Tag: <span>Learning</span>

25 Jun

Top Open Universities Offering Distance Learning PhD Programs in India

Distance learning PhD programs are gradually gaining importance among the employed academic community. Due to the establishment of quality online education facilities in India research scholars can now pursue teaching or academic jobs while studying. Deserving scholars generally give up further specialization mid way due to work pressures and the inability to attend regular college after a while. Quality distance research and doctoral courses have changed that.

Universities in India Offering PhD Distance Learning Programs

There are many such universities, offering doctorate degrees in various subjects:

Indira Gandhi National Open University (IGNOU)

Its main campus is located in Delhi/NCR region. All over India it has 67 centers, offering doctorate degrees in four streams – Education, Physics, Mathematics, and Tourism Studies.

Vardhaman Mahaveer University

Its main campus is located in Kota. This university is situated in 3 centers, offering doctorate programs in History, Economics and Commerce.

Nalanda Open University

Its main campus is located in Patna. All over India it has 6 centers, offering doctorate programs in Urdu, Hindi, Chemistry, History, Economics and Botany.

Dr.B.R. Ambedkar University (BRAOU)

This university’s office is situated in Hyderabad. Doctorate program on Development Studies can be pursued in Development Studies.

Dr. Babasaheb Ambedkar University

Office of this University is located at Ahmedabad. Enroll for online Phd courses at this popular university.

University of Petroleum and Energy Studies Distance Education

The main office of this university is located in Dehradun. It has 2 centers. PhD programs that can be done through distance learning mode include management and technology, science and engineering.

Alagappa University

It is located in Karaikudi, where people can pursue PhD in Biotechnology.

Institute of Management Technology

This is located in Ghaziabad and offers doctorate programs.

IGNOU

People can select their preferred subject in pursuing their research and submit their researched work to receive doctorate degree from Indira Gandhi National Open University (IGNOU). It is one of the most renowned open universities in India.

Let us check eligibility criteria of PhD program of this Open University:

A person should have got a minimum of 55% marks from a recognized university during post graduation on any of the following subjects with specialization in computers in education or Educational technology:

– Educational Technology

– Distance Education

– Education

– Instructional Design

In case of a SC/ST/Physically Handicapped (PH) candidate, minimum 50% marks is a must.

– M.Phil

– 5 year of professional / teaching / administrative experience in ODLI

Other details:

Fee of the IGNOU distance learning PhD program is Rs. 15000, to be paid in 3 annual installments of equal amount. Duration of the program can be anywhere between 2 and 5 years.



Source by Kali Pada Giri

07 Jun

Understanding Artificial Intelligence, Machine Learning and Deep Learning

Artificial Intelligence (AI) and its subsets Machine Learning (ML) and Deep Learning (DL) are playing a major role in Data Science. Data Science is a comprehensive process that involves pre-processing, analysis, visualization and prediction. Lets deep dive into AI and its subsets.

Artificial Intelligence (AI) is a branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence. AI is mainly divided into three categories as below

  • Artificial Narrow Intelligence (ANI)
  • Artificial General Intelligence (AGI)
  • Artificial Super Intelligence (ASI).

Narrow AI sometimes referred as ‘Weak AI’, performs a single task in a particular way at its best. For example, an automated coffee machine robs which performs a well-defined sequence of actions to make coffee. Whereas AGI, which is also referred as ‘Strong AI’ performs a wide range of tasks that involve thinking and reasoning like a human. Some example is Google Assist, Alexa, Chatbots which uses Natural Language Processing (NPL). Artificial Super Intelligence (ASI) is the advanced version which out performs human capabilities. It can perform creative activities like art, decision making and emotional relationships.

Now let’s look at Machine Learning (ML). It is a subset of AI that involves modeling of algorithms which helps to make predictions based on the recognition of complex data patterns and sets. Machine learning focuses on enabling algorithms to learn from the data provided, gather insights and make predictions on previously unanalyzed data using the information gathered. Different methods of machine learning are

  • supervised learning (Weak AI – Task driven)
  • non-supervised learning (Strong AI – Data Driven)
  • semi-supervised learning (Strong AI -cost effective)
  • reinforced machine learning. (Strong AI – learn from mistakes)

Supervised machine learning uses historical data to understand behavior and formulate future forecasts. Here the system consists of a designated dataset. It is labeled with parameters for the input and the output. And as the new data comes the ML algorithm analysis the new data and gives the exact output on the basis of the fixed parameters. Supervised learning can perform classification or regression tasks. Examples of classification tasks are image classification, face recognition, email spam classification, identify fraud detection, etc. and for regression tasks are weather forecasting, population growth prediction, etc.

Unsupervised machine learning does not use any classified or labelled parameters. It focuses on discovering hidden structures from unlabeled data to help systems infer a function properly. They use techniques such as clustering or dimensionality reduction. Clustering involves grouping data points with similar metric. It is data driven and some examples for clustering are movie recommendation for user in Netflix, customer segmentation, buying habits, etc. Some of dimensionality reduction examples are feature elicitation, big data visualization.

Semi-supervised machine learning works by using both labelled and unlabeled data to improve learning accuracy. Semi-supervised learning can be a cost-effective solution when labelling data turns out to be expensive.

Reinforcement learning is fairly different when compared to supervised and unsupervised learning. It can be defined as a process of trial and error finally delivering results. t is achieved by the principle of iterative improvement cycle (to learn by past mistakes). Reinforcement learning has also been used to teach agents autonomous driving within simulated environments. Q-learning is an example of reinforcement learning algorithms.

Moving ahead to Deep Learning (DL), it is a subset of machine learning where you build algorithms that follow a layered architecture. DL uses multiple layers to progressively extract higher level features from the raw input. For example, in image processing, lower layers may identify edges, while higher layers may identify the concepts relevant to a human such as digits or letters or faces. DL is generally referred to a deep artificial neural network and these are the algorithm sets which are extremely accurate for the problems like sound recognition, image recognition, natural language processing, etc.

To summarize Data Science covers AI, which includes machine learning. However, machine learning itself covers another sub-technology, which is deep learning. Thanks to AI as it is capable of solving harder and harder problems (like detecting cancer better than oncologists) better than humans can.



Source by Cinoy Ravindran

04 Jun

How Math Software in the Classroom Accelerates and Enriches the Learning Experience

Although the subject matter is practical, many students have trouble grasping mathematical concepts expressed in words without any visual math models to follow. Math software can help improve math skills by allowing them to practice with interactive visual elements that they can associate with complex concepts and numbers.

The best way to understand how software aids the comprehension of math concepts is by looking at how it applies to teaching fractions. Not all students instantly grasp the concept of solving fraction problems when presented in abstract form, for example: ½ + 2/3. Most teachers have difficulty teaching the topic due to the fact that fractions present a major conceptual leap for students. It helps to present them with visual fractions first, which allow them to see whole objects divided into equal parts.

By allowing them to transition from fraction models to solving abstract problems at their own pace, students will find that they have a deeper foundation in the subject, which will help them consolidate more complex concepts like mixed fractions and operations between fractions.

At the same time, visual math models are not the only way that educational software helps in the teaching process. Another way that math software helps is by providing the student with constant feedback. Unlike a teacher who collects dozens of papers and needs time to correct them, educational software spots mistakes instantaneously and does not let misunderstood concepts linger. With immediate and constant feedback, having the software aid the student can greatly speed up the learning process.

In addition, the software goes beyond telling what is right or wrong. Rather than telling the student to “Try again,” effective math software for teaching fractions and other mathematical concepts offers strategic feedback to target specific conceptual and procedural errors. Additionally, as educators would know, it doesn’t help to simply feed the answers to students. Effective educational software is also designed with this in mind, letting students figure out the answers on their own and reinforcing the correct method.

While software can be used as a tool for tutoring, it can also enrich any math curriculum. Math software suitable for classroom instruction should be able to record each student’s performance and allow teachers to make recommendations for advancement or remediation at a glance. This way, teachers can monitor students’ progress and assist them accordingly.

With the boom of interactive media and more and more time being spent on computers, students now also have a chance to learn though the same channels that they use for entertainment and to communicate with their peers. Using software to aid classroom instruction can make a great difference in how students pick up the concepts.



Source by Jack M Patterson

05 Jan

Gender Differences In Learning Style Specific To Science, Technology, Engineering And Math – Stem

There are gender differences in learning styles specific to science, math, engineering and technology (STEM) that teachers of these subjects should keep in mind when developing lesson plans and teaching in the classroom. First, overall, girls have much less experience in the hands-on application of learning principles in lab settings than boys. This could occur in the computer lab, the science lab, or the auto lab – the principle is the same for all of these settings – it requires an overall technology problem-solving schema, accompanied by use and manipulation of tools, and spatial relation skills that very few girls bring with them to the classroom on day one in comparison to boys.

Let’s look at some of the reasons why girls come to the STEM classroom with less of the core skills needed for success in this subject area. Overall, girls and boys play with different kinds of games in early childhood that provide different types of learning experiences. Most girls play games that emphasize relationships (i.e., playing house, playing with dolls) or creativity (i.e., drawing, painting). In contrast, boys play computer and video games or games that emphasize building (i.e., LEGO®), both of which develop problem-solving, spatial-relationship and hands-on skills.

A study of gender differences in spatial relations skills of engineering students in the U.S. and Brazil found that there was a large disparity between the skills of female and male students. These studies attributed female student’s lesser skills set to two statistically significant factors: 1) less experience playing with building toys and 2) having taken less drafting courses prior to the engineering program. Spatial relations skills are critical to engineering. A gender study of computer science majors at Carnegie-Mellon University (one of the preeminent computer science programs in the country) found that, overall, male students come equipped with much better computer skills than female students. This equips male students with a considerable advantage in the classroom and could impact the confidence of female students.

Are these gender differences nature or nurture? There is considerable evidence that they are nurture. Studies show that most leading computer and video games appeal to male interests and have predominantly male characters and themes, thus it is not surprising that girls are much less interested in playing them. A study of computer games by Children Now found that 17% of the games have female characters and of these, 50% are either props, they tend to faint, have high-pitched voices, and are highly sexualized.

There are a number of studies that suggest that when girls and women are provided with the building blocks they need to succeed in STEM they will do as well if not better than their male counterparts. An Introductory Engineering Robotics class found that while males did somewhat better on the pre-test than females, females did as well as the males on the post-test following the class’s completion.

Another critical area of gender difference that teachers of STEM should keep in mind has less to do with actual skills and experience and more to do with perceptions and confidence. For females, confidence is a predictor of success in the STEM classroom. They are much less likely to retain interest if they feel they are incapable of mastering the material. Unfortunately, two factors work against female confidence level: 1) most girls will actually have less experience with STEM course content than their male counterparts and 2) males tend to overplay their accomplishments while females minimize their own. A study done of Carnegie Mellon Computer Science PhD students found that even when male and female students were doing equally well grade wise, female students reported feeling less comfortable. Fifty-three percent of males rated themselves as “highly prepared” in contrast to 0% of females.

It is important to note that many of the learning style differences described above are not strictly gender-based. They are instead based on differences of students with a background in STEM, problem-solving, and hands-on skills learned from childhood play and life experience and those who haven’t had the same type of exposure. A review of the literature on minority students and STEM finds that students of color are less likely to have the STEM background experiences and thus are missing many of the same STEM building blocks as girls and have the same lack of confidence. Many of the STEM curriculum and pedagogy solutions that work for female students will also work for students of color for this reason.

Bridge Classes/Modules to Ensure Core Skills

Teachers will likely see a gap in the core STEM skills of female and minority students for the reasons described above. Below are some solutions applied elsewhere to ensure that girls and women (and students of color) will get the building block STEM skills that many will be missing.

Teachers in the Cisco Academy Gender Initiative study assessed the skill levels of each of their students and then provided them with individualized lesson plans to ensure their success that ran parallel to the class assignments. Other teachers taught key skills not included in the curriculum at the beginning of the course, such as calculating math integers and tool identification and use. Students were provided with additional lab time, staffed by a female teaching assistant, knowing that the female students would disproportionately benefit from additional hands-on experience.

Carnegie-Mellon University came to view their curriculum as a continuum, with students entering at different points based on their background and experience. Carnegie-Mellon’s new frame of a “continuum” is purposefully different than the traditional negative model in which classes start with a high bar that necessitates “remedial” tutoring for students with less experience, stigmatizing them and undermining their confidence. Below is a list of ideas and suggestions that will help ALL students to succeed in the STEM classroom.

1. Building Confidence

How do teachers build confidence in female students who often have less experience than their male counterparts and perceive they are behind even when they are not?

1) Practice-based experience and research has shown that ensuring female students have the opportunity to gain experience with STEM, in a supportive environment, will increase their confidence level.

2) Bringing in female role models that have been successful in the STEM field is another important parallel strategy that should be used to assist your female students in seeing themselves as capable of mastering STEM classes: if she could do it, then I can too!

3) Consistent positive reinforcement by STEM teachers of their female students, with a positive expectation of outcome, will assist them in hanging in there during those difficult beginning weeks when they have not yet developed a technology schema or hands-on proficiency and everything they undertake seems like a huge challenge.

2. Appealing to Female Interests

Many of the typical STEM activities for the classroom appeal to male interests and turn off girls. For example, curriculum in robots often involves monsters that explode or cars that go fast. “Roboeducators” observed that robots involved in performance art or are characterized as animals are more appealing to girls. Engineering activities can be about how a hair dryer works or designing a playground for those with disabilities as well as about building bridges. Teachers should consider using all types of examples when they are teaching and incorporating activities in efforts to appeal female and male interests. Teachers can also direct students to come up with their own projects as a way of ensuring girls can work in an area of significance to them.

Research also shows that there are Mars/Venus differences between the genders and how each engages in technology. Overall, girls and women are excited by how the technology will be used – its application and context. Men will discuss how big the hard drive or engine is, how fast the processor runs, and debate the merits of one motherboard or engine versus another. These are topics that are, overall, of less interest to most females.

The Carnegie-Mellon Study took into account the differences of what engages female students and modified the Computer Science programs’ curriculum so that the context for the program was taught much earlier on in the semester and moved some of the more technical aspects of the curriculum (such as coding) to later in the semester. Authors observed that the female students were much more positive about getting through the tedious coding classes when they understood the purpose of it. Teachers should ensure that the context for the technology they are teaching is addressed early on in the semester by using real world stories and case studies to capture the interest of all of their students.

3. Group Dynamics in the Classroom

Research studies by American Association of University Women and Children Now have found that most females prefer collaboration and not competition in the classroom. Conversely, most males greatly enjoy competition as a method of learning and play. Many hands-on activities in technology classes are set up as competitions. Robotics for example, regularly uses competitiveness as a methodology of teaching. Teachers should
be cognizant of the preference of many girls for collaborative work and should add-in these types of exercises to their classes. Some ways to do this are by having students work in assigned pairs or teams and having a team grade as well as an individual grade. (See Reading 2 on Cooperative Learning.)

Another Mars/Venus dynamic that STEM teachers should be aware of occurs in the lab there male students will usually dominate the equipment and females will take notes or simply watch. Overall, male students have more experience and thus confidence with hands-on lab equipment than their female counterparts. Teachers should create situations to ensure that their female students are spending an equal amount of time in hands-on activities. Some approaches have been: 1) to pair the female students only with each other during labs in the beginning of the class semester so that they get the hands-on time and their confidence increases, putting them in a better position to work effectively with the male students later on, 2) allot a specific time for each student in pair to use the lab equipment and announce when it’s time to switch and monitor this, and 3) provide feedback to male students who are taking over by letting them know that their partner needs to do the activity as well.

4. Moving Female Students from Passive Learners to Proactive Problem Solvers

The main skill in STEM is problem solving in hands-on lab situations. For reasons already discussed regarding a lack of experience, most girls don’t come to STEM classes with these problem-solving skills. Instead, girls often want to be shown how to do things, repeatedly, rather than experimenting in a lab setting to get to the answer. Adding to this issue, many girls fear that they will break the equipment. In contrast, male students will often jump in and manipulate the equipment before being given any instructions by their teacher. Teachers can address this by such activities as: 1) having them take apart old equipment and put it together again, 2) creating “scavenger hunt” exercises that force them to navigate through menus, and 3) emphasizing that they are learning the problem solving process and that this is equally important to learning the content of the lesson and insisting that they figure out hands-on exercises on their own.

Research has also shown that females tend to engage in STEM activities in a rote, smaller picture way while males use higher order thinking skills to understand the bigger picture and the relationship between the parts. Again, moving female students (and the non-techsavvy student in general) to become problem solvers (versus just understanding the content piece of the STEM puzzle) will move them to use higher order thinking skills in STEM.

Finally, many teachers have reported that many female students will often want to understand how everything relates to each other before they move into action in the lab or move through a lesson plan to complete a specific activity. The female students try to avoid making mistakes along the way and will not only want to read the documentation needed for the lesson, they will often want to read the entire manual before taking any action. In contrast, the male student often needs to be convinced to look at the documentation at all. Boys are not as concerned with making a mistake a long the way as long as what they do ultimately works. The disadvantage for female students is that they often are so worried about understanding the whole picture that they don’t move onto the hands-on activity or they don’t do it in a timely fashion, so that they are consistently the last ones in the class to finish. Teachers can assist female (and non-tech-savvy) students to move through class material more quickly by providing instruction on how to quickly scan for only the necessary information needed to complete an assignment.

5. Role Models

Since the numbers of women in STEM are still small, girls have very few opportunities to see female role models solving science, technology, engineering or math problems. Teachers should bring female role models into the classroom as guest speakers or teachers, or visit them on industry tours, to send the message to girls that they can succeed in the STEM classroom and careers.

Bibliography

Medina, Afonso, Celso, Helena B.P. Gerson, and Sheryl A. Sorby. “Identifying Gender Differences in the 3-D Visualization Skills of Engineering Students in Brazil and in the United States”. International Network for Engineering Eucation and Research page. 2 August 2004: [http://www.ineer.org/Events/ICEE/papers/193.pdf].

Milto, Elissa, Chris Rogers, and Merredith Portsmore. “Gender Differences in Confidence Levels, Group Interactions, and Feelings about Competition in an Introductory Robotics Course”. American Society for Engineering Education page. 8 July 2004: [http://fie.engrng.pitt.edu/fie2002/papers/1597.pdf].

“Fair Play: Violence, Gender and Race in Video Games 2001”. Children Now page. 19 August 2004: [http://www.childrennow.org/media/video-games/2001/].

“Girls and Gaming: Gender and Video Game Marketing, 2000”. Children Now page. 17 June 2004: [http://www.childrennow.org/media/medianow/mnwinter2001.html].

Tech-Savvy: Educating Girls in the New Computer Age. District of Columbia: American Association of University Women Educational Foundation, 2000.

Margolis, Jane and Allan Fisher. Unlocking the Computer Clubhouse: Women in Computer. Cambridge, MA: The MIT Press, 2003.

Taglia, Dan and Kenneth Berry. “Girls in Robotics”. Online Posting. 16 September 2004: http://groups.yahoo.com/group/roboeducators/.

“Cisco Gender Initiative”. Cisco Learning Institute. 30 July 2004: [http://gender.ciscolearning.org/Strategies/Strategies_by_Type/Index.html].



Source by Donna Milgram

12 Nov

Learning Good Study Habits

With many habits, the sooner you start practicing and developing good habits, the better chance you will have that you will continue with them. We all know that good study habits are essential to educational success. Good study habits are an important part of any student’s success. We probably can diminish the academic dishonesty by promoting good study habits with students, and letting the students know that good study habits are very important when it comes to school. Still, even procrastination can be overcome with proper study habits, and improving your study habits is the key to better studying. Good study habits are a great tool to have in the toolbox of life.

Many of the tips for success for online students are the same as those for students in an onsite classroom. Consider asking your school’s student council to take on a study tips project. Following a few simple study tips can help students effectively learn new concepts and theories. There have been numerous published tips students can use as a guide for good study habits.

A good way to stay organized is to use folders so you child can keep his/her assignments until needed and it is a great way of staying organized. Once children reach the grades where homework and tests are part of the curriculum, there are many things parents can do to encourage good study habits. An effective way to study is to study before and while you do the homework. A little amount of homework may help elementary school students build study habits. Being organized and having homework routines are the most important things in helping your child develop good study habits for life.

All learning, however, is a process which settles into certain steps. Students with learning problems, however, may still have generally inefficient and ineffective study habits and skills. Becoming aware of your learning style will help you to understand why you sometimes get frustrated with common study methods.

Effective study habits are a very import part of the learning process. Good study habits are all about keeping to a daily routine and giving all subjects equal treatment. If your study habits are weak, take a “study skills” course or have someone show you good study habits. The problem is that those high school study habits are hard to shake. Hard work and good study habits are assets that should be nurtured. Motivation and study habits are obviously crucial as well. Good habits are important for all students to protect investments of time and money and to achieve educational goals. After that experience your study habits are permanently altered, this will help your own preparation as you start teaching and last a lifetime. The main priorities are class attendance, time management, and great studying habits are necessary workings for an academic success.



Source by David Fishman

04 Oct

The Joy of Learning Mathematics

For many students, maths is a phobia at par with the fear of snakes, lizards, elevators, water, flying, public speaking, and heights. Though the “ailment” is neither genetic, nor infectious, they “inherit” it from their parents; and “catch” it from their friends. What are the reasons behind maths’ dreadful reputation that divides the society into mathematical “haves” and “have-nots”?

“One reason why students fare badly in Maths is that they are learning it mechanically, often not understanding what they are learning and they are unable to apply it to real-life situation,” says Vijay Kulkarni, the leader of the First Annual Status of Education Report (ASER) released recently by the well known Bombay-based non-governmental organization, Pratham.

Explaining the dismal scenario that the report portrays, especially about mathematics – forty two per cent of children between seven to ten years cannot subtract – Kulkarni says that the children are turned off, because the straitjacketed conventional teaching in classrooms has squeezed out the joy of learning, turning the schools into robotic factories.

Outdated teaching methods and an outdated curriculum – far removed from the students’ everyday experiences – contribute nothing to a student’s appreciation of the subject. Intelligence is often measured by the marks he gets in mathematics and his self confidence is eroded when he gets drubbed as dumb for scoring less in it.

Yet, taught the right way, learning mathematics can be easy, fun and can fill one with a sense of awe, with its inherently beautiful harmony and order. Both parents and teachers should convey the message that learning mathematics can be fun. Their expressions of interest, sense of wonder and enjoyment are critical to the child’s interest in the subject.

“Parents are the first mentors for a child. Even before the children can be formally admitted in pre-school kindergartens, they can start playing with numbers,” suggests Dr.MJ Thomas, a child psychologist in the city. Children are playful by nature and have irrepressible curiosity to explore the world through experimenting with the objects around them: see, touch, hear, taste, smell and arrange the objects, put things together or take them apart. Through such experience the children understand their world intuitively.

Dr. Thomas’ suggestions: collect beads of various colours and tell the kids to alternately string two beads of, say, two colours. Tell them to bring red and green balls and make two piles of equal number of balls. Another game could be to arrange playing cards in rows of three or four. These activities can enforce quantitative thinking and help make numbers our friend.

“While the other sciences have some amount of hands on activity included in the syllabus and the idea of a physics, chemistry or biology lab is common, maths is still taught only by the chalk and talk method,” says Dr. S.N.Gananath, recipient of Ashoka Fellowship for innovations in teaching activity-based mathematics. “This is particularly unfortunate as a subject like maths can be understood only when a child experiences, first-hand, the idea of weight and volume, shape and size, number and pattern,” he says.

Dr. Gananath has designed Maths Kits, with charts, diagrams and games, to explain various difficult concepts in Mathematics, like place-value, fractions or decimals. He takes a piece of paper, marks off lengths a and b and in minutes, by suitably folding the paper, arrives at formulas for (a+b) 2 and (a-b)2. Such activity-based teaching stimulates thinking, encourages discussion or search for alternate ways of solving problems. On the other hand traditional teaching in schools seems to give the impression that there is only one way to solve a given problem.

“Learning does not mean simply “knowing” facts; but understanding the underlying concepts that are anchored in experience,” says H.N.Parmesh, head-master of Born Free, a government school in the village of Banjarpalya, off Banaglore-Mysore road. His school has the rare distinction of all the students securing first-class in the VII standard public examination for several consecutive years. Parmesh and his team of dedicated teachers have used inexpensive materials like match-boxes and coloured beads made of baked clay to make educational aids that they affirm have helped the slow learners to understand maths better.

Several organizations like the Akshara Foundation and the Azim Premji Foundation, with support from corporate bigwigs, have collaborated with the government and used computers to capture the bored rural children’s attention, and spur their curiosity and imagination. However, using computer effectively to support teaching is no easy task. It needs good planning and design; otherwise it may end up as an expensive replacement for rote learning, if all it does is to replace dull text with colorful animations.

IT can be innovatively used to usher in interactive learning, as has been attempted by Oracle Education Foundation, which has designed a web-based educational environment – think.com for teachers and students in Bangalore, and elsewhere. This has enabled students and teachers to create personal Web pages and communicate or discuss with each other through message boards and e-mails. The website has made the students more creative and the teachers more responsive and accessible to students.

Games and puzzles are a sure way to aid learning. As children, we have asked each other the puzzle: a goat, a tiger and a bunch of grass should be transported across a river through a boat which can carry only one of the three at a time. Given that the goat will eat the grass and the tiger will eat the goat if left alone, how would you take them across one by one and save their lives? There is a similar exercise in logical thinking in the classic example of a village with two tribes – one which always speaks the truth and the other always tells lies. When you reach a point where the road forks into two paths, with one leading to treasure and the other to death, you see a member of each tribe. If you are permitted to ask only one of them a single question, who will you ask and what will you ask, so as to get the treasure?

Puzzles like this will initiate a lot of discussion. And the lessons learnt will not be easily forgotten; they will be applied when a similar situation occurs.

Learning must be guided by generalized principles in order to discover strategies for problem solving. Knowledge learned through rote memory rarely transfers to new, even though similar, situations.

Teacher-centric classrooms where teacher dominates the scene should soon become a thing of the past. Teachers should be facilitators of learning; they should stimulate thinking, which would lead to self-discovery, so that the child experiences the sheer joy of learning.



Source by Uma Shankari

25 Sep

Regular Courses VS Distance Learning MBA

Everyone knows that education plays a important role in our life. We learn from education more things that we use in our life. But it’s only a basic education that teaches us how to live in a decorous manner. But after basic education, we go forwards to higher education. Some of us want to jobs and some looking for higher education. But good jobs get only those people who have a higher educational degree like MBA programs. Presently, we can get higher education in two ways- regular mode and distance learning mode. In regular classes, we can get a good quality education, but at that time we can’t do any other work, I mean jobs and other professional business. So this mode of education learning is not so much good for working people. In such case they have to leave their jobs for attending regular classes. And mostly in India, there will be limited seats in regular courses and a very high competition in such courses like Executive MBA. While in distance learning mode like correspondence learning among the professionals is very popular. Because they don’t need to leave their jobs and easily can get a higher degree like distance learning MBA.

But in this mode there is lack of interaction between faculty and students. So this mode is applicable only for sharp minded students and those able to study themselves. And they are able to find solutions themselves.

In such cases we can say this mode is also not so good for less than average knowledge students. But to remove these constraints of distance learning academic intellectuals searched a new way- “Online Education”. We can say it has created a new revolution in the field of distance learning. In this mode you can take classes like a real regular class in your home and at your flexible time. So we can say for online MBA programs, you can do it with your job and after completion of it you can achieve a higher education degree and promote your self in your business fields.



Source by Dinesh Rohila

10 Sep

Learning Energizes Your Brain To Learn More

Have you ever wanted to learn about something but didn’t know how? You’re not alone. For every question, there is usually an answer; it’s merely a matter of discovering the most appropriate avenue of access that will lead you to an explanation. Sometimes it’s a short road, other times it can seem like the never-ending highway to bewilderment.

Deciphering conscious thought is a more complex process than you might imagine. For the brain to input new quantities of information, an entire series of biological connections have to occur. Those connections are transmitted via electrical impulses called neurons. Explaining how conscious thoughts arise from electric signals is something numerous scientists are still trying to learn.

Not as simple as it seems, considering the brain is considered “the most complex object in the known universe,” according to Christof Koch, Chief Scientific Officer of the Allen Institute for Brain Science. Koch is one of many researchers diligently working on uncovering the mystery of how the brain connects its 100 billion neurons to perform the myriad of daily conscious activities we all experience.

Neurological Landscape Of The Brain Constantly Expanding

Science is now trying to explain questions about the brain that analytical thinking has not been able to answer. Koch compares studying the brain to examining the rainforest. With the amount of biological diversity found throughout a tropical jungle, new generations of scientific investigators continually discover new and uncharted territories. And again, the universe expands, presenting new questions and providing new observations.

It is much the same with our brain. As exploratory tools evolve, so too, does our capacity to analyze and understand the complexities within our brain. Neurologists have uncovered possibilities previously unknown, such as humans possessing 1,000 different types of nerve cells, just as there are 1,000 different species of trees in the rainforest.

Understanding how things work, reflecting on why they are, theorizing about possible explanations for unclear experiences, then experimenting to either prove or disprove a theory is referred to as the learning cycle: Experiencing > Reflecting > Theorizing > Experimenting. This scientific interpretation of the learning process may seem overly simplistic, but nonetheless represents the cognitive steps that occur when we learn.

What Learning Style Are You?

Keep in mind these actions happen must faster in the deep unexplored recesses of the brain than in the relative surface-level awareness of the conscious mind. Learning time can vary based on experiential differences; reflections may emerge quicker if the brain recognizes a previous related experience; theorizing can become more efficient if a reflection mirrors a previous action, and experimentation could be minimized given the cycle is familiar.

In other words, we learn as a result of previous learning.

D.A. Kolb, Ph.D. in social psychology from Harvard University, condenses the learning process into what has become known as the Four Learning Styles: Divergers are people who analyze experiences and think deeply about them; Convergers conceptualize experiences then give them the practicality test; Accomodators like to ‘do’ rather than ‘think’, and Assimilators prefer to think rather than act… they prefer collecting information over excessive experimentation.

Attempting to decipher the mysteries of the brain without reflecting on our past experiences to do so, would be short-changing the very learning process we are seeking to unravel.



Source by Gary G Sweet

15 Jul

Intricacies of Machine Learning in Data Science

Machine learning served as APIs

Machine learning is no longer just for geeks. Nowadays, any programmer can call some APIs and include it as part of their work. With Amazon cloud, with Google Cloud Platforms (GCP) and many more such platforms, in the coming days and years we can easily see that machine learning models will now be offered to you in API forms. So, all you have to do is work on your data, clean it and make it in a format that can finally be fed into a machine learning algorithm that is nothing more than an API. So, it becomes plug and play. You plug the data into an API call, the API goes back into the computing machines, it comes back with the predictive results, and then you take an action based on that.

Machine learning – some use cases

Things like face recognition, speech recognition, identifying a file being a virus, or to predict what is going to be the weather today and tomorrow, all of these uses are possible in this mechanism. But obviously, there is somebody who has done a lot of work to make sure these APIs are made available. If we, for instance, take face recognition, there has been a plenty of work in the area of image processing that wherein you take an image, train your model on the image, and then finally being able to come out with a very generalized model which can work on some new sort of data which is going to come in the future and which you have not used for training your model. And that typically is how machine learning models are built.

The case of antivirus software

All your antivirus software, typically the case of identifying a file to be malicious or good, benign or safe files out there and most of the anti viruses have now moved from a static signature based identification of viruses to a dynamic machine learning based detection to identify viruses. So, increasingly when you use antivirus software you know that most of the antivirus software gives you updates and these updates in the earlier days used to be on signature of the viruses. But nowadays these signatures are converted into machine learning models. And when there is an update for a new virus, you need to retrain completely the model which you had already had. You need to retrain your mode to learn that this is a new virus in the market and your machine. How machine learning is able to do that is that every single malware or virus file has certain traits associated with it. For instance, a trojan might come to your machine, the first thing it does is create a hidden folder. The second thing it does is copy some dlls. The moment a malicious program starts to take some action on your machine, it leaves its traces and this helps in getting to them.



Source by Shalini M

12 Jun

Significance Of Equivalent Fractions In Math Learning

Basic math skills are one of the keys to succeed in math. To study basic math, students need to learn fractions as the major part of arithmetic and hence, as the basic math. To learn fractions, they can be divided into many subsections. One most basic subsection in fraction study is the equivalent fractions. Students need to know two main things about the equivalent fractions and they are their definition and their applications to other sections of fractions and mathematics.

The definition:

When two factions have the same value then they are called the equivalent fractions. Note that, these fractions have different numerators and denominators, but still represent the same part of a whole or a group of things.

Let’s take an example of two equivalent fractions from a daily life activity. Consider Ron and Billy are two brothers and Ron likes cheese pizza and Billy likes pepperoni pizza.

Their mom makes two pizzas of same size for them, cheese for Ron and pepperoni for Billy. Ron likes to eat small slices, so mom cuts his cheese pizza into six equal slices. Billy doesn’t care about the size of the slice so mom just cuts pepperoni pizza into four big slices.

Now, Billy eats two slices out of all four slices of pepperoni pizza and hence he eats “half” of his pizza which can be written as a fractions of “2/4”. Ron gets hungry and he eats three slices of his cheese pizza and which can be written as 3/6. But, 3 out of 6 slices is also “half”. So, Ron eats half of his pizza too.

So both boys eats same amount of each pizza, which is half. But Ron’s amount is 3/6 of his pizza and Billy eats 2/4 of his pizza, but both of them eat equal amount of a pizza which is half. Therefore, 2/4 and 3/6 are the equivalent fractions, as they represent the same amount of pizza eaten by two persons.

You can pick any other similar example to explain it further to kids, such as, two same sized apples cut into two and four equal pieces. Many sites online have more ideas about the concept and can be used to improve the knowledge of kids in this basic math skill.

Applications in math:

Equivalent fractions have many applications to learn higher fractional topics. There are the following main fractional topics, which need the knowledge of equivalent fractions as a base:

1. To simplify fractions into lowest terms
2. Comparing and ordering fractions
3. Adding and subtracting fractions

Therefore, kids need to know equivalent fractions before they want to learn above topics of fractions. Therefore, it is the best idea to review your kids knowledge of this topic before asking him/her to do the higher math topics.

As a conclusion, kids in elementary grades need to know the definition and the applications of equivalent fractions to learn higher math or arithmetic concepts. Kids can start learning this skill as soon as they get the basic idea of writing fractions or drawing fractions. Also most kids in grade three learn this skill.



Source by Manjit Singh Atwal