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• W2530175078 abstract "Personalised learning is an emerging paradigm of educational organisation that aims to move away from the “one size fits all” model where every student – even though everyone is different – receives education in the same form. The ideology of personalised learning stems from the desire to recognize individual differences in learning and advocates that students ought to be taking on more active roles in making their own educational choices, enabling them to become co-authors of their educational script. Even though personalised learning does not necessarily include the use of technology, the two are often inseparably linked. This thesis is an assessment of the desirability of personalised technology as a tool to achieve the ideals of the ideology of personalised learning.When the black box of personalised learning technology is opened, it can be divulged that these systems vary in the extent to which they are responsive to students’ needs: from customisation, where the action of the user is required, to data-driven systems that automatically adapt the material to the predicted individual needs. Critique of artificial intelligence entails that rule-based algorithms cannot make the complex decisions that teachers can because computational systems lack contextual knowledge. Even though this might be the case, technology might still be an improvement compared to a teacher who does not have the capacity to anticipate needs of many students and provide them with tailored approaches. However, even though data-driven personalised learning systems might do a decent job at tailoring, the ideology of personalised learning argues for tailored education only in the sense that the student becomes the agent of its educational decision-making. When personalised learning systems are providing tailored education automatically, they no longer require the users’ action for the personalisation which undermines their autonomy. Personalised learning technology does not only risk failing to achieve its own educational ideal, the data-intensive form of monitoring student learning poses a threat to student privacy. This might have negative consequences of the students but also for the quality of learning itself.When personalised learning technology will be implemented as a fix for the traditional model of education, policy-making and technology design should aim to avoid automatic personalisation since it undermines student autonomy and also strive to protect student privacy and student data according to the contextual information sharing norms." @default.
• W2530175078 created "2016-10-21" @default.
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• W2530175078 date "2016-01-01" @default.
• W2530175078 modified "2023-09-26" @default.
• W2530175078 title "It's getting personal: an assessment of the desirability of personalised learning technology" @default.
• W2530175078 hasPublicationYear "2016" @default.
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