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• Testing the Sametest-effect in a BSc-level Business Communication Course Examination

  10-15

  András István Kun

  János Farkas

  Csilla Juhász

  Views:

  56

  Using secondary data, we empirically examine two biasing effects that may arise in the written evaluation of large groups of students. Suppose the students take the examination in consecutive groups, and we wish to avoid the distortion caused by tests of different difficulty. In that case, we can decide to use the same examination questions. However, the danger of the "same test effect" arises, according to which the group writing later can perform better if it receives information from the examinees in the previous round. Using the same examination tests cannot be recommended if that effect is significant. Another related potential phenomenon is the "revealed sameness effect". Accordingly, if the examinees are aware of the repetition of the questions, it significantly increases the scores of the following group. We tested these phenomena using the data of a three-round written examination. A previously published analysis of a larger sample found that the "same test effect" can be expected if the students decide in which round they take the examination. Since it was possible to freely register for the examination rounds for the assessment analyzed in this study, we assume that the "same test effect" will be significant. Based on the literature, we also expected that the "revealed sameness effect" would occur in the third round. The performed linear regression analysis (N=77) only found some weak evidence for the 'revealed sameness effect' but not for the 'same test effect'.

• A Literature Review: Artificial Intelligence Impact on the Recruitment Process

  108-119

  JihaD FraiJ

  Várallyai László

  Views:

  9080

  This paper aim is to review the implementation of artificial intelligence (AI) in the Human Resources Management (HRM) recruitment processes. A systematic review was adopted in which academic papers, magazine articles as well as high rated websites with related fields were checked. The findings of this study should contribute to the general understanding of the impact of AI on the HRM recruitment process. It was impossible to track and cover all topics related to the subject. However, the research methodology used seems to be reasonable and acceptable as it covers a good number of articles which are related to the core subject area. The results and findings were almost clear that using AI is advantages in the area of recruitment as technology can serve best in this area. Moreover, time, efforts, and boring daily tasks are transformed to be computerized which makes a good space for humans to focus on more important subjects related to boosting performance and development. Acquiring automation and cognitive insights as well as cognitive engagement in the recruitment process would make it possible for systems to work similarly to the human brain in terms of data analysis and the ability to build an effective systematic engagement to process the data in an unbiased, efficient and fast way.