Typology of possible research findings (i.e., “contributions”)


A good academic text delivers a clear and interesting message. That is often described as “contribution”. Good contributions teach something to the text’s readers: they change the reader’s way of thinking or acting, and increase their understanding and knowledge about an interesting subject. Thus, “a contribution is made when a manuscript clearly adds, embellishes, or creates something beyond what is already known” (Ladik & Stewart, 2008, p. 157). Such findings therefore present something that the researchers did not know so far; that is what makes the research article interesting.

Also a BA or a MA thesis deliver contributions. But their requirements for significant contribution are lower, as it is not crucial that a finding of a thesis should be a considered as a research contribution that generates novel understanding in the scientific community.

So, what are the possible findings and contributions that academic texts can make? Understanding what a contribution can be becomes easier over time, as one reads more literature and sees more examples of academic publications. But to get started more quickly, this article presents some classifications that I have found from other researchers’ writings, and finally presents a longer list that I have tailored for the fields of design and HCI.

The presentation of contributions in this article is in two parts: first I will discuss academic articles, and then I will add notes about BA/MA theses in HCI and design.

Types of findings and contributions in academic articles

Contributions can be classified along several dimensions. Some of the existing classifications are oriented to theoretical contributions. For example, Ladik and Stewart’s (2008) “contribution continuum”, written for a marketing research audience, divides the possible contributions to 8 classes, organized from minor to fundamental scientific impacts:

  1. Straight replications: studies that verify whether a finding that has been already published can be repeated.
  2. Replication and extension: similar to the one above, but with an adjustment.
  3. Extension of a new theory/method in a new area.
  4. Integrative review (e.g., meta-analysis).
  5. New theories to explain an old phenomenon, possibly also including a comparison between an existing and the new theory against each other to find out which one works better.
  6. Identifications of new phenomena worth of attention.
  7. Grand syntheses that integrate earlier theories together.
  8. New theories that predict new phenomena.

In addition to presenting the continuum, Ladik and Stewart’s (2008) text is great also in emphasizing many other characteristics of good academic texts too, such as a need to think about the target reader audience, need to emphasise surprise, and demonstrate passion and relevance of the topic that has been studied.

In human–computer interaction (HCI), which is more oriented to human-created objects, other kinds of contributions can be recognized. Wobbrock (2012) and Wobbrock and Kientz (2016) do not define the contributions based on their magnitude, but in terms of types of outcomes. As we can see, the theoretical contributions that were listed above are only one possibility in applied fields such as HCI and design:

  • empirical research findings (e.g., what factors and phenomena play an important role in different situations where people use technologies)
  • artefacts (i.e., designs and technologies)
  • methods
  • theories
  • datasets
  • surveys and reviews of existing research
  • opinions

In this classification, Wobbrock and Kientz’s papers themselves could be best classified as survey-like contributions, since their focus is on reviewing the kinds of research contributions in a research field as a whole. In this sence they synthesize together and explicate the practices in the field. In addition to being more directly useful also for HCI/design, Wobbrock’s suggestions are also great because both texts list papers from HCI research that exemplify these contribution types.

What is particular in the list above is the role of artifacts as research contributions. This is particular since it highlight’s HCI’s (and also design’s) nature as a “problem-solving” science (Oulasvirta and Hornbæk, 2016): in addition to producing the traditionally well-acknowledged empirical and conceptual (theoretical) contributions, HCI researchers also make constructive contributions by developing new technologies and designs.

Final distinction between contributions is their level of critical stance towards earlier research and practice. Most contributions are knowledge-increasing: they present new findings, expand the research to new areas, make existing theories and methods more detailed, accurate or more appropriate for some context, for example. These contributions are really common: with my colleagues we found, for example, that 94% of research papers in information systems research are knowledge-increasing (Salovaara et al., 2020). Many of the contribution classes presented in the lists above are like these too.

Other contributions are knowledge-contesting: they identify problems in the existing theories and methods, or in the practices by which they are used (Salovaara et al., 2020). They may also identify limits (“boundary conditions”) to the extent to which earlier contributions can be applied. In the spirit of science and research being a self-correcting process, the purpose of these knowledge-contesting contributions is to correct earlier mistakes in research and keep the research on the right track.

To summarise the considerations above, the following table presents a synthesis of possible contributions in HCI and design. A vast majority of the papers represent one (or sometimes several) of these contributions:

Contribution type Description Example
Boundary condition E.g., finding that there is a hard limit in some theory or a method that cannot be overcome by following the existing strategies. In mobile settings, users are usually not able to attend to their mobile phones more than 4 seconds at a time (Oulasvirta et al., 2005).
Demonstration of novel possibilities E.g., a new technology that has not been possible to build before Machine learning can help web designers develop better user interface layouts (Todi et al., 2016).
Extension to a new field E.g., adapting an approach to a new context What HCI research can offer for sexual wellbeing (Bardzell and Bardzell, 2011).
Falsification Demonstration that an accepted theory/belief is not true or has limited generalizability User interfaces should not be designed by having a premise that human behaviour is always planful. That is because of the situatedness of human action. Communication breakdowns between humans and technologies happen are inevitable, and assuming planful behaviour increases their severity (Suchman, 1987).
Incremental improvement Presentation of a solution that outperforms earlier approaches In mobile maps, it is better to visualize off-screen targets with triangle-like shapes (“wedges”) than with earlier-recommended arrows or radius-based circles (Gustafson et al., 2008).
Introducing another research field to one’s own field’s researchers, and showing that it can help in solving an interesting problem Presentation of a research field whose importance has not been noticed but which offers a lot of value Information foraging theory: that the theories about animals’ food-hunting can be applied to humans’ ways of searching for information in information spaces (Pirolli and Card, 1995).
New method Description of a method that is useful in many situations “Wizard of Oz” method: Futuristic technologies that cannot be built yet may be realistically studied if a human plays the computer’s part without the user’s awareness (Gould, 1983)
Novel concept E.g., an important phenomenon that needs to be remembered in future research and design ”Plausible deniability”: In human-human communication through a technology (e.g., a chat), technology should offer a possibility for humans to remain non-responsive without fear of “losing their face” (Nardi et al., 2000)
Sense-making E.g., an open-ended study that reports and analyses a phenomenon that is so far poorly understood What conversation strategies do online trolls use to derail and harm online conversations (Hardaker, 2013).
Synthesis / meta-analysis / review Summary of existing knowledge in the field Review of literature about the differences in novice and expert designers’ design processes (Cross, 2004).
Recommendations / guidelines Description by an experienced researcher or researcher team on how to use a certain method correctly. How qualitative data should be analysed using thematic analysis (Braun & Clarke, 2006).
Research agenda / manifesto Call for researchers to start addressing a neglected issue Call for attending to the widely spread misunderstanding and misuse of the term ”affordance” in much of design practice (Torenvliet, 2003).

This list is not comprehensive, and some areas have been covered in more detail than others. What is however notable in this list’s items is that papers about these contributions can be written using the same narrative format. That is because most of these contributions require a study: some method by which some material is analysed so that findings can be presented. Such papers can be readily written following the IMRaD-style narrative. Only the last two contributions – recommendations/guidelines and research agendas/manifestos – may need a different kind of a narrative and can therefore be harder to write well.

Examples of non-contributions in academic research

Notably, there are also certain types of papers that are often submitted for publication but which are often rejected and will therefore be rarely found in academic literature. When one is writing an article, it is a good idea to make sure that one is not writing one of those types of papers. Four common non-contributions are following:

  • Presentation of a well-designed system and its design process. These papers present well-designed systems and include evaluations that demonstrate the high quality of the outcome. The problem with these kinds of papers is that for a researcher looking for novel information, such papers offer very little to learn: they “only” describe well-conducted design process that already uses well-known methods. Only if these design processes solve hard problems in some contexts, and that these problems and their solutions generalise to other contexts too, the papers start to have value in terms of an academic contribution. That is because then the academic reader may conclude that the authors have found a way to address a problem that previously has been considered difficult to tackle. This kind of a study can be turned into an academic contribution by identifying a “design problem” that was solved in the process, and explaining why this problem is difficult and in what design situations similar problems can be encountered (i.e., where does the design problem and solution generalise to).
  • Case study report. Papers of this kind present observations or interview-based findings from field studies, and describe carefully methods that were used in these studies. A lot of effort may have been put into gathering all the data and to analyse it. Unfortunately, despite all the effort spent, also in this case, the conclusion by a reader may be that the story is interesting but lacks novelty: papers of this kind may be a well-conducted research projects but which only have applied rigorous methods without yielding novel findings. This kind of a study can be turned into an academic contribution by identifying an interesting and novel finding, and deepening the literature research so that it convinces the reader about the novelty and the need for this finding in the research field (e.g., a “research gap”).
  • Mappings of findings to a framework. Some papers present analyses from a complex settings and map these findings to a well-known theoretical framework (e.g. activity theory). The problem with such a finding is that it counts mostly as a demonstration that the framework can be used to make sense of observational data. This may not be surprising, if the same has been shown in numerous earlier studies too. This can be turned into an academic contribution, for example, by finding out that the framework cannot be used to make sense of some parts of the data, or that the framework needs adaptation because of the novel findings.
  • Landscaping and clustering studies without conclusions. Some automatic data analysis methods nowadays allow researchers to generate elaborate descriptive visualizations and groupings that can summarise complex phenomena in a neat manner. Examples of these methods include social network analysis, clustering methods of multidimensional data (e.g., factor analysis, k-means clustering and topic modeling), and sentiment analysis about natural language. If a paper only presents the outputs of such analyses, without identifying non-obvious patterns or conclusions, the paper easily lacks a clear contribution. An academic contribution would include an actionable message to the research field: a call for changing the research focus, or think about a common phenomenon in a new way. Typically this requires that the researchers interpret their clusters and identify something unexpected from them.

Contributions and findings in BA and MA theses in HCI and design

In BA and MA theses, the requirements are slightly different than in academic articles. The difference lies in the need for presenting a contribution vs another, more modest kind of a finding. A thesis does not need to demonstrate novelty to an entire research field; it only needs to demonstrate the ability to apply the relevant methods, theories and analytical thinking with respect to a meaningful problem of practical importance. Therefore the three last above-presented examples of non-contributions are, in fact, good candidates for excellent BA or MA theses even if they lack an academic contribution.

One may therefore conclude that in BA and MA theses, the goals can be more practically determined: They may orient to finding good designs or solutions for specific design problems. They may be reflections about the nature of a design process, such as explorations whether a certain design approach yields findings that satisfy the designer. They may also be oriented towards a designer or practitioner community than the researchers. Therefore they may deliver a call or message to those communities to start addressing issues or become aware of matters that are being neglected. Such issues do not need to relate to academic activities, but to societal issues, for example.

One or many contributions?

There can be one or many contributions in a paper. Some contribution types also go naturally together. For example, sometimes the most interesting contributions appear in the Discussion, after the answers to the research question(s) have already been presented. Thus a paper about an exploratory study may be sense-making in its Findings (e.g., by identifying an interesting underlying pattern or concept in the findings and by giving a name for it), but a manifesto-like contribution in its Discussion if it then shows how that concept may be crucial to remember in other situations too. Many readers may find that this manifesto-like contribution is actually more important than the text’s original finding.

However, many instructions on academic writing recommend that every text focuses on delivering only one “contribution”. For example, instructions published in Nature’s web page recommend to “Keep your message clear” (Gewin, 2018). There is a good reason for this: To offer a clear and interesting message, different contributions usually require different investigations. If one tries to combine several contributions together, they may require different methods, and these methods may conflict with each other, leading to biased and compromised results. Another problem is the need to reach a high clarity with the paper: if there are several intended contributions, explaining them clearly can be difficult. Jumping from talking about one contribution to another may be necessary, but this may confuse the reader. It is important to remember that it is the author’s responsibility to demonstrate that the findings are significant and interesting (e.g., Ladik and Stewart, 2008). Confusions should be avoided at all cost.


To conclude, to offer a clear contribution or a finding, it is a good idea to identify early on what kind of a story one wants to tell with their text. Following the recommendations of the IMRaD structure, for instance, all the attention of the paper’s argumentation can then be directed to delivering that message as clearly and convincingly as possible. This helps the readers – evaluators, reviewers, and others – appreciate the work that the author has done.


Thanks for Oscar Person for tipping me about Ladik & Stewart’s paper on research continuum.


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