Simon Knight
Biographic Data
| ID | 4218549 |
|---|---|
| NAME | Simon Knight |
| GIVEN NAMES | Simon |
| FAMILY NAME | Knight |
| SIGNATURE | KNIGHT S |
| AFFILIATIONS | University of Technology Sydney |
| ORCID | 0000-0002-8709-5780 |
| VERIFIED | Yes |
| TOTAL WORKS | 14 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 14 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2018 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Am I an Education Researcher
How individual researchers and communities of scholars situate themselves with respect to each other has a range of consequences, relating to issues from identity and norms of practices, to how one is benchmarked or positioned to apply for jobs or funding. Education, perhaps more than other disciplines, has a longstanding attention to tensions in this situating. This paper provides a reflection from an individual researcher, relating their experi…
Identifying and Designing Evidence-Informed Practice, in Practice
Across sectors, including education, there are a confluence of pressures towards integration of research and evidence into practice. These include a focus on evidence quality in practice and policy, inclusion of research and evidence evaluation in professional training, and development of implementation standards and translational resources to support evidence mobilisation. However, while current approaches to evidence synthesis support many purp…
Inverting {{Citation needed}}
Discussion of the potential of open data for impact – including in education – has grown. Open data from Wikipedia, the world's largest open educational resource, is used in a variety of learning contexts. A sociotechnical concern in this data is that it arises in a platform-based social dynamic, governed by norms and conventions, and negotiated by sets of volunteers for the particular purpose of writing an encyclopedia. This paper uses one featu…
Pre-emptive living donor kidney transplantation
OPINION article Front. Public Health, 17 March 2023Sec. Health Economics Volume 11 - 2023 | https://doi.org/10.3389/fpubh.2023.1124453
A reflective design case of practical micro‐ethics in learning analytics
A burgeoning literature, policy landscape, and set of practice resources and guidelines have emerged around ethical educational technology development and implementation, particularly in the context of data or artificial intelligence informed tools. However, while these resources provide valuable tools to support navigation of the ethical landscape, they suffer from some limitations. These include a focus on coarse‐grained, clear cut cases; a lac…
Why do experts disagree? The development of a taxonomy
People are increasingly exposed to conflicting health information and must navigate this information to make numerous decisions, such as which foods to consume, a process many find difficult. Although some consumers attribute these disagreements to aspects related to uncertainty and complexity of research, many use a narrower set of credibility-based explanations. Experts’ views on disagreements are underinvestigated and lack explicit identificat…
Generative AI in the Australian education system
The launch of new tools in late 2022 heralded significant growth in attention to the impacts of generative AI (GenAI) in education. Claims of the potential impact on education are contested, but there are clear risks of inappropriate use particularly where GenAI aligns poorly with learning aims. In response, in mid-2023, the Australian Federal Government held an inquiry, calling for public submissions. This inquiry offers a lens onto the policy f…
Rethinking the entwinement between artificial intelligence and human learning
The proliferation of AI in many aspects of human life—from personal leisure, to collaborative professional work, to global policy decisions—poses a sharp question about how to prepare people for an interconnected, fast-changing world which is increasingly becoming saturated with technological devices and agentic machines. What kinds of capabilities do people need in a world infused with AI? How can we conceptualise these capabilities? How can we …
Explainable Artificial Intelligence in education
There are emerging concerns about the Fairness, Accountability, Transparency, and Ethics (FATE) of educational interventions supported by the use of Artificial Intelligence (AI) algorithms. One of the emerging methods for increasing trust in AI systems is to use eXplainable AI (XAI), which promotes the use of methods that produce transparent explanations and reasons for decisions AI systems make. Considering the existing literature on XAI, this p…
Educator perspectives on learning analytics in classroom practice
Implementing learning analytics for learning impact
Learning analytics has the potential to impact student learning, at scale. Embedded in that claim are a set of assumptions and tensions around the nature of scale, impact on student learning, and the scope of infrastructure encompassed by 'learning analytics' as a socio-technical field. Drawing on our design experience of developing learning analytics and inducting others into its use, we present a model that we have used to address five key chal…
Data in practice
Data about learning can support teachers in their decision-making processes as they design tasks aimed at improving student educational outcomes. However, to achieve systemic impact, a deeper understanding of teachers’ perspectives on, and expectations for, data as evidence is required. It is critical to understand how teachers’ actions align with emerging learning analytics technologies, including the practices of pre-service teachers who are de…
Calibrating assessment literacy through benchmarking tasks
In calibration tasks students assess exemplar texts using criteria against which their own work will be assessed. Typically, these tasks are used in the context of training for peer assessment. Little research has been conducted on the benefits of calibration tasks, such as benchmarking, as learning opportunities in their own right. This paper examines a dataset from a long-running benchmarking task (∼500 students per semester, for four semesters…
A discursive approach to the analysis of epistemic cognition
No prominent works on this page.
A discursive approach to the analysis of epistemic cognition
Calibrating assessment literacy through benchmarking tasks
In calibration tasks students assess exemplar texts using criteria against which their own work will be assessed. Typically, these tasks are used in the context of training for peer assessment. Little research has been conducted on the benefits of calibration tasks, such as benchmarking, as learning opportunities in their own right. This paper examines a dataset from a long-running benchmarking task (∼500 students per semester, for four semesters…
Educator perspectives on learning analytics in classroom practice
Implementing learning analytics for learning impact
Learning analytics has the potential to impact student learning, at scale. Embedded in that claim are a set of assumptions and tensions around the nature of scale, impact on student learning, and the scope of infrastructure encompassed by 'learning analytics' as a socio-technical field. Drawing on our design experience of developing learning analytics and inducting others into its use, we present a model that we have used to address five key chal…
Data in practice
Data about learning can support teachers in their decision-making processes as they design tasks aimed at improving student educational outcomes. However, to achieve systemic impact, a deeper understanding of teachers’ perspectives on, and expectations for, data as evidence is required. It is critical to understand how teachers’ actions align with emerging learning analytics technologies, including the practices of pre-service teachers who are de…
Rethinking the entwinement between artificial intelligence and human learning
The proliferation of AI in many aspects of human life—from personal leisure, to collaborative professional work, to global policy decisions—poses a sharp question about how to prepare people for an interconnected, fast-changing world which is increasingly becoming saturated with technological devices and agentic machines. What kinds of capabilities do people need in a world infused with AI? How can we conceptualise these capabilities? How can we …
Explainable Artificial Intelligence in education
There are emerging concerns about the Fairness, Accountability, Transparency, and Ethics (FATE) of educational interventions supported by the use of Artificial Intelligence (AI) algorithms. One of the emerging methods for increasing trust in AI systems is to use eXplainable AI (XAI), which promotes the use of methods that produce transparent explanations and reasons for decisions AI systems make. Considering the existing literature on XAI, this p…
Pre-emptive living donor kidney transplantation
OPINION article Front. Public Health, 17 March 2023Sec. Health Economics Volume 11 - 2023 | https://doi.org/10.3389/fpubh.2023.1124453
A reflective design case of practical micro‐ethics in learning analytics
A burgeoning literature, policy landscape, and set of practice resources and guidelines have emerged around ethical educational technology development and implementation, particularly in the context of data or artificial intelligence informed tools. However, while these resources provide valuable tools to support navigation of the ethical landscape, they suffer from some limitations. These include a focus on coarse‐grained, clear cut cases; a lac…
Why do experts disagree? The development of a taxonomy
People are increasingly exposed to conflicting health information and must navigate this information to make numerous decisions, such as which foods to consume, a process many find difficult. Although some consumers attribute these disagreements to aspects related to uncertainty and complexity of research, many use a narrower set of credibility-based explanations. Experts’ views on disagreements are underinvestigated and lack explicit identificat…
Generative AI in the Australian education system
The launch of new tools in late 2022 heralded significant growth in attention to the impacts of generative AI (GenAI) in education. Claims of the potential impact on education are contested, but there are clear risks of inappropriate use particularly where GenAI aligns poorly with learning aims. In response, in mid-2023, the Australian Federal Government held an inquiry, calling for public submissions. This inquiry offers a lens onto the policy f…
Inverting {{Citation needed}}
Discussion of the potential of open data for impact – including in education – has grown. Open data from Wikipedia, the world's largest open educational resource, is used in a variety of learning contexts. A sociotechnical concern in this data is that it arises in a platform-based social dynamic, governed by norms and conventions, and negotiated by sets of volunteers for the particular purpose of writing an encyclopedia. This paper uses one featu…
Am I an Education Researcher
How individual researchers and communities of scholars situate themselves with respect to each other has a range of consequences, relating to issues from identity and norms of practices, to how one is benchmarked or positioned to apply for jobs or funding. Education, perhaps more than other disciplines, has a longstanding attention to tensions in this situating. This paper provides a reflection from an individual researcher, relating their experi…
Identifying and Designing Evidence-Informed Practice, in Practice
Across sectors, including education, there are a confluence of pressures towards integration of research and evidence into practice. These include a focus on evidence quality in practice and policy, inclusion of research and evidence evaluation in professional training, and development of implementation standards and translational resources to support evidence mobilisation. However, while current approaches to evidence synthesis support many purp…
Computer Science (12 works) · Psychology (8 works) · Engineering (7 works) · Knowledge management (6 works) · Online Learning and Analytics (6 works) · Sociology (6 works) · Data science (5 works) · Engineering ethics (4 works) · Epistemology (4 works) · Analytics (3 works)