3.2 Methods

3.2 Methods

Next, I outline the specific details for this proposed research in terms of data gathering (Vagle, 2018) and data engagement (Ellingson & Sotirin, 2020). I outline the proposed timeline, participant sampling, access and management of field notes, interview planning and design, data coding and analysis, data interpretation, and ethical considerations. Data will be assembled from an examination of social media locations, semi-structured interviews, participant generated reflective stories and/or graphic representations which may include word clouds and mind-maps, and observational field notes. These data collection methods support crystallization by celebrating “multiple points of view of a phenomenon across the methodological continuum” (Ellingson, 2009, p. 22) while exploring participant’s fluencies, collaborations, patterns and networks (Hine, 2015; Markham, 2016).

3.2.1.  The Gathering

Vagle (2021) posits P-IP researchers gather materials rather than data, in order to semantically separate research endeavors from qualitative, positivist perspectives surrounding what researchers collect. While this is a compelling notion, I will apply the term data gathering for this research proposal. While Vagle (2018) suggests “the phenomenon calls for how it is to be studied” (p. 75) he describes multiple data gathering moments including observations, writings, interviews, drawings, and music collected over a specified period of time. In fitting with the research topic, this methodological approach honours the openness of OEPr while examining a multiplicity of textual information and an openness in data gathering. Vagle (2018) suggests data moments could include arts-based methods such as drawings, paintings, photos, visuals, films, and performance art. Unstructured interviews are the most common interview type in phenomenology due to the open dialogic nature (Kennedy, 2016; Vagle, 2018).

Data gathering will begin with web searches of FoE sites for participant related information. The digital information originating from daily digital interactions by participants in online platforms could be “extremely insightful to understand what digital actors ‘do’, rather than who they ‘are’” (Caliandro & Gandini, 2017). These open sources of information, such as participants’ social media locations such as blog sites, Twitter, Instagram, and course websites (when these are posted openly), can provide information which can be woven into an interview as a conversation prompt or question. While information garnered from multiple web sources can reveal open educational practices and digital literacies in action, it will foremost provide insights into the lived experiences, intentionalities, and digital identities of the participants. While gathering these data materials, I will create observational notes and begin to establish preliminary connections to possible MDL exhibited within and through these online data assets. In this way, in the early stages of the research, I will begin my engagement with data making (Ellingson & Sotirin, 2020) as well as begin to create dynamic representations for each participant. I will begin using a conceptual map of connections, locations, and literacies in order to “animate new ways of thinking and relating by affirming heretofore unimagined configurations” (Ellingson & Sotirin, 2020, p. 11).

3.2.2.  Timeline

The proposed timeline for this research is provided in both text and graphic formats. While this timeline suggests a linear process, there will be looping-back and revisiting of data and field notes as part of an iterative, rhizomatic, and crystallizing process. This supports the assembling of data engagements (Ellingson & Sotirin, 2020) since data may emerge through lived experiences and intentionality of TEds as revealed through actions, artifacts, technologies, and discourses within the research phases. Throughout the research, I will iteratively use digital data analysis tools such as NVivo and Voyant, as well as graphic visualizations, and concept mapping, following the three ethical commitments posited by Ellingson and Sotirin (2020) of pragmatism, compassion, and joy.

Phase 1 includes the initial contact and informed consent, followed by a round of first interview(s) scheduled and conducted. The recorded interviews will be transcribed and then reviewed by re-listening while reading the transcript. This will support making any necessary edits and adding to the observational field notes. In this way, I will re-encounter data within an agentic and dynamic state (Ellingson & Sotirin, 2020). While the recordings or transcripts will not materially change (Ellingson & Sotirin, 2020), I will engage with this data from a different moment in time, thus shifting my views in subtle or dramatic ways. This will be followed by analysis and coding of the transcript and field notes for each interview as they are conducted, along with conversion of the transcript into a word cloud. Both the transcript and visual word cloud image will be shared with the participant for review and comments.

Phase two will include an artifact production completed by each participant following the first phase. Prior to this artifact production participants will be asked to explore and reflect on frameworks for MDL (Hoechsmann & DeWaard, 2015; Stordy, 2015) and OEPr (Bates, 2014). At the end of the first interview, and in subsequent email communication, participants will be asked to prepare this digital artifact, using a technology of their choice (text, image, graphic, audio, video), to reflect their MDL and OEPr lived experiences. As suggested by Ellingson and Sotirin (2020), this “participatory data engagement requires exceptional openness to change, to uncertainty and ambiguity, and to attending carefully to how different forms of knowledge emerge” (p. 95).

Through this artifact, I will delve more deeply into the lived experiences with MDL within OEPr. This will be an opportunity to “focus on analysis and creative representations of participants’ experiences, with consideration of the researcher in a secondary role” (Ellingson, 2009, p. 23). In this artifact, which could be a written reflection, a graphic rendering such as an infographic, an audio recording, or a video response, the participants will share their insights on how MDL are enacted within their OEPr. This digital artifact will reveal a representation of MDL and OEPr in action, as a process of becoming. This second phase is a way of “leading to a co-authored understanding of the experience being discussed between the participant and the researcher” (Ranse et al., 2020, p. 6). A timeline chart will be maintained to ensure completion of these phases within the proposed timeline benchmarks (see Appendix D).

3.2.3.  Participants

Vagle (2018) suggests the number of data moments rather than the number of participants should be a primary consideration in P-lP research. I will apply purposeful sampling in order to make judgements as I select participants, based on my experience and knowledge of open educational practitioners and Canadian teacher education. The benefit of purposeful sampling is that it allows me to select teacher educators in Canadian FoE who best meet criteria that relate to the purpose of this research (Cresswell & Guetterman, 2019; Tracy, 2020). I will seek participants who meet a combination of two of these open educational practitioner criteria:

• The participant is currently working or has worked within a Canadian faculty of education as an instructor within the previous two years
• the participant has an active and easily discoverable social media presence on Twitter, Instagram, Facebook, YouTube, or other social media spaces (eg. TikTok, Linkedin, Canva, Soundcloud, Slack);
• the participant has maintained and/or is currently maintaining an active presence using a website, blog, wiki, or media curation space (e.g. Canva, Flickr, Pinterest);
• the participant shows evidence of using social media in their teaching, as evidenced in their academic biographical information and/or course syllabi, where available;
• the participant engages in open educational practices as described by Paskevecius (2018) and Paskevecius and Irvine (2019) and evidenced in course syllabi (if available), academic writing, or the content of social media comments and contributions; and/or
• the participant has written about open educational practices, media and digital literacies, or efforts to engage within educational social media networks, as evidenced in their academic publications and their social media outputs (tweets, blog posts, etc).

By establishing these criteria, I will mitigate one of the weaknesses of purposeful sampling, that of inaccuracy or inconsistency in my selection criteria (Gay et al., 2012).  

While a listing of potential participants from my known networks is a starting point, this does not imply willingness to participate (see Appendix B). Participants from a diverse, representative set of up to fifteen teacher educators from Canadian FoE will be selected. The sample size in this proposed research, as suggested by Cresswell and Guetterman (2019), will determine the depth and manageability of the data picture, with each additional individual adding to the research time requirements and complexity. With up to fifteen participants, I will have some flexibility should any participants become unavailable for the full research protocol. While a preliminary list is suggested (see Appendix A), finding additional participants can be done through snowball sampling as participants reveal others who may fit the research criteria. In this way I can better ensure a willing participant pool for the two research phases proposed for this research while still ensuring participants can withdraw from the research at any time. As the research evolves, I will consider the total number of potential data moments that will encompass the totality for this research.

Initial research information, followed by informed consent forms will be emailed once initial contact and interest in participation is gained. Upon completion of the informed consent, a web search for each participant will be conducted while notes and observations of current social media engagements and activities are collected. One semi-structured interview and one reflective artifact created by the participants will be the primary methods of information gathering. A preliminary set of potential questions or points of conversation will be sent to each participant. This semi structured interview will be video recorded using technology such as Zoom.

From the video recorded interviews, a transcript will be generated through the use of technology such as Otter.ai. The transcripts of these interviews will be converted into a word cloud and used to generate a concept map to gain differing perspectives and explore the “yet-to-be-known” (Kinchin et al., 2010, p. 1) while clarifying the elements of the TEd’s stories of becoming. These images, visualizations, and transcripts will be shared with the participants for review and feedback.

3.2.4.  Field notes and visualizations

For the duration of the research, I will keep both digital and paper versions of field notes and observations, since both are fluid territories for me. This will include audio recordings, annotations, video recordings, and textual artifacts. These will be curated, stored, and organized in folders on my computer hard drive, on private blog posts, and, where anonymity is maintained, in open blog posts. A spreadsheet will be maintained to catalogue and identify all participant generated and researcher created files (mp3, mp4, jpg, png, and pdf) with date/time stamps and locations (folders, files, URLs).

Field notes for this research will include jottings; descriptive observations of social media engagements such as tweets, blog posts, Linkedin updates; cognitive connections; and marginalia. Since jottings and cognitive connections can occur at any time, these will be recorded at any time, in any place, and with any media, indicative of the fluid nature of the research process. Saldaña (2016) suggests these private, personal, written and recorded musings become “question-raising, puzzle-piecing, connection-making, strategy-building, problem-solving, answer-generating, rising-above-the-data” heuristics (p. 44). I will heed the caution to not rely on “mental notes to self” (Saldaña, 2016, p. 45) as a method, and apply the technologies at hand to capture the wonderings and wanderings along the research paths. Vagle (2018) suggests walks to provide time and space for phenomenological musings to occur. In true P-IP fashion, the technology will make me as researcher while I make research data. For my research, the liveliness of my field notes and musings, as data productions, will be revealed in the “affective or entangled engagements with materializations or textualizations whether as a glow or a strange idea or an imaginative glimpse into a new becoming” (Ellingson & Sotirin, 2020, p. 22).

3.2.5.  Interview planning and design

Vagle (2018) suggests that the myth of the unstructured interview as a wide-open event without boundaries or parameters hinders P-IP researcher preparation. Having a “clear sense of the phenomenon under investigation” (Vagle, 2018, p. 86) and orienting the interview toward that phenomenon are essential considerations. Prior to being used with research participants, the semi-structured questions proposed for this research (see Appendix C) will be piloted with two or three teacher educators, thus excluding them from the pool of potential participants. In this way, I will make and remake the data gathering from interviews in a pragmatic, adaptive and agile manner (Ellingson & Sotirin, 2020). These prepared questions, provocations, and points of conversation will not only provide detail for research ethics approval, but provide guidance during interviews since interviewing is a new research practice for me as a novice researcher. These questions and provocations will probe and explore the lived experiences and stories relevant to the intersection between MDL and OEPr. These provocations may include questions such as outlined in Appendix C.

3.2.6.  Data: Coding, Analysis, Interpretation

Throughout the study it will be important to “document, wonder about, and question our connections/discussions, assumptions of what we take to be normal, bottom lines, and moments we are shocked” (Vagle, 2018, p. 154). In this phase of the research, “it is not a matter of looking harder or more closely, but of seeing what frames our seeing – spaces of constructed visibility and incitements to see which constitute power/knowledge” (Lather, 1993, p. 675). The gathering of P-IP moments is delicately intertwined with analysis (Vagle, 2018) so both will be conducted simultaneously and recursively. Thus, data coding and analysis will be done throughout the research phases. Computer assisted qualitative data analysis software (CAQDAS) will be used throughout the project. Knowing that software products provide varying affordances, secondary CAQDAS tools will also be integrated, based on the data management needs of the project, the privacy and security the software provides, and the visualizations the software supports.

Digital technologies proposed for the analysis of the researcher’s observational notes and interview transcripts include Nvivo, DeDoose and/or Atlas.ti, while examining textual trends and patterns can be done using Voyant Tools software. As previously mentioned, the transcript texts from the interviews will be imported into the WordArt word cloud generator, after the removal of references to names or locations and unnecessary text elements such as prepositions and conjunctions. Concept mapping tools such as Lucidchart will be used to map out the ideas and conceptions of MDL and OEPr as evidenced in the interview transcripts, observational notes, and word cloud images. In this way, I will engage in the crystallization of understanding since recordings and digital artifacts “offer lively and intriguing options for making, assembling, and becoming qualitative data” (Ellingson & Sotirin, 2020, p. 33, emphasis in original).

Vagle (2018) suggests a whole-part-whole sequence for data analysis and synthesis that includes: 1) a holistic reading of the full text to become “attuned to the whole material-gathering event” (p. 110); 2) a first line-by-line reading while note taking, adding marginalia, and journaling; 3) writing follow-up questions to ask the participants; (4) a second line-by-line reading to examine meanings and extracting excerpts, thus creating a new data moment from these gathered texts; (5) a third line-by-line reading focusing on analytical thoughts; and (6) subsequent readings to reveal and name the emergent patterns, themes, and  meaningful units across and amongst the participant’s collective data. Within this process, I will apply multimodal, media making and creative constructions to enhance the potential of opening new lines of meaning and understanding, of seeing what frames my seeing (Lather, 1993). Patterns that emerge from the field notes and visualizations will be subject to categorization and coding (Saldaña, 2011).  Subsequent deep readings will lead to the development of code memos and themes reflective of the participant’s “routines, rituals, rules, roles, and relationships” (Saldaña & Omasta, 2018, p. 15). Visualizations will also be revisited and reviewed to examine how they reflect the lived experience of the participants.

While the exact coding techniques and strategies will emerge from the data and the research design, awareness of essential skills and attributes will support the coding of my research. Saldaña (2016) identifies personal attributes that qualitative researches should possess – organization, perseverance, ability to deal with ambiguity, flexibility, creativity, rigorously ethical, and an extensive vocabulary. These support the cognitive skills of “induction, deduction, abduction, retroduction, synthesis, evaluation, and logical and critical thinking” (Saldaña, 2016, p. 338) required for qualitative researchers.