Task-based and Problem-based heuristics: Could they be mobilized as a Verification Mechanism for Usability Heuristics?

Prior research in design indicates that design considerations (as reflected through designers’ decisions) can greatly differ from users’ viewpoints when interacting with technologies. This is typically evidenced within designers’ proposals to focus on utility and appearance whilst users’ viewpoints (or reactions) to technologies can take multiple forms (e.g. visceral, behavioral and reflective). Heuristics are simple 'rules of thumb' applied in designing technologies, focusing on design principles that aim to satisfy utility and appearance while providing a means of ‘standardization’ for designers; the same applies to usability heuristics, which are employed at the end of the design process, to assess the usability of designed systems, both in terms of usability and aesthetics. Whilst design and evaluation heuristics can offer a level of ‘standardization’, users’ viewpoints, reactions and interpretation of the designed technology can be diverse (i.e. their emotional and behavioral responses can greatly differ, making it difficult to ‘standardize’). There are several reasons why this is happening, e.g. from individual differences to context and domain-based reasons; the latter is, indeed, one of the common issues in heuristics-based design and usability heuristics i.e. these are domain-specific. It appears that there is limited research in attempting to understand the relationship and mapping between users’ own behavior (i.e. behavior-based heuristics) and design heuristics. An open question is to what extent the ‘expertise’ and empirical knowledge of designers can overlook any intuitive or unconscious behavior-oriented heuristics that manifest 'discreetly' and 'automatically' when designing technologies.The present paper is drawing data from two different user studies (route optimization problem solving and data analytics), aiming to explore what types of behavior-based heuristics people employ when performing data analytic tasks and problem-solving tasks (without the use of computer interfaces). These two different domains are chosen as they contain different requirements (i.e. completion of healthcare data analytic tasks versus completion of visuospatial mathematical optimization problems), thus providing a diverse enough comparison to explore user behaviors within domains that require some form of computer interface. By identifying behavioral patterns and heuristics people employ when engaging with these two different domains, we are able to identify interactional needs that can inform the design of novel user interfaces (i.e. decision-support systems) that can assist in the completion of complex tasks, instead of designing technologies first and then applying design heuristics to adjust and evaluate the designs. Observation methods, problem-based/scenario-based approaches and Think Aloud protocols have been employed to identify heuristics in both studies while overall performance (in terms of task completion and accuracy) has also been measured. The research found that behavior-based heuristics can be task-based and problem-based and can manifest early in design thus need capturing at user requirements elicitation. Such behavior-based heuristics can be interactional, systemic, cognitive and experiential and need to be considered alongside usability heuristics. There is a need to formalize experiences against tasks, especially as ‘smart’ technologies and multi-systemic data exchange can be stakeholders and ‘end-users’. A conceptual design verification framework is proposed to enhance design and evaluation processes.