Assessment Related Skills and Knowledge Are Increasingly Mentioned in Library Job Postings
Bibliographic record
Abstract
A Review of:
 Passoneau, S., & Erickson, S. (2014). Core competencies for assessment in libraries: A review and analysis of job postings. Library Leadership & Management, 28(4):1-19. https://journals.tdl.org/llm/index.php/llm/article/view/7080
 
 Abstract
 
 Objective – The authors sought to determine whether existing definitions of assessment agree with assessment-related skills sought in job postings, and to identify key assessment-related skills, needs for training, and trends in assessment.
 
 Design – Content analysis. 
 
 Setting – Job postings from six library-specific websites: the American Library Association, the Library & Information Technology Association, the Society of American Archivists, the Council on Library and Information Resources, the Association of Research Libraries, and Library Assessment job announcements at http://libraryassessment.info/?cat=13.
 
 Subjects – Job titles and descriptions published during an 18-month period between Summer 2012 and Winter 2013 that met the inclusion criteria (n=231).
 
 Methods – Job postings were searched and analyzed in two separate sets whose inclusion criteria is as follows: First, job postings with the term assessment in the position title or as the main focus of the position (n=44) were retrieved; of these, three postings were too old to contain descriptions, so were excluded from analysis. Second, job postings were retrieved with the terms assessment, evaluation, metrics, and strategic in the descriptive text of postings with position titles that did not specifically mention assessment (n=187). The full text of both sets was downloaded to ATLAS.ti software for analysis using a grounded theory approach. Mutually exclusive terms emerging from the coding process were documented and defined; from this analysis, networks of code “families” or co-relational groupings helped to create categories and sub-categories. The context of terms was closely examined to understand the meaning of assessment-related terms in job descriptions. Following this step, Microsoft Excel was used to generate tables and pivot tables, aiding understanding and illustrating data. 
 
 Main Results – All 44 job posts containing the term assessment as part of the position title were from research universities or four year colleges; of these, most were ARL member libraries. For these postings, the concept of assessment was more clearly aligned with definitions of assessment as an ongoing process. The positions described, requiring a minimum of three years’ of experience, ranged from entry-level to administrative in nature. 
 
 In the second set (187 postings), the interchangeable use of the terms “assessment” and “evaluation” was particularly evident in job postings unrelated to library instruction. No library types other than academic were recruiting for assessment librarians, but related skills, usually referred to as evaluation in public and special libraries, were mentioned in all areas of library practice including instruction, administration, public services, user behavior, and to a lesser extent, access services, archives, information technology, cataloging, and more. While less prominent, these less often mentioned areas of practice also appear to be increasing their awareness of assessment.
 
 Key skills and knowledge areas needed for assessment in libraries emerged from content analysis of the job postings. These were grouped under eight main areas of competency and were augmented by the authors’ own experiences as assessment librarians: background in library assessment, research methods, statistical and analytic skills, visualization and presentation skills, and project management and people skills. 
 
 Conclusions – Based upon analysis of this set of documents, a culture of assessment in libraries appears to be emerging, demonstrating a possible upward trend when contrasted with the earlier research of Walter and Oakleaf (2010). Overall, assessment related skills and knowledge were increasingly evident across all library types and positions. Suggestions for aiding the development of an emerging culture of assessment include fostering liaisons between ALA divisions and library schools to persuade the schools of the need for related coursework, workshops focused on assessment-related skills, certification programs, and a proposed minor in library assessment. Opening avenues for discussion between library types could enhance the growth of an assessment culture beyond academic librarianship. Additional research to better understand the diffusion of assessment culture and practice into non-academic libraries is also recommended.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.761 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".