Tag: <span>learn science</span>

17 Oct

Language – The Core of Science
Posted in Education by anshbookstore on October 17, 2021 @ 7:58 pm

We live in a world of science, the most profound force changing our lives. Language is closely linked to the intelligence of mankind. It is employed to explain and convey science, with scientific writings being records of sciences. Language itself is considered no science. However, in my recent article “independence of written language from the non-textual world” we noted that the texts are part of science. We mentioned the world can be re-explained. Now, let’s start re-explaining the world from discussing “writing as part of science”. Herein, as always, we consider written language the essential form of language.

Principle of investigation

We treat texts as independent visual information, capable of forming part of science, instead of as representations of science.

We consider science as collections of sensory information, mostly what we see. Science is divided into textual portion and non-textual (visual and non-visual) portion. Investigations are carried out on the characteristics of the information, and the effect and contribution of the information on the senses and the mind. We examine the properties of texts and reading to know what roles texts play in science.

Common properties of science and written language

Being an infinite empire, sciences have a few key properties. We can see many commonalities between the key properties of written language and science. Below list some of them. These qualities are not possessed by non-texts, at least not so genuinely. That suggests texts lie in the heart of science. They give science its core properties; and laid the foundation for all sciences.

1. Sequential: Sequential texts permit cause-result reasoning. They also form procedures. Scientific methods emphasize procedure, in which things are conducted step by step.

2. Clarity: This makes us “see things” more clearly. Even though phenomena themselves are not clear, the texts describing them are fit for seeing. Because of this, science possesses the power of diving into the details and “invisible parts” of things. Researchers strived to see things clearly, e.g. with microscopes and telescopes. What they are doing in fact, is to generate visual information visible to their eyes.

3. Compactness and simplicity: Scientists always strive to make simple descriptions of knowledge. Breaking down complex things into simpler elements is a key spirit of science, as repeated experimental observations can be codified into combination of symbols.

4. Organized and systematic: Because of textual arrangements, science becomes organized and systematic.

5. Rigor: There are established rules for the formation of words, sentences, paragraphs and books. That contributes to the rigor of science.

6. Cumulative and branched: New theories are usually based on or derived from existing theories. Accumulation occurs by means of citing, modifying, editing, and expanding existing scientific writings. Accumulation of the sciences also necessitates divisions into various disciplines and branches, which are laid out by texts.

7. Integrated and interconnected: Due to the symbolic connections and organizations in texts, the infinite growth of sciences doesn’t result in disarray since they have texts to center on. Sciences are glued together with relations between them established. Interdisciplinary fields are also developed in between.

8. Stable and memorizable: Due to simplicity, clarity and sequential properties, writings remain stable during the accumulation process. Existing sciences are unchanged when new phenomena emerge. During expansion, sciences need to be memorized for use, which is facilitated by texts.

9. Predictive: Associations between non-texts and texts are somewhat arbitrary, variable and expandable. A literate mind is equipped with texts to analyze new phenomena and make new associations. In this way, science is said to predict the future.

10. Representational and explanatory: Science represents things and explains why things are and how things work. The most useful for explaining are the texts, figures, diagrams, books, and papers. For complex scientific thinking, literates are not sure until they can explain their thoughts in texts. The explanatory nature of language and writing might have been overlooked.

Texts: the foundation of a scientific mind

Scientific publications describe theories and findings. The descriptions form the centerpiece of scientific thought. Scientific texts organize; empower our mind to work out solutions. When we think about solutions, we imagine the symbols, lines, curves, and shapes, to depict what we study [1]. Scientific thinking takes effect via reasoning on the texts [2], by means of fixating, contradicting, moving, searching, comparing, organizing, etc. Without texts, we cannot truly understand science. We read them to learn science. They inject science into our minds, where it takes effect.

During research, scientists read extensively. During and after the reading, they actually are performing scientific thinking based on texts. Scientists write to create science. They publish to spread science.

This notion can obviously be applied to science and technology in a broad sense. Social sciences, applied sciences, technology, engineering, and so forth all bear the very essence of science: text-centered. The qualities of texts and reading also have to do with almost all other fields, such as law and history. The endless expansion of texts has commonized the mental forms of many seemingly unrelated disciplines, all of which share text-based scientific properties. People’s daily life is filled with texts. Even though many of the texts are not science oriented, they enrich people’s minds with scientific qualities.

Texts and non-texts in science

The texts have association with non-texts to form the whole of science. Non-texts are the purposes, resources, material and occurrences of science. Sciences are defined and categorized according to the characteristics of non-texts. Usually, the textual core is not the goal, but the means. Via connection with the textual mind, non-textual goals are achieved. The overwhelming non-texts could even undermine texts’ visibility and realness, not to mention its central status in science. Indeed, what we are proposing is not to reject the dominance of non-texts as sensory information, but that such dominant information becomes scientific due to their association with texts.

Many words have multiple meanings in diverse disciplines, for science and non-science. We need to read sentences and paragraphs to know the exact meaning. Reversely, a theory might be described in numerous ways. The texts look casual, subjective, and variable, contradicting the formal, objective and fixed properties of science. In fact, there is no conflict. Such properties are reached by individual minds’ processing of enormous texts originating from visual encounters.

Conclusion

Science encompasses an extremely vast collection of information, textual and non-textual. Texts’ visual features and the characteristics of reading reflect key properties of science, suggesting scientific writings are the central part of science. The texts provide people with the visual information to study, remember, process, and search, building a scientific foundation in the mind.

Two years ago, I had discussed the significance of the textual mind, which supports science. Now, we go a step further to consider texts as the core of the powerful sciences, incorporating the texts into science. That can form a new basis for analysis of the science or text-related world.

[1] Diagrams, figures are contained in scientific texts to assist describing. They are additions to symbolic dimension of texts. Still, letters and words are usually part of formula and embedded into diagrams and figures.

[2] In literate minds, texts are activated when we analyze non-textual objects. New texts, even new theories can be produced this way. The literates might not know the underlying force come from the texts in mind.



Source by Charley Pein

17 Sep

Best Place to Learn Data Science in Canada
Posted in Education by anshbookstore on September 17, 2021 @ 7:43 pm

Data Science is the Future.

The internet has almost single-handedly changed the lives of every person around the world. This paradigm shift has made data the most important aspect of our lives. No one can imagine getting through a single day without using data. Some economists have even stipulated data as the fuel of the future.

Since data has become one of the most important assets of the modern world, it should come as no surprise that data science is a career with great potential for the future. There is a high demand for its courses now, and achieving a certain level of finesse can exponentially boost your career opportunities.

Data Science Canada is one of the Best Choices.

If you are one of the people aiming to make it your area of expertise for the future, then there are limitless opportunities right now. Several organizations and institutes offer both physical and online classes. The number of online classes might be too high for you to choose from. In the past couple of years, it has gained quite a bit of popularity, resulting in many places that offer decent its courses in Canada.

Since there are many choices when it comes to learning the courses, you must choose the best one. Data science involves a lot of basic coding using the languages you are most comfortable with, so it becomes almost impossible to differentiate between courses and advanced coding lessons. Try to check if your course is progressing towards machine learning as it has now become an important part of data science.

Toronto is Developing more Courses.

There is a high demand for such courses all over the globe right now, so most of the places are developing excellent courses for interested students. Data science is practically a new field, so the course is being updated every day, and the understanding of the field is evolving with time. So, unlike other courses, there cannot be a simple template for the lessons followed by the other institutes. Every place that offers a course has to be always technologically capable of incorporating the advancements required for the course.

Toronto has been making quite a few developments when it comes to lessons for data science. The infrastructure in various institutes has been greatly improved to offer a technologically advanced place for the training.

Aspects of Data Science

The field is much wider than it sounds, so there are different aspects of it you will need to master to achieve some expertise in the field. Every place where a the course is offered, some of the most popular aspects are machine learning, SQL, and artificial intelligence, among many others. So it is clear that there are many concepts you will need to familiarize yourself with if you want to progress with it as a career. These are not optional but necessary as it deals with all the relevant information you can extract from unstructured data using mathematical and statistical techniques.



Source by Shalini M

18 Aug

What is Scientific Inquiry?
Posted in Education by anshbookstore on August 18, 2021 @ 7:27 pm

Scientific inquiry requires students to use higher order thinking skills as they learn science using a hands-on minds-on approach. Inquiry’s foundation has its roots in John Dewey’s book Democracy in Education (1916). In this book he describes how true learning begins with the curiosity of learners.

Defining Scientific Inquiry

His research found that student curiosity and involvement real science investigations moves students from passive learners to active learners. This is evidenced when students:

  • ask questions during an investigation
  • design their own investigations
  • conduct investigations using their design
  • formulate explanations of findings
  • present their findings
  • reflect upon their findings

Scientific inquiry causes a fundamental change in science education, moving it away from traditional teaching practices of lecture and demonstration to a collaborative relationship between teacher and student. In these collaborative environments, students take risks without fear of ridicule and begin to think about science. Teachers become facilitators of their student’s inquiry by:

  • modeling and immersing their students in scientific inquiry
  • ask guiding questions which provoke thought and reflection
  • allow student creativity in experimental design
  • allow students to discover experiments can be successful, yet fail to answer the original question being investigated

Initial confusion by students analyzing experimental findings is not necessary bad, because they are using critical thinking processes. Confusion is good in this setting, because it demonstrates students are trying to determine why they did not find the typical canned answer. Also, a hypothesis can actually result in a non-support statement as a result of the experiment.

Too often students investigate canned labs which result in a guided hypothesis which can only result in supported finding. This leads them to feel when their experiment does not support their hypothesis they failed. They have not failed, however they do not know this in traditional science teaching.

Scientific Inquiry Involves Asking Questions

Student success designing experiments is based on asking the right questions. They need to develop questions which do not lead to yes/no or true/false answers, because the best questions are open-ended and inquiry-based. As students analyze evidence to explain findings, open-ended questions provide the answers they need to formulate meaningful explanations.

Answering questions in a student’s own words is important for higher level of thinking and knowledge. A student’s own words disclose level of understanding and reveal misconceptions based on prior knowledge and experiences.

Impact of Using Scientific Inquiry

When students make personal connections when using scientific inquiry, internalization of the new knowledge takes place. The key attributes of scientific inquiry-based teaching and learning result in students:

  • learning how to design research
  • learning how to ask questions
  • internalizing new knowledge
  • realizing findings depend on experimental design
  • increasing their level of understanding of science
  • learning to investigate like scientists



Source by David Wetzel

19 Jul

Data Science Course – Learn From Skilled Professionals and Master the Art of Data Science
Posted in Education by anshbookstore on July 19, 2021 @ 7:12 pm

Data Science is a fast-evolving technology field that offers numerous benefits for businesses and organizations. The storage and processing of data are the two main challenges faced by organizations. To overcome these challenges, the field of data science was originated.

It is a mixture of several algorithms and visualization tools that can be used to derive meaningful insights from unprocessed data. The main agenda is to discover hidden patterns in raw data.

The processing is done by professional data scientists analyzing from different perspectives and using machine learning algorithms to derive conclusions. To become a highly skilled data scientist, the data science course Africa is considered the best option to gain a deep insight.

Why is Data Science Needed?

In today’s world, data is available everywhere abundantly. Efficient frameworks have also been evolved to store abundant data and use it whenever needed. But the storage of abundant data has led to data explosion. Therefore, the storage alone does not bring in benefits. It’s the processing that matters.

Since abundant data is available, the team can use several tools and algorithms to develop the desired results for the organization.

For example, if a particular organization decides to host a survey to collect user feedback about a particular product, a large amount of data will be collected and stored. This large amount of data can be processed and analyzed using different techniques provided by data science. Using this technique, meaningful conclusions can be generated, and the organization can improve the product.

To master the art, a data science course in Cape Town is extremely beneficial as you can get hands-on experience that is essential for your career.

Essential Skills to Acquire for the Role of Data Scientist:

The field is boundless with a wide range of concepts and principles. This field consists of numerous applications as it is the future of Machine Learning and Artificial Intelligence (AI). Therefore, there is a huge need for skilled data scientists and professionals who are aware of the importance of this field.

Given below are some skills to be mastered to excel in this field.

  • Master your Basics: As beginners, it is extremely important to learn the basics. Without basic knowledge about the field, practical implementation would be difficult.
  • Sharpen your Programming Skills: Programming is yet another important skill to acquire to apply the different techniques effectively. R and Python are the most popular languages used in data science.
  • Statistical Skills: To derive meaningful insights from raw data and to build models, statistics is important. Basic knowledge of concepts like mean, median, mode, variance, normal distribution, etc., is mandatory.

In addition to the above-mentioned skills, there are many other domains to master to become a skilled data scientist. However, it is not mandatory to master all the domains. One should be an expert in at least one of the domains.



Source by Shalini M