| Course | PSY-3220 Research in Experimental Psychology |
|---|---|
| Module | Module 4 |
| Paper type | Research methods paper: observational and survey methods |
| Length | About 1,000 words, 6 pages |
| Format | APA 7 student paper |
| School | Thomas Edison State University |
| Program | Bachelor of Arts in Psychology |
| Updated | October 2026 |
Free sample paper for PSY 3220 Module 4
What People Say and What Phones Record: Designing a Survey of Study Habits
Student Name
Bachelor of Arts in Psychology, Thomas Edison State University
PSY-3220: Research in Experimental Psychology
Mentor Name
Month Day, Year
What People Say and What Phones Record: Designing a Survey of Study Habits
Introduction
Before running my experiment, I want to know how adult online learners actually study: where, when and with their phones in which places. A survey can describe these habits across many people, and observational data can check whether what people report matches what they do. This paper explains the strengths and weaknesses of survey and observational methods and describes the survey I designed.
Descriptive Research
Observational and survey research describe behavior and relationships as they occur, without manipulating variables. Naturalistic observation records behavior in everyday settings; systematic observation uses defined coding categories; surveys ask people to report on their own behavior, attitudes and experiences. These methods can describe how common a behavior is and whether variables are related, but correlations alone cannot show cause and effect.
How Respondents Answer
Krosnick (1991) proposed that answering survey questions well requires effort: understanding the question, searching memory, forming a judgment and mapping it onto the response options. When respondents are tired, unmotivated or face difficult questions, they may satisfice, giving an answer that seems acceptable rather than the best answer. Mild forms include settling on the first plausible choice or simply agreeing with whatever a statement says. Strong satisficing includes saying "don't know," giving the same answer to every item in a grid or answering randomly. Satisficing is more likely when the task is difficult, the respondent's ability is limited and motivation is low.
Common Method Bias
Podsakoff et al. (2003) reviewed evidence that when the same respondents report both predictor and outcome variables, using the same format at the same time, relationships between variables can be inflated or deflated by the method itself. Sources include a desire to appear consistent, social desirability, mood at the time of response and similar item wording. They recommend procedural remedies, such as obtaining predictor and outcome from different sources, separating measurement in time, protecting anonymity, varying response formats and reducing ambiguity, along with statistical checks.
Do People Know How Much They Use Their Phones?
Andrews et al. (2015) asked young adults to estimate how much they used their smartphones and compared the estimates with data recorded by an app on their phones. Participants used their phones far more than they estimated, about twice as often, checking them many times a day in brief sessions. Estimates of total time were only weakly related to actual use. The authors concluded that self-report is a poor substitute for recorded behavior when studying technology use.
| Source | Key point | Application to my survey |
|---|---|---|
| Krosnick (1991) | Respondents satisfice when questions demand too much | Short, specific, concrete items |
| Podsakoff et al. (2003) | Same-source, same-time measures inflate relationships | Use recorded data for phone use |
| Andrews et al. (2015) | Estimated phone use differed sharply from recorded use | Do not rely on self-reported phone time |
My Survey Design
The survey will go to students in two online courses, with instructor permission. To limit satisficing, it will be short, about ten minutes, with concrete questions about the past week rather than general habits: "On how many days last week did you study for at least 30 minutes?" and "During your longest study session last week, where was your phone?" with specific options. Agreement grids will be kept short and include reverse-worded items. "Don't know" will be offered only where respondents truly might not know.
Recorded Phone Use
Following Andrews and colleagues, I will not ask participants to estimate their screen time. Instead, participants who agree will copy the daily screen-time figures and number of pickups that their phone's settings already record for the past week, a simple form of observational data. This also addresses Podsakoff and colleagues' concern, since phone use and self-reported study outcomes will come from different sources.
Observational Component
With consent, a subset of participants will complete a 30-minute study session on video, with only the desk and hands in view, coded for how often they look at or touch their phone. Two coders will use defined categories and their agreement will be checked, a test of interrater reliability.
What the Survey Can and Cannot Show
The survey can show how common different phone locations are while studying and whether they relate to self-reported focus or grades. It cannot show that phone location causes differences, since people who keep phones nearby may differ in other ways. That causal question belongs to the experiment.
Sampling
A survey describes only the people who answer it. Sending the survey to two courses will reach students who are active enough to read course announcements, and the people who reply may be more conscientious than those who ignore it. I will report the response rate and compare respondents with course enrollment figures on age and gender to judge how representative the sample is.
Privacy
Screen-time data reveal personal habits. Participants will enter only totals, not app-by-app details, and the video observation will exclude faces and screens. All data will be stored with code numbers rather than names.
Turning Observations Into Data
The coding scheme will define each behavior precisely: a glance is any head or eye movement toward the phone lasting at least one second, and a touch is any hand contact. Coders will practice on two recordings not used in the study, discuss disagreements and then code independently, with agreement measured on a fifth of the sessions.
Linking Survey and Experiment
The survey will also help recruit experiment participants and describe how typical the experiment's conditions are, for example how many learners actually study with phones on the desk.
Limits
Course-based samples may not represent all adult learners. Screen-time features differ across phone models, and video observation may change behavior.
Conclusion
Krosnick showed why demanding questions invite shortcuts, Podsakoff and colleagues showed how shared methods distort relationships and Andrews and colleagues showed that people misjudge their own phone use. A short, concrete survey, recorded screen-time data and a coded observation give my study a realistic picture of how adult learners study with their phones.
References
Andrews, S., Ellis, D. A., Shaw, H., & Piwek, L. (2015). Beyond self-report: Tools to compare estimated and real-world smartphone use. PLoS ONE, 10(10), Article e0139004. https://doi.org/10.1371/journal.pone.0139004
Krosnick, J. A. (1991). Response strategies for coping with the cognitive demands of attitude measures in surveys. Applied Cognitive Psychology, 5(3), 213-236. https://doi.org/10.1002/acp.2350050305
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879-903. https://doi.org/10.1037/0021-9010.88.5.879
PSY 3220 Module 4 instructions, in plain terms
Observational and Survey Research is Module 4 in TESU's public syllabus for PSY-3220. Explain the purposes and limits of descriptive research, then use evidence on how respondents answer questions and on method bias to design a short survey related to your research question. Show sample items and explain how they reduce satisficing and bias. Add an observational or behavioral measure that checks self-report, describe how it will be coded reliably and state clearly what your descriptive data can and cannot show about cause and effect. Address sampling and privacy. Some sections ask for a naturalistic observation study instead of a survey. Check whether the full questionnaire should be attached.
Inside the PSY 3220 Module 4 example
Kendra Lopez, the invented TESU psychology student, designs a survey of adult online learners' study habits to give her experiment context. Descriptive methods are explained, then Krosnick's satisficing theory, Podsakoff and colleagues' common method bias and Andrews and colleagues' finding that people misjudge their phone use are summarized and linked to design decisions in a table. Her survey uses short, concrete, past-week items, collects phone-recorded screen time instead of estimates and adds a coded video observation with interrater checks. Sections on what the data can show, limits and a conclusion follow. Sections on sampling and response rate and on protecting privacy in screen-time and video data come before the limits. A coding scheme with practice sessions supports reliable observation.
Where the marks sit in the PSY 3220 Module 4 rubric
Survey and observation papers earn credit when they explain what descriptive methods can and cannot show and then design an instrument shaped by evidence on how people answer. Readers look for sample items that are concrete and specific, for steps that reduce satisficing and common method bias and for a behavioral or recorded measure that checks self-report. Describing coding categories and an interrater reliability check shows observational rigor. A clear statement that correlations cannot establish cause, and attention to sampling and privacy, show sound research judgment. Reporting response rates and protecting privacy in recorded data show careful descriptive research. Linking the survey to the experiment shows a coherent research program.
Common PSY 3220 Module 4 mistakes, and how to avoid them
Survey papers often list question types without showing actual items or explaining how they reduce bias. Write sample questions about specific recent behavior, keep the survey short and avoid long agreement grids. Use a recorded or observed measure where self-report is known to be inaccurate, and describe how observers will code behavior reliably. State what the data cannot show. Send the survey prompt along with your topic; a free first draft of the questionnaire comes back to you. Report how you will judge whether respondents represent the population, and how you will protect their data. Describe your coding scheme precisely. Coding observations with clear rules makes the descriptive data trustworthy.
Write yours, or have the desk draft it
This paper is an original model document written by our desk, not a submitted student paper and not an official Thomas Edison State University document. Read it for the moves, then write your own to the instructions in your classroom. If you want one built to your exact prompt and rubric, the first custom sample is free and arrives in 24 to 48 hours.
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PSY 3220 Module 4 questions, answered
Where can I find a free PSY 3220 Module 4 sample paper?
The survey and observation paper, from satisficing to recorded screen time, is posted here.
What is satisficing in surveys?
Krosnick's term for respondents giving acceptable rather than optimal answers when questions demand too much effort.
What is common method bias?
Podsakoff and colleagues showed measuring predictors and outcomes with the same method and source can distort relationships.
Do people accurately report their phone use?
Andrews and colleagues found young adults used their phones about twice as often as they estimated.
Can surveys show cause and effect?
No; they describe behavior and relationships, but correlations cannot establish causation.