Teenagers today are coming of age under unprecedented, pervasive networks of institutional mass surveillance technologies. Surveillance technologies spreading in youth spaces are impacting young people's prospects today and are expected to continue in the future. Additionally, today's teenagers will be tomorrow's decision-makers, tasked with…

The COVID-19 pandemic suspended established practices that, in normal times, are seen as central to the functioning of education systems. For example, in England, school closures led to the cancellation of national examinations in 2020, and their attempted replacement with an algorithmic model. Following public outcry about what were seen as the…

Aim/Purpose: The study focused on learner sentiments and experiences after using the Moodle assessment module and trained a machine learning classifier for future sentiment predictions. Background: Learner assessment is one of the standard methods instructors use to measure students' performance and ascertain successful teaching objectives. In…

The quality education goal is a Sustainable Development Goal (SDG) that the United Nations aim to achieve by 2023. While there is still a long way to go to achieve the goal, information and communications technologies (ICT) provide efficient tools to substantially strengthen and accelerate the process. Thus, in this chapter, the authors design an…

Algorithms and machine learning models are being used more frequently in educational settings, but there are concerns that they may discriminate against certain groups. While there is some research on algorithmic fairness, there are two main issues with the current research. Firstly, it often focuses on gender and race and ignores other groups.…

Commonly used methods to simulate the oxidation-reduction (redox) titration curves include the three-step method and the rigorous method. The simple three-step method simulates the redox titration curve with the assumption that the reaction is complete, which is widely used in undergraduate quantitative analysis courses. For the rigorous…

This work proposes Dynamic Linear Epsilon-Greedy, a novel contextual multi-armed bandit algorithm that can adaptively assign personalized content to users while enabling unbiased statistical analysis. Traditional A/B testing and reinforcement learning approaches have trade-offs between empirical investigation and maximal impact on users. Our…

Many patterns found in natural language syntax have multiple possible explanations or structural descriptions. Even within the currently dominant Minimalist theoretical framework (Chomsky 1995, 2000), it is not uncommon to encounter multiple analyses for the same phenomenon proposed in the literature. A natural question, then, is whether one could…

In this thesis, we incorporate information theory into statistical signal processing and machine learning in order to achieve robust learning in presence of outliers (or generally in environments with non-Gaussian structure). In other words, by incorporating information theory especially when structure of environment is non-Gaussian, the…

We are currently in a century of data where massive amount of data are collected and processed every day, and machine learning plays a critical role in automatically processing the data and mining useful information from it for making decisions. Despite the wide and successful applications of machine learning in different fields, the robustness of…

Background: Despite global interest in the interface of Algorithmically-driven writing tools (ADWTs) and academic integrity, empirical data considering educators' perspectives on the challenges, benefits, and policies of ADWTs use remain scarce. Aim: This study responds to calls for empirical investigation concerning the affordances and…

The application of machine learning (ML) has grown and is now used to enhance learning outcomes. In blended classroom settings, ML, emerging smartphones and wearable technologies are commonly used to improve teaching and learning. The combination of these advanced technologies and ML plays a crucial role in enhancing real-time feedback quality.…

The rapid advancement of powerful Large Language Models (LLMs), such as ChatGPT and Llama, has revolutionized the world by bringing new creative possibilities and enhancing productivity. However, these advancements also pose significant challenges and risks, including the potential for misuse in the form of fake news, academic dishonesty,…

Purpose: This study aims to develop a talent selection model for learning organizations capable of connecting two groups, candidates in a talent hiring process and managers of the hiring company, in a reliable process, promoting organizational learning and increasing employee satisfaction. Design/methodology/approach: This paper integrates…

One trending theme within research on learning and teaching is an emphasis on artificial intelligence (AI). While AI offers opportunities in the educational arena, blindly replacing human involvement is not the answer. Instead, current research suggests that the key lies in harnessing the strengths of both humans and AI to create a more effective…