Investigating Academic Achievement Satisfaction of Students in India: An Application of ANN Model

Rashi Taggar, Advitya Indu Mahajan, Arti Maini

Abstract

This study deliberates how online learning impacts Academic Achievement Satisfaction (AAS) among higher education professional course students in India. Online learning offers students more flexibility and convenience, but it also presents challenges, such as a lack of face-to-face interaction with instructors and peers, technical difficulties, and difficulty in maintaining motivation and engagement. Artificial Neural Networks (ANN) are trained on this data to create a predictive model that identifies the most important predictors of AAS in online learning environments. The results showed that the 'distracting elements' are the most critical factor while measuring the AAS, followed by the 'Institutional Support' factor. 'Social Synergy', 'Own Room', 'Internet Potency', and 'Technical Self Efficacy' have also been found to impact the AAS. Ultimately, the findings of this study could contribute to the ongoing efforts to improve the quality of online learning for higher education professional course students. 

Keywords

Academic Achievement; Satisfaction; ANN; Online learning; Self-determination theory.

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DOI: https://doi.org/10.26220/aca.5053

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