논문 8편

This article theorizes predictive curricula: the reorganization of schooling around data extraction, dashboards, and algorithmic governance that translate learners into dividual profiles and narrow inquiry to what is computable. It maps how protocol and platform logics preempt pedagogical judgment,

Algorithmic decision-making systems such as Learning Analytics (LA) are widely used in an educational setting ranging from kindergarten to university. Most research focuses on how LA is used and adopted by teachers. However, the perspective of students and parents who experience the (in)direct conse

While AI-powered digital platforms are transforming the economy through forms of algorithmic governance that prioritize the automation of work and decision-making, it is critical to ensure that human education remains relevant in the age of machine learning. Unrestricted reliance on artificial intel

As part of a broader information literacy agenda, academic libraries are interested in advancing algorithmic literacy. Folk theories of algorithmic decision-making systems, such as recommender systems, can provide insights into designing and delivering enhanced algorithmic literacy initiatives. User

As algorithmic decision making is increasingly deployed in every walk of life, many researchers have raised concerns about fairness-related bias from such algorithms. But there is little research on harnessing psychometric methods to uncover potential discriminatory bias inside decision-making algor

Artificial intelligence in higher education is becoming more prevalent as it promises improvements and acceleration of administrative processes concerning student support, aiming for increasing student success and graduation rates. For instance, Academic Performance Prediction (APP) provides individ

This article seeks to explore different combinations of human and Artificial Intelligence (AI) decision-making in the context of distributed learning. Distributed learning institutions face specific challenges such as high levels of student attrition and ensuring quality, cost-effective student supp

In the socio-technical imaginary of higher education, algorithmic decision-making offers huge potential, but we also cannot deny the risks and ethical concerns. In fleeing from Frankenstein's monster, there is a real possibility that we will meet Kafka on our path, and not find our way out of the ma