What is Philosophical Research?

Meaning of Philosophy:

There are three conceptions of philosophy. These are the following: 

1. Philosophy as Wisdom: Philosophy as thoughtful response to a question or situation. It is of two types :

                                i.            Personal reflection on broad questions

                             ii.            Prophetic wisdoms

2. Philosophy as Ideology:  It is a more highly organized body of opinion. It usually

serves programs of action and organizational needs.

3. Philosophy as Critical Inquiry: It treats knowledge as tentative. It is a method, not personal authority that establishes truth; it does not encourage us to become followers. Each person is required to think for himself/herself.

Emmanuel Kant ascribed a “critical” function to philosophy that is inquiry. Philosophical inquiry is reflection upon human experience in order to decipher the fundamental principles of reality and principle of existence itself.

Methodology of Philosophical Research:

The educational researches are designed to achieve following four objectives:

• To formulate new theory, principles and laws
• To establish new truth or reality
•  To find out new facts
•  To suggest new applications.

These objectives are achieved by conducting Historical, Experimental Surveys, and Philosophical Researches.

Major Approaches in Philosophical Research:

·         A System of Thought

·         A Critical Appraisal of the Thought of Great Personage

The philosophical inquiry is usually made at least into these following areas:

• Logic
• Metaphysics
• Epistemology
• Psychology
• Ethics
• Theodicy
• Aesthetic.

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What is Correlation coefficient?

To understand how to study the relationship between two variables when both are quantitative, one needs a basic understanding of a correlation coefficient.

Correlation is the relationship between two or more paired variables or two or more sets of data. The degree of relationship is measured and represented by the coefficient of correlation.

It is a numerical index that provides information about the strength and direction of the relationship between two variables. It provides information about how two variables are associated.

More specifically, a correlation coefficient is a number that can range from -1 to 1, with zero standing for no correlation at all.

Positive Correlation:

If the number is greater than zero, there is a positive correlation. (A positive correlation is present when scores on two variables tend to move in the same direction).

Negative Correlation:

If the number is less than zero, there is a negative correlation. (A negative correlation is present when scores on two variables tend to move in opposite directions—as one variable goes up, the other tends to go down and vice versa)

No Correlation:

If the number is equal to zero, then there is no correlation between the two variables being correlated.

Perfect Correlation:

If the number is equal to +1 or equal to -1, the correlation is called perfect; that is, it is as strong as possible.

Data analysis for Correlation Research:

Pearson product-moment—when you have two interval or ratio scale variables

Spearman—when variables are at least ordinal

Multiple correlation—relationship between one variable and a set of variables

Canonical correlation—relationship between two sets of variables

Partial correlation—correlation of one variable with another after statistically removing the effects of a third variable

Coefficient of determination—squared correlation—explains the variability in the first variable (proportion of variance accounted for)

Spurious correlation—significant correlation between two variables that is likely due to coincidence, i.e., there is no obvious reason why the two variables should be correlated but they are. 

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What is Correlational Research?

Correlational Research

Correlational Research is a non-experimental research method. In this research method, there is no manipulation of an independent variable. 

In correlational research, the researcher studies the relationship between one or more quantitative independent variables and one or more quantitative dependent variables; that is, in correlational research, the independent and dependent variables are quantitative.

Also Read: What is Correlation coefficient?

It is important to stress that correlations refer to measures of association and do not necessarily indicate causal relationships between variables.

Mouly puts it like this: “The correlation simply implies concomitance; it is not synonymous with causation. It may suggest causation in the same sense that the variables involved are part of a cause and effect system, but the nature of the system and the direction in which the components operate is not specified in the correlation. The two variables are not necessarily (or perhaps even commonly) the cause and effect of each other. The correlation between X and Y is often nothing more than the reflection of the operation of a third factor.”

When correlational research is appropriate:

Correlational research is appropriate in the following two instances:

First, it is appropriate when there is need to discover or clarify relationships and where correlation coefficients will achieve these ends. It is especially useful in this connection in the initial stages of a project where a certain amount of basic groundwork has to be covered to get some idea of the structure of relationships. In this way, it gets at degrees of relationships which may become a source of hypotheses and further research.

The correlational approach is also valuable when variables are complex and do not lend themselves therefore to the experimental method and controlled manipulation. It also permits the measurement of several variables and their relationships simultaneously in realistic settings.

Second, correlational research is appropriate where objective, or one of a set of objectives, is to achieve some degree of prediction. (prediction studies are appropriate where a firm basis of previous knowledge is present, the assumption being that at least some of the factors will relate to the behavior to be predicted).

Advantages of Correlational Research:

Correlational research is particularly useful in tackling the problems of education and social sciences because it allows for the measurement of a number of variables and their relationships simultaneously.

The experimental approach, by contrast, is characterized by the manipulation of a single variable and is thus appropriate for dealing with problems where simple causal relationship exist.

In educational and behavioral research, it is invariably the case that a number of variables contribute to a particular outcome. Experimental research thus introduces a note of unreality into research, whereas correlational approaches, while less rigorous, allow for the study of behavior in more realistic settings.

Correlational research yields information concerning the degree of relationship between the variables being studied. It thus provides the researcher with insights into the way variables operate that cannot be gained by other means.

Limitations of Correlational Research:

Correlational research only identifies what goes with what—it only implies concomitance and therefore does not necessarily establish cause-and-effect relationships.

It is less rigorous than the experimental approach because it exercises less control over the independent variables. It is prone to identify spurious relation patterns. It adopts an atomistic approach.

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Experimental, Non-experimental, Descriptive, & Causal-comparative Research

Experimental research:

It is the research in which the researcher manipulates the independent variable and is interested in showing cause and effect.

The purpose of experimental research is to determine cause-and-effect relationships. The experimental research method enables us to identify causal relationships because it allows us to observe, under control conditions, the effects of systematically changing one or more variables.

Non-experimental research:

In non-experimental research, there is no manipulation of an independent variable. There is also no random assignment to groups by the researcher.

As a result of these two deficiencies (no manipulation and no random assignment), evidence gathered in support of cause-and-effect relationships in non-experimental research is severely limited and much weaker that evidence gathered in experimental research.

If the researcher wants to study cause and effect, he/she should try to conduct an experiment, but sometimes this is not feasible. When important causal research questions need to be answered and an experiment can’t be done, research must still be conducted. In research, we try to do the best we can.

For example, during the 1960s, extensive research linking cigarette smoking to lung cancer was conducted. Experimental research with humans was not possible because it would have been unethical. Therefore, in additional to experimental research with laboratory animals, medical researchers relied on non-experimental research methods for their extensive study of humans.

Descriptive Research:

A descriptive study describes and interprets what is. It is concerned with conditions or relationships that exist, opinions that are held, processes that are going on, effects that are evident, or trends that are developing.

Descriptive study deals with the relationships between variables, the testing of hypotheses, and the development of generalizations, principles, or theories that have universal validity.

Descriptive study is sometimes divided into correlational research, causal-comparative research, and other descriptive research that is neither correlational nor designed to find out causation but describes existing conditions.

In carrying out a descriptive research project, in contrast to an experiment, the researcher does not manipulate the variable, decide who receives the treatment, or arrange for events to happen. Descriptive research also involves events that have already taken place and may be related to a present condition.

Descriptive research seeks to find answers to questions through the analysis of variable relationships. What factors seem to be associated with certain occurrences, outcomes, conditions, or types of behaviors?

Because it is often impracticable or unethical to arrange occurrences, an analysis of past events or of already existing conditions may be the only feasible way to study causation. This type of research is usually referred to as ex-post facto or causal-comparative research or, when correlational analyses are used, as correlational research.

Causal-comparative research:

In causal-comparative research, the researcher studies the relationship between one or more categorical independent variables and one or more quantitative dependent variables.

Because independent variable is categorical (that is males vs females, parents vs non-parents, or public school teachers vs private school teachers), the different group’s average scores on a dependent variable are compared to determine whether a relationship is present between the independent variable and dependent variable.

Despite the presence of the word causal included in the term causal-comparative research, one must keep in mind that causal-comparative research is a non-experimental research method, which means that there is no manipulation of an independent variable by a researcher.

Because of lack of manipulation and weaker techniques of controlling for extraneous variables, it is much more difficult to make statements about cause and effect in causal-comparative research than in experimental research.

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What are various types of Variables?

Types of Variables:

Before explaining the types of variables, let's understand first the concept of variable and constant in educational research. Then after, we will discuss the types of variables.  

Variable:

A variable is a condition or characteristic that can take on different values or categories. A much-studied educational variable is intelligence, which varies from low to high for different people. Age is another variable.

Constant:

A constant is a single value or category of a variable. The variable gender is a marker for two constants: male and female. The category (that is constant) male is a marker for only one thing; it is one of the two constants forming the variable called gender. Gender varies, but male does not vary. Therefore, gender is a variable, and male is a constant.

Now, let's understand the types of variables. Following are the major types of variables which are being used in educational research.  

Quantitative variable: It is a variable that varies in degree or amount. It usually involves numbers.

Categorical variable: It is a variable that varies in type or kind. It usually involves different groups.

Independent variable: It is a variable that is presumed to cause a change to occur in another variable.

Dependent variable: It is a variable that is presumed to be influenced by one or more independent variables. The dependent variable is the variable that is “dependent on” the independent (that is antecedent) variable(s).

A cause-and-effect relationship between an independent variable and dependent variable is present when changes in the independent variable tend to cause changes in the dependent variable. Sometimes researchers call the dependent variables an outcome variable or a response variable because it is used to measure the effect of one or more independent variables.

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What are the “Research Paradigms”?

Research Paradigms

Research is always a planned, systematic and rigorous activity in order to make known whatever is unknown to others and/or verify whatever is already known. It is action oriented. In other words, it can be defined as a systematic investigation into and study of materials and sources in order to establish facts and reach new conclusions.

As far as research paradigm is concerned, it is a perspective about research held by a community of researchers. The perspective is based on a set of shared assumptions, concepts, values, and practices. More simply, it is an approach to thinking about and doing research.

There are three major educational research paradigms or approaches: quantitative research, qualitative research, and mixed research.

The either-or position (that is, one must use quantitative or qualitative research but not both) is called the incompatibility thesis.

Pure quantitative research relies on the collection of quantitative data (that is numerical data) and follows the other characteristics of the quantitative research paradigm.

Pure qualitative research relies on the collection of qualitative data (that is, non-numerical data such as words and pictures) and follows the other characteristics of the qualitative research paradigm.

Mixed research involves the mixing of quantitative and qualitative research methods, approaches, or other paradigm characteristics.

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What are Measures of Variability?

Measures of variability are also called the measures of spread or dispersion. It lets the researcher know how scattered the scores are from their central tendency.

For example, if a group is homogeneous (containing individuals of nearly the same ability), most of its scores will fall around the same point on the scale; therefore, the range will be relatively short and the variability will be small.

But, if the group is heterogeneous (having individuals of widely differing capacities), scores will be strung out from high to low; thus, the range will be relatively wide and the variability will be large.

In order to indicate the variability or dispersion, the following four measures have been devised. These are:

1.    Range: It is the simplest form of measures of variability. It is the difference between the highest and the lowest scores in a distribution. Range is the crudest form of variability as it considers the extremes scores only. It is not a stable statistic (unreliable) because its value can differ from sample to sample drawn from the same population.

2.    Quartile Deviation: The quartile deviation (generally represented by “Q”) is one-half of the scale distance between the third quartile (75^th percentile) and the first quartile (25^th percentile) in a frequency distribution. First quartile is a point below which 25 percent of the scores lie, while the third quartile refers to the point below which 75 percent of the scores lie. Quartile Deviation (QD) is preferred when scores are widely dispersed or scattered.

3.  Average Deviation: It is also called “Mean Deviation”. It refers to the average of deviation of all scores from their mean. It does not consider signs (negative and positive) of the scores; that is, all deviation whether plus or minus are treated as positive.

4.     Standard Deviation: Standard Deviation (SD) is the square root of variance. It is the most stable form of measures of variability. It is employed in experimental work. Variance refers to the average of the square deviations of the measures or scores from their mean. Standard Deviation (SD) is used when scores are not widely dispersed or scattered.

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What are Parametric Tests & Non-Parametric Tests?

Parametric Tests & Non-Parametric Tests

Parametric Tests (for example, “t” test, and “f” test) are regarded as one of the most powerful tests. It is used during the stage of data analysis of a research work.

Parametric Tests are used when certain basic assumptions are fulfilled. If those assumptions are not fulfilled, that kind of tests comes under the ambit of Non-Parametric Tests (such as, chi square test, and Mann-Whitney Test).

Following are the basic assumptions of the parametric tests. If these assumptions are fulfilled, then parametric tests could be used; otherwise, non-parametric tests would be employed. Let’s discuss the basic assumptions of:

1.    Normality of Distribution: The sample (which has been drawn from the population) must be normally distributed for parametric tests. If samples are not normally distributed, it would not fall under the category of non-parametric tests; that is why, non-parametric tests are also known as distribution-free tests.

2. Randomization: The condition for selecting sample from the populations must be random. It means any technique, which is under the category of probability sampling technique, needs to be adopted. If samples are not selected through the process of randomization, we cannot apply parametric tests; in that case, we would apply non-parametric tests.

3. Homogeneity of Variance: The samples have equal, or nearly equal, variances. Homogeneity means sameness (in other words, more or less it should be same). For example, if we calculate the variance of two populations from where samples are drawn, they must have more or less same variance.  If there is a wide difference among the variance of the sample, parametric tests cannot be used; in such case, non-parametric tests will be used.

4.   Null-Hypothesis: This assumption is pre-requisite for both parametric as well as non-parametric tests. Therefore, this assumption is not the distinctive feature of parametric tests; this is the common feature of both parametric and non-parametric tests.

In both type of tests (parametric test or non-parametric test), a null-hypothesis must be formed. A null-hypothesis states that there is no significant difference or relationship between two or more parameters.

What are Parametric and Non-Parametric Data?

There are two types of data which are recognized during the application of statistical treatments. These are the following:

        i. Parametric Data: It refers to the data which are measured. As it has already been discussed above, parametric tests assume that the data are normally (or nearly normally) distributed. Parametric tests are applied to both interval and ratio scaled data.

     ii.Non-Parametric Data: Data of this type are either counted (nominal) or ranked (ordinal). 

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Educational Technology in India's Higher Education

Education plays an extremely critical role in the development of any country. In the era of knowledge economy which is widely being talked about, it would not be wrong to say that education is a nation’s strength. A developed country is inevitably an educated nation.

For developing countries like India, the nation is striving to achieve excellence in higher education that plays a pivotal role in the development process of the country, since it is viewed as a powerful means to build knowledge based society. Immediately after getting independence, the government in 1948 had set up the University Education Commission in order to enhance access and quality of higher education across the country.

On educational front, the country witnessed an appreciable rise in reaching out to all the classes of its society. However, at tertiary level of education, the nation is facing challenges in terms of access and quality.

The government took several steps during the 11^th Five Year Plan to increase access to higher education by adopting state specific strategies, enhancing the relevance of higher education through curriculum reforms, information technology adoption and distance education along with reforms in governance.

However in terms of Gross Enrollment Ratio (GER), India still lags behind the worldwide average and emerging countries like Brazil and China.

The 12^th Five Year Plan (2012-2017) confronts the challenges facing India’s higher education system and has proposed several initiatives to resolve them. These include increased funding for disadvantaged groups, imbibing cutting-edge technologies, faculty improvement programs, improved governance and provision of incentives for advanced research.

The government has laid out plans to achieve enrollment of 35.9 million students in higher education institutions, targeting a GER of 25.2 per cent, through these initiatives towards the end of the plan period. It also intends to improve the quality of the system significantly, while encouraging the co-existence of multifarious, research-centric, teaching and vocation-focused institutions.

As of 2011, Indian higher education system, which is controlled and monitored by the University Grants Commission (UGC), is spread over 42 central universities, 275 state universities, 130 deemed universities and 90 private universities. Additionally, 5 institutions were established functioning under the State Act, along with 33 Institutes of National Importance.

Nearly 33,000 institutions function as Government and Private Degree Colleges which also include 1800 exclusive women's colleges. Currently, over 60 per cent of higher education institutions in India are promoted by the private sector.

While the focus of the government has largely been on school education, in the context of post secondary and higher education, consistent and quality growth however has become debatable. A demographic divide still persists in the access to quality higher education with several communities still remaining under represented, contradicting the very objective of equity within the social growth of the country.

Challenges in India's Higher Education:

With the urban and the rural divide having significantly narrowed due to the onset of technology, communication and better infrastructure over the last two decades, there has been an appreciable improvement in the reach of better higher education to several under-represented groups across the country.

However, the need of the hour is a provision of high quality education across all sectors to match the requirements of a growing Indian economy. The suffering of the under-represented communities has not been appreciably alleviated as unemployment, inflation, low income and lack of adequate access to quality education continue to plague them.

Some of the key challenges for India in terms of access and quality of higher education are the following:

Poor Infrastructure – This shortcoming is perhaps the chief of all in delivery of quality education. While focus on the urban segment has been heavy, the same is not replicated in most of the rural areas. Establishment of quality higher education institutes in the rural sector has not been significant, which is a serious deterrent for the rural community in general.

There is wide disparity in higher education GER across states, urban versus rural areas, gender and communities that have to be bridged.

Inadequate faculty – The student teacher ratio on the whole is at a lamentable state. While it is still lower in the urban areas, the rural areas take the brunt of the scene with the ratios being at very high rate.

Unqualified or untrained faculty-- Even as the woes of inadequate faculty remain, a major part of the ones who are present to impart higher education are woefully unequipped in terms of either qualifications or experience or proper training.

Inappropriate or over load in curriculum – The curriculum of most higher education courses is very infrequently updated even as the world sees a continuously changing scenario in industry manpower requirements. This has caused a crass divide between the industry expectations and the college pass-outs who are poorly equipped with the right technical, business or social skills to be employed.

The above mentioned are some of the key challenges to access of higher education. I believe access is pre-requisite for quality. Until and unless access, that refers to availability of suitable number of institutions across region to fulfill demand, is given, it is virtually impossible to bring in quality at the tertiary level of education across the country. In simple term, it can be said that quality (to provision of suitable infrastructure, trained faculty and effective pedagogy in higher education institutions aimed at delivering expected outcomes) is a step ahead of access.

These challenges can be effectively addressed with the help of education technology in order to take higher education to the door steps of each and every citizen of the country.

Educational Technology:

Now-a-days, educationists have realized that in education “learning” is more important that “teaching”. As we know that learning is concerned with students, whereas teaching is related with pupils and teachers.

Gone were the days when a teacher was the only source of knowledge. The students learnt what the teacher taught. With the advent of textbooks and other learning aids, the teacher’s personal knowledge, though important, ceased to be the only or even paramount source of learning.

There are two factors which have posed critical problems for education. These are: “informational explosion” and “population explosion”, that means more things are to be learnt and more individuals are to learn. It is not possible to solve them by conventional means. In order to overcome these problems successfully, educational technology are required.

Now the question is “what is educational technology?”. In layman term, educational technology can be defined as the use of all educational resources—men and materials, methods and techniques, means and media--in an integrated and systematic manner for optimizing learning. It can also be defined as anything which can facilitate the process of learning.

According to PoA (p.183), “Educational technology offers the means to reach numbers in remote and inaccessible areas, remove disparity in educational facilities available to the disadvantaged and provide individualized instruction to learners conveniently suited to their needs and pace of learning.”

The Association for Educational Communications and Technology (AECT), Educational Technology defines it as:

 “Educational Technology is the study and ethical practice of facilitating learning and improving performance by creating, using, and managing appropriate technological processes and resources.”

Need For Educational Technology:

In the wake of growing population of the country, it has become the need of the hour to go for educational technology in order to provide education to the masses. That is why, the National Policy on Education, 1986 as well as the revised NPE, 1992 have laid emphasis on the use of educational technology for improving both “quality” and “quantity” of education for the first time in the history of Indian education.

The NPE, 1986 (p.22) stated, “Educational technology will be employed in the spread of useful information, the training and retraining of teachers, to improve the quality, sharpen awareness of art and culture, inculcate abiding values, etc, both in the formal and non-formal sections.”

In developing countries like India, the educational technology has to be mastered and utilized by educationists, if they are to keep pace with each other and catch up with developed nations. Both quantitative expansion as well as qualitative enhancement of education can be facilitated and accelerated with the help of educational technology.

As Apater has pointed out, “Today,  a technology of education is being developed with the aim not only of making education more widely available, but also of improving the quality of education which is already available.” 

Technology Trends in Indian Universities:

Educational technology has successfully been used for improving the quality as well as expanding the frontiers of higher education in the country. The tools help to create a social, highly collaborative and personalized environment with innovative solutions that will enhance the way students learn, communicate and collaborate and study both on and off campus. It has broken the monopoly of oral communication and invaded the classrooms of the colleges and universities.

Since August 15, 1984, the University Grants Commission launched the project “Countrywide Classrooms” and has been investing huge amount on establishing production centers providing TV sets, producing and purchasing suitable Educational Television (ETV) programs.

The ETV programs are produced at the different media centers, namely, Educational Media Resources Centers (EMRCs) located at Ahmedabad, Hyderabad, Pune, MCRC situated at Jamia Millia Islamia, New Delhi.

A Mass Communication Bureau has also been functioning at the UGC New Delhi and ETV production facilities have also been developed in the Technical Teachers Training Institute (TTTIs) located at different cities of the country.

Indira Gandhi National Open University (IGNOU) has been set up as an effective alternative model of higher education on September 20, 1985 by an Act of Parliament. The instructional system of IGNOU is different from that of conventional universities as it adopts a multimedia approach to education.

Some of the exciting technology trends in Indian Universities are:


Mobility

With the proliferation of mobile phones on campus, colleges everywhere are compelled to capitalize on feature-rich phones that are capable of much more than just voice calls.Adoption of the BlackBerry, iPhone and other smart devices that have Internet access allows students and faculty to perform a wide range of assignments. Tasks like administration, sharing class notes, downloading lectures, instant messaging, etc., are possible anywhere cell phone service is available.
Mobile phones are also being used to access computer files from remote locations. With services like “Soonr”, students who have forgotten to bring an assignment to class can use their cell phone to access the completed work on their home computer and show it to the professor.

Digitization of Books (E-Text Books)
There is an increased trend towards creation of a digital repository of books to create a digital learning environment for students. The digital version of the books embedded with text, pictures along with video, simulations and visualizations help students learn the concepts in an interactive way.
The National mission on Education through ICT plans to generate new online course content for UG, PG and Doctoral education. Efforts are already underway to prepare course content for 130 courses (UG and PG).

Content Delivery using IT/ICT
Higher Education is purely a content driven play where educational content is delivered through innovative use of ICT. There is an increased trend in higher education institutes to render content through Radio, TV and Satellite

Open Education Resources
Many Indian universities are contemplating Technology enabled free access of education resources. AICTE - Indian National Digital Library in Engineering & Technology (AICTE - INDEST) is a consortium set up by the Ministry of Human Resource to enhance greater access and generate annual savings in access of bibliographic databases.
The University Grants Commission (UGC) has also launched its Digital Library Consortium to provide access to peer reviewed journals and bibliographic databases covering subjects such as arts, humanities, technology and sciences

Virtual Technical University
The National mission on Education through ICT is working on a war foot to establish a virtual technical university to impart training to UG/PG students along with new teachers.

Social Learning
The emergence of Web 2.0 and social networking such as blogs and wikis, as well as new online video repository and delivery websites such as YouTube, iTunes U and Big Think is influencing a new trend in higher education.
The emergence of smartphones such as the iPhone and other intelligent devices has enhanced mobile learning (referred to as m-learning). These technologies create new channels for content delivery, online video expansion and podcasting. Also, the adoption of virtual reality websites such as “Second Life” has provided higher-education institutions with new venues for class gatherings and learning.
A combination of Web 2.0 tools viz., Blogs, Wikis, Podcasts, Mashups, and Social Networking Communities are transforming the traditional learning environment into something more social and personalized. While traditional Learning Management Systems (LMS) like Blackboard, Sakai, Moodle or Web CT are course-centered and driven by faculty, the new trend in education is to create a “learner-centric” system.

Educational Technology for Teacher Education:

The NPE 1986 emphasizes the teachers’ accountability to the pupils, their parents, the community and to their own professions.

At present, there are several institutions for training of elementary schools teachers and for preparing secondary school teachers. But a large number of these institutions suffer from inadequate facilities—human, physical and academic to provide good professional education. Curricula of teacher education are also felt outdated and teaching practices unsuitable as well as undemocratic.

Besides, improving these facilities, it is necessary to provide modern media, materials and methods for accelerating the teaching-learning process and energizing the training practices at various levels.

State Institutes of Educational Technology (SIET) have been established initially in Andhra Pradesh, Bihar, Gujarat, Maharashtra, Odisha, and Uttar Pradesh. Besides, a Central Institute of Educational Technology (CIET) has been set up in the NCERT with 100 per cent central assistance, to generate educational software in general and for teachers in particular for updating teachers’ knowledge and skills and improving their professional growth.

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