CONTROL DE CALIDAD

While this work has sought to elucidate some of the ways in which the use of data visualisations can have an impact on learning, engagement, and the DRE as a whole, it is by no means exhaustive or complete. In fact, it serves to lay the groundwork for future work to expand on the findings herein and explore new avenues. This work serves not as an end point, but rather as a beginning—a shifting of the field’s under- standing of the role data visualisations play and their importance in the learning and research processes. By laying the initial groundwork, this work hopes to establish a foundation upon which future research can be built.

6.4. Looking Towards the Future 171

6.4.1 New Areas of Exploration

When considering the findings put forth by this thesis, multiple avenues present themselves for exploration. Perhaps first and foremost would be to further solidify the link between inductive and deductive reasoning and how the user’s preferred mode of reasoning affects their interaction with an interactive visualisation-based search. A further case study could be conducted that specifically tests from the out- set whether the user leans more towards a deductive reasoning approach or an in- ductive reasoning approach. This would likely rely upon a collaboration with psy- chology in order to determine the best set of metrics for determining not only how to test for these two modes of reasoning, but also how to scale them (as it is unlikely that the results of such tests would lead to a purely dichotomous result). Leveraging this data in conjunction with further data collection similar to that detailed in Chap- ter5would allow for confirmation of the findings and further support the need for providing tools that accommodate divergent modes of reasoning.

A second avenue would be to expand some of the work conducted here into types of visualisations more commonly seen in the humanities. The Alcalá Record Books was somewhat unique in its construction and utilisation of data visualisations, as most of the data is of a financial nature and thus more tightly structured, lending itself to more traditional implementations of a data visualisation such as bar charts, pie charts, and line graphs. Conversely, the type of data (and the relatively small size of the corpus) did not lend itself as well to more common visualisations seen in Digital Humanities, such as those discussed in Chapter2: topic modelling, vector space analysis, sentiment analysis, etc. This type of text mining tends to produce visualisations that not only need additional contextualisation—a challenge in and of itself—but also present technical challenges when attempting to tie nodes and edges to specific points within the data (as the statistical model upon which these types of visualisations are often built is obfuscates the underlying raw data). Thus, there is a potential Computer Science application here to develop frameworks and/or li- braries that would allow for more interactive data visualisations, and for this type of tie to the underlying raw data to be easily exposed to facilitate a more interactive search via the visualisation itself.

Yet a third avenue would be a further exploration of the mechanism(s) for visual search, which was alluded to in the discussion section of Chapter5. While the vi- sualisation search in the Alcalá Record Books certainly facilitated both learning and engagement for deductive reasoners, both the data presented in Chapter5and the analysis presented earlier in this chapter suggest a need for more beyond the annota- tion mechanism and the basic visualised search. As such, an extension of the current visualisation-based search could be developed and tested that would seek to incor- porate additional tools to facilitate the learning process for the deductive reasoner. Such a tool would likely allow for the following:

remove specific cases from the visualisation, which may involve being able to see the detail records and selectively remove discriminate values. Such func- tionality is actually supported by the qualitative analysis, in which numerous participants requested a similar process.

• a log of every customisation - this log would act as a history of the deduc- tive reasoning process, allowing the user to trace her reasoning through her respective customisation(s).

• additional reporting tools - the aforementioned log should also include the ability to visualise its contents in order to further facilitate the deductive mode of logical regression. If the visualisation of the log proves to be cumbersome, at minimum a function should exist that allows the user to export her search process, providing reproducible steps to defend her argument. In essence, this export should act as a model that could potentially be reloaded into the system and produce the same result.

• a regression component - working in conjunction with the log, this feature would provide the user with the ability to trace back to a particular point in her search process and create a branch of the model that allows her to explore addi- tional paths through the data. Such a tool would facilitate a type of branching narrative wherein each branch produces its own unique model, and each of these models could then be integrated and compared.

This tool would seek to address some of the difficulties encountered by deduc- tive reasoners with the inductive annotation process by shifting the process into a visualisation-based approach with the same learning outcomes. Whereas the anno- tation model follows the inductive process of building from the small to the general, this tool would leverage the deductive process by further facilitating and document- ing the movement from general to specific. While still theoretical, this model would serve as a useful subject for evaluation to determine if deductive reasoners can be helped to scaffold information in a Humanities context using a deductive reason- ing approach while relying upon tools which facilitate the deductive, rather than inductive, approach to learning.

6.4.2 Alternative Paths

It would be remiss to not also consider the alternative paths this work chose not to take. One such path is seen in the second avenue for further research listed above: incorporating more traditional humanities-based visualisations such as topic models, network graphs, etc. As previously explained, these types of visualisations were specifically avoided for the purposes of this work for two reasons:

• These methods are better suited towards larger corpra (or at least corpra with a higher amount of textual content). The data contained in Alcalá is small (only