# Network Analysis for Learners' Concept Maps While Using Mobile Augmented Reality Gaming
## 2 Materials and Methods  
Qualitative research methods were applied for data collection in order to assess the educational activity that was carried out centered around the location-based MAR game Ingress, which is selected due to the fact that it is a game suitable for adults and, moreover, it is a widely used open access location-based MAR game, which can be played without ethical concerns by users of all. Two open questions were posed to the participants, which aimed to examine the impact of constructivism through game-based learning:  
Q\({}_{1}\): How do you feel when you endow the geographical space with personal preferences? Q\({}_{2}\): Do you think that the game offers opportunities for learning and teaching geography, building on your previous geographical knowledge? These questions explore the impact of a constructivist approach [25; 26] to this adult education research, in which learners learn actively and construct new geography-bound knowledge and experiences by using the location-based MAR game Ingress and how these new knowledge and experiences are based on their prior knowledge. The data obtained from this qualitative research were examined in detail by means of methods of \"content analysis\", \"concept maps\", and \"social network analysis\" (Figure 1). The research involved 36 adult learners in Greece, aged 20 to 60 years old. Participants were trained for 4 h, and the following day, they played Ingress for 3 h. They visited all points of interest (Ingress portals) that were close to their neighborhood during those hours. Various usability issues affected their experience, and all voices (interviews) were recorded and analyzed with the method of content analysis. They were chosen on the basis of four characteristics: (a) they had already been using an Android smartphone, (b) they understood written and spoken English, so they could understand the directions that the game provided them (either written or orally), and (c) they were not familiar with Ingress at all. Of the participants, 19.44% were graduates of secondary education, 8.33% were university students, 44.44% were university graduates, 22.22% held a master's degree, and 5.55% held a doctoral degree. The 36 participants of this research were evenly distributed per age group: four age groups were defined with 9 persons in each group and at 10-year intervals: 20-30, 30-40, 40-50, and 50-60. The means and the standard deviations per age group are given in Table 1.  
The research project was articulated in five phases, as shown in Figure 1.
1. The first step was the recording of the participants' responses, after they were trained in the use of Ingress and began using it. 2. Their responses were analyzed following methods of content analysis, which is \"a research technique for making replicable and valid inferences from texts (or other meaningful matter) to the contexts of their use\" [27]. Content analysis as a method necessitates the use of advanced techniques and is independent of the researcher's personal authority [27]. Six steps are usually followed in content analyses: unitizing, sampling/coding, data reduction, inferring conclusions, and narrating. What results from this phase is a set of concepts and sub-concepts that correspond to each one of the two questions that were asked. 3. Once the main concepts were identified from within the participants' responses, the concepts and their sub-concepts were articulated in tree diagrams, and thus, they become suitable to create networks of concepts. 4. The agreements among participants over a given concept or sub-concept were registered and formed the basis for the construction of networks of concepts: the nodes of networks represent the concepts or sub-concepts, and the links between nodes stand for the agreements among participants that some concepts (or sub-concepts) co-occurred in their responses. So, if two nodes are linked, it means the two corresponding concepts emerge together from within the content analysis, as referred to by the same person(s).