Administering Likert-type questionnaires to online samples risks contamination of the data by malicious computer-generated random responses, also known as bots. Although nonresponsivity indices (NRIs) such as person-total correlations or Mahalanobis distance have shown great promise to detect bots, universal cutoff values are elusive. An initial…

This systematic literature review investigates the fairness of machine learning algorithms in educational settings, focusing on recent studies and their proposed solutions to address biases. Applications analyzed include student dropout prediction, performance prediction, forum post classification, and recommender systems. We identify common…

Cyberbullying is the use of digital communication tools and spaces to inflict physical, mental, or emotional distress. This serious form of aggression is frequently targeted at, but not limited to, vulnerable populations. A common problem when creating machine learning models to identify cyberbullying is the availability of accurately annotated,…

This article investigates the impact of educational contexts on automatic classification of online discussion messages according to cognitive presence, an essential construct of the community of inquiry model. In particular, the work reported in the article analyzed online discussion messages written in Brazilian Portuguese from two different…

The past two decades witnessed increased attention in the role of Written Corrective Feedback (WCF) in improving the English as a second language (ESL) students' written linguistic accuracy. Several methods were suggested, including the use of the electronic means of providing corrective feedback. The electronic methods proved to be effective…

Drawing on Vygotskian sociocultural theory of mind and social constructivism, and adopting a sequential exploratory mixed-methods approach, this study explored the impact of online dynamic assessment (DA) on EFL learners' academic writing skills through one-on-one individual and online synchronous DA sessions over Google Docs. It also investigated…

Within the landscape of educational data, textual natural language is an increasingly vast source of learning-centered interactions. In natural language dialogue, student contributions hold important information about knowledge and goals. Automatically modeling the dialogue act of these student utterances is crucial for scaling natural language…