This research investigates the impact of goal-oriented visualization on machine learning knowl-edge acquisition, particularly exploring its poten-tial to address procrastination in academic settings. By examining participants with no prior machine learning experience, the study employs compara-tive and correlational measures to analyze quiz per-
formance, study times, and visualization practices. While encouraging trends are observed, the small sample size emphasizes the need for further re-search to definitively establish the impact of visu-alization on academic performance. The study ad-heres to ethical guidelines, ensuring participant pri-vacy and obtaining informed consent, contributing to responsible research practices.

The Artificial-Social-Agent (ASA) questionnaire is an instrument for rating Human-ASA interactions. The questionnaire was built to make evaluation results more comparable between different agents and to make findings more generalizable. The ASA questionnaire was designed in English, which limits its usage to people who have a firm grasp of the English language, so translating the questionnaire into different languages allows for the inclusion of other people and cultures, as well as opening up the possibility of comparing different cultures. A previous study performed a translation of the ASA questionnaire into Chinese, and this repeats a similar process by translating the questionnaire into Dutch. This research project employs a survey-based approach, utilizing the Prolific and Qualtrics platforms to collect valuable insights and responses from bilingual English and Dutch participants. Participants watch a video depicting an ASA-human interaction and then complete a questionnaire designed to assess their perceptions. The main research question focuses on identifying the cultural variations in the perceptions of ASAs. By addressing this question, this research contributes to the existing body of knowledge on ASAs and culture. The methodology involves translating and refining the questionnaire, followed by data collection and analysis using Intraclass correlation coefficients (ICCs) to measure agreement between the English and Dutch versions of the questionnaire. The final evaluation and analysis includes a deeper statistical analysis, and a comparison between Dutch-English bilingual participants, and mixed-English participants.