scholarly journals Modul Berbasis Logika Pembuktian untuk Mengurangi Level Abstraksi Topik Grup dan Sifat-Sifatnya

2021 ◽  
Vol 5 (1) ◽  
pp. 33-40
Author(s):  
Defri Ahmad ◽  
Fridgo Tasman ◽  
Ronal Rifandi ◽  
Saddam Al Aziz ◽  
Rara Shandy Winanda
Keyword(s):  
University Students ◽  
Mathematical Object ◽  
Abstract Algebra ◽  
Student Response ◽  
Abstract Concept ◽  
Abstract Concepts ◽  
Abstraction Level ◽  
Teaching Group

The most essential thing in mathematics is proof, it makes mathematics being different with other subjects. One of subject in mathematics that always need prove to understand the concept is abstract algebra. In studying abstract algebra, student need various abstract concepts to include in its concepts. It is hard for student to understand the structures in abstract algebra and prove some of mathematical object that satisfy the structures. Group and its properties is the first structure in abstract algebra that has an abstract concept. It is hard for student to understand some objects, that is proven satisfy a structure and why the proof steps just flow. By giving explanation and reason in every proofing step, we try to increase student proving level and reduce the abstraction level of the concepts. To see how this module reduces the abstraction level in teaching group, this module is applied to university students and evaluated by interviewing and questionnaires to the students. Base on student response and by some perspectives, student proving ability increase and the abstraction level of the concept is diminished in some aspects.

Representation of Complex Emotional and Abstract Meanings by Simple Forms

1979 ◽  
Vol 49 (3) ◽  
pp. 839-842 ◽  
Author(s):  
Bernard Lyman
Keyword(s):  
Adverse Effect ◽  
University Students ◽  
Television Viewing ◽  
Chance Level ◽  
Abstract Concepts ◽  
Line Drawings

Using curved and angular line drawings, several investigators found a relation between form and meaning in individuals reared before the age of television. In the present study 60 university students who had been exposed to television from earliest childhood were asked to indicate whether a curved or angular figure best represented each of 40 emotion or abstract concepts. For 36 of the concepts the frequencies were significantly different from a chance level, and it was concluded that television viewing had no adverse effect on the fittingness of form and meaning. Several possible explanations for the phenomenon are discussed.

scholarly journals Drawing with Metaphors. Mediating ideational content in drawing through metaphors

2013 ◽  
Vol 6 (3) ◽  
Author(s):  
Berit Ingebrethsen
Keyword(s):  
Abstract Concept ◽  
Abstract Concepts ◽  
Visual Metaphors ◽  
Linguistic Research ◽  
Cognitive Linguistic ◽  
Educational Issue ◽  
Metaphor Theory ◽  
Different Types ◽  
George Lakoff ◽  
The Subject

It is not easy to express abstract concepts, such as time and society, in a drawing. The subject of this article is rooted in the educational issue of visually expressing themes represented by abstract concepts. However, it is possible to find means and devices to express such ideas. This article shows how metaphors can be used to express such ideas visually. Cognitive linguistic research argues that metaphors are crucial in the verbal communication of abstract concepts. This article also attempts to show that metaphors are important in visual communication. The cognitive linguistic metaphor theory of George Lakoff and Mark Johnson is used here to investigate how metaphors are used to construct meaning in the drawings of cartoonist and illustrator Finn Graff and artist Saul Steinberg. The article presents a few examples of how visual devices structure the abstract concept of time. It then proceeds to explain how symbols function as metonymies and provides an overview of the different types of metaphors and how they are used to express meaning in drawings. The article concludes by attempting to provide new insights regarding the use of visual metaphors.

scholarly journals Exploring Geometric Feature Hyper-Space in Data to Learn Representations of Abstract Concepts

2020 ◽  
Vol 10 (6) ◽  
pp. 1994 ◽  
Author(s):  
Rahul Sharma ◽  
Bernardete Ribeiro ◽  
Alexandre Miguel Pinto ◽  
F. Amílcar Cardoso
Keyword(s):  
Training Data ◽  
Geometric Feature ◽  
Automatic Identification ◽  
Computational Domain ◽  
Abstract Concept ◽  
Abstract Concepts ◽  
Concept Representation ◽  
Data Problem ◽  
Rans Modeling ◽  
Concrete Concepts

The term concept has been a prominent part of investigations in psychology and neurobiology where, mostly, it is mathematically or theoretically represented. Concepts are also studied in the computational domain through their symbolic, distributed and hybrid representations. The majority of these approaches focused on addressing concrete concepts notion, but the view of the abstract concept is rarely explored. Moreover, most computational approaches have a predefined structure or configurations. The proposed method, Regulated Activation Network (RAN), has an evolving topology and learns representations of abstract concepts by exploiting the geometrical view of concepts, without supervision. In the article, first, a Toy-data problem was used to demonstrate the RANs modeling. Secondly, we demonstrate the liberty of concept identifier choice in RANs modeling and deep hierarchy generation using the IRIS dataset. Thirdly, data from the IoT’s human activity recognition problem is used to show automatic identification of alike classes as abstract concepts. The evaluation of RAN with eight UCI benchmarks and the comparisons with five Machine Learning models establishes the RANs credibility as a classifier. The classification operation also proved the RANs hypothesis of abstract concept representation. The experiments demonstrate the RANs ability to simulate psychological processes (like concept creation and learning) and carry out effective classification irrespective of training data size.

Using abstract concepts in impact-focussed organisational research

2017 ◽  
Vol 12 (1) ◽  
pp. 18-34 ◽  
Author(s):  
Peter Lugosi
Keyword(s):  
Design Methodology ◽  
Applied Research ◽  
Data Generation ◽  
Abstract Concept ◽  
Abstract Concepts ◽  
Business Research ◽  
Content Type ◽  
Change In Practice ◽  
Organisational Research ◽  
Context Specific

Purpose The purpose of this paper is to conceptualise and examine the processes through which abstract concepts, or abstractions, can be utilised in co-creating knowledge within “impact-focussed” organisational and business research, i.e. applied research that primarily seeks to promote change in practice rather than principally aiming to make theoretical contributions to academic debates. The paper uses the abstraction “hospitality” as an empirical example and discusses the techniques used to “operationalise” this concept, i.e. make it understandable for research participants enabling researchers to use it within data generation and the creation of practical insights in organisational enquiry. Design/methodology/approach The study employed two methods: first, participant-generated photos; and second, two interactive workshops with 38 practitioners where the abstract concept “hospitality” was used to generate practical organisational insights. Findings The paper distinguishes between four stages: the elaboration of abstraction, concretisation of abstraction, probing perspectives on abstraction and exploring experiences of abstraction. It is argued that utilising specific techniques within these four stages facilitates: recognisability: the extent to which organisational stakeholders understand the content and meanings of the abstraction; and relatability: the extent to which stakeholders appreciate how the abstract concepts are relevant to interpreting their own practices and experiences. Research limitations/implications This is an exploratory study, used to develop and refine elicitation techniques, rather than to draw definitive conclusions about the applicability of specific abstract concepts. Nevertheless, reflecting on the processes and techniques used in the utilisation of abstractions here can help to operationalise them in future impact-focussed research. Originality/value The paper conceptualises the processes through which abstract concepts can be made apprehendable for non-specialist, non-academic practitioners. In doing so, it discusses how various elicitation techniques support the utilisation of abstractions in generating insights that can support the development of constructive, context-specific practices in organisations and businesses.

scholarly journals Contributions of different prefrontal cortical regions to abstract rule acquisition and reversal in monkeys

2017 ◽  
Author(s):  
Giancarlo La Camera ◽  
Sebastien Bouret ◽  
Barry J. Richmond
Keyword(s):  
Orbitofrontal Cortex ◽  
Brain Regions ◽  
Abstract Concept ◽  
Abstract Concepts ◽  
Prefrontal Cortical ◽  
Rule Acquisition ◽  
Learning Rules ◽  
Association Task ◽  
Abstract Rule ◽  
Cortical Regions

AbstractThe ability to learn and follow abstract rules relies on intact prefrontal regions including the lateral prefrontal cortex (LPFC) and the orbitofrontal cortex (OFC). Here, we investigate the specific roles of these brain regions in learning rules that depend critically on the formation of abstract concepts as opposed to simpler input-output associations. To this aim, we tested monkeys with bilateral removals of either LPFC or OFC on a rapidly learned task requiring the formation of the abstract concept of same vs. different. While monkeys with OFC removals were significantly slower than controls at both acquiring and reversing the concept-based rule, monkeys with LPFC removals were not impaired in acquiring the task, but were significantly slower at rule reversal. Neither group was impaired in the acquisition or reversal of a delayed visual cue-outcome association task without a concept-based rule. These results suggest that OFC is essential for the implementation of a concept-based rule, whereas LPFC seems essential for its modification once established.

scholarly journals Abstract concept learning in a simple neural network inspired by the insect brain

2018 ◽  
Author(s):  
Alex J. Cope ◽  
Eleni Vasilaki ◽  
Dorian Minors ◽  
Chelsea Sabo ◽  
James A.R. Marshall ◽  
...  
Keyword(s):  
Executive Control ◽  
Honey Bees ◽  
Mushroom Body ◽  
Insect Brain ◽  
Abstract Concept ◽  
Abstract Concepts ◽  
Top Down ◽  
Learning Tasks ◽  
Learning Rates ◽  
Simple Neural Network

AbstractThe capacity to learn abstract concepts such as ‘sameness’ and ‘difference’ is considered a higher-order cognitive function, typically thought to be dependent on top-down neocortical processing. It is therefore surprising that honey bees apparantly have this capacity. Here we report a model of the structures of the honey bee brain that can learn same-ness and difference, as well as a range of complex and simple associative learning tasks. Our model is constrained by the known connections and properties of the mushroom body, including the protocerebral tract, and provides a good fit to the learning rates and performances of real bees in all tasks, including learning sameness and difference. The model proposes a novel mechanism for learning the abstract concepts of ‘sameness’ and ‘difference’ that is compatible with the insect brain, and is not dependent on top-down or executive control processing.

DYING IS HARD TO DESCRIBE: METONYMIES AND METAPHORS OF DEATH IN THEILIAD

2018 ◽  
Vol 68 (2) ◽  
pp. 359-383 ◽  
Author(s):  
Fabian Horn
Keyword(s):  
Cognitive Linguistics ◽  
Figurative Language ◽  
Human Mind ◽  
Abstract Concept ◽  
Abstract Concepts ◽  
Epic Poem ◽  
Recent Developments ◽  
Battle Scenes

Homer'sIliadis an epic poem full of war and battles, but scholars have noted that ‘[t]he Homeric poems are interested in death far more than they are in fighting’. Even though long passages of the poem, particularly the so-called ‘battle books’ (Il.Books 5–8, 11–17, 20–2), consist of little other than fighting, individual battles are often very short with hardly ever a longer exchange of blows. Usually, one strike is all it takes for the superior warrior to dispatch his opponent, and death occurs swiftly. The prominence of death in Homeric battle scenes raises the question of how and in which terms dying in battle is being depicted in theIliad: for while fighting can be described in a straightforward fashion, death is an abstract concept and therefore difficult to grasp. Recent developments in cognitive linguistics have ascertained that, when coping with difficult and abstract concepts, such as emotions, the human mind is likely to resort to figurative language and particularly to metaphors.

On Concept Algebra

2011 ◽  
pp. 126-148
Author(s):  
Yingxu Wang
Keyword(s):  
System Modeling ◽  
Formal Theory ◽  
Mathematical Structure ◽  
Abstract Concept ◽  
Abstract Concepts ◽  
Formal Knowledge ◽  
Adaptive Capability ◽  
Algebraic Operations ◽  
Complex Knowledge ◽  
Object Attribute

Concepts are the most fundamental unit of cognition that carries certain meanings in expression, thinking, reasoning, and system modeling. In denotational mathematics, a concept is formally modeled as an abstract and dynamic mathematical structure that encapsulates attributes, objects, and relations. The most important property of an abstract concept is its adaptive capability to autonomously interrelate itself to other concepts. This article presents a formal theory for abstract concepts and knowledge manipulation known as “concept algebra.” The mathematical models of concepts and knowledge are developed based on the object-attribute-relation (OAR) theory. The formal methodology for manipulating knowledge as a concept network is described. Case studies demonstrate that concept algebra provides a generic and formal knowledge manipulation means, which is capable to deal with complex knowledge and software structures as well as their algebraic operations.

scholarly journals Abstract Concept Learning in Cognitive Robots

2021 ◽  
Author(s):  
Alessandro Di Nuovo ◽  
Angelo Cangelosi
Keyword(s):  
Concept Learning ◽  
Cognitive Robotics ◽  
Abstract Concept ◽  
Abstract Concepts ◽  
Knowledge Based ◽  
Abstract Knowledge ◽  
Benchmark Datasets ◽  
Artificial Learning ◽  
Concrete Concepts ◽  
Cognitive Robots

Abstract Purpose of Review Understanding and manipulating abstract concepts is a fundamental characteristic of human intelligence that is currently missing in artificial agents. Without it, the ability of these robots to interact socially with humans while performing their tasks would be hindered. However, what is needed to empower our robots with such a capability? In this article, we discuss some recent attempts on cognitive robot modeling of these concepts underpinned by some neurophysiological principles. Recent Findings For advanced learning of abstract concepts, an artificial agent needs a (robotic) body, because abstract and concrete concepts are considered a continuum, and abstract concepts can be learned by linking them to concrete embodied perceptions. Pioneering studies provided valuable information about the simulation of artificial learning and demonstrated the value of the cognitive robotics approach to study aspects of abstract cognition. Summary There are a few successful examples of cognitive models of abstract knowledge based on connectionist and probabilistic modeling techniques. However, the modeling of abstract concept learning in robots is currently limited at narrow tasks. To make further progress, we argue that closer collaboration among multiple disciplines is required to share expertise and co-design future studies. Particularly important is to create and share benchmark datasets of human learning behavior.

scholarly journals Development of MISTION Software to Detect and Reduce Students' Misconception with Conceptual Change Text Strategy on Stoichiometry Materials

2021 ◽  
Vol 5 (3) ◽  
pp. 423
Author(s):  
Rizky Amallia Prastika ◽  
Sukarmin Sukarmin
Keyword(s):  
Conceptual Change ◽  
Construct Validation ◽  
Student Response ◽  
Abstract Concepts ◽  
Content Validation ◽  
Research Subjects ◽  
Reaction Equation ◽  
Adobe Flash ◽  
Conceptual Change Text ◽  
Chemical Material

Misconceptions often occur, especially in chemical material like stoichiometry which are full of abstract concepts. The purpose of this study was to determine the feasibility of mistion software to detect and reduce misconceptions in stoichiometric material with conceptual change text strategy. This research was conducted using the Research and Development (R&D) method with 15 students of SMAN 1 Gedangan as research subjects. Software is developed using Adobe Flash CS 6 with action script 3.0. The software's feasibility is viewed from the validity practicality, and effectiveness. The data analysis results show that 1) the software is very valid with the average result of content validation is 93.52%, and the construct validation is 91.82%. 2) The software is very practical, with an average result of student response questionnaires is 95.28% and supported with the average result of student observations is 85%. 3) Software is effective with the average result of misconception shift for sub-concept basic chemical law is 77.27% with effective category, sub-concept of reaction equation is 85.05% with very effective category, and sub-concept of mole is 73,72% with effective category. Based on the result, we can conclude that mistion software is feasible to detect and reduce students' misconception.

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