Machine Learning in the educational context: Evidence of prediction accuracy considering essays in English as a foreign languageAbstract: Essay writing is an important skill in both first and foreign language learning. ...
Computational PsychiatryAbstract. Computational psychiatry is a young research field which attempts to bring advances from theoretical and experimental neurosciences to bear on clinical issues in psychiatry. The motivation for the use of computational ...
Since a couple of years, the term Big Data describes technologies to extract knowledge from data. Applications of Big Data and their consequences are also increasingly discussed in the mass media. Because medicine is an empirical science, we discuss the ...
Medicina ex Machina: Machine Learning in MedicineAbstract. Machine learning (ML) is an active field of research in computer science and has already markedly changed our daily lives in the past few years. As a result of the ongoing developments, ...
Artificial Intelligence in Radiology – Definition, Potential and ChallengesAbstract. Artificial Intelligence (AI) is omnipresent. It has neatly permeated our daily life, even if we are not always fully aware of ...
Between Human and Machine: Artificial Intelligence to Facilitate Learning ProcessesAbstract.Introduction: Since the recent digitalization offensive, the role and use of artificial intelligence (AI) and machine ...
Machine Learning to Foster Higher Level CompetenciesAbstract:Background: The radical changes that modern societies have experienced through digitalization have made it essential to equip current and future ...
Abstract: Performance efficiency in cognitive tasks is a combination of effectiveness, that is, accuracy, and cognitive effort. Resting-state and task-related autonomic and cortical activity, together with psychological variables, may represent effective ...
Abstract. Mindfulness refers to a stance of nonjudgmental awareness of present-moment experiences. A growing body of research suggests that mindfulness may increase cognitive resources, thereby buffering stress. However, existing models ...
Abstract. Research interest in personality dynamics over time is rapidly growing. Passive personality assessment via mobile sensors offers an intriguing new approach for measuring a wide variety of personality dynamics. In this paper, we ...
Abstract. The predictive accuracy of personality-criterion regression models may be improved with statistical learning (SL) techniques. This study introduced a novel SL technique, BISCUIT (Best Items Scale that is Cross-validated, Unit-...
Abstract. Modern prediction methods from machine learning (ML) and artificial intelligence (AI) are becoming increasingly popular, also in the field of psychological assessment. These methods provide unprecedented flexibility for ...
Abstract. Posttraumatic stress disorder (PTSD) is a debilitating disease that can occur after experiencing a traumatic event. Despite recent progress in computational research, it has not yet been possible to identify precise and reliable ...
Abstract. Novel technological advances allow distributed and automatic measurement of human behavior. While these technologies provide exciting new research opportunities, they also provide challenges: datasets collected using new ...
Abstract: Autonomous sensory meridian response (ASMR) is a tingling sensation occurring in response to specific sensory stimuli. Scholarship has yet to investigate what attributes these stimuli possess that allows them to facilitate ...
Abstract. In recent years, machine learning (ML) modeling (often referred to as artificial intelligence) has become increasingly popular for personnel selection purposes. Numerous organizations use ML-based procedures for screening ...
Abstract. The increasing usage of new technologies implies changes for personality research. First, human behavior becomes measurable by digital data, and second, digital manifestations to some extent replace conventional behavior in the analog world. ...
Abstract. Longitudinal panels include several thousand participants and variables. Traditionally, psychologists analyze only a few variables – partly because common unregularized linear models perform poorly when the number of variables (p) approaches ...
Abstract. Machine learning tools are increasingly used in social sciences and policy fields due to their increase in predictive accuracy. However, little research has been done on how well the models of machine learning methods replicate across samples. ...
Abstract. In our era of accelerated accumulation of knowledge, the manual screening of literature for eligibility is increasingly becoming too labor-intensive for summarizing the current state of knowledge in a timely manner. Recent ...