scholarly journals DECODING VIEWS AND SENTIMENTS OF PROGRAM HEADS TOWARDS THE SUPERVISION OF INSTRUCTION DURING THE COVID-19 PANDEMIC

2021 ◽  
pp. 323-329
Author(s):  
Jesus M. Meneses ◽  
Karen W. Cantilang ◽  
Delbert A. Dala ◽  
Jovito B. Madeja
Keyword(s):  
Machine Learning ◽  
Sentiment Analysis ◽  
Latent Semantic Indexing ◽  
State University ◽  
Written Responses ◽  
Strategic Role ◽  
To Come ◽  
Learning Software ◽  
Supervision Of Instruction

The purpose of this study was to decode the hidden views and sentiments from the collated written responses of Eastern Samar State University’s Program Heads regarding supervision of instructions amidst the COVID-19 pandemic. This study utilized Exploratory Sequential Mixed Method to explore and understand the perspective or sentiments of Eastern Samar State University program heads towards supervision of instruction in the midst of the COVID-19 pandemic. Data were collected/collated from the participants indirectly using an interview questionnaire containing an open-ended question. The same were processed and analyzed using an open-source machine learning software called Orange toolbox (Demsar et al., 2013) wherein pre-processing, sentiment analysis and topic modelling built-in tools were utilized. The results showed that the most prominent words generated by the machine learning tool from the text file of responses are the words pandemic, performance, program, learning, difficult, supervision, instruction, internet, faculty, online students, teaching, delivery confusing, challenging, poor and connectivity. The dominant sentiment associated thereof lean towards negative polarity which implicate negative sentiments. Hidden topics were automatically generated by the machine which allowed the researchers to come up with the following related themes: “Impact of pandemic in the supervision of instruction of faculty and learning of students”, “Challenges in the delivery of instruction and supervision due to poor internet connectivity”, and “Strategic role of online modalities and connectivity in supervision and delivery of instruction”. There are limited researches navigating in text mining and sentiment analysis with the use of Orange toolbox particularly those that deals with supervision of instruction in a Philippine State University. There are related studies using machine learning software, but nothing like this study directed towards a specific gap in specific locale. KEYWORDS: Pandemic, Latent Semantic Indexing, Orange Toolbox, Sentiment Analysis, Thematic Analysis.

Artificial Intelligence & Machine Learning Role in Financial Services

2021 ◽  
Author(s):  
Prudhvi Parne
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Financial Services ◽  
Gold Mine ◽  
Short Period ◽  
The World ◽  
To Come ◽  
Financial Transactions ◽  
New Algorithms

Financial services are the economical backbone of any nation in the world. There are billions of financial transactions which are taking place and all this data is stored and can be considered as a gold mine of data for many different organizations. No human intelligence can dig in this amount of data to come up with something valuable. This is the reason financial organizations are employing artificial intelligence to come up with new algorithms which can change the way financial transactions are being carried out. Artificial Intelligence can complete the task in a very short period. Artificial intelligence can be used to detect frauds, identify possible attacks, and any other kind of anomalies that may be detrimental for the institution. This paper discusses the role of artificial intelligence and machine learning in the finance sector.

Review of Passions Within Reason: The Strategic Role of the Emotions.

1990 ◽  
Vol 35 (7) ◽  
pp. 729-730
Author(s):  
No authorship indicated
Keyword(s):  
Strategic Role

Formation of financial literacy in training of informatics teachers on the basis of the 1С:Enterprise system

2020 ◽  
Vol 1 (1) ◽  
pp. 11-18
Author(s):  
M. A. Rodionov ◽  
I. V. Akimova
Keyword(s):  
Financial Literacy ◽  
Basic Knowledge ◽  
State University ◽  
Science And Literature ◽  
Successful Development ◽  
Mathematics History ◽  
School Subjects ◽  
Personal Finances ◽  
The Right

In the submitted study the problem of the formation of financial literacy of students at informatics lessons and relevant training of future informatics teachers is considered. Financial literacy is understood as a set of basic knowledge in the field of finance, banking, insurance, as well as budgeting for personal finances that allow a person to choose the right financial product or service, soberly assess and take risks that may arise during the use of these products, correctly accumulate savings and identify doubtful (fraudulent) investment schemes. The authors conclude that successful development of meaningful lines of the course of financial literacy requires integration of a few school subjects, such as mathematics, history, informatics, social science and literature. The role of modern informatics teacher in the formation of financial literacy of students is great. Therefore, in the training of a future informatics teacher, it should be paid the attention to issues related to the study of elements of financial literacy in informatics lessons. In order to solve the problem, the authors propose to use the special course “Basics of work in 1С:Enterprise”, which is implemented at Penza State University. The article contains a program of the course and the methodological recommendations for its implementation.

Alignment

2016 ◽  
pp. 33-50
Author(s):  
Pier Giuseppe Rossi
Keyword(s):  
Teaching And Learning ◽  
Enactive Approach ◽  
The World ◽  
Strategic Role ◽  
Education Today ◽  
Current Context ◽  
The Subject

The subject of alignment is not new to the world of education. Today however, it has come to mean different things and to have a heuristic value in education according to research in different areas, not least for neuroscience, and to attention to skills and to the alternation framework.This paper, after looking at the classic references that already attributed an important role to alignment in education processes, looks at the strategic role of alignment in the current context, outlining the shared construction processes and focusing on some of the ways in which this is put into effect.Alignment is part of a participatory, enactive approach that gives a central role to the interaction between teaching and learning, avoiding the limits of behaviourism, which has a greater bias towards teaching, and cognitivism/constructivism, which focus their attention on learning and in any case, on that which separates a teacher preparing the environment and a student working in it.

Peran Bank Syariah: Menuju Perekonomian Masyarakat Madani

2019 ◽  
Vol 1 (2) ◽  
pp. 131-144
Author(s):  
Dini Maulana Lestari ◽  
M Roif Muntaha ◽  
Immawan Azhar BA
Keyword(s):  
Financial Markets ◽  
Islamic Law ◽  
Financial Service ◽  
Islamic Banks ◽  
Free Society ◽  
The Public ◽  
Turn On ◽  
The People ◽  
Strategic Role

Islamic banks are present in the community as financial institutions whose activities are based on the principles of Islamic law for the benefit of the people. This study aims to determine the strategic role of Islamic Banks as financial service institutions, the importance of the existence of Islamic Banks and Islamic-based markets and financial instruments in them. In its development, Islamic banks have a role as institutions that turn on public funds, channel funds to the public, transfer assets, liquidity, reallocation of income and transactions. In the Indonesian economic system, the existence of Islamic Banks is important as an alternative solution to the problem of conflict between bank interest and usury. Islamic financial markets and instruments provide a free society of interest and follow a different set of principles. Distribution of profit/ loss according to evidence of participation in the management fund. The division of rental income in the form of musharaka.

Exchange Spin Coupling from Gaussian Process Regression

2020 ◽  
Author(s):  
Marc Philipp Bahlke ◽  
Natnael Mogos ◽  
Jonny Proppe ◽  
Carmen Herrmann
Keyword(s):  
Machine Learning ◽  
Gaussian Process ◽  
Gaussian Process Regression ◽  
Molecular Magnets ◽  
Molecular Structures ◽  
Spin Coupling ◽  
Structure Property ◽  
Data Set ◽  
Uncertainty Estimates

Heisenberg exchange spin coupling between metal centers is essential for describing and understanding the electronic structure of many molecular catalysts, metalloenzymes, and molecular magnets for potential application in information technology. We explore the machine-learnability of exchange spin coupling, which has not been studied yet. We employ Gaussian process regression since it can potentially deal with small training sets (as likely associated with the rather complex molecular structures required for exploring spin coupling) and since it provides uncertainty estimates (“error bars”) along with predicted values. We compare a range of descriptors and kernels for 257 small dicopper complexes and find that a simple descriptor based on chemical intuition, consisting only of copper-bridge angles and copper-copper distances, clearly outperforms several more sophisticated descriptors when it comes to extrapolating towards larger experimentally relevant complexes. Exchange spin coupling is similarly easy to learn as the polarizability, while learning dipole moments is much harder. The strength of the sophisticated descriptors lies in their ability to linearize structure-property relationships, to the point that a simple linear ridge regression performs just as well as the kernel-based machine-learning model for our small dicopper data set. The superior extrapolation performance of the simple descriptor is unique to exchange spin coupling, reinforcing the crucial role of choosing a suitable descriptor, and highlighting the interesting question of the role of chemical intuition vs. systematic or automated selection of features for machine learning in chemistry and material science.

Sign in / Sign up

Export Citation Format

Share Document