formal context
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2022 ◽  
Vol 12 (1) ◽  
pp. 30
Author(s):  
Valentina Domenici

Non-formal learning environments, such as science museums, have a fundamental role in science education and high potentialities as ideal contexts for science teachers’ training. These aspects have been analyzed and reported in several recent works mainly focused on students’ perception of science and increased engagement towards scientific disciplines. In this work, a project-based learning methodology optimized and experimented in the frame of a pre-service chemistry teachers’ course at the University of Pisa (Italy), during the last eight years, involving in total 171 participants, is presented. This educational project has several distinctive features related to the STEAM philosophy, with a high level of multi-disciplinarity and creativity. Most of the laboratories and chemistry-centered activities were conceived, planned and carried out by the future chemistry teachers in non-formal contexts, such as science museums. A case study based on a series of non-formal laboratories designed by a group of students during their training in the academic year 2018–2019 and performed in a science museum is reported and examined in details. In this paper, all steps of the STEAM project-based learning methodology are described underlining the main learning outcomes and cognitive levels involved in each step and the relevant methodologies proposed during the training course and adopted in the project. The effectiveness of this pre-service teachers’ training methodology is finally discussed in terms of participants’ motivation and interest towards the course’s content, students’ final judgment of their training experiences and, in particular, of the STEAM project-based learning activities. From the students’ feedbacks and final assessment, the role of the non-formal context in teaching and learning chemistry and the efficacy of developing educational activities related to current and real-life chemistry-centered topics emerged as very positive aspects of the proposed approach.


2022 ◽  
pp. 323-340
Author(s):  
Nuno Ricardo Oliveira ◽  
Ana Patricia Almeida

In recent years, there has been a growing interest in integrating mobile technologies into the formal system in the field of formal education and, in particular, higher education. Furthermore, due to the circumstances caused by the pandemic panorama that extended to most countries in the world in 2020, various sectors, in which education is included, were forced to reinvent and transform themselves in order to adapt to emergency remote education. What the authors propose with this chapter is to make an analysis of the state of the art on the theme of informal communication in the educational context, and particularly in higher education, with the use of the available technology, namely mobile media. Through a literature review already initiated in previous studies, it is intended to know the national and international panorama about the use of mobile applications in the context of higher education and in what way the devices traditionally conceived for informal communication are being used and adapted to a formal context.


2021 ◽  
Vol 18 (2) ◽  
pp. 139-165
Author(s):  
Marina Jajić Novogradec

The aim of the paper is to explore the appearance of positive and negative lexical transfer of plurilingual learners in English vocabulary acquisition. Cross-linguistic influences in the study are examined by word translation tasks from Croatian into English, including true, partial, and deceptive cognates or false friends in English, German, and Italian. The results have revealed different language dominances and positive or negative transfer manifestation. Lexical transfer from L4 German is manifested positively, but the Italian language seems to play a dominant role in the acquisition of English vocabulary. The effect of Croatian is manifested both positively and negatively. The study has confirmed previous psycholinguistic studies on the complexity of lexical connections in plurilingual learners and the dynamic interaction of various learning-based factors, such as language recency, proficiency, exposure to languages, the order in which languages are learned, and the formal context in language learning.


2021 ◽  
Vol 7 (2) ◽  
pp. 21-29
Author(s):  
Stella Takvoryan

This paper examines the effect of race, context, and white public space on the extent to which speakers articulate, hyperarticulate, hypo-articulate, or glottalize word-final English alveolar stops -/t/ and -/d/ in the controlled environment of the quadrennial US Presidential Inaugural Prayer. It shows that African-American speakers hyperarticulated and articulated /t,d/ more frequently than the white speaker, who hypo-articulated and glottalized /t,d/ consistently, especially on words like God, Lord, and Christ. These results suggest that the highly formal context required African-American speakers to perform /t,d/ to index themselves as authorities to an unfamiliar, white audience, while the white speaker did not consider race to influence listeners’ judgements of him, allowing him to index familiarity and trustworthiness. 


Symmetry ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 2363
Author(s):  
Ning Lan ◽  
Shuqun Yang ◽  
Ling Yin ◽  
Yongbin Gao

The application of knowledge graphs has been restricted in some domains, especially the industrial and academic domains. One of the reasons is that they require a high reliability of knowledge, which cannot be satisfied by the existing knowledge graph research. By comparison, traditional knowledge engineering has a high correctness, but low efficiency is an inevitable drawback. Therefore, it is meaningful to organically connect traditional knowledge engineering and knowledge graphs. Therefore, we propose a theory from Attribute Implications to Knowledge Graphs, named AIs-KG, which can construct knowledge graphs based on implications. The theory connects formal concept analysis and knowledge graphs. We firstly analyze the mutual transformation based on the ideas of symmetry with a strict proof among the attribute implication, the formal context and the concept lattice, which forms the closed cycle between the three. Particularly, we propose an Augment algorithm (IFC-A) to generate the Implication Formal Context through the attribute implication, which can make knowledge more complete. Furthermore, we regard ontology as a bridge to realize the transformation from the concept lattice to the knowledge graph through some mapping methods. We conduct our experiments on the attribute implication from the rule base of an animal recognition expert system to prove the feasibility of our algorithms.


Information ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 502
Author(s):  
Stefan Wagenpfeil ◽  
Paul Mc Kevitt ◽  
Matthias Hemmje

Multimedia feature graphs are employed to represent features of images, video, audio, or text. Various techniques exist to extract such features from multimedia objects. In this paper, we describe the extension of such a feature graph to represent the meaning of such multimedia features and introduce a formal context-free PS-grammar (Phrase Structure grammar) to automatically generate human-understandable natural language expressions based on such features. To achieve this, we define a semantic extension to syntactic multimedia feature graphs and introduce a set of production rules for phrases of natural language English expressions. This explainability, which is founded on a semantic model provides the opportunity to represent any multimedia feature in a human-readable and human-understandable form, which largely closes the gap between the technical representation of such features and their semantics. We show how this explainability can be formally defined and demonstrate the corresponding implementation based on our generic multimedia analysis framework. Furthermore, we show how this semantic extension can be employed to increase the effectiveness in precision and recall experiments.


2021 ◽  
Author(s):  
John Conallin ◽  
Nathan Ning ◽  
Jennifer Bond ◽  
Nicholas Pawsey ◽  
Lee Baumgartner ◽  
...  

Abstract. Implementation failure is widely acknowledged as a major impediment to the success of water resource plans and policies, yet there are very few proactive approaches available for analysing potential implementation issues during the planning stage. The Motivations and Abilities (MOTA) framework was established to address this planning stage gap, by offering a multi-stakeholder, multi-level approach to evaluate the implementation feasibility of plans and policies. MOTA is a stepwise process focusing on the relationship between trigger, motivation, and ability. Here we outline the base model of the MOTA framework and review existing MOTA applications in assorted water resource management contexts. From our review we identify the strengths and limitations of the MOTA framework in various institutional implementation and social adoptability contexts. Our findings indicate that the existing MOTA base model framework has been successful in identifying the motivations and abilities of the stakeholders involved in a range of bottom-up water resource planning contexts, and in subsequently providing insight into the types of capacity- or consent-building strategies needed for effective implementation. We propose several complementary add-in applications to complement the base model, which specific applications may benefit from. Specifically, the incorporation of formal context and stakeholder analyses during the problem definition stage (Step 1), could provide a more considered basis for designing the latter steps within the MOTA analyses. In addition, the resolution of the MOTA analyses could be enhanced by developing more nuanced scoring approaches, or by adopting empirically proven ones from well-established published models. Through setting the base model application, additional add-in applications can easily be added to enhance different aspects of the analysis while still maintaining comparability with other MOTA applications. With a robust base model and a suite of add-in applications, there is great potential for the MOTA framework to become a staple tool for optimising implementation success in any water planning and policy-making context.


2021 ◽  
Vol 21 (S7) ◽  
Author(s):  
Fengbo Zheng ◽  
Rashmie Abeysinghe ◽  
Licong Cui

Abstract Background As biomedical knowledge is rapidly evolving, concept enrichment of biomedical terminologies is an active research area involving automatic identification of missing or new concepts. Previously, we prototyped a lexical-based formal concept analysis (FCA) approach in which concepts were derived by intersecting bags of words, to identify potentially missing concepts in the National Cancer Institute (NCI) Thesaurus. However, this prototype did not handle concept naming and positioning. In this paper, we introduce a sequenced-based FCA approach to identify potentially missing concepts, supporting concept naming and positioning. Methods We consider the concept name sequences as FCA attributes to construct the formal context. The concept-forming process is performed by computing the longest common substrings of concept name sequences. After new concepts are formalized, we further predict their potential positions in the original hierarchy by identifying their supertypes and subtypes from original concepts. Automated validation via external terminologies in the Unified Medical Language System (UMLS) and biomedical literature in PubMed is performed to evaluate the effectiveness of our approach. Results We applied our sequenced-based FCA approach to all the sub-hierarchies under Disease or Disorder in the NCI Thesaurus (19.08d version) and five sub-hierarchies under Clinical Finding and Procedure in the SNOMED CT (US Edition, March 2020 release). In total, 1397 potentially missing concepts were identified in the NCI Thesaurus and 7223 in the SNOMED CT. For NCI Thesaurus, 85 potentially missing concepts were found in external terminologies and 315 of the remaining 1312 appeared in biomedical literature. For SNOMED CT, 576 were found in external terminologies and 1159 out of the remaining 6647 were found in biomedical literature. Conclusion Our sequence-based FCA approach has shown the promise for identifying potentially missing concepts in biomedical terminologies.


Entropy ◽  
2021 ◽  
Vol 23 (11) ◽  
pp. 1397
Author(s):  
Ting Qian ◽  
Yongwei Yang ◽  
Xiaoli He

Three-way concept analysis (3WCA) is extended research of formal concept analysis (FCA) by combining three-way decision. The three-way object oriented concept lattice (OEOL) is one of the important data structures which integrates rough set, concept lattice and three-way decision in 3WCA. In the paper, we investigate the characteristics of formal context based on the isomorphic relationship among the kinds of concept lattices with OEOL. Firstly, II-dual intersectable attributes and II-dual intersectable context are proposed and the relationship between the type I-dual intersectable context(dual intersectable context) and the type II-dual intersectable context are studied. In addition, the relationship among the kinds of concept lattices with OEOL are studied when the formal context is both I-dual intersectable context and II-dual intersectable context. Finally, the inverse problems of the above conclusions are discussed and the following two conclusions are obtained: (1) the formal context is the type II-dual intersectable context, when the object oriented concept lattice and OEOL are isomorphic. (2) In addition, the formal context is the type I-dual intersectable context, when the concept lattice and OEOL are anti-isomorphic.


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