Affordances of Learning Analytics for Mediating Learning

Learning analytics acceptance and adoption is a socio-technological endeavour. Understanding how learning analytics impact practice is an important part of demonstrating their value. In the study presented in this thesis, "Mediated Learning" provides a framework through which to describe how learning analytics can impact psychological, social and material aspects of learning, from the perspective of educators and learners. It also offers a structure through which to make recommendations for improving the mediatory effects of learning analytics. A qualitative research design, based on "Grounded Theory" was implemented and 10 educators from 3 European universities were recruited through convenience and purposive sampling for exploratory interviews. A subsequent case study of the Open University provided critical perspectives from both educators (n=18) and learners (n=22) about the institutional, departmental, domain-related and epistemological factors that broadly influence perceptions of learning analytics. The study applied "Affordance Theory" to identify what participants were most easily able to recognise as beneficial to their own practice. Participant contributions were open-coded to uncover emerging themes and then organised into thematic categories and subcategories. Respondent validation, as well as triangulation of data between the exploratory interviews and focus groups support the validity of the study. Findings suggested that domain-related epistemological assumptions and previous experience influence how and why an individual could make use of learning analytics insights. Gaining stakeholder acceptance involves targeting the right training and opportunities at the appropriate disciplines. Findings also indicate that learning analytics has the strongest mediatory effect for learners when the technology is capable of exposing them to other learners' strategies, or when it assists them personally, and continually in goal orientation adoption. The implications of the study are important for higher education institutions looking to implement large-scale learning analytics initiatives, in particular, those with a diverse student body

<i>“We’re Seeking Relevance”</i>: Qualitative Perspectives on the Impact of Learning Analytics on Teaching and Learning

Whilst a significant body of learning analytics research tends to focus on impact from the perspective of usability or improved learning outcomes, this paper proposes an approach based on Affordance Theory to describe awareness and intention as a bridge between usability and impact. 10 educators at 3 European institutions participated in detailed interviews on the affordances they perceive in using learning analytics to support practice in education. Evidence illuminates connections between an educator’s epistemic beliefs about learning and the purpose of education, their perception of threats or resources in delivering a successful learning experience, and the types of data they would consider as evidence in recognising or regulating learning. This evidence can support the learning analytics community in considering the proximity to the student, the role of the educator, and their personal belief structure in developing robust analytics tools that educators may be more likely to use

When decision support systems fail: insights for strategic information systems from Formula

Decision support systems (DSS) are sophisticated tools that increasingly take advantage of big data and are used to design and implement individual - and organization - level strategic decisions . Yet, when organizations excessively rely on their potential the outcome may be decision - making failure, particularly when such tools are applied under high pressure and turbulent conditions. Partial understanding and unidimensional interpretation can prevent learning from failure. Building on a practice perspective, we study an iconic case of strategic failure in Formula 1 racing. Our approach, which integrates the decision maker as well as the organizational and material context , identifies three interrelated sources of strategic failure that are worth investigation for decision - makers using DSS and big data: (1) t he situated nature and affordances of decision - making ; (2) t he distributed nature of cognition in decision - making; and (3) the performativity of the DSS. We outline specific research questions and their implications for firm performance and competitive advantage. Finally, we advance an agenda that can help close timely gaps in strategic IS research

Young children learning with mobile devices: Research on design and implementation

The increasing growth and usage of mobile devices, such as tablets and iPads, by young children has not yet been accompanied by systematic research about the effects they have on children's learning and the conditions that facilitate or hinder learning and engagement. As a result, only few empirically-based guidelines exist to guide parents, educators, and application (app) designers when choosing or designing apps for young children, often leading to non-evidence-based decisions, or the design of apps with little educational value. This symposium aims to bring together researchers from Australia, the UK and USA to discuss what evidence exist about the learning potential of mobile devices and apps for young children and how it could be used to inform relevant stakeholders

Rethinking affordance

n/a – Critical survey essay retheorising the concept of 'affordance' in digital media context. Lead article in a special issue on the topic, co-edited by the authors for the journal Media Theory

AI Affordance Actualisation: Empirical Evidence from Mobility Ecosystem Organisations

One of the UN Sustainable Development Goals (SDGs) is to transform urban mobility to be more accessible, efficient, safe, and sustainable. Artificial Intelligence (AI) can be applied to address some critical urban mobility issues and facilitate the achievement of SDGs. However, there is a need to understand how mobility ecosystem organisations use AI in alignment with their organisational goals to contribute to SDGs. To address this puzzle, this study draws on the affordance theory and preliminary interviews with ten key informants from mobility organisations in Australia. The preliminary findings show that mobility organisations’ exploitation of AI systems and technologies leads to the emergence of decarbonising, optimising, conditioning asset management, and provisioning customer-centric services. To do so, they develop AI literacy, business-IT collaboration, change management, and technology and data foundation. The paper contributes a tentative framework linking AI affordances with mobility-related SDGs, serving as a guide for future research and practice

Digital transformation of higher education in Australia: Understanding affordance dynamics in E-Textbook engagement and use

This paper addresses digital transformation in higher education by exploring the engagement and use of e-textbooks through an affordance theory lens. Drawing on the insights from in-depth interviews (n = 18), focus group discussions (n = 15), a pilot survey (n = 83) and the main survey (n = 344) in Australia, we developed and validated an affordance actualisation model for the engagement and use of e-textbooks. The partial least squares (PLS) technique was used to validate the dimensions of affordance actualisation and its relationship with e-textbooks engagement and affordance effect. The findings indicate the efficacy of the two affordance constructs, as well as the significant mediating effect of engagement. An important lesson for the e-textbook industry is that firms need to consider affordance actualisation dimensions (i.e., portability, accessibility, searchability, highlighting, copying, browsing, hedonic and utilitarian value) when enhancing digital engagement and use of e-textbooks

What Makes AI Different? Exploring Affordances and Constraints - The Case of Auditing

This study aims to gain a comprehensive understanding of the differences between classic IT and AI artefacts. To achieve this objective, the study employs a grounded theory literature review approach and analyses 81 papers related to the application of classic IT and AI artefacts in the auditing industry. Drawing on the Technology Affordances and Constraints Theory, we examine the actions that can be potentially enabled or restricted by using classic IT and AI artefacts. This analysis allows us to conceptualise and compare the affordances and constraints associated with these two types of artefacts. The study addresses the need for more research on AI from both social and technical perspectives. Our findings may facilitate practitioners in improving their business processes and promoting effective collaboration between humans and AI

Affordance-Experimentation-Actualization Theory in Artificial Intelligence Research – A Predictive Maintenance Story

Artificial intelligence currently counts among the most prominent digital technologies and promises to generate significant business value in the future. Despite a growing body of knowledge, research could further benefit from incorporating technological features, human actors, and organizational goals into the examination of artificial intelligence-enabled systems. This integrative perspective is crucial for effective implementation. Our study intends to fill this gap by introducing affordance-experimentation-actualization theory to artificial intelligence research. In doing so, we conduct a case study on the implementation of predictive maintenance using affordance-experimentation-actualization theory as our theoretical lens. From our study, we find further evidence for the existence of the experimentation phase during which organizations make new technologies ready for effective use. We propose extending the experimentation phase with the activity of ‘conceptual exploration’ in order to make affordance-experimentation-actualization theory applicable to a broader range of technologies and the domain of AI-enabled systems in particular