1 Introduction

In cartography and spatial cognition, researchers regularly stress the steadily increasing importance of understanding cognitive structures in map use (e.g. Andrienko et al. 2014; Dickmann 2018; Griffin 2017; Montello et al. 2018; Roth et al. 2017; Touya et al. 2018). If cartographers are familiar with cognitive structures during the user’s processing (e.g. reading and learning) of map content, new cartographic design rules could be considered to improve the efficiency of cartographic communication in (multimedia) maps (Bestgen et al. 2013, Dickmann et al. 2015, 2013).

New proposals of cartographic design rules for ‘better communicating’ maps go back to the outcomes of user studies (e.g. Çöltekin et al. 2017, 2018; Edler et al. 2018a, b; Keil et al. 2018, 2019; Kuchinke et al. 2016). Such user studies are based on study designs that try to minimize interfering factors as much as possible. Following the standards of experimental psychology, the behavioural data of the study participants should only be influenced by the factors and conditions declared and examined (e.g. Myers and Hansen 2014).

To collect-usually quantitative-behavioural data, such as distance estimations or the distance error of recalled or recognized object locations (Bestgen et al. 2017a, b; Okabayashi and Glynn 1984) in cartographic user studies, research groups either use existing ‘standard software’, for e.g. Tobii Studio or OGAMA for eye-tracking analyses (Voßkühler et al. 2008), or develop their own customized software solutions (Edler et al. 2014, 2015a; Popelka et al. 2016; Sasinka et al. 2017). These customized solutions are adjusted to the individual study purpose. However, the inclusion of diversified multimedia elements in such lab software is still rare. Although the relevance of investigating auditory stimuli is regularly emphasized in user-oriented cartography (e.g. Ballatore et al. 2018; Bearman and Lovett 2010; Dodt et al. 2017; Edler et al. 2012, 2018c; Lammert-Siepmann et al. 2011, 2014, 2017; Papadimitriou et al. 2009; Schiewe 2015; Schito and Fabrikant 2018; Reagan and Baldwin 2006), it is no common standard to include auditory stimuli as data elements in study software.

To gather behavioural data on quantitative measures of the performance in memory of object-locations, a software tool for lab studies was developed in the Geography Department at the Ruhr-University Bochum (RUB). The tool is based on ActionScript 3.0, and updated versions of the tool are exported in the cross-platform runtime system (Adobe AIR, formerly Adobe Integrated Runtime). The scripted tool was recently extended to measure the impact of acoustic map elements on spatial memory performance (Lammert-Siepmann et al. 2017).

Related versions of this audio-featured ActionScript-based tool have been used in several studies dealing with cognitive structures in map use. Identified effects, such as the grid effect on map-based object-location memory performance (Edler et al. 2014), have repeatedly been confirmed based on a related recall memory paradigm and a similar (ActionScript-based) software tool (Edler et al. 2015b, 2018b; Dickmann et al. 2017).

This paper is intended to present and discuss some main functionalities of this tool which supports the automatized execution of a recall memory paradigm. The presentation of the tool is based on case examples of written and ‘commented’ scripting code (in the object-oriented programming language ActionScript 3.0). These code-based examples are focussed on important aspects of experimental design. Before these code-examples are presented, the procedure of study design which represents the conceptional background of the tool is briefly introduced.

2 A Recall Memory Paradigm Including Audio Elements

The methodological paradigm used in this study is based on a standard paradigm of experimental and cognitive psychology. It is used to investigate recall performance in memory (Baddeley 1997; Mandler et al. 1969). The method presented in the following is an adaptation of the recall memory paradigm to measure the performance in memory of object locations (see also Postma and De Haan 1996). It includes visual and auditory stimuli linked with topographic maps. The audio files are recordings of spoken place names. They were recorded with a music studio equipment.

The (visual) study materials include digital topographic base maps-an adjustable number, but six in this case. These maps are based on open (ATKIS) data (.shp-files) provided by “Geobasis NRW” (https://open.nrw/). These open data allow to (re-)build topographic maps of North Rhine-Westphalia (NRW), Germany, in the currently defined graphical style. The size (30 cm × 20 cm; in pixels: 1065 × 710), format (landscape) and scale of all maps (1/10,000) were identical in this example. The digital maps are designed for being displayed on a TFT-LCD 24″ screen. They are created and exported with ESRI ArcGIS (v. 10.5). The screen was calibrated to mirror the official colours.

Another graphical layer included six circular (point) symbols which are added to each topographic base map. These points (size: d = 0.5 cm, fill color: #e100c8) marked fictional locations within the represented topography. Each point is given a fictional (German) place name consisting of two syllables and eight characters. Both, location (spatial information) and name (attribute information), are randomly selected for each map. The selection is based on a pool of 40 possible locational options, combined with 48 possible place names. Each place name can only appear in one map.

In the study maps, the place names are presented either purely graphically (written text) or audiovisually (written text, plus played voice recording). The six maps are randomly subdivided into two groups comprising three maps each. The two groups refer to the different conditions of communicating the place names (visual vs. audiovisual). The theoretical background to the study leading to these two study conditions is documented in Lammert-Siepmann et al. (2017).

The procedure of the recall memory study consists of three major phases: (1) memory encoding, (2) filler task, (3) memory recall/retrieval. Memory encoding (60 s) refers to learning the locations of map objects and their semantic identities (place names). The names can be-depending on the study condition: visual vs. audiovisual-(dis-)played by clicking on the point symbols representing the locations. The filler task (45 s) is a visual search task which was independent from the memory-related tasks in the encoding and retrieval phases. Memory retrieval (60 s) involves the recall of encoded object locations and their corresponding semantic object identities (place names). The time values are based on a pre-test that was focused on the definition of suitable time parameters.

The dependent measures to be collected and statistically analysed firstly comprise the Euclidian distance between the original location of the map object and the location of the recalled object. It is quantified in the unit pixels (px) and refers to each recalled object in each map. The second dependent measure is the rate of correctly recalled place names bound to object locations. Based on a threshold of 1 cm, the data were further automatically processed and classified into correct recalls (within 0–1 cm range) and incorrect recalls (outside of the range). The data export (in.txt-files) is structured and exported in labelled columns for each participant. It is demanded to get export files that are easily compatible with standard software for advanced statistics, such as SPSS or R. Figure 1 sums up the sequence of the study trial which leads to the concept of the study software.

Fig. 1
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Structure of the study trial as the basis for the study software

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3 A Scripted Tool for Experimental Testing of Audiovisual Maps

The study software is based on the object-oriented language ActionScript 3.0 and has been created to run the trial sequences of the user-study automatically and in a standardized way. Using an automatized (digital) approach supports a high comparability of the test results and a minimization of individual confounding factors, such as inaccuracies that might occur if test results are gathered manually or semi-automatized. The created software consists of several modules that could be easily adapted to the requirements of different studies. In other words, its structure was planned to be adaptable without investing too much additional programming/scripting work. In the following, several code-based examples are given to highlight relevant aspects of experimental design. The code blocks are commented so that the functional ideas behind the lines of scripting code are indicated.

3.1 Randomization: Assigning Study Materials to Different Study Conditions

Randomization is a core concept used in many modern experimental studies. When repeating a study sequence several times, the sequence should be changed between the participants. This helps to avoid effects that are linked to a standardized sequence order (e.g. Barker and Milivojevich 2016). The programmed tool supports randomization at different stages. The base maps are selected in a random order and they are also randomly assigned to the two different study conditions (visual vs. audiovisual). A random-based procedure is also used for the selection of (x- and y-) coordinates of the object locations and to the allocation of the corresponding place names.

The code block in Fig. 2 gives an example how randomization can be programmed in ActionScript 3.0 to divide the base maps (imported as image files from Adobe Animate’s library) into two groups that correspond to the visual and audiovisual study conditions. In this step, the method Math.random() is employed. It generates a randomized number between 0 and 1. This random value can be used to assign the maps to the groups. The number of the (in total: six) maps assigned to each group is reduced to three. Using the same randomization method, the order of the maps presented to the individual participants is specified.

Fig. 2
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Randomization as important concept to vary the study sequence between participants

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Approaches of randomization are further used for the allocation of object locations and place names to the (topographic) base maps. Technically, suitable place names for all base maps are stored in a single array, an ActionScript class designed for listing, holding and accessing data. In the initialization of the study software, each map is assigned a specified number of names from this array via the Math.random() method. Similarly, locations on the base map for these place names are chosen from an array that contains multiple previously chosen suitable pairs of coordinates for each map. This selection of locations also takes place during the initialization, managed by a function init ().

3.2 Time Management in the Trial Sequence

The trial sequence itself is controlled by an ActionScript Timer object. This object ensures that each step of the trial is executed with the desired duration. The time management of the software especially refers to the correct durations of the three study phases (see chapter 2). In the tool (Fig. 3), an initial white screen of 3 s (used as beginning slide) is followed by the study phase (60 s), a filler task (45 s), another white screen (3 s) and, finally, the recall phase (60 s). The timer class offers the study leaders the complete control over the time spans defined for the individual phases of the trial sequence. It only refers to time management and does not restrict any other interaction of the participants.

Fig. 3
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Time management used to control the durations of the trial sequences

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3.3 Tracking Behavioural Data of Study Participants

ActionScript 3.0 offers several options for the recording of user input, which is vital for gaining behavioural data in experimental user studies. For example, this refers to the tracking of recalled object locations and object identities (place names). The tracking of user data can also be related to the counting of specific interactions, such as the amount of activating the sound files to learn (encode) the located place names. This automatized analysis may allow conclusions on the comparability of place names used. If there were specific names which have been activated more often, the analyst would have a strong indication for a different level of difficulty, which would be a base for the detection of outliers and, thus, improve the quality of the statistical analysis. If no outliers are identified, the analyst would generate an additional quantity to back up the robustness of the study design and method. Tracking the amount of clicks also allows to check if each participant has played each audio files at least once throughout the encoding phase.

The study software includes such a counter (Fig. 4) used to track the number of clicks on the point symbols (in the audiovisual condition linked with activating the audio file). In technical terms, an Event Listener is attached to the point symbols contained in the map. The listener tracks how often participants click on a symbol. Every time, a counter variable is incremented by one. The final value can be exported in the end.

Fig. 4
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Tracking user interaction to monitor the encoding phase and to reflect the method

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3.4 Visual Map-Based Summary of the Behavioural Data

Supporting the evaluation of the study, the software exports screenshots for a user-friendly visual examination of the study results. These screenshots are an additional output to the txt.-files containing the data for statistical analyses. The screenshots are nothing but individual maps which visually summarize the behavioural data of each participant. These map-based information collages give a first visual impression of the data and the spatial measures (Fig. 5).

Fig. 5
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Tracking user interaction to monitor the encoding phase and to reflect the method (Base map data: State of North Rhine-Westphalia-Data Licence Germany-attribution-Version 2.0)

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They include the original (violet) and recalled (yellow) locations and identities of objects. The order of recall (red number above yellow points) and the deviations (black numbers) between original and recalled locations (representing the distortion error in spatial memory) are also included. In addition to a first visual analysis, these screenshots also serve as a tool to give a feedback to the (interested) participants after the test [see a similar approach of visually and spatially summarizing behavioural user data in Edler (2015)].

The screenshots are created and exported based on a custom function (Fig. 6). From the scripting perspective, the software places the screen content into a variable and puts this variable into an array. If the trial has been entirely completed by the user, each item in this array, i.e. screenshot, is saved as an image (in the JPEG format) with a dynamic file name depending on the user ID assigned at the beginning of the trial and the map name (01–06). A separate function is used to add the content mentioned above (Fig. 6).

Fig. 6
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Exporting map-based information collages to support visual analysis of the behavioural data

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In addition, a text file containing the results of all trials for each participant is generated by a specific function (Fig. 7). In the function, the results for each map are added to an array (“pushed”). After a unique file name has been assigned, the results are written into the text file. This text file can now be loaded into software for statistical analysis. If the software (Adobe AIR file) is installed on a Windows PC, all exports (screenshots and txt-files) are automatically stored on the desktop.

Fig. 7
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Exporting (quantitative) behavioural data for further statistical analyses

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4 Summary and ‘Flash’

This paper was intended to give a compact overview of a self-scripted study tool that was created to run experimental trials including auditory map stimuli in spatial memory tasks. This tool is characterized by features that help to increase the quality of automatized user testing and the subsequent analysis of collected behavioural data. In addition to the integration of audio files as map elements, this tool includes randomization, time management and a data export based on formatted text files and visual cartographic interpretations of the data. To allow an easy customization of the software to related studies focused on spatial memory tasks, the code was commented and structured into separate units. As ActionScript 3.0 is known (e.g. Huddleston 2009; Muehlenhaus 2013; Richardson and Milbourne 2014) for its simplicity, modifications of the code can be made in relatively easy steps.

In the present literature and online contributions, ActionScript 3.0, which is linked with Adobe Flash, is sometimes no longer considered as a modern, but rather outdated (object-oriented) scripting language (e.g. Fish and Calvert 2016). Such opinions often refer to the forthcoming ‘expiry date’ of the Flash Player at the end of 2020 (Hurtig and Scharlach 2018). The worldwide distribution of interactive and creative contents is more and more associated with open standards, such HTML 5, WebAssembly and WebGL, which has also found its way into cartography (e.g. Crickard III 2014; Derrough 2013; Dickmann 2018). These new standards support modern options of interactivity and visualization and are highly transparent in terms of contents and the programming job.

However, advantages of ActionScript-based air-files are still obvious. A ‘closed system’, like a locally installed air-file, runs without a browser and a connection to the internet. It is not influenced by web-related factors and is easy to script and set up. Therefore, there is still great value of ActionScript-based software for lab studies, which are highly focused on standardization and a reduction of interfering factors.