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Fonooni, Benjamin. "Cognitive Interactive Robot Learning." Doctoral thesis, Umeå universitet, Institutionen för datavetenskap, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-97422.
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Building general purpose autonomous robots that suit a wide range of user-specified applications, requires a leap from today's task-specific machines to more flexible and general ones. To achieve this goal, one should move from traditional preprogrammed robots to learning robots that easily can acquire new skills. Learning from Demonstration (LfD) and Imitation Learning (IL), in which the robot learns by observing a human or robot tutor, are among the most popular learning techniques. Showing the robot how to perform a task is often more natural and intuitive than figuring out how to modify a complex control program. However, teaching robots new skills such that they can reproduce the acquired skills under any circumstances, on the right time and in an appropriate way, require good understanding of all challenges in the field. Studies of imitation learning in humans and animals show that several cognitive abilities are engaged to learn new skills correctly. The most remarkable ones are the ability to direct attention to important aspects of demonstrations, and adapting observed actions to the agents own body. Moreover, a clear understanding of the demonstrator's intentions and an ability to generalize to new situations are essential. Once learning is accomplished, various stimuli may trigger the cognitive system to execute new skills that have become part of the robot's repertoire. The goal of this thesis is to develop methods for learning from demonstration that mainly focus on understanding the tutor's intentions, and recognizing which elements of a demonstration need the robot's attention. An architecture containing required cognitive functions for learning and reproduction of high-level aspects of demonstrations is proposed. Several learning methods for directing the robot's attention and identifying relevant information are introduced. The architecture integrates motor actions with concepts, objects and environmental states to ensure correct reproduction of skills. Another major contribution of this thesis is methods to resolve ambiguities in demonstrations where the tutor's intentions are not clearly expressed and several demonstrations are required to infer intentions correctly. The provided solution is inspired by human memory models and priming mechanisms that give the robot clues that increase the probability of inferring intentions correctly. In addition to robot learning, the developed techniques are applied to a shared control system based on visual servoing guided behaviors and priming mechanisms. The architecture and learning methods are applied and evaluated in several real world scenarios that require clear understanding of intentions in the demonstrations. Finally, the developed learning methods are compared, and conditions where each of them has better applicability are discussed.Att bygga autonoma robotar som passar ett stort antal olika användardefinierade applikationer kräver ett språng från dagens specialiserade maskiner till mer flexibla lösningar. För att nå detta mål, bör man övergå från traditionella förprogrammerade robotar till robotar som själva kan lära sig nya färdigheter. Learning from Demonstration (LfD) och Imitation Learning (IL), där roboten lär sig genom att observera en människa eller en annan robot, är bland de mest populära inlärningsteknikerna. Att visa roboten hur den ska utföra en uppgift är ofta mer naturligt och intuitivt än att modifiera ett komplicerat styrprogram. Men att lära robotar nya färdigheter så att de kan reproducera dem under nya yttre förhållanden, på rätt tid och på ett lämpligt sätt, kräver god förståelse för alla utmaningar inom området. Studier av LfD och IL hos människor och djur visar att flera kognitiva förmågor är inblandade för att lära sig nya färdigheter på rätt sätt. De mest anmärkningsvärda är förmågan att rikta uppmärksamheten på de relevanta aspekterna i en demonstration, och förmågan att anpassa observerade rörelser till robotens egen kropp. Dessutom är det viktigt att ha en klar förståelse av lärarens avsikter, och att ha förmågan att kunna generalisera dem till nya situationer. När en inlärningsfas är slutförd kan stimuli trigga det kognitiva systemet att utföra de nya färdigheter som blivit en del av robotens repertoar. Målet med denna avhandling är att utveckla metoder för LfD som huvudsakligen fokuserar på att förstå lärarens intentioner, och vilka delar av en demonstration som ska ha robotens uppmärksamhet. Den föreslagna arkitekturen innehåller de kognitiva funktioner som behövs för lärande och återgivning av högnivåaspekter av demonstrationer. Flera inlärningsmetoder för att rikta robotens uppmärksamhet och identifiera relevant information föreslås. Arkitekturen integrerar motorkommandon med begrepp, föremål och omgivningens tillstånd för att säkerställa korrekt återgivning av beteenden. Ett annat huvudresultat i denna avhandling rör metoder för att lösa tvetydigheter i demonstrationer, där lärarens intentioner inte är klart uttryckta och flera demonstrationer är nödvändiga för att kunna förutsäga intentioner på ett korrekt sätt. De utvecklade lösningarna är inspirerade av modeller av människors minne, och en primingmekanism används för att ge roboten ledtrådar som kan öka sannolikheten för att intentioner förutsägs på ett korrekt sätt. De utvecklade teknikerna har, i tillägg till robotinlärning, använts i ett halvautomatiskt system (shared control) baserat på visuellt guidade beteenden och primingmekanismer. Arkitekturen och inlärningsteknikerna tillämpas och utvärderas i flera verkliga scenarion som kräver en tydlig förståelse av mänskliga intentioner i demonstrationerna. Slutligen jämförs de utvecklade inlärningsmetoderna, och deras applicerbarhet under olika förhållanden diskuteras.
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Yoder, Ryan J. "Learning Cognitive Feedback Specificity during Training and the Effect on Learning for Cognitive Tasks." Ohio University / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1256155902.
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Yoder, Ryan J. "Learning cognitive feedback specificity during training and the effect of learning for cognitive tasks." Ohio : Ohio University, 2009. http://www.ohiolink.edu/etd/view.cgi?ohiou1256155902.
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任春華 and Chun-wa Yum. "Learning strategies and cognitive engagement." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2008. http://hub.hku.hk/bib/B41717053.
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Yum, Chun-wa. "Learning strategies and cognitive engagement." Click to view the E-thesis via HKUTO, 2008. http://sunzi.lib.hku.hk/hkuto/record/B41717053.
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Reeder, Sarah. "Relationships in Aging, Cognitive Processes, and Contingency Learning." TopSCHOLAR®, 2006. http://digitalcommons.wku.edu/theses/259.
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This study investigated the influence of age, processing speed, working memory,and associative processes on the acquisition of contingency information. Young and older adults completed positive (+.65) and negative (-.65) contingency tasks that measured their ability to discover the relationship between a symptom (e.g., FEVER) and a fictional disease (e.g., OLYALGIA). Both d' scores, i.e., contingency learning, and contingency estimates, i.e., contingency judgment, were examined. Participants were also asked to complete cognitive tasks that measure the constructs of processing speed, working memory resources, associative memory, and associative learning. Structural equation modeling was used to examine the direct and indirect relationships between processing speed, working memory resources, associative memory, associative learning, and positive and negative contingency learning and judgment for young and older adult groups. Young adults outperformed older adults on the cognitive tasks and on contingency learning and judgment tasks. However, age differences were smaller for the positive contingency than for negative contingency. A comparison of the structural equation models for young and older adults showed no relationship between any cognitive construct and negative contingency learning. However, young adults' judgment for the negative contingency was directly influenced by associative learning, while their learning and judgment for the positive contingency was directly influenced by associative memory. For older adults, working memory executive function directly influenced their judgment for the negative contingency and their learning and judgment for the positive contingency. Processing speed had an indirect effect on older adults' contingency learning and judgment that was mediated by working memory executive functioning. The differences in the young adults' models as well as the difference between the young and older adults' models for positive and negative contingencies suggest that while associative processing is important, it may not account for all of the variation in contingency learning and judgment. The young adults' models for the negative contingency task indicates that higher level processes, such as inductive reasoning, maybe involved in negative contingency judgment because the associative learning task required some level of hypothesis testing. In contrast, positive contingency learning and judgment could rely primarily on more basic associative processes. The present findings therefore suggest that an overall model of contingency learning must include both associative processes and inductive reasoning processes. Older adults' general contingency performance was most directly related to their working memory executive functioning, suggesting that the decline in their working memory has the strongest effect on their ability to acquire and use information about contingencies. In fact, the age related decline in working memory seems to affect older adults' ability to acquire both positive and negative contingencies. The similarities across the older adult models for positive and negative contingencies indicate that the underlying deficit in older adults' working memory executive functioning that affects their overall contingency learning and judgment performance. This basic working memory executive functioning deficit for older adults also explains why their models for positive and negative contingency did not exhibit direct relationships between associative tasks and contingency learning as observed for the young adult models.
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Wong, Pik-ha. "Cognitive obstacles in learning the laws of indices." [Hong Kong : University of Hong Kong], 1994. http://sunzi.lib.hku.hk/hkuto/record.jsp?B13834216.
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Strehler, Anne. "The relationship between cognitive load, cognitive style and multimedia learning." Thesis, Pretoria : [s.n.], 2008. http://upetd.up.ac.za/thesis/available/etd-10282008-120644/.
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Leboe, Jason P. Milliken Bruce. "The inferential basis of perceptual performance /." *McMaster only, 2002.
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Eleftheriou, Georgie. "Cognitive reinforcement learning across the lifespan." Thesis, University of Surrey, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.616939.
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From the moment of birth, there is a direct interaction to our environment. This is the main principle of learning (Sutton & Barto, 1998). For instance when a new-born is playing there is a sensory and motor connectivity to the environment by allowing the cause and effect information, the outcome of an action and the achievement of a goal to be learned (Sutton & Barto, 1998). Moreover, learning provides lmowledge about us and our environment. Wliether we learn to ride a bicycle in adolescence or learn to drive a car in adulthood we are conscious of the several responds to our actions, which we want to influence what is happening in our behaviour during the lifespan. Learning from interactions is considered as an important field of research, underlying all theories of behaviour. The approached theory we explored is called reinforcement learning and it is more goal directed learning from interaction. Previous work in this area has focused mainly to what extend people learn to make choices that lead to positive outcomes and avoid making those that lead to negative outcomes (Frank et aI., 2004). This thesis extended this work by behaviourally investigating reinforcement learning across life span (7-55 years old). Using the reward bias coefficient (RBc) a measurement of an individual's tendency to follow reward or avoid punishment, in the face ofunceliainty, results demonstrated significant age differences in learning from positive and negative probablistic feedback between these age groups (7-10, 11-14, 15-18, 19-35 and 40-55 years old). This is the first study to compare qualitative changes in RBc across lifespan indicating the importance of positive and negative feedback learning in cognitive perfomance.
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Ball, N. R. "Cognitive maps in Learning Classifier Systems." Thesis, University of Reading, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.280670.
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Baban, Shaswar Tharwat Mohammed. "Context-aware cognitive radios learning from data using machine learning techniques." Thesis, King's College London (University of London), 2016. https://kclpure.kcl.ac.uk/portal/en/theses/contextaware-cognitive-radios-learning-from-data-using-machine-learning-techniques(674aef35-8640-41d2-97b2-922182f096cc).html.
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Wired or wireless, connectivity has been a vital commodity of life and more so recently in the realm of information age. Those who have access to faster, more reliable and more ubiquitous connectivity—put simply, those who are “better connected”—will have significant advantages in commerce, research and a host of other arenas. In regards to wireless communications, due to the explosion in demand for higher capacity networks, availability of free spectrum resources have become increasingly scarce. The UHF spectrum band in particular, due to its excellent electromagnetic properties, has been reported as inefficiently used and congested by many spectrum regulators of the world. This spectrum resource scarcity issue combined with the ongoing research and development for more intelligent, autonomous and self-aware radio communication led to a vast amount of research on the concept of Cognitive Radio. This thesis researches the learning unit of cognitive radios. The learning unit is responsible for processing information and autonomous decision making. In particular, the research is focused on the extraction and usage of contextual information from the radio environment (e.g. Radio Access Technology type, channel access pattern learning/recognition) and how such information could be exploited to improve the performance of the cognitive radio. The key metrics discussed will be based on information extraction under noise, channel blocking and interference reduction to primary users. We present a set of novel works involving Machine Learning, which is a branch of Artificial Intelligence. New implementation and use cases of state-of-the-art machine learning algorithms are presented that learn from real-life data. In a testbed setup we program software defined radios to recognize different Radio Access Technologies and their channel access patterns. The main technique used in the majority of the thesis is Artificial Neural Networks, concretely: Multi-Layer Perceptron Neural Nets, Self-Organizing Neural Nets, and Deep Auto-Encoders. In some of the works these neural network architectures have been combined in a novel way with Support Vector Machines, and Reinforcement Learning algorithms for channel classification and access. In this thesis we show that it is possible to achieve 95% correct classification at -25 dB among three different radio access technologies, namely, DVB-T, WCDMA and IEEE 802.11a, where, consequently, we can reason over the outcome of this classification to differentiate between primary and secondary transmissions. We also show that, through the use of the proposed autoencoder approximate Q-learning technique, such context-aware cognitive radio can achieve better key performance metrics in dynamic spectrum access as compared to previously researched Q-learning algorithms.
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Bevington, Jason P. "Cognitive management : using cognitive therapy to facilitate organisational change and learning." Thesis, University of Edinburgh, 1999. http://hdl.handle.net/1842/26327.
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Employees in today's organisations face the challenge of coping with difficulties caused by constant change. Although an abundance of change management strategies and organisational learning initiatives are available, the literature is abound with examples of projects that have been ineffective. This thesis brings the organisational, clinical and cognitive levels of analysis together by exploring the efficacy of applying cognitive therapy to organisations. This psychotherapeutic approach has been used successfully and extensively in clinical psychology and psychiatry to identify and challenge people's interpretations of situations and events. Utilising a non-equivalent groups pre-test/ post-test design, it is hypothesised that 'cognitive management', a combination of cognitive therapy and organisational strategies, will help group members to identify and modify their work-related automatic thoughts and assumptions and consequently lead to improved employee well-being and effectiveness. As groups provide the foundations of many organisations, this method of working constitutes the focus of the research. The sample comprises of two teams (one intervention and one control) from the public sector and two teams (one intervention and one control) from the private sector. Both quantitative and qualitative methods were used. The results of the empirical investigation suggest that cognitive management is effective in positively changing employees work-related thoughts, emotions and behaviours. Methodological considerations are discussed and further applications of cognitive management are outlined.
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Lee, Saebyul. "Learning Abstract Numbers in Concrete Environment." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1482751226985893.
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Noble, Rhonda. "An assessment of student cognition in basic instruction bowling classes." Morgantown, W. Va. : [West Virginia University Libraries], 2002. http://etd.wvu.edu/templates/showETD.cfm?recnum=2539.
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Thesis (Ed. D.)--West Virginia University, 2002.Title from document title page. Document formatted into pages; contains viii, 152, [25] p. : ill. Includes abstract. Includes bibliographical references (p. 141-152).
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Geddes, Bruce Wynter. "The effects of learning goals on implicit and explicit learning." Thesis, Durham University, 1997. http://etheses.dur.ac.uk/4898/.
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This thesis, using Berry & Broadbent's (1984) computer-person interaction task, shows that three different learning goals result in three different learning modes. Experiment 1 demonstrated this effect: a pattern search goal resulted in explicit rule learning; a control task goal, as used in previous studies, resulted in instance learning where all instances are entered into a look-up table irrespective of whether the instance had been performed correctly or incorrectly; a dual goal, consisting of a combination of the last two goals, resulted in instance learning where only correct instances were entered into a look-up table. Experiment 2 refuted one explanation of the learning goal effect - it is not due to an indirect effect of altering the range of interactions that subjects see. Therefore, it must be due to a direct cognitive effect. Experiment 3 explored this direct effect showing that, in terms of Klahr and Dunbar's (1988) Dual Space model, a pattern search goal encourages the search primarily of rule space whereas a control task goal confines subjects to a search of instance space. The positive effect of self- explanations on both instance and rule learning was also demonstrated. Experiment 4 showed that subjects with the dual goal learn purely implicitly - all goal groups with a concurrent task of random number generation produced identical results to those of Experiment 1's dual goal group. Experiment 5 examined the leaning goal effect on memory. Surprisingly, pattern search learners may still learn instances and dual goal subjects may still memorise instances on which they make errors. Control task learners' abilities are a simple reflection of their memories. Experiments 6a and 6b showed that only near transfer of leaning occurs for control task instance learners. However, far transfer also occurs for pattern search learners, but only when the task transferred to is less complex, or of comparable complexity.
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Shaik, Kadir Munirah. "Enlightening Science: Addressing the Cognitive and Non-Cognitive Aspects of Science Learning." Thesis, Australian Catholic University, 2018. https://acuresearchbank.acu.edu.au/download/62b15f077f8030a2d790b4b72bc33a91600baaf09ed4f6985e88b65dd6c99d62/6070465/SHAIK_KADIR_2018_Enlightening_science_addressing_the_cognitive_and.pdf.
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Physical science (or physics) is known to be one of the least popular school curriculum domains, mainly because of its complexity. When students encounter seemingly insurmountable difficulties when learning something, they lose the motivation to continue. It has been suggested that both the cognitive (e.g., students’ conceptual understanding and achievement) and non-cognitive (e.g., psychological aspects such as academic self-concept and motivation) factors of learning are essential for helping students achieve their optimal best in a curriculum domain. However, there has not been much research, if any, which uses a dual approach to investigate both aspects of science learning. Most research focused on either the cognitive or non-cognitive aspect. Research on cognitive aspects of learning suggests that element interactivity is a useful construct with which to examine students’ cognitive processes and the complexity of learning materials. However, there has been no illustration on how an analysis of interacting elements in science learning tasks may improve learning. Studies on the effects of reducing element interactivity on students’ achievement and motivation are also scarce. Research on non-cognitive aspects of learning suggests that motivation is necessary to sustain students’ engagement in learning. However, if the complexity of learning tasks is so high that students experience repeated failures, their motivation is not sustained. Therefore, both cognitive and non-cognitive factors play a crucial role in students’ learning and both must be present to ensure an optimal learning environment.
The overarching aim of this thesis is to investigate the cognitive (i.e., students’ achievement and cognitive processes in terms of element interactivity) and non-cognitive aspects (i.e., self-concept and other motivational factors) of students’ learning of science. The thesis includes five studies. The first study showed that the five main findings from past self-concept research were applicable to the Grade 7 students from Singapore selected for the study. Students’ sense of competence in a curriculum domain enhanced their future achievement in that domain only, except for physics and math, which showed interrelatedness (i.e., the enhancement was transferable from one domain to the other). The findings showed a strong interplay between academic self-concept and achievement and highlighted the important role that academic self-concept plays in determining students’ learning outcomes. Therefore, strategies to enhance students’ self-concept should be implemented in schools.
The results of the second study showed strong positive correlations between students’ achievement and their motivation within a school year. Students’ Grade 6 (final primary school year) achievement did not strongly contribute to their motivation in Grade 7, indicating the importance of providing an optimal learning environment in Grade 7 for a positive start to their secondary school education.
The third study showed how the interactions between the elements (i.e., element interactivity) in problem solving tasks reflect their level of complexity and how the number of operational lines that students used to solve problems could indicate their level of expertise in problem solving in that domain. This study highlighted the role of element interactivity as a planning tool for learning tasks and how teachers may use it to gain insights into students’ cognitive processes.
The fourth study involved an intervention, which reduced element interactivity during science instruction, and the results revealed that students’ achievement improved, and their science self-concept was maintained. The results and implications of the first four studies were used to design a dual-approach instruction to facilitate both cognitive and non-cognitive aspects of students’ learning in the fifth and final study. The results of the final intervention study indicated that the dual-approach instruction was beneficial. The experimental group of students outperformed the comparison group in both cognitive and non-cognitive factors. Results from multiple regression analyses revealed that those who experienced the intervention not only had higher achievement than those in the comparison group in the complex problem tasks, but also had higher motivation (i.e., self-regulation, task goal, inquiry, and educational and career aspirations) and higher academic self-concept (i.e., sense of competence).
This thesis demonstrates that there are strong associations and a significant interplay between students’ achievement and motivation levels (i.e., cognitive and non-cognitive aspects of learning). The analysis of learning tasks and instruction in terms of element interactivity enables the scaffolding of complex learning tasks to suit students’ cognitive levels, leading to higher achievement. Higher achievement contributes to higher motivation levels, including students’ academic self-concept. When learning environments attend to basic psychological needs (i.e., a sense of competence, autonomy, and relatedness), students’ motivation is enhanced and when motivated students experience learning that is within their ability and cognitive load capacities, their self-beliefs and motivation in the learning domain are sustained. Attention to both cognitive and non-cognitive factors in learning situations maximizes students’ learning potential and should therefore be strongly considered by educators and curriculum planners.
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Turaga, Srinivas C. "Learning image segmentation and hierarchies by learning ultrametric distances." Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/54626.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 2009.Cataloged from PDF version of thesis.
Includes bibliographical references (p. 100-105).
In this thesis I present new contributions to the fields of neuroscience and computer science. The neuroscientific contribution is a new technique for automatically reconstructing complete neural networks from densely stained 3d electron micrographs of brain tissue. The computer science contribution is a new machine learning method for image segmentation and the development of a new theory for supervised hierarchy learning based on ultrametric distance functions. It is well-known that the connectivity of neural networks in the brain can have a dramatic influence on their computational function . However, our understanding of the complete connectivity of neural circuits has been quite impoverished due to our inability to image all the connections between all the neurons in biological network. Connectomics is an emerging field in neuroscience that aims to revolutionize our understanding of the function of neural circuits by imaging and reconstructing entire neural circuits. In this thesis, I present an automated method for reconstructing neural circuitry from 3d electron micrographs of brain tissue. The cortical column, a basic unit of cortical microcircuitry, will produce a single 3d electron micrograph measuring many 100s terabytes once imaged and contain neurites from well over 100,000 different neurons. It is estimated that tracing the neurites in such a volume by hand would take several thousand human years. Automated circuit tracing methods are thus crucial to the success of connectomics. In computer vision, the circuit reconstruction problem of tracing neurites is known as image segmentation. Segmentation is a grouping problem where image pixels belonging to the same neurite are clustered together. While many algorithms for image segmentation exist, few have parameters that can be optimized using groundtruth data to extract maximum performance on a specialized dataset. In this thesis, I present the first machine learning method to directly minimize an image segmentation error. It is based the theory of ultrametric distances and hierarchical clustering. Image segmentation is posed as the problem of learning and classifying ultrametric distances between image pixels. Ultrametric distances on point set have the special property that
(cont.) they correspond exactly to hierarchical clustering of the set. This special property implies hierarchical clustering can be learned by directly learning ultrametric distances. In this thesis, I develop convolutional networks as a machine learning architecture for image processing. I use this powerful pattern recognition architecture with many tens of thousands of free parameters for predicting affinity graphs and detecting object boundaries in images. When trained using ultrametric learning, the convolutional network based algorithm yields an extremely efficient linear-time segmentation algorithm. In this thesis, I develop methods for assessing the quality of image segmentations produced by manual human efforts or by automated computer algorithms. These methods are crucial for comparing the performance of different segmentation methods and is used through out the thesis to demonstrate the quality of the reconstructions generated by the methods in this thesis.
by Srinivas C. Turaga.
Ph.D.
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Campbell, Bruce. "Age Matters: The Cognitive Strategies and Benefits of Learning Among College-Degreed Older Adults." [Yellow Springs, Ohio] : Antioch University, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=antioch1140733437.
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Thesis (Ph.D.)--Antioch University, 2006.Title from PDF t.p. (viewed Mar. 27, 2007). Advisor: Alan Guskin, Ph.D. Keywords: late life learning, cognitive strategies, mental acuity, benefits of learning, lifespan learning, importance of learning. Includes bibliographical references (p. 217-227).
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Skulmowski, Alexander, and Günter Daniel Rey. "Measuring Cognitive Load in Embodied Learning Settings." Universitätsbibliothek Chemnitz, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-227345.
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In recent years, research on embodied cognition has inspired a number of studies on multimedia learning and instructional psychology. However, in contrast to traditional research on education and multimedia learning, studies on embodied learning (i.e., focusing on bodily action and perception in the context of education) in some cases pose new problems for the measurement of cognitive load. This review provides an overview over recent studies on embodied learning in which cognitive load was measured using surveys, behavioral data, or physiological measures. The different methods are assessed in terms of their success in finding differences of cognitive load in embodied learning scenarios. At the same time, we highlight the most important challenges for researchers aiming to include these measures into their study designs. The main issues we identified are: (1) Subjective measures must be appropriately phrased to be useful for embodied learning; (2) recent findings indicate potentials as well as problematic aspects of dual-task measures; (3) the use of physiological measures offers great potential, but may require mobile equipment in the context of embodied scenarios; (4) meta-cognitive measures can be useful extensions of cognitive load measurement for embodied learning.
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Krundel, Ludovic. "On microelectronic self-learning cognitive chip systems." Thesis, Loughborough University, 2016. https://dspace.lboro.ac.uk/2134/21804.
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After a brief review of machine learning techniques and applications, this Ph.D. thesis examines several approaches for implementing machine learning architectures and algorithms into hardware within our laboratory. From this interdisciplinary background support, we have motivations for novel approaches that we intend to follow as an objective of innovative hardware implementations of dynamically self-reconfigurable logic for enhanced self-adaptive, self-(re)organizing and eventually self-assembling machine learning systems, while developing this new particular area of research. And after reviewing some relevant background of robotic control methods followed by most recent advanced cognitive controllers, this Ph.D. thesis suggests that amongst many well-known ways of designing operational technologies, the design methodologies of those leading-edge high-tech devices such as cognitive chips that may well lead to intelligent machines exhibiting conscious phenomena should crucially be restricted to extremely well defined constraints. Roboticists also need those as specifications to help decide upfront on otherwise infinitely free hardware/software design details. In addition and most importantly, we propose these specifications as methodological guidelines tightly related to ethics and the nowadays well-identified workings of the human body and of its psyche.
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Eaton, Dennis. "Cognitive and affective learning in outdoor education." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape10/PQDD_0005/NQ41587.pdf.
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Durand, Marianne. "Nonverbal learning difficulties : mathematical and cognitive deficits." Thesis, University of York, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.424523.
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Swainson, Rachel. "Cognitive flexibility and learning in Parkinson's disease." Thesis, University of Cambridge, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.624971.
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Valle, Arias Antonio, Cabanach Ramón González, Lozano Alfonso Barca, and Pérez José Carlos Núñez. "Cognitive-motivational dimmensions and self-regulated learning." Pontificia Universidad Católica del Perú, 1996. http://repositorio.pucp.edu.pe/index/handle/123456789/99958.
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This paper discusses schoollearning from a cognitive-motivational perspective. A number of relevant ideas are highlighted as relevant to undersrand the cognitive-motivational factors that influence school learning.El artículo analiza el aprendizaje escolar donde una perspectiva cognitivo- motivacional, en la que se destacan una serie de ideas relevantes de profundizar en la comprensión de los factores cognitivo-motivacionales que inciden en el aprendizaje escolar.
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Azmat, Freeha. "Machine learning and energy efficient cognitive radio." Thesis, University of Warwick, 2016. http://wrap.warwick.ac.uk/85990/.
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With an explosion of wireless mobile devices and services, system designers are facing a challenge of spectrum scarcity and high energy consumption. Cognitive radio (CR) is a promising solution for fulfilling the growing demand of radio spectrum using dynamic spectrum access. It has the ability of sensing, allocating, sharing and adapting to the radio environment. In this thesis, an analytical performance evaluation of the machine learning and energy efficient cognitive radio systems has been investigated while taking some realistic conditions into account. Firstly, bio-inspired techniques, including re y algorithm (FFA), fish school search (FSS) and particle swarm optimization (PSO), have been utilized in this thesis to evaluate the optimal weighting vectors for cooperative spectrum sensing (CSS) and spectrum allocation in the cognitive radio systems. This evaluation is performed for more realistic signals that suffer from the non-linear distortions, caused by the power amplifiers. The thesis then takes the investigation further by analysing the spectrum occupancy in the cognitive radio systems using different machine learning techniques. Four machine learning algorithms, including naive bayesian classifier (NBC), decision trees (DT), support vector machine (SVM) and hidden markov model (HMM) have been studied to find the best technique with the highest classification accuracy (CA). A detailed comparison of the supervised and unsupervised algorithms in terms of the computational time and classification accuracy has been presented. In addition to this, the thesis investigates the energy efficient cognitive radio systems because energy harvesting enables the perpetual operation of the wireless networks without the need of battery change. In particular, energy can be harvested from the radio waves in the radio frequency spectrum. For ensuring reliable performance, energy prediction has been proposed as a key component for optimizing the energy harvesting because it equips the harvesting nodes with adaptation to the energy availability. Two machine learning techniques, linear regression (LR) and decision trees (DT) have been utilized to predict the harvested energy using real-time power measurements in the radio spectrum. Furthermore, the conventional energy harvesting cognitive radios do not assume any energy harvesting capability at the primary users (PUs). However, this is not the case when primary users are wirelessly powered. In this thesis, a novel framework has been proposed where PUs possess the energy harvesting capabilities and can get benefit from the presence of the secondary user (SU) without any predetermined agreement. The performances of the wireless powered PUs and the SU has also been analysed. Numerical results have been presented to show the accuracy of the analysis. First, it has been observed that bio-inspired techniques outperform the conventional algorithms used for collaborative spectrum sensing and allocation. Second, it has been noticed that SVM is the best algorithm among all the supervised and unsupervised classifiers. Based on this, a new SVM algorithm has been proposed by combining SVM with FFA. It has also been observed that SVM+FFA outperform all other machine leaning classifiers Third, it has been noticed in the energy predictive modelling framework that LR outperforms DT by achieving smaller prediction error. It has also been shown that optimal time and frequency attained using energy predictive model can be used for defining the scheduling policies of the harvesting nodes. Last, it has been shown that wirelessly powered PUs having energy harvesting capabilities can attain energy gain from the transmission of SU and SU can attain the throughput gain from the extra transmission time allocated for energy harvesting PUs.
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Smith, Shelley L. "The cognitive learning styles of international students." PDXScholar, 1986. https://pdxscholar.library.pdx.edu/open_access_etds/3731.
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The purpose of this research was to examine the usefulness of David A. Kolb's Learning Styles Inventory (LSI) as a tool for categorization and analysis of systematic differences between American and International students. The research addressed five primary questions:
1. Are the learning styles of the International students tested different from those established by Kolb in previous studies of American students?
2. Do the learning styles of the International students tested differ among the various groups?
3. Are there differences among the groups of International students tested that can be related to gender?
4. Do the learning styles of the International students tested show any variation according to age? And if present, does that pattern differ in any way from patterns identified for American subjects tested?
5. Are the learning styles of the International students tested similar or dissimilar from the norms established by Kolb for American students in various fields of academic study?
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Pate, Shari Ann. "Web tools: An aid for cognitive learning." CSUSB ScholarWorks, 2004. https://scholarworks.lib.csusb.edu/etd-project/2777.
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The purpose of this project is to provide students and teachers with a disk of tools to aide in the development of Web pages either in the classroom or through online (distance education) learning. Many of the tools supplied on this disk have been field tested in a high school Web design class. When students are allowed to be creative and are able to fuse interesting visual displays the results can be significant in increasing cognitive and multiple intelligences skills.
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Stachenfeld, Kimberly. "Learning Neural Representations that Support Efficient Reinforcement Learning." Thesis, Princeton University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10824319.
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RL has been transformative for neuroscience by providing a normative anchor for interpreting neural and behavioral data. End-to-end RL methods have scored impressive victories with minimal compromises in autonomy, hand-engineering, and generality. The cost of this minimalism in practice is that model-free RL methods are slow to learn and generalize poorly. Humans and animals exhibit substantially improved flexibility and generalize learned information rapidly to new environment by learning invariants of the environment and features of the environment that support fast learning rapid transfer in new environments. An important question for both neuroscience and machine learning is what kind of ``representational objectives'' encourage humans and other animals to encode structure about the world. This can be formalized as ``representation feature learning,'' in which the animal or agent learns to form representations with information potentially relevant to the downstream RL process. We will overview different representational objectives that have received attention in neuroscience and in machine learning. The focus of this overview will be to first highlight conditions under which these seemingly unrelated objectives are actually mathematically equivalent. We will use this to motivate a breakdown of properties of different learned representations that are meaningfully different and can be used to inform contrasting hypotheses for neuroscience. We then use this perspective to motivate our model of the hippocampus. A cognitive map has long been the dominant metaphor for hippocampal function, embracing the idea that place cells encode a geometric representation of space. However, evidence for predictive coding, reward sensitivity, and policy dependence in place cells suggests that the representation is not purely spatial. We approach the problem of understanding hippocampal representations from a reinforcement learning perspective, focusing on what kind of spatial representation is most useful for maximizing future reward. We show that the answer takes the form of a predictive representation. This representation captures many aspects of place cell responses that fall outside the traditional view of a cognitive map. We go on to argue that entorhinal grid cells encode a low-dimensional basis set for the predictive representation, useful for suppressing noise in predictions and extracting multiscale structure for hierarchical planning.
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Salovaara, H. (Hanna). "Achievement goals and cognitive learning strategies in dynamic contexts of learning." Doctoral thesis, University of Oulu, 2005. http://urn.fi/urn:isbn:9514277635.
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Abstract This study investigates secondary school students' motivational achievement goals and cognitive learning strategies in inquiry-based computer supported collaborative learning. The study undertakes a contextual approach where students' context specific interpretations are highlighted. Achievement goals and cognitive learning strategies are introduced within a theoretical framework of self-regulated learning to explain their interrelationship and magnitude within a learning process. The research design was a longitudinal, quasi intervention design involving multiple methods, namely quantitative self-reports and qualitative process oriented interviews. Empirical parts of the study are reported in four individual articles. The purpose of Study I was to recognise strategic patterns emerging in students' computer supported collaborative inquiries. The results indicated that strategies were adjusted according to the demands of the learning situation. Although students' inquiry processes were dominated by surface-level strategies, also deeper level and metacognitive strategies were reported. Study II investigated students' use of cognitive learning strategies in two pedagogically different learning contexts. The results suggest that inquiry-based computer supported collaborative learning activities may enhance the use of deeper level cognitive strategies, such as monitoring, sharing information and creating representations. Study III examined the changes in students' motivational achievement goal interpretations and the situational dynamics of students' goals and strategies over a period of three years. The data show how the students' interpretations of their goals and strategies vary during different years of the study. The students seem to develop both individual and contextual goals, as well as strategies, to self-regulate in the new pedagogical culture. Study IV looked at the congruence between students' general achievement goals and their context specific goals. The findings indicate incongruence between general level goal orientations and contextual goal interpretations and, thus, underline the importance of subjective interpretations of achievement goals. The results indicate that both achievement goals and cognitive learning strategies have contextual characteristics and illustrate the need to understand the interplay of motivational and cognitive processes. The results also show the importance of longitudinal research for pointing out some of the motivational and cognitive effects of the pedagogical interventions. Finally, the results of the study suggest that the social dimension of students' cognitive and motivational processes and self-regulation should be studied in more detailTiivistelmä Tutkimuksessa tarkastellaan yläasteen oppilaiden motivationaalisia tavoitteita ja kognitiivisia oppimisstrategioita tietokoneavusteisen kollaboratiivisen oppimisen sekä tutkivan pedagogisen lähestymistavan periaatteita noudattavissa oppimistilanteissa. Teoreettisesti tutkimus nojautuu sosiokognitiiviseen näkemykseen oppimisesta ja korostaa kontekstuaalista lähestymistapaa, jossa painotetaan oppijoiden yksilöllisten ja kontekstiin sidottujen tulkintojen merkitystä. Taustalla on näkemys oppimisen kontekstien ainutlaatuisuudesta, jatkuvasta muuttumisesta ja dynaamisuudesta, joka puolestaan vaikuttaa oppimisen motivationaalisiin ja tiedollisiin prosesseihin. Tutkimus koostuu neljästä itsenäisestä empiirisestä artikkelista sekä tutkimuksen teoreettisen taustan, tavoitteet, menetelmät ja tulokset kokoavasta yhteenveto-osasta. Tutkimuksen teoreettisessa osassa pyritään hahmottamaan motivationaalisten saavutustavoitteiden sekä kognitiivisten oppimisstrategoiden välisiä yhteyksiä sekä niiden merkitystä oppimisprosessin kokonaisuudessa. Tutkimuksen keskeiset käsitteet, motivationaaliset tavoitteet ja kognitiiviset oppimisstrategiat esitetään osana oppimisen itsesäätelyn teoreettista viitekehystä. Kolmivuotisessa tutkimuksessa toteutettiin pedagoginen interventio, jossa ryhmä oppilaita työskenteli yläasteen ajan tietokoneavusteisen kollaboratiivisen oppimisympäristön tukemana tutkivan oppimisen mallia noudattaen äidinkielen tunneilla. Oppilaiden motivaatiota ja kognitiivisia oppimistrategioita tarkasteltiin useiden menetelmien avulla. Pääosan tutkimuksen aineistosta muodostavat oppilaiden toistetut kvantitatiiviset itsearviot sekä kvalitatiiviset prosessisuuntautuneet haastattelut. Kokonaisuudessaan neljässä empiirisessä artikkelissa raportoidun tutkimuksen tulokset osoittavat, että sekä motivationaalisiin tavoitteisiin että kognitiivisiin oppimisstrategioihin liittyy tilannesidonnainen ulottuvuus, jossa oppijoiden omilla henkilökohtaisilla tulkinnoilla on suuri merkitys. Lisäksi tutkimuksen tulokset kuvasivat motivaation ja kognitiivisten strategioiden vuorovaikutusta oppimisessa ja nostivat esiin tarpeen tarkastella oppimista eri osaprosessien välisen dynamiikan kautta. Tutkimuksen pitkittäistulokset osoittavat pitkäjänteisen tutkimuksen olevan tarpeen pedagogisten interventioiden sekä oppimiskontekstien dynamiikan tutkimisessa. Erityisesti haastatteluaineistosta esiin nostetut tulokset osoittavat sosiaalisen kontekstin merkitystä oppimisen kognitiivisissa ja motivationaalisissa prosesseissa sekä oppimisen itsesäätelyssä
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Thomas, Charles Nolan. "The relationships between cognitive deficits and spiritual development." Lynchburg, Va. : Liberty University, 2008. http://digitalcommons.liberty.edu.
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Barton, John Wesley. "Fluid intelligence and use of cognitive learning strategies /." Digital version accessible at:, 1999. http://wwwlib.umi.com/cr/utexas/main.
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Rucinski, Marek. "Modelling learning to count in humanoid robots." Thesis, University of Plymouth, 2014. http://hdl.handle.net/10026.1/2995.
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This thesis concerns the formulation of novel developmental robotics models of embodied phenomena in number learning. Learning to count is believed to be of paramount importance for the acquisition of the remarkable fluency with which humans are able to manipulate numbers and other abstract concepts derived from them later in life. The ever-increasing amount of evidence for the embodied nature of human mathematical thinking suggests that the investigation of numerical cognition with the use of robotic cognitive models has a high potential of contributing toward the better understanding of the involved mechanisms. This thesis focuses on two particular groups of embodied effects tightly linked with learning to count. The first considered phenomenon is the contribution of the counting gestures to the counting accuracy of young children during the period of their acquisition of the skill. The second phenomenon, which arises over a longer time scale, is the human tendency to internally associate numbers with space that results, among others, in the widely-studied SNARC effect. The PhD research contributes to the knowledge in the subject by formulating novel neuro-robotic cognitive models of these phenomena, and by employing these in two series of simulation experiments. In the context of the counting gestures the simulations provide evidence for the importance of learning the number words prior to learning to count, for the usefulness of the proprioceptive information connected with gestures to improving counting accuracy, and for the significance of the spatial correspondence between the indicative acts and the objects being enumerated. In the context of the model of spatial-numerical associations the simulations demonstrate for the first time that these may arise as a consequence of the consistent spatial biases present when children are learning to count. Finally, based on the experience gathered throughout both modelling experiments, specific guidelines concerning future efforts in the application of robotic modelling in mathematical cognition are formulated.
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CASTOLDI, VALERIA. "THE INTERACTION BETWEEN HIGH COGNITIVE ABILITIES, LEARNING AND CULTURE." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2017. http://hdl.handle.net/10281/153290.
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Uno degli obiettivi della psicologia cognitiva riguarda la comprensione dei fattori cognitivi legati all’intelligenza umana, con lo scopo di formulare modelli il più possibile esplicativi del funzionamento della mente. Nella mia tesi ho tentato di dare una definizione del concetto di intelligenza, intesa come l’insieme dei processi consci e inconsci che determinano la nostra conoscenza, in associazione con specifiche abilità cognitive come ragionamento e problem solving. Mi sono inoltre proposta di investigare l’interazione tra intelligenza, apprendimento e cultura, considerati come fattori esogeni che concorrerebbero alla manifestazione delle differenze individuali. A tal fine sono stati condotti tre studi. Il primo studio riguarda la valutazione dell’insight problem solving nell’infanzia, in interazione con le capacità pragmatico-interpretative del linguaggio, che si svilupperebbero grazie all’apprendimento nelle situazioni sociali. Il secondo studio si focalizza ancora sui problemi insight, ma in età adulta: la performance in questo tipo di problema è valutata in relazione alle differenze culturali e in interazione con specifici fattori cognitivi come la capacità inibitoria e la Mindfulness. Nel terzo studio, l’intelligenza e la capacità di ragionamento, in un gruppo di studenti di scuola secondaria superiore, vengono analizzate in relazione a specifici contesti di apprendimento. Le ricerche dimostrano la necessità di trovare una definizione maggiormente soddisfacente del concetto di intelligenza e il coinvolgimento della cultura e dell’apprendimento nella sua evoluzione.One of the purpose of Cognitive Psychology is the comprehension of the cognitive factors related to human intelligence, in order to formulate explanatory models of the mind processes. In my thesis I tried to define the concept of intelligence as the sum of conscious and unconscious processes linked to our knowledge and related with specific cognitive abilities, such as reasoning and problem solving. I also investigated the interaction between intelligence, learning and culture, considered as exogenous factors which would be involved in individual differences. Three studies were, therefore, conducted. The first study concerns the insight problem solving in childhood, in interaction with the pragmatic-interpretive skills of the language that would develop through learning in social situations. The second study is still focused on the insight problems, but in adulthood: the performance in this kind of problems would be influenced by the cultural differences and by the interactions with specific cognitive factors such as the Inhibitory Ability and Mindfulness. In the third study, intelligence and reasoning skills are analyzed in a group of secondary school students in relation to some specific learning contexts. Results underlie the need to better define the concept of intelligence and the involvement of culture and learning in its evolution.
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Yeung, Chui-ngan, and 楊翠顔. "Exploring the cognitive conflict in learning through Knowledge Forum." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2002. http://hub.hku.hk/bib/B26835939.
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Östergren, Rickard. "Mathematical Learning Disability : Cognitive Conditions, Development and Predictions." Doctoral thesis, Linköpings universitet, Psykologi, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-96799.
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The purpose of the present thesis was to test and contrast hypotheses about the cognitive conditions that support the development of mathematical learning disability (MLD). Following hypotheses were tested in the thesis: a) domain general deficit, the deficit is primarily located in the domain general systems such as the working memory, b) number sense deficit, the deficit is located in the innate approximate number system (ANS), c) numerosity coding deficit, the deficit is located to a exact number representation system, d) access deficit, the deficit is in the mapping between symbols and the innate number representational system (e.g., ANS), e) multiple deficit hypothesis states that MLD could be related to more than one deficit. Three studies examined the connection between cognitive abilities and arithmetic. Study one and three compared different groups of children with or without MLD (or risk of MLD). Study two investigated the connection between early number knowledge, verbal working memory and the development of arithmetic ability. The results favoring the multiple deficit hypothesis, more specifically the result indicate that number sense deficit together with working memory functions constitutes risk-factors to the development of MLD in children. A simple developmental model that is based on von Asters and Shalev´s (2007) model and the present results is suggested, in order to understand the development of MLD in children.Avhandlingens syfte var att testa och kontrastera hypoteser om vilka kognitiva förutsättningar som är centrala för utvecklandet av matematiska inlärningssvårigheter (MLD) hos barn. De hypoteser som prövas i avhandlingen är följande: a) den domängenerella hypotesen, detta innebär att den förmodade störningen/nedsättningen finns primärt i barnets generella förmågor, främst då i arbetsminnes funktioner. b) en nedsättning i den medfödda approximativa antalsuppfattningen. c) nedsättning i den exakta antalskodningen. d) nedsättning gällande kopplingen mellan den kulturellt betingande symboliska nivå (räkneord och siffror) samt den medfödda antalsuppfattningen (eller antalskodningen). e) slutligen prövas även hypotesen att MLD kan härröras från flera nedsättningar i dessa förmågor. I tre studier undersöktes kopplingen mellan kognitiva förmågor och aritmetik. i studie1 och 3 jämfördes grupper av barn med MLD (eller risk för MLD) med grupper av barn som inte hade MLD i studie 2 undersöktes kopplingen mellan förmågorna verbalt arbetsminne och tidig sifferkunskap samt tidig aritmetiskförmåga. Sammantaget indikerar resultaten från denna avhandling att det kan vara både multipla och enstaka kognitiva förmågor, primärt i den approximativa antalsuppfattningen samt i arbetsminnesfunktioner, som kan fungera som riskförutsättningar för utvecklande av MLD hos barn. Dock måste dessa förmågor samspela med andra faktorer som kan fungera kompensatoriskt eller riskhöjande för utvecklandet av MLD. En förenklad utvecklingsmodell med utgångspunkten i resultaten från studierna samt von Asters och Shalevs (2007) modell föreslås. Syftet med modellen är att den ska kunna användas som teoretiskt ramverk för att förstå utvecklingen av MLD hos barn.
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Jankowska, Gierus Bogumila. "Learning with visual representations through cognitive load theory." Thesis, McGill University, 2011. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=104827.
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This study examined two different strategies of learning with diagrams: drawing diagrams while learning or learning from pre-constructed diagrams. One hundred ninety six junior high school students were randomly placed in a condition either to draw while learning about how airplanes fly or to study from pre-constructed diagrams. Before the learning, students' prior knowledge and elaboration strategies were measured. During learning in either condition, students reported their mental effort. Afterwards, students' learning was tested on both a similar task and transfer task. Cook's (2006) theoretical framework, which combines prior knowledge and cognitive load theory on visual representations in science education, was used to analyze the results. Results showed that students' mental effort significantly increased in the drawing condition, yet results on the posttest were mixed. Students did not do better, and sometimes did worse, on the posttest measures when they learned by drawing diagrams versus using pre-constructed diagrams to learn. The exception was that students with low initial prior knowledge did do better. Elaborations strategies did not have an effect on students' achievement or mental effort in either condition.Cette étude a examiné deux stratégies différentes d'apprendre à l'aide des diagrammes: le dessin de diagrammes tout en apprenant ou en apprenant sur la base des diagrammes préconstruits. Cent quatre-vingt-seize étudiants de lycée ont été aléatoirement placés dans une condition où soit ils dessinaient tout en se renseignant sur la façon dont les avions volent ou étudiaient à partir des diagrammes préconstruits. Avant l'étude, les stratégies de connaissance et d'élaboration des étudiants ont été vérifiées. Pendant l'étude sous l'une ou l'autre des conditions, les étudiants signalaient leur effort mental. Suite à cela, l'étude des étudiants est examinée sur une tâche semblable et une tâche de transfert. Cadre théorique de Cook (2006), qui combine la théorie de la connaissance antérieure et de charge cognitive sur les représentations visuelles dans l'éducation de la science, ont été employés pour analyser les résultats. Les résultats ont prouvé que l'effort mental des étudiants a augmenté sensiblement sous condition de dessin, pourtant les résultats sur le post-test étaient mitigés. En règle générale, les étudiants ont fait plus ou moins mauvais sur les mesures de post-test quand ils ont appris en traçant des diagrammes au contraire de l'utilisation des diagrammes préconstruits pour apprendre. Cependant, les étudiants ayant une faible connaissance de base ont mieux exécuté le post-test en traçant leurs propres diagrammes. Les stratégies d'élaborations n'ont pas exercé d' effet sur l'accomplissement ou l'effort mental des étudiants pour chacune des conditions.
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Wong, Pik-ha, and 王碧霞. "Cognitive obstacles in learning the laws of indices." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1994. http://hub.hku.hk/bib/B31957559.
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DaCosta, Boaventura. "THE EFFECT OF COGNITIVE AGING ON MULTIMEDIA LEARNING." Doctoral diss., University of Central Florida, 2008. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/3650.
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If not designed in consideration to the workings of the human mind, multimedia learning environments can impose too high a demand on working memory. While such high cognitive load presents challenges for learners of all ages, older learners may be particularly affected as research on cognitive aging has shown the efficiency of working memory declines with age. Research has suggested that cognitive load theory (CLT) and the cognitive theory of multimedia learning (CTML) are likely to accommodate the cognitive needs of older learners; however, few of the principles emerging from these theories have been examined in the context of cognitive aging. The abundance of studies has focused on younger learners, prompting the need for further research of CLT and CTML principles with regard to age. This study contributes to the body of research on the cognitive aging principle by extending research on the modality effect with middle-aged learners. Ninety-two participants ranging in age from 30 to 59 were exposed to multimedia learning treatments presented as animation with concurrent narration and animation with concurrent text, followed by retention, concept, and transfer tests of multimedia learning. Demographic and descriptive statistics were performed along with a multivariate analysis of variance. The findings did not show a modality effect with middle-aged learners; however, results need to be interpreted with care as possible explanations may entail other causes for the lack of a modality effect other than age.Ph.D.
Department of Educational Research, Technology and Leadership
Education
Education PhD
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Cuevas, Haydee. "TRANSFORMING LEARNING INTO A CONSTRUCTIVE COGNITIVE AND METACOGNITIVE." Doctoral diss., University of Central Florida, 2004. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/3931.
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This study explored the effectiveness of embedding a guided, learner-generated instructional strategy (query method), designed to support learners' cognitive and metacognitive processes, within the context of a computer-based complex task training environment (i.e., principles of flight in the aviation domain). The queries were presented as "stop and think" exercises in an open-ended question format that asked learners to generate either simple (low-level elaboration) or complex (high-level elaboration) sentences from a list of key training concepts. Results consistently highlighted the benefit of presenting participants with low-level elaboration queries, as compared to the no-query or high-level elaboration queries. In terms of post-training cognitive outcomes, participants presented with the low-level elaboration queries exhibited significantly more accurate knowledge organization (indicated by similarity to an expert model), better acquisition of perceptual knowledge, and superior performance on integrative knowledge assessment involving the integration and application of task-relevant concepts. Consistent with previous studies, no significant differences in performance were found on basic factual knowledge assessment. Presentation of the low-level elaboration queries also significantly improved the training program's instructional efficiency, that is, greater performance was achieved with less perceived cognitive effort. In terms of post-training metacognitive outcomes, participants presented with the low-level elaboration queries exhibited significantly greater metacomprehension accuracy and more effective metacognitive self-regulation during training. Contrary to predictions, incorporating the high-level elaboration queries into the training consistently failed, with only a few exceptions, to produce significantly better post-training outcomes than the no-query or the low-level elaboration query training conditions. The results of this study are discussed in terms of the theoretical implications for garnering a better understanding of the cognitive and metacognitive factors underlying the learning process. Practical implications for training design are presented within the context of cognitive load theory. Specifically, the increased cognitive processing of the training material associated with the high-level elaboration queries may have imposed too great a cognitive load on participants during training, minimizing the cognitive resources available for achieving a deeper, integrative understanding of the training concepts and hindering successful performance on the cognitive measures. The discussion also highlights the need for a multi-faceted approach to training evaluation.Ph.D.
Department of Psychology
Arts and Sciences
Psychology
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Fath, El-Bab Mohamed. "Cognitive event related potentials during a learning task." Thesis, University of Southampton, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.367971.
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Chen, Ye. "Fuzzy Cognitive Maps: Learning Algorithms and Biomedical Applications." University of Cincinnati / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1423581705.
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Awe, Olusegun P. "Machine learning algorithms for cognitive radio wireless networks." Thesis, Loughborough University, 2015. https://dspace.lboro.ac.uk/2134/19609.
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In this thesis new methods are presented for achieving spectrum sensing in cognitive radio wireless networks. In particular, supervised, semi-supervised and unsupervised machine learning based spectrum sensing algorithms are developed and various techniques to improve their performance are described. Spectrum sensing problem in multi-antenna cognitive radio networks is considered and a novel eigenvalue based feature is proposed which has the capability to enhance the performance of support vector machines algorithms for signal classification. Furthermore, spectrum sensing under multiple primary users condition is studied and a new re-formulation of the sensing task as a multiple class signal detection problem where each class embeds one or more states is presented. Moreover, the error correcting output codes based multi-class support vector machines algorithms is proposed and investigated for solving the multiple class signal detection problem using two different coding strategies. In addition, the performance of parametric classifiers for spectrum sensing under slow fading channel is studied. To address the attendant performance degradation problem, a Kalman filter based channel estimation technique is proposed for tracking the temporally correlated slow fading channel and updating the decision boundary of the classifiers in real time. Simulation studies are included to assess the performance of the proposed schemes. Finally, techniques for improving the quality of the learning features and improving the detection accuracy of sensing algorithms are studied and a novel beamforming based pre-processing technique is presented for feature realization in multi-antenna cognitive radio systems. Furthermore, using the beamformer derived features, new algorithms are developed for multiple hypothesis testing facilitating joint spatio-temporal spectrum sensing. The key performance metrics of the classifiers are evaluated to demonstrate the superiority of the proposed methods in comparison with previously proposed alternatives.
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Bozeman, Marci L. "The impact of service-learning on cognitive development." Thesis, This resource online, 1996. http://scholar.lib.vt.edu/theses/available/etd-02132009-171324/.
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Jiang, Tao. "Reinforcement learning-based spectrum sharing for cognitive radio." Thesis, University of York, 2011. http://etheses.whiterose.ac.uk/1960/.
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This thesis investigates how distributed reinforcement learning-based resource assignment algorithms can be used to improve the performance of a cognitive radio system. Decision making in most wireless systems today, including most cognitive radio systems in development, depends purely on instantaneous measurement. The purpose of this work is to exploit the historical information the cognitive radio device has learned through the interactions with the unknown environment. Two system architectures have been investigated in this thesis. A point-to-point architecture is examined first in an open spectrum scenario. Then, for the first time distributed reinforcement learning-based algorithms are developed and examined in a novel two-hop architecture for Beyond Next Generation Mobile Network. The traditional reinforcement learning model is modified in order to be applied to a fully distributed cognitive radio scenario. The inherent exploration versus exploitation trade-off seen in reinforcement learning is examined in the context of cognitive radio. A two-stage algorithm is proposed to effectively control the exploration phase of the learning process. This is because cognitive radio users will cause a higher level of disturbance in the exploration phase. Efficient exploration algorithms like pre-partitioning and weight-driven exploration are proposed to enable more efficient learning process. The learning efficiency in a cognitive radio scenario is defined and the learning efficiency of the proposed schemes is investigated. Results show that the performance of the cognitive radio system can be significantly enhanced by utilizing distributed reinforcement learning since the cognitive devices are able to identify the appropriate resources more efficiently. The reinforcement learning-based ‘green’ cognitive radio approach is discussed. Techniques presented show how it is possible to largely eliminate the need for spectrum sensing, along with the associated energy consumption, by using reinforcement learning to develop a preferred channel set in each device.
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Tio, Yee Pin. "COGNITIVE EFFECTS OF LEARNING MANDARIN CHINESE NUMERAL CLASSIFIERS." OpenSIUC, 2016. https://opensiuc.lib.siu.edu/theses/2004.
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This study examines the relationship between language and cognition with a focus on Chinese numeral classifiers (CNCs). NCs are ideally suited to exploring the link between language and semantic categorization, as classifier selection depends on the physical attributes of the associated noun (e.g., Mandarin zhi is used for long and rigid objects and tiao for long and flexible objects). Previous studies on numeral classifiers have addressed the language-cognition link by comparing the cognitive performance of monolingual as well as bilingual speakers of different languages (Lucy, 1992; Saalbach & Imai, 2005; Gao & Malt, 2009). In contrast, the present study sought to address the cognitive effects of numeral classifiers via a training study that investigated whether exposure to CNCs influenced Native-English speakers’ object categorization preferences, inhibitory control and memory retrieval. The participants of this study were 99 Native-English speaking College students. They were randomly assigned to an experimental group, which received training on four commonly used CNCs during the initial phase of the experiment, or a control group, which did not receive similar treatment during the initial phase. After the initial phase, the experimental group and the control group were assessed on a Forced Choice Task, a Go/No-Go Task and a Memory Task. A Mixed-design ANOVA indicated that the experimental group displayed a preference for objects sharing the same classifier in the Forced Choice Task and the Go/ No-Go Task (i.e. Go trials) when compared to the controls. The effect of exposure to numeral classifiers on inhibitory control was supported with a significantly lower false alarm rate (in the No-Go trials) for the experimental group. However, no group differences were observed in the results of the analysis of the participants’ median reaction times in the Go/No-Go tasks. Similarly, the differences between the two groups’ scores on the Memory Task was not found to be significant. The results of the study indicated that exposure to CNCs influenced Native-English speakers’ categorization. The results also revealed partial support for the influence of exposure to CNCs on inhibitory processing, but not in the case of object clustering.
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Kovanovic, Vitomir. "Assessing cognitive presence using automated learning analytics methods." Thesis, University of Edinburgh, 2017. http://hdl.handle.net/1842/28759.
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With the increasing pace of technological changes in the modern society, there has been a growing interest from educators, business leaders, and policymakers in teaching important higher-order skills which were identified as necessary for thriving in the present-day globalized economy. In this regard, one of the most widely discussed higher order skills is critical thinking, whose importance in shaping problem solving, decision making, and logical thinking has been recognized. Within the domain of distance and online education, the Community of Inquiry (CoI) model provides a pedagogical framework for understanding the critical dimensions of student learning and factors which impact the development of student critical thinking. The CoI model follows the social-constructivist perspective on learning in which learning is seen as happening in both individual minds of learners and through the discourse within the group of learners. Central to the CoI model is the construct of cognitive presence, which captures the student cognitive engagement and the development of critical thinking and deep thinking skills. However, the assessment of cognitive presence is challenging task, particularly given its latent nature and the inherent physical and time separation between students and instructors in distance education settings. One way to address this problem is to make use of the vast amounts of learning data being collected by learning systems. This thesis presents novel methods for understanding and assessing the levels of cognitive presence based on learning analytics techniques and the data collected by learning environments. We first outline a comprehensive model for cognitive presence assessment which builds on the well-established evidence-cantered design (ECD) assessment framework. The proposed assessment model provides a foundation of the thesis, showing how the developed analytical models and their components fit together and how they can be adjusted for new learning contexts. The thesis shows two distinct and complementary analytical methods for assessing students’ cognitive presence and its development. The first method is based on the automated classification of student discussion messages and captures learning as it is observed in the student dialogue. The second analytics method relies on the analysis of log data of students’ use of the learning platform and captures the individual dimension of the learning process. The developed analytics also extend current theoretical understanding of the cognitive presence construct through data-informed operationalization of cognitive presence with different quantitative measures extracted from the student use of online discussions. We also examine methodological challenges of assessing cognitive presence and other forms of cognitive engagement through the analysis of trace data. Finally, with the intent of enabling for the wider adoption of the CoI model for new online learning modalities, the last two chapters examine the use of developed analytics within the context of Massive Open Online Courses (MOOCs). Given the substantial differences between traditional online and MOOC contexts, we first evaluate the suitability of the CoI model for MOOC settings and then assess students’ cognitive presence using the data collected by the MOOC platform. We conclude the thesis with the discussion of practical application and impact of the present work and the directions for the future research.
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Stelljes, Andrew D. "Service-learning and cognitive development: An exploratory study." W&M ScholarWorks, 2007. https://scholarworks.wm.edu/etd/1550154171.
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Khalil, M. S. "Computer-assisted cognitive remediation with learning disabled children : an evaluation using cognitive-neuropsychological model." Thesis, University of Newcastle Upon Tyne, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.334458.
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Tobias, Cindel K. "Complex instruction giving students the education they deserve /." Online pdf file accessible through the World Wide Web, 2010. http://archives.evergreen.edu/masterstheses/Accession89-10MIT/Tobias_CKMiT2010.pdf.
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