2017 ASEE Annual Conference & Exposition

This research paper investigates the use of interpretative phenomenological analysis (IPA) in two studies that contribute to engineering education research (EER). We critically examine adaptations made to IPA to address cultural considerations and research focuses of EER. The authors provide varying perspectives in relation to their experiences using IPA. In this paper, we capture an open dialogue that describes adaptations made to IPA and critically question these adaptations.

IPA is a qualitative methodology used to examine subjective lived experiences of individuals. Experiences can be tangible first-order experiences (e.g., initial enrollment in college) or second-order attitudinal experiences (e.g., motivations for solving problems). IPA acknowledges the role of the researcher in interpreting students’ descriptions and co-constructing findings. IPA’s philosophical foundation focuses on participants’ idiosyncratic experiences, interpretation of lived experiences, and ways of describing experiences. We present two studies that have made pragmatic adaptations to IPA paired with a critical conversation of these methodological changes.

The first study explored engineering doctoral students’ motivations and identities that were influenced by experiences in their degree programs. Focus groups and interviews were utilized for data collection to prioritize participant availability, which deviates from IPA traditions. While IPA has a history of using interviews or focus groups as primary data sources, utilizing mixed data sources is not present in current literature. Use of multiple data sources required researchers to shift their interpretive stances to consider the significance of additional voices at the time of participant sensemaking and how this differs from lone participants. While analyzing this mixed data provided unique insights, the research team also had an increased burden to account for how dissimilar data sources inherently focused on synergistic yet distinct social realities.

The second study focused on students perceptions of diversity after working in diverse teams, with engineering teams as the unit of analysis. Data for this study came from observations of teams, two individual interviews, pre- and post-intervention survey data, team member rating, and a measure of students’ unconscious bias. In analyzing these data, priority was given to students’ stories and perceptions elicited through interviews. Interviews were analyzed by a team of researchers rather than an individual. This approach required the negotiation of distinct viewpoints in analysis and the merging of individual’s approaches to coding participants’ lived experiences as well as documenting each researcher’s positionality within the work. IPA typically introduces personal reflection during the analysis phase that draws on the researcher’s experiential knowledge. Reconciling across a research team’s experiential knowledge is a non-trivial task. Additionally, reconciliation may increase the risk of diluting participant experiences. Vigilance to return to the participant’s words is necessary to preserve their meaning-making of the experiences.

As IPA gains popularity in EER, it is important to consider how we adapt methodology to fit engineering education and how we gain new insight by utilizing different methodologies. By critically engaging the topic of methodology in EER, this paper intends to sharpen our community’s command of IPA and deepen our collective insight into engineering education.