Images as an Educational Tool: Cartoon Analysis as an Example in Teaching Tourism with the use of webQDA software

Images as an Educational Tool: Cartoon Analysis as an Example in Teaching Tourism with the use of webQDA software

QNOW blog post: Images as an Educational Tool: Cartoons Analysis as an Example in Teaching Tourism with the use of webQDA software
Ana Isabel Rodrigues, Higher School of Technology and Management
Polytechnic Institute of Beja, Portugal

Ana Isabel Rodrigues, Higher School of Technology and Management Polytechnic Institute of Beja (Portugal)

The text here presented was written essentially with excerpts from two works by the author: (a) Rodrigues, A. (2020). Exploring the Use of Visual Methods in Teaching Tourism. In Antónia Correia & Metin Kozak (Eds.), Tourism Analysis: An Interdisciplinary Tourism & Hospitality Journal, 2-3, 203-214, doi: https://doi.org/10.3727/108354220X15758301241710 and, (b) Rodrigues, A.  (2022). Métodos e dados visuais em Investigação Qualitativa: Natureza, Função e Exemplo Prático com uso de Fotografias. New Trends in Qualitative Research, 10, e527. https://doi.org/10.36367/ntqr.10.2022.e527.

Visual methodologies in education have the potential for engaging students in a process of self-reflection to change behaviours. This essay aims to explore the benefits of image-based data and methodologies, such as cartoon analysis, in tourism educational environments, based on an exploratory exercise undertaken with students in the Tourism Graduation of the Polytechnic Institute of Beja. Framed by a visual culture field (Mitchell, 2008), visual methodologies in education have the potential to engage students in a process of self-reflection in an effort to change behaviours (Rodrigues, 2017, 2018). According to Mitchell (2008), a range of tools in education might be used to engage participants in visual research (drawing, simple point-and-shoot cameras, video cameras, and family photographs are some examples).

Therefore, this study explores the results of ongoing work that started a few years ago in tourism classes with the purpose of testing the benefits of image-based methodologies within tourism education environments. This is the case of a visual analysis using cartoons as visual data applied in classes proposed to students from a tourism degree course at the Polytechnic Institute of Beja, within the subject named “International Tourism”. Therefore, a group of students participated in a reflexivity and visual analysis exercise through the use of tourism cartoons from the International Tourism Cartoons Competition. The rationale of this pedagogical exercise is grounded on Mitchell’s (2008) line of thought about the use of visual methodologies in education environments when he states that:

I seek to ensure that the term “visual methodologies” is not simply reduced to one practice or to one set of tools, and, at the same time, to ensure that this set of methodologies and practices is appreciated within its full complexity. (p. 365)

The author of this paper advocated that image-based pedagogical tools like this could provide sufficient stimulation to engage learners in knowledge discovery, and simultaneously develop new skills that are truly important for students (Rodrigues 2016; Rodrigues, 2020; Rodrigues & Amaral, 2019).

The use of visual data was first proposed by Collie in the field of anthropology and social scientists started to realize that interviewees respond to photographs without hesitation (Hurworth, 2003). In fact, the adoption of photography as a research method has been successfully addressed by a number of academics (e.g. Caldarola, 1985; Schwartz, 1989; Wagner, 1987). This stage marked the beginning of employing photographs to extract information from people, particularly the use of photographs to provoke a response, which became known as the photo-elicitation technique (Harper, 1988, 2002). Various visual analysis techniques have been highlighted in handbooks (Rose, 2007; Van Leeuwen & Jewitt, 2001). According to Rose (2007), all images have three potential sites of analysis: (i) the site of production (ii) the site of the image itself, and (iii) the site of the audience.

Regarding the education field, as suggested by Mitchell (2008), one of the goals is to enhance the social responsibility of the educator among their students, by exploring particular topics generating a mode of representation, a mode of diffusion of new thinking and knowledge based on perspective views, ideas. As argued by Mitchell (2011: xiii) “with the visual creates a generative space for looking, and then looking anew (…) can be a liberating experience”. Apart from that, it is important to develop the field of visual literacy with the students so that we know how to analyze visual data, this ability to construct meanings from images (Giorgis et al. cited in Bamford, 2003), allowing us to understand and use visual elements with the intention to communicate with others (Ausburn & Ausburn, cited in Bamford, 2003). Visual literacy works on the ability to accurately send and receive messages that are transmitted by a variety of signals perceived through the sense of sight (Rezabek, 2005), making the cognitive link between the knowledge we have and the image we see. In short, it adds context to the interpretation of the image. Lester (2020) designates the process of acquiring knowledge through the analysis and interpretation of an image as `visual communication circle dance´ (see Figure 1): (i) the more we know the more our eyes and brain will feel; (ii) the more we feel the more our mind will select; (iii) the more we select, the more we understand and perceive what we are seeing; (iv) the more we perceive, the more we will remember what we are seeing and the images will be part of our long-term memory; (v) the more we remember, the more we learn because we compare the new images with those stored in our memory; and finally, (Vi) the more we learn, the more we know and, the more we know, the more we see. The “dance of visual communication” starts again. This means, therefore, that it is not enough to look at an image, it is necessary to perceive, analyze and interpret it (depending on the objective in question), and, for that, the use of visual data might stimulate all these stages of the reflexive process (look, perceive, analyze and interpret) and engage with the students that lead and guide this entire circle.

As already mentioned, the intention with this work is to demonstrate the benefits of working with the visual, based on a set of methodologies and procedures used in classes. Students were introduced to each topic in its theoretical dimension in order to consolidate concepts, through the proposed visual practice.

Goals of the exercise and procedure

The exercise consists of the analysis of a visual element, in this case, cartoons from the International Tourism Cartoons Competition organized in Turkey since 2007. Every year the theme is different, representing worldwide circumstances. 2018 is the ninth edition with the theme “Travel Memories: What is left behind – reflections on travel memories”. For more information see http://tourismcartoon.com/index.php. The premise is that using cartoons for extracting information might increase levels of engagement with the topic taught in classes.

Specifically, the goals of the exercise were the following: 

1. To embed students in tourism as a global phenomenon, with societal impacts at various levels;

2. To apply theoretical material taught during the semester;

3. To broaden knowledge and perspectives on tourism, allowing them to work with a sense of openness based on the cartoons;

4. To develop the ability to contextualize tourism worldwide, highlighting important events. 

The students were asked to answer the following questions to guide reflections on the cartoons. Additionally, several steps in terms of methodology are taken:

1. To explore the source of data (international cartoon competition official website);

2. To select the cartoons to be analyzed (selection of the visual corpus to be analyzed);

3. Analysis of the cartoon (year, name of the cartoonist, the reason for choosing, identify each pictorial element in the cartoon);

4. Explaining the message/action in the cartoon;

5. Linking the cartoon to the contents taught in this subject; i.e. application of knowledge;

6. Student’s opinions.

Visual and textual data sample and analysis

As the objective of this study is to explore impressions and opinions-based images, a more interpretative technique is needed to analyse the data, such as content analysis. Content analysis is used as a research technique for making replicable and valid inferences from data to context (Krippendorff, 1980; Bardin, 1979). From this perspective “photographs, videotapes, or any other item that can be made into text are amenable to content analysis” (Miles & Huberman, 1994, p. 240).

The strategy is based on the analysis of visual data through the textual comments that students write about each cartoon. In total, 10 cartoons were randomly chosen to constitute the visual corpus for content analysis. In terms of strategy, a textual analysis of the students’ comments in reference to each cartoon was carried out. The type of coding was also descriptive, in accordance with Saldaña (2009). Each answer to these guidelines in each cartoon was inserted in the webQDA® software, as an internal source and was content-analysed based on five main categories. webQDA®, a computer-assisted qualitative data analysis software (CAQDAS), (webqda.net) was used for the analysis of the cartoons (visual data) and comments (textual data) (Costa, Moreira & Souza,  2019).

The findings obtained are organized here in five main domains/categories, aiming to answer the five corresponding starting questions: (A) theme/topic of the cartoon; (B) meaning of the cartoon; (C) reason for choosing the cartoon regarding the subject; (D) description of the cartoon/elements; (E) students’ opinions about the cartoon. In each category, several ideas emerged throughout the descriptive coding process with the use of WebQDA® qualitative software analysis (see Figure 1).

Figure 1: Results from webQDA® coding procedure with tree nodes: categorization in five domains. Source: Outputs generated by webQDA® software, version 3.1 (2019).

a)     Regarding the first and second categories (A and B): Topics and meaning of the cartoon

A range of topics was extracted from the analysis of the cartoons. In sum, three main themes were highlighted by the students: (i) climate change and its impact on tourism; (ii) the impacts of technology on tourism; and (iii) the phenomenon of overtourism. This category instantly allows students to come into contact with the hottest issues that the tourism industry is facing at the moment. The students expressed very personal reflections and thoughts about the message contained in it. Here are some examples of the references coded in this category, which demonstrate the level of thoughts and meanings, which emerge from a visual stimulus such as a cartoon: “Global warming, water scarcity and their impact on tourist behavior” (Ref.1/cartoon 1), “The concept of traveling has changed over time” (Ref.2/cartoon 2).

b)     Regarding the third category (C): Reason for choosing the cartoon

The students expressed various reasons that express interesting thoughts about the topics. Here are some examples: “Tourism might have a worldwide impact, which will have negative consequences for destinations” (Ref.1/Cartoon 1), “Evolution of means of transport affects international tourism flows” (Ref.2/Cartoon 2), “People have different priorities (motivations) that led them to travel” (Ref.3/Cartoon 2), “Tourism must take into account the external environment that surrounds it” (Ref.3/Cartoon 3), “Tourism might have a worldwide impact, which will have negative consequences for destinations” (Ref.1/Cartoon 1). A few times, the students highlighted the link between these impressions and opinions about the cartoons and the contents that were taught during the classes, such as “This cartoon refers to one of the tourism trends studied during our classes” (Ref. 8/Cartoon 9), which corroborates the idea that images can help students to express understanding about what they are really learning during the semester.

c)     Regarding the fourth category (D): Description of the cartoon/elements

 Aiming to share the description of the cartoons and their features, a word cloud as a visual representation of text is presented based on the students’ responses (see Figure 2). These words correspond to the visual elements contained in each cartoon, which are in line with the students’ main perceptions and impressions previously presented (e.g. people, technology, sea, alienation, heritage, security, crowds, walls, among others). This is a word frequency analysis that allows the message in each cartoon to be supported and contribute to a deeper understanding of the concepts learned in classes. 

Figure 2: Word cloud with the elements extracted from the cartoons. Source: Generated by WordItOut

d)     Regarding the fifth category (E): Students´ opinions

With reference to the last category, it allowed an understanding of the students’ opinions about the cartoon and, consequently, about the subject itself. Therefore, here are the key ideas expressed by the students´ comments that summarize all the thoughts and impressions. Here are some examples extracted from the content analysis: (a) natural catastrophes; future crisis; impact on human life; extreme poverty as one of the projections for tourism if not well developed; (b) in the future, diversification of tourist motivations will be strongly influenced by technology; (c) the impact of political disagreements, terrorist attacks and natural disasters in tourism; (d) tourism as a sector of constant transformation due to technology; (c) safety is a decisive factor in the choice of destinations by tourists; (d) a new insight on nature and heritage as a resource that represents identity and value, among others.

In conclusion, this exercise demonstrates that visual data, such as cartoons, seems to work very well with the students since they place themselves as a central element of an interpretative and reflective process.  Employing visual-based methods and data within the students has the potential to make the classroom less secret and boring, potentially facilitating understanding of the topics, concepts, and phenomena under study and the education process itself. In an educational context, visual-based methods such as those previously presented encourage students to strengthen the use of critical thinking, cognitive flexibility, reflexivity, and awareness about the world today. It is important to highlight that one of the significant aims of education is to produce students who are well informed, able to understand and filter ideas that are highly significant, powerful, and useful and that can really change society for the better. This means that visual data and methods and the adoption of visual approaches, methods, and techniques within educational contexts offer new insights and perspectives that need to be more explored in the future. In fact, visual images can exemplify “experience, humanity, and meaning … and thus … edify the significance in the humanness and affectivity of research participants” (Russell, 2013, p. 433). Apart from that, the use of computer-assisted qualitative data analysis software, such as webQDA, has been revealed as a suitable tool for visual data analysis (Rodrigues, Costa & Moreira, 2019).

For more detailed reading about this topic please check this paper: Rodrigues, A. (2020). Exploring the Use of Visual Methods in Teaching Tourism. In Antónia Correia & Metin Kozak (Eds.), Tourism Analysis: An Interdisciplinary Tourism & Hospitality Journal, 2-3, 203-214, doi: https://doi.org/10.3727/108354220X15758301241710

Acknowledgments. The author would like to thank the group of students from the Polytechnic Institute of Beja, Tourism Graduate Course who agreed to participate in this study. 

REFERENCES

Bardin, L. (1979). Análise de Conteúdo [Content Analysis]. Lisbon: Edições 70.

Bamford, A. (2003). The visual literacy white paper, Adobe Systems Incorporated, 2003. https://aperture.org/wp-content/uploads/2013/05/visual-literacy-wp.pdf

Caldarola, V. (1985). Visual contexts: a photographic research method in Anthropology. Studies in Visual Communication, 11(3), 33-53.

Costa, A. P., Moreira, A., & Souza, F. N. (2019). webQDA (version 3.1) – Qualitative Data Analysis. Aveiro University and MicroIO, Aveiro.

Harper, D. (1988). Visual sociology: expanding sociological Vision. The American Sociologist. Spring, 54-70.

Harper, D. (2002). Talking about pictures: a case for photo elicitation. Visual Studies, 17, 13-26.

Hurworth, R. (2003). Photo-interviewing for research. Social Research Update, 40(1), 1-4.

Krippendorf, K. (1980). Content Analysis: An Introduction to its Methodology. USA, The Sage CommText Series.

Lester, P. M. (2020). Visual communication: images with messages. 8ª ed. USA: Lex Publishing.

Miles M., & Huberman A. (1994). Qualitative data analysis: an expanded source book. Sage Publications, Thousand Oaks, CA.

Mitchell, C. (2008). Getting the picture and changing the picture: Visual Methodologies and Educational Research in South Africa. South African Journal of Education, 28, 365-383.

Mitchell, C. (2011). Doing Visual Research. Los Angeles, London, New Dehli, Singapore, Washington DC: Sage.

Rezabek, L. L., (2005). Why visual literacy: consciousness and convention. TechTrends: Linking Research & Practice to Improve Learning, 49(3), 19-20.

Rodrigues, A.  (2022). Métodos e dados visuais em Investigação Qualitativa: Natureza, Função e Exemplo Prático com uso de Fotografias. New Trends in Qualitative Research, 10, e527. https://doi.org/10.36367/ntqr.10.2022.e527

Rodrigues, A. (2020). Exploring the Use of Visual Methods in Teaching Tourism. In Antónia Correia & Metin Kozak (Eds.), Tourism Analysis: An Interdisciplinary Tourism & Hospitality Journal, 2-3, 203-214, doi: https://doi.org/10.3727/108354220X15758301241710

Rodrigues, A. (2017). Are visual methods a suitable tool for tourism education? The reflective photography as an example, proceedings of the 9th World Conference for Graduate Research in Tourism, Hospitality and Leisure 06-11 June 2017, Cartagena, Spain.

Rodrigues, A. (2016). The camera as an educational tool: Reflective photography for examining impressions and perceptions about a destination, Proceedings of the 1st International Symposium on Qualitative Research,12-14 July 2016, Universidade Lusófona, Porto. Available at http://proceedings.ciaiq.org/index.php/ciaiq2016/issue/view/16. ISBN: 978-972-8914-62-2.

Rodrigues, A. I., & Amaral, M. (2020). From Observations and Pictures to Images: Learning Lab@PP2 in Tourism Classes. The Qualitative Report, 25(13), 104-118. Retrieved from https://nsuworks.nova.edu/tqr/vol25/iss13/8

Rodrigues A., Costa A.P., & Moreira A. (2019) Using CAQDAS in Visual Data Analysis: A Systematic Literature Review. In: Costa A., Reis L., Moreira A. (eds) Computer Supported Qualitative Research. WCQR 2018. Advances in Intelligent Systems and Computing, vol 861. Springer, Cham https://doi.org/10.1007/978-3-030-01406-3_20

Rose, G. (2007). Visual methodologies: an introduction to researching with visual materials. London: Sage.

Russell, A, Diaz N (2013). Photography in social work research: Using visual image to humanize findings. Qualitative Social Work, 12(4), 433–453. doi: https://doi.org/10.1177/1473325011431859

Schwartz, D. (1989). Visual ethnography: using photography in qualitative research. Qualitative Sociology, 12(2), 119-154.

Van Leeuwen, T. & Jewitt, C. (2001). The Handbook of Visual Analysis, SAGE Publications Ltd.

Wagner, J. (Ed.) (1987). Images of Information: Still Photography in the Social Sciences. Beverly Hills. California: Sage.

Related products

Share

Related News

A integração equilibrada entre as potencialidades da Inteligência Artificial e as competências dos investigadores será decisiva para garantir que o futuro da investigação em educação seja mais inclusiva, inovadora e diversificada.
WCQR2025 pre-conference panel discussion “Redefining the Qualitative Researcher’s Role in the Era of AI…”
This paper focuses on qualitative research in its various forms, highlighting the emergent and iterative epistemological features of qualitative data collection and analysis.