We Are at an Extreme Point Where We Have to Go All in on What We Really Believe Education Should Be About

McQuillan, Dan; Jarke, Juliane; Pargman, Teresa Cerratto

doi:10.1007/s42438-023-00433-5

Cited by 6 publications

(1 citation statement)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We as users have agency that is being denied to us through the use of this rhetoric. This inadvertent denial of agency could be part of the kinds of harm that are alluded to by McQuillan et al (2023). Even though there are predictions that AI will change education, not destroy it (Haven, 2023), AI still appears like a novel solution seeking a yet undiscovered problem to solve.…”

Section: Introductionmentioning

confidence: 99%

Scrutinizing the Synthetic Syllabus

Koutropoulos

2023

telji

View full text Add to dashboard Cite

In this article I explore the scenario of syllabus creation using ChatGPT as a type of Assistant Course Designer. During the early parts of 2023, one of the scenarios for LLM-based technologies, such as ChatGPT, was the creation of course materials, assignments, and syllabi for courses. The use case presented at Teaching and Learning Conferences during this time always included an adjunct instructor who was assigned a course at the last minute; or an early career academic who might have not had previous experience in syllabus creation. The scenarios always hinged upon either a lack of time to prepare, or lack of prior work that a user could adapt to the current scenario, or both. While ChatGPT passes a surface-level inspection for this scenario, a deeper analysis of the output highlights the problems with relying on such a tool for this job.

show abstract

Section: Introductionmentioning

confidence: 99%

Scrutinizing the Synthetic Syllabus

Koutropoulos

2023

telji

View full text Add to dashboard Cite

show abstract

Perspectives of Generative AI in Chemistry Education Within the TPACK Framework

Feldman-Maggor,

Blonder,

Alexandron

2024

J Sci Educ Technol

View full text Add to dashboard Cite

Artificial intelligence (AI) has made remarkable strides in recent years, finding applications in various fields, including chemistry research and industry. Its integration into chemistry education has gained attention more recently, particularly with the advent of generative AI (GAI) tools. However, there is a need to understand how teachers’ knowledge can impact their ability to integrate these tools into their practice. This position paper emphasizes two central points. First, teachers technological pedagogical content knowledge (TPACK) is essential for more accurate and responsible use of GAI. Second, prompt engineering—the practice of delivering instructions to GAI tools—requires knowledge that falls partially under the technological dimension of TPACK but also includes AI-related competencies that do not fit into any aspect of the framework, for example, the awareness of GAI-related issues such as bias, discrimination, and hallucinations. These points are demonstrated using ChatGPT on three examples drawn from chemistry education. This position paper extends the discussion about the types of knowledge teachers need to apply GAI effectively, highlights the need to further develop theoretical frameworks for teachers’ knowledge in the age of GAI, and, to address that, suggests ways to extend existing frameworks such as TPACK with AI-related dimensions.

show abstract

Postdigital Citizen Science: Mapping the Field

Jandrić,

Tolbert,

Hayes

et al. 2023

Postdigit Sci Educ

View full text Add to dashboard Cite

This paper provides a brief overview of citizen science, attending to its tensions and possibilities. We acknowledge the creative potential of citizen science for expanding and diversifying public participation in knowledge production and dissemination, and we also draw attention to its contradictions. We point to emerging postdigital tensions as new technologies and vast public databases are increasingly becoming cornerstones of citizen science. We discuss how postdigital citizen science operates in the context of knowledge capitalism while aiming at its transformation and highlight three key challenges for postdigital citizen science: the challenge of technology, the challenge of political economy, and the challenge of participation. Different postdigital challenges cannot be separated from each other, so we call for a deep reimagination and reconfiguration of citizen science in and for the postdigital condition. We start this reimagination by asking three questions: What is postdigital citizen science? Who (or what!) is the postdigital citizen scientist? How to conduct postdigital citizen science?

show abstract

We Are at an Extreme Point Where We Have to Go All in on What We Really Believe Education Should Be About

Cited by 6 publications

References 12 publications

Scrutinizing the Synthetic Syllabus

Scrutinizing the Synthetic Syllabus

Perspectives of Generative AI in Chemistry Education Within the TPACK Framework

Postdigital Citizen Science: Mapping the Field

Contact Info

Product

Resources

About