An Emerging Theory for Evidence Based Information Literacy Instruction in School Libraries, Part 1: Building a Foundation
Bibliographic record
Abstract
Objective – Part I of this paper aims to create a framework for an emerging theory of evidence based information literacy instruction. In order to ground this framework in existing theory, a holistic perspective views inquiry as a learning process that synthesizes information searching and knowledge building. An interdisciplinary approach is taken to relate user-centric information behavior theory and constructivist learning theory that supports this synthesis. The substantive theories that emerge serve as a springboard for emerging theory. A second objective of this paper is to define evidence based information literacy instruction by assessing the suitability of performance based assessment and action research as tools of evidence based practice. Methods – An historical review of research grounded in user-centered information behavior theory and constructivist learning theory establishes a body of existing substantive theory that supports emerging theory for evidence based information literacy instruction within an information-to-knowledge approach. A focused review of the literature presents supporting research for an evidence based pedagogy that is performance assessment based, i.e., information users are immersed in real-world tasks that include formative assessments. An analysis of the meaning of action research in terms of its purpose and methodology establishes its suitability for structuring an evidence based pedagogy. Supporting research tests a training model for school librarians and educators which integrates performance based assessment, as well as action research. Results – Findings of an historical analysis of information behavior theory and constructivist teaching practices, and a literature review that explores teaching models for evidence based information literacy instruction, point to two elements of evidence based information literacy instruction: the micro level of information searching behavior and the macro level of the learning task. On the micro level users are confronting information, and searching is seen as the entire process of the interaction of users with a series of information tasks, as described in Kuhlthau’s Information Search Process. The micro level is the level of deep understanding as critical thinking skills craft the connection between information and knowledge. On the macro level the learning task, designed by an instructional team, shapes the inquiry. It is the context for information tasks. The learning task is relevant, engaging, and rigorous to sustain the interest and interaction of the user with information and emerging knowledge. The macro level is the level of instruction whereby the learning task fosters self-reflection, self-correction, and self-regulation. The role of evidence, which is generated by performance assessment and action research, is critical to both levels. On each of these levels the learning task informs the information search. Conclusion – Evidence is the link between information and knowledge in the learning process called inquiry. Sources of this evidence are information tasks embedded in the learning task, which are nested in a teaching and learning culture of inquiry. In order to generate evidence continuously throughout the inquiry unit, the task is characterized by research-based tools such as performance-based assessment and action research. The synergy of these elements in Part 1 of this article establishes the foundation for building a theory that supports further research of evidence based information literacy instruction.
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.003 | 0.031 |
| Scholarly communication | 0.010 | 0.017 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".