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1
Haho, P. (Päivi). "Learning enablers, learning outcomes, learning paths, and their relationships in organizational learning and change." Doctoral thesis, Oulun yliopisto, 2014. http://urn.fi/urn:isbn:9789526203584.
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Abstract The purpose of this thesis is to examine the role of learning and the constituents of learning in creating process innovations and realizing organizational change. Organizational learning was studied and the data was collected in process development projects, in which process simulations were used as a development method for process innovations and change. The empirical research was carried out mainly in 1988–2001. In this thesis, the results of those studies are reflected on, together with the recent literature related to organizational learning theories in the context of process innovations and management of change. Specifically, the concepts of learning enablers, learning outcomes (intangible/tangible), learning paths, and their relationships are studied. Qualitative longitudinal action research with case studies and abductive reasoning are used as the research methods throughout this thesis. The data consists of 34 cases and 99 process simulations in 12 different industries and varies from large core processes to support processes. The case organizations were mainly Finnish companies with Finns as the majority of participants. One case organization was from Switzerland, and in five cases, multicultural groups participated in the process simulations. In each project, process simulations were used at least once during a change project, in some cases even five to eight times. The data analysis proceeded in an abductive manner throughout the included five articles, and the findings are summarized based on the research questions. The theoretical contribution of this thesis is fourfold. The findings give new understanding 1) about learning enablers, their relationships to each other and influence on learning and process innovations, 2) about the role of intangible and tangible learning outcomes in individual and organizational learning processes and 3) about learning paths in process innovations and related change processes. The thesis also defines 4) a model for effective learning processes in change projects concerning process innovations. The contribution in the practical and managerial context should be applicable field of North and West European commercial organizations. This thesis highlights individual and organizational learning in the creation of process innovations, and it also defines the features of an effective development method for creating and implementing process innovationsTiivistelmä Tämän väitöskirjan tarkoituksena on tutkia organisaation oppimisen ja sen eri osatekijöiden roolia prosessi-innovaatioiden luomisessa ja muutoksen aikaansaamisessa organisaatiossa. Organisaation oppimista tutkittiin ja aineisto kerättiin prosessien kehittämisprojekteissa, joissa prosessisimulaatioita käytettiin prosessi-innovaatioiden menetelmänä. Tutkimuksen aineisto kerättiin pääsiassa vuosien 1988–2001 aikana. Tässä väitöskirjassa näitä tuloksia analysoidaan vallitsevien organisaatio-oppimisen teorioiden valossa prosessi-innovaatioiden ja muutoksen johtamisen asiayhteydessä. Erityisesti tutkitaan oppimisen mahdollistajia, oppimisen tuloksia (aineettomia/aineellisia), oppimisen polkuja ja kaikkien näiden keskinäisiä suhteita. Tutkimusmenetelmänä on käytetty laadullista pitkittäistä toimintatutkimusta tapaustutkimuksineen ja abduktiivisine päättelyineen. Aineisto koostuu 34 tapaustutkimuksesta ja 99 prosessisimulaatiosta, jotka toteutettiin 12 eri toimialalla, ja vaihtelevat ydinprosesseista tukiprosesseihin. Suurimmaksi osaksi tapausorganisaatiot olivat suomalaisia yrityksiä, ja yksi tapausorganisaatio oli sveitsiläinen. Projektiryhmät olivat pääasiassa suomalaisia, mutta monikulttuurinen ryhmä osallistui prosessisimulointiin viidessä tapaustutkimuksessa. Jokaisessa projektissa prosessisimulointia käytettiin ainakin kerran muutosprojektin aikana, joissakin tapauksissa jopa viidestä kahdeksaan kertaan. Väitöskirjan viiden artikkelin aineiston analysointi suoritettiin abduktiivisen päättelyn periaattein, ja tutkimuksen tulokset esitetään tutkimuskysymysten mukaisesti. Tutkimuksen teoreettinen tulos kohdistuu neljään osa-alueeseen. Tulokset lisäävät ymmärrystä 1) oppimisen mahdollistajista, niiden suhteesta toisiinsa ja vaikutuksesta oppimiseen ja prosessi-innovaatioihin, 2) aineettomien ja aineellisten oppimistulosten roolista yksilön ja organisaation oppimisprosesseissa, ja 3) prosessi-innovaatioiden ja niihin liittyvien muutosprosessien oppimisen poluista. Tutkimus myös määrittelee 4) prosessi-innovaatioita koskevien muutosprojektien oppimista korostavan mallin. Tutkimuksen tuloksia voitaneen soveltaa Pohjois- ja Länsi-Euroopan yritysmaailmassa. Tutkimus korostaa yksilön ja organisaation oppimisen merkitystä prosessi-innovaatioiden luomisessa ja lisäksi se määrittelee vaikuttavan prosessi-innovaatioiden kehittämisen ja käyttöönoton menetelmän piirteet
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Beal, Jacob Stuart Michael. "Learning by learning to communicate." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/42056.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Includes bibliographical references (p. 215-218).
Human intelligence is a product of cooperation among many different specialists. Much of this cooperation must be learned, but we do not yet have a mechanism that explains how this might happen for the "high-level" agile cooperation that permeates our daily lives. I propose that the various specialists learn to cooperate by learning to communicate, basing this proposal on the phenomenon of communication bootstrapping, in which shared experiences form a basis for agreement on a system of signals. In this dissertation, I lay out a roadmap for investigating this hypothesis, identifying problems that must be overcome in order to understand the capabilities of communication bootstrapping and in order to test whether it is exploited by human intelligence. I then demonstrate progress along the course of investigation laid out in my roadmap: * I establish a measure of developmental cost that allows me to eliminate many possible designs * I develop a method of engineering devices for use in models of intelligence, including characterizing their behavior under a wide variety of conditions and compensating for their misbehavior using failure simplification. * I develop mechanisms that reliably produce communication bootstrapping such that it can be used to connect specialists in an engineered system. * I construct a demonstration system including a simulated world and pair of observers that learn world dynamics via communication bootstrapping.
by Jacob Stuart Michael Beal.
Ph.D.
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Paulsson, Fredrik. "Modularization of the Learning Architecture : Supporting Learning Theories by Learning Technologies." Doctoral thesis, Stockholm : Datavetenskap och kommunikation, Kungliga Tekniska högskolan, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-4712.
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Gredley, Susan. "Learning through experience: making sense of students' learning through service learning." Master's thesis, University of Cape Town, 2013. http://hdl.handle.net/11427/14005.
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This study asks how we can make sense of students' learning in service learning. I employed a qualitative research methodology to explore the learning experiences of four students as they journeyed through the UCT Global Citizenship course: Thinking about volunteering: service, boundaries and power. This is a service learning course which attracts students from all disciplines and years of study. The course has two learning components: the students' self-organised voluntary community service, which forms the primary learning text, and guided facilitation and reflection through face-to-face and online learning activities. I had access to students' coursework which provided two written reflective assignments and a number of online blogs. At a later stage I conducted small-scale in-depth interviews. I used two methods to organise and analyse the data. The first was an analytic framework made up of three interconnected learning domains of 'knowing', 'being' and 'acting' (adapted from Barnett and Coate, 2005); the second was qualitative thematic analysis. My data suggest that we can make sense of students' learning in service learning through an analysis of students' 'being' in relation to their 'knowing' and 'acting'. My data also show that 'being' is embedded in students' 'knowing' and 'doing' and therefore 'being' is a key component of student learning. Additionally, the concept of a 'learning journey' is useful in positioning learning as something that takes place over time and in space. Finally, my data show that context matters: students' "personal foundations of experience" (Boud and Walker, 1991) influence their learning, as does the more immediate context of the classroom and their community service work. This study ends by briefly pointing to two key 'enablers' of students' learning, critical reflection and peer learning.
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Stamer, Tylie. "Promoting Learning Strategies in Students with Learning Disabilities Through Blended Learning." Thesis, McKendree University, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10255720.
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This study was designed to investigate possible changes in the use of four specific learning strategies by students who had learning disabilities: using a device, thinking about knowledge, finding a starting point, and acting differently in the future. The five student participants were instructed in a special education pull-out reading classroom using the blended learning classroom model. The researcher explored behavioral changes related to student participants’ use of these learning strategies in general education classrooms. This study attempted to investigate student participants’ and general education teachers’ perceptions of the four learning strategies. A math teacher, a social studies teacher, and a science teacher from the researcher’s teaching team also contributed their perceived observations of student participants’ use of the four learning strategies in their classrooms. The triangulation of data used in this study was achieved through use of pre-surveys and post-surveys that inquired into use of learning strategies on the parts of student participants and general education teachers at the inception of the study and again at its conclusion. Interviews with each of the study’s participants were also conducted at the conclusion of the study. Student binders used by the student participants in the blended learning instructional model were analyzed for evidence. The results of the study indicated that although according to survey data, students did not demonstrate changes in their ability to use the four learning strategies, most student participants reported using the strategies in their general education classes.
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Yik, Ping-chui. "Learning styles and language learning outcomes." Click to view the E-thesis via HKUTO, 2007. http://sunzi.lib.hku.hk/hkuto/record/B38598073.
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Menke, Joshua E. "Improving machine learning through oracle learning /." Diss., CLICK HERE for online access, 2007. http://contentdm.lib.byu.edu/ETD/image/etd1726.pdf.
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Yik, Ping-chui, and 易平璀. "Learning styles and language learning outcomes." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2007. http://hub.hku.hk/bib/B38598073.
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Tarasova, H. S., and O. V. Shakhmatova. "Flipped learning as interactive learning environment." Thesis, Інститут інноваційної освіти, 2019. http://repository.kpi.kharkov.ua/handle/KhPI-Press/41237.
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The use of the flipped classroom as an alternative to the traditional learning environments has been increasingly attracting the attention of researchers and educators. The advancement in technological tools such as interactive videos, interactive in-class activities, and video conference systems paves the way for the widespread use of flipped classrooms. It is even asserted that the flipped classroom, which is used to create effective teaching environments at schools, is the best model for using technology in education. Studies about the flipped classroom appear in different disciplines including information systems, engineering, sociology, and humanities, mathematics education, and English composition. The purpose of this paper is to fulfil the needs regarding the review of recent literature on the use of the flipped classroom approach in education.
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Jellis, Christopher Henry. "Metalearning : PGCE students learning about learning." Thesis, Durham University, 2006. http://etheses.dur.ac.uk/2583/.
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As students, trainee teachers are required to reflect upon and take ownership of their own learning, but because of their future position as teachers, they also have to understand the learning of others. Trainee teachers have many ideas about teaching, but unless they have previous experience in the field, it is likely that their main understanding of what constitutes teaching and learning will be from their experiences of themselves as students. Many trainee teachers follow an uninterrupted route from school to university and then straight onto a PGCE course and will throughout their time in education have been experiencing teaching only from one direction 一 that of a student. During this time, many will develop ideas about what teachers actually do, but since a lot of what teachers do is preparation outside of the classroom, can students really get a balanced idea of the working life of a teacher? Trainee teachers, and indeed all postgraduate students need to reflect on their own learning in order to maximise their ability to assimilate and understand new information. This is the idea behind the concept of metalearning. Metalearning is a comparatively new phrase and as such, its meaning is still evolving. Originally defined by John Biggs (1985) as a process of being aware, and taking control, of one's own learning, it has subsequently been revisited and redefined. Some authors equate the concept with a practical form of metacognition, others with ideas involving reflective practice whilst others consider the phrase to mean "learning about learning" (Jackson, 2004). In the text which follows, the word is taken to mean "learning about learning" which could, in many cases be shown to subsume both the metacognitive and reflective theories. In any case, it is a very apt description of the principal role of trainee teachers. This longitudinal study tracks a group of trainee teachers following a PGCE course in order to observe their development and understanding of learning, both their own and that of their pupils and also to gain some insights into the experience of being a PGCE student in the 21 St Century.
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Akrour, Riad. "Robust Preference Learning-based Reinforcement Learning." Thesis, Paris 11, 2014. http://www.theses.fr/2014PA112236/document.
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Les contributions de la thèse sont centrées sur la prise de décisions séquentielles et plus spécialement sur l'Apprentissage par Renforcement (AR). Prenant sa source de l'apprentissage statistique au même titre que l'apprentissage supervisé et non-supervisé, l'AR a gagné en popularité ces deux dernières décennies en raisons de percées aussi bien applicatives que théoriques. L'AR suppose que l'agent (apprenant) ainsi que son environnement suivent un processus de décision stochastique Markovien sur un espace d'états et d'actions. Le processus est dit de décision parce que l'agent est appelé à choisir à chaque pas de temps du processus l'action à prendre. Il est dit stochastique parce que le choix d'une action donnée en un état donné n'implique pas le passage systématique à un état particulier mais définit plutôt une distribution sur l'espace d'états. Il est dit Markovien parce que cette distribution ne dépend que de l'état et de l'action courante. En conséquence d'un choix d'action, l'agent reçoit une récompense. Le but de l'AR est alors de résoudre le problème d'optimisation retournant le comportement qui assure à l'agent une récompense maximale tout au long de son interaction avec l'environnement. D'un point de vue pratique, un large éventail de problèmes peuvent être transformés en un problème d'AR, du Backgammon (cf. TD-Gammon, l'une des premières grandes réussites de l'AR et de l'apprentissage statistique en général, donnant lieu à un joueur expert de classe internationale) à des problèmes de décision dans le monde industriel ou médical. Seulement, le problème d'optimisation résolu par l'AR dépend de la définition préalable d'une fonction de récompense adéquate nécessitant une expertise certaine du domaine d'intérêt mais aussi du fonctionnement interne des algorithmes d'AR. En ce sens, la première contribution de la thèse a été de proposer un nouveau cadre d'apprentissage, allégeant les prérequis exigés à l'utilisateur. Ainsi, ce dernier n'a plus besoin de connaître la solution exacte du problème mais seulement de pouvoir désigner entre deux comportements, celui qui s'approche le plus de la solution. L'apprentissage se déroule en interaction entre l'utilisateur et l'agent. Cette interaction s'articule autour des trois points suivants : i) L'agent exhibe un nouveau comportement ii) l'expert le compare au meilleur comportement jusqu'à présent iii) l'agent utilise ce retour pour mettre à jour son modèle des préférences puis choisit le prochain comportement à démontrer. Afin de réduire le nombre d'interactions nécessaires entre l'utilisateur et l'agent pour que ce dernier trouve le comportement optimal, la seconde contribution de la thèse a été de définir un critère théoriquement justifié faisant le compromis entre les désirs parfois contradictoires de prendre en compte les préférences de l'utilisateur tout en exhibant des comportements suffisamment différents de ceux déjà proposés. La dernière contribution de la thèse est d'assurer la robustesse de l'algorithme face aux éventuelles erreurs d'appréciation de l'utilisateur. Ce qui arrive souvent en pratique, spécialement au début de l'interaction, quand tous les comportements proposés par l'agent sont loin de la solution attendueThe thesis contributions resolves around sequential decision taking and more precisely Reinforcement Learning (RL). Taking its root in Machine Learning in the same way as supervised and unsupervised learning, RL quickly grow in popularity within the last two decades due to a handful of achievements on both the theoretical and applicative front. RL supposes that the learning agent and its environment follow a stochastic Markovian decision process over a state and action space. The process is said of decision as the agent is asked to choose at each time step an action to take. It is said stochastic as the effect of selecting a given action in a given state does not systematically yield the same state but rather defines a distribution over the state space. It is said to be Markovian as this distribution only depends on the current state-action pair. Consequently to the choice of an action, the agent receives a reward. The RL goal is then to solve the underlying optimization problem of finding the behaviour that maximizes the sum of rewards all along the interaction of the agent with its environment. From an applicative point of view, a large spectrum of problems can be cast onto an RL one, from Backgammon (TD-Gammon, was one of Machine Learning first success giving rise to a world class player of advanced level) to decision problems in the industrial and medical world. However, the optimization problem solved by RL depends on the prevous definition of a reward function that requires a certain level of domain expertise and also knowledge of the internal quirks of RL algorithms. As such, the first contribution of the thesis was to propose a learning framework that lightens the requirements made to the user. The latter does not need anymore to know the exact solution of the problem but to only be able to choose between two behaviours exhibited by the agent, the one that matches more closely the solution. Learning is interactive between the agent and the user and resolves around the three main following points: i) The agent demonstrates a behaviour ii) The user compares it w.r.t. to the current best one iii) The agent uses this feedback to update its preference model of the user and uses it to find the next behaviour to demonstrate. To reduce the number of required interactions before finding the optimal behaviour, the second contribution of the thesis was to define a theoretically sound criterion making the trade-off between the sometimes contradicting desires of complying with the user's preferences and demonstrating sufficiently different behaviours. The last contribution was to ensure the robustness of the algorithm w.r.t. the feedback errors that the user might make. Which happens more often than not in practice, especially at the initial phase of the interaction, when all the behaviours are far from the expected solution
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Menke, Joshua Ephraim. "Improving Machine Learning Through Oracle Learning." BYU ScholarsArchive, 2007. https://scholarsarchive.byu.edu/etd/843.
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The following dissertation presents a new paradigm for improving the training of machine learning algorithms, oracle learning. The main idea in oracle learning is that instead of training directly on a set of data, a learning model is trained to approximate a given oracle's behavior on a set of data. This can be beneficial in situations where it is easier to obtain an oracle than it is to use it at application time. It is shown that oracle learning can be applied to more effectively reduce the size of artificial neural networks, to more efficiently take advantage of domain experts by approximating them, and to adapt a problem more effectively to a machine learning algorithm.
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Feffer, James F. "Teacher Learning Within Professional Learning Communities." CSUSB ScholarWorks, 2015. https://scholarworks.lib.csusb.edu/etd/166.
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Professional Learning Community (PLC) structures require focused sessions of teacher collaboration as part of developing effective instructional practices leading to improved student performance outcomes. The PLC structured collaboration model has been implemented in schools across the country, however the current body of research regarding PLC structures has been focused on student performance and rather than the teacher learning processes that occur within the model. Teachers must learn throughout the PLC model, as they collaborate, plan instruction, create assessments, analyze data, and adjust implementation to improve results.
A mixed-methods approach was used to explore correlations between PLC structure ratings and teacher self-identified learning preferences, with Kolb’s (1984) Experiential Learning Theory as the basis for determining learning preferences. The study included 115 elementary teacher participants from a school district that has prioritized PLC structures for nearly 10 years. Significant correlations were identified between PLC structural elements and teacher learning preferences, with qualitative results providing additional descriptive analysis regarding teacher perceptions of their learning within PLCs. The findings within this study indicate that teacher learning preferences may be a key consideration for school site administrators as part of PLC team construction and development.
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Adams, Evelyn May. "Lifelong learning and the learning culture of a college flexible learning centre." Thesis, University of Stirling, 2009. http://hdl.handle.net/1893/2751.
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This study aims to address a gap in knowledge about Further Education college flexible learning centres and their contribution to lifelong learning. Flexible learning centres were established as a response to the lifelong learning agenda of the 1990s and are now in the front line in responding to government initiatives to improve employability and foster social inclusion. Their tutors work in a contested area where the boundaries between teaching and supporting learning are blurred and the learning achieved may be undervalued by the Inspectorate and college authorities. This study adopts a qualitative approach of narrative inquiry to analyse the learning culture of the Flexible Learning Centre (FLC) of Hollypark College, focusing on 15 learners’ and 2 tutors’ narratives elicited by episodic interviews. The narratives of learning biographies and work biographies of learners and tutors are explored, supplemented by quantitative data from College databases. The study evaluates the ways in which the pedagogical approach of selfdirected study with tutor support appears to be successful for predominantly mature learners wishing to acquire mainly Information Technology (IT) skills which may enhance their chances of employment or benefit them in other ways. Building on recent work on learning cultures, social capital, well-being and identity theories, the study gives a voice to these learners who are so far unheard and despite the demographic population shift to increasing numbers of older people, are not the focus of current government policy initiatives. Focus on employability which is equated with acquiring skills is seen as too narrow to encompass the wider needs met and benefits accrued by attending the FLC. The findings are that this FLC’s approach is particularly effective for older learners in general in acquiring IT skills. Those made redundant, the retired, those in work and carers who may have been out of the workforce for some time may flourish in this learning environment where mainstream courses cannot offer equivalent flexibility and opportunities to structure their own learning. The learning culture of the Flexible Learning Centre provides a space where such learners may not only acquire IT skills but may also increase their social and cultural capital while opening up new horizons for their future. Tutor/learner relationships are of key importance and the learning taking place should be re-evaluated by the Inspectorate and government alike.
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Wolfson, Larry. "Learning through service : community service learning and situated learning in high school." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape8/PQDD_0018/NQ46449.pdf.
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Bernhard, Jonte, Anna-Karin Carstensen, and (née Gonzalez-Sampayo) Margarita Holmberg. "Investigating engineering students‘ learning – learning as the learning of a complex concept." Linköpings universitet, Fysik och elektroteknik, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-65601.
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In both engineering and physics education, a common objective is that students should learn to use theories and models in order to understand the relation between theories and models, and objects and events, and to develop holistic, conceptual knowledge. During lab-work, students are expected to use, or learn to use, symbolic and physical tools (such as concepts, theories, models, representations, inscriptions, mathematics, instruments and devices) in order both to understand the phenomena being studied, and to develop the skills and abilities to use the tools themselves. We have earlier argued that this learning should be seen as the learning of a complex concept, i.e. a “concept” that makes up a holistic system of “single” interrelated “concepts” (i.e. a whole made up of interrelated parts). On the contrary, however, in education research it is common to investigate “misconceptions” of “single concepts”. In this paper we will show the power of analysing engineering students’ learning as the learning of a complex concept. In this model “single concepts” are illustrated as nodes or “islands” that may be connected by links, while the links that students actually make are represented by arrows. The nodes in our model are found by looking for “gaps” in the actions and conversations of students. A gap corresponds to a non-established link, and when a gap is filled and the students establish a relation between two nodes, this is represented by a link. The more links that are made, the more complete the knowledge. In this study we report an analysis of a sequence of labs about AC-electricity in an electric circuit theory course. In for example electric circuit theory the “concepts” of current, voltage and impedance are interdependent. Rather, the central physical phenomenon is “electricity” represented by Ohms law as a generalization of the current/voltage/impedance/frequency-relationship of a circuit or circuit element. The results show the learning of “electricity” as a complex concept with students’ knowledge becoming more complete. Furthermore, according to our analysis “entities” that in later labs were fused into one were separate in the earlier labs. For example in a later lab we could note that “the physical circuit” and “the circuit drawing” had fused into a single “real circuit”. Our results suggest that the learning of a complex concept first start with establishing more and more links. As links become well established, “entities” that have been separate fuse into a whole. Our model suggests a method for finding “learning difficulties” since these corresponds to “gaps” and non-established links. As teachers and experts in a field we can miss to uncover these since for us the ‘complex concept’ has become a conceptual whole and we may no longer be able to distinguish the parts in the complex. In line with the thesis of M. Holmberg we also argue that learning problems in electric circuit theory may be due to the common failure to appreciate that concepts are relations.
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Sobol, Sky Harris. "ASSOCIATIVE LEARNING IN ANTS: ODOR LEARNING VS. COLOR LEARNING IN NOVOMESSOR COCKERELLI." Thesis, The University of Arizona, 2016. http://hdl.handle.net/10150/613629.
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Associative learning is a form of learning where an animal learns to associate a stimulus with a behavioral response. Associative learning has been generated in the laboratory for many species, including insects, by using classical conditioning. Previous experiments show that ants can learn to associate odors and colors with a sugar reward. When ants are trained to associate a stimulus with a sugar reward, they exhibit the proboscis extension response (PER) to the stimulus alone, but it was unknown whether ants are better at color association or odor association. In order to test this, two separate experiments were undertaken. The first used classical conditioning to train ants to associate a sucrose solution with an odor. The second used classical conditioning to train two groups of ants. The first group was trained to associate a sucrose solution with a blue light. The second group was trained to associate a sucrose solution with a green light. For both experiments a significant percentage of ants demonstrated learning by exhibiting PER when presented solely with the odor or light. There was, however, no significant difference between the percentages of ants that demonstrated learning from the blue light, the green light, or the odor.
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McLachlan, Benita. "Learning for excellence : professional learning for learning support assistants within further education." Thesis, Anglia Ruskin University, 2012. http://arro.anglia.ac.uk/297145/.
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The 1980s saw an increase in learning support assistants (LSAs’) in colleges for further education to support post-sixteen learners with learning difficulties and disabilities (LDD). LSAs’ were appointed on an ad hoc basis with little or no experience, or relevant qualifications to deliver support in ‘inclusive’ vocational classrooms. The Workforce Development Plan in 2004 acknowledged this phenomenon and advocated that occupational standards be developed. Two years later, in October 2006, the first National Occupational Standards (NOS) for college LSAs was launched but it did not include an official training framework for their professional learning and although there are some training structures in place, this still remains the case today. Learners with LDD are, therefore, still supported by untrained LSAs’ who are not professionally equipped to deal with the particular challenges they present. Educators like myself who work alongside LSAs’ in colleges, must seek to naturalistically explore professional learning opportunities to enhance their knowledge and skills. Such professional learning opportunities should reflect the creative and dynamic contribution college LSAs’ bring to inclusive classrooms and, thereby, not only improve the quality of the support LSAs’ give but the overall integrative, ethical and non-discriminative ethos of a college. With this knowledge, I developed and implemented an Enhanced Learning Support Assistant Programme (ELSAP) for the professional learning of volunteer LSA participants with the aim of improving their knowledge and skills to deliver a more meaningful education for postsixteen learners with LDD. For the acquisition of new knowledge and skills, professional learning for LSAs’ needs to occur systemically over time and be integrated within the multilayered context of a college to allow dynamic and reciprocal influences to make transformative connections. Critically, my action research study strengthens the connection between socio-political theory and practice within the sociology of disability education on moral, ethical and human rights grounds.
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McLachlan, Benita. "Learning for Excellence: Professional learning for learning support assistants within further education." Thesis, Anglia Ruskin University, 2012. https://arro.anglia.ac.uk/id/eprint/297145/6/McLachlan_2012.pdf.
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The 1980s saw an increase in learning support assistants (LSAs’) in colleges for further
education to support post-sixteen learners with learning difficulties and disabilities (LDD).
LSAs’ were appointed on an ad hoc basis with little or no experience, or relevant
qualifications to deliver support in ‘inclusive’ vocational classrooms. The Workforce
Development Plan in 2004 acknowledged this phenomenon and advocated that occupational
standards be developed. Two years later, in October 2006, the first National Occupational
Standards (NOS) for college LSAs was launched but it did not include an official training
framework for their professional learning and although there are some training structures in
place, this still remains the case today.
Learners with LDD are, therefore, still supported by untrained LSAs’ who are not
professionally equipped to deal with the particular challenges they present. Educators like
myself who work alongside LSAs’ in colleges, must seek to naturalistically explore
professional learning opportunities to enhance their knowledge and skills. Such professional
learning opportunities should reflect the creative and dynamic contribution college LSAs’
bring to inclusive classrooms and, thereby, not only improve the quality of the support LSAs’
give but the overall integrative, ethical and non-discriminative ethos of a college. With this
knowledge, I developed and implemented an Enhanced Learning Support Assistant
Programme (ELSAP) for the professional learning of volunteer LSA participants with the aim
of improving their knowledge and skills to deliver a more meaningful education for postsixteen
learners with LDD. For the acquisition of new knowledge and skills, professional
learning for LSAs’ needs to occur systemically over time and be integrated within the multilayered
context of a college to allow dynamic and reciprocal influences to make
transformative connections. Critically, my action research study strengthens the connection
between socio-political theory and practice within the sociology of disability education on
moral, ethical and human rights grounds.
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Kim, Dong Ki S. M. Massachusetts Institute of Technology. "Learning to teach and meta-learning for sample-efficient multiagent reinforcement learning." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/128312.
Full textAbstract:
Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2020Cataloged from PDF of thesis.
Includes bibliographical references (pages 89-97).
Learning optimal policies in the presence of non-stationary policies of other simultaneously learning agents is a major challenge in multiagent reinforcement learning (MARL). The difficulty is further complicated by other challenges, including the multiagent credit assignment, the high dimensionality of the problems, and the lack of convergence guarantees. As a result, many experiences are often required to learn effective multiagent policies. This thesis introduces two frameworks to reduce the sample complexity in MARL. The first framework presented in this thesis provides a method to reduce the sample complexity by exchanging knowledge between agents. In particular, recent work on agents that learn to teach other teammates has demonstrated that action advising accelerates team-wide learning.
However, the prior work simplified the learning of advising policies by using simple function approximations and only considering advising with primitive (low-level) actions, both of which limit the scalability of learning and teaching to more complex domains. This thesis introduces a novel learning-to-teach framework, called hierarchical multiagent teaching (HMAT), that improves scalability to complex environments by using a deep representation for student policies and by advising with more expressive extended-action sequences over multiple levels of temporal abstraction. Our empirical evaluations demonstrate that HMAT improves team-wide learning progress in large, complex domains where previous approaches fail. HMAT also learns teaching policies that can effectively transfer knowledge to different teammates with knowledge of different tasks, even when the teammates have heterogeneous action spaces.
The second framework introduces the first policy gradient theorem based on meta-learning, which enables fast adaptation (i.e., need only a few iterations) with respect to the non-stationary fellow agents in MARL. The policy gradient theorem that we prove inherently includes both a self-shaping term that considers the impact of a meta-agent's initial policy on its adapted policy and an opponent-shaping term that exploits the learning dynamics of the other agents. We demonstrate that our meta-policy gradient provides agents to meta-learn about different sources of non-stationarity in the environment to improve their learning performances.
by Dong Ki Kim.
S.M.
S.M. Massachusetts Institute of Technology, Department of Aeronautics and Astronautics
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Lynggaard, Henrik Eisner. "Learning disabilities and systemic psychotherapy : a field of rich learnings." Thesis, Manchester Metropolitan University, 2017. http://e-space.mmu.ac.uk/618900/.
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This paper reviews eleven publications that I submit for the degree of Doctor of Philosophy. Three themes are identified that together constitute major strands running through the publications: a) promoting and making the systemic approach accessible and relevant in the field of learning disabilities; b) challenges and opportunities in working systemically with people affected with learning disabilities; c) raising the question of who and what in the system needs to change. Following discussion of the three themes the analytical commentary moves on to highlight four areas entitled 'rich learnings' that emerged from reviewing fifteen years of publications and practice. The areas include: a consideration of the knowledge that emerge in relationship and dialogue; learning from difference and diversity; and the learning that can develop from teaching, transmission and partnership working. The central argument of the analytical commentary is that taken as a whole body of work, the publications and the associated practices demonstrate that I have made an original contribution to the field of systemic psychotherapy in the area of learning disabilities, and that I have played a significant role in transmitting the approach to others.
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Pacheva, Daniela Jivkova. "College students with learning disabilities: a developmental perspective on conceptions of learning, learning disability, and others in learning." Thesis, University of British Columbia, 2007. http://hdl.handle.net/2429/366.
Full textAbstract:
A call for the design of programs focused on the development of self-awareness skills permeates the field of research and practice on postsecondary students with learning disabilities (LD). Important components of self-awareness are students' advanced understanding of learning, LD, and the social context (peers, instructors, classmates) of college learning.
This study explores students with LD's conceptual understanding of learning and LD by situating it within developmental theoretical frameworks delineating the form and content of adult reasoning. Twelve female and five male college-students with LD participated in two-hour interviews. Students' thinking about others was explored by asking participants to reason about the behaviors, intentions, feelings and traits of the characters in two scenarios depicting typical dilemmas faced by students with LD. Students' conceptual understanding of learning and LD was elicited by means of open-ended questions followed by prompts. Students' responses were scored for level of cognitive complexity and coded for conceptual content.
Overall, the students reasoned abstractly about learning and LD at a level of complexity expected from college-age population. They demonstrated well-developed understanding of others' expectations and motivations especially as they relate to the themes of self-identification, seeking accommodations, and understanding of LD. Students' conceptions of learning and LD presented qualitatively different variations on main themes. These variations paralleled the increase in complexity and were associated with experience(number of years of education). The overarching understanding of learning as acquiring knowledge transitioned from understanding learning as an external, given task to learning as an internal, personal-development process. The common understanding of LD as a difference transitioned from a difference related to an external label and an imposed constraint, to meaning of "difference" as a special ability, an asset, and a source of identity.
These results indicate a possible progression in the evolution of the concepts of learning and LD throughout the college career of students with LD. The approach to this conceptual content and its description can inform and serve as starting points in the development of programs that foster the conceptual understanding of learning, LD, and the social-context of the educational enterprise, as a way of building these students' self-awareness skills.
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Jönsson, Andreas. "Learning cohesively : Cohesion in Second Language Learning." Thesis, Högskolan i Gävle, Avdelningen för humaniora, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-8537.
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This essay concerns itself with the importance of learning English as a second language cohesively. The research focus is on student responsibility to learn English and if as well as how this responsibility contributes to have students' perceptions of learning the language cohesively. The applied research method consists of a student questionnaire and two teacher interviews. The questionnaire produces a description of students' relationship to, and view of, the English language and how they understand their learning process in acquiring it. The two teacher interviews establish if and how the teachers influence the students' cohesive understanding of the English language.
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Foulds, James Richard. "Learning Instance Weights in Multi-Instance Learning." The University of Waikato, 2008. http://hdl.handle.net/10289/2460.
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Multi-instance (MI) learning is a variant of supervised machine learning, where each learning example contains a bag of instances instead of just a single feature vector. MI learning has applications in areas such as drug activity prediction, fruit disease management and image classification. This thesis investigates the case where each instance has a weight value determining the level of influence that it has on its bag's class label. This is a more general assumption than most existing approaches use, and thus is more widely applicable. The challenge is to accurately estimate these weights in order to make predictions at the bag level. An existing approach known as MILES is retroactively identified as an algorithm that uses instance weights for MI learning, and is evaluated using a variety of base learners on benchmark problems. New algorithms for learning instance weights for MI learning are also proposed and rigorously evaluated on both artificial and real-world datasets. The new algorithms are shown to achieve better root mean squared error rates than existing approaches on artificial data generated according to the algorithms' underlying assumptions. Experimental results also demonstrate that the new algorithms are competitive with existing approaches on real-world problems.
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Kapmeier, Florian. "Dynamics of interorganizational learning in learning alliances /." Frankfurt am Main [u.a.] : Lang, 2007. http://www.gbv.de/dms/zbw/525116672.pdf.
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Henley, Jennie. "The learning ensemble : musical learning through participation." Thesis, Birmingham City University, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.527426.
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This thesis is an examination of the learning processes employed by adults who learn to play an instrument within an ensemble. The alms of the research were threefold. Firstly, to discover how a person learns in a group and what the role of the soclo-cultural environment is In learning. Secondly, to Investigate the role that Identity plays In learning and whether the students regard themselves as musicians. Rnally, to explore the role of the performance in the musical learning process. The research has been carried out using case-study research and a four-year autoethnographlc study. The theoretical framework Is provided by literature from the fields of cultural psychology, music psychology and adult learning. Activity Theory has been used as the main analytical tool. The discussion firstly considers the leaming process in order to construct an activity system of muslcalleamlng within an ensemble. Then, using this activity system, the motivational factors inherent In the learning ensemble and the role of Identity In generating motivation are considered. Through analysing motivation and Identity In relation to the activity system, I have demonstrated how the activity system can be developed into a three-dimensional system by Incorporating Identity as a constituent, thus stabilising the activity system. A three-dimensional system then allows for multiple activities to be analysed through the construction of activity constellations. The result of this study is a model of partidpative learning. Partidpative learning takes Into consideration the purpose of learning and the soclo-cultural environment so that musical leaming Is embedded In social music making. This then provides music education with a new model for leamlng a musical Instrument.
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Reeder, John. "Life Long Learning in Sparse Learning Environments." Doctoral diss., University of Central Florida, 2013. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5845.
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Life long learning is a machine learning technique that deals with learning sequential tasks over time. It seeks to transfer knowledge from previous learning tasks to new learning tasks in order to increase generalization performance and learning speed. Real-time learning environments in which many agents are participating may provide learning opportunities but they are spread out in time and space outside of the geographical scope of a single learning agent. This research seeks to provide an algorithm and framework for life long learning among a network of agents in a sparse real-time learning environment. This work will utilize the robust knowledge representation of neural networks, and make use of both functional and representational knowledge transfer to accomplish this task. A new generative life long learning algorithm utilizing cascade correlation and reverberating pseudo-rehearsal and incorporating a method for merging divergent life long learning paths will be implemented.Ph.D.
Doctorate
Electrical Engineering and Computing
Engineering and Computer Science
Computer Engineering
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Farrell, Tracie. "Affordances of learning analytics for mediating learning." Thesis, Open University, 2018. http://oro.open.ac.uk/57621/.
Full textAbstract:
Learning analytics acceptance and adoption is a socio-technological endeavour. Understanding how learning analytics impact practice is an important part of demonstrating their value. In the study presented in this thesis, "Mediated Learning" provides a framework through which to describe how learning analytics can impact psychological, social and material aspects of learning, from the perspective of educators and learners. It also offers a structure through which to make recommendations for improving the mediatory effects of learning analytics. A qualitative research design, based on "Grounded Theory" was implemented and 10 educators from 3 European universities were recruited through convenience and purposive sampling for exploratory interviews. A subsequent case study of the Open University provided critical perspectives from both educators (n=18) and learners (n=22) about the institutional, departmental, domain-related and epistemological factors that broadly influence perceptions of learning analytics. The study applied "Affordance Theory" to identify what participants were most easily able to recognise as beneficial to their own practice. Participant contributions were open-coded to uncover emerging themes and then organised into thematic categories and subcategories. Respondent validation, as well as triangulation of data between the exploratory interviews and focus groups support the validity of the study. Findings suggested that domain-related epistemological assumptions and previous experience influence how and why an individual could make use of learning analytics insights. Gaining stakeholder acceptance involves targeting the right training and opportunities at the appropriate disciplines. Findings also indicate that learning analytics has the strongest mediatory effect for learners when the technology is capable of exposing them to other learners' strategies, or when it assists them personally, and continually in goal orientation adoption. The implications of the study are important for higher education institutions looking to implement large-scale learning analytics initiatives, in particular, those with a diverse student body.
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Berger, Ulrich. "Learning to trust, learning to be trustworthy." WU Vienna University of Economics and Business, 2016. http://epub.wu.ac.at/4806/1/wp212.pdf.
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Interpersonal trust is a one-sided social dilemma. Building on the binary trust game, we ask how trust and trustworthiness can evolve in a population where partners are matched randomly and agents sometimes act as trustors and sometimes as trustees. Trustors have the option to costly check a trustee's last action and to condition their behavior on the signal they receive. We show that the resulting population game admits two components of Nash equilibria. Nevertheless, the long-run outcome of an evolutionary social learning process modeled by the best response dynamics is unique. Even if unconditional distrust initially abounds, the trustors' checking option leads trustees to build a reputation for trustworthiness by honoring trust. This invites free-riders among the trustors who save the costs of checking and trust blindly, until it does no longer pay for trustees to behave in a trustworthy manner. This results in cyclical convergence to a mixed equilibrium with behavioral heterogeneity where suspicious checking and blind trusting coexist while unconditional distrust vanishes. (author's abstract)Series: Department of Economics Working Paper Series
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Riis, Jonathan. "Learning about innovations: learning styles and characteristics." Thesis, Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-32965.
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Purpose - The purpose of this paper is to explore what people think is the best way to learn about innovations by different learning styles and characteristics. The paper will give answers to which learning style that people think is the best way to use when learning about innovation. Methodology - The data for this study were collected via online-surveys and through paper surveys. A total of 224 usable responses were obtained. The method will consist of primary data, which will be collected through surveys. Secondary research will be presented in the empire which will be retrieved from databases like Scopus, Diva, Emerald, Web of Science and Google Scholar. Implications/findings - Of the four different learning styles investigated in this study the result revealed that people best learn about innovations from the tactile/kinaesthetic learning style. The least pedagogic method to learn about innovations was the visual/verbal learning style. Paper type - Research paper
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Hussein, Ahmed. "Deep learning based approaches for imitation learning." Thesis, Robert Gordon University, 2018. http://hdl.handle.net/10059/3117.
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Imitation learning refers to an agent's ability to mimic a desired behaviour by learning from observations. The field is rapidly gaining attention due to recent advances in computational and communication capabilities as well as rising demand for intelligent applications. The goal of imitation learning is to describe the desired behaviour by providing demonstrations rather than instructions. This enables agents to learn complex behaviours with general learning methods that require minimal task specific information. However, imitation learning faces many challenges. The objective of this thesis is to advance the state of the art in imitation learning by adopting deep learning methods to address two major challenges of learning from demonstrations. Firstly, representing the demonstrations in a manner that is adequate for learning. We propose novel Convolutional Neural Networks (CNN) based methods to automatically extract feature representations from raw visual demonstrations and learn to replicate the demonstrated behaviour. This alleviates the need for task specific feature extraction and provides a general learning process that is adequate for multiple problems. The second challenge is generalizing a policy over unseen situations in the training demonstrations. This is a common problem because demonstrations typically show the best way to perform a task and don't offer any information about recovering from suboptimal actions. Several methods are investigated to improve the agent's generalization ability based on its initial performance. Our contributions in this area are three fold. Firstly, we propose an active data aggregation method that queries the demonstrator in situations of low confidence. Secondly, we investigate combining learning from demonstrations and reinforcement learning. A deep reward shaping method is proposed that learns a potential reward function from demonstrations. Finally, memory architectures in deep neural networks are investigated to provide context to the agent when taking actions. Using recurrent neural networks addresses the dependency between the state-action sequences taken by the agent. The experiments are conducted in simulated environments on 2D and 3D navigation tasks that are learned from raw visual data, as well as a 2D soccer simulator. The proposed methods are compared to state of the art deep reinforcement learning methods. The results show that deep learning architectures can learn suitable representations from raw visual data and effectively map them to atomic actions. The proposed methods for addressing generalization show improvements over using supervised learning and reinforcement learning alone. The results are thoroughly analysed to identify the benefits of each approach and situations in which it is most suitable.
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Zweers, Gerard Antonie. "Learning to be authentic and authentic learning." Thesis, University College London (University of London), 2012. http://discovery.ucl.ac.uk/10020694/.
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Some of the main challenges facing education at the beginning of the twenty first century concern our relationship with life and living beings. More precisely, the main theories of learning which inform educational practice in the west - such as behaviourism, constructivism, information processing, and situated learning - do not allow for a learning that results in the learner having a true understanding of the being of living beings and of life itself. Against this kind of learning, which will be called learning as modification and growth, a second process is proposed, called learning to be authentic, which is based on Heidegger's notion of authenticity as a state in which a true understanding of the being of living beings and life itself is present. This learning to be authentic allows for the entities involved to be approached in a way that is appropriate to life and living beings. It is experienced, on the one hand, as a process of letting go and quieting down, and, on the other hand, as a process of opening up and being in touch with the entities that are encountered. It involves a growing non-reflective self-awareness and the awakening of another way of being, and it demands a kind of educational practice that is in many ways different from what is current in most educational settings. Learning as modification and growth and learning to be authentic can merge into one process, which allows for the process learning as modification and growth to take place in such a way that it is guided by the openness that characterizes authentic existence. This integrated process, which constitutes a form of learning that results in the learner having a true understanding of the being of living beings and of life itself, will be called authentic learning.
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Mahadevan, Shankar. "A Learning Object Model For Electronic Learning." Thesis, Virginia Tech, 2002. http://hdl.handle.net/10919/34060.
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Digital libraries are fast expanding into the role of independent educational entities that aspire not only to complementing traditional classroom teaching, but also allow open electronic learning for distance and continued education. These multifaceted roles can be realized only if the course content and the related content management system are versatile enough to be captured into any individual's learning needs. Many studies have defined a concept of "learning object" to address the issues and needs. But in attempting to solve the problem, the definitions have emphasized some aspects of the digital library while leaving the other issues to be solved later. Thus, the whole system dynamics is either weak or too cumbersome to navigate. As a part of this masters work, firstly the current model of pedagogical endowment was investigated. In order to accommodate the digital nature of education, a new modern profile of learning is proposed that allows modular yet efficient transfer of knowledge from the teacher to the pupil. The thesis then proposes a comprehensive learning object (LO) model, along with the associated system model, that will allow complete and flexible integration of content into the modern digital library profile. The process will be user-centric (both for knowledge developers and learners) as well as metadata-centric. It is scalable and interoperable with legacy and existing content databases and display systems. This thesis covers how the LO model is integrated into the core of the library's content development, discovery, and delivery process. The results of the experiment in terms of ease-of-use, flow-control, and feasibility of the model are documented. A beta-version of these concepts has been successfully tested with volunteers and implemented as a part of the Digital Library Network for Engineering and Technology (DLNET) project.Master of Science
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Zhang, Jingwei [Verfasser], and Wolfram [Akademischer Betreuer] Burgard. "Learning navigation policies with deep reinforcement learning." Freiburg : Universität, 2021. http://d-nb.info/1235325571/34.
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Evanshen, Pamela, L. Phillips, C. Nester, and Melody Archer. "Real Learning: Ways to Make Learning Meaningful." Digital Commons @ East Tennessee State University, 2002. https://dc.etsu.edu/etsu-works/4397.
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Martin, Trudi. "Workplace learning for Learning Support Assistants in a special school." Thesis, University of Manchester, 2017. https://www.research.manchester.ac.uk/portal/en/theses/workplace-learning-for-learning-support-assistants-in-a-special-school(8490d814-7a76-431e-bafe-13e3cf2edc04).html.
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This research explored the factors that influence whether Learning Support Assistants (LSAs), who support the learning of pupils with very complex learning needs, are equipped with the necessary skills to help these students learn. A significant feature in the delivery of educational support to pupils with low incidence needs is that it is LSAs who provide the majority of educational instruction and, furthermore, these paraeducators work with only limited supervision from class teachers. It therefore follows that if high quality educational assistance is to be available to pupils, then those undertaking the majority of this support need to have appropriate pedagogical knowledge. I explored this complex subject by undertaking a workplace ethnography at a single special school over the course of an academic year. In my ethnography, I used a number of data collection methods, including semi-structured interviews with teachers, LSAs and therapists, as well as participant and non-participant observations. The limited literature on the topic of LSA learning concludes that they are not being provided with the learning opportunities they need for the demanding work they do. However, because of the scarcity of information in the literature pertaining to the development of this important group of the educational workforce, I needed to look to the literature on organisational learning more broadly to inform my work and relate it to my own area of interest. The lack of priority given to non-formal learning was a key theme across these texts, with opportunities for participative learning emerging as an important feature. However, this aspect alone could not explain the reasons why these paraeducators did not have access to learning provision appropriate to their needs and so I looked to other theories of workplace learning. The conceptual and analytical approach of the Working as Learning Framework (WALF) (Felstead, et al., 2009), with its incorporation of the concepts of systems of production, discretion, and learning environments and territories, offered me the opportunity to scrutinise the situation regarding the learning and development of LSAs from a wide perspective. Through my adoption of the WALF I have identified the influences that shaped the workplace learning environment of the LSAs at the special school. In doing so, I have added to the limited research on this important and yet inadequately understood group. Although my study focused on one special school this research can inform how the abilities of paraeducators in different educational settings can be developed, because of my adoption of the theoretical standpoint of the WALF. Furthermore, by applying the WALF, my thesis has utilised workplace learning theory to make an important intellectual contribution to the discussion about how high quality educational provision can be delivered. My thesis is also apposite, because the number of children with more complex learning difficulties is increasing and these individuals require specialist paraeducators to be appropriately equipped to meet their needs, whether they are being educated in special or mainstream schools.
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Alrayes, Amal. "Investigating the learning performance in computer supported collaborative learning environments." Thesis, University of Manchester, 2013. https://www.research.manchester.ac.uk/portal/en/theses/investigating-the-learning-performance-in-computer-supported-collaborative-learning-environments(369f64e0-3309-499e-a00a-c097ae7e5d03).html.
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This thesis concerns groupwork, Computer Supported Collaborative Learning (CSCL) and social relationships. The use of the computer, especially when it involves the web, is claimed to be one of the most powerful tools for providing teachers and learners with an interactive and independent learning environment. This claim is justified by the immediate and wide accessed to resources. Although CSCL involves many technologies and functions, it is agreed that its universal feature is to encourage students to seek in-depth learning. The main purpose of this research is to empirically investigate the influences on learning outcomes in CSCL environments, specifically to understand how affordances for collaboration contribute to user experience as well as performance in groupwork; and to study social relationships and how they may affect learning performance. The main motivations behind this research are: 1) contradictions in the literature about the effectiveness of using the technology in groupwork, and 2) the shortcomings of existing collaborative environments, such as a poor sense of presence and limited non-verbal communication. Evaluations of collaborative technology have tended to follow either an ethnographic approach to investigate the context of use in depth, or more focused experimental analyses directed towards specific questions about collaboration. However, this research followed the mixed methods approach which has been successfully applied in HCI (Murphy et al., 1999; Ormerod et al., 2004), so this approach is suitable for investigating CSCL affordances and requirements. A series of seven field studies was conducted, using both quantitative (questionnaires) and qualitative (observations and interviews) methods. Synthesising the analysis of the seven studies involved experimentally comparing the affordances of some existing collaborative technologies (Blackboard and SecondLife). Overall, the results offer four main contributions. First, a conceptual model of the factors that impact performance in CSCL environments is developed, including three main dimensions: technology, group and learner features. Second, the key theoretical findings in this research show that social relationships and overall group activities do not correlate directly with performance, so our results appear to agree with previous findings that social relationships have no positive effect on learning performance. However, some social familiarity does appear to promote group interaction and performance. Comparing the use of technologies with face-to-face collaboration produced a complex picture. The 3D virtual world did not produce the expected benefit, probably because of usability problems encountered with the avatars. In contrast, the text-based virtual world was perceived as being more usable, even though for some groups it was considered to be boring and not a stimulating user experience. Although face-to-face collaboration was expected to be most effective, and indeed it was quickest and rated best on experience and positive emotions, it did not produce more accurate results. Third, was the mixed methods research approach and the discourse analysis method used to analyse the Blackboard threads in this research. Finally, the research provides guidelines for both educators and designers of CSCL environments. Although the exploratory nature of the study resulted in certain limitations, the study enriches existing knowledge in the area of CSCL and provides theoretical, methodological and practical insights that suggest promising opportunities for future research.
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Abu, Alqumboz Moheeb Abed. "Challenges to interorganisational learning in learning networks : implications for practice." Thesis, University of Manchester, 2015. https://www.research.manchester.ac.uk/portal/en/theses/challenges-to-interorganisational-learning-in-learning-networks-implications-for-practice(a449165f-f826-4f1c-afd6-378c4e0f0afd).html.
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Research on organisational learning (OL) was mainly positioned within the psychological and sociological domains. Past and extant research on OL focused on the behavioural, cognitive and intuitive perspectives in addition to a growing track of research grounded on social theory. So far, a countless number of research studies attempted to address inter-organisational learning (IOL) from various perspectives. However, the lack of understanding of how IOL occurs in networks can be observed due to the social tensions that are created at the inter-organisational level such as free-riding and knowledge leakage. This thesis, therefore, aims to draw theoretical explanations of IOL and how it occurs in learning networks, taking into consideration similarities and contradictions amongst a network’s participating organisations. Towards this end, the thesis employs two theoretical lenses, namely structure-agency and social exchange theories to draw conclusions that provide fresh explanations of how networks are helpful in fostering or hindering learning activities in addition to how reciprocity as an efficacy device mediates IOL dynamics. Positioned within a qualitative vein, the thesis employs an interpretive perspective to collect and analyse empirical evidence. The qualitative data were developed through a mixture of participant observations, semi-structured interviews and casual conversations with network administrators and participants. The data were analysed using thematic analysis which generated codes, following which conclusions were drawn. The main contributions of this article are (1) unfolding the network as agency which provides a fresh understanding of how the agential role of networks mediates IOL and (2) drawing a framework of dimensions of reciprocal exchanges that explains how IOL occurs in networks. The first conclusion of this thesis explained how the agential role is socially constructed and how the interpretive device facilitated this construction. The second conclusion of this thesis explained how reciprocal exchanges mediate IOL and provide a framework that suggested IOL can be better understood through temporal, spatial, directional and symmetrical perspectives.
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Slimani, A. "The teaching/learning relationship : Learning opportunities and learning outcomes an Algerian case study." Thesis, Lancaster University, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.381067.
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The major thrust of the study was to explore the relationships between what a group of Algerian learners claimed to have learned from lessons and the interactive work in which, together with their Algerian teacher, they have participated. This opportunity is taken to examine, in the light of our data, some variables, claimed by classroom centered and second language acquisition studies to be, in some strong sense, relevant to second language development. These variables are: the impact of frequency of language use, the effect of the use of conversational adjustments (CAs) in the discourse, and the role of participation in the classroom. The analysis of the learners' responses has led also to the examination of the importance of the participants' topicalisation. Besides the investigation of the claims, the data was used to test the limits of direct classroom observation to provide answers as to how second language learning develops in the classroom. Two types of data were necessary for the investigation of the issue: Learners' specific claims collected through questionnaires, and detailed accounts of the learning opportunities obtained through systematic observation of 11 hours of audio- recorded naturally occurring classroom data. The latter set was supplemented with field notes taken by the observer and author of this study. The numerical information obtained through the analysis of the data was used in combination with a qualitative analysis of the classroom interaction to derive the following suggestive findings. The relationship between interaction and uptake was seen, in this study, to be far more complicated and indirect than the claims made by others in the field might have led us to believe. Frequency of the ttl teacher's use of language presented a rather low correlation with the students' learning outcomes. The use of CAs did not show an overall significant correlation with the learners' claims. Most of the coding schemes used to quantify learner input generation failed to show a correlation between interaction and progress. A weak correlation appeared between interaction and achievement. The examination of the theme of topicalisation has shown the learners, as discourse initiators, to be more influential than the teacher on what gets claimed to be learned in this specific instructional setting.
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Kaiser, Robert Cresswell. "Adult Learning: Evaluation of Preferences for Technology and Learning Sources for Workplace Learning." Thesis, University of North Texas, 2016. https://digital.library.unt.edu/ark:/67531/metadc955033/.
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The purpose of this research was to provide an initial investigation of the preferences for both technology and learning sources that are available today in the modern workplace at a large financial institution with a national presence in the USA. In addition to the preferences of the participants, the research includes insights about the culture of the learning organization by using the Dimension of Learning Organization Questionnaire (DLOQ) and two preference surveys. The research methods used in this study are categorized as mixed methods and include both quantitative and qualitative methods. This study is nonpositivist and descriptive. It is based on a triangulation design method which is comprised of analysis from data obtained from the DLOQ and preference surveys, as well as semi-structured interviews with several survey participants. The results of the studies provide the foundational information for an extended quantitative analysis.
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Andersson, Viktor. "Machine Learning in Logistics: Machine Learning Algorithms : Data Preprocessing and Machine Learning Algorithms." Thesis, Luleå tekniska universitet, Datavetenskap, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-64721.
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Data Ductus is a Swedish IT-consultant company, their customer base ranging from small startups to large scale cooperations. The company has steadily grown since the 80s and has established offices in both Sweden and the US. With the help of machine learning, this project will present a possible solution to the errors caused by the human factor in the logistic business.A way of preprocessing data before applying it to a machine learning algorithm, as well as a couple of algorithms to use will be presented.Data Ductus är ett svenskt IT-konsultbolag, deras kundbas sträcker sig från små startups till stora redan etablerade företag. Företaget har stadigt växt sedan 80-talet och har etablerat kontor både i Sverige och i USA. Med hjälp av maskininlärning kommer detta projket att presentera en möjlig lösning på de fel som kan uppstå inom logistikverksamheten, orsakade av den mänskliga faktorn.Ett sätt att förbehandla data innan den tillämpas på en maskininlärning algoritm, liksom ett par algoritmer för användning kommer att presenteras.
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Esho, Samuel Oluwadara. "Learning Learning Algorithms." Master's thesis, 2020. http://hdl.handle.net/10400.6/10817.
Full textAbstract:
Machine learning models rely on data to learn any given task and depending on the universal diversity of each of the elements of the task and the design objectives, multiple data may be required
for better performance, which in turn could exponentially increase learning time and computational cost. Although most of the training of machine learning models today are done using GPUs
(Graphics Processing Unit) to speed up the training process, most however, depending on the
dataset, still require a huge amount of training time to attain good performance.
This study aims to look into learning learning algorithms or popularly known as metalearning
which is a method that not only tries to improve the learning speed but also the model performance and in addition it requires fewer data and entails multiple tasks. The concept involves
training a model that constantly learns to learn novel tasks at a fast rate from previously learned
tasks.
For the review of the related work, attention will be given to optimization-based methods and most
precisely MAML (Model Agnostic MetaLearning), because first of all, it is one of the most popular
state-of-the-art metalearning method, and second of all, this thesis focuses on creating a MAML
based method called MAML-DBL that uses an adaptive learning rate technique with dynamic
bounds that enables it to attain quick convergence at the beginning of the training process and
good generalization towards the end.
The proposed MAML variant aims to try to prevent vanishing learning rates during training and
slowing down at the end where dense features are prevalent, although further hyperparameter tunning might be necessary for some models or where sparse features may be prevalent, for improved
performance.
MAML-DBL and MAML, were tested on the most commonly used datasets for metalearning models, and based on the results of the experiments, the proposed method showed a rather competitive
performance on some of the models and even outperformed the baseline in some of the carried out
tests.
The results obtained with both MAML-DBL (in one of the dataset) and MAML, show that metalearning methods are highly recommendable solutions whenever good performance, less data and
a multi-task or versatile model are required or desired.Os modelos de aprendizagem automática dependem dos dados para aprender qualquer tarefa e, dependendo da diversidade de cada um dos elementos da tarefa e dos objetivos do projeto, a quantidade de dados pode ser elevada, o que, por sua vez, pode aumentar exponencialmente o tempo de aprendizagem e o custo computacional. Embora a maioria do treino dos modelos de aprendizagem automática hoje seja feito usando GPUs (unidade de processamento gráfico), ainda é necessária uma quantidade enorme de tempo de treino para obter o desempenho desejado. Este trabalho tem como objetivo analisar os algoritmos de aprendizagem de aprendizagem ou popularmente conhecidos como metalearning, que são métodos que não apenas tentam melhorar a velocidade de aprendizagem, mas também o desempenho do modelo e, além disso, requerem menos dados e envolvem várias tarefas. O conceito envolve o treino de um modelo que aprende constantemente a aprender tarefas novas em ritmo acelerado, a partir de tarefas aprendidas anteriormente. Para a revisão do trabalho relacionado, será dada atenção aos métodos baseados em otimização e, mais precisamente, ao MAML (Model Agnostic MetaLearning), porque em primeiro lugar é um dos métodos de metalearning mais populares e em segundo lugar, esta tese foca a criação de um método baseado em MAML, chamado MAML-DBL, que usa uma técnica de taxa de aprendizagem adaptável com limites dinâmicos que permite obter convergência rápida no início do processo de treino e boa generalização no fim. A proposta variante de MAML tem como objetivo tentar evitar o desaparecimento das taxas de aprendizagem durante o treino e a desaceleração no fim onde entradas densas são predominantes, embora possa ser necessário um ajuste adicional dos hiperparâmetros para alguns modelos ou onde entradas esparsas podem ser predominantes, para melhorar o desempenho. O MAML-DBL e o MAML foram testados nos conjuntos de dados mais comumente usados para modelos de metalearning, e com base nos resultados das experiências, o método proposto mostrou um desempenho bastante competitivo em alguns dos modelos e até superou o baseline em alguns dos testes realizados. Os resultados obtidos com o MAML e MAML-DBL (num dos conjuntos de dados) mostram que os métodos de metalearning são soluções altamente recomendáveis sempre que um bom desempenho, menos dados e um modelo versátil ou com várias tarefas são necessários ou desejados.
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Rücklé, Andreas. "Representation Learning and Learning from Limited Labeled Data for Community Question Answering." Phd thesis, 2021. https://tuprints.ulb.tu-darmstadt.de/18508/1/representation-learning-and-learning-from-limited-labeled-data-for-cqa.pdf.
Full textAbstract:
The amount of information published on the Internet is growing steadily. Accessing the vast knowledge in them more effectively is a fundamental goal of many tasks in natural language processing. In this thesis, we address this challenge from the perspective of community question answering by leveraging data from web forums and Q&A communities to find and identify answers for given questions automatically. More precisely, we are concerned with fundamental challenges that arise from this setting, broadly categorized in (1) obtaining better text representations and (2) dealing with scenarios where we have little or no labeled training data.
We first study attention mechanisms for learning representations of questions and answers to compare them efficiently and effectively. A limitation of previous approaches is that they leverage question information when learning answer representations. This procedure of dependent encoding requires us to obtain separate answer representations for each question, which is inefficient. To remedy this, we propose a self-attentive model that does not suffer from this drawback. We show that our model achieves on-par or better performance for answer selection tasks compared to other approaches while allowing us to encode questions and answers independently. Due to the importance of attention mechanisms, we present a framework to effortlessly transform answer selection models into prototypical question answering systems for the interactive inspection and side-by-side comparison of attention weights.
Besides purely monolingual approaches, we study how to transfer text representations across languages.
A popular concept to obtain universally re-usable representations is the one of sentence embeddings. Previous work either studied them only monolingually or cross-lingually for only a few individual datasets. We go beyond this by studying universal cross-lingual sentence embeddings, which are re-usable across many different classification tasks and across languages. Our training-free approach generalizes the concept of average word embeddings by concatenating different kinds of word embeddings and by computing several generalized means. Due to its simplicity, we can effortlessly extend our approach to new languages by incorporating cross-lingual word embeddings. We show that our sentence embeddings outperform more complex techniques monolingually on nine tasks and achieve the best results cross-lingually for the transfer from English to German and French.
We complement this by studying an orthogonal approach where we machine translate the input from German to English and continue monolingually. We investigate the impact of a standard neural machine translation model on the performance of models for determining question similarity in programming and operating systems forums. We highlight that translation mistakes can have a substantial performance impact, and we mitigate this by adapting our machine translation models to these specialized domains using back-translation.
In the second part, we study monolingual scenarios with (a) little labeled data, (b) only unlabeled data, (c) no target dataset information. These are critical challenges in our setting as there exist large numbers of web forums that contain only a few labeled question-answer pairs and no labeled similar questions.
One approach to generalize from small training data is to use simple models with few trainable layers. We present COALA, a shallow task-specific network architecture specialized in answer selection, containing only one trainable layer. This layer learns representations of word n-grams in questions and answers, which we compare and aggregate for scoring. Our approach improves upon a more complex compare-aggregate architecture by 4.5 percentage points on average, across six datasets with small training data. Moreover, it outperforms standard IR baselines already with 25 labeled instances.
The standard method for training models to determine question similarity requires labeled question pairs, which do not exist for many forums. Therefore, we investigate alternatives such as self-supervised training with question title-body information, and we propose duplicate question generation. By leveraging larger amounts of unlabeled data, we show that both methods can achieve substantial improvements over adversarial domain transfer and outperform supervised in-domain training on two datasets. We find that duplicate question generation transfers well to unseen domains, and that we can leverage self-supervised training to obtain suitable answer selection models based on state-of-the-art pre-trained transformers.
Finally, we argue that it can be prohibitive to train separate specialized models for each forum. It is desirable to obtain one model that generalizes well to several unseen scenarios. Towards this goal, we broadly study the zero-shot transfer capabilities of text matching models in community question answering. We train 140 models with self-supervised training signals on different forums and transfer them to nine evaluation datasets of question similarity and answer selection tasks. We find that the large majority of models generalize surprisingly well, and in six cases, all models outperform standard IR baselines. Our analyses reveal that considering a broad selection of source domains is crucial because the best zero-shot transfer performance often correlates with neither domain similarity nor training data size. We investigate different combination techniques and propose incorporating self-supervised and supervised multi-task learning with data from all source forums. Our best model for zero-shot transfer, MultiCQA, outperforms in-domain models on six datasets even though it has not seen target-domain data during training.
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"Learning about organizational learning : creating a learning history." [MIT Center for Organizational Learning, Sloan School of Management], 1995. http://hdl.handle.net/1721.1/2666.
Full text
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Hsu, Ho-Li, and 許和莉. "The Effects of Learning Styles, Web Learning, and Mobile Learning on Learning Performance." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/3zwn9g.
Full text
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TAO, TE-FANG, and 陶德芳. "Learning's Learning Motivation and Learning Satisfaction on Food and Beverage Courses in Taipei's Community Colleges." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/85206784957257317613.
Full textAbstract:
碩士世新大學
觀光學研究所(含碩專班)
94
This study addressed the topic on learning motivation and learning satisfaction of students who joined the food & beverage courses in Taipei's community colleges. Specifically, the study discussed the differences of various individual background variables between learning motivation and learning satisfaction; the study further discussed the relationships between learning motivation and learning satisfaction, as well as the relationships of learning satisfaction perspectives. The questionnaire was used in this study, and it includes a learning motivation section, a learning satisfaction section, and a background information section. The study subjects were the students in 11 community colleges of Taipei which have F&B courses. The numbers of study sample were 371, and the return rate of the questionnaire was 95.96%. Descriptive analysis, item analysis, factor analysis, t-test, one-Way ANOVA and correlation were administered. The findings of this study are: 1) there was a high agreement that learning motivation was essential for students to participate F&B courses in Taipei's community colleges; 2) students had a high learning satisfaction on F&B courses; 3) differences occurred between learning motivation and learning satisfaction based on various individual background items; 4) there was a positive correlation between learning motivation and learning satisfaction, and relationships also happened among all perspective factors of learning satisfaction. The study suggests that learning facility and equipments are needed to be improved, as well as curriculum design needs to be innovative for the F&B courses in Taipei's community colleges.
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Belo, David José da Silva Aresta. "Learning Biosignals with Deep Learning." Doctoral thesis, 2020. http://hdl.handle.net/10362/126518.
Full textAbstract:
The healthcare system, which is ubiquitously recognized as one of the most influential
system in society, is facing new challenges since the start of the decade.The myriad of
physiological data generated by individuals, namely in the healthcare system, is generating
a burden on physicians, losing effectiveness on the collection of patient data. Information
systems and, in particular, novel deep learning (DL) algorithms have been prompting a
way to take this problem.
This thesis has the aim to have an impact in biosignal research and industry by
presenting DL solutions that could empower this field. For this purpose an extensive study
of how to incorporate and implement Convolutional Neural Networks (CNN), Recursive
Neural Networks (RNN) and Fully Connected Networks in biosignal studies is discussed.
Different architecture configurations were explored for signal processing and decision
making and were implemented in three different scenarios: (1) Biosignal learning and
synthesis; (2) Electrocardiogram (ECG) biometric systems, and; (3) Electrocardiogram
(ECG) anomaly detection systems. In (1) a RNN-based architecture was able to replicate
autonomously three types of biosignals with a high degree of confidence. As for (2) three
CNN-based architectures, and a RNN-based architecture (same used in (1)) were used
for both biometric identification, reaching values above 90% for electrode-base datasets
(Fantasia, ECG-ID and MIT-BIH) and 75% for off-person dataset (CYBHi), and biometric
authentication, achieving Equal Error Rates (EER) of near 0% for Fantasia and MIT-BIH
and bellow 4% for CYBHi. As for (3) the abstraction of healthy clean the ECG signal
and detection of its deviation was made and tested in two different scenarios: presence of
noise using autoencoder and fully-connected network (reaching 99% accuracy for binary
classification and 71% for multi-class), and; arrhythmia events by including a RNN to the
previous architecture (57% accuracy and 61% sensitivity).
In sum, these systems are shown to be capable of producing novel results. The incorporation
of several AI systems into one could provide to be the next generation of
preventive medicine, as the machines have access to different physiological and anatomical
states, it could produce more informed solutions for the issues that one may face in the
future increasing the performance of autonomous preventing systems that could be used
in every-day life in remote places where the access to medicine is limited. These systems will also help the study of the signal behaviour and how they are made in real life context
as explainable AI could trigger this perception and link the inner states of a network with
the biological traits.O sistema de saúde, que é ubiquamente reconhecido como um dos sistemas mais influentes da sociedade, enfrenta novos desafios desde o ínicio da década. A miríade de dados fisiológicos gerados por indíviduos, nomeadamente no sistema de saúde, está a gerar um fardo para os médicos, perdendo a eficiência no conjunto dos dados do paciente. Os sistemas de informação e, mais espcificamente, da inovação de algoritmos de aprendizagem profunda (DL) têm sido usados na procura de uma solução para este problema. Esta tese tem o objetivo de ter um impacto na pesquisa e na indústria de biosinais, apresentando soluções de DL que poderiam melhorar esta área de investigação. Para esse fim, é discutido um extenso estudo de como incorporar e implementar redes neurais convolucionais (CNN), redes neurais recursivas (RNN) e redes totalmente conectadas para o estudo de biosinais. Diferentes arquiteturas foram exploradas para processamento e tomada de decisão de sinais e foram implementadas em três cenários diferentes: (1) Aprendizagem e síntese de biosinais; (2) sistemas biométricos com o uso de eletrocardiograma (ECG), e; (3) Sistema de detecção de anomalias no ECG. Em (1) uma arquitetura baseada na RNN foi capaz de replicar autonomamente três tipos de sinais biológicos com um alto grau de confiança. Quanto a (2) três arquiteturas baseadas em CNN e uma arquitetura baseada em RNN (a mesma usada em (1)) foram usadas para ambas as identificações, atingindo valores acima de 90 % para conjuntos de dados à base de eletrodos (Fantasia, ECG-ID e MIT -BIH) e 75 % para o conjunto de dados fora da pessoa (CYBHi) e autenticação, atingindo taxas de erro iguais (EER) de quase 0 % para Fantasia e MIT-BIH e abaixo de 4 % para CYBHi. Quanto a (3) a abstração de sinais limpos e assimptomáticos de ECG e a detecção do seu desvio foram feitas e testadas em dois cenários diferentes: na presença de ruído usando um autocodificador e uma rede totalmente conectada (atingindo 99 % de precisão na classificação binária e 71 % na multi-classe), e; eventos de arritmia incluindo um RNN na arquitetura anterior (57 % de precisão e 61 % de sensibilidade). Em suma, esses sistemas são mais uma vez demonstrados como capazes de produzir resultados inovadores. A incorporação de vários sistemas de inteligência artificial em um unico sistema pederá desencadear a próxima geração de medicina preventiva. Os algoritmos ao terem acesso a diferentes estados fisiológicos e anatómicos, podem produzir soluções mais informadas para os problemas que se possam enfrentar no futuro, aumentando o desempenho de sistemas autónomos de prevenção que poderiam ser usados na vida quotidiana, nomeadamente em locais remotos onde o acesso à medicinas é limitado. Estes sistemas também ajudarão o estudo do comportamento do sinal e como eles são feitos no contexto da vida real, pois a IA explicável pode desencadear essa percepção e vincular os estados internos de uma rede às características biológicas.
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YANG, CHANG-JUNG, and 楊昌融. "The Effects of Learning Environment, Learning Approach and Learning Style on Inquiry-based Ubiquitous Learning." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/51225790185820366671.
Full textAbstract:
碩士中華大學
資訊工程學系碩士班
103
Accompanying with the development of mobile technology, learning activities are no longer limited in classrooms or specific places. They can be performed at outdoor. Such kind of ubiquitous learning becomes more and more important. On the other hand, many researches reveal that inquiry-based learning turns students from passive knowledge receivers into active learning-activity participants, and benefits the students in promoting their critical thinking abilities. Thus Inquiry-based Ubiquitous Learning becomes an emergent research topic. However, further investigation is needed to verify the superiority of the inquiry-based ubiquitous learning over normal ubiquitous learning environment. Moreover, it is interesting to develop an inquiry-based ubiquitous learning approach to further promote students’ critical thinking. In recent years, personalized learning that considers the individual differences of students has gained much more attentions. Nevertheless, little related research is done on inquiry-based ubiquitous learning. To investigate the effects of learning environment, learning approach and learning style on inquiry-based ubiquitous learning, an inquiry-based ubiquitous learning system is proposed and developed. The 5E learning cycle is applied as the inquiry-based ubiquitous learning approach. Moreover, the Kolb’s learning style is considered to allocate suitable types of guidance problems in the inquiry-based ubiquitous learning. A serial of field experiments are conducted and the analysis results show that both learning achievement and critical thinking ability are promoted in the proposed inquiry-based learning environment. The full 5E learning cycle further promotes the critical thinking and the personalized learning strategy further promotes the learning achievement.
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Tsai, Kun-jung, and 蔡昆榮. "Veterans participate in Vocational and Technical Training, Learning Motivation, Learning Attitude, Learning Inputs And Learning Effectiveness." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/29524425900484802674.
Full textAbstract:
碩士國立雲林科技大學
資訊管理系碩士班
100
The young age of the Veterans brothers contribution to life to the country, after the war, most of them facing the dilemma of employment difficulties, Veterans Affairs Commission Executive Yuan, R.O.C. For this reason, Proud of the vocational and technical training, and look forward to once again put into the workplace through vocational and technical training, veterans can successfully find the ideal job. The empirical study aims at the Veterans for job, to accept vocational and technical training of Veterans Affairs Commission Executive Yuan, R.O.C. To investigate between learning motivation, learning attitude, learning inputs and learning effectiveness and the dimensionsthe association The total of 350 questionnaires were valid questionnaires were obtained for 314, effective response rate was 89.7%. The application of structural equation modeling empirical results show that the measurement model and structural model of this study are to have a good fit to model a total of six hypotheses are supported. This study found that learning motivation and learning attitude has a direct effect on the learning effectiveness , and joining the study into mediating role, not only has a significant effect, the overall effect (direct effect + indirect effects) are greater than the direct effect, said the study and put into the mediating effectBack. In conclusion, public and private vocational and technical training institutions to enhance students'' learning outcomes, learning inputs to strengthen the focus.
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Yu, Wei Yang, and 楊育瑋. "Effect of Quality on Learning Effectiveness, Learning Intention and Learning Satisfaction." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/33103201736800445556.
Full textAbstract:
碩士德明財經科技大學
行銷管理系
101
With the communication technology, computer and other information technology progress, it impacted and changed the dissemination of information and personal learning (Njagi 2003). Jay Cross first proposed e-learning In 1999, that set off the enthusiasm of business and school in e-learning (Internet Time Blog, 2007). In the 21st century, e-learning continued to grow in higher education institutions at an alarming rate and gradually being taken seriously (Anderson, 2003; Liao & Lu, 2008). Hoffman & Schraw (2009) pointed out that learning effectiveness based on a minimum of time spent, effort or cognitive resources to achieve established learning objectives ability. Kolfschoten et al. (2010) believes that learning effectiveness for novice learners acquire skills and knowledge to enable them perform tasks like a pro. Guglielmino (1977) pointed out that the learning intention means individuals can trigger independent continuous learning, arrange appropriate learning steps, develop learning plans and take advantage of time to complete. Hoyt (1973) also pointed out that the stronger learning intention learner that will produce satisfactory experience in learning activities. Piccoli, Ahmad & Levs (2001) pointed out, revealing understanding learning satisfaction can evaluate and predict learners in the future possibilities and opportunities in similar learning styles. Delone & McLean (1992) proposed that the information quality available to learners of e-learning has a positive correlation with the value of their learning experience. Bharati (2002) mession that ease of use, convenience of access and system reliability to assess system quality, that is indeed a positive effect on the work support satisfaction. Cronin, Brady & Hult (2000) pointed out that the first line of customer service in the service encounter plays an important role to influence customer perceptions. Sale staffs’ expertise and attitude help customers get good service experience in services (Baker et al, 2002). Therefore, this study suggests information quality, system quality, and service quality in e-learning center will affect learning effectiveness, learning intention and learning satisfaction. The study explored Taiwan Knowledge Bank’s (the biggest e-learning service center in Taiwan) e-learning course students as a sample, developed scale, verified information quality, system quality and service quality on learning effectiveness, learning intention and learning satisfaction that are significant. These results can be used as reference in the promotion of e-learning as other business or education institutional.