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Record W2133166779 · doi:10.18438/b8bs3x

User Studies Differ Across Some Disciplines and May Not Be Very Effective

2007· article· en· W2133166779 on OpenAlexaffvenue
Virginia Wilson

Bibliographic record

VenueEvidence Based Library and Information Practice · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicFocus Groups and Qualitative Methods
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsInterviewComputer scienceFocus groupBridging (networking)Qualitative researchPsychologySociologyLibrary scienceSocial science

Abstract

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Objective – As part of a multi-staged project, this study seeks to identify the unanswered questions about users as found in three fields: library and information science (LIS), human computer interaction, and communication and media studies, as well as the convergences and divergences across these fields.
 
 Design – A multi-phased, qualitative study involving individual face-to-face and telephone interviews, as well as self interviewing and focus groups.
 
 Setting – The fields of LIS, human computer interaction, and communication and media studies as examined in interview situations.
 
 Subjects – 83 international experts across 
 the three fields, as well as 31 local experts from central Ohio, USA.
 
 Methods – The majority of the 83 international experts in the fields of LIS, human computer interaction, and communication and media studies were interviewed by telephone (some in person). Thirty-one local experts (7 public and 24 academic library directors) were individually interviewed and also took part in focus groups. The Sense-Making Methodology was used as an interview approach with its emphasis on bridging gaps. Neutral interview questions were used to tease out the gaps in certain situations—in the case of this project, the gaps involve communication and the unanswered questions about users. Brenda Dervin developed this approach, which has been transformed and adapted by Dervin and a host of other LIS researchers over the past 25 years. It is a metatheoretical approach that has “evolved into a generalized communication-based methodology seen as useful for the study of human sense-making (and sense-unmaking) in any context” (Dervin 729). The Sense-Making metatheory is implemented three ways in the method: “in the framing of research questions; in the designing of interviewing; and in the analyzing and concluding processes of research” (Dervin 737). In the research under review for this summary the answers to the gap-identifying questions allow different disciplines to begin to communicate and understand each other. Using Sense-Making in focus groups involves self interviewing (diaries, journals) and group discussions.
 
 Interviews were transcribed using the “smooth verbatim approach” in which non fluencies such as repetition, hesitancies, and partial words are eliminated. Care was taken to ensure anonymity, as this is necessary in the first step of the Sense-Making approach. The transcripts were analyzed for themes to capture a broad picture of what the participants struggle with across disciplinary and research-practice divides. Analysis was carried out by using comparative coding developed in early grounded theory combined with the Sense-Making methodology’s emphasis on gaps and bridging gaps. The “quotable quote” was the unit of analysis, and thematically representative quotes were selected from the transcriptions.
 
 Main Results – In an attempt to analyze communication across and within disciplines, the researchers did a thematic analysis on the interviews conducted with their international and local experts. The thematic analysis found 12 major themes, which included a total of 75 sub themes. The 12 major themes include the following: Participants wanted to make a difference with their work; participants agreed that current user research is not doing the job; there are fundamental disagreements about users and user studies; there are fundamental disagreements about the purposes of using user studies; there are external forces that make carrying out and applying user studies difficult; there was a lengthy list of differing suggestions for improving user studies; interdisciplinary communication across the three fields that do user studies is not effective; it was agreed that interdisciplinary contact is difficult; communication across the research/practice divide is not going well; some participants saw academic researchers as the problem, while some participants viewed practitioners as the problem; and most participants agreed that contact across fields and the research/practice divide would be beneficial.
 
 The researchers contend that this analysis is one of many that could be done on the information retrieved from the interviews. Their goal was not to find the definitive answers, but to describe the difficulties that participants are having across disciplines and across the research/practice divide in terms of communication and relating to user studies. The researchers wanted to tease out implications for communication and to illustrate the multiplicity that they found.
 
 Conclusions – It is difficult for this study to draw conclusions except in the most general sense, as it is part of a larger, multi-staged research project. However, this study did find that although participants across fields wanted a synthesis, they also expressed their inability to understand syntheses from fields other than their own. There were some who wanted more theories, while some claimed there were too many theories already. There was much criticism about communication across disciplines, but few solutions offered. The researchers can offer up no “magic wands” as solutions for these results, but they do suggest that the modes of communication traditionally used in user studies research are not working.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.854
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.170
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.065
GPT teacher head0.447
Teacher spread0.382 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2007
Admission routes2
Has abstractyes

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