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...

There is widespread concern that climate policy is moving too slowly and that decarbonization of economic development is coming too late for effective climate protection. We analyze three different effects that emerge endogenously during decarbonization and amplify current policies: growing...

Do agents believe to be agreeing more with others in the long-run? This paper designs an experiment to study how cognitive abilities affect actual and perceived disagreement in a standard sequential belief updating task with public signals. We document a persistent gap in the perception of...

Children appear to learn better when taught in their mother tongue. This finding gives rise to an argument that mother tongue-based multilingual education could effectively improve learning outcomes in low- and middle-income countries. However, the challenges of implementing an effective...

We evaluate the impact of a large‐scale teacher coaching program in Peru, a context with high teacher turnover, on teachers' pedagogical skills and student learning. Previous studies find that small‐scale coaching programs can improve teaching of reading and science in developing countries....

This study applies the Technology Acceptance Model to examine user acceptance of emerging technologies - specifically LINE and Google Translate- -for language learning. A multimodal interactive teaching program, combining cooperative learning and problem-based learning, was implemented at a...

People often form mental models based on incomplete information, revising them as new relevant data becomes available. In this paper, we experimentally investigate how individuals update their models when data on predictive variables are gradually revealed. We find that people's models tend to...

We study a dynamic principal-agent setting in which both sides learn about the importance of effort. The quality of the agent's output is not observed directly. Instead, the principal jointly designs an evaluation technology and a wage schedule. More precise performance evaluation reduces...

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 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...

Although sports are a dream career for many young people, only a small percentage of athletes can make a living from this. Moreover, even elite athletes with high incomes must find other employment after sports. This justifies the development of their human capital via education valued by...

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...