ISSN-2231 0495

Volume 4 || Issue 1 - Jan. 2014

Promoting Inquiry-Based Activities Across Boundaries of Content: A Review of Technology Integration for ‘Enabling Interactive Learning Using Computers’

Promoting Inquiry-Based Activities Across Boundaries of Content: A Review of Technology Integration for Enabling Interactive Learning Using Computers’

Rakesh Kumar

Assistant Professor


University of Delhi.


From the simple application of providing Audio-Visual Aids, to such as, using computers for delivering coursework, there had been many initiatives in the area of the use of Computer Assisted Learning. But such initiatives had been criticised as being non-interactive in nature. A contrasting perspective to the previous non-interactive interface is the interactive interface. This paper has built the context of interactive computer use in contrast with the non-interactive. It includes researches such as those related to use of models and simulations and using computers for manipulation of variables etc. While researches on the use of models and simulations highlighted the paucity of understanding their use in addressing Alternative Frameworks. They also point towards the applicability of Computer Assisted Learning in addressing Alternative Frameworks amongst learners in science.

Key Words: Computer Assisted Learning, Models, Simulations, Interactive computer use


Different studies related to Computer Assisted Learning in the present information society are so broad-based that it is not possible for the researcher to incorporate all areas and dimensions. The overall literature reviewed indicates that computers can be useful in confronting learners with their Alternative Frameworks and promoting conceptual change. Initial investigations related to use of computers for acquisition of conceptual knowledge seems promising. Computer use can be related with effective problem-solving strategies, appropriate theory building, enquiry activities etc.

The key points that emerged in the context of the study are as under

  • Computers can be used in a number of ways and in a number of contexts. In order to support the learning environments, computers can be used in a variety of ways. The multimedia approach of using a computer in which audio-visual aids are being provided by the computer is one approach. Going beyond the multimedia approach, computers have so many different roles to play.
  • Science learning involving formation of mental models to understand different dimensions of experiences with reality can be supported by the use of computers in the classroom and also outside it. Similarly, the same computers can be used for stimulating cognitive dissonance, articulating their own is testing hypothesis facilitated analysis and reflections, and creating and scaffolded environment. The interactive nature of computer can be harnessed by creating tutorials, designing concept specific tools and cultivating an online two-way communication.

Enabling Interactive Learning Using Computers

There is a common understanding about how computers can assist the teacher in providing/supplying visual aids, for which the criticism lies in it not being interactive in nature. Use of the interactive nature of computer technology can support learners in carrying out inquiry-based activities, using topics, questions, and even theories that they themselves define and develop. The interactive technology can be used to do away with the traditional and the associated passivity, in which the learner is usually considered to be an empty vessel that can be filled with knowledge. “Furthermore, learners who are permitted to use their own resources in developing, implementing and evaluating projects are likely to find, with little doubt, need for considerable revision. This, in turn, illustrates that the possibility always may exist for critique (scepticism) of methods associated with all scientific conclusions” (Bencze, J.L, Bowen, G.M., & Oostveen, 2003). Some studies that support the above cited claims have been referred to in the coming discussion.

Study by (Crosby & Iding, 1997) examines high school learners' performance on an interactive multimedia tutorial for learning physics concepts in conjunction with their individual differences. Results showed that learners in general performed better on the knowledge acquisition than knowledge application phases of the tutorial and differences emerge between learners with left and right hemispheric preferences on performance at different stages of knowledge acquisition. The results indicated that learners with right hemispheric preferences might benefit more from instructional strategies typically employed in tutorials for learning science, such as the inclusion of illustrations, analogies, and animation.

(Ronen, 1993) describes the designing and using of an open graphic interface called RAY, for instruction in geometrical optics. The RAY program offers a learning and a problem solving environment in which the learner can actively provide his/her own feedback without any kind of hesitation. However, a problem witnessed with this program is that learners cannot make a distinction between the representations of physical entities (light rays) and a geometrical construction (for instance, the continuation of a ray behind the mirror) since both are represented in a ray diagram by lines. A research conducted on its effectiveness reveals that it can indeed contribute to overcoming some learning difficulties, which learners have.

(Matsuda, 2006) describes the effectiveness of two kinds of education system, one is a Cyber Assistant Professor (CAP) and another is a Cyber Theatre (CT). CAP has been designed for a self-learning system, which enables interactive communication between virtual teacher and learner. The study claims that the production of interactive actual videos taken on location as teaching-learning materials is difficult in some cases, but the production of interactive 3D animation teaching-learning materials in CAP is not that difficult. They also argue that this technology would make learners aware about the computer that it is not only a tool for browsing information, but also a tool for creating information.

The study by (Young & Integrating, 2003) revealed that a computer mediated communication environment could lower learners' psychological barriers to enable them to express their opinions freely and to communicate actively on the Internet and that it could also enhance their critical thinking, problem solving and communication skills through online activities or class homepage construction. Computer access was also a concern of those learners who did not have computers at home.

(Mas, Mesquida, & Gilabert, 2011) have developed a tool called MiProJOC gameplay. The tool can also be used to assess knowledge in scholarship and learner independent work. MiProJOC is designed to facilitate the maintenance of a repository of questions from different areas, different game modes to define and present the statistical results from the use of the game. The study contends that a combination of traditional teaching methods with innovative teaching mechanisms generates a positive effect on learning of any subject.

(Gupta, Tejovanth, & Murthy, 2012) find that the introduction of logic programming and computer-hardware interfacing at the high school level is advantageous in terms of creating an interactive environment fostering learning and creativity.

(Blake & Scanlon, 2007) proposes a reconsideration of use of computer simulations in science education. Study discusses three studies of the use of science simulations for undergraduate distance learning learners have been discussed. The first one, The Driven Pendulum simulation is a computer-based experiment on the behaviour of a pendulum. The second simulation, Evolve is concerned with natural selection in a hypothetical species of a flowering plant. The third simulation, The Double Slit Experiment deals with electron diffraction and learners are provided with an experimental setup to investigate electron diffraction for double and single slit arrangements. Study involved evaluation of each simulation, with 30 learners each for The Driven Pendulum and Evolve simulations and about 100 learners for The Double Slit Experiment. From these evaluations study has developed a set of features for the effective use of simulations in distance learning have been developed. The features include learner support, multiple representations, and tailorability. Models and Simulations Models are the important tools used in science investigations, and are a valuable means of expressing an understanding of a process and of constructing knowledge.

Table 1: Summary of Researches on Models and Simulations in Science Education

Software: Reference

Study Purpose/Theory

Study Contribution

Running Simulations

Brna       (1987,

1991): DYNLAB

Software presented a variety of situations which were expected to cause learner to confront discrepancies between their beliefs about motion and the behaviour of their model

The simulation provided opportunities for learners to change their conceptual understanding and to articulate their new beliefs.

Gorsky         & Finegold (1992):  5  force simulations

Investigated the use of computer simulations to help restructure learners' conceptions of force

Simulations led to varying degrees of cognitive dissonance and were effective in eliciting learners' beliefs about forces acting on objects at rest and in motion. Learners who directly experienced the outcomes of their own Alternative Frameworks apparently rejected their incorrect views and accepted the scientific ones, at least in the context of the simulation.

(White,   1993): ThinkerTools

Described a physics motion simulation used in an inquiry curriculum, designed to help learners develop conceptual knowledge

Sixth graders performed much better on classic force & motion problems than high school learners in traditional physics classes.

Slack & Stewart (1990): GCK

Explored individual learners'  problem- solving strategies and developed a model of learner performance; GCK genetics simulation was used to present problems and data to learners

Learners followed these strategies: unplanned approach (lack of hypotheses

& testing strategy); working backward (explaining rather than predicting); and emphasizing quantitative counting and ratios. Learners lacked problem-solving abilities and skills such as genotypic thinking and generational thinking.

Hafner (1991); Stewart, Hafner, Johnson, & Finkel (1992): GCK

Used GCK to investigate individual learners' model-revising processes, general and domain-specific heuristics, and criteria for model acceptance

Learners engaged in model-revising problem-solving successfully, and were able to produce revisions which were generally compatible with accepted scientific theory. The simulation allowed learners to engage in knowledge production, and significantly increased the amount of “research” they could do.

Finkel    (1993,

1994); Finkel &

Stewart (1994): GCK

Studied how model-revision strategies and knowledge were used as learners worked in groups to solve genetics problems using the GCK simulation

Learners' strategies for model revision included a variety of actions  such as recognizing anomalous aspects of the data, making crosses, and developing, assessing and accepting multiple alternative models. Learners used their understanding of genetics, of the process of model revision, and of their own problem-solving strategies during model revision.

Simmons & Lunetta (1993): CATLAB

Explored general patterns of problem- solving behaviours and genetics conceptual organizers in experts and novices interacting with a genetics simulation

Successful expert and novice problem solvers employed the most complex patterns of problem-solving behaviours, mainly using description problem- solving sequences; least successful employed random patterns of behaviours.

Ronen,  Langley,                 and Ganiel    (1992): STEP


Reported and analyzed a large scale integration of computerized simulations into the present structure of Israeli high schools

Researchers speculated that problems encountered were symptoms of problems which occur in systems in transition. They also suggested that real change can only occur after teachers experience the advantages offered by computer simulations.

Kruper & Nelson (1991): Biota

The software allowed learners to construct meaning by providing opportunities to define problems, construct and test alternative hypotheses, and communicate subsequent evaluation of these hypotheses to peers

They reported no significant differences on pre- and post-test between treatment and control groups on tests of science reasoning skills, however, there were differences between learning processes. They concluded that strategic simulations can offer learners’ valuable experiences which help develop deeper content understanding.

Feurzeig (1992): Cardio

Provided an interactive visual environment for investigating the physiological behaviour of the heart. The simulation incorporates process visualization aids in the introduction of model-based inquiry skills, and supports advanced work in science research

Learners were able to explain nonlinear dynamical behaviour and to solve heart repair problems.

Richards, Barowy                   & Levin    (1992): Explorer Science

Provided learners with a coherent set of experiences that challenge the way they think about the world; provided opportunities to construct and test explanations for phenomena

Learners developed a sense of how scientists use models. Researchers reported that learner interaction with simulated models facilitated analysis and conceptual understanding of physical phenomena.

Creating Models

Jackson, Stratford, Krajcik,      and Soloway (1995):  Model- It

Described intentional scaffolding strategies designed to make system dynamics modelling accessible to pre- college learners

Learners built reasonable models; software strategies made modelling accessible; building models allowed learners to refine and articulate their understanding of complex systems.

Mandinach (1988): STELLA

Investigated the effectiveness of using STELLA in the systems-thinking curricula

Learners tested well on their knowledge of STELLA, but were less able to translate knowledge and skills to more general problems.

Mandinach (1989): STELLA

Tested the potentials and effects of using STELLA to teach content-specific knowledge as well as general problem solving  skills

Learners acquired knowledge of systems concepts and applied them to scientific problems at varying levels of complexity and sophistication.

Mandinach & Cline (1992): STELLA

Examined the impact of learning from a systems thinking approach to instruction and from using simulation-modelling software

The researchers concluded from their experiences and observations that gaining a working knowledge of system dynamics, STELLA software, and the Macintosh is substantially different from acquiring information within a content area of expertise.

Miller,   Ogborn, Briggs,  Brough, Bliss,    Boohan, Brosnan, Mellar,                 and Sakonidis (1993):  IQON

Researchers described the design of and rationale for modelling tools that are claimed to be simple enough for young teenaged learners (grade 8) to learn

Pupils built meaningful models of considerable complexity and contributed ideas about the relation of IQON models to reality. Researchers observed that learners began to understand complex models as interconnected systems. Pupils constructing models saw their models as fallible, tended to consider revisions, and made more interesting modifications than those who were simply exploring pre-defined models.

Schecker (1993): STELLA

Research focused on having learners develop and test models with STELLA; researcher suggested that modelling can help to accentuate the conceptual structure of a physical domain and help clarify the qualitative meaning of physical concepts

It took about 2 instructional units for learners to become familiar with software to make models on their own, after which they were able to work out model structures themselves in classroom discussions or work groups.

Creating Simulation Programs

diSessa (1991): Boxer

Investigated ways in which sixth grade learners invented ways of working on difficult  problems

Learners engaged in learner-initiated learning (they learned to “cheat” at the simulation in order to solve difficult problems).

Fuertzeig (1992):

Function Machines

Investigated the use and benefits of visualization in model-based inquiry activities

The researcher suggested that appropriate computer modelling activities can make the experience of doing science concrete and highly motivating for high school learners.

Guzdial (1995): EMILE

Created a scaffolded environment in which helped learners to create physics simulations in HyperCard without learning to program first

Learners learned about programming, and learned physics concepts (velocity, acceleration, projectile motion) through creating simulations in HyperCard.


Different studies across the globe suggest that computer simulations and models can be effectively utilised in supporting/challenging models that learners make to develop their science concepts. Some works like Biota, suggest contrary results on development of scientific reasoning skills.

(Stratford, 1997) reviewed Computer-Based Model Studying Precollege Science Classrooms in nineties showing that studying the field is not new. On the other hand we need to acknowledge the changes in the hardware and software settings. The summary is presented in the form of a table organized into three categories: running simulations, modelling, and writing simulation programs.  The table contains, for each study, the name of the software, the main purpose of the study, and its contribution to the literature.

(Raghavan, 1995), (Driver, 1986) and (Gilbert, 1998), report  that models and model-based reasoning have been found to be important in the development of science concepts and the development of learners’ understanding of the processes of science (Thomas, 2001). Using computer simulations and modelling, learners tend to develop new strategies for solving problems, complete  tasks  of greater cognitive complexity, test personal hypotheses by making predictions, develop higher-order thinking skills, and engage in complex causal reasoning (Cox, 2000).

(Mohanty & Routray, 2012) present a novel and efficient ways of E-learning, E-experimenting and E-assessment for a basic level course on embedded systems for undergraduate learners. In a country like India where the total number of learners in electrical sciences in a given semester is close to 500,000 an automated and animated laboratory in embedded systems is very useful. In this virtual web based laboratory, a learner can perform experiments, simulations and experimental validation of results. 3D animation sequences are provided in each experiment, to facilitate a real world experience of microcontroller programming, interfacing and real time processing. The entire process is of three stages comprising the learning, experimenting and self- assessment to achieve the objectives set forth.

The review of the summary in the table shows that studies have been conducted in specific conceptual areas in science but studies pertaining to developing a broader understanding of addressing alternative frameworks are very few.

According to (Thamarai Selvi & Panneerselvam, 2012), Indian learners lack the skill of Self-regulated Learning (SRL) that is indispensable for lifelong learning. A Learning Management System (LMS) is presented that provides learners with electronic materials and supporting tools to inculcate Self-regulated Learning by way of providing an environment to learn a programming language. The results show that the learners who underwent the course show increase in the self-regulation components and the interest to learn in-depth.

(Bhattacharya, Chakraborty, Basu, & Roy, 2012) addressed the issue of providing personalized user interface to e-learner under web based e-learning environment. A frame work, based on concept map trees has been proposed that intelligently tracks the learning pattern of an e-learner and helps the learner to attain his learning objective through the recommender agent.

(Pati, Misra, & Mohanty, 2012) have developed a virtual laboratory for software engineering course. According to the study, the virtual labs software engineering help in improving software engineering education and, in turn, in preparing software engineering learners for professional careers. It is envisaged that the virtual lab will also help the software engineering educators in underprivileged educational institutions having lack of teaching resources, and who are willing to improve education at their institutions. The study emphasises that the evaluation of the effectiveness of learning software engineering by using virtual labs should be addressed and proposed a conceptual model for evaluating effectiveness of software engineering virtual labs course.

Conclusions and Reflections:

Manipulation of variables is an important process for understanding cause and effect relationships in science. Simulated microcomputer-based laboratory experiments can be used to support this manipulation of variables.  Different strategies have been used for delivering coursework at different levels of science learning and the effectiveness of the strategy to use computers has been supported by   many studies.  This approach   of   delivering   coursework   gains   special importance when there is a question mark on the authenticity of sources available to the learner. Many times some wrong information is available to the child as a source which becomes a reason for Alternative Frameworks. Many researchers have compared traditional teaching methods with the use of computers in classrooms. In different subject areas and across boundaries of content, use of computers has largely been seen as being more effective than traditional classroom approaches and strategies. Although the whole system seems to be benefited by this approach, the science learners have been argued to be main beneficiaries. The use of computers in the classroom or outside it by both learners and teachers demands a positive outlook by them towards computers. Technology integration has to be impacted by teacher’s technological knowledge, pedagogical knowledge and a supportive community.


  • Bencze, J.L, Bowen, G.M., & Oostveen, R. V. (2003). Web-mediated intellectual independence in science knowing. Chicago, Illinois.
  • Bhattacharya, S., Chakraborty, A., Basu, P., & Roy, S. (2012). A framework for interactive pattern based adaptive recommender agent using concept map for personalized e-learning: IPBARA. In IEEE International Conference on Technology Enhanced Education (ICTEE) (pp. 1–5). IEEE.
  • Blake, C., & Scanlon, E. (2007). Reconsidering simulations in science education at a distance : Features of effective use, 491–502. doi:10.1111/j.1365-2729.2007.00239.x
  • Cox, M. (2000). Information and communications technologies: Their role and value for science education. In M. M. & and J. Osborne (Ed.), Good practice in science teaching – what research has to say. Buckingham, England: Open University Press.
  • Crosby, M. E., & Iding, M. K. (1997). The influence of a multimedia physics tutor and user differences on the development of scientific knowledge. Computers and Education 29 127136, 29(2), 127–136.
  • Driver, R. (1986). The approach of the children’s learning in science project. Paper Presented at the Annual Meeting of the American Educational Research Association, San Francisco, 67, 443–456.
  • Gilbert, J. (1998). On mental modelling in science and technology centres: A pilot study. Paper Presented at the Annual Meeting of NARST, San Diego, 1998, 1–19.
  • (pp. 1–3). Retrieved from
  • (pp. 1–6). Retrieved from
  • Matsuda, H. (2006). Yoshiaki Shindo. Education System Using Interactive 3D Computer Graphics 3DCG Animation and Scenario Language for Teaching Materials Innovations in Education and Teaching International, 43(2 SRC - GoogleScholar), 163–182.
  • (Vol. 2nd, pp. 92–95). Retrieved from
  • Pati, B., Misra, S., & Mohanty, A. (2012). A model for evaluating the effectiveness of software engineering virtual labs. In Technology Enhanced Education (ICTEE), 2012 IEEE International Conference on (pp. 1–5). IEEE.
  • Raghavan, K. (1995). Model-based analysis and reasoning in science: The MARS curriculum. Science Education, 79, 37–61.
  • Ronen, M. (1993). To see or not to see: The eye in geometrical optics - when and how? Physics Education, 28(4 SRC - GoogleScholar), 52–59.
  • Stratford, S. J. (1997). A Review of Computer-Based Model Research in Precollege Science Classrooms. Journal of Computers in Mathematics and Science Teaching, Volume 16(Number 1).
  • (pp. 191–196). Retrieved from
  • Thomas, G. P. (2001). Using a metaphor for learning to improve students’ metacognition in the chemistry classroom. Journal of Research in Science Education, 38, 222–2259.
  • Young, S. C., & Integrating, I. C. T. (2003). Integrating ICT into second language education in a vocational high school. Journal of Computer Assisted Learning, 19 (4)(4 SRC - GoogleScholar), 447–461.





Bihari Lal
Head Master, Uchchatar Madhyamik.Vidyalaya,
Modinagar,Mugalsarai, Chandauli, UP
Vivek Singh
Junior Research Fellow,
Faculty of Education (K),  B.H.U.,
Varanasi,  UP
Secondary education is a crucial stage in the educational hierarchy, as it prepares the students for higher education and also for the world of work. With the liberalization and globalization of the Indian economy, the rapid changes witnessed the scientific and technological world. Taking the importance of secondary education in consideration central government of India has launched the scheme ‘Rastriya Madhyamic Shiksha Abhiyan’. The scheme was launched in March, 2009 with the objective to increase access and to improve the quality of secondary education. The implementation of scheme has started from 2009-10.North-east region of India is not so much linked with the rest India, because it is less accessible to shortage of rail and road due to uneven physiographic condition. So this part of country has not equal participation with national progress and development. Though this part of country is full of natural and social diversity, yet due to ethnic, regional, and disputes based on language and other factors has stagnated the current of regional development. If we become able to solve these problems, there will be a broad scope of the development for this region.  Education is known as liberating and democratic force and secondary education has a great role in the development of these values. The RMSA is based on sociological and psychological bases of education. This scheme could be very much effective in the progress and development education, society and environment. In this way north-east India can march towards happiness among people with symbiotic relationship between different community and people of different regions, religions and languages. This paper deals about how the RMSA would meet the challenges and create environment of inclusive and sustainable development of the region.
Keywords- RMSA, North-east India, Universalization, secondary education.
Education is most important and liberating force in the process of development of nation as well as society. North east India is very important part of India for its diversity as well as national progress and security. North eastern India consist 8 states of the country. North east part of India is below the national average. The education can be very important tool in the process of growth and development of this part of country. North east Indian people think that they are deprived of the Indians' progress and development.
Framework of Rastriya Madhyamic Shiksha Abhiyan (RMSA) 2009 states "Secondary Education is a crucial stage in the educational hierarchy as it prepares the students for higher education and also for the world of work. Classes IX and X constitute the secondary stage, whereas classes XI and XII are designated as the higher secondary stage. The normal age group of the children in secondary classes is 14-16 whereas it is 16-18 for higher secondary classes. The rigor of the secondary and higher secondary stage, enables Indian students to compete successfully for education and for jobs globally. Therefore, it is absolutely essential to strengthen this stage by providing greater access and also by improving quality in a significant way.
Goals and  Objectives
To ensure that all secondary schools have physical facilities, staffs and supplies at least according to the prescribed standards through financial support in case of Government/ Local Body and Government aided schools, and appropriate regulatory mechanism in the case of other schools. To improve access to secondary schooling to all young persons according to norms – through proximate location (say, Secondary Schools within 5 kms, and Higher Secondary Schools within 7-10 kms) / efficient and safe transport arrangements/residential facilities, depending on local circumstances including open schooling. However in hilly and difficult areas, these norms can be relaxed. Preferably residential schools may be set up in such areas.
  • To ensure that no child is deprived of secondary education of satisfactory quality due to gender, socio-economic, disability and other barriers.
  • To improve quality of secondary education resulting in enhanced intellectual, social and cultural learning.
  • To assure good quality of education.
Achievement of the above objectives would also, inter-alia; signify substantial progress in the direction of the Common School System. North eastern part of India has greater literacy rate than the other part of the country, so improving secondary education is more necessary than the rest of India. So RMSA is more important in this part of country. In the north eastern part of the country primary education is good, but secondary education is not so good in this region so if RMSA would properly implemented in this part of country, the secondary education can be improved in this part of country and it can be foundation for quality higher education in this region. Through RMSA our government is committed to empower youth with quality and life skill education that will enable them too effectively with the demand and challenges and everyday life in the world. Now government of India is planning for universalization of higher education in the name of Rastriya Uchchatar Shiksha Abhiyan (RUSA).
North eastern part of India is famous for its diversity. Here both types of diversity as natural and cultural diversity is found, because of natural and physiographic diversity there exist a vast diversity in cultures. Most of the north eastern region has uneven topography and easy movement of people from one place to another place is not easy. So, different cultures are found in different place of the region. due to unavailability of easy mobility of people, there is a vast gap found among the cultures. Ethnic group and culture is very much effective in this region. One group of community attacks on another ethnic community to make their dominance in the region and to occupy their recourses. These people not believe in the country but believe in community and ethnic group. Every community seems themselves as well as their culture superior than the others. In north-eastern part of India different languages are found and due to this there is a broad communication gap is also found. That result a great deal of unrest among students. So here a number of movement and agitation takes place and in these activities youth and student play very important role.
The major problem of north-eastern part of India is regional imbalance and communal disharmony and lack of modern pattern of development. Intercultural violence and disagreement between government policy and program and disharmony among different group are the major problem in this region. Due to misunderstanding between different cultures many violent activities takes place in this region. The citizens of this age group are like unripe pots, what shape society gives to these teenagers will not easily change in the rest of their life. So it is duty of government as well as society to promote them in constructive activities. Disruptive forces try to brainwash these teenagers and develops misleading concepts. These teenagers have unparallel energy and will power, so direction in this age group is very important. If these teenagers will get proper and constructive educational facility, they will be resource for the country, community and personal level. And if these future citizens will misguide then they will create unrest in the society and indulge in agitation arson violence in the society and decrease the process of development.
The student of secondary education comes under the teen age or adolescent age. This teen age group is very important from the point of view of character formation, personal as well as social development. Many psychologists treat this age group as foundation age and given different name like age of storm and strains and high school age. The role of secondary education play very important role in personal as well as social development of pupils. If we provide education to these communities they would understand each-other and live with cooperation.  Secondary education is intermediate point between primary and higher education. The student of Secondary education is comes under the age group between 14th years to 18 years. The population of this age group of people can easily misguided by the destructive forces. If we provide proper secondary education to this age group of people can understand the real situation and will not indulge in disruptive activities in the society. Secondary education has very important effect on man’s future life. RMSA ensures the provision of quality secondary education to makes citizen competent to do any job properly. Quality education composes not only acquisition of basic knowledge, but also development of values and competencies. Secondary education is backbone of higher education for the promotion of higher education research and development. So, secondary education has very important place in the process of growth and development of country.
The RMSA is very much relevant in the progress of secondary education in north-east India. It makes many provisions for the development of secondary education in India, which is more relevant in educational development of north-east India. The RMSA states that school knowledge should be related to family and surrounding environment. It support psychological bases of learning which is also focused in NCF-2005 and NCFTE-2009. North-east region has greater the literacy rate than the rest of the country’s average literacy rate. So this part of country has better opportunity for educational development. The gap between male and female literacy rate is also very low than the rest of the Indian national average. But due to lack of resources these students could not continue their higher education. In RMSA it is provision to open new model schools in educationally backward blocks. So this program will be very much fruitful in this region.
Secondary education has very important effect on man’s future life. If the government will provide proper secondary education the future citizens will get competency to do any job properly. Secondary education is foundation and backbone of higher education research and development. In this way secondary education has very important place in the process of growth and development of the country. The aim of education is not only to provide information, but also the main objective of education is to make student better citizen as well as human being. The RMSA focus on interactive learning and learning related to learners needs. NCF 2005 also claims that providing bookish knowledge will not become fruitful in learners life and learning should be according to the learners own needs and interest, so that pupils can enjoy the classroom and will not feel education as burden.
The RMSA states that learning of school should be linked with the knowledge of local community and ethnic groups. For the north-east region this concept is very important, because in this region culture and tradition is very much different from the Indian culture and a broad cultural diversity is found in this region. We should not always try to make a national identity but we should respect the different fabric of diversity. Sustainable development and sustainable economy is the need of present pattern of development. For the sustainable economy local cultural practices should be involve in the development process. Some tribes have very sustainable pattern of life that should be preserve and promoted. Local knowledge should be included in the curriculum as well as learning. The barefoot ecologist cultures and knowledge could be very much effective in promotion of sustainable future in this region.
There are many provisions for the development of north-east people, but till now the condition is not satisfactory. Government should not give the fish to the people to eat, but should train the people to catch the fish. RMSA tries to provide this type of training to the students. These regional should provide the motivation that only they can develop themselves and people participation in their development should be ensured. Orchid and other agriculture related industry and tourism can be major sources of their economy. Apart from this hydro-electricity energy generation can contribute to their development. Due to regional and cultural diversity inter-cultural conflict is the main problem this region of India. Many agitation and unrest takes place in this region due to their narrow minded outlook and small horizon. Through proper education RMSA help future citizen to understand that they are human being like others people and every culture is important. They can understand that National harmony and national identity is more important than the tribe or ethnic identity. And intercultural co-operation is the key to their progress and development. RMSA can make understanding among student that many good cultures are found in this region that should preserve and enlighten rationally.
National integration is the main problem of this region. Education Commission on secondary education (1953) states, that national integration is the main objective of secondary education. For the proper implementation of RMSA central and state government should have proper cooperation. The officer related to this scheme should be sensitive toward its implementations. So that, the available program will accessible to the common people. Inclusive development and egalitarian society is the need of global peace and progress, so this region of India should promote to become under the mainstream of national development. The RMSA has made provision of this type of society. National curriculum framework (NCF), 2005 recommend that children life must be linked to their life outside the school. This principle mark a departure from the legacy of bookish learning which continue to shape our system and cause a gap between the school, home and community. It attempt to discourage rote learning and the maintenance of sharp boundaries between different subject areas. We must recognize that given space, time and freedom, children generate new knowledge by engaging with the information passed on them by adults. These all things are included in RMSA.
All India Survey in Higher Education 2011-12 (2012). New Delhi, MHRD: Department of Higher Education, Government of India.
Annual Report (2011-12).MHRD, Government of India.
Annual Status of Education Report (ASER) 2010 (14 January 2011). Mumbai, Pratham Resource centre.
Biswas, P.C. & Mondal, M.(1995) In sixth survey of educational research(1993-2000) Vol-II  New Delhi: NCERT. Pp.466.
Kothary, D.S. (1966). Report of education commission(1964-66): Education and national development, Ministry of Education. Govt. of India  p.-275, 293-296, 325-334, 365
Framework For Implementation Of Rashtriya Madhyamik Shiksha Abhiyan 2009 MHRD, Govt of India
Ross, aileen D. (1969).student unrest in India: a comparative approach. Review by: Kenneth N. Walker.In social forces vol 48 no.4 jun..1970 pp-556-557.
Ray A.B.(1977). Student and politics in India: the role of caste, language and religion in an Indian university. New Delhi: Manohar publication
Susan, Wallace (2008). A Dictionary of education. OXFORD university press. Pp128-129.
World Education Report (2000). Right to Education: toward Education throughout life.. UNESCO publishing.



Dr. Paramjeet Kaur Brar
HRM College of Education


Teachers come across such students who appear to have average or above average scholastic aptitude, yet they are doing very poorly in their course of study. Some students reach their goal but many are unable to achieve what they aspire. The reasons may be lack of educational aspiration or mental health.

Diversity of culture is a fact in the world. Modern capitalist economy has systematically revised geographical pattern of mankind, destroyed traditional and regional divisions, has brought together as free or forced collaborators as equal partners or as competitors, people from four corners of the world. Government has also made provisions for education of depressed class of the society such as scheduled caste in order to bring them near people of general category.

With the growing realization of the fact that this centuries old "Varna Vyavastha" has seriously impaired the over all development of the society, Govt. of India has provided special reservation for the socially deprived lower caste namely "Shudras".

However, inspite of all these special treatments including financial help and social development packages, situation does not seem to be very much in control.


No doubt, the legislative measures of the government have ensured enhanced numerical reservation of the scheduled castes, but it is worth exploring whether these provisions for reservations for SC's have helped them in the enhancement of their mental ability, and mental health. Does caste factor affect their level of educational aspiration? Based on an extensive field survey, the present study attempts to answer all such questions.


Studies Related to Educational Aspiration

Suman (1986) in her study on 200 Arts and 100 Science students found that for Arts students master degree was an important aspiration where as for science students master degree in medicine was main aspiration.

Vijay (1990) in his study found significant difference in the educational aspiration level of children of working and non-working mothers.

Hmingthanzuala (2001) in his study found that students from different socio-economic status and different regions have significant differences in interests, aspiration and academic performances.

Kaur (2007) conducted her study on a sample of 400 students of +1 class taken from Jalandhar city (Punjab). Study revealed that high or low stress students differ significantly in their level of educational aspiration. Also it was revealed that education aspiration level influences academic achievement of adolescents.

Studies Related to Mental Health:

Rejio et al. (1988) conducted a longitudinal study on 272 children (9-13 years) and revealed that development of mental health disorders and occurrence of symptoms increased with age and that men and women differ in many ways in terms of the nature of the mental health.

Sproul (1993) suggested certain factors foster good mental health among persons with mild intellectual impairments.

Dewan (2003) in her study on a sample of 769 students found that students with average academic stress were more emotionally stable as compared to the students having high academic stress.


To study and compare the difference in the level of educational aspiration and mental health of general and scheduled caste students.


(1) There will be no significant difference in the level of educational aspiration of general and scheduled caste students.

(2) There will be no significant difference in the mental health of general and scheduled caste students.

To test this hypothesis following sub-hypotheses are tested:

(a)  There will be no significant difference in the positive self evaluation of general and scheduled caste students.

(b) There will be no significant difference in the perception of reality of general and scheduled caste students.

(c)  There will be no significant difference in the integration of personality of general and scheduled caste students.

(d) There will be no significant difference in the autonomy of general and scheduled caste students.

(e)  There will be no significant difference in the group oriented attitudes of general and scheduled caste students.

  1. There will be no significant difference in the environmental competence of general and scheduled caste students.


Descriptive survey method is used in the present study.


Present study is conducted on 713 BA(I) class students (general category= 456 and scheduled caste category =257) studying in degree colleges in the Union Territory of Chandigarh. For the selection of colleges and classes randomization technique is used.


  1. 1. Educational Aspiration Scale (Sharma and Gupta, 1997)
  2. Mental Health Scale (Jagdish and Srivastava 1983)


In the present study, statistical techniques of mean, S.D and t –ratio are used.


TABLE 1:Values Of Means, SD's And T-Ratio To Locate Difference In The Educational Aspiration Between General And Scheduled Caste Students

Vr. No.








Level of Significance




Educational Aspiration

General Category








Significant at .05 level

Scheduled Caste Category





As per the results of table 1 significant difference in the educational aspiration of general and scheduled caste students was found due to significant t-value at .05 level (t=1.98). it was evident from their mean scores that students of scheduled category have higher educational aspiration (mean=35.07) as compared to general caste (mean=33.68).

The results may be explained on the basis of awareness scheduled caste students might be getting form the  media and dissemination of information in the college/school about various courses and because a bright future after completing the course might be encouraging them to have high educational aspiration in life. Moreover facilities provided by Government for the upliftment of weaker sections lure them to get education and have higher educational aspiration in life.

TABLE 2: Values of means, SD's and t-ratio to locate difference in the measures of mental health between general andscheduled caste students (N = 701)

Vr. No.








Level of Significance


Positive Self-Evaluation

General Category






Not Significant


Scheduled Caste Category





Perception of Reality

General Category







Scheduled Caste Category






Integration of Personality

General Category







Scheduled Caste Category






General Category








Scheduled Caste Category





Group-Oriented Attitudes

General Category






Not Significant

Scheduled Caste Category





Environmental Competence

General Category






Not Significant



Scheduled Caste Category





Mental Health

General Category






Not Significant


Scheduled Caste Category






Results of present study as entered in table 2 reveal insignificant differences in the positive self evaluation, group oriented attitude; environmental competence and overall mental health of students of general and scheduled caste category due to insignificant t-value at .05 level. Thus hypothesis  2(a), (e), (f) and (g) are accepted.

Contrary to the above results, significant differences are found in the perception of reality, integration of personality and autonomy measures of mental health of students of general and scheduled caste category. Therefore hypothesis 1(b), (c), and (d) are not accepted.

Hence as per the results of preset study students of general category were found to be higher on perception of reality, integration of personality and autonomy as compared to students of scheduled caste category.


Finding of the present study would provide the basis for intervention and treatment for modifying, strengthening, accelerating the outcomes of the students belonging to general and scheduled caste categories. Study is also more important for teachers, to enable them to capitalize the opportunities for the students according to their socio-cultural features.

The present study is also helpful from guidance point of view to parents, teachers and educational administrators because, it will enable them to know the level of mental health and educational aspirations of students of general and scheduled caste category. It will lead to make arrangements for better environment for developing mental health and raising the educational aspirations of students’ social culture.


Dewan, A.M. (2003) "Effect of stress, locality and gender on selected cognitive and non-cognitive variables". Ph.D. (Education) Punjab University, Chandigarh.

Hmingthanzuala (2001) "The relation between manifest anxiety and intelligence" Journal of Education and Psychology, Vol. 24 (4).

Jagdish and Srivastava (1983): Manual of Mental Health Scale, Agra Psychological Research Cell, Agra.

Kaur, P. (2007) "The effect of stress and educational aspirations on the academic achievement of adolescent students" M.Ed.      Dissertation, GND University, Amritsar.

Reijo et al. (1988) as quoted by Paramjit Singh (2000)  "Effects of environment of mental health of adolescents", M.Ed.          Dissertation, Panjab University, Chandigarh.

Sharma, V.P. and Gupta (1997):  A Manual of Educational Aspiration Scale. National Psychological Corporation Kacheri Ghat, Agra.

Sproul, Norma Theresa (1993) "Relationship between social support and mental health status of persons with mind intellectual connections". Dissertation Abstract International, Vol. 54, No.9, 1993.

Suman, S. (1986) "A Socio-psychological study of goals and aspirations of female students". Ph.D. (Psy.) Magadh University.

Vijay (1990) "A study of personality, educational achievement and level of aspiration among the children of working and non-working mothers" Ph.D. (Edu), Agra University, Agra.


Students' Attitude Towards Natural Science In Primary Schools

Students' Attitude Towards Natural Science In Primary Schools

Yazachew Alemu Tenaw  

Natural Science Department,   

Debre Markos College of Teacher Education 

Debre Markos, Ethiopia 



This study examines attitudes to school science classes amongst primary school students based on the assumption that these will influence their attitudes and choices later in life. 980 primary school students in grades 4-6(Debre Markos Town, Ethiopia)) were given a Likert-type questionnaire and asked to provide verbal explanations for their agreement/disagreement with each item. The items are divided into three "clusters," representing three central influences on student attitudes: "motivational factors", "locus of control" and "relevance of science."   My results support the findings of previous research in elements such as students' enthusiasm for experiments, and reveal some interesting discrepancies in the way boys and girls assess the relevance of science they learn in school. While the questionnaire shows that most of the students saw discussion in science class as a source of interest, students' explanations and their answers to the open-ended questions also indicate that the most common model of a science lesson they see is readings from the textbook, accompanied by the teacher’s explanations. Only about one half of the students claim to take an active part in classes, answering questions asked by the teacher in class, taking part in class discussions, and expressing their opinions. The teacher is perceived as a significant part of the learning process. The students’ explanations indicate that they see the teacher as a primary source of information and authority.

Keywords: locus of control, relevance of science, self-efficacy, science subjects, attitudes


Despite the ever-growing importance of science in my daily lives, recent research shows a continuous decline in the number of students who choose to study scientific subjects in high school and to later pursue scientific careers [27]. While to date only a relatively small body of work has been devoted to assessing the attitudes of primary school students towards the learning of science [22], as early as three decades ago researchers showed that age 8-13 is a crucial period in the development of attitudes towards science [25]. Further research showed that a positive attitude towards science significantly impacts motivation to learn it, both in school and in other educational frameworks, and that attitudes developed in primary school influence the choices of students later in their life [27]. This study therefore assesses the attitudes of primary school students towards learning science, attempting both to characterize their science-education experience, and to identify the central components that influence their perception of it. One element it examines in this context is gender, and the manner and extent to which it may influence students' experience of science, even at such an early age.

Motivation and Attitudes towards Learning Science in Primary School

Attitudes and motivation have been the subject of educational research for several [22, [25], [34]. Despite the rather limited amount of studies conducted into the attitudes of primary school students towards science [20] a number of patterns have nevertheless been identified. These include the significance of the teacher’s role, the recognition of science as important, the perception of science class as a positive, "fun" experience [20], a distinct gender difference in students’ attitudes [17],  [31]. Research has shown a correlation between teacher conduct, class atmosphere, and pupils' attitudes in different ages. Students have indicated teacher conduct in science class as an influential factor in developing their attitudes and their views about science in school and science in general [13]. Moreover, studies of student’s level of satisfaction with their science classes found that the satisfaction students derive from science class, as well as their motivation for learning science, are influenced by the way they are taught [6]. Good teachers have been described as those who are fond of what they are teaching, who link topics learned in class to everyday life and who teach in an orderly way. Using diverse ways of teaching and involving pupils in active learning has also been pointed out by the students as positively influencing their attitude to science in school and in general [22]. Pupils with positive attitudes towards science tend to develop a more positive approach towards topics learned in school and toward science class as a whole [3]. The interaction of students with their teachers and with the study material involves yet another very important and widely studied feature in attitude and motivation research - self-efficacy. The belief in one's capacity to successfully perform a particular task is one of the most powerful motivational predictors of how well a person will perform at almost any endeavor. A person’s self-efficacy is a strong determinant of their effort, persistence, and strategizing, as Ill as their learning and further performance. Studies have shown that students’ self-concept of their ability in science has a continuous and crucial influence in the development of their attitude towards science classes and science in general [13]. A high rate of self-efficacy towards a certain task leads to a stronger determination to persist in performance, as Ill as making the task seem more important and enjoyable [35].

Teachers’ conduct can provide students with verbal and non-verbal indications about their progress, which they use to build up their self-efficacy. While this has been found to be true of high-school students, primary school pupils have been found to have a relatively high (3 of 5) and stable notion of self-efficacy in science that was not dependent on external variables, such as their general attitude to school or their academic achievement in other subjects [40]. Furthermore, some studies showed that younger students showed more self-efficacy than older ones [20].

An additional factor influencing motivation and attitudes towards science is the very recognition of science as something important and worthwhile. Studies show that primary school pupils see science as important, helpful and useful for future life [20]. Recent decades, however, show that interest in science at school is in a distinct state of decline, which starts in junior high and becomes even stronger in high school [36]. Furthermore, Osborne, Simon & Collins (2003) have found that despite the general recognition of the importance of science studies, students relate to science more as a technical tool for success, rather than as something interesting worth indulging in. On a personal level, many students described science as a prestigious subject, and students who succeed in science are seen as “smarter”. At the same time, however, students did not mention that science was interesting, and even pointed out that some science topics Ire completely unnecessary in their opinion.

Unlike older students, primary school students have been shown to see science as highly important and valuable, even as an end unto itself [21]. A high percentage of primary school pupils spoke about science in terms of interest, though its practical value is by no means overlooked: about 90% of primary school pupils agreed that science would help them in their future career, and more than 70% of them described science as relevant and useful in everyday life [29].

Gender Differences in Primary School Attitudes and Motivation

There are, however, certain variables that continuously influence the attitudes of students in all age groups, and one of these is gender. Gender issues in education, including academic preferences and motivation, have already been studied for a number of [4], [19]. Though the significance of differences has been shown to increase with age, studies of primary school students revealed that distinct gender differences Ire already present, with boys tending to like physics and chemistry related topics, while girls gravitate toward topics related to the human body, healthy lifestyle, and communication between animals [3], [18] and the recognition of science as important and relevant also changes between genders with age. In primary school, boys and girls alike report a high level of awareness that learning science is important and relevant to their lives, but as students grow older, this conviction decreases markedly, especially in girls. In high school the number of girls voicing strong support of the importance and relevance of science is much smaller than that of boys [19]. Decreasing interest in science amongst girls was discovered in extracurricular activities as Ill. An extensive survey of questions sent by pupils and students to a popular Ask-A-Scientist site held over 10 years showed that around the world girls tended to send in fewer questions as they grew older [5].  On the other hand, despite their less positive attitude towards science, girls have usually boasted higher academic achievement than boys [41]. However, lower achievement notwithstanding; boys have nevertheless reported higher self-efficacy than girls, a difference that also increased as they grew older [19]. In addition, it was found that science and science related careers are seen by students as "more suitable for boys" [18], [22, [41].

Primary school pupils, boys and girls alike, report an all-embracing support for conducting experiments in science classes. Despite the fact that pupils sometimes describe science as "dangerous and destructive" [18] most of them relate to experiments as the most interesting and the enjoyable part of the science lesson [20], [31]. In discussing science classes with students, studies suggest that in general primary school pupils expect science class to be "a bit different", involving more creative and practical hands-on activities than other classes [30], and see science as "exciting, magic, important and understandable" [20].

Science Education in Ethiopia Primary Schools

Primary education in Ethiopia is an integral part of the state’s compulsory education system. It is divided into grades 1 through 6, for students between the ages of six and twelve. The science curriculum employed today is based on the Ethiopian Ministry of Education (MOE), 1994 approach, which holds that science and technology are an essential part of proper modern education, necessary for any person striving to become an active contributing citizen. It includes topics from different scientific fields (life-science, material science, earth science and technology) which reflect interactions between science, technology and human society, such  as environmental issues, energy production (power stations etc.), human body and medicine, and the  plants and animals dwelling in students’ immediate environment.  Topics included in the primary school science curriculum deal with a number of fundamental scientific concepts and terms, such as the definition of matter and state of matter, power and energy, the definition of "system" etc. Pupils learn to solve hypothetical problems and practical assignments related to environmental issues, animals and their habitat, energy production and sources of energy in everyday life, basics of electrical engineering (electric circuit, conduction, insulating etc.), human body and diseases.

Research Goals and Questions

This study aims to characterize the attitudes of primary school students towards learning science. My research questions address three of the factors identified in Osborne (2003) as particularly influential in defining students’ attitudes. I therefore ask the following: a) which motivational factors are manifested in the attitudes of primary school students towards learning science? b) how do locus of control issues figure in and influence the attitudes of primary school students’ towards learning science? c) How do primary school students assess the relevance of the science they learn in school?

Research method


The study was conducted among primary school students ranging from grade 4 to grade 6, selected from twelve primary  schools in Debre Markos town to represent different socio-economic  backgrounds  and various types  of population points (town, village, agricultural residential area). The sample included 980 participants (420 boys (42.9% of the sample) and 560 girls (57.1% of the sample), a size sufficient to allow us to identify internal sub-groups in the sample and check their prospective interrelationship.

Research Tools

The questionnaire I used was developed especially for this study. I based the development of the items on previous research [3], [8], [17], [22], [30]. Most of that research focused on high school students, so I carried out a preliminary test, interviewing 5 primary school students to get feedback and adjust the items I developed for use in primary school.

Quantitative data collected from Likert-type items, however, is not sufficient for forming an understanding of the reasons underlying a phenomenon. While it is an efficient tool for identifying the nature of a phenomenon, quantitative research provides very little information for the purpose of understanding it (i.e., it can indicate that a phenomenon has occurred, but it cannot explain how or why). For these reasons my study combined the use of a Likert type questionnaire with open-ended questions, in which the participants were asked to explain the extent to which they agree with the questionnaire statements. Using qualitative and quantitative data together in this way lent greater credibility to the findings by triangulating the data through both source types [8].

Data Analysis

Since my research tools combined quantitative and qualitative techniques, data analysis involved statistical tests as well as the categorization of text. The explanations the students wrote for each Likert item and their answers to the open-ended questions Ire analyzed based on the interpretative methods of qualitative research [24] and according to the following steps:

1. Finding the main idea of every explanation – each was summarized into a short sentence representing its main point.

2. Division into categories – categorization was carried out concurrently with the interview analysis to ensure the identification of categories that are as precisely representative as possible. This process was evaluated and validated throughout by the researcher’s advisor to further ensure its accuracy.

Categories were numbered separately for each Likert item, as Ill as for every item from the second part of the questionnaire.  This allowed us to perform statistical tests in order to identify internal patterns within the explanations.

The quantitative analysis was carried out using SPSS 6.0 software. A reliability test was performed (Alpha Cronbach) over the total research sample with the result of 0.79, indicating high reliability. Confirmatory factor analysis showed three "clusters" of items, corresponding to the three factors described in the research questions. In order to check the significance of the differences between the clusters, One-way Repeated Measures Anova was performed for the three factors found in the factor analysis. The test showed a significance of F(2,978)=8.28, Wilks'  Λ=0.987,  p<0.001. Further t-tests for each pair of clusters showed a significant difference between Clusters #1 and #2 (t[979]=4.02, p<0.001), and between Cluster #1 and #3 (t[979]=2.33, p=0.02).


Table  1. Factor analysis findings (N=980)

Item / Factor loading  

Cluster 1


factors in



Cluster 2

Locus of

control in



Cluster 3




I enjoy science classes  because I  have interesting discussions on science topics




I enjoy science classes because the teacher and students do experiments




I'm not really interested in the science I learn in class  




I do  not enjoy science classes,  because I don't like class discussions




Science topics I learn in class are usually very interesting to me




If I don't understand a science concept, I'll turn to the teacher for explanation for explanation




I feel that I have a good command and understanding of science topics we learn




I take an active  part in science classes  and answer the teacher’s questions orally




I take part in class discussions and express my opinion




Science topics that I learn in school are important, because they help me understand different  phenomena in the  world around me




During science classes I deal with topics from everyday life




Science topics I learn in class are not related to real life








Percent difference  





On the whole, the attitude of my study population towards science was found to be positive. Data analysis showed that, when asked in the questionnaire to name their favorite subject, the overall population of the study named science third most popular at 11.6%, while the most popular was sports (46.3%) and the second most popular was mathematics (12.3%). The analysis also showed minor gender differences in the popularity of science: boys graded science their second most popular subject with 11.3% support, while girls graded it third most popular with 11.9%. The mean value at each one of three clusters found by the factor analysis was above 2.4 (Table 2), which suggests that the general attitude of the primary school students tends toward the favorable.

Table  2. Analysis Of Gender Differences



Mean value

Standard deviation














Locus of control in learning science









Relevance of










The results presented here, which address the factors contributing to this favorable attitude, are divided into three “clusters.” These correspond to the three influential factors addressed in the research questions, and reflect elements that have already been marked as important in the literature.  My analysis showed significant differences between the three clusters, implying that the influence of motivational factors and relevance issues on attitudes is stronger than that of locus of control.

Cluster 1: Motivational Factors and Their Influence on Student Attitudes

Data for this cluster was drawn from items 1 through 5 in the questionnaire. Analysis showed that students listed class discussions, lab experiments and interest in the topics being learned as motivational factors for learning science. As Table 3 indicates, a high percentage of the participants, girls and boys alike, chose the "not sure" option (a phenomenon that recurs in Clusters 2 and 3 below).

Table  3. Cluster 1- Motivation Factors In Learning Science



Degree of agreement





Degrees of freedom



2-Not sure

1- Disagree




































































































1*I enjoy science classes because I have interesting discussions about science-related topics.

2* I enjoy science classes because the teacher and students do experiments

3* I'm not really interested in the science I learn in class

4* I do not enjoy science classes, because I don't like class discussions

5* Science topics I learn in class are usually very interesting to me

Nevertheless, the results showed that most students see class discussion as interesting (49.8% agreed with statement 1).  The most common explanation for this was “because it is a funner way to study science.” Nevertheless, it is worth noting that only 5.5% of the students cited discussion as the source of interest in class, and only 9.6% see it as a good and efficient way of conducting a science class. The most common model arising from students' explanations (Table 4) is highly teacher-oriented. Thus 39.3% of students reported that usually science class is based on discussion of scientific topics conducted by the teacher, and 37.8% reported that reading in the textbook combined with teacher's explanation are the main components of the science lesson. Interest in the study topics is a key part of students' motivation to learn science, as shown by their extensive disagreement with statement 3 (55.8%). This is also supported by such explanations as “this year I learned many interesting things.”

While many of the items in the questionnaire did not show a significant difference between boys and girls, this cluster did reveal some gender differences in the students’ approach to experiments. 55.2% of girls stated that they like science classes because of experiments, while only 50.3% of boys supported this statement. This was further supported by the analysis of the students’ explanations for the Likert items in this cluster, which showed that 40.7% of girls vs. 37.2% of boys listed experiments as a main source of enjoyment in class: "I love experiments", "I like experiments, they are really interesting!", "I perform lab experiments and they are one of the main things I like about science classes". On the other hand, however, analysis of the answers to the items from the second part of the questionnaire suggests that boys are more dissatisfied with the small quantity of lab experiments in the class: 59.8% of the boys vs. 56.2% of the girls state that an interesting science class must include experiments, and 75% of the boys vs. 70% of the girls would like the class to be taught through experiments only. Interestingly, the number of boys and girls who asked for more experiments to be added to the regular science class was almost identical at 54.6% and 55% respectively. The seemingly contradictory evidence presented here suggests that, despite the apparent significance of the differences shown here, the question of gender-based attitudes to experiments in science class requires further inquiry.

Cluster 2: Locus of Control Issues and Their Influence on Student Attitudes

This cluster was addressed in items 6 through 9. Previous studies [22] show that mastery of the learning process is an important factor in generating meaningful learning. In my study, most of the students indicated that they did feel a mastery and an understanding of the material they taught class (52.7 agreement with item 7). 40.8% of the students said that they take an active part in classes and answer questions posed by the teacher in class (item 8), and 52.6% claimed to participate in discussions and express their ideas in class (item 9). Their explanations suggest that the main motive defining students’ mastery of the subject is self-efficacy, consisting of statements like: "I know and I understand, I've got excellent perception!"; "I feel that I know it Ill"; "I know I've got a lot to contribute to the discussion and that's why I always answer and speak out"; “Yes, because I understand and I’m ready to answer questions orally”; “I participate a lot, because the material is easy for me,” as Ill as statements indicating a lack of self-efficacy, such as: "I'm not a big shot in science." It is worth noting that on the whole students did not see testing as a primary indicator of academic success, with only 3.8% mentioning tests in their explanations for item 7.

The students’ explanations also indicate that they see active participation as a way to learn. 13% of them saw discussion and expressing opinions as an effective learning strategy, providing explanations like: “yes, in order to understand the material I ask” and “I keep trying all the time”. The explanations also mention other methods of studying, such as: “I listen in class and learn,” “yes, because I study at home.”

Aside from self-efficacy, the teacher is portrayed as a significant figure in the learning process. 79.8% agreed with item 6, that they would not hesitate in approaching their teacher if they do not understand something. Explanations show that students perceive the teacher as a source of knowledge and authority: “yes, because he knows how to help with difficulties!”; “yes, because she understands it best and can help me”; “because when the teacher explains, I understand the material.”

While analysis of the Likert items in this cluster revealed that more boys than girls declared their mastery of the subject (see Table 4, item 7*), the current study revealed no statistically significant gender differences in the ramification of locus of control issues for the students’ attitudes towards learning science. The dispersal of the students’ agreement with these statements is presented in Table 4 below.

Table  4. Science Class Components As Seen By The Students

Item#7. How would you prefer you science class to be conducted? Choose an alternative below



General population %


Female %

The teacher  runs a  discussion and a  conversation about science topics




Students conduct experiments




Students  read a textbook  and afterwards the teacher explains the subject




Students learn a new topic by doing research projects





Item #8. How are science classes conducted in your school? (choose an alternative from Question 7 above)



General population %


Female %

The teacher  runs a  discussion and a  conversation about science topics





Students conduct experiments




Students  read a textbook  and afterwards the teacher explains the subject





Students learn a new topic by doing research projects





Cluster 3: The Relevance of Science and Its Influence on Student Attitudes

This cluster was addressed by questionnaire items 10 through 12. The dispersal of the students’ agreement with these statements is presented in Table 5 below. Studies have shown that primary school students find the material learned in science more relevant than older students do [22]. My population found them highly relevant (77.4% agreement with item 10). Explanations show the importance of science as a central component in the students’ interest (26.9%). “It’s fun to learn important things”; “they help me understand important things.” Another recurring factor in the students’ explanations was curiosity (at 11.7%, the third most prominent explanation for item 10): “science classes help me understand phenomena that I’ve wanted to understand for a long time.” Interestingly, these two reasons showed a certain difference of emphasis here between boys and girls, with boys placing more emphasis on the importance of science (21.6% of the boys vs. 19.2% of the girls), while more girls based their need to learn on interest and curiosity (46.3% of girls vs. 39% of boys). A third relevant component for the students was the benefit/value of learning science. This topic came up in the explanations for all of the items in this cluster, but only in those for item 10 did it find a significant percentage of support (17.8%).

Gender differences found in this cluster Ire statistically significant in each one of the three Likert items, as shown in Fig. 8. 50.2% of the girls vs. 43.6% of the boys stated that in science classes they deal with issues from everyday life (item 11*). Moreover, in item 12*, 57.7% of the girls vs. 51.2% of the boys confirmed (inversely, by denying the negative) that the science topics they learn in class are related to real life, a point that is also stressed in the explanations students wrote for those items, including: "I deal with problems from real life, like heart and health", "Science is related to all people", "Science is related to real life, like power stations." The girls Ire also more positive in affirming (item 10*) that science they learn in class helps them understand the world around them (80.8% vs. 73.2% respectively), while the explanations for this item showed that one of the main factors of influence here is interest and curiosity: "Things in the world are so interesting to me", "It's fun to learn new things."

Table 5. Cluster 2 - Locus Of Control In Learning Science




Degree of agreement





Degrees of freedom



2-Not sure

1- Disagree

















































































6* If I don't understand a science concept, I'll turn to the teacher for an explanation

7* I feel that I have a good command and understanding of the science topics I learn

8* I take an active part in science classes and answer the teacher?s questions orally

9* I take part in class discussions and express my opinion

Table 6. Cluster 3 - Relevance Of Science




Degree of agreement





Degrees of freedom





2-Not sure

1- Disagree


































































10*Science topics that I learn in school are important because they help me understand different phenomena in the world around me

11* during science classes I deal with topics from everyday life

12* Science topics I learn in class are not related to real life


The primary conclusions that may be drawn from the results of my study are:

  1. Most of the students saw discussion in science class as a source of interest, but their explanations and the answers to the open-ended questions indicate that the most common model of a science lesson they see is readings from the textbook, accompanied by the teacher’s explanations.
  2. The central source of the students? Interest is experiments.
  3. Most of the students find the topics studied in science class interesting.
  4. Only about one half of the students claim to take an active part in classes, answering questions asked by the teacher in class, taking part in class discussions, and expressing their opinions.
  5. The teacher is perceived as a significant part of the learning process. Most of the students claimed that they would not hesitate to ask their teacher to explain something they do not understand. The students’ explanations indicate that they see the teacher as a primary source of information and authority.

Motivational Factors

The motivational factors raised by the students in this study included class discussion and experiments. A large percentage of the students described class discussion as both interesting and enjoyable. Nearly half of the students saw it as a tool to make science class more fun, but only a small percentage mentioned it as an effective and interesting way to learn. This contradiction most likely arises from the fact that students see discussion as a tool for independent thought, which allows them a certain amount of freedom and raises their involvement in the learning process [23], whereas in practice their experience is of class discussions governed by the teacher’s closed questions, which  do not encourage  independent thought,  but require the memorization of details and facts [23].

Indeed, the students’ answers show that the most common model of a science class they see is a lesson based on reading from the textbook, explanations from the teacher and discussion which the teacher controls – a result in keeping with findings in other literature [21], [23] Despite the importance of discussion to creating a meaningful learning process, teachers are minimal in their use of it [37]. Reasons for this cited in the literature include the pressure of being unsure of the material, the lack of training for teachers in running an effective discussion, and teachers’ psychological difficulty in changing the teaching style to which they have been accustomed [21], [23]. My results suggest that providing teachers with the proper training and gradually introducing discussion into classroom routine would constitute a positive step [10]. In addition to class discussion, experiments and lab work in science class have for several decades been a point of interest in science education research [20]. My study supports previous literature in showing that more than half of the students see experiments as a significant point of interest in classes, claiming that science class becomes much more interesting when it includes experiments [20], [31].  Furthermore, the students’ explanations indicate their belief that there are not enough experiments currently included in their science studies. Nearly two thirds of my students claimed that the main thing they would like added to the science classes in their school is experiments. A similar percentage maintain that for a science class to be “truly interesting”, it must include an experiment. Other researchers have raised similar results [20], [30].

Interestingly, while the percentage of girls in this study who cited experiments as a particular source of their enjoyment of science classes was higher than that of the boys, more boys than girls complained that the amount of lab experiments in science classes was insufficient, and more boys wanted science classes to be taught mainly by means of experiments. This discrepancy may possibly be explained by the different definition girls and boys have for the term “experiment”. Most of the experiments in classes are done as demonstrations performed by the teacher only, while the class watched, and this may not have been enough for boys. Boys see science as something "dangerous, destructive, exciting" [18]) and engage in more out-of-class activities involving technical or scientific equipment, such as electrical or optical devices [19]. These findings suggest that boys may be unsatisfied with the number of “hands-on” experiments included in science classes. Some researchers [19]; Adamson et al., 1998 have mentioned that girls' attitude to experiments is also influenced by their previous experience with science. Perhaps in primary school girls have not yet accumulated any negative science experience and they still see it as enjoyable. Moreover, biology and chemistry are considered "girl-oriented" and a lot of the science curriculum is therefore "girl-favored" [22], since it includes less physics or technology experiments. These factors may explain why boys might feel deprived and express a desire for more experiments.

Research has shown that primary school students expect science class to be more “practical and creative” than their other classes [31]. They see science as something “exciting” [22]. A lack of response on the part of teachers and curriculum to this expectation could significantly diminish students’ motivation towards science [31]. I must therefore address this, designing primary school science classes that include a greater number of experiments render science class more interesting and challenging for the students.

Locus of Control in the Learning Process

Approximately half of the students participating in this study claimed that they are active in classes, answer the teacher’s questions, participate in discussions and express their opinions in class. Their explanations indicate that the principle motivation behind this is self-efficacy. Other studies support this correlation, and suggest that the connection is mutual – some show active participation to enhance students’ self-efficacy [33], while others also argue that students with high self-efficacy tend to participate more often [39], [42] has also found that students’ level of self-efficacy determines their learning methods, so that the higher their self-efficacy, the more active their class participation becomes.

It is interesting to note that in studies into the correlation between active participation and self-efficacy, results indicated that the conduct of the teacher can influence these mutual [11], [29]. The question of the teacher’s role in the learning process arose in my study as well. My students perceived teachers as a significant part of the learning process, seeing them as a source of information and authority. The students in my study voiced a great deal of trust in their teachers, proclaiming their readiness to approach them with questions about material they did not understand.

This echoes the results of other studies into the figure of the primary school teacher [22]. The primary school science teacher is perceived by most students as someone who loves what they teach, is ready to answer questions, and provides personal attention and leadership [7]. As mentioned, teacher conduct and self-efficacy may be connected, with students drawing upon their teacher for indications of their progress, and using these in their own assessment of their ability for continued learning [11], [14].

My findings suggest that despite the relatively high level of self-efficacy displayed by these students and their active participation in class, the science teacher nevertheless has a significant role in creating effective learning processes in the lesson. An in-depth understanding of the mutual interactions between the elements comprising the locus of control in science studies will allow teachers to make proper, informed choices when deciding upon courses of action.

5.3 Relevance of Science Studies

The relevance of learning science has been at the center of research education for several years. In light of the declining tendency of youthful interest in science, researchers have been trying to identify those elements that affect students’ perception of the topic’s relevance [20], [26], [35]. My study found that curiosity is what serves as a significant basis for students’ decision that what they learn in class is relevant. My data showed a substantial amount of curiosity towards the material on the part of the students. Other studies have similarly found that close to sixty percent of students of primary school age claim that science classes arouse their curiosity [41]. Another element that influenced the students’ perception of science’s relevance in this study was their awareness of the importance of studying science. The students’ explanations indicate that they were interested in the material they learned because they considered it important. This phenomenon too has already been remarked upon in the research literature [7], [26], [31].

While my findings in this area correlate to those of other studies, which also indicate that primary school students see what they learn is science class to as relevant to their lives [20], my study nevertheless revealed a measure of ambiguity amongst my students. This was manifested as a gap between the percentage of students who agreed with the Likert items on the topic of relevance, and those who also expressed similar sentiments in their explanations. The ambivalence suggested here may be the result of teaching methods that do not encourage students’ natural curiosity, such as teachers’ complete control over activity in class, a lack of independent work and requiring students to do an overlarge amount of reading and writing [17], [20]. Another possible explanation is the disparate messages students get from their environment: on the one hand, the educational system stresses the importance of studying science and succeeding academically, while on the other, students’ close environment does not always define being a scientists as the highest form of self-actualization and success.

The reason underlying the necessity of learning science was one source of gender difference found in this study. A comprehensive overview of the various available studies suggests on the whole that at primary school ages the two genders’ enthusiasm for the subject of science is nearly identical [36]. In my study girls explained that I need to learn science because of curiosity and desire to learn more about the surrounding world, while the boys explained that learning science is necessary because science is important for human society. This difference may be the result of social expectations, since boys more than girls are expected to succeed in science-related disciplines and go on to science related careers [2], [18] However, further inquiry is yet to be made into what exactly boys mean by the term “important”.

Girls and boys in my study also showed different perceptions of the relevance of science to their lives. More girls confirmed that the science they learned in class was relevant, which is consistent with findings in literature that girls tend to see science as something related directly to people and close environment [1], [6]. The primary school science curriculum does indeed include many topics dealing with practical everyday issues and the immediate environment of humans. This seems to increase the emotional involvement of girls, and subsequently to increase their perception of learning science as immediately relevant [31].


[1] Adamson, L. B., Foster, M. A., Roark, M. L., & Reed, D. B. (1998). Doing a science project: Gender differences during childhood. Journal of Research in Science Teaching, 35(8), 845-857.

[2] Andre, T., Whigham, M., Hendrickson, A., & Chambers, S. (1999). Competency beliefs, positive affect, and gender stereotypes of elementary students and their parents about science versus other school subjects. Journal of Research in Science Teaching, 36(6), 719-747.

[3] Atwater, M. M., Wiggins, J., & Gardner, C. M. (1995). A study of urban middle school students with high and low attitudes toward science. Journal of Research in Science Teaching, 32 (6), 665-677.

[4] Baird, J. H., Lazarowitz, R., & Allman, V. (1984). Science choices and preferences of middle and secondary school students in Utah. Journal of Research in Science Teaching, 21,47-54.

[5] Baram-Tsabari, A., Yarden, A., Sethi, R. J., & Bry, L. (2009). Asking scientists: A decade of questions analyzed by age, gender, and country. Science Education, 93(1), 131-160.

[6] Brophy, J. (2004). Motivating Students to learn (2nd ed). Erlbaurn: Mahwah, NJ.

[7] Caleon, I. S., & Subramaniam, R. (2008). Attitudes towards science of intellectually gifted and mainstream upper primary students in Singapore. Journal of Research in Science Teaching, 45 (8), 940-954.

[8] Creswell, J. W., & Tashakkori, A. (2007). Developing Publishable Mixed methods Manuscripts. Journal of Mixed Methods Research, 2(1), 107111.

[9] Den Brok, P., Fisher, Darrell, & Scott, RoIna. (2005). The Importance of Teacher Interpersonal Behaviour for Student Attitudes in Brunei Primary Science Classes. International Journal of Science Education, 27(3), 765-779.

[10] Driver, R., Newton, P., & Osborne, J. (2000). Establishing the Norms of Scientific Argumentation in Classrooms. Science Education, 84(3), 287-312.

[11] Furrer, C., & Skinner,  E. (2003).  Sense of relatedness as a factor in students's academic engagement and performance. Journal of Educational Psychology, 95(1), 148-162.

[12] George, R. (2000). Measuring Change in Students' Attitudes toward Science over Time: An Application of Latent Variable Growth Modeling. Journal of Science Education and Technology, 9(3), 213-225.

[13] Haladyna, T., Olsen, R., & Shaughnessy, J. (1982). Relations of student, teacher, and learning environment variables to attitudes toward science. Science Education, 66(5), 671-687.

[14] Hamre, B. K., & Pianta, R. C. (2005). Can Instructional and Emotional Support in the First-Grade Classroom Make a Difference for Students at Risk of School Failure? Child Development, 76(5), 949-967.

[15] Hanrahan, M. (1998).  The effect  of learning environment factors  on students’  motivation and learning. International Journal of Science Education, 20(6), 737-753.

[16] Jang, H., Reeve, J., & Deci, E. L. (2010). Engaging Students in Learning Activities: It is Not Autonomy Support or Structure but Autonomy Support and Structure. Journal of Educational Psychology, 102(3), 588-600.

[17] Jarman, R. (1993). Real experiments with Bunsen Burners: Pupils’ perceptions of the similarities and differences between primary and secondary science. School Science Review, 74(268), 19-29.

[18] Jones, M. G., Howe, A., & Rua, M. J. (2000). Gender Differences in Students' Experiences, Interests, and Attitudes toward Science and Scientists. Science Education, 84 (2), 180-192.

[19] Kahle,  J. B., & Rennie,  L. J.  (1993). Ameliorating Gender Differences in  Attitudes about Science:  A Cross-National Study. Journal of Science Education and Technology, 2(1), 321-334.

[20] Murphy, C., & Beggs, J.  (2001). “Pupils” attitudes, perceptions and understanding of primary  science: Comparisons between Northern Irish and English schools’. Paper presented at the Annual Conference of the British Educational Research Association, University of Leeds, Leeds, and 13–15 September.

[21] Naylor, S., Keogh, B.,  &  Downing, B.  (2007). Argumentation and primary science. Research in Science Education, 37(1), 17-39.

[22] Neathery, M.  F. (1997). Elementary and secondary students' perceptions toward science: Correlations  with gender, ethnicity, ability, grade, and science achievement. Electronic Journal of Science Education, 2(1), 11.

[23] Newton, P., Driver, R. & Osborne, J. (1999). The place of argumentation in the pedagogy of school science. International Journal of Science Education, 21(5), 553-576.

[24] OECD. (2007). Executive Summary PISA 2006: Science Competencies for Tomorrow’s World. Paris: OECD. Ormerod, M. B., & Duckworth, D. (1975). Pupils Attitudes to Science. Slough: NFER Publishing Company.

[25] Osborne, J., & Collins, S. (2001). Pupils' views of the role and value of the science curriculum: A focus-group study. International Journal of Science Education, 23(5), 441-467.

[26] Osborne, J., Simon, S., & Collins, S. (2003). Attitudes towards Science: A Review of the Literature and Its Implications. International Journal of Science Education, 25 (9),1049-1079.

[27] Palmer, D. (2005). A motivational view of constructivist-informed teaching. International Jmynal of Science Education, 27, 1853-1881.

[28] Patrick, H., Ryan, A. M.,  & Kaplan,  A. (2007). Early Adolescents'  Perceptions  of the Classroom Social Environment, Motivational Beliefs, and Engagement. Journal of Educational Psychology, 99(1), 83-98.

[29] Pell, T., & Jarvis, T. (2001). Developing attitude to science scales for use with students of ages from five to eleven years. International Journal of Science Education, 23, 847–862.

[30] Reiss, M. J. (2004). Students’ attitudes towards science: A long term perspective. Canadian Journal of Science, Mathematics and Technology Education, 4,97-109.

[31]  Reiss, M. J. (2005). The importance of affect in science education. In Steve Alsop (Ed), Beyond Cartesian Dualism (pp. 17-25). Netherlands: Springer

[32] Richter, F. D. & Tjosvold, D. (1980). Effects of student participation in classroom decision making on attitudes, peer interaction, motivation, and learning. Journal of Applied Psychology, 65,74-80.

[33] Roeser, R. W., Midgley, C., & Urdan, T. C. (1996). Perceptions of the school psychological environment and early adolescents’ psychological and behavioral functioning in school: The mediating role of goals and belonging. Journal of Educational Psychology, 88(3), 408-422.

[34] Schreiner, C., & Sjøberg,  S. (2004). Sowing the seeds of ROSE. Background, Rationale,  Questionnaire Development and Data Collection for ROSE (The Relevance of Science Education) - a comparative study of students' views  of science and science education.  Department of Teacher Education and School Development, University of Oslo.

[35] Sorge, C. (2007). What Happens? Relationship of Age and Gender with Science Attitudes from Elementary to Middle School. Science Educator, 16(2), 33-37.

[36] Southerland, S., Kittleson, J., Settlage, J., & Lanier, K. (2005). Individual and group meaning-making in an urban third  grade classroom: Red fog, cold cans, and seeping  vapor.Journal  of Research in Science teaching, 42(9), 1032-1061.

[37] Speering, W., & Rennie, L. (1996). Students' Perceptions about Science: The Impact of Transition from Primary to Secondary School. Research in Science Education, 26 (3), 283-298.   [38] Strauss, A., & Corbin, J (1990). Basics of Qualitative Research: Grounded Theory Procedures and Techniques. London: Sage Publications.

[39] Tobin, K. (1990). Research on Science Laboratory Activities: In Pursuit of Better Questions and Answers to Improve Learning. School Science and Mathematics, 90(5), 403-418.

[40] Tymms, P. (1997). Science in Primary Schools: an investigation into differences in the attainment and attitudes of pupils across schools. Research in Science and Technological Education, 15 (2), 149-160.

[41] Weinberg, M.  (1995). Gender Differences in Student Attitudes toward Science:  A Meta-Analysis of the Literature from 1970 to 1991. Journal of Research in Science Teaching, 32(4), 387-398.

[42] Zimmerman, B. J. (2000). Self-Efficacy: An Essential Motive to Learn. Contemporary Educational Psychology, 25(1), 82-91.


Study Of Factors Affecting Persistence Amongst Distance Learners In Distance Education Institutes

Study Of Factors Affecting Persistence Amongst Distance Learners In Distance Education Institutes

Maryam Hassani Golyakh,
Ph.D student,
Department of Education,
Panjab University, Chandigarh


This study is an investigation of the persistence amongst distance learners in Indian Universities. The study was conducted on Distance learners enrolled in study centers of IGNOU (Indira Gandhi National Open University), Alagappa University and Panjab University. The objectives of the study were to study contribution of students’ characteristics including gender, marital status, working status and age in persistence among Distance learners. Persistence in Distance Education Scale (PDES) and a Questionnaire for demographics of students were developed and used for the study. Seven hundred questionnaires were distributed to distance learners during their PCP (Personal Contact Program) classes from the centers located in Chandigarh and New Delhi. 527 questionnaires were completed, tabulated and statistical analysis were done to analyze the data. Significant difference in persistence with regard to gender, age groups, marital and employment status were found.

Key words: Persistence, Distance Learning


There has been continuous development for distance education as an alternate to face-to-face instruction since its beginning in the mid-1800. This growth is witnessed by the fact that in 2002 nearly 78 percent of all adult students had done education in some forms of distance learning. This massive demand of adults asking distance education courses has occurred in part because of the progress in technology and in part because of the state of modern life. While society calls for lifelong learning, employment and family responsibilities call for adults to seek forms of education other than traditional, face-to-face instruction. Distance education affords adults the required formal education while allowing for flexible scheduling.

With the growth of distance-education has come the problem of exceedingly high attrition rates. Carr and Ledwith (2000) found rates to exceed 40 percent in some institutions. In an attempt to identify causes for non-completion, numerous studies have centered on application of a variety of traditionally-based theoretical models to the distance education setting. Diaz (2002) used a test of learning styles to determine the correlation between students who scored as independent, self-directed individuals and completion of online instruction. Diaz reported a statistically significant correlation between self-motivation and academic persistence.

There is a critical need for institutions and open learning to be able to predict with some accuracy the potential persistence of distance education students. With institutions of higher education generally receiving governmental support based on enrollment, the issue of attrition is particularly important. If rate of completion could be enhanced, through better placement and counseling of distance education students, subsequent fiscal budgets could become more predictable.

The current study sought to find out the factors affecting distance learners’ persistence in India.  This study examined the persistence of distance learners in three university of India with relation to their age, gender, marital status and working status. While numerous variables such as financial aid (Parker, 1999) and experience levels of instructors (Carr, 2000) have been stated as predictors of attrition in distance education, student’s demography can consistently be useful for decision makers. The problem facing academic administrators and instructors tasked with finding answers to the current high levels of attrition in distance delivered courses is the limited number of studies utilizing this variable.


Vann (1988) conducted a study on pre-college to determine how it related to student’s performance and persistence (as measured by following dependent variable: number of terms completed, number of hours completed, cumulative grade point average, number of changes of major and proportion earning a degree). He found out no significant relationship between males and females within the matriculant group on the way of the measures used in his study.

Kim Rapp (2003) examined the factors associated with persistence decisions of doctoral students affiliated with two programs of interdisciplinary study at two major research universities. He concluded that faculty and student affairs staff should be advised that the male and female students leave college for different reasons (e.g., housing and major departments). Any program or policy designed to increase student persistence should take gender difference into account.

Cohen, Crecilla Vonetta (2004) studied the impact of personal resources on college persistence and educational attainment. Results indicated that, net of other important background characteristics, personal resources ad measured by respondent’s aspirations, advanced math taking and SAT/ACT preparation efforts significantly influence educational outcomes. However, their educational attainment affected more by:

-          Background characteristics

-          Personal resources

-          Aspiration rather than persistence.

The effects of advance math course on degree attainment are significantly stronger for women.

Chao, Maureen (2004) studied academic performance and persistence among international students with and without participation in an intensive English as a second language program. NO significance was found in academic success for duration of attendance at the college between with and without regular participation groups. Demographical information revealed differences in academic performance and persistence related to the independent variables of age group, country of citizenship/region, gender and for former IESL group, the number of quarters spent in the IESL program.

Hoef, Ted F. (2004) studied within-year persistence of four-year college students by gender. This study found that the sample of male four-year college students had 24 variables that were significant and associated with persistence. Female college students had 20 variables that were significant and associated with persistence. The differences between males and females included:

-          Ethnicity

-          High test scores

-          Dependent

-          Father with college experience

-          Doctoral institution, were positively associated with persistence for males but not females; low test scores and living on campus were positively associated with persistence for females but not males;  high debt and low debt were negatively associated with persistence for males but not females and Hispanic ethnicity was negatively associated with persistence for females but for males.

Perantoni (2010) experimented a Course design based on the Kolb learning style as it relates to student success in online classes to determine if there was a relationship between the accommodator or diverger learning styles and mean improvement scores in a class. Gender, ethnicity, and year in school were also tested, but no statistically significant relationship was identified relative to the mean improvement scores.

As the review of the literature for persistence indicates there is not homogeneity among the results of the studies done on Persistence with regard to gender but most of them found significant difference between males and females so this study with the purpose of scrutinizing the gender differences for higher education persistence along with age, marital and working status differences was done in three universities of India.


With each of the research hypotheses based on review of the literature a null hypothesis for statistical analysis is proposed.

H1. There will be significant difference in Persistence among distance learners with reference to gender.

H01 there will be no significant difference in Persistence among distance learners with reference to gender.

H2.  There will be significant difference in Persistence among distance learners with reference to marital status.

H02. There will be no significant difference in Persistence among distance learners with reference to marital status.

H3. There will be significant difference in Persistence among distance learners with reference to working status.

H03. There will be no significant difference in Persistence among distance learners with reference to working status.

H4. There will be significant difference in Persistence among distance learners with reference to age in three groups (G1= below 23, G2= 23-30 and G3= below 30).

H04. There will be no significant difference in Persistence among distance learners with reference to age in three groups (G1= below 23, G2= 23-30 and G3= below 30).


The method of investigation used was descriptive and exploratory survey. For the current investigation, the population was the distance learners of IGNOU (Indira Gandhi National Open University, Distance Education Department of Alagapa University, Kerela and University School of Open learning of Panjab University, Chandigarh (USOL). The study centers of these institutions at Chandigarh and New Delhi which were holding PCP classes were selected for data collection.

To study the factors affecting persistence among distance learners, a survey questionnaire comprising of two sections was used. In section I, Student Characteristics variables of gender, age (three groups below 23 years old, 23-30 years old and above 30 years old), marital status (married and single), were included. Section II of the survey questionnaire consisted of Student Persistence measured by endurance/perseverance characteristics of the students and intent to continue enrollment were investigated.

Questionnaires were distributed among 700 students who were attending PCP classes in both cities and 527 were collected back.

Both survey questionnaires were hand scored with SA=5, A=4, U=3, D=2, SD=1 for positive items and SA=1, A=2, U=3, D=4, SD=5 for negative items.


To determine whether significance difference exists, null hypotheses were tested. Independent sample t-tests were used. t-ratio Tables are as following:

Table 1 .Significance Of Difference In Persistence Among Distance Learners With Regard To Gender, Marital And Working Status





Std. Deviation

Std. Error Mean



Sig. (2-tailed)















Marital Status














Working Status









Not working






t-ratio table 1 indicates the significant difference in persistence of Male and Female distance learners as the obtained t-value (t=-3.268 with 512.522 degree of freedom) were found to be significant at 0.01 level of confidence (two-tailed p-value is 0.001) when equal variances were assumed. The mean score of Persistence of Male distance learners was found to be (M=61.42) which is lower than that of female distance learners (M=63.73). So sex did significantly affect their Persistence. Hence null hypothesis is rejected.

These results are similar with the findings of  (Vann 1988,  Kim Rapp 2003, Cohen, Crecilla Vonetta 2004, Chao, Maureen 2004, hoef, Ted F. 2004, Perantoni 2010) that there was significant difference between male and female distance learners on Persistence.

Therefore hypothesis 1that there will be significant difference in persistence of male and female distance learners stands accepted.

The outputs for Married and Single are shown in this table reveal statistically significant difference in Persistence of Married and Single distance learners as the obtained t-value (t=3.922 with 527 degrees of freedom) were found to be significant at 0.01 level of confidence (two-tailed p-value is 0.000) when equal variances assumed.  The mean score of Persistence of Married distance learners was found to be (M=65.63) which is higher than that of and Single distance learners (M=61.96). Therefore marital status did significantly affect their Persistence.

These results are similar with the findings of ( Key, Roby Van 1988, Boldt 2000, Hoef, Ted F. 2004) that there was significant difference between Married and Single distance learners on Persistence

Therefore hypothesis 2 that there will be significant difference in persistence of Married and Single distance learners stands accepted and null hypothesis is rejected.

The outputs for Not working and Working are shown in the table1 reveal the statistically significant difference in Persistence of Not working and Working distance learners as the obtained t-value (t=4.683 with 527 degrees of freedom ) were found to be significant at 0.01 level of confidence when equal variances assumed (two-tailed p-value is 0.000). The mean score of Persistence of Not working distance learners was found to be (M=61.10) which is lesser than that of and Working distance learners (M=64.39). Therefore working status did significantly affect their Persistence.

These results are similar with the findings of (Blong, John Thomas 1992, Brien, Susan Jeanne 1992) that there was significant difference between Not working and Working distance learners on Persistence.

Therefore hypothesis 3 that there will be significant difference in persistence of Not working and Working distance learners stands accepted and null hypothesis is rejected. The mean difference of different groups in their persistence is as below. As it indicates the persistence of females are more than males, Married more than singles and not working more than working.

Table 2 .Significance Of Difference In Persistence Among Distance Learners With Regard To Age (G1,G2,G3)


Age sub-groups



Std. Deviation

Std. Error Mean



Sig. (2-tailed)

G1 & G2

< 23













G1 & G3

< 23








> 30





G2 & G3









> 30






t-ratio Table 2 indicates the significant difference in persistence of distance learners with regard to three age groups which are G1: below 23 , G2: 23-30 and G3: above 30. The first raw is for G1 and G2 which reveals statistically significant difference in Persistence of below 23years and 23-30 years old distance learners as the obtained t-value were found to be significant (t= 2.358 with 468 degrees of freedom) at 0.05 level of confidence when equal variances assumed(two-tailed p-value is 0.019). The mean score of Persistence of below 23years old distance learners was found to be (M=61.30) which is higher than that of and 23-30 years distance learners (M=63.13). Therefore age did significantly affect their Persistence.

These results are similar with the findings of (Mickens, Caesar 1995, Motter, Kristi Lynn 2003, Chao, Maureen 2004) that there was significant difference between below 23years and 23-30 years old distance learners on Persistence

Therefore hypothesis 4(G1-G2) that there will be significant difference in persistence of below 23years and 23-30 years old distance learners stands accepted and the null hypothesis is rejected.

The outputs for below 23years and above 30 years old are shown in the Table 2 reveal the statistically significant difference in Persistence of below 23years above 30 years old distance learners as the obtained t-value (t-ratio is 5.412 with 353 degrees of freedom) were found to be significant at 0.01 level of confidence when equal variances assumed (two-tailed p-value is 0.000). The mean score of Persistence of below 23years old distance learners was found to be (M=61.30) which is lesser than that of and above 30 years old distance learners (M=67.39). Therefore age did significantly affect their Persistence.

These results are similar with the findings of (Mickens, Caesar 1995, Motter, Kristi Lynn 2003, Chao, Maureen 2004) that there was significant difference between below 23years and above 30 years old distance learners on Persistence.

Therefore hypothesis 4 (G1-G3) that there will be significant difference in persistence of below 23years and above 30 years old distance learners stands accepted and null hypothesis is rejected.

The outputs for 23-30 years old and above 30 years old are shown in this Table reveal statistically significant difference in Persistence of 23-30 years old above 30 years old distance learners as the obtained t-value (3.565 with 231 degrees of freedom) were found to be significant at 0.01 level of confidence when equal variances assumed (two-tailed p-value is 0.000). The mean score of Persistence of 23-30 years old distance learners was found to be (M=63.13) which is lesser than that of and above 30 years old distance learners (M=67.39). Therefore age did significantly affect their Persistence.

These results are similar with the findings of (Mickens, Caesar 1995, Motter, Kristi Lynn 2003, Chao, Maureen 2004) that there was significant difference between 23-30 years old and above 30 years old distance learners on Persistence

Therefore hypothesis 4(G2-G3) that there will be significant difference in persistence of 23-30 years old and above 30 years old distance learners stands accepted and the null hypothesis is rejected. The graph of mean difference of Persistence among different age groups is as below:


The study led the researcher to conclude that :

  1. There is significant difference in persistence of male and female distance learners.
  2. There is significant difference in persistence of Married and Single distance learners.
  3. There is significant difference in persistence of Not working and Working distance learners.
  4. a. There is significant difference in persistence of below 23years and 23-30 years old distance learners.

b. There is significant difference in persistence of below 23years and above 30 years old distance learners.

c. There is significant difference in persistence of 23-30 years old and above 30 years old distance learners,


The results of the study generated the implications that gender, age, marital status and working status does impact the persistence of higher education distance learners. So university administrators and policy makers who are trying to serve the needs of distance learners should pay attention to these factors. The requirements of separate groups should be addressed and researched upon.


Blong, John Thomas (1992). The relationship of selected variables to student attrition and persistence, Dissertation Abstracts International, Vol. 53, No.7, P.2260-A.

Brien, Susan Jeanne (1992). A case study in recruitment, persistence and perceived quality, Dissertation Abstracts International, Vol.53, No.7, P.2203-A.

Carr, R. & Ledwith, F. (2000). Helping disadvantaged students. Teaching at a distance, 18, 77-85.

Carr, S. (2000). As distance education comes of age, the challenge is keeping the students. The Chronicle of Higher Education.

Chao, Maureen (2004). Academic performance and persistence among international students with and without participation in intensive English as a second language program. Dissertation Abstract, University of Nebraska-Lincoln. Retrieved from

Cohen, Crecilla Vonetta (2004). Principles and methodology for CAI design, dissertation Abstract, The university of Arizona. Retrieved from

Diaz, D., & Cartnal, R. (1999). Student’s learning styles in two classes: Distance learning and equivalent on-campus, College Teaching, 47(4), 130-135.

Hoef, Ted F. (2004). Within-year persistence of four-year college students by gender, dissertation Abstract, University of Missouri-Saint Louis. Retrieved from

Key, Roby Van (1988). Characteristics that differ between persisting and non-persisting freshmen students in Bible college, Dissertation Abstracts, International, Vol. 50, No.3, P.584-A.

Kim Rapp (2003). Persistence decisions of doctoral students affiliated with interdisciplinary programs: A case study. Retrieved from

Kim Rapp (2003). Persistence decisions of doctoral students affiliated with interdisciplinary programs: A case Study. Retrieved from

Mickens, Caesar (1995). Effects of Learner characteristics and computer-based instruction on achievement and persistence of adult basic education (ABE) and adult secondary education(ASE) students, Dissertation Abstracts International, Vol.56, No.5, P.1626-A.

Motter, Kristi Lynn (2003). Student versus staff perceptions of selected university student services and relationships between student satisfaction and academic perseverance, Dissertation Abstract, University of Southern Mississipi. Retrieved from

Parker, A. (2003). Identifying predictors of academic persistence in distance education. USDLA Journal, 17 (1). Retrieved from

Perantoni, E. (2010). Course design based on the Kolb learning style as it relates to student success in online classes. Ed.D. dissertation, Lindenwood University, United States -- Missouri. Retrieved April 27, 2010, from Dissertations & Theses: Full Text.(Publication No. AAT 3389397).

Vann Robert, G. (1988). Pre-college stopout : how it relates to students' performance and persistence. Thesis (Ph. D.). Southern Illinois University at Carbondale. Retrieved from

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