Relevant bibliographies by topics / Domain-specific theories of learning

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  2. Dissertations / Theses
  3. Books
  4. Book chapters
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Academic literature on the topic 'Domain-specific theories of learning'

Author: Grafiati
Published: 4 June 2021
Last updated: 6 February 2022

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Journal articles on the topic "Domain-specific theories of learning"

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Sternberg, Robert. "Applying Psychological Theories to Educational Practice." American Educational Research Journal 45, no. 1 (March 2008): 150–65. http://dx.doi.org/10.3102/0002831207312910.

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Two approaches to the application of psychological theories to education might be referred to as domain-general and domain-specific. The domain-general approach seeks a general theory of cognitive and other skills that apply across subject-matter areas. The domain-specific approach seeks to apply specific theories within given domains, such as reading or mathematics. The latter approach is more widely used. But it fails to provide a unified model of learning and instruction. One of the greatest challenges facing modern research in learning and instruction is devising and then empirically testing domain-general theories. This article describes efforts to devise and test one such model, the theory of successful intelligence.
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Hatano, Giyoo, and Kayoko Inagaki. "Domain-specific constraints of conceptual development." International Journal of Behavioral Development 24, no. 3 (September 2000): 267–75. http://dx.doi.org/10.1080/01650250050118240.

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Although we have made much progress in understanding the growth of mind by shifting from Piagetian theory to a variety of views of conceptual development as the domain-specific construction of knowledge under constraints, the key notion of “constraints” is not yet well articulated. As a result, the views have not yet constituted a coherent theory that replaces Piagetian theory. In this article, after summarising “dominant” views of conceptual development, we reconceptualise the notion of “innate constraints”, more specifically as preferences and biases that serve as learning mechanisms, not as innate knowledge or representational contents. We then propose to expand the notion of “constraints” to include interactive, sociocultural constraints as well as internal, cognitive ones, which enable even young children to acquire knowledge in uniquely human ways. We believe that these formulations make the current views of conceptual development better specified and more comprehensive. Finally we offer our prospect for the future of conceptual development theories.
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Das, Kaushik. "Realistic Mathematics & Vygotsky’s Theories in Mathematics Education." Shanlax International Journal of Education 9, no. 1 (December 1, 2020): 104–8. http://dx.doi.org/10.34293/education.v9i1.3346.

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Mathematics education is not mathematics, it makes a basic use of highly specialized kinds of mathematical knowledge. The modern world feels a crisis of proper mathematics education in any nation. Realistic Mathematics Education is a domain-specific instruction theory for mathematics. This paper introduces realistic mathematics education (RME) and Vygotskian impacts on mathematics education for learning mathematics. This article describes the development of teaching-learning mathematics & learning theories from a socio-cultural perspective. The methodology of the study is based on qualitative type.
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Donoho, S. K., and L. A. Rendell. "Rerepresenting and Restructuring Domain Theories: A Constructive Induction Approach." Journal of Artificial Intelligence Research 2 (April 1, 1995): 411–46. http://dx.doi.org/10.1613/jair.129.

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Theory revision integrates inductive learning and background knowledge by combining training examples with a coarse domain theory to produce a more accurate theory. There are two challenges that theory revision and other theory-guided systems face. First, a representation language appropriate for the initial theory may be inappropriate for an improved theory. While the original representation may concisely express the initial theory, a more accurate theory forced to use that same representation may be bulky, cumbersome, and difficult to reach. Second, a theory structure suitable for a coarse domain theory may be insufficient for a fine-tuned theory. Systems that produce only small, local changes to a theory have limited value for accomplishing complex structural alterations that may be required. Consequently, advanced theory-guided learning systems require flexible representation and flexible structure. An analysis of various theory revision systems and theory-guided learning systems reveals specific strengths and weaknesses in terms of these two desired properties. Designed to capture the underlying qualities of each system, a new system uses theory-guided constructive induction. Experiments in three domains show improvement over previous theory-guided systems. This leads to a study of the behavior, limitations, and potential of theory-guided constructive induction.
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Zhang, Qian, Lin Li, Xiuyan Guo, Li Zheng, Yuyan Wu, and Chu Zhou. "Implicit learning of symmetry of human movement and gray matter density: Evidence against pure domain general and pure domain specific theories of implicit learning." International Journal of Psychophysiology 147 (January 2020): 60–71. http://dx.doi.org/10.1016/j.ijpsycho.2019.10.008.

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Chen, Yi-Chun, Fang-Ying Yang, and Cheng-Chieh Chang. "CONCEPTUALIZING SPATIAL ABILITIES AND THEIR RELATION TO SCIENCE LEARNING FROM A COGNITIVE PERSPECTIVE." Journal of Baltic Science Education 19, no. 1 (February 10, 2020): 50–63. http://dx.doi.org/10.33225/jbse/20.19.50.

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Science learning requires visuospatial thinking. Accordingly, spatial ability is regarded as the key to learning science well, but its effects are sometimes not as significant as expected. To this end, this research aims to conceptualize spatial abilities and to clarify their relation to science learning based on an analysis of empirical studies. Content analysis of 39 studies showed that (1) intrinsic-dynamic skills are the most frequently measured, (2) the explored science topics mostly involve well-established knowledge, (3) the effects of spatial ability on science achievement are inconsistent, and (4) educational interventions are not always effective in improving students’ spatial abilities or science achievement. It is argued that domain knowledge interferes with the study results and that domain-specific spatial ability exists, referring to apply spatial-type and domain-specific knowledge. Supported by cognitive theories and empirical evidence, a model is constructed to exhibit the relations between domain-general and domain-specific spatial ability as well as their effects on science achievement. According to the model, the two spatial abilities functionally partially overlap in the operations of spatial skills, and educational experience and malleable spatial skills are reciprocal; however, improvement in general spatial ability, involving the function of the central executive system, is likely limited. Keywords: domain-generality, domain-specificity, spatial ability, domain knowledge, science learning, educational intervention
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Evans, Jonathan St B. T., and David E. Over. "The role of language in the dual process theory of thinking." Behavioral and Brain Sciences 25, no. 6 (December 2002): 684–85. http://dx.doi.org/10.1017/s0140525x02330127.

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Carruthers’proposals would seem to implicate language in what is known as System 2 thinking (explicit) rather than System 1 thinking (implicit) in contemporary dual process theories of thinking and reasoning. We provide outline description of these theories and show that while Carruthers’characterization of non-verbal processes as domain-specific identifies one critical feature of System 1 thinking, he appears to overlook the fact that much cognition of this type results from domain-general learning processes. We also review cognitive psychological evidence that shows that language and the explicit representations it supports are heavily involved in supporting System 1 thinking, but falls short of supporting his claim that it is the medium in which domain-general thinking occurs.
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Hamrick, Phillip, Carine Graff, and Brittany Finch. "Contributions of episodic memory to novel word learning." Mental Lexicon 14, no. 3 (December 31, 2019): 381–98. http://dx.doi.org/10.1075/ml.19019.ham.

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Abstract Multiple theories predict that word learning is intimately linked to episodic memory, at least in the early phases of learning. However, it is unclear to what degree this link reflects more domain-specific (i.e., those dedicated to language or the lexicon) or more domain-general episodic memory processes that operate outside of language. One way to address this possibility is by using a behavioral individual differences design. This study examined whether behavioral individual differences in episodic memory abilities predicted adult word learning abilities. If behavioral performance in a nonlinguistic episodic memory task is predictive of behavioral performance in word learning, then it is likely that they share a common underlying nonlinguistic, memory-based mechanism. The results revealed that individual differences in episodic memory abilities predicted word learning abilities shortly after learning but not two days later. These behavioral results are consistent with prior neuropsychological observations (e.g., in amnesia: Kensinger, Ullman, & Corkin, 2001) as well as with theories positing a shift in reliance in lexical development from episodic memory to a distributed neocortical memory system after a period of sleep (e.g., Davis & Gaskell, 2009).
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Poulin-Dubois, Diane. "How to build a baby: A new toolkit?" Behavioral and Brain Sciences 34, no. 3 (May 19, 2011): 144–45. http://dx.doi.org/10.1017/s0140525x11000070.

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AbstractCarey proposes a theory of conceptual development that specifies innate conceptual representations that get learning started. Those representations are the output of innate domain-specific input analyzers. I contend that innate core cognition about agency is itself a gradual construction and that the role of Quinian bootstrapping needs elaboration to account for the development of intuitive theories of psychology.
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Kohnert, Kathryn, and Kerry Danahy Ebert. "Beyond morphosyntax in developing bilinguals and “specific” language impairment." Applied Psycholinguistics 31, no. 2 (March 11, 2010): 303–10. http://dx.doi.org/10.1017/s0142716409990464.

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In the Keynote Article, “The Interface Between Bilingual Development and Specific Language Impairment,” Johanne Paradis considers issues and evidence at the intersection of children learning two languages and primary or specific language impairment (SLI). The review focuses on morphosyntactic evidence and the fit of this evidence with maturational (domain-specific) and limited processing capacity (LPC; domain-general) theories of language impairment. We agree with Paradis that studies that systematically and simultaneously investigate the behavioral profile of dual-language learners and children with language impairment are of significant theoretical and practical value. In our commentary we aim to broaden the behavioral profile to be considered in these populations, beyond the level of morphosyntax. In line with this aim we use the term primary language impairment (PLI) for the same population referred to as SLI by Paradis.
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Dissertations / Theses on the topic "Domain-specific theories of learning"

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Weibell, Christian J. "Principles of Learning: A Conceptual Framework for Domain-Specific Theories of Learning." BYU ScholarsArchive, 2011. https://scholarsarchive.byu.edu/etd/2759.

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This study is predicated on the belief that there does not now exist, nor will there ever exist, any single theory of learning that is broad enough to account for all types of learning yet specific enough to be maximally useful in practical application. Perhaps this dichotomy is the reason for the apparent gap between existing theories of learning and the practice of instructional design. As an alternative to any supposed grand theory of learning—and following the lead of prominent thinkers in the fields of clinical psychology and language teaching—this study proposes a shift toward principles. It presents a principle-based conceptual framework of learning, and recommends use of the framework as a guide for creating domain-specific theories of learning. The purpose of this study was to review theories of learning in the behavioral, cognitive, constructive, human, and social traditions to identify principles of learning local to those theories that might represent specific instances of more universal principles, fundamentally requisite to the facilitation of learning in general. Many of the ideas reviewed have resulted from, or been supported by, direct empirical evidence. Others have been suggested based on observational or practical experience of the theorist. The ideas come from different points in time, are described from a variety of perspectives, and emphasize different aspects and types of learning; yet there are a number of common themes shared among them regarding the means by which learning occurs. It is hypothesized that such themes represent universal and fundamental principles of learning. These principles were the objective of the present study. They have been sought through careful review and analysis of both theoretical and empirical literature by methods of textual research (Clingan, 2008) and constant comparative analysis (Glaser & Strauss, 1967). By way of textual research a methodological lens was defined to identify general themes, and by way of constant comparative analysis these themes were developed further through the analysis and classification of specific instances of those themes in the texts reviewed. Ten such principles were identified: repetition, time, step size, sequence, contrast, significance, feedback, context, engagement, and agency. These ten facilitative principles were then organized in the context of a comprehensive principles-of-learning framework, which includes the four additional principles of potential, target, change, and practice.
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Malik, Zeeshan. "Towards on-line domain-independent big data learning : novel theories and applications." Thesis, University of Stirling, 2015. http://hdl.handle.net/1893/22591.

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Feature extraction is an extremely important pre-processing step to pattern recognition, and machine learning problems. This thesis highlights how one can best extract features from the data in an exhaustively online and purely adaptive manner. The solution to this problem is given for both labeled and unlabeled datasets, by presenting a number of novel on-line learning approaches. Specifically, the differential equation method for solving the generalized eigenvalue problem is used to derive a number of novel machine learning and feature extraction algorithms. The incremental eigen-solution method is used to derive a novel incremental extension of linear discriminant analysis (LDA). Further the proposed incremental version is combined with extreme learning machine (ELM) in which the ELM is used as a preprocessor before learning. In this first key contribution, the dynamic random expansion characteristic of ELM is combined with the proposed incremental LDA technique, and shown to offer a significant improvement in maximizing the discrimination between points in two different classes, while minimizing the distance within each class, in comparison with other standard state-of-the-art incremental and batch techniques. In the second contribution, the differential equation method for solving the generalized eigenvalue problem is used to derive a novel state-of-the-art purely incremental version of slow feature analysis (SLA) algorithm, termed the generalized eigenvalue based slow feature analysis (GENEIGSFA) technique. Further the time series expansion of echo state network (ESN) and radial basis functions (EBF) are used as a pre-processor before learning. In addition, the higher order derivatives are used as a smoothing constraint in the output signal. Finally, an online extension of the generalized eigenvalue problem, derived from James Stone’s criterion, is tested, evaluated and compared with the standard batch version of the slow feature analysis technique, to demonstrate its comparative effectiveness. In the third contribution, light-weight extensions of the statistical technique known as canonical correlation analysis (CCA) for both twinned and multiple data streams, are derived by using the same existing method of solving the generalized eigenvalue problem. Further the proposed method is enhanced by maximizing the covariance between data streams while simultaneously maximizing the rate of change of variances within each data stream. A recurrent set of connections used by ESN are used as a pre-processor between the inputs and the canonical projections in order to capture shared temporal information in two or more data streams. A solution to the problem of identifying a low dimensional manifold on a high dimensional dataspace is then presented in an incremental and adaptive manner. Finally, an online locally optimized extension of Laplacian Eigenmaps is derived termed the generalized incremental laplacian eigenmaps technique (GENILE). Apart from exploiting the benefit of the incremental nature of the proposed manifold based dimensionality reduction technique, most of the time the projections produced by this method are shown to produce a better classification accuracy in comparison with standard batch versions of these techniques - on both artificial and real datasets.
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Kotze, Yolanda. "Developing a framework for the writing of ESP study guides / Yolanda Kotze." Thesis, North-West University, 2007. http://hdl.handle.net/10394/1699.

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Teaching through specifically designed and produced learning materials is a widely used and accepted way of teaching in higher education both nationally and internationally. Although this kind of teaching is used mainly in the field of distance education, it has become increasingly popular at traditional universities in face-to-face methods of education. Developing language-learning materials that meets the needs of English for Specific Purposes learners is a process that requires meticulous planning as English for Specific Purposes courses are aimed at meeting the career needs of the learners. An empirical study was conducted to determine the perceptions and concerns of learners using the ENGL 122 study guide at the North-West University (Potchefstroom Campus). The results of the study indicated that the learners were positive that the study guide enhanced their learning process, but various concerns were also raised by the learners. This study also aimed to create a framework for the writing of English for Specific Purposes (ESP) study guides. In order to achieve this, a literature study was done to provide information about the relevant theories and principles that apply to ESP study guide development. The literature study also included aspects that need to be taken into consideration when designing or planning the development of an ESP study guide.
Thesis (Ph.D. (English))--North-West University, Potchefstroom Campus, 2007.
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Cotgageorge, Ed. "Domain-specific learning: A neuropsychological rehabilitation investigation of vanishing cues." Diss., The University of Arizona, 1992. http://hdl.handle.net/10150/185956.

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This project represents a descriptive study of 19 neurologically impaired adults. The etiology of the impairment includes traumatic brain injury and progressive neurological disease such as Alzheimer's Disease. Four non-impaired geriatric adults were controls for the Alzheimer's Disease patients in this study. Subjects in the study were taught, through the method of vanishing cues, information about computer operating system commands and computer programming. The primary purpose of this project was to determine whether or not these groups could acquire this information and determine the extent to which memory and attention deficits contribute to learning new information in neurologically impaired individuals. Subjects participated in learning sessions presented by a microcomputer. The sessions lasted for twenty minutes to one hour, depending on the subjects ability to attend to the task. Each subject interacted with the computer by answering the questions or doing the procedures presented. Not all of the subjects reached the criteria of zero or one hints that are required before moving on to the next lesson. None of the subjects with progressive neurological disease completed any of the lessons. Linear regression and multiple regression were used to determine whether or not the degree of memory loss or the degree of attention deficit a subject demonstrated accounts for a significant amount of variance on the criteria variable of number of trials to complete the learning lessons. Generally, differences between all of the groups was found and the variance accounted for by degree of memory loss and attention deficit was found to be significant. A principal components factor analysis determined that there was a memory and general intelligence factor and an attention factor that contributed to a subjects performance on the learning lessons. The factors when entered simultaneously into a multiple regression equation accounted for about.50 percent of the variance in the number of trials required to complete the learning lessons. It was concluded, that the factors were statistically significant in determining performance on the learning lessons.
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Bandhakavi, Anil. "Domain-specific lexicon generation for emotion detection from text." Thesis, Robert Gordon University, 2018. http://hdl.handle.net/10059/3103.

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Emotions play a key role in effective and successful human communication. Text is popularly used on the internet and social media websites to express and share emotions, feelings and sentiments. However useful applications and services built to understand emotions from text are limited in effectiveness due to reliance on general purpose emotion lexicons that have static vocabulary and sentiment lexicons that can only interpret emotions coarsely. Thus emotion detection from text calls for methods and knowledge resources that can deal with challenges such as dynamic and informal vocabulary, domain-level variations in emotional expressions and other linguistic nuances. In this thesis we demonstrate how labelled (e.g. blogs, news headlines) and weakly-labelled (e.g. tweets) emotional documents can be harnessed to learn word-emotion lexicons that can account for dynamic and domain-specific emotional vocabulary. We model the characteristics of realworld emotional documents to propose a generative mixture model, which iteratively estimates the language models that best describe the emotional documents using expectation maximization (EM). The proposed mixture model has the ability to model both emotionally charged words and emotion-neutral words. We then generate a word-emotion lexicon using the mixture model to quantify word-emotion associations in the form of a probability vectors. Secondly we introduce novel feature extraction methods to utilize the emotion rich knowledge being captured by our word-emotion lexicon. The extracted features are used to classify text into emotion classes using machine learning. Further we also propose hybrid text representations for emotion classification that use the knowledge of lexicon based features in conjunction with other representations such as n-grams, part-of-speech and sentiment information. Thirdly we propose two different methods which jointly use an emotion-labelled corpus of tweets and emotion-sentiment mapping proposed in psychology to learn word-level numerical quantification of sentiment strengths over a positive to negative spectrum. Finally we evaluate all the proposed methods in this thesis through a variety of emotion detection and sentiment analysis tasks on benchmark data sets covering domains from blogs to news articles to tweets and incident reports.
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Poitras, Eric. "The Metahistoreasoning tool: fostering domain-specific metacognitive activities in learning through historical inquiry." Thesis, McGill University, 2013. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=119573.

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Learning about complex historical events requires that undergraduate students regulate their understanding in accordance with disciplinary-based practices. However, students often fail to notice that the causes of historical events are unknown, uncertain, or unreported. Furthermore, they neglect to formulate tentative explanations in an effort to gain better understanding. As such, the current program of research sought to develop and evaluate the MetaHistoReasoning tool, a computer-based learning environment that aims to support students in learning disciplinary-based skills while performing an authentic task in the domain of history. This dissertation outlines the theoretical, instructional, and empirical foundations for the development, design, and evaluation of the MetaHistoReasoning tool. The findings have implications for building an improved version of the educational system as a means to provide adaptive and flexible instruction that is better suited to the specific needs of different students.
Apprendre à propos d'évènements historiques complexes requiert que les étudiants et étudiantes universitaires régulent leur compréhension en accord avec les pratiques spécifiques à la discipline. Toutefois, les étudiants et étudiantes universitaires faillissent de reconnaître les causes des évènements historiques qui sont inconnues, incertaines, et non déclarées. De plus, ils négligent de formuler des explications tentatives pour but d'améliorer leur compréhension. En tant que tel, le programme actuel de recherche a cherché à développer et évaluer le MetaHistoReasoning tool, un environnement d'apprentissage informatisé qui vise à soutenir les élèves dans l'apprentissage des habiletés spécifique au domaine tout en effectuant une tâche authentique dans le domaine de l'histoire. Cette thèse présente les fondements théoriques, pédagogiques, et empiriques pour le dévelopement, la conception, et l'évaluation du MetaHistoReasoning tool. Les résultats ont des implications pour la construction d'une version améliorée du système éducatif comme un moyen de fournir un enseignement adapté et flexible, mieux adapté aux besoins spécifiques des différents élèves.
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Wahlberg, Sara. "Teaching and Learning Protein Synthesis through Domain-Specific Language in Upper Secondary Education." Licentiate thesis, Karlstads universitet, Institutionen för ingenjörs- och kemivetenskaper (from 2013), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-70684.

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The aim of this licentiate thesis is to contribute to understanding of upper secondary teaching and learning of protein synthesis with a focus on domain-specific language. It is based on two studies, designated Studies I and II. Study I addressed upper secondary students’ understanding of protein synthesis through their usage of domain-specific concepts. Data collected through semi-structured group interviews show that students can better reason about core concepts than peripheral concepts, and they compartmentalise the concepts into five clusters. Study II focused on chemistry and biology textbooks’ presentation of protein synthesis through domain-specific concept usage and effects of context on these presentations. The textbooks were analysed using a content analysis approach involving data mining techniques implemented by a computer-generated algorithm. The results reveal that chemistry textbooks focus more on peripheral concepts and generally tend to identify fewer relationships among more concepts than biology textbooks, which emphasise core concepts and tend to highlight more relationships among fewer concepts. Jointly, Studies I and II reveal four facets of teaching and learning protein synthesis: ‘mechanistic or conceptual descriptions’, ‘compartmentalisation’, ‘mRNA as a core concept’ and ‘canonical representation’. By acknowledging the results reported herein, teaching can improve the facilitation and reduce the hindrance in learning protein synthesis through the awareness of the domain-specific language usage.
Proteins are crucial to life: no proteins – no life. Every picosecond, thousands of proteins are constructed in each cell in what is referred to as protein synthesis. Due to its importance for understanding the mechanism for life, protein synthesis is globally regarded as a cornerstone of molecular life sciences and education in the field. Like any area of expertise, the molecular life sciences share a domain-specific language. However, research on teaching and learning protein synthesis through this domain-specific language is scarce. The aim of this licentiate thesis is thereby to contribute to understanding of upper secondary teaching and learning of protein synthesis with a focus on domain-specific language. The thesis is based on two studies: Study I addressed students’ understanding where the results show that students can better reason about core concepts than peripheral concepts, and they compartmentalise the concepts into five clusters. Study II focused on chemistry and biology textbooks’ presentation and effects of context on these presentations. The results reveal that chemistry textbooks focus more on peripheral concepts and generally tend to identify fewer relationships among more concepts than biology textbooks, which emphasise core concepts and tend to highlight more relationships among fewer concepts. Jointly, Studies I and II reveal four facets of teaching and learning protein synthesis. By acknowledging the results reported herein, teaching can improve the facilitation and reduce the hindrance in learning protein synthesis through the awareness of the domain-specific language usage.
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Grahn, Fredrik, and Kristian Nilsson. "Object Detection in Domain Specific Stereo-Analysed Satellite Images." Thesis, Linköpings universitet, Datorseende, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-159917.

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Given satellite images with accompanying pixel classifications and elevation data, we propose different solutions to object detection. The first method uses hierarchical clustering for segmentation and then employs different methods of classification. One of these classification methods used domain knowledge to classify objects while the other used Support Vector Machines. Additionally, a combination of three Support Vector Machines were used in a hierarchical structure which out-performed the regular Support Vector Machine method in most of the evaluation metrics. The second approach is more conventional with different types of Convolutional Neural Networks. A segmentation network was used as well as a few detection networks and different fusions between these. The Convolutional Neural Network approach proved to be the better of the two in terms of precision and recall but the clustering approach was not far behind. This work was done using a relatively small amount of data which potentially could have impacted the results of the Machine Learning models in a negative way.
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Zhang, Zhuo. "A planning approach to migrating domain-specific legacy systems into service oriented architecture." Thesis, De Montfort University, 2012. http://hdl.handle.net/2086/9020.

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The planning work prior to implementing an SOA migration project is very important for its success. Up to now, most of this kind of work has been manual work. An SOA migration planning approach based on intelligent information processing methods is addressed to semi-automate the manual work. This thesis will investigate the principle research question: 'How can we obtain SOA migration planning schemas (semi-) automatically instead of by traditional manual work in order to determine if legacy software systems should be migrated to SOA computation environment?'. The controlled experiment research method has been adopted for directing research throughout the whole thesis. Data mining methods are used to analyse SOA migration source and migration targets. The mined information will be the supplementation of traditional analysis results. Text similarity measurement methods are used to measure the matching relationship between migration sources and migration targets. It implements the quantitative analysis of matching relationships instead of common qualitative analysis. Concretely, an association rule and sequence pattern mining algorithms are proposed to analyse legacy assets and domain logics for establishing a Service model and a Component model. These two algorithms can mine all motifs with any min-support number without assuming any ordering. It is better than the existing algorithms for establishing Service models and Component models in SOA migration situations. Two matching strategies based on keyword level and superficial semantic levels are described, which can calculate the degree of similarity between legacy components and domain services effectively. Two decision-making methods based on similarity matrix and hybrid information are investigated, which are for creating SOA migration planning schemas. Finally a simple evaluation method is depicted. Two case studies on migrating e-learning legacy systems to SOA have been explored. The results show the proposed approach is encouraging and applicable. Therefore, the SOA migration planning schemas can be created semi-automatically instead of by traditional manual work by using data mining and text similarity measurement methods.
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Abedmouleh, Aymen. "Approche Domain-Specific Modeling pour l'opérationnalisation des scénarios pédagogiques sur les plateformes de formation à distance." Phd thesis, Université du Maine, 2013. http://tel.archives-ouvertes.fr/tel-01019917.

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Ce travail de recherche porte sur la spécification et l'opérationnalisation des scénarios pédagogiques sur les plateformes de formation à distance dans une perspective d'ingénierie et de réingénierie des EIAH (Environnements Informatique pour l'Apprentissage Humain). En se situant dans une approche centrée plateformes, nous supposons que les plateformes disposent de leur propre paradigme de conception. Pour cela, nous proposons aux développeurs et à la communauté de développement des plateformes un processus spécifique d'identification et d'explicitation du langage de conception pédagogique des plateformes de formation par le biais d'un métamodèle. Nous exploitons l'approche outillée Domain-Specific Modeling comme cadre pratique pour le développement de langages et d'outils de conception graphiques basés sur le métamodèle du langage de conception pédagogique. Afin de répondre à des besoins récurrents d'opérationnalisation de scénarios pédagogiques, nous utilisons également ce métamodèle pour la spécification des modules d'import/export intégrés au sein des plateformes. Ces modules permettent d'opérationnaliser les scénarios conformes au langage identifié et également d'exporter les scénarios existants sur les plateformes afin de permettre leur adaptation par les outils développés. Nous avons expérimenté nos propositions théoriques sur deux plateformes de formation Moodle et Ganesha. Enfin, nous avons vérifié la cohérence de notre approche par la mise à l'essai des outils développés. Par le biais de notre approche, nous favorisons une opérationnalisation de ces scénarios sans pertes d'information ni de sémantique.
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Books on the topic "Domain-specific theories of learning"

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Slowey, Maria, ed. Comparative Adult Education and Learning. Florence: Firenze University Press, 2017. http://dx.doi.org/10.36253/978-88-6453-422-0.

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This volume explores the topics of adult learning and education through the specific lens of comparative research. The book is divided into four chapters comprising two parts: an analytic essay followed by an anthology of readings from a selection of key texts intended to illustrate different perspectives, theories and/or approaches from varying perspectives in different countries. The book represents the second of a series dedicated to adult learning and education and developed within the ESRALE European project. Its companion books are: Empirical Research Methodology in Adult Learning and Education. Authors and Texts and Researches in Adult Learning and Education: the European dimension.
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Math from three to seven: The story of a mathematical circle for preschoolers. Providence. R.I: American Mathematical Society, 2011.

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Bauer, William I. Music Learning Today. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780197503706.001.0001.

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Grounded in a research-based, conceptual model called Technological Pedagogical and Content Knowledge (TPACK), the essential premise of Music Learning Today: Digital Pedagogy for Creating, Performing, and Responding to Music is that music educators and their students can benefit through use of technology as a tool to support learning in the three musical processes—creating, performing, and responding to music. Insights on how technology can be used to advantage in both traditional and emerging learning environments are provided, and research-based pedagogical approaches that align technologies with specific curricular outcomes are described. Importantly, the book advocates that the decision on whether or not to utilize technology for learning, and the specific technology that might be best suited for a particular learning context, should begin with a consideration of curricular outcomes (music subject matter). This is in sharp contrast to most other books on music technology that are technocentric, organized around specific software applications and hardware. The book also recognizes that knowing how to effectively use the technological tools to maximize learning (pedagogy) is a crucial aspect of the teaching-learning process. Drawing on the research and promising practices literature in music education and related fields, pedagogical approaches that are aligned with curricular outcomes and specific technologies are suggested. It is not a “how to” book per se, but rather a text informed by the latest research, theories of learning, and documented best practices, with the goal of helping teachers develop the ability to understand the dynamics of effectively using technology for music learning.
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Blair, R. J. R. The Developing Moralities. Edited by Philip David Zelazo. Oxford University Press, 2013. http://dx.doi.org/10.1093/oxfordhb/9780199958474.013.0005.

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This chapter will make five claims regarding the development of morality. First, there are at least three, computationally distinct forms of social norm: victim-based, disgust-based, and social conventional. All three can be referred to as moral (although not all individuals place all of these categories of norm within their domain of morality). Second, these three forms of norm develop because of the existence of specific emotion-based learning systems (victim-based reliant on an emotional response to distress cues, disgust-based reliant on an emotional response to disgusted expressions, and social conventional norms reliant on an emotional response to anger). Third, the development of specific classes of norm can be disrupted if these emotion-based learning systems are dysfunctional. Fourth, these emotion-based systems are not automatic but instead under considerable attentional control. Fifth, these emotion-based systems alone cannot lead to the development of all aspects of morality. Specifically, they will not determine which norms the individual places within the moral domain—that is highly dependent on an individual’s culturally influenced theories of morality. In addition, judgments of morality require access to a concept of immorality to compare the action against. For most individuals, part of the concept of an immoral act includes its intentional nature. In short, full moral development requires the integration of mental state information provided by theory of mind with outcome information provided by the emotion learning systems.
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Chase, Sharon E. Moffat. Domain-specific self-perceptions of university students with and without learning disabilities. 1992.

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Chase, Sharon E. Moffatt. Domain-specific self-perceptions of university students with and without learning disabilities. 1992.

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Heath, Nancy Lee. Domain-specific self-perceptions, achievement and depressive symptomatology in children with and without learning disabilities. 1992.

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Heath, Nancy Lee. Domain-specific self-perceptions, achievement and depressive symptomatology in children with and without learning disabilities. 1992.

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Danks, David. Singular Causation. Edited by Michael R. Waldmann. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199399550.013.15.

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Causal relations between specific events are often critically important for learning, understanding, and reasoning about the world. This chapter examines both philosophical accounts of the nature of singular causation, and psychological theories of people’s judgments and reasoning about singular causation. It explores the content of different classes of theories, many of which are based on either some type of physical process connecting cause and effect, or else some kind of difference-making (or counterfactual) impact of the cause on the effect. In addition, this chapter examines various theoretical similarities and differences, particularly between philosophical and psychological theories that appear superficially similar. One consistent theme that emerges in almost every account is the role of general causal relations in shaping human judgments and understandings about singular causation.
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Garb, Erica. Can general metacognitive strategies improve domain-specific learning for academically at-risk young adults?: Evaluating a metacognitive EFL curriculum. 2001.

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Book chapters on the topic "Domain-specific theories of learning"

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Pulman, Stephen G., and Maria Liakata. "Learning domain theories." In Recent Advances in Natural Language Processing III, 29. Amsterdam: John Benjamins Publishing Company, 2004. http://dx.doi.org/10.1075/cilt.260.05pul.

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Clark, Peter, and Stan Matwin. "Learning domain theories using abstract background knowledge." In Machine Learning: ECML-93, 360–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/3-540-56602-3_151.

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Zhang, Yichuan, Junkai Ren, Junxiang Li, Qiang Fang, and Xin Xu. "Deep Q-learning with Explainable and Transferable Domain Rules." In Intelligent Computing Theories and Application, 259–73. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-84529-2_22.

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Li, Bo, Ping-Ping Zheng, Jin Liu, and Xiao-Long Zhang. "Face Recognition via Domain Adaptation and Manifold Distance Metric Learning." In Intelligent Computing Theories and Application, 3–10. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63312-1_1.

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Huffman, Scott B., Douglas J. Pearson, and John E. Laird. "Correcting Imperfect Domain Theories: A Knowledge-Level Analysis." In Foundations of Knowledge Acquisition: Cognitive Models of Complex Learning, 209–44. Boston, MA: Springer US, 1993. http://dx.doi.org/10.1007/978-1-4615-3172-2_6.

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VanLehn, Kurt. "A Workbench for Discovering Task Specific Theories of Learning." In New Directions in Educational Technology, 23–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-77750-9_3.

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Leonard, Laurence B. "Theories of Language Learning and Children with Specific Language Impairment." In New Directions In Language Development And Disorders, 1–5. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4157-8_1.

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Hoang, Thai Son, Laurent Voisin, and Michael Butler. "Domain-Specific Developments Using Rodin Theories." In Implicit and Explicit Semantics Integration in Proof-Based Developments of Discrete Systems, 19–37. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5054-6_2.

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Navaitienė, Julita, and Eglė Stasiūnaitienė. "The Goal of the Universal Design for Learning: Development of All to Expert Learners." In Inclusive Learning and Educational Equity, 23–57. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-80658-3_2.

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AbstractOver the past 10 years, every learner’s ability to achieve the highest level of learning success has become quite an important topic. The Universal Design for Learning (UDL) sets a goal to allow all learners to achieve their optimal learning experience that matches inclusive education. Learners who can assess their own learning needs set their personal learning goals, and monitor their progress are termed the expert learners (McDowell. Developing expert learners: a roadmap for growing confident and competent students. Corwin, 2019). This chapter focuses on theoretical backgrounds for expert learners’ paradigm. It starts from fundamental constructivist theories and moves towards the theory of self-regulation and cognitive neuroscience approach. It concentrates on the theory of self-determination, which, in our opinion, validates in the best way the nature of the expert learners’ development. Implementation of the Universal Design for Learning allows all learners to access, participate in, and progress in the general-education curriculum. This chapter presents the specific profile of the expert learners covering their main characteristics and qualities and revealing the essence of the UDL framework. Educators could use the profile as the educational guidelines conductive to understand how the process of becoming the expert learner proceeds.
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Reimann, Peter, and Wilfrid Utz. "Modeling Learning Data for Feedback and Assessment." In Domain-Specific Conceptual Modeling, 555–74. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39417-6_25.

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Conference papers on the topic "Domain-specific theories of learning"

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Ahmad, Mifrah, Lukman Ab Rahim, and Noreen Izza Arshad. "An interpretive approach to model educational games: Learning theories domain using multi-domain framework." In 2015 International Symposium on Technology Management and Emerging Technologies (ISTMET). IEEE, 2015. http://dx.doi.org/10.1109/istmet.2015.7359065.

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Naji, Abdelwahab, and Mohamed ramdani. "Proposal for a metamodel of studied domain & automatic re-contextualization of learning scenarios." In 2013 8th International Conference on Intelligent Systems: Theories and Applications (SITA). IEEE, 2013. http://dx.doi.org/10.1109/sita.2013.6560798.

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Ahmad, Mifrah, Lukman Ab Rahim, and Noreen Izza Arshad. "A multi-domain framework for modelling educational games: Towards the effective development in perspective of learning theories." In 2015 International Symposium on Mathematical Sciences and Computing Research (iSMSC). IEEE, 2015. http://dx.doi.org/10.1109/ismsc.2015.7594027.

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Zhang, Hongbao, Baoping Lu, Lulu Liao, Hongzhi Bao, Zhifa Wang, Xutian Hou, Amol Mulunjkar, and Xin Jin. "Combining Machine Learning and Classic Drilling Theories to Improve Rate of Penetration Prediction." In SPE/IADC Middle East Drilling Technology Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/202202-ms.

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Abstract Theoretically, rate of penetration (ROP) model is the basic to drilling parameters design, ROP improvement tools selection and drill time & cost estimation. Currently, ROP modelling is mainly conducted by two approaches: equation-based approach and machine learning approach, and machine learning performs better because of the capacity in high-dimensional and non-linear process modelling. However, in deep or deviated wells, the ROP prediction accuracy of machine learning is always unsatisfied mainly because the energy loss along the wellbore and drill string is non-negligible and it's difficult to consider the effect of wellbore geometry in machine learning models by pure data-driven methods. Therefore, it's necessary to develop robust ROP modelling method for different scenarios. In the paper, the performance of several equation-based methods and machine learning methods are evaluated by data from 82 wells, the technical features and applicable scopes of different methods are analysed. A new machine learning based ROP modelling method suitable for different well path types was proposed. Integrated data processing pipeline was designed to dealing with data noises, data missing, and discrete variables. ROP effecting factors were analysed, including mechanical parameters, hydraulic parameters, bit characteristics, rock properties, wellbore geometry, etc. Several new features were created by classic drilling theories, such as downhole weight on bit (DWOB), hydraulic impact force, formation heterogeneity index, etc. to improve the efficiency of learning from data. A random forest model was trained by cross validation and hyperparameters optimization methods. Field test results shows that the model could predict the ROP in different hole sections (vertical, deviated and horizontal) and different drilling modes (sliding and rotating drilling) and the average accuracy meets the requirement of well planning. A novel data processing and feature engineering workflow was designed according the characteristics of ROP modelling in different well path types. An integrated data-driven ROP modelling and optimization software was developed, including functions of mechanical specific energy analysis, bit wear analysis and predict, 2D & 3D ROP sensitivity analysis, offset wells benchmark, ROP prediction, drilling parameters constraints analysis, cost per meter prediction, etc. and providing quantitative evidences for drilling parameters optimization, drilling tools selection and well time estimation.
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Zhu, Weihang, Jiang Zhou, Md Aminul Islam, Md Abu Shufean, and Xinyu Liu. "Development of a Mobile App for Learning System Dynamics." In ASME 2013 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/imece2013-62512.

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This paper presents the development of a mobile app for learning System Dynamics. A course in System Dynamics is required in most mechanical and other engineering curricula. The app implements several types of the first order and the second order systems under various conditions. Based on the user inputs, the app solves the relevant System Dynamics equations and displays the graphs. The users are able to observe and analyze results by changing the parameters. The user-friendly app was developed for Android and iOS smartphone platforms. The developed app can serve as a complementary learning tool for System Dynamics in Mechanical Engineering. It may help students to understand important concepts and theories behind numerical results, such as the relationships between input and output, solutions in time-domain and frequency-domain, three vibration modes for the systems, and the effects of equation constants and input selections on output responses.
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Sui, Yanan, Masrour Zoghi, Katja Hofmann, and Yisong Yue. "Advancements in Dueling Bandits." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/776.

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The dueling bandits problem is an online learning framework where learning happens ``on-the-fly'' through preference feedback, i.e., from comparisons between a pair of actions. Unlike conventional online learning settings that require absolute feedback for each action, the dueling bandits framework assumes only the presence of (noisy) binary feedback about the relative quality of each pair of actions. The dueling bandits problem is well-suited for modeling settings that elicit subjective or implicit human feedback, which is typically more reliable in preference form. In this survey, we review recent results in the theories, algorithms, and applications of the dueling bandits problem. As an emerging domain, the theories and algorithms of dueling bandits have been intensively studied during the past few years. We provide an overview of recent advancements, including algorithmic advances and applications. We discuss extensions to standard problem formulation and novel application areas, highlighting key open research questions in our discussion.
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Sáiz-Sánchez, Héctor, Javier Martínez-De-La-Torre, Roger Esteller-Curto, Enric Serradell-López, Teresa Gallego-Navarro, and Andrea Rubert-Albiol. "Personal development in the virtuality; online activities for individual and group growth." In Third International Conference on Higher Education Advances. Valencia: Universitat Politècnica València, 2017. http://dx.doi.org/10.4995/head17.2017.5494.

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Online teaching is commonly offered for courses and it is aimed students acquire specific skills based on the subject requirements. Regarding soft-skills, collaborative and creative activities are usually deployed face-to-face in contrast to online environments, where communication, group dynamics and activities that require interactivity among the participants can be managed easier. Because of this we loose skills acquisition opportunities and other potential benefits of real collaboration mediated by on-line environments. We propose an ICT-based method appropriated for project-based learning, innovative teams and personal development. It has 7 phases and has been designed under the theories of field theories of humanism with the main aim to make possible that everybody in the on-line platform can grow and develop individually together with the group. Professor can apply this as a whole (the 7 phases) or some of them as we have related the phases with on-line tasks. We tested this method with a group of 17 post-graduate students. We concluded that when members have enough maturity and experience, these ICT-based-methods make shared learning possible, with great impact on the course skills and competences, but also on soft skills, which are acquired informally while learning the main course subject.
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Kulmanov, Maxat, Wang Liu-Wei, Yuan Yan, and Robert Hoehndorf. "EL Embeddings: Geometric Construction of Models for the Description Logic EL++." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/845.

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An embedding is a function that maps entities from one algebraic structure into another while preserving certain characteristics. Embeddings are being used successfully for mapping relational data or text into vector spaces where they can be used for machine learning, similarity search, or similar tasks. We address the problem of finding vector space embeddings for theories in the Description Logic ??⁺⁺ that are also models of the TBox. To find such embeddings, we define an optimization problem that characterizes the model-theoretic semantics of the operators in ??⁺⁺ within ℝⁿ, thereby solving the problem of finding an interpretation function for an ??⁺⁺ theory given a particular domain Δ. Our approach is mainly relevant to large ??⁺⁺ theories and knowledge bases such as the ontologies and knowledge graphs used in the life sciences. We demonstrate that our method can be used for improved prediction of protein--protein interactions when compared to semantic similarity measures or knowledge graph embeddings.
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Liu, Qi. "Towards a New Generation of Cognitive Diagnosis." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/703.

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Cognitive diagnosis is a type of assessment for automatically measuring individuals' proficiency profiles from their observed behaviors, e.g. quantifying the mastery level of examinees on specific knowledge concepts/skills. As one of the fundamental research tasks in domains like intelligent education, a number of Cognitive Diagnosis Models (CDMs) have been developed in the past decades. Though these solutions are usually well designed based on psychometric theories, they still suffer from the limited ability of the handcrafted diagnosis functions, especially when dealing with heterogeneous data. In this paper, I will share my personal understanding of cognitive diagnosis and review our recent developments of CDMs mostly from a machine learning perspective. Meanwhile, I will show the wide applications of cognitive diagnosis.
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Foster, Dylan J., and Vasilis Syrgkanis. "Statistical Learning with a Nuisance Component (Extended Abstract)." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/654.

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We provide excess risk guarantees for statistical learning in a setting where the population risk with respect to which we evaluate a target parameter depends on an unknown parameter that must be estimated from data (a "nuisance parameter"). We analyze a two-stage sample splitting meta-algorithm that takes as input two arbitrary estimation algorithms: one for the target parameter and one for the nuisance parameter. We show that if the population risk satisfies a condition called Neyman orthogonality, the impact of the nuisance estimation error on the excess risk bound achieved by the meta-algorithm is of second order. Our theorem is agnostic to the particular algorithms used for the target and nuisance and only makes an assumption on their individual performance. This enables the use of a plethora of existing results from statistical learning and machine learning literature to give new guarantees for learning with a nuisance component. Moreover, by focusing on excess risk rather than parameter estimation, we can give guarantees under weaker assumptions than in previous works and accommodate the case where the target parameter belongs to a complex nonparametric class. We characterize conditions on the metric entropy such that oracle rates---rates of the same order as if we knew the nuisance parameter---are achieved. We also analyze the rates achieved by specific estimation algorithms such as variance-penalized empirical risk minimization, neural network estimation and sparse high-dimensional linear model estimation. We highlight the applicability of our results in four settings of central importance in the literature: 1) heterogeneous treatment effect estimation, 2) offline policy optimization, 3) domain adaptation, and 4) learning with missing data.
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Reports on the topic "Domain-specific theories of learning"

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Klenk, Matthew, and Ken Forbus. Cross Domain Analogies for Learning Domain Theories. Fort Belvoir, VA: Defense Technical Information Center, January 2007. http://dx.doi.org/10.21236/ada471251.

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Klenk, Matthew, and Kenneth D. Forbus. Learning Domain Theories via Analogical Transfer. Fort Belvoir, VA: Defense Technical Information Center, January 2007. http://dx.doi.org/10.21236/ada470404.

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Lavoie, Benoit, Michael White, and Tanya Korelsky. Learning Domain-Specific Transfer Rules: An Experiment with Korean to English Translation. Fort Belvoir, VA: Defense Technical Information Center, January 2002. http://dx.doi.org/10.21236/ada457732.

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Loehle, C. S. Constraints on the formulation of ecological models and theories: Conservation laws and domain-specific rule bases. Office of Scientific and Technical Information (OSTI), January 1988. http://dx.doi.org/10.2172/6103296.

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