indicator stood out with a significantly higher level of performance in retaining and accurately retrieving information, with a mean score of 95.00 (SD = 10.49). This underscores the students' adeptness in accurately retaining and accessing information and hints at a pedagogical approach that prioritizes deep comprehension and fosters long-lasting knowledge retention, laying a solid foundation for academic success and future endeavors in STEM disciplines.

Conversely, among the indicators of memorization efficacy, recall speed emerges with the lower mean score of 72.56 (SD = 12.93), which is lower than the overall mean, which means students have a moderate level of efficiency in recalling information promptly. The relatively lower mean score for recall speed than other indicators underscores a potential area for targeted improvement in enhancing students' ability to access and retrieve information swiftly. Strategies such as mnemonic devices or speed-reading techniques can be explored to address this aspect of memorization efficacy and further optimize learning outcomes within the STEM education context.

The analysis of memorization efficacy among senior high STEM students yields findings consistent with prior research, with a mean score of 72.56 (SD = 12.93) for recall speed. The study's results echo observations made by Gerst, Cirino, Macdonald, Miciak, Yoshida, Woods, and Gibbs 72 regarding the variability in processing speed affecting tasks such as recall. This underscores the importance of interventions targeting improved information retrieval efficiency, as emphasized by Wang, Muenks, and Yan 73 in advocating for cognitive training programs. Conversely, the high mean score of 95.00 (SD = 10.49) for retention rate and retrieval accuracy mirrors findings from Listiana, Bahri, Jamaluddin, Muharni, and Malik 74 and McIntyre, Gundlach, and Graziano 75, who emphasize the critical role of effective memory retention in learning outcomes. These results are further supported by the studies of Nero and Zulkiply 76 and Ludwig and Rausch 77, highlighting the significance of accurate information retrieval for successful academic performance and problem-solving abilities. By aligning with existing literature, the study provides valuable insights into the importance of targeted interventions to optimize recall speed while recognizing the strengths in retention and retrieval accuracy among senior high STEM students.

In summary, the analysis of memorization efficacy among senior high STEM students underscores both strengths and opportunities for growth. While students demonstrate commendable abilities in retaining and accurately retrieving information, particularly evident in the high retention rate and retrieval accuracy, there remains room for improvement in recall speed. Addressing this aspect could enhance students' efficiency in accessing and recalling information swiftly, thereby optimizing learning outcomes within the STEM education context.

Relationship of Cognitive Strategies and Memorization Efficacy

Table 4 presents the correlations between participants’ cognitive strategies and memorization efficacy, aiming to address whether there is a significant relationship between the two variables. Spearman’s rho was utilized to assess the strength of the relationship between each independent variable, including rehearsal, elaboration, and organization, paired with the dependent variable, memorization efficacy. Based on the data, the overall correlation between cognitive strategies and memorization efficacy results in Spearman's rho coefficient of r = .018 with p = .859. This result indicates a negligible positive correlation that is not statistically significant. Therefore, there is no significant relationship between participants’ cognitive strategies and memorization efficacy.

The findings of Almarzouki et al. 60 provide additional evidence for the absence of a relationship between cognitive strategies and memorization efficacy. Their experimental investigation specifically targeted short-term information retention, examining the effectiveness of various cognitive strategies. Despite implementing approaches such as frequent quizzes and summarization during lectures, they found that these strategies did not notably improve memorization efficacy. Moreover, their study highlighted that factors like mind-wandering and attention deficits during lectures had a detrimental effect on the student's information retention. These insights suggest that cognitive strategies possess no effectiveness in enhancing memorization efficacy without addressing broader factors such as attention and engagement.

Furthermore, the study by Pilotti et al. 61 provides substantial evidence that there is no relationship between cognitive strategies and memorization efficacy. Their investigation into rote memorization practices in Chinese education compared to problem-solving approaches in the United States suggests that the connection between cognitive strategies and memorization outcomes may be more intricate than previously assumed. Despite the assumption that rote learning leads to superior memory skills, the findings suggest an ambiguous relationship, challenging the traditional understanding of the effectiveness of cognitive strategies in enhancing memorization.

Focusing on the individual indicators, the Spearman correlation analysis revealed no significant relationship between the indicators of cognitive strategies (rehearsal, elaboration, organization) and the memorization efficacy measures (recall speed, retention rate, and retrieval accuracy). Specifically, for rehearsal, the positive negligible correlation with recall speed (r = .013, p = .903) and negative negligible correlation to retention rate (r = -.022, p = .834) imply that repeating information is not sufficient to enhance memory performance within this study’s context. Similarly, the negative negligible correlation to elaboration showed no significant correlation with recall speed (r = -.063, p = .545) and retention rate (r = -.098, p = .346). Additionally, the negative negligible correlation of organization did not exhibit a significant correlation with recall speed (r = -.017, p = .867) and retention rate (r = -.059, p = .573). These findings suggest that, within this study, the examined cognitive strategies did not show statistically significant associations with memorization efficacy measures.

The findings of this study are supported by the Levels of Processing Theory introduced by Craik and Lockhart (1972), proposing that the depth of processing during encoding determines memory retention. For instance, information processed more deeply through semantic analysis and meaningful connections is more likely to be retained in memory compared to shallow, surface-level processing. Despite the presence of cognitive strategies, the lack of correlation between these strategies and memorization efficacy persists, highlighting the influence of depth of processing as proposed by the Levels of Processing Theory.

In summary, the results investigate the relationship between cognitive strategies and memorization efficacy. Through an analysis of various cognitive techniques, including rehearsal, elaboration, and organization, the research reveals a lack of significant correlation between these strategies and the effectiveness of memorization. Despite their implementation, cognitive strategies do not markedly enhance memorization outcomes. The study underscores the complexity of the relationship between cognitive strategies and memorization efficacy, highlighting the need for other approaches to understanding how various factors contribute to successful memory retention.

Relationship of Visual-spatial Abilities and Memorization Efficacy

Table 5 illustrates the correlations between students’ visual-spatial abilities and memorization efficacy, aiming to ascertain the significant relationship between these variables. Spearman’s rho is utilized to evaluate this relationship, pairing the indicators of visual-spatial abilities (visualization, interpretation, and manipulation) with the indicators of memorization efficacy (recall speed, retention rate, and retrieval accuracy). The Spearman’s correlation analysis reveals a significant correlation between visual-spatial abilities and memorization efficacy, with a Spearman’s rho coefficient of r = .403 and a significant level of p = .000, indicating a low positive correlation that is statistically significant. This underscores a high connection between students’ visual-spatial abilities and their effectiveness in memorization tasks.

The findings revealed a significant positive correlation, indicating that stronger visual-spatial abilities contribute to more efficient memorization. This underscores the pivotal role of visual-spatial abilities in aiding students' capacity to retain and retrieve information effectively. Importantly, the Babu et al. 65 study further supports this notion, demonstrating that nurturing visual-spatial abilities establishes a foundation for executive functions and enhances long-term memory, particularly in scientific disciplines.

The findings are congruent with the recent research by Zhang et al. 64, indicating the critical role of visual-spatial abilities in improving memory efficiency, especially in biology education, where traditional assessments often emphasize rote memorization. To foster deeper learning, educators are urged to transition towards assessing higher-level cognitive abilities through visual communication evaluations. This shift not only assesses comprehension but also underscores the potential for growth and improvement in visual-spatial abilities, which are crucial for grasping intricate biological concepts. Emphasizing visual communication in assessments has the potential to shift students’ perceptions of biology and facilitate the development of advanced cognitive abilities. By harnessing visual-spatial abilities, educators can enhance memory efficiency and create more enriching learning environments, empowering students to take control of their learning.

In addition to the findings of the study, Macchitella et al. 62 propose a limited connection between visual-spatial abilities and memorization efficacy, emphasizing the role of other cognitive factors like verbal reasoning skills and working memory capacity. This notion prompts further investigation into the complexity of cognitive processes in learning and memory. Nonetheless, prior research, notably the ex post facto research by Badmus et al. 63, supports the assertion of a significant correlation between visual-spatial abilities and memorization efficacy, particularly in physics. Their synthesis of data from various studies underscores the crucial role of visual-spatial abilities in enhancing memory retention and recall speed across different domains, reinforcing the novelty and importance of the findings. Despite divergent perspectives, these consistent findings highlight the importance of acknowledging visual-spatial abilities’ impact on memory processes.

The correlation analysis reveals that visualization has a statistically significant positive correlation with recall speed (r = .286, p = .005) and retention rate and retrieval accuracy (r = .267, p = .009), indicating a meaningful association between strong visualization skills and faster recall speeds along with improved retention and retrieval accuracy. Similarly, interpretation also demonstrates a significant positive correlation with recall speed (r = .360, p = .000) and retention rate and retrieval accuracy (r = .248, p = .015), suggesting that adept interpretation skills are linked with quicker recall and enhanced retention with retrieval accuracy. Conversely, manipulation shows a negligible correlation with recall speed (r = .191, p = .063) and almost no correlation with retention rate and retrieval accuracy (r = .043, p = .678), implying that the ability to manipulate information may not significantly influence recall speed or retention rate with retrieval accuracy.

Moreover, the results exhibit a strong correlation between visual-spatial abilities and memorization efficacy, echoing the principles of the Dual Coding Theory proposed by Allan Paivio (1971), which posits that utilizing both verbal and visual information enhances learning outcomes, and the findings underscore the significance of visual-spatial abilities in memory retention. Individuals proficient in visual-spatial abilities tend to manipulate visual information effectively, creating vivid mental representations that aid in memory consolidation and recall. Moreover, the strong correlation observed aligns with the theory’s emphasis on integrating verbal and visual learning strategies to optimize learning outcomes. However, it is essential to note that while these results support the theory, there may be instances where other factors, such as motivation levels, prior knowledge, or individual cognitive differences, influence memorization efficacy independently of visual-spatial abilities. Nonetheless, the overall pattern of the findings remains in accordance with the fundamental principles of the Dual Coding Theory, emphasizing the importance of multimodal instructional approaches for enhancing memory retention and learning outcomes.

In summary, the study confirms a significant correlation between visual-spatial abilities and memorization efficacy, aligning with existing research that emphasizes their pivotal role in memory efficiency. However, conflicting findings suggest the need for further exploration into the cognitive processes underlying this relationship. Nonetheless, prior research provides robust support for the significant association between visual-spatial abilities and memorization efficacy, underlining the importance of effectively integrating verbal and visual learning strategies to optimize learning outcomes.

Influence of Cognitive Strategies and Visual-Spatial Abilities to Memorization Efficacy

Table 6 delves into the influence of cognitive strategies and visual-spatial abilities on memorization efficacy among senior high school STEM students. Examining the coefficients pertaining to cognitive strategies reveals intriguing insights into their influence on memorization efficacy. The unstandardized coefficient of B = 2.191 suggests a positive relationship, indicating that an increase in cognitive strategy utilization corresponds to a higher level of memorization efficacy. However, the associated significance level of p = .161 exceeds the conventional threshold of .05, leading to the retention of the null hypothesis and indicating a lack of statistical significance. Thus, the observed relationship may not be reliably attributable to cognitive strategies in this context.

Conversely, visual-spatial abilities demonstrate a stronger predictive relationship with memorization efficacy. The unstandardized coefficient of B = 0.396 indicates a positive association, suggesting enhanced visual-spatial abilities are associated with greater memorization efficacy. Significantly, the associated significance level of p = .000 falls well below the .05 threshold, steering into rejecting the null hypothesis and signifying a strong and statistically significant influence of visual-spatial abilities and memorization efficacy in this study.

These findings resonate with existing literature emphasizing the critical role of visual-spatial abilities in shaping learning outcomes. Studies by Kubik, Del Missier, and Mäntylä 59 and Yousif, Rosenberg, and Keil 78 corroborate the results, highlighting the significance of spatial cognition in memory processes. However, contrary evidence from the study by Heald, Lengyel, and Wolpert 79 suggests that the relationship between cognitive strategies and memorization efficacy may vary depending on contextual factors. Nevertheless, the robust findings of this study persist in emphasizing the paramount importance of visual-spatial abilities in memory processes. Building upon the theoretical framework proposed by Baddeley and Hitch’s model of working memory 80 provides further support, positing that the visuospatial sketchpad, a component of working memory, plays a pivotal role in retaining and manipulating visual and spatial information. Thus, despite the contrasting evidence presented, this study’s conclusions remain steadfast, offering valuable insights for educational practice and future research endeavors.

These findings are drawn from the Environmental Enrichment Theory by Rosenzweig 81, which underscores the significance of exposure to diverse visual stimuli in enhancing cognitive functions, including memory; the results suggest that visual-spatial abilities play a pivotal role in facilitating efficient memorization. This theory elucidates how individuals encode and retrieve information based on the richness of their environmental experiences, which include visual elements such as shapes, colors, and spatial arrangements. It posits that individuals exposed to enriched environments with varied visual stimuli are better equipped to encode and retrieve information effectively, as emphasized by Diamond, Krech, and Rosenzweig 82, thereby highlighting the crucial influence of visual-spatial abilities in the memorization process.

In summary, the findings of this study underscore the importance of incorporating visual-spatial learning experiences into educational curricula to enhance students’ memory retention and promote academic success.

4. Conclusions and Recommendations

This research, focusing on 95 senior high school STEM students at the University of Mindanao, Matina Campus, has uncovered significant insights in exploring the influence of cognitive strategies and visual-spatial abilities in memorization efficiency. To answer the first research question, "What is the level of the cognitive strategies among the respondents, in terms of rehearsal, elaboration, and organization?" the findings revealed a moderate degree of utilization of various cognitive techniques, with a strong inclination towards rehearsal strategies and a comparatively lower utilization towards organization strategies.

To answer the second research question, "To what extent do participants exhibit proficiency in visual-spatial abilities, particularly in their capacity to visualize, interpret, and manipulate spatial objects?" the findings revealed an average proficiency level in visual-spatial abilities, particularly in their interpretation capacity, which indicates a relatively high proficiency level among students. Manipulation abilities, on the other hand, indicate a deficiency among the participants.

To answer the third research question, "To what extent do participants exhibit memorization efficacy, as indicated by their performance in retrieval accuracy, retention rate, and recall speed?" the findings revealed a high level of memorization efficacy, reflecting the students' significantly higher level of performance to retain and retrieve information effectively; on the other hand, recall speed reveals a moderate level of efficiency in recalling information promptly.

Furthermore, in addressing the fourth research question, "Is there a significant relationship between participants' cognitive strategies and their memorization efficacy?" the results indicate an absence of a significant relationship. This conclusion is drawn from the negligible positive correlation observed, which does not attain statistical significance. In contrast, when exploring the fifth research question, "Does participants' performance on visual-spatial ability assessments correlate significantly with their memorization efficacy?" the findings underscore a compelling and noteworthy association between visual-spatial abilities and the efficiency of memorization tasks. This assertion is supported by the substantial correlation that bears statistical significance and suggests a meaningful connection between visual-spatial abilities and memorization efficacy within the study cohort.

To answer the sixth question, "Among the variables studied, cognitive strategies and visual-spatial abilities, which one demonstrates stronger influence towards memorization efficacy among the participants in the study?" the variables studied revealed that visual-spatial abilities had greater influence towards memorization efficacy among the study participants compared to cognitive strategies. This underscores the importance of visual-spatial abilities in the process of memorization. Although cognitive strategies positively correlate with memorization efficacy, their influence is eclipsed by the firm and statistically significant association observed with visual-spatial abilities. Therefore, visual-spatial abilities play a more influential role in determining memorization efficacy in this study cohort.

The findings of the research on the level of cognitive strategies, visual-spatial abilities, and memorization efficacy among senior high school STEM students reveal several recommendations that can be made to address the identified areas of concern. For cognitive strategies, specifically organization, students can benefit from tools and resources for effective time management, such as planners or digital calendars, to assist them in prioritizing tasks and efficiently managing their workload efficiently. Regarding visual-spatial abilities, integrating technology-based tools and applications, such as virtual reality simulations or 3D modeling software, can offer students immersive experiences that enhance their manipulation abilities. Additionally, for memorization efficacy, encouraging a collaborative and nurturing learning environment where students can engage in peer-to-peer learning, group discussions, and knowledge sharing can enhance their recall speed.

Stakeholders, including educators, industry professionals, and experts in STEM fields, play a pivotal role in supporting students' development in these areas. To address low organizational skills among students, educators can integrate organizational tools like digital planners and task management apps into the curriculum. Moreover, engaging industry professionals, including engineers, scientists, and technology experts, can provide practical contexts for enhancing manipulation skills among students by showcasing real-world applications of visual-spatial concepts that bridge the gap between theoretical knowledge and practical skills. Additionally, collaborative efforts among stakeholders can foster environments conducive to improving recall speed, offering resources such as memory enhancement workshops and tutoring services to support students in overcoming challenges in this area. Through these collaborative endeavors, students can gain valuable insights from professionals outside academia, enhancing their understanding of how STEM concepts are utilized in real-world scenarios and fostering a culture of continuous improvement in their academic pursuits.

For future researchers, it is essential to consider methodological improvements to enhance the validity and reliability of findings in similar studies. Increasing sample sizes and employing longitudinal research designs can provide a more comprehensive understanding of the long-term effects of interventions targeting cognitive strategies, visual-spatial abilities, and memorization efficacy. Additionally, integrating innovative technologies, such as virtual reality simulations and eye-tracking devices, can offer new insights into the underlying mechanisms of these cognitive processes. Collaborative research efforts across disciplines can further enrich the study of these variables, contributing to the advancement of educational practices and student outcomes in STEM education.

APPENDIX A

Thesis/Capstone Title Proposal

APPENDIX B

Assignment of Research Personnel

APPENDIX C

Letter to Adviser

APPENDIX D

Letter to Validators

APPENDIX E

Letter to Data Analyst/Statistician

APPENDIX F

Endorsement for Thesis Outline Defense

APPENDIX G

Sample Letter of Invitation to the Panel Member for Outline Defense and Final Defense

APPENDIX H

Questionnaire

APPENDIX I

Questionnaire Validation Sheets

APPENDIX J

Sample Tabulation and Computation of Data

APPENDIX K

Endorsement for Thesis Final Defense

APPENDIX L

Thesis Evaluation Form (Title, Outline, Final)

APPENDIX M

CTE Research Routing Form

APPENDIX N

Consent Form for Undergraduate Thesis Utilization

APPENDIX O

Turnitin Originality Report

APPENDIX P

Grammarly Report

APPENDIX Q

References

[1]  Pillado, I. A., Futalan, M. C. Z., & Comighud, S. M. T. (2020). Factors on memory retention: Effect on students’ academic performance. Zenodo (CERN European Organization for Nuclear Research).
In article      
 
[2]  Read, S., Comas-Herrera, A., & Grundy, E. (2019). Social isolation and memory decline in later-life. The Journals of Gerontology: Series B, 75(2), 367–376.
In article      View Article  PubMed
 
[3]  Schneider, F., Horowitz, A. B., Lesch, K., & Dandekar, T. (2020). Delaying memory decline: Different options and emerging solutions. Translational Psychiatry, 10(1).
In article      View Article  PubMed
 
[4]  Daher, W., Diab, H., & Rayan, A. (2023). Artificial intelligence generative tools and conceptual knowledge in problem solving in chemistry. Information, 14(7), 409.
In article      View Article
 
[5]  Wu, Y., Carstensen, C. H., & Lee, J. (2019). A New perspective on memorization practices among East Asian students based on PISA 2012. Educational Psychology, 40(5), 643–662.
In article      View Article
 
[6]  Chen, H., & Yang, J. (2020). Multiple exposures enhance both item memory and contextual memory over time. Frontiers in Psychology, 11.
In article      View Article  PubMed
 
[7]  Darling-Hammond, L., Flook, L., Cook-Harvey, C. M., Barron, B., & Osher, D. (2019). Implications for educational practice of the science of learning and development. Applied Developmental Science, 24(2), 97–140.
In article      View Article
 
[8]  Farias-Gaytan, S., Aguaded, I., & Ramírez-Montoya, M. S. (2023). Digital transformation and digital literacy in the context of complexity within higher education institutions: A Systematic literature review. Humanities & Social HultbergSciences Communications, 10(1).
In article      View Article
 
[9]  Lodge, J. M., Kennedy, G., Lockyer, L., Arguel, A., & Pachman, M. (2018). Understanding difficulties and resulting confusion in learning: An Integrative review. Frontiers in Education, 3.
In article      View Article
 
[10]  Sun, T., & Kim, J. (2022). The Effects of online learning and task complexity on students’ procrastination and academic performance. International Journal of Human-computer Interaction, 39(13), 2656–2662.
In article      View Article
 
[11]  Moussaoui, H., Mahmoudi, K., Marragh, H., & Hamza, M. (2023). Comparison of cognitive learning strategies of dental students at the beginning and at the end of their university course. OAlib, 10(08), 1–9.
In article      View Article
 
[12]  Pearson, J., & Keogh, R. (2019). Redefining visual working memory: A Cognitive-Strategy, Brain-Region approach. Current Directions in Psychological Science, 28(3), 266–273.
In article      View Article
 
[13]  Rea, S. D., Wang, L., Muenks, K., & Yan, V. X. (2022). Students can (mostly) recognize effective learning, so why do they not do it? Journal of Intelligence, 10(4), 127.
In article      View Article  PubMed
 
[14]  Hultberg, P. T., Calonge, D. S., & Lee, A. E. S. (2018). Promoting long-lasting learning through instructional design. the Journal of Scholarship of Teaching and Learning, 18(3).
In article      View Article
 
[15]  Peng, Y., & Tullis, J. G. (2020). Theories of intelligence influence self-regulated study choices and learning. Journal of Experimental Psychology: Learning, Memory and Cognition, 46(3), 487–496.
In article      View Article  PubMed
 
[16]  Hanham, J., Castro-Alonso, J. C., & Chen, O. (2023). Integrating cognitive load theory with other theories, within and beyond educational psychology. British Journal of Educational Psychology.
In article      View Article  PubMed
 
[17]  Van Gog, T., & Rummel, N. (2010). Example-based learning: Integrating cognitive and social-cognitive research perspectives. Educational Psychology Review, 22(2), 155–174.
In article      View Article
 
[18]  Castro-Alonso, J. C., De Koning, B. B., Fiorella, L., & Paas, F. (2021). Five strategies for optimizing instructional materials: Instructor and learner-managed cognitive load. Educational Psychology Review, 33(4), 1379–1407.
In article      View Article  PubMed
 
[19]  Costley, J. (2020). Using cognitive strategies overcomes cognitive load in online learning environments. Interactive Technology and Smart Education, 17(2), 215–228.
In article      View Article
 
[20]  Luo, L. (2022). Identifying Self-Regulation Strategies Students Use When Cognitive Load Occurs. In https://digitalcommons.usu.edu/etd/8613/
In article      
 
[21]  Castro-Alonso, J. C., Ayres, P., & Sweller, J. (2019). Instructional visualizations, cognitive load theory, and visuospatial processing. In Springer eBooks (pp. 111–143).
In article      View Article
 
[22]  Naert, L., Bonato, M., & Fias, W. (2018). Asymmetric spatial processing under cognitive load. Frontiers in Psychology, 9.
In article      View Article  PubMed
 
[23]  Himmer, L., Schönauer, M., Heib, D. P. J., Schabus, M., & Gais, S. (2019). Rehearsal initiates systems memory consolidation, sleep makes it last. Science Advances, 5(4).
In article      View Article  PubMed
 
[24]  Oberauer, K. (2019). Is rehearsal an effective maintenance strategy for working memory? Trends in Cognitive Sciences, 23(9), 798–809.
In article      View Article  PubMed
 
[25]  Zhang, Z., Zhou, C., Ma, J., Lin, Z., Zhou, J., Yang, H., & Zhao, Z. (2021). Learning to rehearse in long sequence memorization. arXiv (Cornell University). http://export.arxiv.org/pdf/2106.01096
In article      
 
[26]  Bartsch, L. M., Loaiza, V. M., Jäncke, L., Oberauer, K., & Lewis-Peacock, J. A. (2019). Dissociating refreshing and elaboration and their impacts on memory. NeuroImage, 199, 585–597.
In article      View Article  PubMed
 
[27]  Bartsch, L. M., & Oberauer, K. (2021). The Effects of elaboration on working memory and long-term memory across age. Journal of Memory and Language, 118, 104215.
In article      View Article
 
[28]  Liu, J., Xiang, P., McBride, R. E., & Chen, H. (2019). Self-regulated learning strategies and achievement goals among preservice physical education teachers. European Physical Education Review, 26(2), 375–391.
In article      View Article
 
[29]  Kabulska, Z., & Lingnau, A. (2022). The Cognitive structure underlying the organization of observed actions. Behavior Research Methods, 55(4), 1890–1906.
In article      View Article  PubMed
 
[30]  Secchi, D., & Cowley, S. J. (2018). Modeling organizational cognition: The Case of impact factor. Journal of Artificial Societies and Social Simulation, 21(1).
In article      View Article
 
[31]  Turi, J. A., Sorooshian, S., & Javed, Y. (2019). Impact of cognitive learning factors on sustainable organizational development. Heliyon, 5(9), e02398.
In article      View Article  PubMed
 
[32]  Akpur, U. (2021). The Predictive level of cognitive and meta-cognitive strategies on academic achievement. International Journal of Research in Education and Science, 593–607.
In article      View Article
 
[33]  Lowrie, T., Logan, T., & Hegarty, M. (2019). The Influence of spatial visualization training on students’ spatial reasoning and mathematics performance. Journal of Cognition and Development, 20(5), 729–751.
In article      View Article
 
[34]  Chikha, A. B., Khacharem, A., Trabelsi, K., & Bragazzi, N. L. (2021). The Effect of spatial ability in learning from static and dynamic visualizations: A Moderation analysis in 6-year-old children. Frontiers in Psychology, 12.
In article      View Article  PubMed
 
[35]  Novitasari, D., Risfianty, D. K., Triutami, T. W., Wulandari, N. P., & Tyaningsih, R. Y. (2021). The Relation between spatial reasoning and creativity in solving geometric problems. Journal of Physics, 1776(1), 012007.
In article      View Article
 
[36]  Novitasari, D., Nasrullah, A., Triutami, T. W., Apsari, R. A., & Silviana, D. (2021). High level of visual-spatial intelligence’s students in solving PISA geometry problems. Journal of Physics.
In article      View Article
 
[37]  Liu, J. (2013). Visual images interpretive strategies in multimodal texts. Journal of Language Teaching and Research, 4(6).
In article      View Article
 
[38]  Abas, S. (2019). Reading the world – teaching visual analysis in higher education. Journal of Visual Literacy, 38(1–2), 100–109.
In article      View Article
 
[39]  Torka, N. (2019). Honesty and genuine happiness. Or why soft healers make stinking wounds (Dutch proverb). British Journal of Guidance & Counselling, 47(2), 200–209.
In article      View Article
 
[40]  Tsang, K. K., & Besley, T. (2020). Visual inquiry in educational research. Beijing International Review of Education.
In article      View Article
 
[41]  Crompton, H., Grant, M. R., & Shraim, K. Y. H. (2018). Technologies to enhance and extend children’s understanding of geometry: A Configurative thematic synthesis of literature. Journal of Educational Technology & Society, 21(1), 59–69
In article      
 
[42]  Lowrie, T., Logan, T., Harris, D., & Hegarty, M. (2018). The Impact of an intervention program on students’ spatial reasoning: Student engagement through mathematics-enhanced learning activities. Cognitive Research: Principles and Implications, 3(1).
In article      View Article  PubMed
 
[43]  Lane, D., & Sorby, S. A. (2021). Bridging the gap: Blending spatial skills instruction into a technology teacher preparation programme. International Journal of Technology and Design Education, 32(4), 2195–2215.
In article      View Article
 
[44]  Rahmawati, Y., Dianhar, H., & Arifin, F. (2021). Analyzing students’ spatial abilities in chemistry learning using 3D virtual representation. Education Sciences, 11(4), 185.
In article      View Article
 
[45]  Khine, M. S. (2017). Spatial cognition: Key to STEM success. In Springer eBooks (pp. 3–8).
In article      View Article
 
[46]  Frankenmolen, N., Overdorp, E. J., Fasotti, L., Claassen, J. A., Kessels, R. P. C., & Oosterman, J. M. (2018). Memory strategy training in older adults with subjective memory complaints: A Randomized controlled trial. Journal of the International Neuropsychological Society, 24(10), 1110–1120.
In article      View Article  PubMed
 
[47]  Ebbinghaus, H. (2013). Memory: A Contribution to experimental psychology. PubMed.
In article      View Article  PubMed
 
[48]  Flavell, J. H. (1979). Metacognition and cognitive monitoring: A New area of cognitive–developmental inquiry. American Psychologist, 34(10), 906–911.
In article      View Article
 
[49]  Juba, B., & Le, H. S. (2019). Precision-recall versus accuracy and the role of large data sets. Conference on Artificial Intelligence, 33(01), 4039–4048.
In article      View Article
 
[50]  Badinlou, F., Kormi-Nouri, R., & Knopf, M. (2018). A Study of retrieval processes in action memory for school-aged children: The Impact of recall period and difficulty on action memory. Journal of Cognitive Psychology.
In article      View Article
 
[51]  Fordyce, A. L. (2023). Examining the effects of retrieval practice on memory for temporal-contextual information. Figshare.
In article      
 
[52]  Frankenstein, A. N., Udeogu, O. J., McCurdy, M. P., Sklenar, A. M., & Leshikar, E. D. (2022). Exploring the relationship between retrieval practice, self-efficacy, and memory. Memory & Cognition, 50(6), 1299–1318.
In article      View Article  PubMed
 
[53]  Wasserman, J., Polack, C. W., Casado, C., Brunel, M., Haj, M. E., & Miller, R. R. (2020). Effects on memory of early testing and accuracy assessment for central and contextual content. Journal of Cognitive Psychology, 32(7), 598–614.
In article      View Article  PubMed
 
[54]  Martini, M., Zamarian, L., Sachse, P., Martin, C., & Delazer, M. (2018). Wakeful resting and memory retention: a study with healthy older and younger adults. Cognitive Processing, 20(1), 125–131.
In article      View Article  PubMed
 
[55]  Zerr, C., Berg, J. J., Nelson, S. M., Fishell, A. K., Savalia, N. K., & McDermott, K. B. (2018). Learning efficiency: Identifying individual differences in learning rate and retention in healthy adults. Psychological Science, 29(9), 1436–1450.
In article      View Article  PubMed
 
[56]  Radvansky, G. A., Doolen, A. C., Pettijohn, K. A., & Ritchey, M. (2022). A New look at memory retention and forgetting. Journal of Experimental Psychology: Learning, Memory, and Cognition, 48(11), 1698–1723.
In article      View Article  PubMed
 
[57]  Albalawi, H. I., & Alnajashi, S. (2022). Recall of vocabulary from a second language: Picture Naming vs. Word Definition. Journal of Educational and Psychological Studies, 16(4), 330–342.
In article      View Article
 
[58]  Gong, D., Draschkow, D., & Nobre, A. C. (2023). Focusing attention in long-term and working memory improves recall and guides perception. Journal of Vision, 23(9), 5103.
In article      View Article
 
[59]  Kubik, V., Del Missier, F., & Mäntylä, T. (2020). Spatial ability contributes to memory for delayed intentions. Cognitive Research, 5(1).
In article      View Article  PubMed
 
[60]  Almarzouki, H. S., Khan, M. A., Al-Mansour, M., Al-Jifree, H. M., Abuznadah, W., & Althubaiti, A. (2023). Effectiveness of Cognitive Strategies on Short-Term Information Retention: An Experimental study. Health Professions Education. https://hpe.researchcommons.org/journal/vol9/iss3/2
In article      View Article
 
[61]  Pilotti, M., Alkuhayli, H., & Ghazo, R. A. (2021). Memorization practice and academic success in Saudi undergraduate students. Learning & Teaching in Higher Education: Gulf Perspectives, 18(1), 19–31.
In article      View Article
 
[62]  Macchitella, L., Tosi, G., Romano, D., Iaia, M., Vizzi, F., Mammarella, I. C., & Angelelli, P. (2023). Visuo-spatial working memory and mathematical skills in children: A Network analysis study. Behavioral Sciences, 13(4), 294.
In article      View Article  PubMed
 
[63]  Badmus, O. T., & Jita, L. C. (2022). Pedagogical implication of spatial visualization ability: A Correlate of students' achievements in physics. Journal of Turkish Science Education.
In article      View Article
 
[64]  Zhang, K. E., & Jenkinson, J. (2024). The Visual science communication toolkit: Responding to the need for visual science communication training in undergraduate life sciences education. Education Sciences, 14(3), 296.
In article      View Article
 
[65]  Babu, R., & Kalaiyarasan, G. (2019). Effectiveness of visual spatial intelligence based instructional materials to enhance the achievements of the secondary school students. Think India (New Delhi), 22(3), 2262–2268.
In article      View Article
 
[66]  Liu, S., Wei, W., Yuan, C., Peyre, H., & Zhao, J. (2021). Visual–spatial ability predicts academic achievement through arithmetic and reading abilities. Frontiers in Psychology, 11.
In article      View Article  PubMed
 
[67]  Tan, S. F., E A. D., Ooi, L. H., & Abdullah, A. C. (2021). Relationship between learning strategies and academic performance: A Comparison between accreditation of prior experiential learning (APEL) and regular entry undergraduates. AAOU Journal, 16(2), 226–238.
In article      View Article
 
[68]  Osarumwense, J. H., & Omorogiuwa, K. O. (2020). Contribution of cognitive learning strategy components to students’ academic achievement in Mathematics. International Journal of Mathematics and Statistics Invention, 8(7), 51–58.
In article      
 
[69]  Selvina, Fitrianawati, M., & Awae, A. (2023). Unleashing creative potential: The Impact of Self-Organized Learning Environments (SOLE) on fifth grade students’ creative thinking skills. Journal of Pedagogy and Education Science, 2(02), 124–131.
In article      View Article
 
[70]  Wael, A., Asnur, M. N. A., & Ibrahim, I. (2018). Exploring students’ learning strategies in speaking performance. IJoLE (International Journal of Language Education), 2(1), 65.
In article      View Article
 
[71]  Abbasi, F. K., Tariverdizadeh, H., & Younesi, J. (2022). A Comparative study on the effectiveness of cognitive and metacognitive learning strategies in goal orientation. Journal of Positive School Psychology, 6(5), 9971–9980. https://journalppw.com/index.php/jpsp/article/view/14201
In article      
 
[72]  Gerst, E. H., Cirino, P. T., Macdonald, K. T., Miciak, J., Yoshida, H., Woods, S. P., & Gibbs, M. C. (2020). The Structure of processing speed in children and its impact on reading. Journal of Cognition and Development, 22(1), 84–107.
In article      View Article  PubMed
 
[73]  Wang, L., Muenks, K., & Yan, V. X. (2023). Interventions to promote retrieval practice: Strategy knowledge predicts intent, but perceived cost predicts usage. Journal of Educational Psychology, 115 (1070–1086).
In article      View Article
 
[74]  Listiana, L., Bahri, A., Jamaluddin, A. B., Muharni, A., & Malik, W. H. (2023). Enhancing cognitive retention of different academic abilities undergraduate students through PBLRQA Strategy. In Advances in social science, education and humanities research (pp. 259–268).
In article      View Article
 
[75]  McIntyre, M. M., Gundlach, J. L., & Graziano, W. G. (2021). Liking guides learning: The Role of interest in memory for STEM topics. Learning and Individual Differences, 85, 101960.
In article      View Article
 
[76]  Nero, C. A., & Zulkiply, N. (2021). The Effects of retrieval practice across levels of thinking and retention interval on reading comprehension. Asian Journal of University Education, 17(4), 288.
In article      View Article
 
[77]  Ludwig, S., & Rausch, A. (2022). The Relationship between problem-solving behaviour and performance – Analysing tool use and information retrieval in a computer-based office simulation. Journal of Computer Assisted Learning, 39(2), 617–643.
In article      View Article
 
[78]  Yousif, S., Rosenberg, M. D., & Keil, F. C. (2021). Using space to remember: Short-term spatial structure spontaneously improves working memory. Cognition, 214, 104748.
In article      View Article  PubMed
 
[79]  Heald, J. B., Lengyel, M., & Wolpert, D. M. (2023). Contextual inference in learning and memory. Trends in Cognitive Sciences, 27(1), 43–64.
In article      View Article  PubMed
 
[80]  Baddeley, A., & Hitch, G. J. (1974). Working memory. In Psychology of Learning and Motivation (pp. 47–89).
In article      View Article
 
[81]  Rosenzweig, M. R. (1965). Environmental complexity, cerebral change, and behavior. American Psychologist, 21(4), 321–332.
In article      View Article  PubMed
 
[82]  Diamond, M. C., Krech, D., & Rosenzweig, M. R. (1964). The Effects of an enriched environment on the histology of the rat cerebral cortex. Journal of Comparative Neurology (1911), 123(1), 111–119.
In article      View Article  PubMed
 

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Normal Style
Doloritos Mico B, Rosario Vincent P, Torrejos Chrestine B. Cognitive Strategies, Visual-Spatial Abilities, and Memorization Efficacy among Stem Senior High School Students. American Journal of Educational Research. Vol. 13, No. 4, 2025, pp 184-232. https://pubs.sciepub.com/education/13/4/5
MLA Style
B, Doloritos Mico, Rosario Vincent P, and Torrejos Chrestine B. "Cognitive Strategies, Visual-Spatial Abilities, and Memorization Efficacy among Stem Senior High School Students." American Journal of Educational Research 13.4 (2025): 184-232.
APA Style
B, D. M. , P, R. V. , & B, T. C. (2025). Cognitive Strategies, Visual-Spatial Abilities, and Memorization Efficacy among Stem Senior High School Students. American Journal of Educational Research, 13(4), 184-232.
Chicago Style
B, Doloritos Mico, Rosario Vincent P, and Torrejos Chrestine B. "Cognitive Strategies, Visual-Spatial Abilities, and Memorization Efficacy among Stem Senior High School Students." American Journal of Educational Research 13, no. 4 (2025): 184-232.
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[1]  Pillado, I. A., Futalan, M. C. Z., & Comighud, S. M. T. (2020). Factors on memory retention: Effect on students’ academic performance. Zenodo (CERN European Organization for Nuclear Research).
In article      
 
[2]  Read, S., Comas-Herrera, A., & Grundy, E. (2019). Social isolation and memory decline in later-life. The Journals of Gerontology: Series B, 75(2), 367–376.
In article      View Article  PubMed
 
[3]  Schneider, F., Horowitz, A. B., Lesch, K., & Dandekar, T. (2020). Delaying memory decline: Different options and emerging solutions. Translational Psychiatry, 10(1).
In article      View Article  PubMed
 
[4]  Daher, W., Diab, H., & Rayan, A. (2023). Artificial intelligence generative tools and conceptual knowledge in problem solving in chemistry. Information, 14(7), 409.
In article      View Article
 
[5]  Wu, Y., Carstensen, C. H., & Lee, J. (2019). A New perspective on memorization practices among East Asian students based on PISA 2012. Educational Psychology, 40(5), 643–662.
In article      View Article
 
[6]  Chen, H., & Yang, J. (2020). Multiple exposures enhance both item memory and contextual memory over time. Frontiers in Psychology, 11.
In article      View Article  PubMed
 
[7]  Darling-Hammond, L., Flook, L., Cook-Harvey, C. M., Barron, B., & Osher, D. (2019). Implications for educational practice of the science of learning and development. Applied Developmental Science, 24(2), 97–140.
In article      View Article
 
[8]  Farias-Gaytan, S., Aguaded, I., & Ramírez-Montoya, M. S. (2023). Digital transformation and digital literacy in the context of complexity within higher education institutions: A Systematic literature review. Humanities & Social HultbergSciences Communications, 10(1).
In article      View Article
 
[9]  Lodge, J. M., Kennedy, G., Lockyer, L., Arguel, A., & Pachman, M. (2018). Understanding difficulties and resulting confusion in learning: An Integrative review. Frontiers in Education, 3.
In article      View Article
 
[10]  Sun, T., & Kim, J. (2022). The Effects of online learning and task complexity on students’ procrastination and academic performance. International Journal of Human-computer Interaction, 39(13), 2656–2662.
In article      View Article
 
[11]  Moussaoui, H., Mahmoudi, K., Marragh, H., & Hamza, M. (2023). Comparison of cognitive learning strategies of dental students at the beginning and at the end of their university course. OAlib, 10(08), 1–9.
In article      View Article
 
[12]  Pearson, J., & Keogh, R. (2019). Redefining visual working memory: A Cognitive-Strategy, Brain-Region approach. Current Directions in Psychological Science, 28(3), 266–273.
In article      View Article
 
[13]  Rea, S. D., Wang, L., Muenks, K., & Yan, V. X. (2022). Students can (mostly) recognize effective learning, so why do they not do it? Journal of Intelligence, 10(4), 127.
In article      View Article  PubMed
 
[14]  Hultberg, P. T., Calonge, D. S., & Lee, A. E. S. (2018). Promoting long-lasting learning through instructional design. the Journal of Scholarship of Teaching and Learning, 18(3).
In article      View Article
 
[15]  Peng, Y., & Tullis, J. G. (2020). Theories of intelligence influence self-regulated study choices and learning. Journal of Experimental Psychology: Learning, Memory and Cognition, 46(3), 487–496.
In article      View Article  PubMed
 
[16]  Hanham, J., Castro-Alonso, J. C., & Chen, O. (2023). Integrating cognitive load theory with other theories, within and beyond educational psychology. British Journal of Educational Psychology.
In article      View Article  PubMed
 
[17]  Van Gog, T., & Rummel, N. (2010). Example-based learning: Integrating cognitive and social-cognitive research perspectives. Educational Psychology Review, 22(2), 155–174.
In article      View Article
 
[18]  Castro-Alonso, J. C., De Koning, B. B., Fiorella, L., & Paas, F. (2021). Five strategies for optimizing instructional materials: Instructor and learner-managed cognitive load. Educational Psychology Review, 33(4), 1379–1407.
In article      View Article  PubMed
 
[19]  Costley, J. (2020). Using cognitive strategies overcomes cognitive load in online learning environments. Interactive Technology and Smart Education, 17(2), 215–228.
In article      View Article
 
[20]  Luo, L. (2022). Identifying Self-Regulation Strategies Students Use When Cognitive Load Occurs. In https://digitalcommons.usu.edu/etd/8613/
In article      
 
[21]  Castro-Alonso, J. C., Ayres, P., & Sweller, J. (2019). Instructional visualizations, cognitive load theory, and visuospatial processing. In Springer eBooks (pp. 111–143).
In article      View Article
 
[22]  Naert, L., Bonato, M., & Fias, W. (2018). Asymmetric spatial processing under cognitive load. Frontiers in Psychology, 9.
In article      View Article  PubMed
 
[23]  Himmer, L., Schönauer, M., Heib, D. P. J., Schabus, M., & Gais, S. (2019). Rehearsal initiates systems memory consolidation, sleep makes it last. Science Advances, 5(4).
In article      View Article  PubMed
 
[24]  Oberauer, K. (2019). Is rehearsal an effective maintenance strategy for working memory? Trends in Cognitive Sciences, 23(9), 798–809.
In article      View Article  PubMed
 
[25]  Zhang, Z., Zhou, C., Ma, J., Lin, Z., Zhou, J., Yang, H., & Zhao, Z. (2021). Learning to rehearse in long sequence memorization. arXiv (Cornell University). http://export.arxiv.org/pdf/2106.01096
In article      
 
[26]  Bartsch, L. M., Loaiza, V. M., Jäncke, L., Oberauer, K., & Lewis-Peacock, J. A. (2019). Dissociating refreshing and elaboration and their impacts on memory. NeuroImage, 199, 585–597.
In article      View Article  PubMed
 
[27]  Bartsch, L. M., & Oberauer, K. (2021). The Effects of elaboration on working memory and long-term memory across age. Journal of Memory and Language, 118, 104215.
In article      View Article
 
[28]  Liu, J., Xiang, P., McBride, R. E., & Chen, H. (2019). Self-regulated learning strategies and achievement goals among preservice physical education teachers. European Physical Education Review, 26(2), 375–391.
In article      View Article
 
[29]  Kabulska, Z., & Lingnau, A. (2022). The Cognitive structure underlying the organization of observed actions. Behavior Research Methods, 55(4), 1890–1906.
In article      View Article  PubMed
 
[30]  Secchi, D., & Cowley, S. J. (2018). Modeling organizational cognition: The Case of impact factor. Journal of Artificial Societies and Social Simulation, 21(1).
In article      View Article
 
[31]  Turi, J. A., Sorooshian, S., & Javed, Y. (2019). Impact of cognitive learning factors on sustainable organizational development. Heliyon, 5(9), e02398.
In article      View Article  PubMed
 
[32]  Akpur, U. (2021). The Predictive level of cognitive and meta-cognitive strategies on academic achievement. International Journal of Research in Education and Science, 593–607.
In article      View Article
 
[33]  Lowrie, T., Logan, T., & Hegarty, M. (2019). The Influence of spatial visualization training on students’ spatial reasoning and mathematics performance. Journal of Cognition and Development, 20(5), 729–751.
In article      View Article
 
[34]  Chikha, A. B., Khacharem, A., Trabelsi, K., & Bragazzi, N. L. (2021). The Effect of spatial ability in learning from static and dynamic visualizations: A Moderation analysis in 6-year-old children. Frontiers in Psychology, 12.
In article      View Article  PubMed
 
[35]  Novitasari, D., Risfianty, D. K., Triutami, T. W., Wulandari, N. P., & Tyaningsih, R. Y. (2021). The Relation between spatial reasoning and creativity in solving geometric problems. Journal of Physics, 1776(1), 012007.
In article      View Article
 
[36]  Novitasari, D., Nasrullah, A., Triutami, T. W., Apsari, R. A., & Silviana, D. (2021). High level of visual-spatial intelligence’s students in solving PISA geometry problems. Journal of Physics.
In article      View Article
 
[37]  Liu, J. (2013). Visual images interpretive strategies in multimodal texts. Journal of Language Teaching and Research, 4(6).
In article      View Article
 
[38]  Abas, S. (2019). Reading the world – teaching visual analysis in higher education. Journal of Visual Literacy, 38(1–2), 100–109.
In article      View Article
 
[39]  Torka, N. (2019). Honesty and genuine happiness. Or why soft healers make stinking wounds (Dutch proverb). British Journal of Guidance & Counselling, 47(2), 200–209.
In article      View Article
 
[40]  Tsang, K. K., & Besley, T. (2020). Visual inquiry in educational research. Beijing International Review of Education.
In article      View Article
 
[41]  Crompton, H., Grant, M. R., & Shraim, K. Y. H. (2018). Technologies to enhance and extend children’s understanding of geometry: A Configurative thematic synthesis of literature. Journal of Educational Technology & Society, 21(1), 59–69
In article      
 
[42]  Lowrie, T., Logan, T., Harris, D., & Hegarty, M. (2018). The Impact of an intervention program on students’ spatial reasoning: Student engagement through mathematics-enhanced learning activities. Cognitive Research: Principles and Implications, 3(1).
In article      View Article  PubMed
 
[43]  Lane, D., & Sorby, S. A. (2021). Bridging the gap: Blending spatial skills instruction into a technology teacher preparation programme. International Journal of Technology and Design Education, 32(4), 2195–2215.
In article      View Article
 
[44]  Rahmawati, Y., Dianhar, H., & Arifin, F. (2021). Analyzing students’ spatial abilities in chemistry learning using 3D virtual representation. Education Sciences, 11(4), 185.
In article      View Article
 
[45]  Khine, M. S. (2017). Spatial cognition: Key to STEM success. In Springer eBooks (pp. 3–8).
In article      View Article
 
[46]  Frankenmolen, N., Overdorp, E. J., Fasotti, L., Claassen, J. A., Kessels, R. P. C., & Oosterman, J. M. (2018). Memory strategy training in older adults with subjective memory complaints: A Randomized controlled trial. Journal of the International Neuropsychological Society, 24(10), 1110–1120.
In article      View Article  PubMed
 
[47]  Ebbinghaus, H. (2013). Memory: A Contribution to experimental psychology. PubMed.
In article      View Article  PubMed
 
[48]  Flavell, J. H. (1979). Metacognition and cognitive monitoring: A New area of cognitive–developmental inquiry. American Psychologist, 34(10), 906–911.
In article      View Article
 
[49]  Juba, B., & Le, H. S. (2019). Precision-recall versus accuracy and the role of large data sets. Conference on Artificial Intelligence, 33(01), 4039–4048.
In article      View Article
 
[50]  Badinlou, F., Kormi-Nouri, R., & Knopf, M. (2018). A Study of retrieval processes in action memory for school-aged children: The Impact of recall period and difficulty on action memory. Journal of Cognitive Psychology.
In article      View Article
 
[51]  Fordyce, A. L. (2023). Examining the effects of retrieval practice on memory for temporal-contextual information. Figshare.
In article      
 
[52]  Frankenstein, A. N., Udeogu, O. J., McCurdy, M. P., Sklenar, A. M., & Leshikar, E. D. (2022). Exploring the relationship between retrieval practice, self-efficacy, and memory. Memory & Cognition, 50(6), 1299–1318.
In article      View Article  PubMed
 
[53]  Wasserman, J., Polack, C. W., Casado, C., Brunel, M., Haj, M. E., & Miller, R. R. (2020). Effects on memory of early testing and accuracy assessment for central and contextual content. Journal of Cognitive Psychology, 32(7), 598–614.
In article      View Article  PubMed
 
[54]  Martini, M., Zamarian, L., Sachse, P., Martin, C., & Delazer, M. (2018). Wakeful resting and memory retention: a study with healthy older and younger adults. Cognitive Processing, 20(1), 125–131.
In article      View Article  PubMed
 
[55]  Zerr, C., Berg, J. J., Nelson, S. M., Fishell, A. K., Savalia, N. K., & McDermott, K. B. (2018). Learning efficiency: Identifying individual differences in learning rate and retention in healthy adults. Psychological Science, 29(9), 1436–1450.
In article      View Article  PubMed
 
[56]  Radvansky, G. A., Doolen, A. C., Pettijohn, K. A., & Ritchey, M. (2022). A New look at memory retention and forgetting. Journal of Experimental Psychology: Learning, Memory, and Cognition, 48(11), 1698–1723.
In article      View Article  PubMed
 
[57]  Albalawi, H. I., & Alnajashi, S. (2022). Recall of vocabulary from a second language: Picture Naming vs. Word Definition. Journal of Educational and Psychological Studies, 16(4), 330–342.
In article      View Article
 
[58]  Gong, D., Draschkow, D., & Nobre, A. C. (2023). Focusing attention in long-term and working memory improves recall and guides perception. Journal of Vision, 23(9), 5103.
In article      View Article
 
[59]  Kubik, V., Del Missier, F., & Mäntylä, T. (2020). Spatial ability contributes to memory for delayed intentions. Cognitive Research, 5(1).
In article      View Article  PubMed
 
[60]  Almarzouki, H. S., Khan, M. A., Al-Mansour, M., Al-Jifree, H. M., Abuznadah, W., & Althubaiti, A. (2023). Effectiveness of Cognitive Strategies on Short-Term Information Retention: An Experimental study. Health Professions Education. https://hpe.researchcommons.org/journal/vol9/iss3/2
In article      View Article
 
[61]  Pilotti, M., Alkuhayli, H., & Ghazo, R. A. (2021). Memorization practice and academic success in Saudi undergraduate students. Learning & Teaching in Higher Education: Gulf Perspectives, 18(1), 19–31.
In article      View Article
 
[62]  Macchitella, L., Tosi, G., Romano, D., Iaia, M., Vizzi, F., Mammarella, I. C., & Angelelli, P. (2023). Visuo-spatial working memory and mathematical skills in children: A Network analysis study. Behavioral Sciences, 13(4), 294.
In article      View Article  PubMed
 
[63]  Badmus, O. T., & Jita, L. C. (2022). Pedagogical implication of spatial visualization ability: A Correlate of students' achievements in physics. Journal of Turkish Science Education.
In article      View Article
 
[64]  Zhang, K. E., & Jenkinson, J. (2024). The Visual science communication toolkit: Responding to the need for visual science communication training in undergraduate life sciences education. Education Sciences, 14(3), 296.
In article      View Article
 
[65]  Babu, R., & Kalaiyarasan, G. (2019). Effectiveness of visual spatial intelligence based instructional materials to enhance the achievements of the secondary school students. Think India (New Delhi), 22(3), 2262–2268.
In article      View Article
 
[66]  Liu, S., Wei, W., Yuan, C., Peyre, H., & Zhao, J. (2021). Visual–spatial ability predicts academic achievement through arithmetic and reading abilities. Frontiers in Psychology, 11.
In article      View Article  PubMed
 
[67]  Tan, S. F., E A. D., Ooi, L. H., & Abdullah, A. C. (2021). Relationship between learning strategies and academic performance: A Comparison between accreditation of prior experiential learning (APEL) and regular entry undergraduates. AAOU Journal, 16(2), 226–238.
In article      View Article
 
[68]  Osarumwense, J. H., & Omorogiuwa, K. O. (2020). Contribution of cognitive learning strategy components to students’ academic achievement in Mathematics. International Journal of Mathematics and Statistics Invention, 8(7), 51–58.
In article      
 
[69]  Selvina, Fitrianawati, M., & Awae, A. (2023). Unleashing creative potential: The Impact of Self-Organized Learning Environments (SOLE) on fifth grade students’ creative thinking skills. Journal of Pedagogy and Education Science, 2(02), 124–131.
In article      View Article
 
[70]  Wael, A., Asnur, M. N. A., & Ibrahim, I. (2018). Exploring students’ learning strategies in speaking performance. IJoLE (International Journal of Language Education), 2(1), 65.
In article      View Article
 
[71]  Abbasi, F. K., Tariverdizadeh, H., & Younesi, J. (2022). A Comparative study on the effectiveness of cognitive and metacognitive learning strategies in goal orientation. Journal of Positive School Psychology, 6(5), 9971–9980. https://journalppw.com/index.php/jpsp/article/view/14201
In article      
 
[72]  Gerst, E. H., Cirino, P. T., Macdonald, K. T., Miciak, J., Yoshida, H., Woods, S. P., & Gibbs, M. C. (2020). The Structure of processing speed in children and its impact on reading. Journal of Cognition and Development, 22(1), 84–107.
In article      View Article  PubMed
 
[73]  Wang, L., Muenks, K., & Yan, V. X. (2023). Interventions to promote retrieval practice: Strategy knowledge predicts intent, but perceived cost predicts usage. Journal of Educational Psychology, 115 (1070–1086).
In article      View Article
 
[74]  Listiana, L., Bahri, A., Jamaluddin, A. B., Muharni, A., & Malik, W. H. (2023). Enhancing cognitive retention of different academic abilities undergraduate students through PBLRQA Strategy. In Advances in social science, education and humanities research (pp. 259–268).
In article      View Article
 
[75]  McIntyre, M. M., Gundlach, J. L., & Graziano, W. G. (2021). Liking guides learning: The Role of interest in memory for STEM topics. Learning and Individual Differences, 85, 101960.
In article      View Article
 
[76]  Nero, C. A., & Zulkiply, N. (2021). The Effects of retrieval practice across levels of thinking and retention interval on reading comprehension. Asian Journal of University Education, 17(4), 288.
In article      View Article
 
[77]  Ludwig, S., & Rausch, A. (2022). The Relationship between problem-solving behaviour and performance – Analysing tool use and information retrieval in a computer-based office simulation. Journal of Computer Assisted Learning, 39(2), 617–643.
In article      View Article
 
[78]  Yousif, S., Rosenberg, M. D., & Keil, F. C. (2021). Using space to remember: Short-term spatial structure spontaneously improves working memory. Cognition, 214, 104748.
In article      View Article  PubMed
 
[79]  Heald, J. B., Lengyel, M., & Wolpert, D. M. (2023). Contextual inference in learning and memory. Trends in Cognitive Sciences, 27(1), 43–64.
In article      View Article  PubMed
 
[80]  Baddeley, A., & Hitch, G. J. (1974). Working memory. In Psychology of Learning and Motivation (pp. 47–89).
In article      View Article
 
[81]  Rosenzweig, M. R. (1965). Environmental complexity, cerebral change, and behavior. American Psychologist, 21(4), 321–332.
In article      View Article  PubMed
 
[82]  Diamond, M. C., Krech, D., & Rosenzweig, M. R. (1964). The Effects of an enriched environment on the histology of the rat cerebral cortex. Journal of Comparative Neurology (1911), 123(1), 111–119.
In article      View Article  PubMed