USOS DE LAS 149 ESPECIES DOCUMENTADAS

The samples from this study are drawn from the population of all faculty members from ALA-accredited schools15 in the United States and Canada. An initial list of these faculty members was taken from an online directory.16 This list was then checked against the school websites to validate that each individual was still a current faculty member and that no new faculty members were omitted.17 In addition, this study limited the population to those who were full-time faculty members, which meant eliminating adjunct professors, doctoral candidates, lecturers, instructors, and emeriti professors from the list. Visiting professors were also

eliminated. The resulting list contained 815 full-time faculty members from 56 ALA-accredited schools in the United States and Canada. By rank, there were 311 assistant professors, 273 associate professors, and 231 full professors in this population.

3.2.1. Questionnaire

From this initial population, two sub-populations were chosen for inclusion in the

electronic questionnaire, called the “advisors” and the “advisees.” The advisors were defined as

15

That is, schools with ALA-accredited masters program (as accreditation by the ALA does not happen at the doctoral level). It should be taken into account that this excludes iSchools that do not have ALA accredited programs, such as Penn State, Berkeley, and Georgia Tech.

16

http://www.slis.indiana.edu/faculty/meho/LIS-Directory/ [no longer available online]

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those tenured professors (at the rank of associate or full) from doctoral degree-granting ALA- accredited schools. Of the 56 ALA-accredited schools, 32 offered a doctoral degree in 2008. Within those 32 schools, there were 374 tenured professors. It was assumed that these professors had the highest potential for serving as advisors to doctoral students.

The advisees were comprised of all assistant professor faculty members from any of the ALA-accredited schools described above. As noted above, there were 311 assistant professors in this category. It was assumed that these faculty members were most recently in the doctoral process and would be best able to provide accurate reflections on their experiences. It should be noted that these faculty members represent one kind of “successful” doctoral experience—that is, they successfully completed their degrees and were hired to serve as faculty members in an ALA-accredited school. This study does not examine those who did not successfully graduate or those who did not become faculty members in these select schools. However, this study should provide a baseline of data against which future studies of different doctoral student populations can be measured.

As noted above, 311 “advisees” and 374 “advisors” were initially selected for participation in the questionnaires. However, during the course of the study, many of these participants were removed due to two main factors: 1) they indicated they no longer served in that position (due to retirement or job relocation) and 2) they served as members of this dissertation committee. The removal of these participants resulted in 294 advisees and 354 advisors, for a total of 648 potential participants in the questionnaire phase of the study.

3.2.2. Interview

The final question on the questionnaires asked individuals if they would be willing to be contacted for a follow-up interview. From that question, contact information for 23 advisees who

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had received degrees within the field of ILS (as identified in the questionnaire) and 33 advisors was received. These 56 faculty members were emailed individually on March 31, 2009 with a request to participate in a 30-minute follow-up interview. The first 30 individuals to respond to the request were selected for the interview phase of the study (although these individuals were split equally between the advisor and advisees, no explicit stratification was done during recruitment/selection).

3.2.3. Bibliometric analysis

A separate sub-population of the original list of faculty members from ALA-accredited schools was selected for inclusion in the bibliometric analysis phase of the study. Three criteria were required for inclusion in this phase of the study, in addition to serving as a faculty member in one of the 56 ALA-accredited schools: 1) the faculty member must have graduated from an ALA-accredited school; 2) the faculty member must have a full dissertation available online (through ProQuest’s Dissertation and Theses Database); and 3) the faculty member must have a full and complete18 CV available online. Ninety-seven faculty members met these criteria and were included in the bibliometric analysis phase of the study.19

3.3.Questionnaires

Two separate, but parallel, questionnaires were created for this study, one for the “advisees” and one for the “advisors” (see Appendices D and E for the full text of the

questionnaires). The questionnaires were informed by a review of the literature and were guided by the research questions (for a full table linking the survey questionnaires to specific literature and research questions, please see Appendix F). In addition, the questionnaires were pilot-tested

18 _{This excluded CVs that had not been updated in 2009 and that contained “selected” publication lists.}

19

Some limitations of this method were that individuals selected for the bibliometric analysis were not equally spread across years or schools.

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with several faculty members and revised based on the feedback received. The final questionnaires were built using Qualtrics20 survey software.

3.3.1. Data collection

The questionnaires were made electronically available and the link to the questionnaire was embedded in an email message sent individually to all 648 potential faculty members in the sample. The full text of this recruitment email is shown in Appendix G. The questionnaires were opened on January 29, 2009 and were closed on March 4, 2009. As all respondents were emailed individually, the solicitation email was sent over a series of days. However, each respondent had at least four weeks to respond. No reminder emails were sent.

3.3.2. Data analysis

The quantitative data from 215 questionnaires were exported to Excel and SPSS for further analysis. In the case of the advisee surveys, only those respondents self-identifying as graduates from ILS programs were included in further analysis.21 The quantitative data was analyzed predominately by means of descriptive statistics. As this was exploratory research, no causality was investigated. The open-ended questions from the questionnaires were exported to NVivo for analysis. These were coded to group similar and identical answers and counts of these answers were reported in the results.22

3.4.Interviews

20_{www.qualtrics.com}

21 _{In the original design of the study, it was hoped that survey results between ILS and non-ILS graduates could be}

compared. However, due to the low response rate of non-ILS graduates, this comparison was not possible.

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Thirty semi-structured phone interviews were conducted, each lasting approximately thirty minutes. Twenty-one interviews were conducted between April 13 and 17, 2009 and the remaining 9 interviews were conducted between April 27 and May 1, 2009.

3.4.1. Data collection

As noted in the population section, 56 potential interview participants were identified through the final question on the electronic questionnaires. These individuals were emailed on March 31, 2009 (after the electronic questionnaire was closed) and a reminder email was sent to all those who had not yet responded on April 5, 2009. The full text of the recruitment email is shown in Appendix H.

Participants were emailed one day before their scheduled interview and were given a list of three themes that would guide the interview conversation. Two themes were consistent across both groups: the difference between an advisee-driven vs. advisor-driven relationship and the extent of collaboration in both the dissertation and products/activities outside of the dissertation. The advisors were additionally asked how they ascertained the individual needs of each advisee and advisees were asked about managing multiple mentors.

Each interview began with a notification that the interview was being recorded. After that, the interviewees were asked whether they had received and reviewed the three questions which would be used to guide the conversation. They were then instructed that although those questions would help guide the conversation, they should feel comfortable to discuss any aspects of doctoral education that interested them. They were also told that they were able to end the conversation at any point, but, at the thirty minute mark, the interviewer would end the

conversation. Then, to initiate the conversation, they were asked to begin describing the doctoral process where they received their doctoral degree (for the advisees) or at their current institution

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(for the advisors). This rhetorical device helped ease the participants into the interview and find relevant anchors for launching into the three questions. All interviews were conducted over telephone and were recorded using an Olympus TP-7 telephone recording device and an Olympus DS-40 digital recorder.

3.4.2. Data analysis

Recordings of the telephone interviews were downloaded and imported into NVivo for transcription and analysis. Coding followed a mixed inductive and deductive approach. In terms of deductive coding, the four elements of Kram’s mentoring model (initiation, cultivation,

separation, and redefinition) as well as the concepts of interdisciplinarity and collaboration were chosen as concepts around which to organize the verbal statements. These topics were therefore established before analysis of the interviews. Additional inductive open coding was also

conducted, in which “codes are suggested by the researcher’s examination and questioning of the data” (Kelly et al., 2007, p. 1037). The inductive analysis yielded additional concepts around which to organize the data, namely: career goals, committeeships, grants, social, pedagogy, peer mentoring, program requirements, proposal, and the uniqueness of each advisee. As these concepts arose out of the data itself, it required iterative listening and (re)coding of the

recordings to ensure that each transcript was fully coded across all concepts. As Strauss (1987) describes, coding is used to “fracture data, rearrange it into categories, and facilitate the

comparison of data within and between categories” (c.f. Kelly et al., 2007). This process is complete when “saturation has been reached and all relevant utterances have been classified” (Kelly, et al., 2007, p. 1037).

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The data were then organized in an Excel spreadsheet in which each column represented a distinct concept, each row represented a distinct participant, and each cell represented the relevant utterance. Therefore, when writing up the results, all utterances in a column were evaluated, in order to provide a balanced report of the opinions and themes across all participants.