Academic Resources Recommender System (ARReS)
Theses and Dissertations

The Academic Resources Recommender System (ARReS) includes collection of Theses and Dissertations available in the Camarines Sur Polytechnic Colleges Library.

Thematic Analysis of CSPC Students’ Perceptions and Attitudes towards Online Class using Latent Dirichlet Allocation
Author: Lagyap, Jessabel A.; Nabor, Zion B.; Obrero, Jullius Fiel J.; Sinfuego, Ryan G.
2022 Computer Science

The topic model Latent Dirichlet Allocation (LDA) is used to classify text in a document to a certain subject. In connection with this, the study aims to develop a model that extracts themes from students’ perceptions and attitudes towards online classes, based on the data provided by the CSPC students amid pandemic. The respondents were limited to the students enrolled in the Camarines Sur Polytechnic Colleges. Questionnaires were utilized to collect data, and Google Forms was used to distribute it to the students. A qualitative research design was used in this study. To extract themes from the acquired data, an LDA-based model was utilized, which included an ensemble technique of data pre-processing, tokenization, and lemmatization. The researchers discovered that the LDA algorithm was effective in identifying topics or themes. The developed model was evaluated based on coherence score and perplexity, yielding a positive outcome. The representation of the topics shows the important keywords of each topic and shows good results that best describe the extracted topics about the students’ sentiments. The topic name and interpretation were both appropriate in explaining the meaning of each topic. As a result, the findings of this study could be used in the academe to improve the teaching and learning process of online classes.


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