CALL FOR PAPER 1/2025
2024-12-23
The Educational Experience and the Effects of Artificial Intelligence
Artificial intelligence (AI) is pervasive and widespread, generating immense wealth and attracting significant investments. It presents opportunities and risks – whose boundaries remain largely unknown – and is accelerating in ways transforming the world.
The intersection of AI and pedagogy is relatively new. We are at the dawn of this relationship: a common ground is yet to be established, and even a shared lexicon is still lacking. However, given its relevance and urgency, we must ask ourselves whether pedagogy has a role (if it makes sense to think it does) in the contexts and domains of AI.
At first glance, and in general terms, one might say that pedagogy could/should play a critical and reflective role in AI. More specifically, pedagogy and pedagogical research – overcoming initial fears and panic – are called upon to explore and deepen ethical issues raised by AI, anthropological concerns related to human-machine interaction, and questions about learning models. In this regard, AI discusses machine learning and deep learning: how different is human learning from a machine, particularly a neural network implemented on a computer? These understandings and discussions raise highly significant epistemological questions for pedagogy. Take, for instance, the different types of AI. In so-called GOFAI (Good Old-Fashioned Artificial Intelligence), based on cognitivism and logic, the code and programming (input) are human, and the result (output) remains, in a sense, human – the machine merely performs tasks faster. Here, the differences between human and artificial teaching-learning processes are relatively evident. In contrast, in a neural network, which is a connectionist, statistical-inferential, and stochastic system, generalization from data – and thus learning – “emerges” at some point. However, we do not fully understand why or how. In this case, the differences between humans and machines appear more nuanced. This example invites us to question how the human dimension differs from the artificial one: is there a specificity for human beings? We would like to answer this question affirmatively, but such an answer is far from self-evident. If there is a human specificity, what is it? And what are the pedagogical implications of such a broad question in the current historical-cultural context?
This call invites the pedagogical community to share reflections on three key questions:
Deadline
Abstract submission (via email only to rivista@sipeges.it): January 26, 2025
Full article submission (via the journal’s OJS platform only): April 13, 2025
Publication: June/July 2025
https://ojs.pensamultimedia.it/index.php/sipeges/about/submissions
Artificial intelligence (AI) is pervasive and widespread, generating immense wealth and attracting significant investments. It presents opportunities and risks – whose boundaries remain largely unknown – and is accelerating in ways transforming the world.
The intersection of AI and pedagogy is relatively new. We are at the dawn of this relationship: a common ground is yet to be established, and even a shared lexicon is still lacking. However, given its relevance and urgency, we must ask ourselves whether pedagogy has a role (if it makes sense to think it does) in the contexts and domains of AI.
At first glance, and in general terms, one might say that pedagogy could/should play a critical and reflective role in AI. More specifically, pedagogy and pedagogical research – overcoming initial fears and panic – are called upon to explore and deepen ethical issues raised by AI, anthropological concerns related to human-machine interaction, and questions about learning models. In this regard, AI discusses machine learning and deep learning: how different is human learning from a machine, particularly a neural network implemented on a computer? These understandings and discussions raise highly significant epistemological questions for pedagogy. Take, for instance, the different types of AI. In so-called GOFAI (Good Old-Fashioned Artificial Intelligence), based on cognitivism and logic, the code and programming (input) are human, and the result (output) remains, in a sense, human – the machine merely performs tasks faster. Here, the differences between human and artificial teaching-learning processes are relatively evident. In contrast, in a neural network, which is a connectionist, statistical-inferential, and stochastic system, generalization from data – and thus learning – “emerges” at some point. However, we do not fully understand why or how. In this case, the differences between humans and machines appear more nuanced. This example invites us to question how the human dimension differs from the artificial one: is there a specificity for human beings? We would like to answer this question affirmatively, but such an answer is far from self-evident. If there is a human specificity, what is it? And what are the pedagogical implications of such a broad question in the current historical-cultural context?
This call invites the pedagogical community to share reflections on three key questions:
- What is the difference between an educational experience among humans and one between humans and machines?
- Why would a human subject prefer to be educated and trained by another human rather than a machine?
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Beyond simple dualisms, how does the concept of hybridization change, if it does, with the advent of AI technologies in education?
Deadline
Abstract submission (via email only to rivista@sipeges.it): January 26, 2025
Full article submission (via the journal’s OJS platform only): April 13, 2025
Publication: June/July 2025
https://ojs.pensamultimedia.it/index.php/sipeges/about/submissions