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Understanding the affective, cognitive and behavioural processes involved in risk taking is essential for treatment and for setting environmental conditions to limit damage. Using Temporal Difference Reinforcement Learning (TDRL) we…

Machine Learning · Computer Science 2015-02-04 Joost Broekens , Tim Baarslag

A new method based on the rejection sampling for finding statistical tests is proposed. This method is conceptually intuitive, easy to implement, and applicable for arbitrary dimension. To illustrate its potential applicability, three…

Methodology · Statistics 2026-03-11 Markku Kuismin

People often deviate from expected utility theory when making risky and intertemporal choices. While the effects of probabilistic risk and time delay have been extensively studied in isolation, their interplay and underlying theoretical…

Theoretical Economics · Economics 2025-04-10 Ho Ka Chan , Taro Toyoizumi

Bounce Rate of different E-commerce websites depends on the different factors based upon the different devices through which traffic share is observed. This research paper focuses on how the type of products sold by different E-commerce…

Econometrics · Economics 2022-05-17 Himanshu Sharma

The success of a security attack crucially depends on time: the more time available to the attacker, the higher the probability of a successful attack. Formalisms such as Reliability block diagrams, Reliability graphs and Attack…

Cryptography and Security · Computer Science 2015-10-02 Rajesh Kumar , Dennis Guck , Marielle Stoelinga

While learning with limited labelled data can improve performance when the labels are lacking, it is also sensitive to the effects of uncontrolled randomness introduced by so-called randomness factors (e.g., varying order of data). We…

Computation and Language · Computer Science 2024-12-03 Branislav Pecher , Ivan Srba , Maria Bielikova

Tournaments are frequently used incentive mechanisms to enhance performance. In this paper, we use field data and show that skill disparities among contestants asymmetrically affect the performance of contestants. Skill disparities have…

General Economics · Economics 2024-10-29 Enzo Brox , Daniel Goller

Consider the sequential testing of binary outcomes. The a posteriori belief process and its objective conditional-probability counterpart generally differ but converge to the same result in well-defined tests. We show that unless the two…

Statistics Theory · Mathematics 2026-02-20 Kangda K. Wren

Classic item response models assume that all items with the same difficulty have the same response probability among all respondents with the same ability. These assumptions, however, may very well be violated in practice, and it is not…

Methodology · Statistics 2021-08-23 Minjeong Jeon , Ick Hoon Jin , Michael Schweinberger , Samuel Baugh

From scientific experiments to online A/B testing, the previously observed data often affects how future experiments are performed, which in turn affects which data will be collected. Such adaptivity introduces complex correlations between…

Machine Learning · Statistics 2018-01-03 Xinkun Nie , Xiaoying Tian , Jonathan Taylor , James Zou

In the modern knowledge economy, success demands sustained focus and high cognitive performance. Research suggests that human cognition is linked to a finite resource, and upon its depletion, cognitive functions such as self-control and…

Computers and Society · Computer Science 2018-09-11 Nathan O. Hodas , Jacob Hunter , Stephen J. Young , Kristina Lerman

Item (question) difficulties play a crucial role in educational assessments, enabling accurate and efficient assessment of student abilities and personalization to maximize learning outcomes. Traditionally, estimating item difficulties can…

Computation and Language · Computer Science 2025-09-19 Alexander Scarlatos , Nigel Fernandez , Christopher Ormerod , Susan Lottridge , Andrew Lan

This paper aims to present an online placement test. It is based on the Item Response Theory to provide relevant estimates of learner competences. The proposed test is the entry point of our e-Learning system. It gathers the learner…

Computers and Society · Computer Science 2014-11-20 Farid Merrouch , Meriem Hnida , Mohammed Khalidi Idrissi , Samir Bennani

We explore whether the human ratings of open ended responses can be explained with non-content related features, and if such effects vary across different mathematics-related items. When scoring is rigorously defined and rooted in a…

Applications · Statistics 2024-05-15 Aubrey Condor

We analyze the effectiveness of working in pairs on the Conceptual Survey of Electricity and Magnetism test in a calculus-based introductory physics course. Students who collaborated with a peer showed significantly larger normalized gain…

Physics Education · Physics 2016-02-25 Chandralekha Singh

Consider a predictor, a learner, whose input is a stream of discrete items. The predictor's task, at every time point, is probabilistic multiclass prediction, i.e. to predict which item may occur next by outputting zero or more candidate…

Machine Learning · Computer Science 2024-12-25 Omid Madani

We designed and ran an experiment to test how often people's choices are reversed by others' recommendations when facing different levels of confirmation and conformity pressures. In our experiment participants were first asked to provide…

Computers and Society · Computer Science 2011-08-30 Haiyi Zhu , Bernardo A. Huberman , Yarun Luon

A rater's ability to assign accurate scores can significantly impact the outcomes of educational assessments. However, common indices for evaluating rater characteristics typically focus on either their severity or their discrimination…

Applications · Statistics 2025-02-14 Y. -G. Wang , J. Wu , X. Qiu

A test is adaptive when its sequence and number of questions is dynamically tuned on the basis of the estimated skills of the taker. Graphical models, such as Bayesian networks, are used for adaptive tests as they allow to model the…

Artificial Intelligence · Computer Science 2021-09-29 Alessandro Antonucci , Francesca Mangili , Claudio Bonesana , Giorgia Adorni

In many areas of data mining, data is collected from humans beings. In this contribution, we ask the question of how people actually respond to ordinal scales. The main problem observed is that users tend to be volatile in their choices,…

Human-Computer Interaction · Computer Science 2017-03-01 Kevin Jasberg , Sergej Sizov