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184 Pages·2016·10.87 MB·English
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An Integrative Model to Predict Scholastic Performance: Fluid Intelligence, Broad Personality Traits, Narrow Traits, and Their Interplay Dissertation zur Erlangung des akademischen Grades Dr. rer. Nat. im Fach Psychologie eingereicht an der Mathematisch-Naturwissenschaftlichen Fakultät II der Humboldt-Universität zu Berlin von Dipl. Psych. Jing Zhang Präsident/Präsidentin der Humboldt-Universität zu Berlin Prof. Dr.-Ing. Dr. Sabine Kunst Dekan der Mathematisch-Naturwissenschaftlichen Fakultät II: Gutachter/Gutachterin 1. Prof. Dr. Matthias Ziegler 2. Prof. Dr. Martin Bäckström 3. Prof. Dr. Ricarda Steinmayr Tag der Verteidigung: 01.07. 2016 Eidesstattliche Erklärungen Hiermit versichere ich des Eides statt, dass • Ich die vorliegende Dissertation mit dem Titel „An Integrative Model to Predict Scholastic Performance: Fluid Intelligence, Broad Personality Traits, Narrow Traits, and Their Interplay“ selbständig und ohne unerlaubte Hilfe angefertigt habe. • Es sich um die Ersteinreichung der vorliegenden Arbeit als Dissertation handelt. • Ich die Promotionsordnung der Humboldt-Universität zu Berlin zur Kenntnis. Berlin, den 20.01.2016 Jing Zhang I Table of Contents Acknowledgements .................................................................................................................. III Abstract .................................................................................................................................... III Zusammenfassung ................................................................................................................. VII General Introduction .................................................................................................................. 1 Paper 1 ..................................................................................................................................... 30 Paper 2 ..................................................................................................................................... 63 Paper 3 ................................................................................................................................... 111 General Discussion ................................................................................................................ 157 Pulications and Conference Contributions ............................................................................ 173 II III Acknowledgements It was a challenging but exciting adventure when I prepared this dissertation. I could not have accomplished it without help. Therefore, I would like to express my gratitude to everyone who had helped me. I give special thanks to my supervisor, Prof. Dr. Matthias Ziegler. I really appreciate his prompt response to my emails, his invaluable and constructive feedbacks, and his professional supervision for every kind of details. I am so lucky to be supervised by you- Your patience and warm support have been encouraging me constantly and your wisdom and research attitude have trained and prepared me to be a potential scholar for the future. Thank you again for giving me such wonderful and unforgettable experiences. I also would like to thank Prof. Dr. Martin Bäckström and Prof. Dr. Ricarda Steinmayr to review my dissertation. Their detailed feedbacks on drafts of the dissertation and helpful suggestions encouraged me to improve my dissertation all the way to its accomplishment. I especially thank my lovely colleagues in the research group of Psychological Diagnostics. I appreciate the help from Anja, Doreen, Ulrike, Steffi, Kai, Isabel, and Matthias when I was preparing the dissertation. I would like to thank John Rauthmann who reviewed my dissertation and made valuable suggestions. Sabine, a very kind and beautiful woman, understood the troubles and joys that I had. In addition, my other Chinese friends, whose companion really encourages me throughout the period of research and writing. I would like to dedicate the dissertation to my parents. Without their hard work and sacrifice in the past, I could not be able to enter a university, not to mention coming to Germany for a doctoral degree. My old brother and two sisters always trust me and cheer me up. I am grateful for being born and growing up in such a happy family with tons of songs and laughter. Last, I want to give my many thanks to China Scholarship Council for supporting me to pursue my PhD degree in Humboldt-Universität zu Berlin. There are also too many people who I want to thank but cannot name them here. I bless you all the best in the future. Berlin, den 20.01. 2016 IV V Abstract This dissertation deals with the prediction of scholastic performance in Chinese culture. All in all, three studies were conducted. Two studies focus on personality and test the Big Five Narrow Trait Model (B5NT) which is one of theoretical corner stones of this thesis. The third study includes cognitive ability and focuses on the interplay between personality and ability predicting scholastic performance. Thus, the thesis uses the constructs of fluid intelligence (Gf), broad personality traits (Big Five), narrow personality traits (i.e., self-beliefs and learning approaches), and their complex interplay (moderation and mediation processes) as predictors of scholastic performance. Following a general introduction summarizing the theoretical foundations as well as outlining the derivation of the B5NT, three papers are presented. In the context of Chinese secondary school students, Paper 1 examined the predictive power of figural reasoning as an indicator of Gf and personality traits on school grades in three subjects (i.e., Mathematics, Chinese, and English), and further investigated their potential interactions. Paper 2 integrated the findings of Paper 1 with the aforementioned B5NT. Within the study, the B5NT is empirically tested and compared to an alternative model proposed in earlier work, the Double Mediation model [DM]. Self-beliefs and learning approaches were considered as relevant mediators within those analyses. In this cross-sectional study, the B5NT model was strongly supported, whereas the DM model did not find strong empirical support. In order to empirically verify the underlying processes from a longitudinal perspective, Paper 3 expanded on the B5NT related findings in a three-wave longitudinal panel design. The findings supported the B5NT model and further warranted a revision model in which reciprocal effects from performance to big traits are suggested. Thus, the presented thesis provides a theoretical model explaining the influence of the Big Five on scholastic performance. Moreover, empirical support for the proposed model from cross-sectional and longitudinal data was found. Finally, integrating interactions with cognitive ability rounds off the perspective. VI

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