Abstract
The growing need for quality education has brought the topic to center stage at academic and policy-making levels. This study measures the quality of higher education by proposing a framework for the learning environment, deep learning, and learning outcomes. A primary survey was conducted on 4403 students from public and private colleges of different universities. The relationship between the antecedents and consequences of a deep approach to learning was hypothesized using a conceptual model. Confirmatory factor analysis tested the validity of the proposed measurement model. The model shows that the learning environment influenced deep learning, positively impacting students’ learning outcomes. The results reveal that learning environment variables such as motivation, self-efficacy, curriculum, and assessment predicted deep learning. Further, deep learning significantly affected learning outcome variables such as critical thinking, problem-solving, life-long learning, self-reflection, ethical values, leadership, and collaboration. Understanding learning environment variables that foster deep learning in students will aid in improving the overall quality of education. The study contributes to the ongoing dialogue about student-centered approaches to education and the role of student voice in shaping educational practices. The contributions of this study are in the context of a specific research environment, which may be considered a limitation of the study if viewed from a broader perspective.
Presenters
Priya ChaudharyAssistant Professor, Human Resource , International Management institute, Delhi, India Reetesh Kumar Singh
Dean, Faculty of Commerce and Business, University of Delhi, Delhi, India
Details
Presentation Type
Paper Presentation in a Themed Session
Theme
KEYWORDS
APPROACH TO LEARNING, LEARNING ENVIRONMENT, LEARNING OUTCOMES, HIGHER EDUCATION
