Explainable artificial intelligence for education and training

K Fiok, FV Farahani, W Karwowski… - The Journal of …, 2022 - journals.sagepub.com
Researchers and software users benefit from the rapid growth of artificial intelligence (AI) to
an unprecedented extent in various domains where automated intelligent action is required …

[HTML][HTML] Sentiment analysis of clinical narratives: a scoping review

K Denecke, D Reichenpfader - Journal of Biomedical Informatics, 2023 - Elsevier
A clinical sentiment is a judgment, thought or attitude promoted by an observation with
respect to the health of an individual. Sentiment analysis has drawn attention in the …

[HTML][HTML] A text classification approach to detect psychological stress combining a lexicon-based feature framework with distributional representations

S Muñoz, CA Iglesias - Information Processing & Management, 2022 - Elsevier
Nowadays, stress has become a growing problem for society due to its high impact on
individuals but also on health care systems and companies. In order to overcome this …

A large-scaled corpus for assessing text readability

S Crossley, A Heintz, JS Choi, J Batchelor… - Behavior Research …, 2023 - Springer
This paper introduces the CommonLit Ease of Readability (CLEAR) corpus, which provides
unique readability scores for~ 5000 text excerpts along with information about the excerpt's …

Explainable automated essay scoring: Deep learning really has pedagogical value

V Kumar, D Boulanger - Frontiers in education, 2020 - frontiersin.org
Automated essay scoring (AES) is a compelling topic in Learning Analytics for the primary
reason that recent advances in AI find it as a good testbed to explore artificial …

Moving beyond classic readability formulas: New methods and new models

SA Crossley, S Skalicky… - Journal of Research in …, 2019 - Wiley Online Library
Background Advances in natural language processing (NLP) and computational linguistics
have facilitated major improvements on traditional readability formulas that aim at predicting …

Multimodal fusion methods with deep neural networks and meta-information for aggression detection in surveillance

N Jaafar, Z Lachiri - Expert Systems with Applications, 2023 - Elsevier
Multimodal fusion has become one of the hottest topics in affective computing and other
research areas. Yet, this topic is less studied in surveillance systems. In general, it focused …

Hate speech and counter speech detection: Conversational context does matter

X Yu, E Blanco, L Hong - arXiv preprint arXiv:2206.06423, 2022 - arxiv.org
Hate speech is plaguing the cyberspace along with user-generated content. This paper
investigates the role of conversational context in the annotation and detection of online hate …

The triangulation of ethical leader signals using qualitative, experimental, and data science methods

GC Banks, R Ross, AA Toth, S Tonidandel… - The Leadership …, 2023 - Elsevier
To advance ethical leadership using signaling theory, the current work presents a mixture of
inductive and deductive studies. Using a constant comparative analysis method, Study 1 …

Automated essay scoring and the deep learning black box: How are rubric scores determined?

VS Kumar, D Boulanger - International Journal of Artificial Intelligence in …, 2021 - Springer
This article investigates the feasibility of using automated scoring methods to evaluate the
quality of student-written essays. In 2012, Kaggle hosted an Automated Student Assessment …