Advertisement

Evolutionary Algorithm Approach to Pupils’ Pedantic Accomplishment

  • Devasenathipathi N. Mudaliar
  • Nilesh K. Modi
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 199)

Abstract

Group learning helps pupils in boosting their learning power by creating interactions among them. However, creating groups among pupils with appropriate coupling and cohesion is still a challenge. Pupils’ groups are formed with some constraints and group formation performed by a single individual is customarily prejudiced in one way or other. In this paper, an approach has been proposed using evolutionary algorithm to increase the pupils’ pedantic accomplishment. This approach helps in optimal pupil group formation on the basis on of their previous examination scores. To justify the proposal, a study was carried out among a class of pupils pursuing post graduation. The semester examination results of pupils before and after group learning were compared. More than 66.07% of pupils scored better than their previous semester examination which positively proved the proposed approach.

Keywords

Group Formation Genetic Algorithm Group Learning Optimization Performance Prediction Academic Improvement 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Devasenathipathi, N., Modi, N.K.: Measuring Individual Knowledge Gain Statistically in a Group Learning Environment. National Journal of Computer Science and Technology 3(2), 25–29 (2011)Google Scholar
  2. 2.
    Hwang, G.J., Yin, P.Y., Hwang, C.W., Tsai, C.C.: An Enhanced Genetic Approach to Composing Cooperative Learning Groups for Multiple Grouping Criteria. Educational Technology & Society 11(1), 148–167 (2008)Google Scholar
  3. 3.
    Isotani, et al.: An Ontology Engineering Approach to the Realization of Theory- Driven Group Formation. International Journal of Computer Supported Collaborative Learning 4(4) (2009)Google Scholar
  4. 4.
    Moreno, J., Ovalle, D.A., Vicari, R.M.: A Genetic Algorithm Approach for Group Formation in Collaborative Learning Considering Multiple Student Characteristics. Computers & Education 58(1), 560–569 (2012)CrossRefGoogle Scholar
  5. 5.
    Shin-ike, K., Iima, H.: A method for Development of collaborative learning by using a neural network and a genetic algorithm. In: Proceedings of ISADS, pp. 417–422 (2009)Google Scholar
  6. 6.
    Kuisma, R.: Assessing Individual Contribution to a Group Project. In: Watkins, D., Tang, C., Biggs, J., Kuisma, R. (eds.) Assessment of University Students in Hong Kong: How and Why, Assessment Portfolio, Students’ Grading - Evaluation of the Student Experience Project, vol. 2, pp. 79–106. City University of Hong Kong, Centre for the Enhancement of Learning and Teaching (1998)Google Scholar
  7. 7.
    Papanikolaou, K., Gouli, E.: Collaboration as an Opportunity for Individual Development. In: International Conference on Intelligent Networking and Collaborative Systems, pp. 54–61 (2010)Google Scholar
  8. 8.
    Bentley, P.J.: The Revolution of Evolution for Real-World Applications. In: Emerging Technologies 1997: Theory and Application of Evolutionary Computation, University College London (1997)Google Scholar
  9. 9.
    Paredes, P., Ortigosa, A., Rodriguez, P.: A Method for Supporting Heterogenous-Group Formation through Heuristics and Visualization. Journal of Universal Computer Science 16(19), 2882–2901 (2010)Google Scholar
  10. 10.
    Bello, T.O.: Effect of Group Instructional Strategy on Students’ Performance in Selected Physics Concepts. African Educational Research Network 11(1), 71–79 (2011)MathSciNetGoogle Scholar
  11. 11.
    Wilkinson, I.A.G., Fung, I.Y.Y.: Small-group composition and peer effects. International Journal of Educational Research (Special issue) 37, 425–447 (2002)Google Scholar
  12. 12.
    Lin, Y.-T., Huang, Y.-M., Cheng, S.-C.: An Automatic Group Composition System for Composing Collaborative Learning Groups using Enhanced Particle Swarm Optimization. Computers & Education 55(4), 1483–1493 (2010)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Devasenathipathi N. Mudaliar
    • 1
    • 2
  • Nilesh K. Modi
    • 3
  1. 1.MCA DepartmentSVIT VasadRajupuraIndia
  2. 2.R & D CentreBharathiar UniversityCoimbatoreIndia
  3. 3.MCA DepartmentSVICSKadiIndia

Personalised recommendations