Artykuły w czasopismach: „Cognitive load management”

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Bae, Su-Young. "Cognitive Load Management Strategies in Piano Education." Korean Society of Music Education Technology 61 (October 31, 2024): 405–30. http://dx.doi.org/10.30832/jmes.2024.61.405.

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This study aims to explore how piano educators perceive and manage students’ cognitive load and propose effective instructional strategies based on these findings. According to Cognitive Load Theory (CLT), learners experience cognitive load due to the limitations of working memory, and in order to improve learning outcomes, it is essential to effectively manage this cognitive load. Piano learning consists of complex cognitive tasks such as sight-reading, musical interpretation and expression, and technical skill development, which can result in a high cognitive load during the learning process. If this cognitive load is not properly managed, it can hinder learning effectiveness. In this study, focus group interviews (FGI) were conducted with college piano instructors to explore how they perceive students' cognitive load and what strategies they use to reduce it. Semi-structured interviews were employed as the research method, with the main questions focusing on the factors contributing to students' cognitive load during the learning process and the strategies instructors use to reduce cognitive load. The results revealed that instructors use various strategies to reduce students' cognitive load, such as personalized repertoire selection guidance, a step-by-step educational approach, the use of visual aids and digital tools, and promoting students' self-directed learning. The instructors found these strategies to be effective in reducing students' cognitive load during piano learning. This study holds significance by presenting various strategies that can effectively manage cognitive load in piano learning, providing practical insights that can be applied in educational settings.

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Mohamed-Ahmed, Ashraf, Nathalie Bonnardel, Pierre Côté, and Sébastien Tremblay. "Cognitive load management and architectural design outcomes." International Journal of Design Creativity and Innovation 1, no. 3 (2013): 160–76. http://dx.doi.org/10.1080/21650349.2013.797013.

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Choi, Younyoung, and Jigeun Kim. "Learning Analytics for Diagnosing Cognitive Load in E-Learning Using Bayesian Network Analysis." Sustainability 13, no. 18 (2021): 10149. http://dx.doi.org/10.3390/su131810149.

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A learner’s cognitive load is highly associated with their academic achievement within learning systems. Diagnostic information about a learner’s cognitive load is useful for achieving optimal learning, by enabling the learner to manage and control their cognitive load in the e-learning environment. However, little empirical research has been conducted to obtain diagnostic information about the cognitive load in e-learning systems. The purpose of this study was to analyze a personalized diagnostic evaluation for a learner’s cognitive load in an e-learning system, using the Bayesian Network (BN) as a learning analytic method. Data from 700 learners were collected from Cyber University. A learner’s cognitive load level was measured in terms of three components: extraneous cognitive load, intrinsic cognitive load, and germane cognitive load. The BN was built by representing the relationship among the extraneous cognitive load, intrinsic cognitive load, germane cognitive load, and academic achievement. The conditional and marginal probabilities in the BN were estimated. This study found that the BN provided diagnostic information about a learner’s level of cognitive load in the e-learning system. In addition, the BN predicted the learner’s academic achievement in terms of their different cognitive load patterns. This study’s results imply that diagnostic information related to cognitive load helps learners to improve academic achievement by managing and controlling their cognitive loads in the e-learning environment. In addition, instructional designers are able to offer more appropriately customized instructional methods by considering learners’ cognitive loads in online learning.

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Choi, Soonri, Soomin Kang, Kyungmin Lee, Hongjoo Ju, and Jihoon Song. "The effect of an agent tutor’s integration of cognitive and emotional gestures on cognitive load, motivation, and achievement." Contemporary Educational Technology 16, no. 1 (2024): ep491. http://dx.doi.org/10.30935/cedtech/14101.

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This study proposes that the gestures of an agent tutor in a multimedia learning environment can generate positive and negative emotions in learners and influence their cognitive processes. To achieve this, we developed and integrated positive and negative agent tutor gestures in a multimedia learning environment directed by cognitive gestures. The effects of emotion type on cognition were examined in terms of cognitive load, learning motivation, and achievement. The subjects were 46 university students in Gyeonggi Province, South Korea. The students were divided into three learner groups: cognition, cognition + negative emotion, and cognition + positive emotion. The learners watched a tutorial lecture on the Notion note-taking app by an agent tutor. Data analysis was conducted using one-way ANOVA to determine the cognitive load, learning motivation, and achievement. The results showed that the positive emotion design was more effective in terms of intrinsic cognitive load, learning motivation, and achievement but had a higher extrinsic cognitive load. However, even the negative + passive group showed more positive learning than the cognition group. Although this study focused on gestures by an agent tutor, it implies that such gestures in multimedia learning contexts must be informed by emotional as well as cognitive design to provide a more meaningful learning experience.

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Bonsang, Eric, and Eve Caroli. "Cognitive Load and Occupational Injuries." Industrial Relations: A Journal of Economy and Society 60, no. 2 (2021): 219–42. http://dx.doi.org/10.1111/irel.12277.

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Khan, Erum. "COGNITIVE OVERLOAD MANAGEMENT: EMPOWERING SIMULATION BASED MEDICAL EDUCATION THROUGH MINDFUL REALITY CHECKS." BMJ Simulation and Technology Enhanced Learning 1, no. 1 (2015): 44.3–44. http://dx.doi.org/10.1136/bmjstel-2015-000044.12.

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AimsTo guide the design of simulation based instructions consistent with the nature of human cognitive architecture.BackgroundCognitive load is the effort required for information handling in the working memory. There is a wealth of research on Human cognition and Instructional science that suggests that effective and efficient instructional strategies should avoid overloading the limited capacity of the working memory; a theory called “Cognitive Load Theory”. The foundational fact of this theory which is critical to any instructional strategy is that beyond a certain limit the cognitive overload starts impairing student learning.Description of Innovation TopicAt Center for Advanced Simulation in Healthcare, Gulf Medical University; simulation based instructions are designed keeping the human cognition in mind. Appropriately planning, integrating and aligning the clinical content and skills with the level of the learner takes care of the content load (Intrinsic load) while on the other hand constructively designing the simulation session with appropriate use of the simulation fidelity, pre-scenario briefing, simulator and learning environment orientation and debriefing facilitation skills matching the expectation, motivation level and interest of the learners ensures a mindful check on the extraneous and germane load that arises when learners interact with the instructional material.ConclusionsSimulation Educators should aim to understand the causes of cognitive overload and stress and have strategies to minimize their impact. Keeping a mindful watch out and frequent reality checks on the intrinsic and extrinsic load of the simulation exercises is highly recommended. We recommend the use of pre-session materials and advanced organizers, a comprehensive pre-briefing and debriefing, small peer group frequent simulation exercises with increasing level of challenges.

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Hindriana, Anna Fitri, Handayani Handayani, and Ina Setiawati. "ANALYSIS ON THINKING SKILL: COGNITIVE LOAD MANAGEMENT IN CONNECTED INTEGRATED LEARNING." Jurnal Pengajaran Matematika dan Ilmu Pengetahuan Alam 25, no. 2 (2020): 34–40. http://dx.doi.org/10.18269/jpmipa.v25i2.33217.

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Connecting related concepts can enable learners to obtain holistic knowledge but designing integrated learning must consider high element interactivity between concepts, so that learning would not result in excessive cognitive load, which will instead hinder learning. The promising benefit of learning plant anatomy and physiology in connected integrated learning was analyzed by assessing preservice biology teachers’ identification and information analysis skills. The influence of learning approach on their cognitive load was also analyzed. Results suggested the advantage of learning in an integrated way, in which cognitive load can be managed by considering the correlation between cognitive load elements.

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K. S, Devayani, G. Kalpana, and P. Jagadeesan. "The Impact of Sentiment and Cognitive Load on Investment Decisions: A Conceptual Framework." Journal of Neonatal Surgery 14, no. 9S (2025): 284–88. https://doi.org/10.52783/jns.v14.2656.

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This conceptual paper examines the hardship that emotional cognition inhibits in investment decisions in light of neurofinance. Based on theories from emotional decision-making, cognitive load theory, and behavioural finance, the present paper builds a framework to gain insight into the relationship between investor sentiment, mental processing, and decision outcomes. Before cognition load, positive sentiment leads to more risk-taking and negative sentiment to risk averse, but cognition load decrease this effect. High cognitive load, such as well-explained when investors are confronted with complex financial decisions, may prejudice their cognitive information process and lead to emotional-based decisions. This research, which combines neuroscience, psychology, and finance to gain a better understanding how investors’ mental states and external emotional stimuli affect their financial decisions. There are implications from the findings for financial advisors, policymakers, and investors to construct strategies that can enhance decision-making efficiency and risk management.

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Kolfschoten, Gwendolyn L., and Frances M. T. Brazier. "Cognitive Load in Collaboration: Convergence." Group Decision and Negotiation 22, no. 5 (2012): 975–96. http://dx.doi.org/10.1007/s10726-012-9322-6.

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Ye, Jianqiang, Junhua Gao, Tingting Lin, Kun He, and Dimei Chen. "COGNITIVE LOAD CHANGE IN CHEMICAL CONCEPT LEARNING: INSIGHTS FROM EVENT-RELATED POTENTIALS." Journal of Baltic Science Education 24, no. 1 (2025): 92–104. https://doi.org/10.33225/jbse/25.24.92.

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This study explored the impact of oxidation-reduction reaction problem difficulty on university students' cognitive load using event-related potentials (ERPs). Forty-eight balanced low and high difficulty problems were designed. Fifteen undergraduate students majoring in chemistry (8 females and 7 males) participated in the study. Results demonstrated significantly increased reaction time, significantly decreased accuracy, and highly significantly elevated subjective effort as task difficulty intensified. ERP analysis revealed significant differences in N200, P300, and N400 amplitudes between easy and difficult problems, indicating increased demands on control, working memory, and in-depth processing under high load. The study provided physiological evidence supporting cognitive load theory and offered implications for optimizing oxidation-reduction reaction teaching. The findings bridged the gap between cognition and education, suggesting potential avenues for improving chemistry education through cognitive load management. Keywords: oxidation-reduction reactions, chemistry learning, cognitive load, event-related potentials

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Allred, Sarah, Sean Duffy, and John Smith. "Cognitive load and strategic sophistication." Journal of Economic Behavior & Organization 125 (May 2016): 162–78. http://dx.doi.org/10.1016/j.jebo.2016.02.006.

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Tingting, P., D. Xun, W. Jun, D. Shu, and Z. Shan. "Mediator Effects of Cognitive Load on Association between Self-Efficacy and Task Load in Intensive Care Unit Nurses." Journal of Nursing Management 2024 (February 2, 2024): 1–7. http://dx.doi.org/10.1155/2024/5562751.

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Aims. To explore the mediating effect of cognitive load on the relationship between self-efficacy and task load among intensive care unit (ICU) nurses. Background. Studies related to ICU nurses’ self-efficacy, cognitive load, and task load are noteworthy but limited. Methods. A total of 253 ICU nurses from three tertiary hospitals in Beijing were recruited and investigated by the Chinese version of the National Aeronautics and Space Administration-Task Load Index (NASA-TLX), General Self-Efficacy Scale (GSES), and an instrument for Measuring Different Types of Cognitive Load (MDT-CL) scales. SPSS 25.0 was used for Pearson correlation analysis and multiple linear regression analysis and mediation effect analysis using Model 4 in PROCESS (5,000 resamples). Results. Mediation analysis indicated that a partial mediating effect of extraneous cognitive load between self-efficacy and task load among ICU nurses was −0.707 (95% CI: −0.940, −0.504), accounting for 51.64% of the total effect. Conclusion. This study suggests that enhancing ICU nurses’ self-efficacy can be a potential strategy to decrease extraneous cognitive load and task load. Implications for Nursing Management. Nursing administrators should actively implement intervention strategies based on influencing the task load pathway of ICU nurses to ensure they can provide safe and high-quality nursing services.

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Fuster, Joan, Toni Caparrós, and Lluis Capdevila. "Evaluation of cognitive load in team sports: literature review." PeerJ 9 (October 8, 2021): e12045. http://dx.doi.org/10.7717/peerj.12045.

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In team sports, load management has become one of the most common areas of investigation, given that effective control over load is the key to being able to optimize performance and avoid injuries. Despite the constant evolution and innovation in the latest theories, we can see a clear tendency in load management that focuses on physiological and mechanical aspects and neglects its cognitive character, which generates the variability inherent in the performance of athletes in a changing environment. Indicators of response that inform methods of control over cognitive load can include cognitive, physiological and behavioral indicators. However, limited investigations exist to support the reliability of each indicator regarding cognitive load. For this reason, the objective of this literature review is to present strategies used to manage cognitive load in team sports, as well as the indicators utilized for such a proposition and their relationships in specific contexts.

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Svechnikov, Konstantin L., and Marsel M. Valeev. "COGNITIVE EFFECTIVENESS IN DATA VISUALIZATION: IMPROVING BUSINESS MANAGEMENT OF INDUSTRIAL ENTERPRISES." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 5/3, no. 158 (2025): 50–59. https://doi.org/10.36871/ek.up.p.r.2025.05.03.007.

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The article explores the role of cognitive efficiency in data visualization for optimizing management decisions in industrial enterprises. The key principles of cognitive psychology, including the theory of dual coding, the concept of cognitive load and Gestalt principles, as well as their application in the design of information systems, are considered. The analysis of BPMN and UML business notations adapted to reduce cognitive load is carried out. Experimental methods (eye-tracking, reaction time analysis) have confirmed that optimization of data visualization increases the speed and accuracy of decision-making. Recommendations on the integration of cognitive principles into management practices, including the development of adaptive dashboards and staff training, are proposed.

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Waluyo, Binsar, and Aan Hendrayana. "MANAGEMENT OF COGNITIVE LOAD ON STUDENT’S MATHEMATICAL PROFICIENCY AT SMP NEGERI 20 KOTA SERANG." SIGMA: JURNAL PENDIDIKAN MATEMATIKA 16, no. 1 (2024): 46–59. http://dx.doi.org/10.26618/sigma.v16i1.14560.

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This research is motivated by the fact that the level of conceptual understanding in Indonesia is still relatively low. The low level of conceptual understanding is related to how students manage and process the information received when they studying material, considering cognitive load. Learning with attention to cognitive load is believed to enhance students' mathematical conceptual understanding. The research aims to determine whether students' mathematical conceptual understanding with cognitive load-aware learning is better than students with conventional learning, both in terms of initial ability and not. The method used in this research is a mixed-method with a sequential explanatory design. Research instruments consist of test and non-test instruments. Data were obtained from initial ability tests and conceptual understanding as test instruments and questionnaires, interviews, and documentation as non-test instruments. The results show that students' mathematical conceptual understanding with cognitive load-aware learning is better than students with conventional learning, both in terms of initial ability and not. The conclusion of the research is that the treatments given to both classes overall have yielded quite positive results in students' mathematical conceptual understanding. However, the comparison between students who received cognitive load-aware learning and those who received conventional learning shows a significant difference.

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Pejovic, Veljko, Martin Gjoreski, Christoph Anderson, Klaus David, and Mitja Lustrek. "Toward Cognitive Load Inference for Attention Management in Ubiquitous Systems." IEEE Pervasive Computing 19, no. 2 (2020): 35–45. http://dx.doi.org/10.1109/mprv.2020.2968909.

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Laamanen, Tomi, Markku Maula, Markus Kajanto, and Peter Kunnas. "The role of cognitive load in effective strategic issue management." Long Range Planning 51, no. 4 (2018): 625–39. http://dx.doi.org/10.1016/j.lrp.2017.03.001.

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Blaywais, Reut, and Mosi Rosenboim. "The effect of cognitive load on economic decisions." Managerial and Decision Economics 40, no. 8 (2019): 993–99. http://dx.doi.org/10.1002/mde.3085.

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Firdaus, Thoriqi, Ainunnuril Amelia, Farah Lailatul Nur Alifiyah, Afida Silmi Nahdliyah, and Fausiyeh Fausiyeh. "Trends and Effects of Psychological and Cognitive Load in Education." Journal of Education and Learning Reviews 2, no. 2 (2025): 97–128. https://doi.org/10.60027/jelr.2025.1084.

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Background and Aim: The cognitive load experienced by students during learning can lead to mental fatigue and significant psychological disturbances, often resulting in negative emotional responses. This study aims to identify trends and examine influential factors in psychological aspects and cognitive load within the educational context, thereby advancing the understanding of educational psychology and cognitive load theory. Materials and Methods: Utilizing a mixed-methods approach, the research integrates bibliometric analysis and a systematic literature review, allowing a comprehensive evaluation of scholarly trends. Research data were sourced from the Scopus database with the keywords "Psychological" AND "Cognitive Load" AND "Education" in article titles, abstracts, and keywords, ensuring alignment with relevant literature. Results: Findings show a fluctuating trend in annual publication citations, marked by phases of notable increases and declines. These patterns are shaped by topical relevance, research quality, and shifts in the academic landscape and technology for information access. The United States leads in publication contributions, comprising 27.4% of total articles, with significant use of terms like cognitive load, learning systems, executive function, and motivation in recent research, while terms like humans, cognition, and education remain consistently emphasized. The insights suggest that innovative learning media, while enhancing outcomes, introduce complexities in managing cognitive load. Conclusion: This study underscores the need for precise cognitive load measurement in developing effective interventions, emphasizing the management of students' emotions as a critical component in online learning and technology acceptance. These findings inform educational practices and policies by highlighting strategies that support emotional well-being and foster effective, student-centred learning environments, laying the groundwork for future research on enhancing educational practices through cognitive and emotional insights.

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Wang, Haibo, Naiqi Jiang, Ting Pan, Haiqing Si, Yao Li, and Wenjing Zou. "Cognitive Load Identification of Pilots Based on Physiological-Psychological Characteristics in Complex Environments." Journal of Advanced Transportation 2020 (November 12, 2020): 1–16. http://dx.doi.org/10.1155/2020/5640784.

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Cognitive load is generated by pilots in the process of information cognition about aircraft control, and it is closely related to flight safety. Cognitive load is the physiological and psychological need that a pilot produces when completing a mission. Therefore, it is meaningful to study the dynamic identification of the cognitive load of the pilot under the complex human-aircraft-environment interaction. In this paper, the airfield traffic pattern flight simulation experiment was designed and used to obtain the ECG physiological and NASA-TLX psychological data. The wavelet transform preprocessing and mathematical statistics analysis were applied on them, respectively. Furthermore, the Pearson correlation analysis method is used to select the characteristic indicators of psycho-physiological data after preprocessing. Based on the psycho-physiological characteristic indicators, the pilot’s cognitive load identification model is constructed by combining RNN and LSTM. The results of this study are more accurate compared with the cognitive load identification models established by other methods such as RNN neural network and support vector machine. This research is able to provide a useful reference for preventing and reduction of human error caused by the cognitive load during flight missions. It will be potential to realize intelligent control of aircraft cockpit, improving the flight control behavior and maintaining flight safety.

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Oettinger, A., J. H. Smith-Spark, F. D. Castillo, V. E. L. Monaghan, J. Fox, and D. W. Glasspool. "Supporting Medical Planning by Mitigating Cognitive Load." Methods of Information in Medicine 46, no. 06 (2007): 636–40. http://dx.doi.org/10.3414/me0441.

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Summary Objectives : Developing a care plan for a patient is a complex task, requiring an understanding of interactions and dependencies between procedures and of their possible outcomes for an individual patient. Decision support for planning has broader requirements than are typically considered in medical informatics applications. We consider the appropriate design of software to assist medical planning. Methods : The likely cognitive loads imposed by planning tasks were assessed with a view to directly supporting these via software. Results : Five types of cognitive load are likely to be important. A planning support system, REACT, was designed to ameliorate these cognitive loads by providing targeted dynamic feedback during planning. An initial evaluation study in genetic counselling indicates that the approach is successful in that role. Conclusions : The approach provides the basis of a general aid for visualizing, customizing and evaluating care plans.

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Fox, Stephen, and Vitor Fortes Rey. "A Cognitive Load Theory (CLT) Analysis of Machine Learning Explainability, Transparency, Interpretability, and Shared Interpretability." Machine Learning and Knowledge Extraction 6, no. 3 (2024): 1494–509. http://dx.doi.org/10.3390/make6030071.

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Information that is complicated and ambiguous entails high cognitive load. Trying to understand such information can involve a lot of cognitive effort. An alternative to expending a lot of cognitive effort is to engage in motivated cognition, which can involve selective attention to new information that matches existing beliefs. In accordance with principles of least action related to management of cognitive effort, another alternative is to give up trying to understand new information with high cognitive load. In either case, high cognitive load can limit potential for understanding of new information and learning from new information. Cognitive Load Theory (CLT) provides a framework for relating the characteristics of information to human cognitive load. Although CLT has been developed through more than three decades of scientific research, it has not been applied comprehensively to improve the explainability, transparency, interpretability, and shared interpretability (ETISI) of machine learning models and their outputs. Here, in order to illustrate the broad relevance of CLT to ETISI, it is applied to analyze a type of hybrid machine learning called Algebraic Machine Learning (AML). This is the example because AML has characteristics that offer high potential for ETISI. However, application of CLT reveals potential for high cognitive load that can limit ETISI even when AML is used in conjunction with decision trees. Following the AML example, the general relevance of CLT to machine learning ETISI is discussed with the examples of SHapley Additive exPlanations (SHAP), Local Interpretable Model-Agnostic Explanations (LIME), and the Contextual Importance and Utility (CIU) method. Overall, it is argued in this Perspective paper that CLT can provide science-based design principles that can contribute to improving the ETISI of all types of machine learning.

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Hansen, Håvard, and Elisabeth Lind Melbye. "Negative Information, Cognitive Load, and Taste Perceptions." Journal of Food Products Marketing 26, no. 3 (2020): 185–96. http://dx.doi.org/10.1080/10454446.2020.1740129.

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Abdellatif, Mohamed Sayed, and Mervat Azmy Zaki Abdul-Gawad. "The contribution of psychological barriers in predicting the cognitive load among the university students’ users of blackboard system." Cypriot Journal of Educational Sciences 16, no. 6 (2021): 3058–72. http://dx.doi.org/10.18844/cjes.v16i6.6498.

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Psychological barriers are one of the most common problems facing individuals nowadays due to everyday life pressures. The current research aimed at identifying the extent to which psychological barriers contribute to predicting the perceived cognitive load of blackboard e-learning management system users. The research sample comprised (240) male and female among the University Students. The descriptive-analytical approach, specifically the predictive correlative research method was utilized to reveal the relationship between the research variables. The research main results revealed that there was a statistically significant correlative positive relationship between the psychological barriers and the cognitive load (intrinsic, extraneous, and the overall degree), and there was no statistically correlative relationship between psychological barriers and the Germane cognitive load. Besides, results concluded that the external psychological barriers were better at predicting the overall degree of the perceived cognitive load. Psychological barriers and cognitive load must be considered within the e-learning settings through making use of the results of the current study in developing training and counseling programs to reduce the students' psychological barriers and cognitive load levels.  Keywords: psychological barriers; cognitive load; Blackboard system

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Surbakti, Rudy, Satria Evans Umboh, Ming Pong, and Sokha Dara. "Cognitive Load Theory: Implications for Instructional Design in Digital Classrooms." International Journal of Educational Narratives 2, no. 6 (2024): 483–93. https://doi.org/10.70177/ijen.v2i6.1659.

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The rapid integration of digital tools in education has transformed classroom environments, creating new opportunities and challenges for instructional design. One key area of focus is the management of cognitive load, which refers to the mental effort required to process information during learning. Cognitive Load Theory (CLT) offers insights into how instructional materials can be optimized to improve learning outcomes. In digital classrooms, the effective design of instructional content becomes even more critical due to the increased multimedia elements and potential for cognitive overload. This study aims to explore the implications of Cognitive Load Theory (CLT) for instructional design in digital classrooms. It examines how digital tools, such as multimedia content and interactive activities, impact learners’ cognitive load and suggests strategies for reducing extraneous cognitive load to enhance learning efficiency and effectiveness. A mixed-methods approach was used, combining quantitative surveys to assess students’ cognitive load during digital learning activities and qualitative interviews with instructors to understand their perspectives on instructional design challenges. The study was conducted across several digital learning environments in higher education. The findings indicate that digital learning environments often lead to high cognitive load, particularly when multimedia content is poorly integrated. However, using principles from CLT, such as segmenting information and reducing unnecessary complexity, can significantly lower cognitive load and improve student learning outcomes. Both students and instructors reported that well-designed digital content led to better engagement and more efficient learning. The study concludes that applying Cognitive Load Theory to instructional design in digital classrooms can enhance learning by minimizing cognitive overload. Educators should be mindful of cognitive load when creating digital learning experiences to improve student performance and engagement.

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Zhang, Xiaochen, Lingling Jin, Jie Zhao, Jiazhen Li, Ding-Bang Luh, and Tiansheng Xia. "The Influences of Different Sensory Modalities and Cognitive Loads on Walking Navigation: A Preliminary Study." Sustainability 14, no. 24 (2022): 16727. http://dx.doi.org/10.3390/su142416727.

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External cognitive burden has long been considered an important factor causing pedestrian navigation safety problems, as pedestrians in navigation inevitably acquire external information through their senses. Therefore, the influences of different types of sensory modalities and cognitive loads on walking navigation are worthy of in-depth investigation as the foundation for improving pedestrians’ safety in navigation. This study investigated users’ performance in visual, auditory, and tactile navigation under different cognitive loads by experimental simulation. Thirty-six participants were recruited for the experiment. A computer program simulating walking navigation was used, and three different cognitive task groups were set up. Participants’ reaction times and performances were recorded during the experiment, and a post-test questionnaire was administered for evaluation purposes. According to the tests, the following points are summarized. First, visual navigation performed the best in load-free conditions, which was significantly faster than auditory navigation and tactile navigation, but the difference between the latter two was not significant. There was a significant interaction between navigation types and cognitive load types. Specifically, in the condition without load, reaction time in auditory navigation was significantly slower than those in visual navigation and tactile navigation. In the condition with auditory load, reaction time in visual navigation was significantly faster than those in auditory navigation and tactile navigation. In the condition with visual load, there were no significant differences among the three navigations.

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Corrente, Salvatore, Salvatore Greco, and Jafar Rezaei. "Better decisions with less cognitive load: The Parsimonious BWM." Omega 126 (July 2024): 103075. http://dx.doi.org/10.1016/j.omega.2024.103075.

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Brosnan, Kylie, Bettina Grün, and Sara Dolnicar. "Cognitive load reduction strategies in questionnaire design." International Journal of Market Research 63, no. 2 (2021): 125–33. http://dx.doi.org/10.1177/1470785320986797.

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Survey data quality suffers when respondents have difficulty completing complex tasks in questionnaires. Cognitive load theory informed the development of strategies for educators to reduce the cognitive load of learning tasks. We investigate whether these cognitive load reduction strategies can be used in questionnaire design to reduce task difficulty and, in so doing, improve survey data quality. We find that this is not the case and conclude that some of the traditional survey answer formats, such as grid questions, which have been criticized in the past lead to equally good data and do not frustrate respondents more than alternative formats.

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Drichoutis, Andreas C., and Rodolfo M. Nayga. "Game form recognition in preference elicitation, cognitive abilities, and cognitive load." Journal of Economic Behavior & Organization 193 (January 2022): 49–65. http://dx.doi.org/10.1016/j.jebo.2021.11.006.

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Betz, Simon, Nataliya Bryhadyr, Olcay Türk, and Petra Wagner. "Cognitive Load Increases Spoken and Gestural Hesitation Frequency." Languages 8, no. 1 (2023): 71. http://dx.doi.org/10.3390/languages8010071.

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This study investigates the interplay of spoken and gestural hesitations under varying amounts of cognitive load. We argue that not only fillers and silences, as the most common hesitations, are directly related to speech pausing behavior, but that hesitation lengthening is as well. We designed a resource-management card game as a method to elicit ecologically valid pausing behavior while being able to finely control cognitive load via card complexity. The method very successfully elicits large amounts of hesitations. Hesitation frequency increases as a function of cognitive load. This is true for both spoken and gestural hesitations. We conclude that the method presented here is a versatile tool for future research and we present foundational research on the speech-gesture link related to hesitations induced by controllable cognitive load.

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Varrasi, Simone, Roberto Vagnetti, Nicola Camp, et al. "How Human–Robot Interaction Can Influence Task Performance and Perceived Cognitive Load at Different Support Conditions." Information 16, no. 5 (2025): 374. https://doi.org/10.3390/info16050374.

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Cognitive load refers to the mental resources used for executing simultaneous tasks. Since these resources are limited, individuals can only process a specific amount of information at a time. Daily activities often involve mentally demanding tasks, which is why social robots have been proposed to simplify them and support users. This study aimed to verify whether and how a social robot can enhance the performance and support the management of cognitive load. Participants completed a baseline where a cognitive activity was carried out without support, and three other conditions where similar activities of increasing difficulty were collaboratively made with the NAO robot. In each condition, errors, time, and perceived cognitive load were measured. Results revealed that the robot improved performance and perceived cognitive load when compared to the baseline, but this support was then thwarted by excessive levels of cognitive load. Future research should focus on developing and designing collaborative human–robot interactions that consider the user’s mental demand, to promote effective and personalized robotic help for independent living.

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Sugiono, Sugiono, Willy Satrio Nugroho, Bayu Rahayudi, Alies Poetri Lintangsari, and Astuteryanti Tri Lustyana. "The development of cognitive workload management framework based on neuronal dynamics principle to maintain train driver’s health and railway safety." EUREKA: Physics and Engineering, no. 3 (May 25, 2023): 144–56. http://dx.doi.org/10.21303/2461-4262.2023.002652.

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Fatigue increases the tendency of poor train driving strategy decision. Decision making in cognitive overload and cognitive underload situation mostly outputs bad decisions. Accordingly, train driver’s cognitive function is required to be sTable during travel so that they can give correct response at a given situation. This study constructs a conceptual framework for cognitive workload management (CWM) of train driver by taking the energy expenses from cognition into the account. This study combines objective and subjective cognitive workload analysis to evaluate train driver duty readiness. The objective load analysis was performed through energy level approximation based on neuronal dynamics simulation from 76 brain regions. The cognitive energy expenditure (CEE) calculated from neuron action potential (NAP) and the ion-membrane current (IMC) from the simulation results. The cognitive load (CL) approximated by converts the continuous time-based CEE to discrete frequency-based CL using Fourier series. The subjective cognitive workload obtained from train simulation results followed by 27 participants. The participants fill the questionnaire based on their simulated journey experience. The results of the evaluation used to build readiness evaluation classifier based on control chart. The control chart evaluation helps the management to determine weekly rest period and daily short rest period treatment base on each train driver workload. The CWM framework allows different recovery treatment to be applied to each train driver. The impact of the CWM application is the performance of train drivers are kept stable. Thus, the CWM framework based on CEE is useful to prevent physical and mental fatigue

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Rose, Jacob M., F. Douglas Roberts, and Anna M. Rose. "Affective responses to financial data and multimedia: the effects of information load and cognitive load." International Journal of Accounting Information Systems 5, no. 1 (2004): 5–24. http://dx.doi.org/10.1016/j.accinf.2004.02.005.

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Chen, Yang, Luying Zhang, and Hua Yin. "A Longitudinal Study on Students’ Foreign Language Anxiety and Cognitive Load in Gamified Classes of Higher Education." Sustainability 14, no. 17 (2022): 10905. http://dx.doi.org/10.3390/su141710905.

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Using gamification as an instructional intervention to manage students’ learning emotions has become a trending topic. Meanwhile, the cognitive load resulting from gamified learning environments may impact learning emotions negatively. In order to clarify students’ foreign language anxiety and cognitive load in a gamified English as a foreign language class, this study designed a gamified flipped learning context in a Chinese university and conducted five surveys, three semi-structured interviews, and consecutive in-class observation in 15 sessions. This study has the following findings: First, neither the foreign language anxiety nor the cognitive load of the students changed significantly through the entire course; second, the game elements produced contradictory effects on the students’ multiple-sourced foreign language anxiety (communication apprehension, fear of negative evaluation, and lack of self-confidence); third, the introduction of games had transient effects on extraneous cognitive load, and the immersion in games indirectly influenced the intrinsic and germane cognitive load; in addition, foreign language anxiety and cognitive load correlated in a complicated and dynamic manner as a result of diverse gamification factors. These findings are expected to provide useful insights for researchers into the significance of utilizing gamification in emotion management while taking cognitive dimensions into account from both the collective and the individual perspectives.

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Jose Paolo L. Mangubat and Dr. James L. Paglinawan. "Task Complexity and Students’ Cognitive Load in Science among Grade 11 Students at Kitubo National High School Bukidnon." International Journal of Latest Technology in Engineering Management & Applied Science 13, no. 11 (2024): 116–23. https://doi.org/10.51583/ijltemas.2024.1311012.

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Abstract: This research study investigates the task complexity and students’ cognitive load in science of grade-11 science students in Kitobo National High School, Kitubo, Kitaotao, Bukidnon during the second quarter of the academic year 2024-2025. The study aims to examine 1. The level of task complexity for the students in science; 2. The level of students’ cognitive load in science; 3. The relationship between task complexity and students’ cognitive load in science. The participant of the study involves 87 science students from 3 different sections of grade-11 selected through purposive sampling. Participants answered a 42-item survey questionnaire divided into two parts focusing on the task complexity and cognitive load. The data collected were analyzed using statistical tool called SPSS. Analysis of the data shows several insights on the cause and effect of task complexity and cognitive load as well as the close direct proportionality of the variables. While complex task triggers the students to do more and improve their output better, there is still a need to improve in delivering and presentation of the task and lesson. A well-structured task that aligns with students' cognitive capabilities and reduce extraneous cognitive load can significantly enhance learning outcomes. By balancing task complexity with appropriate support, educators can foster deeper understanding and more effective learning experiences. Educators should continue refining task design to ensure it supports cognitive load management while promoting engagement. Further research is needed to explore how specific task structures impact different types of cognitive load across various learning environments. Additionally, developing targeted strategies to reduce extraneous load in digital learning contexts could provide valuable insights for improving online education.

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Partarakis, Nikolaos, and Xenophon Zabulis. "Applying Cognitive Load Theory to eLearning of Crafts." Multimodal Technologies and Interaction 8, no. 1 (2023): 2. http://dx.doi.org/10.3390/mti8010002.

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Craft education and training are important for preserving cultural heritage and fostering artisanal skills. However, the pedagogical challenges in this domain are numerous. This research paper presents a comprehensive framework for applying Cognitive Load Theory to enhance craft education and training via eLearning platforms. In this study, practical guidelines based on CLT principles are provided to optimize the instructional design and content delivery. These guidelines scaffold craft learning experiences within eLearning platforms and encompass strategies to manage cognitive load, promote active learning, and facilitate gradual transition. Subsequently, the paper details the implementation of these guidelines within a popular eLearning platform, Moodle, emphasizing its adaptability and utility for craft education. It discusses the customization of Moodle courses to align with the cognitive load management principles, providing a practical blueprint for educators and instructional designers. The research culminates in a case study, wherein the guidelines are applied to a craft eLearning course using Moodle.

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Peishan, Jiang, and Wang Hongyuan. "Research on English Learning Strategies in Junior High Schools Based on Cognitive Load Theory." International Journal of English Language Teaching 10, no. 1 (2023): 1. http://dx.doi.org/10.5430/ijelt.v10n1p1.

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In the case of advocating autonomous learning and lifelong learning, learners need to master English learning strategies and use them effectively. How to exert functions of English learning strategies is a key issue that needs to be solved. In this study, the revised The Strategy Inventory for Language Learning (SILL) to design a questionnaire and interviews were conducted to understand the current situation of English learning strategies used by junior high school students. Then, in order to augment students’ initiative in using learning strategies, based on the cognitive load theory, this study proposed six strategies. First, decrease internal cognitive load: reducing elements and linking old and new knowledge. Second, decrease external cognitive load: setting goals and reducing redundancy. Third, increase germane cognitive load: stimulating learning motivation and multi-modal training.

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Petko, Dominik, Regina Schmid, and Andrea Cantieni. "Pacing in Serious Games: Exploring the Effects of Presentation Speed on Cognitive Load, Engagement and Learning Gains." Simulation & Gaming 51, no. 2 (2020): 258–79. http://dx.doi.org/10.1177/1046878120902502.

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Background. To determine the optimal speed of computer-paced serious games, the interplay of cognitive load variables and game engagement variables can serve as combined criteria. Intervention. In order to test the effects of higher or lower game speeds on different types of cognitive load and engagement, the FRESH FOOD RUNNER game was developed, which teaches the harvest seasons of different fruits and vegetables. Method. In this study, N=58 6th grade primary school students are randomly assigned to play the serious game FRESH FOOD RUNNER at different speeds. Pre-and post-tests are used to assess learning gains, in combination with rating scales for different types of cognitive load and game engagement. Results. Results show that highest learning gains and lowest levels of extraneous cognitive load are prevalent at medium speed settings, which are neither too fast nor too slow. A similar pattern is apparent for student ratings of game engagement. Discussion and Conclusion. In consequence, learning gains, cognitive load and engagement variables can be regarded as suitable criteria to determine the optimal speed of serious games.

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Aghdam, Shamsi Samavi, Roya Ranjbar Mohammadi, Hassan Asadollahfam, and Mohammad Hossein Yousefi. "Enhancing Second Language Vocabulary Acquisition through Self-Regulation, Spaced Repetition, and Cognitive Load Management Strategies." Asian Journal of Education and Social Studies 51, no. 2 (2025): 1–13. https://doi.org/10.9734/ajess/2025/v51i21762.

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This study aims to investigate not only how learners perceive the effectiveness of this approach for long-term retention and practical application, but also how they experience the learning process in terms of cognitive load. Effectively managing cognitive load, the amount of information learners can process at once, is crucial for successful implementation of SR and SpR techniques. Building a strong vocabulary is essential for becoming fluent in a second language. Traditional methods like memorization often prove ineffective. Recent breakthroughs in understanding of memory and learning offer promising alternatives. such as spaced retention and spaced retrieval, believed to work even better together. The integration of SR and SpR positively influences the overall learning experience by promoting deeper cognitive engagement and better retention. Research shows that combining different instructional strategies, such as top-down and bottom-up processes, enhances vocabulary learning and retention. Cognitive load refers to the amount of information that learners can process at one time. While spaced learning offers advantages, it can be overwhelming if learners are presented with excessive vocabulary or complex retrieval tasks. As research on this combined approach continues to evolve, educators can utilize these findings to create inclusive and effective learning environments that empower L2 learners to achieve fluency and confidence in their vocabulary usage.

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Schaule, Florian, Jan Ole Johanssen, Bernd Bruegge, and Vivian Loftness. "Employing Consumer Wearables to Detect Office Workers' Cognitive Load for Interruption Management." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2, no. 1 (2018): 1–20. http://dx.doi.org/10.1145/3191764.

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van Bruggen, J. M., P. A. Kirschner, and W. Jochems. "External representation of argumentation in CSCL and the management of cognitive load." Learning and Instruction 12, no. 1 (2002): 121–38. http://dx.doi.org/10.1016/s0959-4752(01)00019-6.

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Loo, Yew Jie, Hooi-Ten Wong Doris, Mat Zain Zarina, Nur Amir Sjarif Nilam, Ibrahim Roslina, and Maarop Nurazean. "Metrics and Benchmarks for Empirical and Comprehension Focused Visualization Research in the Sales Domain." Indonesian Journal of Electrical Engineering and Computer Science 12, no. 3 (2018): 1340–48. https://doi.org/10.11591/ijeecs.v12.i3.pp1340-1348.

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Data visualization is an effort which aims to communicate data effectively and clearly to the audience through graphical representation. Data visualization efforts must be coordinated with an understanding into the Cognitive Learning Theory (CLT). In the sales domain, sales data visualization are made possible with the available Business Intelligence (BI) tools such as Microsoft Power BI, Tableau, Plotly, and others. These tools allow seamless interaction for the top management as well as the sales force with regard to the data. Sales data visualization comes with an array of advantages such as self-service analysis by business users, rapidly adapt to changing business conditions, and enable continuous on-demand reporting among others. The advantages of sales data visualization also comes with the challenges such as difficulty in identifying visual noise, high rate of image change, and high performance requirements. In an effort to reduce cognitive activity that does not enhance learning, sales visualization dashboard must be designed in a way that is neither too simplistic nor too complex to ensure that the Intrinsic Cognitive Load (ICL), Extrinsic Cognitive Load (ECL), and Germane Cognitive Load (GCL) are in sync with the audience. With the combination of sales data visualization and CLT, understanding complex sales details quickly is made possible by not only the top management of the organization, but also the sales force of the organization.

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E Araujo, Jonas Lenzi d., James Lenzi De Araujo, Tatiane Bacchi Gehlen, Anderson Sestilio Stramari, Marcio Fontana Catapan, and Fernando Deschamps. "Pain and Cognitive Load As Predictors of Absenteeism in Industry." Revista de Gestão Social e Ambiental 18, no. 1 (2024): e04805. http://dx.doi.org/10.24857/rgsa.v18n1-058.

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Purpose: This study delves into the impact of pain and cognitive load on industrial absenteeism, aiming to highlight the importance of these factors in workforce management and productivity enhancement.  Theoretical framework: Anchored in the biopsychosocial model, this research contends that absenteeism is intricately linked to the interplay between pain and cognitive load. Utilizing the Numeric Rating Scale (NRS) and the NASA Task Load Index (NASA-TLX), it seeks to elucidate their combined influence on absenteeism.  Method/design/approach: In a pilot study, NRS and the NASA-TLX were utilized for data collection, with a third-party dataset incorporating seven predictor variables and absenteeism as the dependent variable. Statistical analysis involved the Shapiro-Wilk Test for data normality and the Mann-Whitney U Test for non-normal distributions. Generalized Linear Models were applied to analyze the impact of variables on absenteeism, including multivariate, univariate and combined models. Model performance was evaluated using BIC, AIC, pseudo-R², LogLik, and AUC, with the Delong method for AUC comparison.  Results and conclusion: Pain emerged as a significant absenteeism predictor. The integrated model displayed enhanced discriminatory capacity, underscoring the pronounced interrelation between pain, cognitive load, and absenteeism. These insights advocate for holistic management strategies encompassing both health and occupational aspects.  Research implications: This study reaffirms the crucial role of pain and cognitive load in industrial absenteeism and highlights the importance of a multifaceted, data-driven approach for effective intervention strategies.  Originality/value: This study offers unique perspectives on absenteeism by merging pain and cognitive load assessments, presenting a comprehensive method for understanding and mitigating its impact on the industrial workforce.

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Bogdanov, Konstantin, Dmitry Gura, Dustnazar Khimmataliev, and Yulia Bogdanova. "Teaching students to use Decision trees (Dt) for unstructured data." World Journal on Educational Technology: Current Issues 14, no. 5 (2022): 1518–28. http://dx.doi.org/10.18844/wjet.v14i5.7335.

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The research aims to analyze the importance of teaching to use unstructured data methods that students generate from the learning activities and examine the relative efficiency of the decision trees within load conditions and self-efficacy of each learner. The present research collected the data using a questionnaire to analyze self-efficacy and cognitive load among students. The sample included 150 students divided into two groups. The research revealed no significant differences in self-efficacy between the two groups participants (F = 0.01, p> 0.05). According to the results, no differences were identified between the students who worked with unstructured data using decision trees and those students who analyzed the unstructured data using association rules. The research uses an independent t-test for the analysis of cognitive load within the academic environment. No significant differences were detected concerning cognitive load between the two groups of participants. Keywords: unstructured data, decision trees, association rules, self-efficacy, cognitive load, SDGs.

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Jii Toh, Ting, and Zaidatun Tasir. "The Impact of a Mobile Learning Application on Students’ Cognitive Load and Learning Performance in Biology." Journal of Information Technology Education: Research 23 (2024): 026. http://dx.doi.org/10.28945/5380.

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Aim/Purpose: This study aims to analyze the cognitive load experienced by secondary school students in Biology within m-learning environments and its impact on learning performance. Background: Cognitive load has become a critical issue that schools need to address to ensure students can excel in their learning without being overwhelmed. While principles for reducing cognitive load have been extensively discussed in previous research, studies focusing on mobile learning (m-learning) for Biology among students in Malaysia remain limited. This study employed Cognitive Load Theory (CLT) and Cognitive Theory of Multimedia Learning (CTML) to address this gap. By integrating four key principles—segmenting and pretraining, modality, redundancy, and seductive details—into m-learning tasks using the Successive Approximation Model (SAM1), this study aimed to reduce cognitive load and enhance students’ learning performance. Methodology: This study employed a quantitative approach using a randomized pre-test/post-test quasi-experimental design. Students were randomly assigned to either an intervention group (20 students) or a control group (18 students). The study was conducted over four weeks, comprising a three-week intervention period with a one-week interval. Statistical analyses, including independent t-tests, Mann-Whitney U tests, Quade ANCOVA, and Pearson correlation, were used to analyze the quantitative data. Qualitative feedback was analyzed using thematic analysis. Contribution: This study contributes by providing instructional design strategies that incorporate principles for reducing cognitive load in mobile learning for Biology. It also demonstrates how Cognitive Load Theory (CLT) and Cognitive Theory of Multimedia Learning (CTML) can be effectively integrated. By examining the cognitive load experienced by secondary school students in m-learning environments, the study offers valuable insights for designing and implementing effective instructional strategies. Identifying the factors influencing cognitive load enables educators to develop targeted interventions that enhance learning experiences and optimize performance. Findings: The study indicated that the adoption of mobile learning tasks not only significantly reduced cognitive load but also corresponded to enhanced learning performance. Participants engaging in m-learning experienced lower cognitive load, which was positively associated with superior performance in learning tasks, emphasizing the beneficial impact of mobile learning on cognitive load management and academic achievement. Recommendations for Practitioners: Educators and instructional designers are encouraged to incorporate cognitive load principles into their instructional strategies and learning material design to enhance student performance. Policymakers should consider similar strategies to reduce the cognitive load for students in educational settings to improve learning outcomes. Recommendation for Researchers: Researchers are encouraged to replicate the design elements used in this study when developing mobile or online learning materials to reduce learners’ cognitive load and enhance their performance. They should also consider expanding this research to other topics, subjects, and educational levels to provide further insights and validate the effectiveness of these design elements across different contexts. Impact on Society: The findings of this study have significant implications for society, particularly in addressing mental health and stress issues among the younger generation. By identifying strategies to manage cognitive load and reduce stress in online learning environments, the study provides valuable insights for educators, parents, and policymakers. These strategies can help mitigate the adverse effects of cognitive overload, improve learning experiences, and promote better mental well-being. Additionally, the study’s recommendations can guide the development of more effective and supportive learning environments, contributing to overall societal well-being and academic success. Future Research: Future studies could explore cognitive load beyond the intrinsic and extraneous components focused on in this study, examining additional elements within the frameworks of cognitive load theory and multimedia learning. In addition to using the cognitive load questionnaire, exploring other measurement tools could ensure a more comprehensive understanding of cognitive load. Future research might also consider enriching mobile learning tasks by diversifying subject matter and conducting longitudinal cohort studies. Such studies could provide valuable insights into memory retention over extended periods, aiding in optimizing mobile learning frameworks and enhancing educational experiences.

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Kester, Liesbeth, Paul A. Kirschner, and Jeroen J. G. van Merriënboer. "The management of cognitive load during complex cognitive skill acquisition by means of computer-simulated problem solving." British Journal of Educational Psychology 75, no. 1 (2005): 71–85. http://dx.doi.org/10.1348/000709904x19254.

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Zhu, Xiao Min, and Dong Min Cho. "A Study on the Impact of Cognitive Load Factors in Management Simulation Games on Players' Cognitive Absorption." Korean Society of Science & Art 43, no. 1 (2025): 329–40. https://doi.org/10.17548/ksaf.2025.01.30.329.

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McSherry, David. "Balancing user satisfaction and cognitive load in coverage-optimised retrieval." Knowledge-Based Systems 17, no. 2-4 (2004): 113–19. http://dx.doi.org/10.1016/j.knosys.2004.03.006.

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Shelton, Ben, Keith Nesbitt, Alexander Thorpe, and Ami Eidels. "Assessing the cognitive load associated with ambient displays." Personal and Ubiquitous Computing 26, no. 1 (2022): 185–204. http://dx.doi.org/10.1007/s00779-021-01662-w.

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Chen, Yongliang, Zhongzhi Qin, Li Sun, et al. "GDT Framework: Integrating Generative Design and Design Thinking for Sustainable Development in the AI Era." Sustainability 17, no. 1 (2025): 372. https://doi.org/10.3390/su17010372.

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The ability of AI to process vast datasets can enhance creativity, but its rigid knowledge base and lack of reflective thinking limit sustainable design. Generative Design Thinking (GDT) integrates human cognition and machine learning to enhance design automation. This study aims to explore the cognitive mechanisms underlying GDT and their impact on design efficiency. Using behavioral coding and quantitative analysis, we developed a three-tier cognitive model comprising a macro-cycle (knowledge acquisition and expression), meso-cycle (creative generation, intelligent evaluation, and feedback adjustment), and micro-cycle (knowledge base and model optimization). The findings reveal that increased task complexity elevates cognitive load, supporting the hypothesis that designers need to allocate more cognitive resources for complex problems. Knowledge base optimization significantly impacts design efficiency more than generative model refinement. Moreover, creative generation, evaluation, and feedback adjustment are interdependent, highlighting the importance of a dynamic knowledge base for creativity. This study challenges traditional design automation approaches by advocating for an adaptive framework that balances cognitive processes and machine capabilities. The results suggest that improving knowledge management and reducing cognitive load can enhance design outcomes. Future research should focus on developing flexible, real-time knowledge repositories and optimizing generative models for interdisciplinary and sustainable design contexts.

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