Exploring attitudes and adoption intentions of online assessment, marking, and feedback practices in a post-Covid-19 era

Da Silva Filipe Soares, Anabela; Lerigo-Sampson, Moya

Abstract

As a sector, Higher Education (HE) has become increasingly competitive, and many universities are exploring the use of digital technologies in teaching and learning to help meet market demands and maintain relevancy (Reed and Watmough, 2015; Ahlburg, 2020). Add to this existing competitiveness, a global pandemic (Covid-19), and universities have had to demonstrate the ability to rapidly adapt teaching delivery, as well as consider how learning outcomes are assessed (Brammer and Clark, 2020). This dramatic shift in learning and assessment has substantially increased workloads across the sector and staff have been dealing with high levels of stress and pressure, particularly in management education courses with large intakes (Kim and Asbury, 2020; Beech and Anseel, 2020). That said, some staff have adapted and engaged in pedagogic innovation to meet the challenges associated with changing delivery patterns; whilst others have remained more reticent (Beech and Anseel, 2020; Brammer and Clark, 2020). Indeed, some researchers suggest that the willingness to adopt emerging technologies and educational tools can be shaped by individual differences, attitudes, and social norms (Hu et al, 2020; Dermentzi et al, 2016). Covid-19 has certainly changed our daily routines at both personal and professional levels, so it raises questions around the impact of Covid-19 on the willingness of HE staff to engage with new technologies and tools (Queen, 2021)

Exploring the vast range of technological and pedagogical innovations in HE is beyond the scope of a single study; therefore, it was decided to focus on an area which is consistently highlighted as one to improve; assessment and feedback. The need to improve this area is a trend seen across the HE sector and reflected in the National Student Survey results. One way to address this challenge is to develop and improve the use of technology enhanced feedback and marking tools (such as online rubrics) which facilitate marking processes and satisfy students’ requests for consistent approaches. Underpinned by the Technology Acceptance Model (TAM), this research project aims to explore the attitudes of staff regarding online feedback and marking tools, to establish the current state of usage, and to investigate future adoption intentions.

Universities (and researchers) in general tend to gather a lot of information about their students, but there is less information or guidance available to staff regarding implementation of learning strategies. Taking a case study approach, our research will include a broad outlook of staff perspectives, attitudes, and perceptions, so that we can understand the levels of acceptance towards online marking and feedback throughout the chosen institution. The main goal is to identify gaps in knowledge, training, and perspectives associated with implementing and using online marking and feedback tools. We shall simultaneously address attitudes towards different types of assessments and how these link to online marking and feedback (particularly rubrics). To achieve this, a quantitative research approach has been implemented. The project is currently in the data collection phase and we will be able to present the preliminary findings at the conference.

Citation

Da Silva Filipe Soares, A., & Lerigo-Sampson, M. (2021, June). Exploring attitudes and adoption intentions of online assessment, marking, and feedback practices in a post-Covid-19 era. Paper presented at Teaching and Learning (MKE) Bristish Academy of Management (BAM) Conference

• Presentation Conference Type: Conference Paper (unpublished)
• Conference Name: Teaching and Learning (MKE) Bristish Academy of Management (BAM) Conference
• Start Date: Jun 23, 2021
• Deposit Date: Mar 3, 2022
• Publicly Available Date: Mar 15, 2022
• Series Title: Opportunities and Challenges: The Practice and Scholarship of Learning and Teaching
• Public URL: https://uwe-repository.worktribe.com/output/9097505