In recent years, Natural Language Processing (NLP) models such as Generative Pre-trained Transformer 3 (GPT-3) have shown remarkable improvements in various language-related tasks, including machine translation. However, most studies that have evaluated the performance of NLP models in translation tasks have focused on general-purpose text, leaving the evaluation of their effectiveness in handling specialized text to be relatively unexplored. Therefore, this study aimed to evaluate the effectiveness of GPT-3 in translating specialized Arabic text to English and compare its performance to human translation. To achieve this goal, the study selected ten chapters from a specialized book written in Arabic, covering topics in specialized religious context. The chapters were translated by a professional human translator and by GPT-3 using its translation Application Programming Interface. The translation performance of GPT-3 to was compared to human translation using qualitative measures, specifically the Direct Assessment method. Additionally, the translations were evaluated using two different evaluation metrics, Bidirectional Encoder Representations from Transformers (BERT) score and Recall-Oriented Understudy for Gisting Evaluation (ROUGE) metric, which measure the similarity between the translated text and the reference text.The qualitative results show that GPT produced generally understandable translations but failed to capture nuances and cultural context. On the other hand, the quantitative results of the study showed that GPT-3 was able to achieve a relatively high level of accuracy in translating specialized religious text, with comparable scores to human translations in some cases. Specifically, the BERT score of GPT-3 translations was 0.83. The study also found that the Rouge score failed to fully reflect the capabilities of GPT-3 in translating specialized text.Overall, the findings of this study suggest that GPT-3 has promising potential as a translation tool for specialized religious text, but further research is needed to improve its capabilities and address its limitations.
Having well-prepared engineering graduates for the workplace has been of great importance in the last few decades (Warsame, 2017;Anastasiu, Anastasiu, Dumitran, Crizboi, Holmaghi, & Roman, 2017;Pan, 2014). However, engineering graduates and trainees of a private Lebanese university seem to face difficulties during their training and in the workplace. Furthermore, little research has been done on this university's engineering educational program. Therefore, the aim of this research was to investigate the extent to which the engineering educational program at a private Lebanese university is preparing its students for the workplace. A mixed-methods design and different data collection instruments were used in this research study. A purposive sample of a hundred graduates and trainees of different engineering majors were surveyed. Additionally, six personal interviews were held with three graduates and three trainees of diverse engineering majors. The quantitative data collected were analyzed using Excel while the qualitative data were thematically analyzed. The collected quantitative and qualitative data were triangulated, and a lot of commonalities between them were detected. In fact, the findings revealed that most respondents reported that neither their lab nor their theoretical courses fully prepared them for the workplace. Nevertheless, most participants stated that their internship experience enhanced both their practical and soft skills. Appropriate recommendations such as encouraging instructors to include real-life case studies to enhance students' problem-solving skills and adding up-to-date equipment to the labs, were suggested to improve the engineering educational program at this private Lebanese university so that it can help its engineering graduates better survive in the workplace.
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