The deep approach to learning as a measure of quality education in accreditation

Purpose This paper aims to offer an alternative approach to traditional accreditation processes for measuring the quality of learning in higher education. The paper emphasizes identifying specific learning environment variables that foster deep learning and demonstrable learning outcomes. Design/methodology/approach A survey of 873 students from public and private colleges was conducted. The relationship between the antecedents and consequences of a deep approach to learning was hypothesized using a conceptual model. Findings Learning environment variables like motivation, self-efficacy, curriculum and assessment emerged as robust predictors of deep learning, which in turn led to improved learning outcomes. Practical implications The implications extend beyond the academic realm, informing policy and accreditation frameworks aimed at fostering an enriched and effective learning environment. This paper advocates for the integration of student learning to provide a more nuanced and accurate understanding of educational quality. Originality/value The originality lies in the critical evaluation of traditional accreditation as the primary means of measuring the quality of learning in higher education and its proposition of a complementary approach focused directly on assessing the depth of student learning. This focus on the antecedents and consequences of deep learning, as a complementary lens to accreditation, constitutes a significant contribution to the field.