Knowing You: Personal Tutoring, Learning Analytics and the Johari Window

Ricky Lowes

doi:10.3389/feduc.2020.00101

Abstract

Recent decades have seen increased concern for the student experience by higher education institutions, along with more pressure on students due to the highly competitive job market and the financial implications of doing a degree. The growth in the number of non-traditional students attending higher education has added to pressures on students and staff. There are impacts on the mental health and well-being of both as university education becomes massified, commodified and increasingly time-pressured. In this context, informed and kindly human interaction is crucial to mitigate negative influences. However, staff are less likely than ever to know their students well enough to have meaningful and impactful exchanges. Student record systems and learning analytics present themselves as a promising tool to be used in finding solutions to the complex problems of student achievement and wellbeing. This paper explores the use of big data and learning analytics to facilitate the work of personal tutors (also known as academic advisors), illustrated by practical examples from the Student Support System used at the University of Plymouth. It will argue that learning analytics systems have the potential to facilitate communication and sharing of information, and thus enhance the quality of communication between personal tutors and their tutees to improve student engagement and support the tutee. However, the major contention of the paper is that tutors may need advice and guidance in how to make effective use of this data, and that information requires the lens of a humanistic framework in order to be transformed into knowledge and insight. The heuristic of the Johari Window is presented as a possible tool to stimulate thinking and to integrate the information from learning analytics into a meaningful framework to develop a powerful way of knowing tutees better and thus creating more supportive relationships with them. As such, the paper proposes an original contribution to the underexplored field of the use of learning analytics in personal tutoring in the UK, with ideas applicable to a range of institutional contexts.

Highlights

Learning analytics is emblematic of the new holistic approaches to student retention and is likely to have profound implications for personal tutoring. (Webb et al, 2017, p. 6)Recent decades have seen increased concern for the student experience by higher education institutions (HEIs) in England, Wales and Northern Ireland since the introduction of fees in 1998 and their increase to £9,000 in 2012
This paper aims to stimulate discussion by briefly exploring recent developments in the use of learning analytics in UK higher education institutions and considering their potential and their limitations
Hipkin (2016b) contends that learning analytics offer a potential solution to the difficulties tutors face in providing effective support, while warning us that it is crucial to embed the information presented by learning analytics into a personcentered system of tutoring which draws on other sources of information

Summary

Introduction

Learning analytics is emblematic of the new holistic approaches to student retention and is likely to have profound implications for personal tutoring. (Webb et al, 2017, p. 6)Recent decades have seen increased concern for the student experience by higher education institutions (HEIs) in England, Wales and Northern Ireland since the introduction of fees in 1998 and their increase to £9,000 in 2012 (from 2017 rising with inflation). The widening participation agenda has meant an increase in the number of non-traditional students such as working students, students with parental responsibilities or first generation to attend higher education, who often face greater stress than students with fewer responsibilities or a family tradition of university education This combination of pressures on students (and staff) may in part explain the growth in mental health issues and low levels of wellbeing currently reported (Bentley, 2016a,b; Brown, 2016; Yeung et al, 2016; Clarke et al, 2018; Hughes et al, 2018; Morrish, 2019; Neves and Hillman, 2019). This issue is causing concern and institutions are developing prevention strategies (Universities UK, 2017; Clarke et al, 2018)

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