http://arxiv.org/abs/2110.00840 Francis Bacon popularized the idea that science is based on a process of induction by which repeated observations are, in some unspecified way, generalized to theories based on the assumption that the future resembles the past. This … Continued
As a technical sub-field of artificial intelligence (AI), explainable AI (XAI) has produced a vast collection of algorithms in recent years. However, explainability is an inherently human-centric property and the field is starting to embrace inter-disciplinary perspectives and human-centered approaches. … Continued
Missing data are ubiquitous in the era of big data and, if inadequately handled, are known to lead to biased findings and have deleterious impact on data-driven decision makings. To mitigate its impact, many missing value imputation methods have been … Continued
Departing from the claim that AI needs to be trustworthy, we find that ethical advice from an AI-powered algorithm is trusted even when its users know nothing about its training data and when they learn information about it that warrants … Continued
When machine-learning algorithms are deployed in high-stakes decisions, we want to ensure that their deployment leads to fair and equitable outcomes. This concern has motivated a fast-growing literature that focuses on diagnosing and addressing disparities in machine predictions. However, many … Continued
We are very excited that Eran is joining us in the HTC lab as a guest researcher. Eran is an educational R&D expert and consultant. Worked with municipal and national educational systems, and with business organizations, on developing models and … Continued
The HTC Lab and PhD program are excited to welcome Ilghar Samadzadeh and Ani Meliksetyan to the team. Ilghar has a background in social science research and international education, and Ani also has a background in international education. Both are … Continued
Farhana (PhD student in the HTC lab) recently presented a short talk at the AI4EDU conference on a comprehensive approach for moving from a general concept of AI Literacy to a competency model approach — paper | video
Farhana (HTC PhD student) was recently interviewed for The Weekly Regression podcast. Great listen!
Here is a link to the poster Jessa and Natalie presented at AERA this past week: https://www.quantamagazine.org/a-new-map-of-the-standard-model-of-particle-physics-20201022/ Examining the Relationship Between Teacher Change Fatigue and the Technology Acceptance Model Pre-COVID-19 Pandemic