This article delves deeper into the causal perspective of Necessary Condition Analysis (NCA). In contrast to traditional probabilistic sufficiency approaches in quantitative social science research about what will happen on average in a group of cases, NCA is interested in … Continued
How do language models use information provided as context when generating a response? Can we infer whether a particular generated statement is actually grounded in the context, a misinterpretation, or fabricated? To help answer these questions, we introduce the problem … Continued
E-learning environments are increasingly harnessing large language models (LLMs) like GPT-3.5 and GPT-4 for tailored educational support. This study introduces an approach that integrates dynamic knowledge graphs with LLMs to offer nuanced student assistance. By evaluating past and ongoing student … Continued
The growing integration of AI tools in communication promises enhanced efficiency and productivity. However, concerns about the erosion of trust and authenticity have fueled debates over the disclosure and regulation ofAI-mediated communication. It remains unclear a) how AI mediation influences … Continued
Qualitative analysis is critical to understanding human datasets in many social science disciplines. Open coding is an inductive qualitative process that identifies and interprets “open codes” from datasets. Yet, meeting methodological expectations (such as “as exhaustive as possible”) can be … Continued
The manual assessment and grading of student writing is a time-consuming yet critical task for teachers. Recent developments in generative AI, such as large language models, offer potential solutions to facilitate essay-scoring tasks for teachers. In our study, we evaluate … Continued
Qualitative researchers use tools to collect, sort, and analyze their data. Should qualitative researchers use large language models (LLMs) as part of their practice? LLMs could augment qualitative research, but it is unclear if their use is appropriate, ethical, or … Continued
The promise of human behavioral simulation–general-purpose computational agents that replicate human behavior across domains–could enable broad applications in policymaking and social science. We present a novel agent architecture that simulates the attitudes and behaviors of 1,052 real individuals–applying large language … Continued
In social sciences, researchers often face challenges when conducting large-scale experiments, particularly due to the simulations’ complexity and the lack of technical expertise required to develop such frameworks. Agent-Based Modeling (ABM) is a computational approach that simulates agents’ actions and … Continued
Artificial intelligence (AI) may be the new-new-norm in a post-pandemic learning environment. There is a growing number of university students using AI like ChatGPT and Bard to support their academic experience. Much of the AI in higher education research to … Continued