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This study aimed to develop and evaluate an instrument for measuring 21st-century workplace skills in on-the-job training (OJT) trainees. A literature review identified 20 key skills, which became the foundation of the instrument. Its validity and reliability were tested through a pilot study involving 20 OJT supervisors, employing methods like the item-level content validity index (I-CVI) and Cronbach's alpha. The results confirmed the instrument's effectiveness, indicating the need for further research with larger and more diverse samples to enhance its applicability. This tool is crucial in improving OJT programs by enabling supervisors to assess and support trainees more effectively. Additionally, it serves as a resource for employers and educators in appraising potential hires and graduates, and assists institutions in refining their curricula. [ABSTRACT FROM AUTHOR]

This research applies text mining techniques to examine sentiments and themes among Filipino students adjusting to full in-person classes after pandemic-driven flexible learning, focusing on their experiences during April to June 2023–a period usually marked by vacations due to intense heat. By applying the natural language toolkit (NLTK) for sentiment analysis and Scikit-learn for topic modeling, the study gathered data from Filipino students on their in-person class experiences during this unique calendar shift. Post data cleaning, NLTK was used for sentiment analysis and latent Dirichlet allocation for topic modeling. The findings indicate that the high temperatures adversely affected students, as evidenced by frequent references to terms such as “room,” “focus,” and “hard.” The study identified a mix of positive and negative sentiments and highlighted key issues like academic challenges and the learning environment’s impact. This study also offered insights into students’ coping strategies during extreme heat. These results stressed the importance of considering environmental factors in educational planning and provide actionable insights for institutions to enhance the in-person learning experience, particularly in challenging weather conditions. Moreover, this study demonstrates the effectiveness of sentiment analysis and topic modeling in understanding and unraveling student experiences in specific contexts. [ABSTRACT FROM AUTHOR]