Impact of Part-time Job on Academic Performance of 3rd Year College Student in Quezon City University
Bibliographic record
Abstract
Nothing ever comes to one that is worth having, except because of hard work. (Booker T. Washington) Education is the foundation of all things in this world. It helps our society to become more productive, responsible, and competitive both academical- ly and non-academically. It is important because with an education we succeed to the trials and become a successful in our life. Working through college would not cover all of a student’s education expenses. It can lighten the debt burden, though, and pay off in other ways good news for the growing number of students who work while attend- ing school. Education is a process of receiving or giving systematic instruction at a school or university. There is a lot of bad and good impact of having part time jobs. Ac- cording to Fortenbury (2013), this day most college students are working according to the findings by City and seventeen magazines from a 2013 survey nearly four out of five or almost 80 percent of college students are working clock in a workload of 19 hours per week. The purpose of this study is to encourage our beloved students to continue their lives. Even though it’s hard for to them do some necessary things be- cause of their trials in life, especially their financial problem. This study also helps our beloved students to improve their study habits, to how they handle their studies while having a part-time job. The researchers used the Quantitative Method of research. Ac- cording to Babbie (2010), “Quantitative method emphasizes on objective measure- ments and numerical analysis of data collected through polls, questionnaire, or surveys. The researchers used purposive sampling. According to Ashley Crossman (2017), pur- posive sampling is a selection based on the characteristics of the population and the objective of the study. Purposive sampling is also known as judgmental, selective, or subjective sampling. The researchers present the initial draft of the questionnaire to our thesis adviser. After the comments, corrections, and suggestions, the researchers pre- pared an edited and correct draft for our adviser. The question is to develop and meas- ure the specific aspect of the assumption in the study. The study shown in the data that most of the respondents have the aged of 22 years old. Furthermore, it is shown in the data that most of the respondents are Female BSIE students. It is also shown in the da- ta that most of the respondents spent 6-10 hours working in their part-time job at a Fast-Food Chain restaurant. Most of the respondents have an average grade of 77 – 79/2.75 even though they have a part-time job. It is shown in the data that most of the respondents can manage their time even when they have a part-time job. It denotes that there is a significant relationship between the problem encountered by the re- spondents and their General Ave.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".