Augmented Advising

Abstract

Augmenting academic advising in the era of smart cognitive computing technologies creates new dynamics of engagement that can help academic advising evolve toward a learningcentered paradigm. We examined the self-directed learning readiness of students selected through demographic variables. The results indicate that differences in employment experience, length of employment, and grade point average (GPA) are statistically significant with regard to self-directed learning readiness scores. Preparing learners for self-directed processes can augment student development when purposefully positioned in a learning-centered approach with continuity across mobile, cloud, and cognitive technologybased learning platforms and in components of academic advising processes.

Students’ satisfaction with the service quality of academic advising systems

“…Studies from the US have often used the term 'approaches', whereas those from the UK have mostly resorted to the term 'models' [11]. The key terms 'developmental' and 'prescriptive', which were introduced in seminal articles [12], [13], were eventually identified as core elements of the AA practice [14]. Between these elements, the developmental approach focuses on the development of students, helping them foster personalised and rewarding relationships with their advisors.…”

Academic Advising in Civil Engineering: Design and Evaluation of a Hybrid Model

“…In 1972, seminal articles (later re-published in 1994) by Crookston [16] and O'Banion [17] made an early attempt to conceptualise the ways in which Academic Advising is carried out and introduced the terms 'developmental' and 'prescriptive' advising, which remain central to practice today [18]. The developmental approach is student-centred and takes a holistic view of student development in HE.…”