Cognitive Resource Management Research Articles

Influence of Self-Regulated Learning on the Academic Performance of Engineering Students in a Blended-Learning Environment

The pandemic environment experienced for more than two years strongly accelerated the use of technological resources to support learning. Using these resources made it evident that higher education students expecting to succeed academically must master digital strategies. The combination of learning experiences and autonomous work required students to selfregulate their learning well to attain the expected performance levels for competitive work that characterizes the engineering profession. So, we designed an exploratory study to evaluate the effect of self-regulated learning on mechanical design students in a Blended Learning (BL) environment using Flipped Learning/Classroom didactics (FPC). Fifty-one students studying under two different educational-model curricula participated. The research employed a mixed methodology. For the quantitative part, the students’ academic grades and results of the Motivation and Learning Strategies Questionnaire (MSLQ SF) applied in its short Spanish version were employed. A questionnaire for self-study management and a competency observation rubric based on the Marzano & Kendall New Taxonomy were used for the qualitative part. The results showed that the students with the best levels of self-regulated learning in BL and FPC contexts obtained the best results in cognitive, organizational, and motivational resource management strategies. They also improved their disciplinary skills and had a higher academic performance.

8 The Battery for Executive Functions in Addiction: Validation of a Novel Screening Tool

Objective:Executive functions (EF) are a primary mediator of both typical and atypical functioning, influencing the progression of psychopathology due to their role in supporting self-monitoring/regulation and top-down control of cognitive processes. According to recent models, EF impairments may contribute to the functional decline of patients with substance use disorder (SUD), exacerbating secondary affective and social symptoms. Despite these potential implications, the tools now commonly used to outline neurocognitive, and specifically EF, impairments in patients with addiction are not tailored to this clinical population, having been developed to assess cognitive or dysexecutive deficits in neurology or geriatric patients. Because of their different clinical focus, such tools are frequently unable to fully delineate the dysfunctional EF profile of addiction patients. We here present the development and validation of a novel specific screening battery for executive disorders in addiction: Battery for Executive Functions in Addiction (BFE-A).Participants and Methods:151 SUD patients and 55 control persons were recruited for the validation of the BFE-A battery. The battery consists of two computerized neurocognitive tasks (Stroop and Go/No-go tasks) and five digitalized neuropsychological tests (focus: short/long-term memory, working memory, focused attention, verbal/non-verbal cognitive flexibility). The tests are designed to assess executive control, inhibition mechanisms, and attention bias toward drugs of abuse.Results:In tests of verbal memory, focused attention, and cognitive flexibility, as well as in computerized tasks, inferential statistical analyses revealed lower performance in SUD patients compared to control participants, indicating a lack of inhibitory processes and dysfunctional management of cognitive resources. The investigation of Cohen’s d values has revealed that inhibitory control, verbal/nonverbal fluency, and short/long-term memory are the areas with the most significant impairments.Conclusions:While the evaluation of EF dysfunctions associated to addiction is a currently underrepresented component of the diagnostic procedure in drug assistance/treatment programs, is also is an essential step for both profiling of patients and design of rehabilitation protocols. Clinical interviews should be complemented by early assessment of cognitive weaknesses and preserved EF skills in order to establishing personalized therapy strategy and perhaps organizing a concurrent phase of cognitive rehabilitation.

Memory‐based deep reinforcement learning for cognitive radar target tracking waveform resource management

AbstractA cognitive radar (CR) system can offer enhanced target tracking performance due to its intelligence on the perception‐action cycle, wherein a CR adaptively allocates the limited transmitting resources based on its perception of surrounding environments. To effectively manage the transmit waveform resource for the target tracking task, CR resource management problem is formulated under the partially observable Markov decision process framework. The sequential decision‐making and the inherent partial observability for target tracking problem are considered. In the proposed method, a long short‐term memory (LSTM)‐based twin delayed deep deterministic policy gradient (TD3) algorithm is developed to effectively solve the problem. A reward function is designed considering Haykin's cognitive executive attention mechanism for radar systems such that the CR resource management policy has stability in the decision of transmit waveform, which follows the principle of minimum disturbance. Simulation results demonstrate the superiority of the proposed LSTM memory‐based TD3 with improved target tracking performance and increased mean rewards for CR.

Attention and body awareness: The role of inhibition and the management of cognitive resources in the perception of spontaneous sensations.

Attention and body awareness: The role of inhibition and the management of cognitive resources in the perception of spontaneous sensations.

Étiopathogénie des troubles neurologiques fonctionnels : marqueurs biologiques et modèles théoriques

ObjectivesFunctional neurological disorders have witnessed intense research activity in the fields of structural and functional neuroimaging for more than twenty years. Thus, we propose a synthesis of recent research findings and etiological hypotheses that have been proposed so far. This work should help clinicians to better understand the nature of the mechanisms involved, but also help patients to increase their knowledge about the biological features underlying their functional symptoms. MethodsWe carried out a narrative review of international publications dealing with neuroimaging and biology of functional neurological disorders, from 1997 to 2023. ResultsSeveral brain networks underlie functional neurological symptoms. These networks play a role in the management of cognitive resources, in attentional control, emotion regulation, in agency and in the processing of interoceptive signals. The mechanisms of the stress response are also associated with the symptoms. The biopsychosocial model helps to better understand predisposing, precipitating, and perpetuating factors involved. The functional neurological phenotype results from the interaction between: i) a specific pre-existing vulnerability resulting from biological background and epigenetic modifications, and ii) exposure to stress factors, according to the stress-diathesis model. This interaction causes emotional disturbances including hypervigilance, lack of integration of sensations and affects, and emotional dysregulation. These characteristics in turn impact the cognitive, motor and affective control processes related with the functional neurological symptoms. ConclusionsA better knowledge of the biopsychosocial determinants of brain network dysfunctions is necessary. Understanding them would help developing targeted treatments, but is also critical for patients care.

Instructional Activities and Study Strategies in Learning Less Commonly Taught Languages

The purpose of this study is to investigate the effective instructional activities as well as the effective study strategies for students to use related to their academic performance in less commonly taught language, in the case of learning Japanese. The sample was college students who studied Japanese from 2017 to 2018 at the beginning level. Factor analysis was used to group items into meaningful factors. Independent t tests were used to investigate correlations with Test Scores. The test scores were gathered from the classroom tests (listening and written). Instructions showed that Cooperative and Challenging Instructions revealed statistically positive relation with Test Scores. Communicative Instruction did not show a statistically positive relation with Test Scores. Learning strategies revealed statistically positive relation with Cognitive Strategy, Memory Practice, Study Skills, and Resource Management. Romaji (romanization of the Japanese written language) Use showed negative correlation. The pedagogical implications were presented. Further investigation was suggested using both quantitative and qualitative approaches to together to investigate more in depth.

Self-regulation of attentional stance facilitates induction of meditative states

This study is focused on the novel concept of the origin or seat of the attentional spotlight, the bodily location at which the attended information is felt to impinge. Existing research on the seat of attention, also described as <i>self-location </i>or <i>egocenter</i>, shows that it can be situated in various ways within the experienced body space (Hanley et al., 2020), and that differences in its location have measurable impact on cognitive skill, emotional temperament, and self-construal, as well as social and moral attitudes (Adam et al., 2015; Fetterman et al., 2020; Fetterman & Robinson, 2013). A recent study by Hartelius et al. (2022) showed that this aspect of attention can be volitionally self-regulated into various internal attentional stances, and that these stances are relatively stable as demonstrated by robust within-subject inter-run correlations of EEG-measured patterns of brain activation for each stance; trials with 8 participants showed that most stances were associated with a unique cortical activation pattern in one or more frequency bands. This study also demonstrated that some attentional stances—that is, locations of the seat of attention—can be objectively associated with specific positive emotional states, suggesting that control of attentional stance should provide direct management of specific cognitive and emotional resources. This suggestion is supported by an earlier study with endurance athletes demonstrating that a discrete attentional stance was associated with each of two tasks: a) reading a news story, and b) experiences of a flow state during athletic endurance practice (Hartelius, 2015; Marolt-Sender, 2014).

A Bayesian Network for the Classification of Human Motion as Observed by Distributed Radar

In this article, a statistical model of human motion as observed by a network of radar sensors is presented where knowledge on the position and heading of the target provides information on the observation conditions of each sensor node. Sequences of motions are estimated from measurements of instantaneous Doppler frequency, which captures informative micromotions exhibited by the human target. A closed-form Bayesian estimation algorithm is presented that jointly estimates the state of the target and its exhibited motion class which are described by a hidden Markov model. To correct errors in the estimated motion class distribution introduced by faulty modeling assumptions, calibration of the probability distribution and measurement likelihood is performed by isotonic regression. It is shown, by modeling sensor observation conditions and by isotonic calibration of the measurement likelihood that a cognitive resource management system is able to increase classification accuracy by 5 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${\%}$</tex-math></inline-formula> –10 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${\%}$</tex-math></inline-formula> while utilizing sensor resources in accordance with defined mission objectives.

Reconceptualizing breaks in translation: Breaking down or breaking through?

Various observable on-screen translator behaviors, such as extended pauses in activity, mouse hovering, cycling through tabs/windows, and different kinds of scrolling, all common occurrences during task completion, have been regarded as potential problem indicators (cf. Angelone, 2018). Their presence is often attributed to a breakdown in declarative and/or procedural knowledge at a concrete problem nexus (Angelone and Shreve, 2011). Inspired by recent translation process research on aspects of cognitive ergonomics, pause-related cognitive rhythms (Muñoz and Cardona, 2018), and Kussmaul’s notion of parallel activity in the translation process (1995), we re-examine such phenomena through a different lens. We propose these phenomena may represent the loci of volitional, potentially strategic breaks rather than problem indicators per se. That is, the breaks observed are not necessarily linked to specific problems, but rather to subjects’ cognitive resource management. Our findings suggest that apparently random behaviors, seemingly unrelated to the task, generally have a positive impact on performance from both process and product perspectives. We refer to these breaks as instances of cognitive suspension, and, based on our findings, propose that translators engage in them as a refresh mechanism when performance has either waned or runs the risk of doing so. We start by examining cognitive suspension in terms of types and scope. This is followed by an empirical analysis of its direct impact on translation performance, as established by number of errors, number of generated characters, and number of typos within established windows (areas of interest) that precede and follow its occurrence.

Smart City + IoT Standardization Application Practice Model and Realization of Key Technologies.

Smart city gathers heterogeneous information, which requires a unified data access and collection mechanism. In this paper, based on the computing framework of IoT put forward to satisfy urban sensing network data acquisition, transmission, and computing technology system, according to the function requirements of IoT gateway, we put forward the method of building software system and hardware system and the urban perception network middleware architecture that can meet the demand of M2M, which can realize dynamic management of cognitive resources. It also supports ubiquitous services over HTTP. This is of great significance for providing intelligent services with diversity of solvers, controllers, and computing terminals. This paper focuses on how to comprehensively apply intelligent sensing, wireless transmission, data mining, and other technologies of the Internet of Things to associate data with typical application examples such as vehicle sensing and positioning technology and urban security sensor application. These typical applications can effectively solve the practical problems in urban operation and management, meet the needs of the expansion of the concept of Internet of things in urban management and the continuous deepening of management, and improve the scientific and intelligent level of urban operation and management.

Does the Simon Effect Interfere with the Synergy Between Perception and Action?

Research suggests that - particularly - the execution of precision-demanding far-aiming tasks necessitates an optimal coupling between perception and action. In this regard, the duration of the last fixation before initiating movement - i.e., the Quiet Eye (QE) - has been functionally related to subsequent motor performance. In the current study, we investigated potential mechanisms of QE by applying the Simon paradigm - i.e., cognitive interferences evoked by stimulus-effect incompatibilities over response selection. To this end, we had participants throw balls as precisely as possible, either with their left or right hand (hands condition, HC) or at left or right targets (targets condition, TC), respectively. Via monaural auditory stimuli, participants received information about the hand side and the target side, respectively, either with compatible (i.e., congruent stimulus-effect side) or incompatible (i.e., incongruent stimulus-effect side) stimulus-effect mappings. Results showed that participants reacted slower and showed later first fixation onsets at the target in incompatible vs. compatible trials, thus, replicating and extending the classical Simon effect. Crucially, in the HC, there were earlier QE onsets and longer QE durations in incompatible (vs. compatible) trials, suggesting an inhibition of cognitive interferences over response selection to preserve motor performance. These findings are in line with attentional explanations of QE, suggesting optimized attentional control with efficient management of limited cognitive resources (optimal-attentional-control explanation) or with the inhibition of alternative response parametrization (inhibition explanation).

INVESTIGATING SELF-REGULATED LEARNING STRATEGIES FOR DIGITAL LEARNING RELEVANCY

Purpose: The rise of digital learning and the prevalence of affordable devices are convenient for young adults who are accustomed to using their digital devices for almost everything such as communication, collaboration, and accessing multiple sources of information for solutions. However, the lack of ability to self-regulate learning processes has led to poor learning performance among undergraduates. Therefore, this study examined the effects of self-regulated learning strategies (SRLS) on learning performance among Malaysian IT undergraduates. Methodology: A sample of IT undergraduates from private higher education institutions in Malaysia participated in the study. Quantitative data from a total of 563 respondents was collected through questionnaire surveys and analysed using PLS-SEM. The common method variance was utilized in this paper. Findings: The findings of this study constitute essential results that three out of four SRLS domains (cognitive engagement, resource management, and motivational beliefs) positively influenced the students’ perception of learning performance. Significance: This study provides insight into the best SRLS to excel in digital learning for deeper learning particularly in the Malaysian context. Implications of the findings on higher education institutions as well as recommendations for future research are discussed.

Investigating the Effective Instructional Activities as well as Advising Students to use the Effective Study Strategies related to Their Academic Performance in Less Commonly Taught Language, Particularly Japanese

Investigating the Effective Instructional Activities as well as Advising Students to use the Effective Study Strategies related to Their Academic Performance in Less Commonly Taught Language, Particularly Japanese Masako M. Nunn Abstract The purpose of this study is to investigate the effective instructional activities as well as advising students to use the effective study strategies related to their academic performance in less commonly taught language, particularly Japanese. The sample was college students who studied Japanese from 2017 to 2018 at the beginning level. Factor analysis was used to group items into meaningful factors. Independent ttests were used to investigate correlations with Test Scores. The test scores were gathered from the classroom tests (listening and written). Instructions showed that Cooperative and Challenging Instructions revealed statistically positive relation with Test Scores. Communicate Instruction did not show statistically positive relation with Test Scores. Learning strategies revealed statistically positive relation with Cognitive Strategy, Memory Practice, Study Skills, and Resource Management. Romaji (romanization of the Japanese written language) Use showed negative correlation. The pedagogical implications were presented and further investigation will be conducted using online survey. Full Text: PDF DOI: 10.15640/jehd.v10n3a4

The relationship between cognitive engagement and students’ performance in a simulation-based training environment: an information-processing perspective

ABSTRACT In this paper, we adopted an information-processing perspective to examine the relationship between cognitive engagement and students’ performance in a simulation-based training environment. In particular, we examined what forms of cognitive engagement students used while diagnosing virtual patients and whether engagement forms predicted students’ diagnostic confidence and efficacy. A total of 88 medical students from a large North American university voluntarily participated in this study. We used latent profile analysis (LPA), a person-centered statistical method, to identify groups of students with similar information processing patterns. Findings from this study revealed that students displayed various forms of cognitive engagement, i.e. recipience, resource management, and task-focused. Moreover, we found that group difference in diagnostic confidence was moderated by task complexity. In terms of diagnostic efficacy, students who were task-focused or resource managers did better than the recipience students. The findings advance our understanding of theories of cognitive engagement as well as inform the design of effective interventions in developing simulation-based learning environments.

Transitions Between Low and High Levels of Mental Workload can Improve Multitasking Performance

OCCUPATIONAL APPLICATIONS Complex and dynamic environments including military operations, healthcare, aviation, and driving require operators to transition seamlessly between levels of mental workload. However, little is known about how the rate of an increase in workload impacts multitasking performance, especially in the context of real-world tasks. We evaluated both gradual and sudden workload increases in the dynamic multitasking environment of an Unmanned Aerial Vehicle (UAV) command and control testbed and compared them to constant workload. Workload transitions were found to improve response time and accuracy compared to when workload was held constant at low or high. These results suggest that workload transitions may allow operators to better regulate mental resources. These findings can also inform the design of operations and technology to assist operators’ management of cognitive resources, which include negating the adverse effects of vigilance decrements during low workload periods and data overload during high workload periods.

Moderating Role of Learning Strategies Between Meta-Cognitive Awareness and Study Habits Among University Students

The purpose of present study is to examine the role of learning strategies as moderator between meta-cognitive awareness and study habits among university students. Sample comprises of 200 students (100 male students and 100 female students) of various universities of Islamabad and Rawalpindi with age ranging from 18-25 years. In order to assess study variables questionnaires were used included Meta-Cognitive Awareness Inventory (Schraw &amp; Dennison, 1994) measuring two-components of meta-cognition that are knowledge and regulation of cognition. Study habits demonstrated by the students were measured by the Study Habits Inventory (Wrenn, 1941). Motivated Strategies for Learning Questionnaire (Pintrich, Smith, Garcia, &amp; McKeachie, 1991) which includes motivation and learning strategies scales. In the present study, only the learning strategies section was utilized, which measures the cognitive strategies and resource management strategies. Results revealed positive correlation between research instruments and are also having good reliability. Regression analysis reflected that meta-cognitive awareness predicts study habits among university students. Regression analysis also suggested that learning strategies including resource management strategies and cognitive strategies significantly moderates the relationship between meta-cognitive awareness and study habits. It is also explored gender differences on learning strategies, meta-cognitive awareness and study habits. Future implications of the study were also discussed.

Programs and Practices for Identifying and Nurturing High Intellectual Abilities in Spain

The recent educational legislation in Spain shows a great interest in enhancing the talents of all citizens. Different models of identification and intervention for students with high intellectual abilities (HIAs) coexist. The assessment model based on intelligence is still in force in the psychoeducational guidance field; however, from the research, other multidimensional and developmental models are prevalent, rethinking the nature of giftedness and talent, as well as identification and educational practices. These models consider HIA as potential in development, depending on the interrelation among neurobiological bases, personal, and environmental conditions. Efforts are being made to detect high-ability students. The most common intervention measures are the school enrichment of the curriculum, curricular adaptations, and acceleration. Several universities and some autonomous communities (i.e., school districts in the states) have organized extracurricular enrichment programs, some for longer than 10 years. The training of specialized teachers in high abilities has substantially increased, both in the Ministry of Education and autonomous local communities. Universities have also included some subjects in their programs related to this issue of gifted education with specific training designed in postgraduate courses. The research agendas of HIAs currently focus on studying metric approximation, identification and profiles, cognitive functioning and creativity, management of cognitive resources, socioemotional characteristics, gender, enrichment programs, and their effectiveness.

Designing a Self-Optimization System for Cognitive Wireless Home Networks

In this paper, we describe the design and implementation of an extensible and flexible self-optimization framework for cognitive home networks that employs cognitive wireless networking and agent-based design principles. We provide a “first-principles” derivation of its architecture based on a careful analysis of user requirements on wireless home networks (WHNs), state the related design objectives and constraints, and address those in the context of present-day and emerging radio platforms. We utilize the cognitive resource manager as an architecture of the individual agents. This architecture serves as a “constraint that de-constrains,” i.e., it allows achieving high system flexibility, while providing structural constraints to ensure robustness. We show that the designed system is capable of solving complex utility maximization problems constrained with user, operator, and regulatory policies in the crowded ISM bands. The system successfully operates on an extensible parameter configuration space across multiple protocol layers. For example, the prototype employs diverse optimization algorithms, and can also benefit from radio environment map information on primary transmitters propagated through the integrated policy mechanism. The proposed system delivers both efficient and robust radio resource management, and enables comfortable WHN experimentation by providing extensibility of sensory inputs, actuation parameters, and optimization algorithms.

Cognitive Resource Optimization for the Decomposed Cloud Gaming Platform

Contrary to conventional gaming-on-demand services that stream gaming video from cloud to players' terminals, a decomposed cloud gaming platform supports flexible migrations of gaming components between the cloud server and the players' terminals. In this paper, we present the design and implementation of the proposed decomposed gaming system. The cognitive resource optimization of the system under distinct targets, including the minimization of cloud, network, and terminal resources and response delay, subject to quality of service (QoS) assurance, is formulated as a graph partitioning problem that is solved by exhaustive searches. Simulations and experimental results demonstrate the feasibility of cognitive resource management in a cloud gaming system to efficiently adapt to variations in the service environments, such as increasing the number of supported devices and reducing the network bandwidth consumption of user terminals, while satisfying different QoS requirements for gaming sessions. We also suggest two heuristic algorithms based on local greedy and genetic algorithm approaches, which can potentially provide scalable but suboptimal solutions in large-scale implementations.

Importance of Self-Directed Learning

All changes in society always changing living conditions and human activity putting the human face and many other issues that I always require prompt and adequate continuous adaptation to the requirements of modern life, always based on up to date information and the ability to develop behavior flexible in relation to circumstances. Modern man is forced to continuously learn to cope during his life changes that occur in the universe of knowledge, in his professional work, the entire content of life. This research has proposed the views of students on the introduction of a special course in the academic curricula in order to prepare them for lifelong learning, independent learning. Thus were identified reasons why students should attend this course with functions: motivation for learning, identifying learning styles and strategies, setting learning objectives according to their needs, planning, monitoring and assessment of learning, training and development of cognitive skills, motivational and resource management. The research is important because it measures the contribution of students to their own training through the use of self-directed learning guides, their motivation to prepare and develop as individuals capable of facing life alone and successfully obstacles, particularly those related to training.