Psychologische Forschungsmethoden für Designer Fabian Löwenbrück · Wintersemester 2018

In dem Kurs „Psychologische Forschungsmethoden für Designer“ unter Fabian Löwenbrück, wurden wir an verschiedene Themenbereiche der Statistik und Experimentellen Psychologie herangeführt. Basierend auf den gelernten Grundlagen wurde anschließend eine Umfrage erstellt, durchgeführt und ausgewertet.

Da die Umfrage auf englisch verfasst wurde um eine breitere und vielfältigere Menge an Menschen anzusprechen, ist die folgende Dokumentation im Englischen geschrieben.

Würde mich riesig freuen wenn du die Umfrage auch ausfüllst: https://goo.gl/forms/H3vBBLIMvVxnJLg73

Abstract

Techniques like screen time analysis have recently found their way in iOS, Android and their Applications. Still, the interplay between applications lacks behind. As presented in the following research, many users do not know about those analysis tools and are thus unaware of the interruptions their devices cause. Attention has become a scarce commodity. Name it „Flow“ or „Deep Work“ – our ability to stay committed to a task for more extended periods crippled by the endless stream of unconsidered notifications. How can findings from psychology and cognitive science be used by digital products, to achieve a holistic approach to better focus? How might the calendar, email and chat applications work together to accomplish a distraction-free work environment? How aware are users by the distractions their devices cause? In finding answers to those questions, I hope to gather information to eventually help in creating empowering products that enhance abilities and values of humans rather than corporations.

Formulating the Hypotheses

To phrase the right questions for the survey, I formulated the following directed hypotheses:

• People who structure their day, get less distracted by notifications.
• There is a positive correlation between the time of waking up and the level of perceived productiveness.
• People are unaware of the time they spend on their devices.
• People who structure their day, get less distracted by notifications.

The first part of the questionnaire is all about demographics, to see how age or gender might be related to some of the hypotheses. In the second block of questions, data on the behavior is gathered. How do people structure their days? How much time do they spend on their phones and how often do they get distracted? How likely are they a person of strong willpower and the ability to stay concentrated?

Statistical Evaluation

Important: the number of individuals is not sufficient to base a decision or finding on the data. The set for the following statistical analysis consists of only 24 persons. For this reason, I created a website which continually updates the visualizations after each new response is added to the set (submitting a new response on google forms updates the corresponding spreadsheet which in turn triggers a data update on the website).

Demographics

H0: People who structure their day, get less distracted by notifications.

Correlation between „You have no trouble getting back to work after You've been interrupted“ and „I set weekly daily goals“

Calculating Chi2:(using Rs Pearson's Chi-squared test) Since both answers use a linear scale of 1-5 to capture data, df = 4*4 = 16 X-squared = 18.091 p-value = 0.3186

=> As the p-value 0.3186 is greater than the .05 significance level, we do reject the null hypothesis that having no trouble getting back to work after an interruption is correlated to the habit of setting weekly or daily goals.

H0: People are unaware of the time they spend on their devices.

The mean value to the question of whether the data surprises was 3.217391. Thus, this hypothesis can be rejected for now.

However, it must be noted, that the gathered data on the screen usage part seems to be flawed. Many respondents mistook the asked for weekly total with the daily values.

Fazit

Ob Design Thinking oder Design Sprints, die Bedürfnisse und Wünsche von Menschne stehen immer im Mittelpunkt und zu Anfang eines jeden Design Prozesses. Interviews und resultierende Personas waren im bisherigen Studium das Mittel zum Zweck. Umfragen im größeren Format eher Seltenheit. Die erhobenen Informationen meist in Textform. Durch die Kombination von Statistik und Psychologie hat dieser Kurs ein anderes Licht auf das erheben von Daten geworfen. Daten nicht als Tabelle, als Vector, Integer oder Boolean; Daten als Sprache zwischen Designer und Nutzer, die es erlauben Verbindungen herzustellen die vorher nicht greifbar waren. Eine Sprache die es erlaubt Entscheidungen zu treffen die auf der Stimme eines jeden beruhen. Ich habe gelernt wie das Aufstellen von Hypothesen am Anfang des Prozesses dabei hilft einen Fragebogen zu erstellen der inhaltlich wertfolle Ergebnisse liefert. Wie unglaublich mächtig R und die vorhandenen Libraries sind, um statistische Auswertungen zu generieren (Correlation-Matrix, Chi-Squared, Corrplot ...). Abschließend kann ich sagen, dass mir der Kurs sehr große Freude bereitet, und meinen Designprozess um wertvolles Wissen und Methoden bereichert hat.