Critical success factors for implementing learning analytics in higher education: A mixed-method inquiry

Abstract

Critical success factors (CSFs) have been around since the late 1970s and have been used extensively in information systems implementations. CSFs provide a comprehensive understanding of the multiple layers and dimensions of implementation success. In the specific context of learning analytics (LA), identifying CSFs can maximise the possibilities of an effective implementation and harness the value of converting data into actionable information. This paper proposes a framework that aims to identify and explore the CSFs for the implementation of LA within the higher education sector by examining the viewpoints of higher education professionals. To obtain a rounded insight into stakeholders’ perceptions, we conducted a mixed-method inquiry with factor analysis, profile analysis and thematic analysis of both quantitative and qualitative data collected with an online questionnaire from an international sample. The responses validate five CSFs of LA implementation: strategy and policy at organisational level, information technological readiness, performance and impact evaluation, people’s skills and expertise and data quality. Results also disclose diverse views about the CSFs’ priorities and the associated difficulties and achievements.
 Implications for practice or policy:
 
 Higher education practitioners should consider CSFs for implementing an LA initiative successfully.
 This study validates five dimensions of the CSFs of implementing LA in higher education.
 The validated framework enumerates several factors in each of the main dimensions for achieving optimum results.
 Stakeholders have diverse opinions about the priorities of CSFs, particularly in organisational commitment, data quality and human capital.

Impact of digital technologies upon teaching and learning in higher education in Latin America: an outlook on the reach, barriers, and bottlenecks

“…Also, TEL-based Education (digitized-education) have attained flexibility and mobility in its mode of delivery or paradigms (Aguilera-Hermida et al, 2021;Diaz-Nunez et al, 2021;Okoye et al, 2021;del Rio-Chillcce et al, 2021;TEC, 2020b). This ranges from the innovative (pedagogical) frameworks or theories for teaching (Exter et al, 2019;Ndukwe & Daniel, 2020;Okoye et al, 2022), to the integration of educational technologies (EdTech) that are used to bridge the gap between the modern and traditional models for teaching/learning Shambour & Abu-Hashem, 2022), and in turn, provides new paradigms or practices for achieving sustainability and scalability in the use of EdTech for teaching or educational purposes (Clark et al, 2020;Okoye et al, 2021Okoye et al, , 2022Tondeur et al, 2020;UNESCO, 2015UNESCO, , 2021bYu & Jo, 2014).…”

Towards teaching analytics: a contextual model for analysis of students’ evaluation of teaching through text mining and machine learning classification

“…Concerning the implications of this study, both in practice and the wider spectrum of scientific research and/or educational technologies, in particular, we note that prior studies have looked at the effect that educational technologies, such as the teaching analytical methods, have on the teaching perspectives and experiences for the students (Boring, 2017 ; Engen, 2019 ; Gallego-Arrufat et al, 2019 ; Gomes & Ma, 2020 ; Gordillo et al, 2019 ; Ndukwe & Daniel, 2020 ; Silva et al, 2019 ). Whereas some of the existing studies argued that the students evaluation of teaching (SET) may not necessarily be the most effective way of determining the teachers’ teaching performances and assessment (Boring, 2017 ; Gomes & Ma, 2020 ), other studies have also highlighted the early indicators or success factors that have been achieved over the years, particularly through the use of the educational technologies and data to support the teaching–learning processes and development (Bowdre, 2020 ; Clark et al, 2020 ; Engen, 2019 ; Hilliger et al, 2020 ; Kori et al, 2018 ; Oyedotun, 2020 ; Raffaghelli et al, 2020 ; Silva et al, 2019 ). To note, Engen ( 2019 ) mentioned that, there is now more than ever, the necessity for ample understanding of the emerging methods and digital technologies, both in terms of what can be called the cultural-to-social aspects for use by the educators, in fostering an effective teachers-students learning processes and experience (Dimitriadis et al, 2021 ).…”

Comparing the comparators: How should the quality of education offered by online universities be evaluated?

“…However, examples of operational use of Learning Analytics techniques are emerging as evidenced by Ifenthaler and Yau's review (2020). Clark et al (2020) identified and validated five critical success factors for the implementation of Learning Analytics at universities, including strategy and policy at an organisational level. If an objective approach to comparing universities using techniques drawing on the Learning Analytics field is to be developed, it will require strategy and policy above the level of individual institutions.…”