This paper estimates the causal effect of a large language model-based study assistant on student behavior and learning outcomes in a natural field setting with real academic stakes. I design and deploy a course-specific AI assistant (GPT-UAI) for undergraduate econometrics and evaluate it...

Credit card fraud detection remains a critical challenge for financial institutions, particularly due to extreme class imbalance and the continuously evolving nature of fraudulent behavior. This study investigates two complementary approaches: anomaly detection based on multivariate normal...

The emergence of artificial intelligence (AI) tools has offered new ways of teaching and learning. Businesses have also highlighted the importance of AI literacy in the workplace as AI is transforming operations and entire industries. Given the importance of obtaining AI skills and the...

AI is transforming how students learn, raising concerns about whether it expands educational opportunities or widens existing gaps. We examine this question in a preregistered lab experiment (N=572) in which students study a novel topic under one of three conditions: browsing only (control),...

This study investigates the internal antecedents of Strategic Learning Capability (SLC) within volatile business environments. Specifically, it explores the tripartite relationship between occupational subculture, the cognitive process of sensemaking, and the multi-dimensional facets of SLC...

Myanmar’s education system stands at a critical juncture, shaped by overlapping crises and significant resilience. Following years of conflict, political instability, and economic stress, recent data reveal both progress and persistent vulnerabilities. Primary school enrollment has largely...

When people exchange knowledge, both truths and falsehoods can proliferate. We study the role of explanations for the spread of truths and falsehoods in 15 financial decision tasks. Participants record the reasoning behind each of their answers with incentives for accuracy of their listeners'...

This study examines outcomes associated with a short-term intensive pedagogical experience aimed at developing social entrepreneurship competencies among university students at an Ashoka U-affiliated institution in Mexico. The program, Semana Tec de Agencia de Cambio, is a five-day experiential...

Researchers typically collect experimental data sequentially, allowing early outcome observations and adaptive treatment assignment to reduce exposure to inferior treatments. This article reviews multi-armed-bandit adaptive experimental designs that balance exploration and exploitation. Because...

Researchers typically collect experimental data sequentially, allowing early outcome observations and adaptive treatment assignment to reduce exposure to inferior treatments. This article reviews multiarmed-bandit adaptive experimental designs that balance exploration and exploitation. Because...

Land use transition toward multifunctional practices is greatly affected by social learning, yet the temporal interaction between learning mechanisms and network structure remains underexplored. This study examines two social learning channels, information exchange and normative pressure, and...

Just as backwards design starts with course learning objectives before planning assessments, content and teaching activities, narrative engagement by design imagines how to build engagement into the foundation of course structure and content, not just into teaching and learning activities. This...

This study introduces a novel machine learning-based methodology for detecting and forecasting the strength of weak signals in the labor market, using Greece as a case study and utilizing Eurostat time series data (2000-2023). Weak signals, conceptualized as subtle anomalies within otherwise...

Can a recession have a positive, long-term impact on firm innovation? A downturn represents an opportunity for firms to learn from their peers and try to understand the main drivers of resilience. If they deem R&D capital one of them, they may raise innovation in the following years, in order to...

This study proposes a hierarchical signal-to-policy learning framework for risk-aware portfolio optimization that integrates model-based return forecasting, explainable machine learning, and deep reinforcement learning (DRL) within a unified architecture. In the first stage, next-period returns...

Much research has examined the drivers of firms' R&D investments. However, many questions remain with respect to the role of R&D as a learning target and as a means of achieving legitimacy, particularly in the context of imitative R&D strategy. We develop a theory that integrates different...

The paper examines the early integration of Ukrainian refugee students into Italy's education system following the Russian Federation's full-scale invasion of Ukraine in 2022. Using administrative and survey data, the study presents enrollment trends, academic performance, and barriers to...

Strategic learning self-efficacy reflects the confidence of managers in their ability to learn from the outcomes of past strategic decisions and apply that knowledge to new decisions. This research examines the relationship between strategic learning self-efficacy and a firm's industry-adjusted...

We study a duel game in which each player has incomplete knowledge of the game parameters. We present a simple, heuristically motivated and easily implemented algorithm by which, in the course of repeated plays, each player estimates the missing parameters and consequently learns his optimal...

We discuss the importance of a sustainable education policy for the prosperity and stability of society. Early childhood education, schools and vocational training must all be seen as a lifelong learning project in order to promote equal opportunities. Despite the expansion of day care centres...

Context: Accompanying learners in their increasingly self-directed learning is an important goal in the field of vocational education and training. With digitalisation, the traditional role of the teacher, characterized in terms of an arbiter and transmitter of knowledge, is in crisis. Besides...

Context: The importance of both self-regulated and self-directed learners has been emphasised in lifelong learning. However, in theory, self-regulated learning (SRL) serves as a basis for becoming a self-directed learner. Therefore, SRL (which includes certain skills) needs to be developed in...

In a misspecified social learning setting, agents are condescending if they perceive their peers as having private information that is of lower quality than it is in reality. Applying this to a standard sequential model, we show that outcomes improve when agents are mildly condescending. In...

We introduce a collective experimentation problem where a continuum of agents choose the timing of irreversible actions under uncertainty and where public feedback from the actions arrives gradually over time. The leading application is the adoption of new technologies. The socially optimal...

We introduce a collective experimentation problem where a continuum of agents choose the timing of irreversible actions under uncertainty and where public feedback from the actions arrives gradually over time. The leading application is the adoption of new technologies. The socially optimal...