HCI has a problem…

Human Computer Interaction (HCI) as a field is going through somewhat of an identity crisis.  Conflicting views of its future from both within and outside of the field mean it is difficult to define precisely what HCI is and what it is aiming to accomplish.  Efforts to define HCI are seen as necessary to ensure both the legitimacy and sustainability of the field [2,5].

This paper (HCI Research as Problem-Solving) [4] attempts to move away from the idea of seeing HCI as a discipline with strictly delineated parameters and instead posits that we should view HCI as a problem-solving tool.  The authors have applied Laudan’s problem-solving model [3] and attempted to refine and extend it so that it applies to the whole of the HCI field.  Laudan’s initial work suggested there were two types of research problems: empirical (finding solutions to real-world phenomena) and conceptual (looking at theory development questions which may not solve a specific problem).  This paper has suggested a third type of problem within HCI which they have named constructive and defined as understanding the construction of artefacts.  They are clear to define this as understanding the object’s application – the ideas and principles that come from interacting with the object rather than simply the construction.

To define HCI in such a way, as a field concerned with problem solving, seems to me to be a workable solution to the problems of definition.  It both recognises the breadth of HCI while still maintaining a legitimacy as a field which can offer solutions to wide ranging problems from conceptual to real-world.  It also allows for the trans-disciplinary nature of HCI in maintaining an open definition of what HCI research (and results) may look like.

The paper then goes on to address the issue of a way to assess the outcomes of this type of research.  There has been criticism levelled at HCI in the past that it is not a ‘scientific discipline’ and is lacking clear models of reporting and analysing results. [1].  With ‘science’ often used interchangeably with ‘status’ as a measure of the legitimacy of a field of research, it would seem that this is an important aspect for HCI to get right.  The authors suggest that Laudan’s concept for understanding solutions is a possible model that could be adopted within HCI.  Lauden suggests that we can view the outcomes, findings and results of research as problem solving solutions.  He considers that these solutions can be thought of as having a ‘strength’.  For example, a weak paper would address an insignificant problem and solve it inefficiently, while a strong paper would offer a generalisable and efficient solution to an important and recurring problem.

The idea that HCI research outcomes can also be ‘assessed’ through the problem-solving model makes it an attractive possibility for defining HCI.  My concerns however, are that many of the criteria proposed by Laudan are in themselves subjective measures of ‘success’.  For example, Laudan uses ‘significance’ as a criterion to measure the success of the results, but this is in its very nature a subjective measure and is open to interpretation as are the majority of his criteria.

If we are simply seeking to find a way to define HCI then the idea of HCI as problem solving would seem a good solution.  If, however HCI is seeking to legitimise itself as a scientific field then this may still not be the answer we are looking for.


  1. Jordan Beck and Erik Stolterman. 2017. Reviewing the Big Questions Literature; In Proceedings of the 2017 Conference on Designing Interactive Systems – DIS ’17, 969–981. https://doi.org/10.1145/3064663.3064673
  2. Alan F Blackwell. 2015. HCI as an Inter-Discipline. In Extended Abstracts of the ACM CHI’15 Conference on Human Factors in Computing Systems, 503–516. https://doi.org/10.1145/2702613.2732505
  3. Larry Laudan. 1978. Progress and its problems: Towards a theory of scientific growth. University of California Press.
  4. Sangkeun Park, Joohyun Kim, Rabeb Mizouni, and Uichin Lee. 2016. HCI Research as Problem-Solving. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, 4758–4769. https://doi.org/10.1145/2858036.2858581
  5. Yvonne Rodgers. 2012. HCI Theory: Classical, Modern, and Contemporary. Morgan & Claypool. https://doi.org/10.2200/S00418ED1V01Y201205HCI014




Author: Rebecca Nicholson

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