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Enhancing Job Opportunities in Rural India Through Constrained Cognitive Learning Process: Reforming Basic Education

  • Shivangi Nigam
  • Abhishek Bajpai
  • Bineet Gupta
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 736)

Abstract

Technological advancements in cognitive learning suggest significant changes in methods of teaching and learning process. A Constrained Cognitive Learning (CCL) model links various forms of cognitive learning methods with a restrictive domain. The main objective of this research study is to propose a CCL scheme that integrates cognitive learning theories and instructional prescriptions to achieve an effective learning environment for the basic education system in rural India. It improves both knowledge acquisition and employment in optimized way. Furthermore, our objective is that, the proposed research contributes in promoting the dialogue between professional learners, academic researchers and practitioners that increasingly brings empirical educational and research orientation into the contemporary educational environment across the rural India. Our focus is to plan such a cognitive learning environment so that the learner not only acquire knowledge but also improve their cognitive abilities to apply their knowledge for the employment and extend their knowledge depth to move towards research oriented innovative skills.

Keywords

Constrained Cognitive Learning (CCL) Learning paradigm Behaviorism Cognitivism Constructivism Self regulated learning 

References

  1. Greeno, J.G., Collins, A.M., Resnick, L.B.: Cognition and learning. In: Handbook of Educational Psychology, vol. 77, pp. 15–46 (1996)Google Scholar
  2. Hannafin, M.J., Hannafin, K.M.: Cognition and student-centered, web-based learning: issues and implications for research and theory. In: Learning and Instruction in the Digital Age, pp. 11–23. Springer (2010)Google Scholar
  3. Hill, J.R., Hannafin, M.J.: Cognitive strategies and learning from the world wide web. Educ. Technol. Res. Dev. 45(4), 37–64 (1997)CrossRefGoogle Scholar
  4. Iiyoshi, T., Hannafin, M.J., Wang, F.: Cognitive tools and student- centred learning: rethinking tools, functions and applications. Educ. Media Int. 42(4), 281–296 (2005)CrossRefGoogle Scholar
  5. Ohlsson, S.: Constraint-based modeling: from cognitive theory to computer tutoring–and back again. Int. J. Artif. Intell. Educ. 26(1), 457–473 (2016)CrossRefGoogle Scholar
  6. Pintrich, P.R.: The role of motivation in promoting and sustaining self-regulated learning. Int. J. Educ. Res. 31(6), 459–470 (1999)CrossRefGoogle Scholar
  7. Qian, G., Alvermann, D.: Role of epistemological beliefs and learned helpless-ness in secondary school students’ learning science concepts from text. J. Educ. Psychol. 87(2), 282 (1995)CrossRefGoogle Scholar
  8. Rahman, A., Malik, A., Sikander, S., Roberts, C., Creed, F.: Cognitive behaviour therapy-based intervention by community health workers for mothers with depression and their infants in rural Pakistan: a cluster-randomised controlled trial. Lancet 372(9642), 902–909 (2008)CrossRefGoogle Scholar
  9. Roberson Jr., D.N., Merriam, S.B.: The self-directed learning process of older, rural adults. Adult Educ. Q. 55(4), 269–287 (2005)CrossRefGoogle Scholar
  10. Roediger III, H.L.: Applying cognitive psychology to education: Translational educational science. Psychol. Sci. Publ. Interest 14(1), 1–3 (2013)CrossRefGoogle Scholar
  11. Van Merriënboer, J.J., Ayres, P.: Research on cognitive load theory and its design implications for e-learning. Educ. Technol. Res. Dev. 53(3), 5–13 (2005)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Shri Ramswaroop Memorial UniversityLucknowIndia

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