Method trend estimation

Is my salary rising as fast as my rent? How to interpret line charts correctly

Challenges in trend communication

Why is it relevant to communicate trends?

The aim is for the consumer to be able to make (better) decisions. They need to know precise facts and figures - the so-called evidence - in order to weigh options against each other and better assess risks. This enables them to make informed decisions. Trends that are described statistically are not only relevant for using punctual data as a basis for decision-making. Rather, trends provide a context that may contradict the conclusions drawn from point observations. In addition, nonlinear relationships such as exponential growth or instabilities over time must be communicated in their development, otherwise their effects can hardly be estimated.

 

Why is it problematic to communicate trends?

If you want to communicate trends, you face a number of challenges:

  • Which presentation format is comprehensible for consumers?
  • How can consumers memorise trends better?
  • How can the relevant context be addressed in a visual representation?
  • And how can trends be presented in an appealing way so that consumers also enjoy engaging with them?
What is a suitable scientific approach?

Interactivity can be used to nurture interest. It should be used in an economical, targeted and coherent way with the necessary controls and content. Ultimately, this is achieved when consumers draw the data themselves.

It has been shown that learners better understand the explanations that they draw (Ainsworth et al., 2011; Hall et al., 1997). When consumers predict trends using a line chart as a first step, they can better internalise the actual development of data they are not familiar with (Kim et al., 2017). However, the reflections that accompany the drawing (explanatory attempts) are more decisive for improved numerical estimations than the drawing itself.

Since this is a playful transfer of knowledge from the adult world (Barth, 2018), this interest can be reinforced among certain consumers by addressing the motive of power (competition, status) (Sailer et al., 2014) by comparing their own estimates with those of others. The reduced design refrains from presenting further details that motivate interest. These could contradict the actual goal, particularly if they do not fit harmoniously into the content, or even distract or simply lead to confusion (Eitel & Kühl, 2019).

The technical model was a visualisation by the New York Times (Aisch et al., 2015).

Recommended literature on methodological basics
  • Ainsworth, S., Prain, V., & Tytler, R. (2011). Drawing to learn in science. Science, 333(6046), 1096–1097.
  • Aisch, G., Cox, A., & Quealy, K. (2015). You draw it: How family income predicts children’s college chances. The New York Times, 28. Mai, http://nyti.ms/1ezbuWY.
  • Barth, R. (2018). Möglichkeiten der Nutzung von Game Design Prinzipien in der Erwachsenenbildung. digital. innovativ|# digiPH, 109–118.
  • Eitel, A., & Kühl, T. (2019). Harmful or helpful to learning? The impact of seductive details on learning and instruction. Applied Cognitive Psychology, 33(1), 3–8.
  • Hall, V. C., Bailey, J., & Tillman, C. (1997). Can student-generated illustrations be worth ten thousand words? Journal of Educational Psychology, 89(4), 677–681.
  • Kim, Y. S., Reinecke, K., & Hullman, J. (2017, May). Explaining the gap: Visualizing one's predictions improves recall and comprehension of data. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (pp. 1375–1386). ACM.
  • Sailer, M., Hense, J., Mandl, J., & Klevers, M. (2014). Psychological perspectives on motivation through gamification. Interaction Design and Architecture Journal, 19, 28–37.
How can you implement the method?

Option 1: You can embed the given visualisation
It is possible to embed the visualisation from our website including the frame text via iframe. To do this, use the following html-code for your website: <iframe frameborder="0" height="650px" src="https://static.risikoatlas.de/modules/estimating-trends/index.html" width="1024px"></iframe>

Option 2: You can adapt the given visualisation
If you use your own data as a multiplier, your web developers can enter it into your own consumer fact box with experience-based learning.

We will provide the person responsible for your website with the documented code for download via github. You can then edit the material. The link to the repository is available on request. Contact details can be found here.

Option 3: You can apply the scientific principle independently
If you require assistance, please consult the final report on the RiskAtlas project from July 2020 or contact us. Contact details can be found here.

When using the instruments, please mention the funding agency, which is the German Federal Ministry of Justice and Consumer Protection, and the Harding Centre for Risk Literacy as the responsible developers.

Logos can be downladed here.

Links to other methods
Visualisation with frame text

Is my salary rising as fast as my rent? How to interpret line charts correctly

If you live in a large German city, then you are certainly familiar with the terms "rent increase" or "real estate price development". These topics are more and more often a topic of conversation in families and among friends. Around 40% of German households now spend more than the recommended third of their net income on rent. The extent to which household incomes in Germany keep pace with housing or investment costs is questionable. Such parallel developments are usually illustrated by more complex line charts. It is important to be able to read the charts correctly so that you can interpret them accurately. Click your way through our interactive chart to see where you stand in terms of your statistical knowledge!

Sources and quality of the data

Empirical evaluation with consumers

All research results on the fundamentals and on the effectiveness of the RiskoAtlas tools in terms of competence enhancement, information search and risk communication will be published together with the project research report on 30 June 2020. If you are interested beforehand, please contact us directly (Felix Rebitschek, rebitschek@mpib-berlin.mpg.de).

 

Links to other topics

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