TY - JOUR A1 - Hafner, Verena A1 - Hommel, Bernhard A1 - Kayhan, Ezgi A1 - Lee, Dongheui A1 - Paulus, Markus A1 - Verschoor, Stephan T1 - Editorial: The mechanisms underlying the human minimal self JF - Frontiers in psychology KW - agents KW - self KW - minimal self KW - robotics KW - humanoids KW - cognition Y1 - 2022 U6 - https://doi.org/10.3389/fpsyg.2022.961480 SN - 1664-1078 VL - 13 PB - Frontiers Media CY - Lausanne ER - TY - JOUR A1 - Chevalère, Johann A1 - Lazarides, Rebecca A1 - Yun, Hae Seon A1 - Henke, Anja A1 - Lazarides, Claudia A1 - Pinkwart, Niels A1 - Hafner, Verena V. T1 - Do instructional strategies considering activity emotions reduce students’ boredom in a computerized open-ended learning environment? JF - Computers and education N2 - Providing students with efficient instruction tailored to their individual characteristics in the cognitive and affective domains is an important goal in research on computer-based learning. This is especially important when seeking to enhance students' learning experience, such as by counteracting boredom, a detrimental emotion for learning. However, studies comparing instructional strategies triggered by either cognitive or emotional characteristics are surprisingly scarce. In addition, little research has examined the impact of these types of instructional strategies on performance and boredom trajectories within a lesson. In the present study, we compared the effectiveness of an intelligent tutoring system that adapted variable levels of hint details to a combination of students' dynamic, self-reported emotions and task performance (i.e., the experimental condition) to a traditional hint delivery approach consisting of a progressive, incremental supply of details following students' failures (i.e., the control condition). Linear mixed models of time-related changes in task performance and the intensity of boredom over two 1-h sessions showed that students (N = 104) in the two conditions exhibited equivalent progression in task performance and similar trajectories in boredom intensity. However, a consideration of students' achievement levels in the analyses (i.e., their final performance on the task) revealed that higher achievers in the experimental condition showed a reduction in boredom during the first session, suggesting possible benefits of using emotional information to increase the contingency of the hint delivery strategy and improve students’ learning experience. KW - intelligent tutoring system KW - Betty's brain KW - boredom KW - linear mixed models Y1 - 2023 U6 - https://doi.org/10.1016/j.compedu.2023.104741 SN - 1873-782X SN - 0360-1315 VL - 196 PB - Elsevier ER - TY - JOUR A1 - Nguyen, Dong Hai Phuong A1 - Georgie, Yasmin Kim A1 - Kayhan, Ezgi A1 - Eppe, Manfred A1 - Hafner, Verena Vanessa A1 - Wermter, Stefan T1 - Sensorimotor representation learning for an "active self" in robots BT - a model survey JF - Künstliche Intelligenz : KI ; Forschung, Entwicklung, Erfahrungen ; Organ des Fachbereichs 1 Künstliche Intelligenz der Gesellschaft für Informatik e.V., GI / Fachbereich 1 der Gesellschaft für Informatik e.V N2 - Safe human-robot interactions require robots to be able to learn how to behave appropriately in spaces populated by people and thus to cope with the challenges posed by our dynamic and unstructured environment, rather than being provided a rigid set of rules for operations. In humans, these capabilities are thought to be related to our ability to perceive our body in space, sensing the location of our limbs during movement, being aware of other objects and agents, and controlling our body parts to interact with them intentionally. Toward the next generation of robots with bio-inspired capacities, in this paper, we first review the developmental processes of underlying mechanisms of these abilities: The sensory representations of body schema, peripersonal space, and the active self in humans. Second, we provide a survey of robotics models of these sensory representations and robotics models of the self; and we compare these models with the human counterparts. Finally, we analyze what is missing from these robotics models and propose a theoretical computational framework, which aims to allow the emergence of the sense of self in artificial agents by developing sensory representations through self-exploration. KW - Developmental robotics KW - Body schema KW - Peripersonal space KW - Agency KW - Robot learning Y1 - 2021 U6 - https://doi.org/10.1007/s13218-021-00703-z SN - 0933-1875 SN - 1610-1987 VL - 35 IS - 1 SP - 9 EP - 35 PB - Springer CY - Berlin ER -