Effect of Smart Classroom Learning Environment on Academic Achievement of Rural High Achievers and Low Achievers in Science

Jena, Prakash Chandra

doi:10.18052/www.scipress.com/ILSHS.3.1

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Effect of Smart Classroom Learning Environment on Academic Achievement of Rural High Achievers and Low Achievers in Science

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Abstract:

The present study is an experimental one and conducted in Jalandhar district of Punjab. The investigators has taken 60 secondary school students from Royal Convent School by using simple random sampling technique. For conducting experiment the investigator has used two group randomized pre-test and post-test design. For collection of data the investigator has used an achievement constructed and standardized by the investigator and t-test has also used for analysis and interpretation data. The result of the study reveals that smart class learning environment is better to teach both low achievers and high achievers than traditional class.

Info:

Periodical:

International Letters of Social and Humanistic Sciences (Volume 3)

Pages:

1-9

DOI:

https://doi.org/10.18052/www.scipress.com/ILSHS.3.1

Citation:

P. C. Jena, "Effect of Smart Classroom Learning Environment on Academic Achievement of Rural High Achievers and Low Achievers in Science", International Letters of Social and Humanistic Sciences, Vol. 3, pp. 1-9, 2013

Online since:

September 2013

Authors:

Prakash Chandra Jena

Keywords:

High Achievers, Low Achievers, Smart Classroom Learning Environment

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Distribution:

Open Access

This work is licensed under a
Creative Commons Attribution 4.0 International License

References:

Allen B., Second Survey of Research in Education: New Delhi 13 (2009) 14-22.

Ainley Mary, Hidi Suzanne, Berndorff Dagmar, Journal of Educational Psychology 94(3) (2002) 545-561.

Burnand et al., Social Science Research Unit Institute of Education 6 (2004) 5-16.

Dhamija K., A Computer Study of Effectiveness of these Approaches of Instructions- Conventional, Radio-Vision and Modular Approach on Achievement of Students in School Studies, Ph. D Dissertation Delhi University, Delhi (2000).

K. Dalacosta, M. Kamariotaki-Paparrigopoulou, J. A. Palyvos, N. Spyrellis, Computers and Education 52 (4) (2009) 741-748.

Ena Howse, Effect of Smart Board Interactive White Board on Concept Learning, Generation of Ideas, group process and user Interactive Satisfaction, (2000).

Gupta N. K., Research in Teaching of Science. New Delhi: APH Publishing Corporation (2007).

Gosh B. N., Scientific Methods and Social Research. New Delhi: Sterling Publishers Private Limited 1999.

Kumar et al., Indian Educational Review 27(3) (2000)16-34.

Sidhu N. S., Computer Applications in Education for the M. Ed. (Educational Technology) Course, M. Ed. Dissertation, Punjab University Chandigarh (2002).

Sahoo P. K., Educational Media Research and Instructional Management of Distance Education 11(1995).

Tuzun et al., Computer and Education 52(1) (2009) 68-77.

Raziye et al., Journal of Computer ICT in Education 2(12) (2010) 841-851.

Ray P. K. S., Technology of Instructional Design. (Part-1), Dominant Publication, New Delhi (2006).

Rose and Stella, Journal of Educational Research 32 (1) (2005). ( Received 01 May 2013; accepted 03 May 2013 ).

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