TY - JOUR A1 - Guhn, Anne A1 - Dresler, Thomas A1 - Andreatta, Marta A1 - Müller, Laura D. A1 - Hahn, Tim A1 - Tupak, Sara V. A1 - Polak, Thomas A1 - Deckert, Jürgen A1 - Herrmann, Martin J. T1 - Medial prefrontal cortex stimulation modulates the processing of conditioned fear N2 - The extinction of conditioned fear depends on an efficient interplay between the amygdala and the medial prefrontal cortex (mPFC). In rats, high-frequency electrical mPFC stimulation has been shown to improve extinction by means of a reduction of amygdala activity. However, so far it is unclear whether stimulation of homologues regions in humans might have similar beneficial effects. Healthy volunteers received one session of either active or sham repetitive transcranial magnetic stimulation (rTMS) covering the mPFC while undergoing a 2-day fear conditioning and extinction paradigm. Repetitive TMS was applied offline after fear acquisition in which one of two faces (CS+ but not CS−) was associated with an aversive scream (UCS). Immediate extinction learning (day 1) and extinction recall (day 2) were conducted without UCS delivery. Conditioned responses (CR) were assessed in a multimodal approach using fear-potentiated startle (FPS), skin conductance responses (SCR), functional near-infrared spectroscopy (fNIRS), and self-report scales. Consistent with the hypothesis of a modulated processing of conditioned fear after high-frequency rTMS, the active group showed a reduced CS+/CS− discrimination during extinction learning as evident in FPS as well as in SCR and arousal ratings. FPS responses to CS+ further showed a linear decrement throughout both extinction sessions. This study describes the first experimental approach of influencing conditioned fear by using rTMS and can thus be a basis for future studies investigating a complementation of mPFC stimulation to cognitive behavioral therapy (CBT). KW - fear conditioning KW - memory consolidation and extinction KW - learning KW - transcranial magnetic stimulation (TMS) KW - medial prefrontal cortex (mPFC) Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-111309 ER - TY - JOUR A1 - Krishna, Anand A1 - Peter, Sebastian M. T1 - Questionable research practices in student final theses – prevalence, attitudes, and the role of the supervisor’s perceived attitudes JF - PLoS ONE N2 - Although questionable research practices (QRPs) and p-hacking have received attention in recent years, little research has focused on their prevalence and acceptance in students. Students are the researchers of the future and will represent the field in the future. Therefore, they should not be learning to use and accept QRPs, which would reduce their ability to produce and evaluate meaningful research. 207 psychology students and fresh graduates provided self-report data on the prevalence and predictors of QRPs. Attitudes towards QRPs, belief that significant results constitute better science or lead to better grades, motivation, and stress levels were predictors. Furthermore, we assessed perceived supervisor attitudes towards QRPs as an important predictive factor. The results were in line with estimates of QRP prevalence from academia. The best predictor of QRP use was students’ QRP attitudes. Perceived supervisor attitudes exerted both a direct and indirect effect via student attitudes. Motivation to write a good thesis was a protective factor, whereas stress had no effect. Students in this sample did not subscribe to beliefs that significant results were better for science or their grades. Such beliefs further did not impact QRP attitudes or use in this sample. Finally, students engaged in more QRPs pertaining to reporting and analysis than those pertaining to study design. We conclude that supervisors have an important function in shaping students’ attitudes towards QRPs and can improve their research practices by motivating them well. Furthermore, this research provides some impetus towards identifying predictors of QRP use in academia. KW - supervisors KW - psychology KW - human learning KW - learning KW - careers KW - scientists KW - psychometrics KW - psychologists Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-177296 VL - 13 IS - 8 ER - TY - THES A1 - Hörmann, Markus T1 - Analyzing and fostering students' self-regulated learning through the use of peripheral data in online learning environments T1 - Analyse und Förderung des selbstgesteuerten Lernens durch die Verwendung von peripheren Daten in Online-Lernumgebungen N2 - Learning with digital media has become a substantial part of formal and informal educational processes and is gaining more and more importance. Technological progress has brought overwhelming opportunities for learners, but challenges them at the same time. Learners have to regulate their learning process to a much greater extent than in traditional learning situations in which teachers support them through external regulation. This means that learners must plan their learning process themselves, apply appropriate learning strategies, monitor, control and evaluate it. These requirements are taken into account in various models of self-regulated learning (SRL). Although the roots of research on SRL go back to the 1980s, the measurement and adequate support of SRL in technology-enhanced learning environments is still not solved in a satisfactory way. An important obstacle are the data sources used to operationalize SRL processes. In order to support SRL in adaptive learning systems and to validate theoretical models, instruments are needed which meet the classical quality criteria and also fulfil additional requirements. Suitable data channels must be measurable "online", i.e., they must be available in real time during learning for analyses or the individual adaptation of interventions. Researchers no longer only have an interest in the final results of questionnaires or tasks, but also need to examine process data from interactions between learners and learning environments in order to advance the development of theories and interventions. In addition, data sources should not be obtrusive so that the learning process is not interrupted or disturbed. Measurements of physiological data, for example, require learners to wear measuring devices. Moreover, measurements should not be reactive. This means that other variables such as learning outcomes should not be influenced by the measurement. Different data sources that are already used to study and support SRL processes, such as protocols on thinking aloud, screen recording, eye tracking, log files, video observations or physiological sensors, meet these criteria to varying degrees. One data channel that has received little attention in research on educational psychology, but is non-obtrusive, non-reactive, objective and available online, is the detailed, timely high-resolution data on observable interactions of learners in online learning environments. This data channel is introduced in this thesis as "peripheral data". It records both the content of learning environments as context, and related actions of learners triggered by mouse and keyboard, as well as the reactions of learning environments, such as structural or content changes. Although the above criteria for the use of the data are met, it is unclear whether this data can be interpreted reliably and validly with regard to relevant variables and behavior. Therefore, the aim of this dissertation is to examine this data channel from the perspective of SRL and thus further close the existing research gap. One development project and four research projects were carried out and documented in this thesis. N2 - Lernen mit digitalen Medien ist ein substantieller Bestandteil formeller und informeller Bildungsprozesse geworden und gewinnt noch immer an Bedeutung. Technologischer Fortschritt hat überwältigende Möglichkeiten für Lernende geschaffen, stellt aber gleichzeitig auch große Anforderungen an sie. Lernende müssen ihren Lernprozess sehr viel stärker selbst regulieren als in traditionellen Lernsituationen, in denen Lehrende durch externe Regulation unterstützen. Das heißt, Lernende müssen ihren Lernprozess selbst planen, geeignete Lernstrategien anwenden, ihn überwachen, steuern und evaluieren. Diesen Anforderungen wird in verschiedenen Modellen des selbst-regulierten Lernens (SRL) Rechnung getragen. Obwohl die Wurzeln der Forschung zu SRL bis in die 1980er Jahren zurück reichen, ist die Messung und adäquate Unterstützung von SRL in technologie-gestützten Lernumgebungen noch immer nicht zufriedenstellend gelöst. Eine wichtige Hürde sind dabei die Datenquellen, die zur Operationalisierung von SRL-Prozessen herangezogen werden. Um SRL in adaptiven Lernsystemen zu unterstützen und theoretische Modelle zu validieren, werden Instrumente benötigt, die klassischen Gütekriterien genügen und darüber hinaus weitere Anforderungen erfüllen. Geeignete Datenkanäle müssen „online“ messbar sein, das heißt bereits während des Lernens in Echtzeit für Analysen oder die individuelle Anpassung von Interventionen zur Verfügung stehen. Forschende interessieren sich nicht mehr nur für die Endergebnisse von Fragebögen oder Aufgaben, sondern müssen auch Prozessdaten von Interaktionen zwischen Lernenden und Lernumgebungen untersuchen, um die Entwicklung von Theorien und Interventionen voranzutreiben. Zudem sollten Datenquellen nicht intrusiv sein, sodass der Lernprozess nicht unterbrochen oder gestört wird. Dies ist zum Beispiel bei Messungen physiologischer Daten der Fall, zu deren Erfassung die Lernenden Messgeräte tragen müssen. Außerdem sollten Messungen nicht reaktiv sein – andere Variablen (z.B. der Lernerfolg) sollten also nicht von der Messung beeinflusst werden. Unterschiedliche Datenquellen die zur Untersuchung und Unterstützung von SRL-Prozessen bereits verwendet werden, wie z.B. Protokolle über lautes Denken, Screen-Recording, Eye Tracking, Log-Files, Videobeobachtungen oder physiologische Sensoren erfüllen diese Kriterien in jeweils unterschiedlichem Ausmaß. Ein Datenkanal, dem in der pädagogische-psychologischen Forschung bislang kaum Beachtung geschenkt wurde, der aber nicht-intrusiv, nicht-reaktiv, objektiv und online verfügbar ist, sind detaillierte, zeitlich hochauflösende Daten über die beobachtbare Interkation von Lernenden in online Lernumgebungen. Dieser Datenkanal wird in dieser Arbeit als „peripheral data“ eingeführt. Er zeichnet sowohl den Inhalt von Lernumgebungen als Kontext auf, als auch darauf bezogene Aktionen von Lernenden, ausgelöst durch Maus und Tastatur, sowie die Reaktionen der Lernumgebungen, wie etwa strukturelle oder inhaltliche Veränderungen. Zwar sind die oben genannten Kriterien zur Nutzung der Daten erfüllt, allerdings ist unklar, ob diese Daten auch reliabel und valide hinsichtlich relevanten Variablen und Verhaltens interpretiert werden können. Ziel dieser Dissertation ist es daher, diesen Datenkanal aus Perspektive des SRL zu untersuchen und damit die bestehende Forschungslücke weiter zu schließen. Dafür wurden eine Entwicklungs- sowie vier Forschungsarbeiten durchgeführt und in dieser Arbeit dokumentiert. KW - Selbstgesteuertes Lernen KW - Computerunterstütztes Lernen KW - self-regulated learning KW - process analysis KW - online learning KW - mouse tracking KW - keyboard tracking KW - learning KW - selfregulated Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-180097 ER - TY - JOUR A1 - Schindler, Julia A1 - Richter, Tobias A1 - Mar, Raymond T1 - Does generation benefit learning for narrative and expository texts? A direct replication attempt JF - Applied Cognitive Psychology N2 - Generated information is better recognized and recalled than information that is read. This so‐called generation effect has been replicated several times for different types of material, including texts. Perhaps the most influential demonstration was by McDaniel et al. (1986, Journal of Memory and Language, 25, 645–656; henceforth MEDC). This group tested whether the generation effect occurs only if the generation task stimulates cognitive processes not already stimulated by the text. Numerous studies, however, report difficulties replicating this text by generation‐task interaction, which suggests that the effect might only be found under conditions closer to the original method of MEDC. To test this assumption, we will closely replicate MEDC's Experiment 2 in German and English‐speaking samples. Replicating the effect would suggest that it can be reproduced, at least under limited conditions, which will provide the necessary foundation for future investigations into the boundary conditions of this effect, with an eye towards its utility in applied contexts. KW - expository texts KW - generation effect KW - learning KW - narrative texts KW - replication Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-224496 VL - 35 IS - 2 SP - 559 EP - 564 ER -