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Users’ performance in ideation during computer-mediated creative drawing can be affected by the design of a computer’s User Interface (UI). This paper presents results from a series of empirical comparative studies in which participants were presented with a creative drawing task and their ideation performance was measured in terms of the number and quality of ideas created with the use of three different input methods (mouse, stylus-, and touch-input), or two graphical UIs (GUIs). The results showed no significant differences between the different computer input methods, or between the simple and more complex GUI. However, when present in combination, these test conditions can be expected to create cumulative effects, which might explain the substantial differences observed in previous research on computerized creative drawing tasks. Quality-quantity trade-off and a new form of operational bias were observed and their effects on user satisfaction and ideation performance are discussed.

Ideas are formed in a process of idea generation that includes creation, development, and communication of new ideas. Drawing has been used as a support for ideation for centuries. Today, computerized tools are commonly used for drawing. Such tools form a user interface between the human and the resulting drawing presented on the screen. The interface may come between the user and the drawing in a disruptive way also affecting the ideation process.

Using controlled laboratory studies, this thesis investigates the consequences of drawing with different user interfaces in two types of tasks: creative drawing tasks (based on a standardized test of creativity) and non-creative drawing tasks (i.e. shape-tracing tasks where no new idea is created). The goal was to identify and evaluate the consequences of the several issues originating from the use of different input devices, the functionality of the graphical user interfaces, the formulation of the drawing task, and the user’s previous experience.

The results showed that drawing tasks are oriented toward quality of outcomes and that higher input accuracy led to higher quality of outcomes of both creative and non-creative drawing tasks. This came with a trade-off between the quantity and quality. In ideation, less accurate input devices facilitated significantly more ideas but these were of lower quality. In non-creative tracing, higher speeds caused lower quality of outcomes.

The users subjectively preferred higher accuracy, also when an inaccurate user interface offered an eraser function. However, using the eraser allowed avoiding reinterpretations of ideas and led to ideation strategies characterized by laborious drawing that negatively affected the quality and quantity of the ideas produced. For non-creative drawing, the more difficult the shapes were, the lower the tracing accuracy.

In the thesis a new framework for interaction analysis is introduced that improves the theoretical and practical understanding of computerized drawing tasks and the phenomena resulting from different aspects of the user interface design of computerized drawing tools.

This thesis demonstrates that the inaccuracy of computerized tools cannot only make our drawings less aesthetically pleasing but also negatively affect ideas that are created in the process.

Drawing tasks are rarely addressed experimentally by the HCI community, and even then pointing, steering, or gesturing is promoted as an approach towards drawing. We critically analyze the status quo, propose an improved framework for task analysis, and give suggestions on how to perceive drawing task at a meta-level.

We have applied a multivariate exploratory technique called Correspondence Analysis (CA) to create and analyze a model of the dataset of experiment results. The dataset originates from a comparative usability study of tracing with the use of mouse, pen, and touch input and contains both categorical and continuous data – i.e. results of questionnaires and task measurements. CA allowed to visually and numerically assess the main variables in the dataset and how they interact with each other. In our study, pen input had the best measured performance and was preferred by the users. Touch input was the least accurate of all input methods tested but it was preferred by users over mouse especially in the conditions lacking of visual feedback of drawing. CA helped to detect that secondary effect even though it cannot be explained by the performance results alone. The importance of the influence of user’s previous experience is also noted. We conclude that CA helped to identify all major phenomena known from previous studies but also was sensitive to minor and secondary effects, what makes it a well suited method to quickly evaluate usability data.

This paper is a work-in-progress report on an experimental comparison and evaluation of users' performance in four line-tracing tasks based on two shapes and performed with three input methods (mouse, stylus, and touch-input). The shapes' properties used in the study created the two classes of shapes: easy and hard to replicate. As expected these two classes had different impact on user's performance in each task tested (tracing, lasso selection, steering through narrow and wide tunnel). The results show that participants replicating the shapes using touch-input were the least accurate but were the fastest in comparison to the remaining input methods. The stylus was the least error-prone method and the mouse was the slowest device in drawing tasks (tracing and selection). The differences in error distances between the input methods were less pronounced in steering tasks but timing data showed that mouse was still the slowest one. While the time of replication did not differ between the two shapes tested, the differences between the errors participants made were significant for all tasks and input devices, and patterns of these differences were consistent between the shapes. These results confirm predictions from a previous study and show which shapes' properties can make their replication more difficult. The results can be used to design shapes that are easy to replicate, e.g., in surface-based gestural interaction.

This paper presents the results of an empirical comparative study investigating how the outcomes of a computerized figural creativity test are affected when the participants use two different versions of the Graphical User Interface (GUI) on a mouse-operated desktop PC. The results show that participants get insignificantly lower creativity scores with the elaborated GUI, contrary to the GUI that has no visual artifacts available and offers more similar user experience to pen and paper, even though they spend significantly more time on drawing with the elaborated one. That phenomenon is expected to contribute to the cumulative effect of GUI and input method noticed by previous research. That implies that creative drawing and testing should be carefully introduced into computer-based environments.

The output of creative drawing is negatively influenced by any constrains imposed on the artist. That may be the case especially in computer-based environments. In my research I focus on the identification and assessment of the influence computer input methods (i.e. mouse, stylus-, and touch-input) might have on the results of free-hand drawing tasks in terms of user's creativity and drawing performance.

This paper summarizes observations from four empirical studies focusing on shape replication with three input methods. The aim was to identify and assess how the components of several semirandomly generated shapes influence how accurately untrained users can replicate each of these components. We found that the pen is the least and touch the most error-prone method when used for drawing. Additionally, the distribution of errors was analyzed. The results may be used to predict which shape properties make shape replication more difficult. Additionally, the results may be used to design shapes that are easy to replicate.

This paper presents the results of an experiment comparing mouse, pen- and touch-inputs in computerized figural creativity test. The results show no statistically significant differences in creativity scores obtained by participants using mentioned devices as computer input methods. The results indicate that creativity testing can be introduced to a variety of modern computer devices with insignificant influence of the three most popular input devices tested. That also shows that the differences between the computerized and paper-based TTCT noticed in a previous research might be the result of User Interface artifacts used.

A comparison of the aggregated performance measurements for three input methods in a line-tracing task is presented. Results indicate that users perform best using touch input, both in tasks with and without visual feedback, therefore we recommend touch input as the preferred input method for simple drawing tasks.