scholarly journals A domain specific language notation for a language learning activity generation tool

2021 ◽  
Author(s):  
Gabriel Sebastián ◽  
Ricardo Tesoriero ◽  
Jose A. Gallud
Keyword(s):  
Language Learning ◽  
Learning Activity ◽  
Domain Specific Language ◽  
Development Environment ◽  
Graphical Notation ◽  
Specific Language ◽  
Domain Specific ◽  
Model Based ◽  
Activity Models ◽  
Model Editor

AbstractGlobalization has increased the need for society to master new languages. This need has encouraged the launch of many applications dedicated to language learning. This paper presents a graphical notation for a domain specific language to represent language learning activities. It describes how this notation enables developers to represent language learning activity characteristics using workflow, presentation, content, media and activity model conforming a metamodel that defines the abstract syntax of the domain specific language. This notation is implemented as part of an integrated development environment to build model-based applications. Finally, this proposal is evaluated with a framework that uses the cognitive dimensions of notations for notational systems. The proposed graphic diagram editor exceeds the experience that the user has with the reflexive model editor. In relation to the creation and editing of workflow models and presentation/activity models, the proposed graphical notation its more intuitive and easy to maintain visually than the traditional reflexive tree notation used by many model-based development frameworks.

scholarly journals The Role of a Domain-specific Language Mechanism in Learning Natural and Unnatural Stress

2016 ◽  
Vol 2 (1) ◽  
Author(s):  
Angela C. Carpenter
Keyword(s):  
Language Learning ◽  
Learning Task ◽  
Target Language ◽  
Domain Specific Language ◽  
Training Procedure ◽  
The Novel ◽  
Specific Language ◽  
Domain Specific ◽  
Artificial Language Learning ◽  
French And English

AbstractIn an artificial language-learning task, two groups of English and French participants learned one of two language rules: 1) stress the first heavy (CVC) syllable, else the first syllable, or, 2) stress the first light (CV) syllable, else the first syllable. French and English participants were chosen to compare learning outcomes by speakers of different native stress systems, fixed and variable. Participants were trained on the target language by listening to a set of nonsense familiarization words exemplifying the stress rule. This was followed by a forced-choice task to choose the correct version of the words they had just learned. Following the training procedure, participants were tested on novel words with the same stress pattern to which they were familiarized. The result of the novel word testing was that the natural rule with stress on heavy syllables was learned significantly better than the unnatural, stress light syllables, rule. To account for the learnability of both the natural and the unnatural rules, I argue for the interaction of a general cognitive mechanism that facilitates learning in general and a domain-specific language mechanism that can access universal phonological principles to aid in learning a natural language rule.

scholarly journals Implementing a Domain-specific Language for Model-based Drug Development

2015 ◽  
Vol 63 ◽  
pp. 308-316 ◽  
Author(s):  
Natallia Kokash ◽  
Stuart L. Moodie ◽  
Mike K. Smith ◽  
Nick Holford
Keyword(s):  
Drug Development ◽  
Domain Specific Language ◽  
Specific Language ◽  
Domain Specific ◽  
Model Based ◽  
Model Based Drug Development

Domain-Specific Language Abstractions for Compression

2021 ◽  
Author(s):  
Jessica Ray ◽  
Ajav Brahmakshatriya ◽  
Richard Wang ◽  
Shoaib Kamil ◽  
Albert Reuther ◽  
...  
Keyword(s):  
Domain Specific Language ◽  
Specific Language ◽  
Domain Specific
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