How Can My Peers Become More Productive?

Developing The Idea:

Late last September I observed something interesting happening in my school. My peers, eighth grade students at Westmount Charter schools, were remarkably adept at procrastinating. They generally didn't get much work done. It was rare to see them sit down and work rather than play. However, in one particular classroom, let's call this classroom Class A, my peers were much more productive. It wasn't only me making this observation and another one of my teachers also saw this. I compared Class A to another class I'll call Class B. Class A had dim lighting, plants, and many aesthetic objects around the room. Class B on the other hand, although it still had dim lighting it had less aesthetic objects around the room, and many, once asked, described it to have a different feel entirely. I hypothesised that one's environment had an impact on their productivity.
However, this is something already researched and studied on. Taking this into consideration I decided that rather than trying to prove that your environment impacts you, I decided to find a way to help my peers manipulate this to their advantage. 

Making It A Reality:

- Creating a survey
- Creating an AI
- Limitations within my own knowledge
- The result

To find a way to make my peers more productive I first needed to figure out what stimuli they believe help them the most. To get this data I created an fully anonymous online survey which got ample approval from the administration. Questions were asked in a statement-like manner such as 'You work best when it's cloudy,' and the possible responses were in a spectrum: Strongly Agree, Agree, Neutral, Disagree and Strongly Disagree. This survey is important because not all people are the same. The way they grew up and the people they are impact how different stimuli draw reactions out of them.

With this data I had planned to create an assessment with a Supervised Learning, Machine Learning Algorithm, a Decision Tree Algorithm. The algorithm will go over the data and find patterns. Using those pattersn it will figure out, based on modifications the person can do when doing the assessment, what patterns apply to them and give a suggestion on a recommended stimuli and/or environment. However, I ran into several coding problems that were out of my current capabilities to fix.

Rather than using an AI that will spit out what type of environment you should use, I did something more reachable with my current capabilities and instead used the AI to make a list. This list has different questions such as if you worked best on cloudy days. Then under the question it would say that if you do like working on cloudy days you would also enjoy 'X' stimuli. and if you don't you should stay away from 'Y' stimuli. 

Getting this project done took correspondence with my principal, days of research and youtube tutorials, and a substantial amount of creativity.

Sources of Error:

The survey itself was constructed in a specific manner. Some biases may have come in during the making of this project such as 'Social Desirability Bias,' and 'Extreme Response Bias,' and 'Neutral Responding Bias,' When creating the survey I took time to make sure that the participants were aware that they wouldn't be judged for the answers and that the results wouldn't be able to be tied back to them. The survey also didn't have an equal portion of ethnicities and genders involved. 69.5% of the participants were Asian and 60.7% of the participants were male. Only 1.5% of the participants were African-Canadian, and 2.3% were Latino/Latinx. 

Variables:

Controlled

• -  All surveys were done on laptops

• - The questions are all the same

• - All teachers were given the same instructions on how to introduce the survey

Manipulated

• - The several different responses

Responding

• - The answers

Results:

The AI I initially tried to make had low accuracy. The AI wasn't able to easily find out what attributes someone would enjoy and someone wouldn't enjoy. This isn't too surprising as it's incredibly hard even for humans to try and predict human likes and dislikes from simple survey questions. What the AI was able to find was correlation. Although there wasn't much direct correlation between variables, the program. found factors that seemed to relate to each other. For example, people who were positive also were often more confident. These correlations guided me into creating a list that would allow people to simply go through it and have an idea on what environment they should create for themselves.

Conclusion:

One's environment can impact how they work and there is a correlation between what type of person you are and what environments best suit you. This information can be used in various different places such as schools, offices, and even your own home to help people become more productive. If employees want a four day work week, then they should use this project to maximise the amount of work they get done whilst at work. My peers are always being told to be more productive but they aren’t given an effective way to do so. This will be a part of the solution. My project, although it may not look impressive, is a result of hard work and grit, and I'm proud to show it off at the Calgary Youth Science Fair.

Full Citation List as of March 9th 2024:

Common types of survey bias and how to avoid them. SurveyMonkey. (n.d.). https://www.surveymonkey.com/mp/how-to-avoid-common-types-survey-bias/ 

Chung, L. (2024, February 1). Avoiding biased questions: 7 examples of bad survey questions. Delighted. https://delighted.com/blog/biased-questions-examples-bad-survey-questions#:~:text=A%20survey%20question%20is%20biased,for%20customers%20to%20answer%20honestly. 

Kendra Cherry. (2023, December 10). The arousal theory and our individual behaviors. Verywell Mind. https://www.verywellmind.com/the-arousal-theory-of-motivation-2795380 

DeFranco, T. (n.d.). Principles of Management. Lumen. https://courses.lumenlearning.com/atd-tc3-management/chapter/need-based-theories-of-motivation/#:~:text=There%20are%20four%20major%20theories,and%20McClelland’s%20acquired%20needs%20theory. 

Employee productivity statistics you need to know in 2023 - Oak Engage. Oak Digital Workplace. (2023, April 20). https://www.oak.com/blog/employee-productivity-statistics/ 

Peaton, K., & -Marie, D. (2022, June 9). Time of day and student productivity in middle school and high school. The Journalist’s Resource. https://journalistsresource.org/education/time-day-school-schedule-productive/ 

Grafwallner, P. (2022, October 18). Making sure students’ struggles are productive. Edutopia. https://www.edutopia.org/article/making-sure-students-struggles-are-productive/ 

Quixy Editorial Team. (2024, February 2). 50+ powerful employee productivity statistics that will make you think. Quixy. https://quixy.com/blog/employee-productivity-statistics/#:~:text=General%20Employee%20Productivity%20Statistics&text=The%20typical%20employee%20is%20only,and%2023%20minutes%20per%20day. 

Kulach, K. (2023, October 30). How productive are average office workers? the truth can surprise you!. Medium. https://medium.com/the-shortform/how-productive-are-average-office-workers-the-truth-can-surprise-you-2e9ec674c345 

Marmaras, N., Chapanis, A., Clark, A., Dowell, J., Edholm, O. G., Ehrlich, K., Suri, J. F., Girault, P., Green, B., Howell, W. C., Jastrzebowski, W., & Long, J. (2000, November 27). Fundamentals of Ergonomics in theory and Practice. Applied Ergonomics. https://www.sciencedirect.com/science/article/abs/pii/S000368700000034X 

Workplace ergonomic assessments - home/office assessment & training. Work Wellness. (2021, December 1). https://www.workwellness.com/ergonomics-assessments/ 

Lowe, B. D., Dempsey, P. G., & Jones, E. M. (n.d.). Ergonomics assessment methods used by Ergonomics Professionals. Applied ergonomics. https://pubmed.ncbi.nlm.nih.gov/31422255/ 

(2023, March 14). How do you design and conduct ergonomic surveys and interviews?. How to Design and Conduct Ergonomic Surveys and Interviews. https://www.linkedin.com/advice/0/how-do-you-design-conduct-ergonomic-surveys-interviews 

Northern Illinois University. (n.d.). Ergonomic assessment questionnaire: Environmental health and safety. Ergonomic Assessment Questionnaire. https://www.niu.edu/ehs/resources/ergonomic-assessment.shtml 

How to perform an ergonomic assessment in the Workplace. Proactive MD. (2019, August 2). https://proactive-md.com/how-to-perform-an-ergonomic-assessment-in-the-workplace/ 

Ponto, J. (2015, March 1). Understanding and evaluating survey research. Understanding and Evaluating Survey Research. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4601897/ 

National Institutes of Health. (n.d.). Computer Workstation Ergonomics: Self-assessment checklist. https://ors.od.nih.gov/sr/dohs/Documents/checklist-ergonomics-computer-workstation-self-assessment.pdf 

Influence of indoor environmental quality on work productivity in green ... Research Gate. (n.d.). https://www.researchgate.net/profile/Masoud_Esfandiari/publication/316452092_Influence_of_Indoor_Environmental_Quality_on_Work_Productivity_in_Green_Office_Buildings_A_Review/links/58fee7ef0f7e9bcf65442881/Influence-of-Indoor-Environmental-Quality-on-Work-Productivity-in-Green-Office-Buildings-A-Review.pdf 

Python user input. w3schools.com. (n.d.). https://www.w3schools.com/python/python_user_input.asp 

Byrd, B. (2021, April 2). Creating a multiple choice quiz in python: Terminal. Medium. https://brockbyrdd.medium.com/creating-a-multiple-choice-quiz-in-python-terminal-1c46123b86d5 

“Hailstone 13.” (2014). When making a very simple multiple choice story in python, can I call a line to repeat if neither of the options are selected?. Stack Overflow. https://stackoverflow.com/questions/21082037/when-making-a-very-simple-multiple-choice-story-in-python-can-i-call-a-line-to 

Rohit. (2023, August 7). How to make a multiple-choice question in Python: Example code. Tutorial. https://tutorial.eyehunts.com/python/how-to-make-a-multiple-choice-question-in-python-example-code/#google_vignette 

Devaney, R. (n.d.). Tutorial: User input in python. CodeHS. https://codehs.com/tutorial/rachel/user-input-in-python 

Courtney, P. (2015, January 7). Cognitive Systems platforms using Open source. Performance Evaluation and Benchmarking of Intelligent Systems. https://www.academia.edu/10058740/Cognitive_Systems_Platforms_using_Open_Source 

Chaves, R. (2020, January 5). Building Akinator with python using Bayes theorem. Medium. https://medium.com/analytics-vidhya/building-akinator-with-python-using-bayes-theorem-216253c98daa 

 Amit. (2012, November 30). What kind of algorithm is behind the Akinator Game?. Stack Overflow. https://stackoverflow.com/questions/13649646/what-kind-of-algorithm-is-behind-the-akinator-game 

Akinator Engine. GitHub. (2016). https://github.com/ukushu/AkinatorEngine/tree/master/Akinator 

Breuss, M., Aldren, Arne, G., Kate, & Philipp. (2023, February 24). Chatterbot: Build a chatbot with python. Real Python. https://realpython.com/build-a-chatbot-python-chatterbot/ 

Loebach, J., Rakow, D. A., Meredith, G., & Shepley, M. M. (2022). Time outdoors in nature to improve staff well-being: Examining changes in behaviors and motivations among university staff in the use of natural outdoor environments since the emergence of the COVID-19 pandemic. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.869122 

Vries, S., Hermans, T., & Langers, F. (2023). Effects of indoor plants on office workers: A Field Study in multiple Dutch organizations. Frontiers in Psychology, 14. https://doi.org/10.3389/fpsyg.2023.1196106 

Russell, B. (2022, October 29). New study highlights the benefits of having plants in the workplace. IFA Magazine. https://ifamagazine.com/new-study-highlights-the-benefits-of-having-plants-in-the-workplace/#:~:text=The%20first%2Dever%20study%20on,productivity%20increased%20across%20the%20board. 

Simplilearn. (2023, November 7). The best guide on how to implement decision tree in Python. Simplilearn.com. https://www.simplilearn.com/tutorials/machine-learning-tutorial/decision-tree-in-python 

Li, S. (2022, July 21). Best practice to calculate and interpret model feature importance. Medium. https://towardsdatascience.com/best-practice-to-calculate-and-interpret-model-feature-importance-14f0e11ee660 

Pinterest. (n.d.). https://www.pinterest.ca/ 

U.S. Bureau of Labor Statistics. (n.d.). What is productivity?. U.S. Bureau of Labor Statistics. https://www.bls.gov/k12/productivity-101/content/what-is-productivity/home.htm 

Team, T. A. (2023, January 6). Decision trees explained with a practical example. https://towardsai.net/p/programming/decision-trees-explained-with-a-practical-example-fe47872d3b53 

22 productivity tips for college students: JWU CPS. JWU College of Professional Studies. (2022, June 30). https://online.jwu.edu/blog/22-productivity-tips-college-students/

Thurrott, S. (2023, March 9). 9 simple productivity tips for college students. Azusa Pacific University. https://www.apu.edu/articles/9-simple-productivity-tips-for-college-students/

Whilst completing the project I got help and guidance from my mentors, Tim and Irada, who guided me though finding an objective, finding sources for research, and creating my code. My teachers and my principal were kind enough to allow me to spread the survey across my school, so I must thank them as well. Finally I must thank my brother, my dad, and my mum, who gave me suggestions on how to improve and add depth to my work.