List of publications, papers under evaluation and papers to submit

In this section we list the publications that resulted from the development of this thesis. We also present the submitted papers that are currently under evaluation by the editorial board of journals and the papers that we intend to submit as soon as possible. During the development of this thesis, two international journal papers, one national conference paper and one doctoral consortium paper were published. Moreover, two journal papers are under evaluation; one of them (IJAIED) received a major review and the author of this thesis already submitted a reviewed version of paper that is the second-round review. The other paper received a minor review and we are still reviewing the paper to address reviewers’ comments. Hereafter, we summarize our publications, the papers that are under evaluation and the papers we intend to submit.

Dermeval et al. [2014] – Brazilian Symposium on Software Engineering (SBES): A systematic review on the use of ontologies in requirements engineering

Dermeval et al. [2015a] – Expert Systems with Applications (ESWA): Ontology-based feature modeling: An empirical study in changing scenarios.

Dermeval et al. [2015b] – Requirements Engineering Journal (REEN): Applications of ontologies in requirements engineering: a systematic review of the literature

Dermeval [2016] – User Modelling, Adaptation and Personalization (UMAP): 3

Intelligent authoring of gamified intelligent tutoring systems

Major review on the International Journal of Artificial Intelligence in Education (IJAIED):

3_{The participation in the doctoral consortium track of this conference was of utmost importance to define}

the evaluation strategies of our authoring solution. The author of this thesis had the opportunity to discuss this thesis with important researchers in the topics targeted in this work such as Paul de Bra and Judith Masthoff.

7.3 Limitations 154

Authoring tools for designing intelligent tutoring systems: a systematic review of the literature

Minor review on the International Journal on Knowledge and Learning (IJKL): An ontology-driven software product line architecture for developing gamified intelligent tutoring systems

To submit to IEEE Transactions on Learning Technologies (TLT): Towards an ontological model to apply gamification in intelligent tutoring systems

To submit to International Journal of Artificial Intelligence in Education (IJAIED):

Authoring gamified intelligent tutoring systems

7.3

Limitations

In the development of this thesis, we could identify some limitations that may applied to our work. Note that, as previously mentioned, for each empirical study that we conducted to evaluate our contributions, we presented and discussed some possible threats to the validity of our results (see Sections 5.4.5, 6.3.5, and 6.4.5) and how we tried to mitigate those threats. The reference feature model specified in this thesis includes several variation points and variants of features that could be included in gamified ITS configurations that were identified by the analysis of the literature and industrial gamified ITSs. In this way, the design of gamified ITS in the context of this thesis is limited to the features identified in that feature model, which is constrained: to a particular type of ITS based on curriculum sequencing (i.e., based on existing ITS theories [de Barros Costa et al., 1998, Dillenbourg and Self, 1992, Self, 1990, 1998]) and problem-based learning, to specific game design elements (e.g., badges, level, avatar, etc), to specific educational resources, and so on.

Another limitation of this work may be related to our OntoSPL ontology. Although we presented an ontology for representing feature models that is more flexible and requires less time to change than a well-known ontology for feature models (i.e., Wang et al. [2007]), we did not present a strategy for detecting automatic inconsistency in the configuration of products based on the OntoSPL. Thus, despite relying on the capabilities of ontologies for automatic detecting inconsistency, our ontology is still limited to provide this functionality.

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Furthermore, our approach for identifying the evidence-supported behaviors and their respective set of game design elements was based on the manual investigation of empirical works included in three systematic reviews on the use of gamification in the context of e-learning. Thus, despite considering evidence reported by empirical works in the topic to support, based on these practices, the application of gamification to ITS, the practices identified are limited in time and scope to the works analyzed by the reviews. Indeed, there are mixed results on the use of gamification and more studies are required to identify in which circumstances gamification may be applied, including the conduction of theory-driven empirical studies [Nacke and Deterding, 2017]. Nevertheless, the behaviors identified in this thesis may provide a starting point for constraining the design space of gamified ITS based on the evidence reported by the literature. In addition, our ontological model is flexible enough to support redesign of game design elements when is needed to reconfigure a particular gamified ITS.

Our gamified tutoring ontology imports a gamification domain ontology that conceptualizes core and extended concepts about gamification based on particular gamification theoretical background (i.e., self-determination theory, 6D framework, and

BrainHex player model). Moreover, it is also based on the ITS theories previously

mentioned. Thus, the GaTO ontological model is tied to specific gamification and ITS theories and practices. However, one might note that the way we represented these concepts in the ontologies might favor their extension to support other theories, particularly, for the gamification context.

The main users of interest to our authoring solution are teachers. As such, the authoring computational solution is designed to enable them to actively personalize the gamification model of ITS according to their preferences in simple and usable ways. However, although this authoring solution is based on a conceptualization (GaTO ontology) that considers gamification theories and design practices that might benefit students, the gamification authored by our authoring solution is not fully personalized for students. Nevertheless, we include in our ontological model, concepts (i.e., player types and activity loops) that could further support the personalization of gamification for students.

Finally, we could not empirically evaluate how teachers perceive our authoring solution with respect to the domain model authoring of content and problems, which is also a