Dissertations / Theses on the topic 'Learning preferences'
To see the other types of publications on this topic, follow the link: Learning preferences.
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 dissertations / theses for your research on the topic 'Learning preferences.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse dissertations / theses on a wide variety of disciplines and organise your bibliography correctly.
1
Paciorek, Albertyna. "Implicit learning of semantic preferences." Thesis, University of Cambridge, 2013. https://www.repository.cam.ac.uk/handle/1810/244632.
Full textAbstract:
The research presented in this PhD dissertation examines the phenomenon of semantic implicit learning, using semantic preferences of novel verbs as a test case. Implicit learning refers to the phenomenon of learning without intending to learn or awareness that one is learning at all. Semantic preference (or selectional preference – as preferred in computational linguistics) is the tendency of a word to co-occur with words sharing similar semantic features. For example, ‘drink’ is typically followed by nouns denoting LIQUID, and the verb ‘chase’ is typically followed by ANIMATE nouns. The material presented here spans across disciplines. It examines a well-documented psychological phenomenon - implicit learning – and applies it in the context of language acquisition, thereby providing insights into both fields. The organisation of this dissertation groups its experiments by their methodology. Chapter 1 provides an overview of the current psychological and linguistic literature. Chapter 2 includes a pen-and-paper study carried out in a classroom environment on Polish learners of English, where awareness is assessed by subjective measures taken at each test question as well as a post-experiment questionnaire. Chapter 3 includes a collection of 5 computer-based experiments based on a false-memory paradigm. After exposure to sentential contexts containing novel verbs, participants are shown to endorse more previously unseen verb-noun pairings that follow the correct semantic preference patterns to the pairings that violate it. The result holds even when participants do not reveal any explicit knowledge of the patterns in the final debriefing. Awareness is additionally assessed using indirect measures examining correlations of confidence judgements with performance. Chapter 4 examines whether implicit learning of novel verb semantic preference patterns is automatic. To this end, a reaction time procedure is developed based on two consecutive decisions (“double decision priming”). The method reveals that semantic implicit learning, at least in the described cases, exerts its influence with a delay, in post-processing. Chapter 5 comprises research done in collaboration with Dr Nitin Williams, University of Reading. It documents an attempt at finding neural indices of implicit learning using a novel single-trial analysis of an electroencephalographic (EEG) signal, based on empirical mode decomposition (EMD) denoising. Chapter 6 presents a final discussion and indications for future research. The main contribution of this dissertation to the general field of implicit learning research consists in its challenging the predominant view that implicit learning mainly relies on similarity of forms presented in training and test. The experiments presented here require participants to make generalisations at a higher, semantic level, which is largely independent of perceptual form. The contribution of this work to the field of Second Language Acquisition consists of empirical support for the currently popular but seldom tested assumptions held by advocates of communicative approaches to language teaching, namely that certain aspects of linguistic knowledge can develop without explicit instruction and explanation. At the same time, it challenges any view assuming that vocabulary learning necessarily relies on explicit mediation. The experiments collected here demonstrate that at least word usage in context can be learnt implicitly. A further contribution of this dissertation is its demonstration that the native language may play a key role in determining what is learnt in such situations. A deeper understanding of the phenomenon of semantic implicit learning promises to shed light on the nature of word and grammar learning in general, which is crucial for an account of the processes involved in the development of a second language mental lexicon.
2
Miller, Robert W. "Learning Preferences of Commercial Fishermen." Scholar Commons, 2015. https://scholarcommons.usf.edu/etd/5532.
Full textAbstract:
This study surveyed 435 commercial fishermen across eight coastal regions of the United States where commercial fishing takes place. The regions of the study included: Northeast Atlantic, Mid-Atlantic, Southeast Atlantic, Gulf of Mexico, Great Lakes, Southern Pacific, Pacific Northwest, and Alaska. Participants were asked to complete the Commercial Fishing Worker Survey (CFWS), which is a survey instrument consisting of an approved, adapted version of the Index of Learning Styles instrument (ILS) combined with a demographic section which included questions designed to obtain data regarding the four variables of the study: age, education level, captain's license status, and method of fishing. The instrument was designed to provide data sufficient to answer the three research questions of the study.
1. What are the learning preferences of commercial fishermen?
2. Are there differences in the learning preferences of commercial fishermen across the eight geographical regions of the study?
3. Are there differences in the learning preferences of commercial fishermen based on the demographical variables?
The commercial fishermen showed obvious inclinations toward specific learning preference dimensions. The fishermen indicated that they preferred the active (rather than the reflective) dimension, the sensing (rather than the intuitive) dimension, the visual (rather than the verbal) dimension, and the sequential (rather than the global) dimension. The participant's responses were similar across the eight regions. Where differences existed, they were related to the sensing/intuitive and sequential/global learning preferences dimensions. Region 8 Alaska appeared to have stronger sensing and sequential learning preferences than the other regions.
Age did not appear to influence the learning preferences of the fishermen. The majority of the respondents indicated they were high school graduates. However, education did not appear to affect the learning preferences of the fishermen. Captain's license status had no influence on the learning preferences of the commercial fishermen, since the majority of the respondents did not possess a captain's license.
Respondents indicated that the largest percentage of commercial fishing used net fishing methods as their primary means of fishing. For the majority of the commercial fishermen, method of fishing did not appear to influence the learning preferences of commercial fishermen. However, net and trap fishermen exhibited significant differences related to the sensing/intuitive and sequential/global learning preference dimensions and reported more preference for the sequential/global learning preference dimensions then fishermen using other methods of fishing. Implications and recommendations for further study are enumerated in the last chapter.
3
Qomariyah, Nunung Nurul. "Pairwise preferences learning for recommender systems." Thesis, University of York, 2018. http://etheses.whiterose.ac.uk/20365/.
Full textAbstract:
Preference learning (PL) plays an important role in machine learning research and practice. PL works with an ordinal dataset, used frequently in areas such as behavioural science, medical science, education, psychology and social science. The aim of PL is to predict the preference for a new set of items based on the training data. In the application area of Recommender Systems (RSs), PL is used as an important element to produce good recommendations. Many ideas have been developed to build better recommendation techniques. One of the challenges in RSs is how to develop systems that are proactive and unobtrusive. To address this problem, we have studied the use of pairwise comparisons in preference elicitation as a very simple way of expressing preferences. Research in PL has also discovered this kind of representation and considers it to be learning from binary relations. There are three contributions in this thesis: The first and the most significant contribution is a new approach based on Inductive Logic Programming (ILP) in Description Logics (DL) representation to learn the relation of order. The second contribution is a strategy based on Active Learning (AL) to support the inference process and make choices more informative for learning purposes. A third contribution is a recommender system algorithm based on the ILP in DL approach, implemented in a real-world recommender system with a large used-car dataset. The proposed approach has been evaluated by using both offline and online experiments. The offline experiments were performed using two publicly available preference datasets, while the online experiment was conducted using 24 participants to evaluate the system. In the offline experiments, the overall accuracy of our proposed approach outperformed the other 3 baseline algorithms, SVM, Decision Tree and Aleph. In the online experiment, the user study also showed some satisfactory results in which our proposed pairwise comparisons interface in a recommender system beat a common standard list interface.
4
Sobrie, Olivier. "Learning preferences with multiple-criteria models." Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLC057/document.
Full textAbstract:
L’aide multicritère à la décision (AMCD) vise à faciliter et améliorer la qualité du processus de prise de décision. Les méthodes d’AMCD permettent de traiter les problèmes de choix, rangement et classification. Ces méthodes impliquent généralement la construction d’un modèle. Déterminer les valeurs des paramètres de ces modèles n’est pas aisé. Les méthodes d’apprentissage indirectes permettent de simplifier cette tâche en apprenant les paramètres du modèle de décision à partir de jugements émis par un décideur tels que “l’alternative a est préférée à l’alternative b” ou “l’alternative a doit être classifiée dans la meilleure catégorie”. Les informations données par le décideur sont généralement parcimonieuses. Le modèle d’AMCD est appris au cours d’un processus interactif entre le décideur et l’analyste. L’analyste aide le décideur à formuler et revoir ses jugements si nécessaire. Le processus s’arrête une fois qu’un modèle satisfaisant les préférences du décideur a été trouvé. Le “preference learning” (PL) est un sous domaine du “machine learning” qui s’intéresse à l’apprentissage des préférences. Les algorithmes de ce domaine sont capables de traiter de grands jeux de données et sont validés au moyen de jeux de données artificiels et réels. Les jeux de données traités en PL sont généralement collectés de différentes sources et sont entachés de bruit.Contrairement à l’AMCD, il existe peu ou pas d’interaction avec l’utilisateur en PL. Le jeu de données fourni en entrée à l’algorithme est considéré comme un échantillon éventuellement bruité d’une “réalité” ou “vérité de terrain”. Les algorithmes utilisés dans ce domaine ont des propriétés statistiques fortes leur permettant de s’affranchir du bruit dans ces jeux de données. Dans cette thèse, nous développons des algorithmes d’apprentissage permettant d’apprendre lesparamètres de modèles d’AMCD. Plus précisément, nous développons une métaheuristique afin d’apprendre les paramètres d’un modèle appelé MR-Sort (“majority rule sorting”). Cette métaheuristique est testée sur des jeux de donnéesartificiels et réels utilisés dans le domaine du PL. Nous utilisons cet algorithme afin de traiter un problème concret dans le domaine médical. Ensuite nous modifions la métaheuristique afin d’apprendre les paramètres d’un modèle plus expressif appelé NCS (“non-compensatory sorting”). Finalement, nous développons un nouveau type de règle de veto pour les modèles MR-Sort et NCS qui permet de prendre les coalitions de critères en compte. La dernière partie de la thèse introduit les méthodes d’optimisation semi-définie positive (SDP) dans le contexte de l’aide multicritère à la décision. Précisément, nous utilisons l’optimisation SDP afin d’apprendre les paramètres d’un modèle de fonction de valeur additiveMultiple-criteria decision analysis (MCDA) aims at providing support in order to make a decision. MCDA methods allow to handle choice, ranking and sorting problems. These methods usually involve the elicitation of models. Eliciting the parameters of these models is not trivial. Indirect elicitation methods simplify this task by learning the parameters of the decision model from preference statements issued by the decision maker (DM) such as “alternative a is preferred to alternative b” or “alternative a should be classified in the best category”. The information provided by the decision maker are usually parsimonious. The MCDA model is learned through an interactive process between the DM and the decision analyst. The analyst helps the DM to modify and revise his/her statements if needed. The process ends once a model satisfying the preferences of the DM is found. Preference learning (PL) is a subfield of machine learning which focuses on the elicitation of preferences. Algorithms in this subfield are able to deal with large data sets and are validated withartificial and real data sets. Data sets used in PL are usually collected from different sources and aresubject to noise. Unlike in MCDA, there is little or no interaction with the user in PL. The input data set is considered as a noisy sample of a “ground truth”. Algorithms used in this field have strong statistical properties that allow them to filter noise in the data sets.In this thesis, we develop learning algorithms to infer the parameters of MCDA models. Precisely, we develop a metaheuristic designed for learning the parameters of a MCDA sorting model called majority rule sorting (MR-Sort) model. This metaheuristic is assessed with artificial and real data sets issued from the PL field. We use the algorithm to deal with a real application in the medical domain. Then we modify the metaheuristic to learn the parameters of a more expressive model called the non-compensatory sorting (NCS) model. After that, we develop a new type of veto rule for MR-Sort and NCS models which allows to take criteria coalitions into account. The last part of the thesis introduces semidefinite programming (SDP) in the context of multiple-criteria decision analysis. We use SDP to learn the parameters of an additive value function model
5
Zhu, Ying. "PREFERENCES: OPTIMIZATION, IMPORTANCE LEARNING AND STRATEGIC BEHAVIORS." UKnowledge, 2016. http://uknowledge.uky.edu/cs_etds/46.
Full textAbstract:
Preferences are fundamental to decision making and play an important role in artificial intelligence. Our research focuses on three group of problems based on the preference formalism Answer Set Optimization (ASO): preference aggregation problems such as computing optimal (near optimal) solutions, strategic behaviors in preference representation, and learning ranks (weights) for preferences.
In the first group of problems, of interest are optimal outcomes, that is, outcomes that are optimal with respect to the preorder defined by the preference rules. In this work, we consider computational problems concerning optimal outcomes. We propose, implement and study methods to compute an optimal outcome; to compute another optimal outcome once the first one is found; to compute an optimal outcome that is similar to (or, dissimilar from) a given candidate outcome; and to compute a set of optimal answer sets each significantly different from the others. For the decision version of several of these problems we establish their computational complexity.
For the second topic, the strategic behaviors such as manipulation and bribery have received much attention from the social choice community. We study these concepts for preference formalisms that identify a set of optimal outcomes rather than a single winning outcome, the case common to social choice. Such preference formalisms are of interest in the context of combinatorial domains, where preference representations are only approximations to true preferences, and seeking a single optimal outcome runs a risk of missing the one which is optimal with respect to the actual preferences. In this work, we assume that preferences may be ranked (differ in importance), and we use the Pareto principle adjusted to the case of ranked preferences as the preference aggregation rule. For two important classes of preferences, representing the extreme ends of the spectrum, we provide characterizations of situations when manipulation and bribery is possible, and establish the complexity of the problem to decide that.
Finally, we study the problem of learning the importance of individual preferences in preference profiles aggregated by the ranked Pareto rule or positional scoring rules. We provide a polynomial-time algorithm that finds a ranking of preferences such that the ranked profile correctly decided all the examples, whenever such a ranking exists. We also show that the problem to learn a ranking maximizing the number of correctly decided examples is NP-hard. We obtain similar results for the case of weighted profiles.
6
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/.
Full textAbstract:
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.
7
Foley, Nancy E. "Learning style preferences of undergraduate students with and without learning disabilities /." free to MU campus, to others for purchase, 1997. http://wwwlib.umi.com/cr/mo/fullcit?p9842527.
Full text
8
Gallacher, Sarah. "Learning preferences for personalisation in a pervasive environment." Thesis, Heriot-Watt University, 2011. http://hdl.handle.net/10399/2476.
Full textAbstract:
With ever increasing accessibility to technological devices, services and applications there is also an increasing burden on the end user to manage and configure such resources. This burden will continue to increase as the vision of pervasive environments, with ubiquitous access to a plethora of resources, continues to become a reality. It is key that appropriate mechanisms to relieve the user of such burdens are developed and provided. These mechanisms include personalisation systems that can adapt resources on behalf of the user in an appropriate way based on the user's current context and goals. The key knowledge base of many personalisation systems is the set of user preferences that indicate what adaptations should be performed under which contextual situations. This thesis investigates the challenges of developing a system that can learn such preferences by monitoring user behaviour within a pervasive environment. Based on the findings of related works and experience from EU project research, several key design requirements for such a system are identified. These requirements are used to drive the design of a system that can learn accurate and up to date preferences for personalisation in a pervasive environment. A standalone prototype of the preference learning system has been developed. In addition the preference learning system has been integrated into a pervasive platform developed through an EU research project. The preference learning system is fully evaluated in terms of its machine learning performance and also its utility in a pervasive environment with real end users.
9
Park, Kyounga. "Learning user preferences for intelligent adaptive in-vehicle navigation." Thesis, Imperial College London, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.506034.
Full text
10
Bergling, Oscar. "Evaluation of machine learning methods to predict payment preferences." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-264504.
Full textAbstract:
The last couple of years machine learning has seen a renaissance, with Artificial Neural Networks in particular rising to prominence. The technology is being adopted by more and more businesses, with varying degrees of success. Klarna has already been experimenting with machine learning to predict payment preferences, however currently a hybrid between ad-hoc rules and a random forest model is being used in production. This report aims to find out if a pure machine learning algorithm can outperform a hybrid system for this purpose. To achieve this, four methods were tested; Random Forest, Artificial Neural Net- work, Support Vector Machine and Logistic Regression model. Three of these models outperformed the model in production. Best of these were the Artificial Neural Network which, with a cutoff threshold designed to achieve the same precision, achieved 10 percentage points higher recall. By combining the probabilities produced by an Artificial Neural Network and a Random Forest, even better results could be achieved. That method achieved 11.5 percentage points higher recall than production results with the same precision. It could be shown that the two methods had different strengths and were good at classifying different examples.Explosionen av maskininlärning, och Artificiella Neurala Nätverk i synnerhet, har resulterat i att tekniken appliceras på allt fler användningsområden. Klarna har redan experimenterat med maskininlärning för att förutsäga betalmetoder, men för närvarande används en hybrid av regler och en Random-Forest modell. Denna rapport ämnar att utreda om en ren maskininlärningsmetod kan överträffa den nuvarande hybridmetoden. För att göra detta testades fyra olika metoder, Random Forest, Neurala Nätverk, Support Vector Machines och Logistic Regression. Det visade sig att tre av dessa presterade bättre än modellen i produktion. Bäst av alla metoder var Neurala Nätverk som var 10 procentenheter bättre än modellen i produktion i recall, med samma precision. Genom att kombinera sannolikheterna från en Random Forest samt ett Neuralt Nätverk kunde ännu bättre resultat uppnås, 11.5 procentenheter bättre i recall än modellen i produktion till samma precision.
11
Her, Ming Hang Yun. "An investigation of students' media preferences in learning mathematical concepts." unrestricted, 2006. http://etd.gsu.edu/theses/available/etd-05032006-133322/.
Full textAbstract:
Thesis (Ph. D.)--Georgia State University, 2006.Title from title screen. Christine D. Thomas, committee charir; Nikita D. Patterson, Clara Nosegbe Okoka, Janice S. Scott, Pier A. Junor-Clarke, committee members. Electronic text (176 p. : forms, graphs (some col.)) : digital, PDF file. Description based on contents viewed May 1, 2007. Includes bibliographical references (p. 134-143).
12
Solis, John D. "The relationship between preservice teachers' social learning style preferences and learning activity role choices." Laramie, Wyo. : University of Wyoming, 2006. http://proquest.umi.com/pqdweb?did=1225152311&sid=1&Fmt=2&clientId=18949&RQT=309&VName=PQD.
Full text
13
Hutson, Brad. "Teaching the high school educator| Understanding their learning preferences in an adult-learning environment." Thesis, Trevecca Nazarene University, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10140131.
Full textAbstract:
This mixed-model study utilized the qualitative and quantitative data from high school teachers of one middle Tennessee school district and high school teachers of the Tennessee High School Speech and Drama League to determine if differences existed amongst the learning preferences of high school teachers in adult learning environments. All participants completed the Canfield Learning Styles Inventory to provide quantitative data. Members of an executive board completed a focus group questionnaire to provide qualitative data for the study. The study led to a recommendation that developers of professional development and school officials consider learning preferences because significant differences existed amongst the participants. Accounting for these differences could lead to more effective implementation of professional development content.
14
Kippin, Tod Edward. "Olfactory-conditioned ejaculatory preference in the male rat, implications for the role of learning in sexual partner preferences." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp03/NQ47703.pdf.
Full text
15
Kutay, Huban. "A comparative study about learning styles preferences of two cultures." Columbus, Ohio : Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1143049622.
Full text
16
Gunes, Cevriye. "Learning Style Preferences Of Preparatory School Students At Gazi University." Master's thesis, METU, 2001. http://etd.lib.metu.edu.tr/upload/12605465/index.pdf.
Full textAbstract:
The purpose of this study was to determine the learning styles of preparatory school students from Gazi University and examine the relationship between students&rsquolearning style preferences (LSP) and faculty students will study in, gender, proficiency level of English and achievement scores on listening, reading, grammar, and writing in the English Course. The instrument, Index of Learning Styles (ILS), was administered to 367 randomly selected students. As for the data analysis, descriptive statistics portrayed the frequencies, percentages, means and standard deviations, the t test was conducted to see whether students&rsquo
achievement scores differ according to their LSPs and the Crosstabs procedure was conducted to investigate whether the LSPs of the students at Gazi University differ according to faculty they will study in, gender and level of proficiency. The results indicated that there was no significant difference between students&rsquo
LSPs and faculty, gender, level and achievement scores.
17
Peters, Murray N. "Learning preferences of gifted Chinese-Canadian and gifted Caucasian students." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ37610.pdf.
Full text
18
Brochu, Eric. "Interactive Bayesian optimization : learning user preferences for graphics and animation." Thesis, University of British Columbia, 2010. http://hdl.handle.net/2429/30519.
Full textAbstract:
Bayesian optimization with Gaussian processes has become increasingly popular in the machine learning community. It is efficient and can be used when very little is known about the objective function, making it useful for optimizing expensive black box functions. We examine the case of using Bayesian optimization when the objective function requires feedback from a human. We call this class of problems \emph{interactive} Bayesian optimization. Here, we assume a parameterized model, and a user whose task is to find an acceptable set of parameters according to some perceptual value function that cannot easily be articulated. This requires special attention to the qualities that make this a unique problem, and so, we introduce three novel extensions: the application of Bayesian optimization to "preference galleries", where human feedback is in the form of preferences over a set of instances; a particle-filter method for learning the distribution of model hyperparameters over heterogeneous users and tasks; and a bandit-based method of using a portfolio of utility functions to select sample points. Using a variety of test functions, we validate our extensions empirically on both low- and high-dimensional objective functions. We also present graphics and animation applications that use interactive Bayesian optimization techniques to help artists find parameters on difficult problems. We show that even with minimal domain knowledge, an interface using interactive Bayesian optimization is much more efficient and effective than traditional "parameter twiddling" techniques on the same problem.
19
Srivastava, Mukesh. "Understanding relationships between elearning website feature preferences and learning styles." Thesis, University of Surrey, 2007. http://epubs.surrey.ac.uk/924/.
Full textAbstract:
The primary purpose ofthis research was to investigate the relationship between perceived learning styles ofthe eLearners and their preference of eLearning website features. The secondary purposes ofthis study was to research various models oflearning styles for examining learning styles and eLearning website Systems for studying eLearning website feature preferences ofthe eLearners. A broad research question was undertaken: What impact (if any) does an eLearner's learning style have on their preferences for specific features in an eLearning website system? To follow an exploratory line of investigation three research questions were used to examine the broad question: 1) How can an eLearning website system be meaningfully selected to study eLearning website features preference? 2) How can an eLearner's learning style be meaningfully categorised? 3) How do learning styles impact the eLearner's preference of eLearning website features? ·Unlike Research Question 1 and 2 that· were examined by mainly literature review, Research Question 3 was studied using a full-fledged empirical cycle involving setting up hypotheses, conducting a survey and analysing data using statistical methods.
20
Cavendish, Margaret. "Infant visual preferences and their contribution to learning and memory." Thesis, University of Reading, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.398290.
Full text
21
Lui, Catherine Johnston. "The Perceptual Learning Style Preferences of Hispanic Students in Higher Education." BYU ScholarsArchive, 2017. https://scholarsarchive.byu.edu/etd/6712.
Full textAbstract:
This paper addresses the question of whether higher education Hispanic students of different nationalities have different perceptual learning style preferences. Independent samples t-tests findings suggest the country of origin of a Hispanic student's parents has a statistically significant relationship (n=165, p<0.0073) with student's learning style preferences. ANOVA results also identified a statistically significant relationship between SES and group learning style (p<0.004,) and between visual learning style and two factors: age (p<0.011) and family education (p<0.033).
22
Carnwell, Roselyn June. "Approaches to study in part-time distance education in higher education : a case study of community nurses." Thesis, University of Wolverhampton, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.263330.
Full text
23
Schols, Maurice. "Continuing technology professional development : a technology learning preferences instrument to support teacher educators' workplace learning." Thesis, University of Roehampton, 2016. https://pure.roehampton.ac.uk/portal/en/studentthesis/continuing-technology-professional-development(07a1731f-420f-42ed-af16-7956aeea8eda).html.
Full textAbstract:
The knowledge-based economy, advances in information and communication technologies and new pedagogical perspectives all influence the need to improve competencies in the 21st century. Innovative educational ideas and concepts have transformed the roles of teacher educators and their students. Adequate technology training is therefore a prerequisite for the teacher educator to develop prospective teachers who can use new technologies to support and improve their students’ achievement gains. However, many of these efforts fail since they are mostly based on a formal, institutional delivery of instrumental knowledge and skills. Adequate technology training is a major factor that can help to promote the uptake of emerging technologies into the curriculum, which in turn benefits students (Yoon et al, 2007; Collins & Halverson, 2009; Earley & Porritt, 2014). This research seeks to add to current knowledge about teacher educators’ technology professionalisation and to provide an instrument for the purpose of mapping teacher educators’ technology learning preferences in the workplace. The technology learning preferences instrument (TLP-instrument) designed, implemented and evaluated in this research is intended to create a link between teacher-educators’ technology learning needs in the workplace and the way in which professional development programmes should be tailored to meet teacher educators’ evolving learning needs. The investigation employs a design-based research approach which is cyclical and appropriate for addressing complex problems in educational practice for which no clear guidelines for solutions are available. To collect and analyse the data, a mixed methods approach was used. The rationale for mixing both types of research is that qualitative and quantitative methods complement each other (Creswell & Plano-Clark, 2011). Findings in this dissertation and in follow-up research are intended to lead to more effective technology professionalisation programmes through suggestions for better design and development based on teacher educators’ learning needs.
24
Salomonsson, Cecilia. "Food preferences in captive meerkats (Suricata suricatta)." Thesis, Linköpings universitet, Institutionen för fysik, kemi och biologi, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-70120.
Full textAbstract:
By using a three-choice preference test I tested food preferences in eight meerkats (Sutricata suricatta) for nine different food items. The meerkats were presented with all possible combinations of 9 food items, in total 84 combinations. The meerkats displayed the following rank order of food preference: cricket > zophoba lava > egg white > banana = tomato > orange > apple > cucumber > carrot. A correlation test between the food preference and nutritional content showed that the preference is significantly correlated with protein content. There is also a significant correlation between ash content and the food preference. There were no correlations with water, fat or vitamins and minerals. This suggests that, as in the wild, the captive meerkats at Kolmården wild life park seek food with high protein content. Ash has a high significant correlation with protein, which may explain the correlation between ash and the food preference. A comparison between the individual’s food preferences showed that the oldest individuals had the highest number of correlations with their food preferences to other individual’s food preference. This suggests an observational learning capability from older to younger individuals, which has also been reported in wild meerkat
25
Mike, Kristen Lynne. "School Psychologists' Preferences on Response to Intervention." Diss., The University of Arizona, 2010. http://hdl.handle.net/10150/194065.
Full textAbstract:
As a result of the reauthorization of the Individuals with Disabilities Education Act (IDEA, 2004), Response to Intervention (RTI) became a legal and acceptable basis for determining special education eligibility. While there may be evidence that RTI has had positive effects on the prereferral process for special education in some schools, there still remains controversy in the field of school psychology about many aspects of RTI, in particular the use of RTI in the identification process for children with learning disabilities. The purpose of current questionnaire study was (a) to determine school psychologists' preferences on the use of RTI in both the prereferral and the identification process of students with learning disabilities, (b) to investigate the implementation process in school systems from school psychologists' perspectives, and (c) to examine the role of the school psychologist in RTI implementation efforts and RTI activities.Data were collected from 41 members of the National Association of School Psychologists (NASP). Each participant completed a survey, which related to the above purposes, and responded to items using a 5-point Likert scale. Results indicated that sampled school psychologists generally responded favorably to RTI as a prereferral method, but varied on their level of agreement on using RTI for diagnostic purposes. Most respondents agreed that RTI should not be the sole criteria for determining a learning disability and that a comprehensive evaluation should take place including standardized cognitive and academic testing. Identified benefits to implementing RTI were: interventions for struggling students occur earlier, improved instruction for all students, greater collaboration between general and special education, and improved method of identifying at risk groups/individuals. Identified challenges to implementing RTI were: need for professional development, lack of teacher preparation, lack of support staff to implement interventions, and intervention fidelity. A majority of respondents agreed that the school psychologist's role should include various RTI activities and in particular RTI activities related to data interpretation, consultation, supervising, and training.
26
Nield, Kevin. "A case study of the learning preferences of Chinese distance learners." Thesis, Sheffield Hallam University, 2004. http://shura.shu.ac.uk/20121/.
Full textAbstract:
This study is primarily concerned with two overarching "how" questions. The first question is "how are the teaching, learning and assessment preferences of Chinese Hong Kong learners met by the distance learning courses offered?" Specifically it concerns the feasibility of transferring a western course to the Hong Kong market. The second question interrogates the usefulness of models that measure learning style in categorising learners and making recommendations from them regarding their learning preferences. To enable these questions to be answered six research propositions concerning the learning preferences of Chinese learners were identified. A comprehensive literature review was undertaken. This was founded upon two theoretical building blocks of national culture and learning style theory. This exploration of cultural theory is extended to an examination of differences in Chinese culture that may impact upon educational preferences. To investigate the second building block of learning style theory, certain theories of learning style that attempt to measure learning style are critically examined in depth. To bring cultural differences and learning style theory together a capstone is used. This capstone is six learning preferences of the Chinese learner. These preferences are founded upon application of cultural and learning style theory and other, mainly western perceptions, of the Chinese learner. This section of the literature provides a bridge between cultural and learning style theory and the research. The research questions are answered by using a single case study. The case study focuses upon the teaching, learning and assessment preferences of twenty-five Hong Kong Chinese students studying for two UK Higher Education awards by distance learning. The study makes three contributions to knowledge. First, the study concludes that in transferring the courses from the British culture to the Hong Kong Chinese culture that the study materials in a western context may be appropriate but the method of delivery may not. Second, applying measurements of learning style to national groups is challenged as inappropriate methods of teaching and learning may be advocated and appropriate methods may be ignored. Finally, of the theoretical propositions, only two are supported. These are that this group of learners dislikes classroom discussion and that the role of the teacher/lecturer is didactic.
27
Sawada, Kazuya. "VOCABULARY ACQUISITION THROUGH LISTENING AND ITS RELATION TO LEARNING CHANNEL PREFERENCES." Diss., Temple University Libraries, 2009. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/52572.
Full textAbstract:
CITE/Language ArtsEd.D.
The purposes of this study were to investigate the degree to which Japanese high school students acquire vocabulary from listening, what kind of explanation better promotes vocabulary acquisition, whether vocabulary acquisition through listening varies according to the participants' learning channel preferences, and what factors best predict vocabulary that is acquired through listening. The participants, 116 second-year Japanese high school students, were taught 45 vocabulary items embedded in nine listening passages. In the control condition, no vocabulary explanation was given. In the first treatment condition, the students were provided with a spoken Japanese translation for each target word. In the second treatment condition, the students were provided with a spoken English definition of each target word. Approximately 30 minutes after each listening session, an Immediate Recognition Posttest and a Multiple-choice Posttest were administered. Exactly the same tests were administered as Delayed Recognition and Multiple-choice Posttests 2 weeks after the instruction. Repeated-measures ANOVAs using the listening conditions as the independent variables and the results from the two tests as dependent variables showed that there was a statistically significant difference between the three conditions on the Immediate and Delayed Recognition Posttests. The L1 translation condition was more effective than the L2 definition condition, and the control condition was the least effective. However, for the Immediate and Delayed Multiple-choice Posttests, there was no statistically significant difference between the L1 and L2 conditions. Two three-way ANOVAs using the learning channel subgroups, time, and the listening conditions as independent variables, and the results from the Immediate and Delayed Recognition and Multiple-choice Posttests as dependent variables showed that there were no statistically significant differences among the three learning channel subgroups. However, the auditory learners retained more in the L2 definition condition than the visual and haptic learning channel groups. The final major analysis, a hierarchical multiple regression, indicated that passage comprehension, vocabulary size, and grammatical competence were statistically significant predictors of vocabulary acquisition through listening.
Temple University--Theses
28
Ghandahari, Daniel. "Learning User Preferences for Recommending Radio Channels in a Music Service." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-393278.
Full textAbstract:
Playing music is considered essential for some businesses. When entering a clothing store, a café or a gym, there is most often some music playing in the background. The employees do not have the ability to select music optimally to maximize profit. Their expertise lies within their main duties of the workplace and they should spend most of their time focusing on those duties for an efficient workflow. The problem that arises is how businesses can play suitable music with minimal effort in music selection. To solve this, a recommender system is built with the real-time machine learning algorithm, DR-TRON. It is a lightweight and dynamic algorithm that instantly improves on user interaction. By using the dynamic nature of the algorithm, a more trivial model was initially built to test for some valuable output. Afterward, a more complex model was built where there was more consideration in music channel properties. The second model recommends suitable music channels and reduces the effort of selection.
29
Hoffner, Elizabeth Ann. "A study of the perceptual learning style preferences of Japanese students." PDXScholar, 1991. https://pdxscholar.library.pdx.edu/open_access_etds/4269.
Full textAbstract:
This study was based on a study by Joy Reid (1987) on the perceptual learning style preferences of English as a Second Language (ESL) students. The purpose of this study was to identify the perceptual learning style preferences of three groups of students: Japanese students studying in the US, Japanese students studying in Japan, and American students studying in the US. The perceptual styles studied were visual, auditory, kinesthetic, and tactile, with the additional styles of group and individual learning also being studied. The learning style preferences were identified so as to determine the relationship between style and the variables of native language, length of stay in the US, and major field of study.
30
Sottilare, Robert. "MODELING THE INFLUENCES OF PERSONALITY PREFERENCES ON THE SELECTION OF INSTRUCTIONAL STRATEGIES ININTELLIGENT TUTORING SYSTEMS." Master's thesis, University of Central Florida, 2006. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/3790.
Full textAbstract:
This thesis hypothesizes that a method for selecting instructional strategies (specifically media) based in part on a relationship between learning style preference and personality preference provides more relevant and understandable feedback to students and thereby higher learning effectiveness. This research investigates whether personality preferences are valid predictors of learning style preferences. Since learning style preferences are a key consideration in instructional strategies and instructional strategies are a key consideration in learning effectiveness, this thesis contributes to a greater understanding of the relationship between personality preferences and effective learning in intelligent tutoring systems (ITS). This research attempts to contribute to the goal of a "truly adaptive ITS" by first examining relationships between personality preferences and learning style preferences; and then by modeling the influences of personality on learning strategies to optimize feedback for each student. This thesis explores the general question "what can personality preferences contribute to learning in intelligent tutoring systems?" So, why is it important to evaluate the relationship between personality preferences and learning strategies in ITS? "While one-on-one human tutoring is still superior to ITS in general, this approach is idiosyncratic and not feasible to deliver to [any large population] in any cost-effective manner." (Loftin, 2004). Given the need for ITS in large, distributed populations (i.e. the United States Army), it is important to explore methods of increasing ITS performance and adaptability. Findings of this research include that the null hypothesis that "there is no dependency between personality preference variables and learning style preference variables" was partly rejected. Highly significant correlations between the personality preferences, openness and extraversion, were established for both the active-reflective and sensing-intuitive learning style preferences. Discussion of other relationships is provided.M.S.
Other
Engineering and Computer Science
Modeling and Simulation
31
Arter, Roland K. "The Assent to Learn: An Exploration of Engineering Technology Students' Attitudes and Beliefs Towards Learning in a Classroom Environment." University of Akron / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=akron1428160883.
Full text
32
Fong, Kit Ieng. "An examination of student learning style preferences at the University of Macau." Thesis, University of Macau, 2009. http://umaclib3.umac.mo/record=b2456350.
Full text
33
Su, Bude. "Experiences of and preferences for interactive instructional activities in online learning environment." [Bloomington, Ind.] : Indiana University, 2006. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3215221.
Full textAbstract:
Thesis (Ph.D.)--Indiana University, Instructional Systems Technology, Dept. of School of Education, 2006.Source: Dissertation Abstracts International, Volume: 67-04, Section: A, page: 1304. Adviser: Curtis J. Bonk. "Title from dissertation home page (viewed June 19, 2007)."
34
Cho, Jung-Shih. "Investigating Taiwanese university learners' readiness for online language learning : preferences and perceptions." Thesis, Queen's University Belfast, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.600641.
Full textAbstract:
The goal of this study was to investigate Taiwanese university learners' readiness for online language learning, as well as their preferences and perceptions for this type of learning. This study undertaken was both quantitative and qualitative in nature, and was underpinned by a mixed methods philosophy. The data collection methods used for the purpose of the study included: semi-structured focus group interviews and a questionnaire survey. The findings were descriptively categorized and analysed according to emergent themes. These findings were then interpreted and compared to the literature related to this study. The overall objectives of this dissertation were to gain a general picture of the readiness that Taiwanese university learners have for online language learning, as well as a deeper understanding of the interrelationship between their preferences and perceptions, and how this affected their online learning readiness. There are nine universities in central Taiwan which provide the online language courses that met the requirements for this study; however, only three of them had agreed to participate in this study. Therefore, this study underscored the need to conduct research of a similar nature, with an increased• number and type of participants, using the readiness scale developed from this study. It is hoped that this dissertation wilt provide a lens, from which further fieldwork on this topic could be conducted.
35
Bagger, Toräng Malcolm, and Kasper Aldrin. "A machine learning approach to EEG based prediction of user's music preferences." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-259625.
Full textAbstract:
Music has many benefits for our mood and feelings, especially so when we get to choose our own favorite music. However, accessing one's favorite music is not as easy for everyone. For motorically disabled and locked-in people, interacting with devices used for listening to music is challenging since it requires physical interaction. Machine learning classification methods used with EEG could prove useful for detecting individual musical preferences, extracted without any physical or verbal interaction. The two most common methods within EEG-based classification are Artificial neural networks (ANN) and Support vector machines (SVM). This study compares the performance of these two methods, when used with the DEAP dataset of EEG-monitored participants watching music videos. This comparison can help with gaining insight into which machine learning method is most appropriate for music preference detection, contributing towards more accurate predictions of motorically disabled people’s musical preferences. The participants in the DEAP dataset rated watched music videos by preference from 1 to 9, of which we trained the classification models to separate between higher (chosen as ratings 8 to 9) and lower ratings. From the results it is concluded that ANN performs better than SVM in terms of accuracy, with ANN performing at roughly 86% and SVM at 85%, while the SVMs were substantially faster to train. These accuracy scores were obtained from two ANN and SVM models using the optimal parameter and channel configurations, which were calculated through extensive testing. The accuracies are however likely achieved due to an imbalanced dataset, with too few data samples of higher ratings in proportion to lower, leading to biased classifiers that work well on our dataset but has probably close to random classification performance. Alterations to our methods could give better performing classifiers, and would also lead to more meaningful comparisons of ANN and SVM for EEG-based musical preference prediction.Musik har många fördelar för vårt humör och våra känslor, synnerligen när vi får lyssna på vår favoritmusik. Det är däremot inte lika enkelt för alla att komma åt sin egen favoritmusik. För rörelseförhindrade och personer med inlåsningssyndrom är det utmanande att interagera med de enheter som används för att lyssna på musik eftersom att de kräver fysisk interaktion. Maskininlärningsmetoder för klassificering av EEG-data skulle kunna vara användbara för att upptäcka individuella preferenser av musik utan fysisk eller verbal interaktion. De två vanligaste metoderna inom EEG-baserad klassificering är Artificiella neurala nätverk (ANN) samt Stödvektormaskiner (SVM). Studien jämför prestanda av dessa metoder på DEAP-datasetet av EEG-övervakade deltagare, för att få insikt i vilken maskininlärningsmetod som är mest användbar för klassificering av musikpreferenser. Jämförelsen kan bidra till insikter om vilken maskininlärningsmetod som passar bäst för klassificering av musikpreferenser, vilket skulle kunna bidra till precisare klassificeringar av musikpreferenser bland personer med rörelsehinder. Deltagarna i DEAP-datasetet betygsatte musikvideorna utifrån preferens på en skala mellan 1 till 9, vilket användes för att träna klassificeringsmodellerna för att separera mellan högre (valda som betyg 8 till 9) och lägre betygsättningar. Från resultaten är det slutställt att ANN presterar bättre än SVM vad gäller noggrannhet, där ANN presterar runt 86% och SVM kring 85%, medan SVM var avsevärt snabbare att träna. Dessa noggrannheter erhölls från en ANN och SVM genom att använda de optimala parameter- och kanalkonfigurationer, vilka beräknades genom omfattande tester. Noggrannheterna är däremot troligtvis uppnådda på grund av ett obalanserat dataset, med för få datapunkter med högre betyg i proportion mot de lägre, vilket leder till partiska klassificerare som fungerar väl på vårt dataset men som troligtvis har en klassificeringsprestanda närmre slumpen. Ändringar i våra metoder skulle kunna ge bättre presterande klassificerare, och skulle också kunna leda till mer meningsfulla jämförelser av ANN och SVM för EEG-baserad klassificering av musikpreferenser.
36
Sinclair, Andrew J. "PREDICTING MUSIC GENRE PREFERENCES BASED ON ONLINE COMMENTS." DigitalCommons@CalPoly, 2014. https://digitalcommons.calpoly.edu/theses/1268.
Full textAbstract:
Communication Accommodation Theory (CAT) states that individuals adapt to each other’s communicative behaviors. This adaptation is called “convergence.” In this work we explore the convergence of writing styles of users of the online music distribution plat- form SoundCloud.com. In order to evaluate our system we created a corpus of over 38,000 comments retrieved from SoundCloud in April 2014. The corpus represents comments from 8 distinct musical genres: Classical, Electronic, Hip Hop, Jazz, Country, Metal, Folk, and World. Our corpus contains: short comments, frequent misspellings, little sentence struc- ture, hashtags, emoticons, and URLs. We adapt techniques used by researchers analyzing other short web-text corpora in order to deal with these problems. We use a supervised machine learning approach to classify the genre of comments in our corpus. We examine the effects of different feature sets and supervised machine learning algorithms on classification accuracy. In total we ran 180 experiments in which we varied: number of genres, feature set composition, and machine learning algorithm. In experiments with all 8 genres we achieve up to 40% accuracy using either a Naive Bayes classifier or C4.5 based classifier with a feature set consisting of 1262 token unigrams and bigrams. This represents a 3 time improvement over chance levels.
37
Altun, Eralp H. "Learning through interactive video in secondary science : a study of learner attitudes, anxieties, and preferences for learning settings." Thesis, University of Exeter, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.361342.
Full text
38
Cox, S. M. L. "Learning to like : behavioural expression and neural bases of conditioned preferences in humans." Thesis, University of Cambridge, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.598101.
Full textAbstract:
Novel stimuli in the environment can acquire affective and motivational significance through their association with rewarding events. This process of Pavlovian associative conditioning has consequences for behaviour, as these conditioned stimuli can act as rewards in their own right, eliciting behaviour and affecting mood. Although reward conditioning has been extensively studied in animals, both on a behavioural and neuroanatomical level, relatively little is known about it in humans. Various issues concerning how and under what conditions human Pavlovian conditioning can be observed, and the extent to which research in animals can be extrapolated to humans, have been topics of debate. Unlike animals, humans can be explicitly aware of the conditioning manipulation, which may contaminate the behavioural expression of learning. In this thesis I develop a novel paradigm in which previously neutral stimuli acquire emotional significance in the absence of awareness of the conditioning manipulation. I then use this paradigm to explore reward conditioning and other factors that influence preferences, such as ageing, familiarity, and novelty, in humans. These mechanisms of preference conditioning are subsequently linked to neural substrates through neuropsychological work in patients with brain damage and through functional magnetic resonance imaging (fMRI). fMRI, however, is subject to signal dropout in the inferior part of frontal cortex. These areas are part of the regions of interest in reward processing. Here I demonstrate that fMRI sensitivity in reward-related areas can be improved using a novel methodological tool.
39
Wilson, Edwin L. "A study of the cognitive styles and learning preferences of Fire Service officers." Thesis, University of Birmingham, 1999. http://etheses.bham.ac.uk//id/eprint/287/.
Full textAbstract:
This research examines the relationship between Cognitive Style and Learning Styles of senior officers in the Fire Service and their preferences for different training delivery methods. Data has been gathered from students attending courses at the Fire Service College, in particular those attending the Divisional Command Course (DCC), which is a personal and professional development course for officers aspiring to a senior role in the Fire Service. Three data gathering instruments were used in the research, the Cognitive Styles Analysis (CSA) (Riding, 1991), the Learning Styles Questionnaire (LSQ) (Honey & Mumford, 1982), and a questionnaire specifically designed to gather students’ preference ratings across a range of 14 training delivery methods. The research examines the psychological and educational derivations of models that underpin the CSA and LSQ instruments in order to help clarify the construct systems used to describe both cognitive and learning style; and to examine their relationships with other psychological constructs. Further exploration of the relationships between cognitive and learning styles attempts to answer the question as to whether they have similar attributes and also whether the instruments have any practical predictive utility in predicting suitable delivery methodologies for training. The data findings suggest that the officer students formed a homogeneous group with regard to cognitive style on the ‘wholist–analytic’ dimension, the tendency for bias towards the analytic end of the scale, but were evenly distributed on the ‘verbaliser–imager’ dimension. The sample exhibited a more normal distribution of type with regard to learning style (using the LSQ), although there was a tendency for them to be more ‘reflector’ orientated than a standardized group in the general population. The sample group showed preferences for certain delivery methods that encouraged interactive participation in the learning process but these did not appear to show any significant correlation with either cognitive style or learning style.
40
Buchanan, Phil. "The association between learning preferences and preferred methods of assessment of dental students." Scholarly Commons, 2016. https://scholarlycommons.pacific.edu/uop_etds/38.
Full textAbstract:
This study is designed to gather information concerning a possible relationship between how dental students prefer to take in and communicate new information and how they prefer to be assessed. Though there are numerous references in the literature regarding the learning styles of students there are also references to the inaccuracy of such studies. Part of the problem is in the definition of what construes a particular learning style and how to match the outcomes of one study based on one set of criteria with another study based on a dissimilar set of guide lines. This study focuses on learning preferences that make up just a part of a learning style. To gather information two quantitative surveys were utilized that involved three class years of dental students attending the University of the Pacific Arthur A. Dugoni School of Dentistry. Both surveys were designed to be voluntary and anonymous assuming that the results would be fewer but more accurate. The first survey (VARK Survey), based on the principles of the modes represented by VARK (Visual, Aural, Read-write, and Kinesthetic), gathered information regarding how dental students prefer to take in and give out information when learning is the goal. The second survey (Survey II) gathered information validating the results of the first survey along with information regarding how dental students prefer to be assessed. One hundred forty five students responded to the VARK Survey and one hundred students responded to the Survey II. Results of the VARK Survey indicated that dental students rely heavily on using a combination of modes, a category termed “multimodal.” Responses to singular VARK modes resulted in Kinesthetic followed by Read/write, Aural, and Visual. The preferred methods of assessment in descending order were: Multiple-Choice, Combination of Methods, Essay, Oral Exam, Fill-in-the-Blanks, and True/False. The majority of dental education is presenting information and assessing the results of the teaching. Teaching and assessing strategies should be formulated to achieve optimal results when educating students is the goal. Understanding the interconnection between learning preferences and assessment methods is critical when striving to achieve optimal results educating dental students.
41
Marmon, Michael 1983. "Student Preferences for Technology-Based Learning Environment Interfaces as Influenced by Social Presence." Thesis, University of North Texas, 2016. https://digital.library.unt.edu/ark:/67531/metadc849687/.
Full textAbstract:
The purpose of this research was to investigate the preferences of online students for technology-based learning environments (TBLEs) as influenced by the level of social presence in the online courses the participating students have taken. This investigation was centered around utilizing TBLEs and methods for establishing social presence in online classes (MESPOC) survey instruments to obtain the preferences of current online students at public university in the state of Texas. This study assumed a qualitative research structure comprising analysis of the data obtained on the TBLE and MESPOC instruments followed by semi-structured interviews with some of the survey participants. The results of the studies indicated that an individual’s preferred online learning environments impacted satisfaction in an online course. Moreover, the study, also explored the students’ preferences when it comes to the organization and facilitation of online courses.
42
Caris, Kimberly A. "Long term retention and object preferences in learning set experienced dogs (Canis familiaris) /." The Ohio State University, 1990. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487676847113961.
Full text
43
Kirchner, Jens. "Context-Aware Optimized Service Selection with Focus on Consumer Preferences." Doctoral thesis, Linnéuniversitetet, Institutionen för datavetenskap (DV), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-54320.
Full textAbstract:
Cloud computing, mobile computing, Service-Oriented Computing (SOC), and Software as a Service (SaaS) indicate that the Internet emerges to an anonymous service market where service functionality can be dynamically and ubiquitously consumed. Among functionally similar services, service consumers are interested in the consumption of the services which perform best towards their optimization preferences. The experienced performance of a service at consumer side is expressed in its non-functional properties (NFPs). Selecting the best-fit service is an individual challenge as the preferences of consumers vary. Furthermore, service markets such as the Internet are characterized by perpetual change and complexity. The complex collaboration of system environments and networks as well as expected and unexpected incidents may result in various performance experiences of a specific service at consumer side. The consideration of certain call side aspects that may distinguish such differences in the experience of NFPs is reflected in various call contexts. Service optimization based on a collaborative knowledge base of previous experiences of other, similar consumers with similar preferences is a desirable foundation. The research work described in this dissertation aims at an individually optimized selection of services considering the individual call contexts that have an impact on the performance, or NFPs in general, of a service as well as the various consumer preferences. The presented approach exploits shared measurement information about the NFP behavior of a service gained from former service calls of previous consumptions. Gaining selection/recommendation knowledge from shared experience benefits existing as well as new consumers of a service before its (initial) consumption. Our approach solely focuses on the optimization and collaborative information exchange among service consumers. It does not require the contribution of service providers or other non-consuming entities. As a result, the contribution among the participating entities also contributes to their own overall optimization benefit. With the initial focus on a single-tier optimization, we additionally provide a conceptual solution to a multi-tier optimization approach for which our recommendation framework is prepared in general. For a consumer-sided optimization, we conducted a literature study of conference papers of the last decade in order to find out what NFPs are relevant for the selection and consumption of services. The ranked results of this study represent what a broad scientific community determined to be relevant NFPs for service selection. We analyzed two general approaches for the employment of machine learning methods within our recommendation framework as part of the preparation of the actual recommendation knowledge. Addressing a future service market that has not fully developed yet and due to the fact that it seems to be impossible to be aware of the actual NFP data of different Web services at identical call contexts, a real-world validation is a challenge. In order to conduct an evaluation and also validation that can be considered to be close approximations to reality with the flexibility to challenge the machine learning approaches and methods as well as the overall recommendation approach, we used generated NFP data whose characteristics are influenced by measurement data gained from real-world Web services. For the general approach with the better evaluation results and benefits ratio, we furthermore analyzed, implemented, and validated machine learning methods that can be employed for service recommendation. Within the validation, we could achieve up to 95% of the overall achievable performance (utility) gain with a machine learning method that is focused on drift detection, which in turn, tackles the change characteristic of the Internet being an anonymous service market.
44
Johansson, Magnus. "Formative Assessment:Students’ attitudes and preferences in Swedish Upper Secondary School." Thesis, Örebro universitet, Institutionen för humaniora, utbildnings- och samhällsvetenskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-68821.
Full textAbstract:
For teachers, being able to provide feedback that learners can act upon is paramount for making learning how to write possible. A questionnaire was sent out to students in Swedish Upper Secondary School. The intent was to identify how students perceive feedback, as well as how they react and interpret the feedback they receive on written texts. The results are then used in a discussion that aims to draw attention to the potential implications that feedback may have on students’ motivation to write. In this study, Nicol and Macfarlane-Dick’s seven principles for feedback serve as a measurement for what constitutes good feedback. The results suggest that when a certain form of feedback is not commonly used by teachers or is used differently by different teachers, then the feedback becomes difficult to interpret for students. The respondents consider themselves regular recipients of feedback but struggle with interpreting feedback when there are variations in teachers’ practices in applying feedback.
45
Motloung, Phindiwe Aletta. "A teaching and learning programme to address learning style diversity in an inclusive life orientation classroom setting / Phindiwe Aletta Motloung." Thesis, North-West University, 2011. http://hdl.handle.net/10394/10323.
Full textAbstract:
The purpose of the study was to gauge Grade 4 Life Orientation educators‟ understanding of what learning style diversity entails, and to explore how they accommodate diverse learning styles during teaching and learning in inclusive Life Orientation classrooms. The study explored the educators‟ choice of teaching methods and strategies, learning activities and assessment approaches to accommodate diverse learning styles in their classrooms. The first phase of the study was characterized by a literature review, which guided the formulation of focus group interview questions as well as observation criteria. The literature review explored the notion of accommodating diverse learning style needs as an important aspect of inclusive education, as well as the teaching methods and strategies, learning activities and assessment approaches that could be employed to accommodate learning style diversity in inclusive Life Orientation classrooms. The second phase of the study comprised the empirical research. Within an interprevistic framework, qualitative research by means of focus group interviews and observations was undertaken to collect data in order to determine educators‟ understanding of learning style diversity and to explore how they accommodate diverse learning style needs in their inclusive Grade 4 Life Orientation classrooms. Focus group interviews were conducted with a convenient and purposively selected sample of Grade 4 Life Orientation educators (n=40) who teach at Township schools in the Sedibeng West District of the Gauteng Department of Education. In addition to the focus group interviews, observations were done in the classrooms of five willing educators who took part in the focus group interviews to observe how the educators accommodate diverse learning style needs in practice during their teaching. The data analysis revealed that educators do not have an adequate understanding of what diverse learning style needs imply, and do not accommodate diverse learning style needs in a balanced way in their classrooms. Both the findings from the focus group interviews and observations indicated that educators experience challenges in accommodating diverse learning style needs during the teaching of Grade 4 Life Orientation in inclusive classrooms. These challenges inter alia relate to time, workload, overcrowded classrooms and a need for guidance on how to accommodate diverse learning style needs. Based on the data obtained, examples of teaching, learning and assessment activities that could form part of a teaching and learning programme for Grade 4 Life Orientation was developed to guide educators in addressing learning style diversity during teaching. In the absence of curriculum-based teaching and learning programmes that guide educators in accommodate diverse learning styles during the teaching of Life Orientation, this study makes a valuable contribution. Key concepts: learning style diversity, learning preferences, pedagogical barriers to learning, inclusive educationPhD, Teaching and Learning, North-West University, Vaal Triangle Campus, 2012
46
Banner, Michael J. "Learning/cognitive styles and learning preferences of students and instructors as related to achievement in respiratory therapy educational programs." Gainesville, FL, 1989. http://www.archive.org/details/learningcognitiv00bann.
Full text
47
Honeycutt, Hunter Gibson. "Prenatal Perceptual Experience and Postnatal Perceptual Preferences: Evidence for Attentional-Bias in Perceptual Learning." Thesis, Virginia Tech, 2000. http://hdl.handle.net/10919/36148.
Full textAbstract:
Previous studies have indicated that concurrent multimodal stimulation can interfere with prenatal perceptual learning. However, the nature and extent of this interference is not well understood. This study further assessed this issue by exposing three groups of bobwhite quail embryos to (a) no unusual prenatal stimulation, (b) a bobwhite maternal call, or (c) a maternal call + light compound in the period prior to hatching. Experiments differed in terms of the types of stimuli presented during postnatal preference tests (Exp 1 = familiar call vs. unfamiliar call; Exp 2 = familiar compound vs. unfamiliar compound; Exp 3 = familiar compound verses unfamiliar call; Exp 4 = familiar call vs. unfamiliar compound). Embryos receiving no supplemental stimulation showed no preference between stimulus events in all testing conditions. Embryos receiving exposure to a unimodal call preferred the familiar call over the unfamiliar call regardless of the presence or absence of patterned light during testing. Embryos receiving concurrent audio-visual exposure showed no preference between stimulus events in Exp 1 and Exp 4, but did prefer the familiar call when it was paired with light during testing (Exp 2 and 3). These findings suggest that concurrent multimodal stimulation does not interfere with prenatal perceptual learning by overwhelming the young organism's limited attentional capacities. Rather, multimodal biases what information is attended to during exposure and subsequent testing. Results are discussed within an attentional-bias framework, which maintains that young organisms tend to initially process non-redundant compound events as integrative units rather than processing the components of the compound separately.Master of Science
48
Lowdermilk, Margaret A. "Learning Styles of Physical Therapy and Physical Therapist Assistant Students in Accredited Physical Therapy Programs." Digital Commons @ East Tennessee State University, 2016. https://dc.etsu.edu/etd/3081.
Full textAbstract:
The purpose of this study was to determine the learning styles of Doctor of Physical Therapy (DPT) students and associate degree Physical Therapist Assistant (PTA) students and identify any association between their learning styles and examine the association between gender and age by learning style.
Participants included 337 DPT and PTA students attending CAPTE accredited institutions with doctoral DPT or associate PTA programs in Tennessee and southwest Virginia. The Felder (1996) and Soloman Index of Learning Styles (ILS) was used to determine learning style preferences within 4 learning style dimensions (active-reflective, sensing-intuitive, visual-verbal, and sequential-global).
Demographics included program of study, gender, age, ethnicity, and highest level of education. Participants were 18-63 years (mean age 25.87, standard deviation 5.62, median age 24); 205 (60.8%) DPT students, 132 (39.2%) PTA students; 205 (60.8%) female, 132 (39.2%) male.
Five research questions with 20 null hypotheses were evaluated using Cross-tabulated tables with frequency counts, percentages, and chi square tests. Statistical significance was established using an .05 alpha. Only 1 null hypothesis was rejected (Ho51: There is no difference in the active-reflective learning style among PTA students by age). There was no significant difference between the learning styles of DPT and PTA students. Participants were found to be balanced on the active-reflective dimension, sensing on the sensing-intuitive dimension, visual on the visual-verbal dimension, and balanced on the sequential-global dimension; preferences were toward the active, sensing, visual, and sequential learning styles.
This study demonstrated that DPT and PTA students have a balanced learning style with a strong preference toward active, sensing, visual, and sequential. Therefore, teaching methods should provide an instructional environment that addresses these learning style preferences. The student’s awareness of his or her learning style will enable the learner to capitalize on strengths and develop areas of weakness. This ability to employ effective learning strategies will equip an individual for the challenges of his or her chosen profession and lifelong learning.
49
Snider, Allyn. "A classroom preferences questionnaire based on the theory of multiple intelligences." PDXScholar, 1992. https://pdxscholar.library.pdx.edu/open_access_etds/4426.
Full textAbstract:
A questionnaire based on Gardner's Theory of Multiple Intelligences was developed and administered to forty-five second grade students in three different classrooms. Sections of the fifty-eight item questionnaire dealt with students' preferences for certain classroom activities, methods of learning, and modes of social interaction. Each student's responses were summarized to create an individual profile, indicating preference for linguistic, mathematical, and/ or spatial activity. In addition, students' preferences for receptive and/ or expressive methods of learning, and for working by themselves, with peers, or with adults were profiled.
50
Pullen, Carolyn. "Exploring Learning Experiences and Outcomes among Cardiologists Participating in a Web Conference Workshop Series." Thesis, Université d'Ottawa / University of Ottawa, 2012. http://hdl.handle.net/10393/23492.
Full textAbstract:
Opportunities for supporting physician continuing professional development (CPD) may exist through careful instructional design and creative use of information and communication technology. The overarching goal of this study was to explore the learning experiences and outcomes of cardiologists participating in a web conference (“webinar”) series to understand the factors that can support webinars in being an appealing and satisfying CPD medium for these learners. Acknowledging that a pedagogically-based framework for program design is a cornerstone of effective CPD (Hutchinson & Estabrooks, 2009; Inan & Lowther, 2007; Casimiro, MacDonald, Thompson, & Stodel, 2009), this study used the W(e)Learn Framework (MacDonald, Stodel, Thompson, & Casimiro, 2009) as a process guide and quality standard for program design, development and delivery.
Cardiologists voluntarily participated in an educational webinar series in which they shared their observations and experiences. Informed by the results of a systematic review of physician eLearning design preferences, this dissertation serves as a mechanism to learn about how webinars can be implemented to support learning and practice change within a population of highly specialized physician learners. Methodological approaches included a systematic review of literature examining physician preferences for eLearning design, a case study of webinar implementation, and interviews with cardiologists who participated in the webinars.
The findings of the systematic review, the case study and the interviews aligned to characterize key considerations in webinar implementation. Webinar designers must carefully determine program structures, content, and media to create a satisfying learning experience. Cardiologists seek a webinar experience that responds to their professional reality of competing priorities, complex patients, and ambiguous clinical questions. They seek a mix of evidence-based, authentic and challenging content, delivered by credible content experts. The study found that purposefully designed webinars can be a satisfying learning experience for cardiologists with the potential to influence changes in knowledge and practice. The use of an instructional design framework may structure and enrich webinar implementation; this dissertation encourages their use.