Assessing the Impact of Embedding Online Academic and Information Literacy Resources into a First Year Business Course
Bibliographic record
Abstract
Abstract Objectives – Literature supports the concept that embedding academic and information literacy support into first year university courses enables students to proceed more confidently with researching and writing their assignments, and thus contributes to student success in their course. A need was identified for academic and information literacy support for a cohort of first year business students as part of the development of online course content for Griffith Online, the institution’s online study degree option. This led to a collaboration between information literacy librarians, learning skills advisers, educational designers, and academic course convenors to develop and implement online resources. This paper will present findings on the impact of these online resources. Methods – Drawing on measures and methods identified in ISO16439 “Information and documentation: Methods and procedures for assessing the impact of libraries” (International Organisation for Standardization, 2014), in conjunction with the indicators offered by Lizzio’s (2006) Five Senses of Success framework, evidence was collected and combined from a variety of sources over semester 2, 2014, and semester 1, 2015 to assess the impact of the online resource. Inferred evidence was gathered from usage statistics (number of hits on the sites) and from performance measures (comparing student essay grade between those that did and did not use the resource). Solicited evidence was gathered from a survey of students, students in focus groups, and interviews with course lecturers, tutors and other stakeholders. Results – The inferred evidence showed a positive impact on the student success indicators of the sense of resourcefulness, capability, connection, purpose and identity. The solicited evidence suggests that students saw the online resource in a positive light and that staff were happy with the impact it had on students’ work and learning. It is believed that the gathered evidence indicates the Module did achieve the impact objective of a positive impact on the contribution to student success for these first year business students. Conclusions – The evidence has shown that this resource contributed to student success, and that staff and student satisfaction with the resource contributed to increased confidence with student academic skills and information literacy in respect to their assignment task. Assessing the impact of the online resource on student success has helped to demonstrate the value of the library at Griffith University to the wider community. The four-pronged collaboration relationship required for this approach was fostered with stakeholders outside of the library.
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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 | 0.011 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".