Anmerkungen:
In: International Conference on Business Planning and Practice Management, 2022
Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments 2022 erstellt
Beschreibung:
Universities are tasked with the job of improving students' talents in a broad number of fields; one of these fields is preparing students for their future academic efforts. The pupils' histories, the locations of their houses, the resources they access possible to them, their temperaments, and other circumstances will all play a role in determining how successful their future academic attempts will be. It is the job of educational institutions like universities to develop students' abilities across a broad array of fields. The goal of this research is to evaluate whether or not specific personality features may serve as reliable predictors of the possibility of future academic achievement for a psychology Ph.D. candidate. Not only was there an emphasis put on descriptive writing, but also on analytical writing in this specific piece of writing. The population consisted of all of the senior students who were registered in the Psychology and Education department. Following this, 86 of these students were chosen at random by a standard procedure of random selection. The prototype questionnaire and the NEO short form personality traits questionnaire had reliability coefficients of 0.93, while the NEO short form questionnaire's reliability coefficient was equal to 0.96. Variables in the area of Futures Studies, such as extroversion, openness, and compatibility, seem to have associations with one another, but characteristics in the field of Futures Studies, such as neuroticism and conscience, do not seem to have any associations with one another (because the significance level is smaller than 0.05). The findings of the structural equation modeling and Amos software tests provided support for some of the research hypotheses, and the high values of the goodness fit indices (GFI =0.92 and AGFI =0.94) indicate that the model is well-suited to the data