Investigating a Peer-to-Peer Community Service Learning Model for LIS Education.
Bibliographic record
Abstract
IntroductionLibrary and Information Science (LIS) faculty attempt to impart balance of theoretical and practical knowledge and skills to prepare graduates as professionals in diverse settings. However, transition from student to professional is more than an epistemic shift; it is transformation of self, whereby learners come to exemplify values, behaviors, and thinking of professional community (Dall'Alba, 2009; Weidman, Twail, & Stein, 2001). This occurs when learners have opportunities to interact with established professionals (Mehra & Robison, 2009) as well as those whom profession serves. LIS programs facilitate this by engaging established professionals to teach, inform curricula, and supervise experiential learning opportunities. However, as Dall'Alba (2009) notes, the most challenging task of learning professional ways of being ... is left to students themselves (p. 43). This is problematic given that a clearly defined professional identity . . . [determines] . . . work-readiness, recruitment, retention, job satisfaction and work-related motivation (Tsang, 2010 p. 1). As LIS educators, how do we support students' journeys into profession?There are number of educational para- digms from which to draw answers to this question. LIS programs in North America have typically included practicum component as graduation requirement, and additional opportunities, such as part-time placements and longer co-operative terms exist to give students professional experience. Experiential learning, which emphasizes in situ problem solving and rests upon intrinsically motivated self-directed learners (Knud, 2007), is an important element of LIS education and is enthusiastically embraced by students. Another model, community service learning (CSL), is receiving increasing attention. CSL encourages students to contextualize course work and to acknowledge patrons as equals and experts, with goal of benefitting learner and community where learning occurs (Mehra & Robinson, 2009, p. 30). In addition, peer tutoring has been explored for its benefits for both tutees and tutors. This has received little recognition in LIS, despite intellectual, emotional and social gains that have been documented (Badura, Millard, Johnson, Stewart & Bartolomei, 2003; Elmendorf, 2006; Fantuzzo, Riggio, Connelly & Dimeff, 1989). Thus we sought to formally explore application of these experiential learning models in LIS education.From 2008 to 2010 we developed Rescue, an experiential learning opportunity for LIS students at University of British Columbia, which draws upon CSL and peer tutoring models. We hypothesized that by participating in program, emerging librarians would come to understand their position in learning process, act as role models, and enhance their knowledge and professional identity through reflection and interaction (Badura et al, 2003). In this paper, we describe Research Rescue and report on learning outcomes for LIS student participants. We begin paper by examining what it means to become an information professional. We then introduce peer tutoring as way of facilitating professional be- coming, rooting it in experiential and community service learning. Next, we describe Research Rescue program and report on students' experiences as peer tutors. Lastly, we analyze and interpret these experiences qualitatively, and discuss our findings. We provide evidence that students took steps towards formation of their professional identities through their participation in Research Rescue.Literature ReviewDiscussions concerning professional identity are abundant in LIS, yet tend to focus on stereotypes (e.g., Seal, 2008) or on changing identities of established professionals. Julien and Genuis (2011), for example, surveyed more than 700 Canadian information professionals to explore relationship between library instruction duties and self-identification as teacher. …
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".