Action without Interaction

Guideline: Use interaction in visualization sparsely and cautiously.

I accidentally found this guideline online. I guess that the author (Gröller) may not wish to call it a guideline, but I find this intriguing as many in visualization seem to argue for more interaction. I also find this thinking may be useful in many situations. I am wondering how much interaction is too much and how much is too little. I also wonder if the amount of interaction is a function of data, users, and tasks. Can Der Meister or his former and current students offer more insights on this guideline?

Interaction typically requires considerable effort and cognitive load. Static reproductions have to do without. So there must be very good reasons to resort to interactive investigations. If interaction is necessary, the user should be supported by, e.g., guided suggestions.

1 Like

I think that it is useful to distinguish between visualisations that require user interaction in order to be useful at all, and those that merely allow the user to interact.

It is possible to have a visualisation that works as a static visualisation but also allows the user to further explore using interactivity, such as by mousing-over a data point to see the precise value corresponding to that point or additional information about it in a tooltip.
I think that there is generally little cost (to the user) associated with adding such interactivity to a visualisation, as long as it is done in a way that does not create clutter or confusion.

One of the issues mentioned in Groller’s slides is that “interaction hampens reporting”. I think that the transfer of viewer state for interactive visualisations in order to facilitate collaboration and handoff between users requires further work.

1 Like

To follow up on this interesting discussion, we conducted a user study with a hypothesis – “the amount of interaction may influence a person’s opinion as how easy it is to use a visualization tool”. If the same task is performed using two different tools, the tool that requires fewer interactions or less interactive time corresponds to “using interaction” more “sparsely and cautiously”.

The study consists of four trials. For each trial, participants are required to create two bar charts to visualize a given data set. We use MS-Excel and Tableau as the two visualization tools. At the end of the second and fourth trials, participants were given s subjective questionnaire to rate the easiness of using the two visualization tools and for the overall impression. We collected – the number of interactions (NI) and the task completion time (CT).

We observed that that participants’ opinions on the relative easiness depend mainly on the task completion time, and to some extent also on the number of interactions. In some cases, the familiarity of the software may modify the direct correlations among NI, CT, and subjective judgement.

The data for the experiment can be found at GitHub.

I’d like to follow up on this interesting discussion with some related work that I’ve been doing research on.

Some of the last comments are on the relative easiness from the user’s point of view of visualizations with different degrees of interactivity or on whether interactivity is really required for information transfer or not. These are quite important points, because of course interactivity should not be perceived as burden or unnecessity by the user.

An important point that has not yet been addressed, however, is whether interactivity leads to higher learning and improves comprehension. Of course, it assists knowledge acquisition if learning happens easily and is perceived as relevant (to address the previous points). But especially when it is not only about knowledge representation but also knowledge transfer as a goal of a visualization, simplicity is not always in the first priority. Much more important is whether a learning effect takes place and which kind of knowledge can be absorbed better/worse with which amount of interactivity.

Several studies have shown, especially in learning environments and science education, that interactive learning tools like computer simulations, interactive learning modules or animations lead to a better retention of material. Not only the time to absorb knowledge was shortened, but the knowledge was also absorbed more sustainably and effectively (Millard, 2000, Pinter et al., 2010, Rutten et al., 2012). Furthermore, it was shown that specific interactive visualizations led to a deeper and clearer understanding of what was presented (Lengler and Eppler, 2007) and helped to achieve intrinsic motivation as well as self efficacy (Barak et al., 2011). Other studies showed that the exploratory component and challenge to interpretation skills prompted learners to invent their own investigative strategies and thus constructively build knowledge (Liang and Sedig, 2010; Spence, 2007, Thomas and Cook, 2005).

One study in particular explores more what was originally asked in this forum post: How much interaction is too much/too little? More specifically, the study examines the question of when a higher degree of interaction leads to higher learnings. In doing so, authors Patwardhan and Murthy (2015) found that different types of knowledge require different levels of interaction - but also improve learning overall. Most importantly, they found that when it comes to understanding information, interaction tends to be a constraint because it takes up cognitive resources - which was addressed in the comments above. However, when it comes to applying certain knowledge subsequently in a task, interactivity was found to be helpful.

A possible adaptation of the above guideline “Use interaction in visualization sparingly and cautiously” would therefore be to encourage interactivity more in visualizations that are primarily intended to convey information in order to apply the depicted knowledge in a task.

While many of these examples and studies are specific to learning environments, I think other fields of visualization can benefit from these insights as well, since the communication and direct application of knowledge can become important in many visualization scenarios.

I’m excited to hear your opinions on this!

Some literature:

D.L. Millard
Interactive learning modules for electrical engineering education
Electronic Components & Technology Conference, 2000. Proceedings. 50th, IEEE (2000), pp. 1042-1047

R. Pinter, D. Radosav, S.M. Cisar
Interactive animation in developing e-learning contents
MIPRO, 2010 Proceedings of the 33rd International Convention, IEEE (2010), pp. 1007-1010

N. Rutten, W.R. Van Joolingen, J.T. Van der Veen
The learning effects of computer simulations in science education
Computers & Education, 58 (1) (2012), pp. 136-153

M. Barak, T. Ashkar, Y.J. Dori
Learning science via animated movies: Its effect on students’ thinking and motivation
Computers & Education, 56 (3) (2011), pp. 839-846

H.-N. Liang, K. Sedig
Can interactive visualization tools engage and support pre-university students in exploring non-trivial mathematical concepts?
Computers & Education, 54 (4) (2010), pp. 972-991

R. Spence
Information visualization: Design for interaction
(2nd ed.), Pearson Education Limited, Harlow, UK (2007)

J.J. Thomas, K.A. Cook (Eds.)
Illuminating the path: The research and development agenda for visual analytics
IEEE Computer Society Press (2005)

Patwardhan, M., & Murthy, S.
When does higher degree of interaction lead to higher learning in visualizations? Exploring the role of ‘Interactivity Enriching Features’.
Computers & Education , 82 , 292-305 (2015).