First Year University Students Arrive with Some Search Skills, But Struggle with Scholarly Sources
Bibliographic record
Abstract
A Review of:
 Salisbury, F., & Karasmanis, S. (2011). Are they ready? Exploring student information literacy skills in the transition from secondary to tertiary education. Australian Academic & Research Libraries, 42(1), 43-58.
 
 Objective – To determine what existing information literacy skills first year students possess upon entering university.
 
 Design – Quantitative survey questionnaire.
 
 Setting – A research university in Australia.
 
 Subjects – 1,029 first year students in the health sciences.
 
 Methods – First year students enrolled in the health sciences were asked to complete a paper questionnaire in their first week of classes in 2009. The 20 question survey was distributed in student tutorial groups. The first 10 questions collected information on student demographics, expected library use, and existing information seeking behaviour. The remaining 10 questions tested students’ understanding of information literacy concepts. Data collected from the survey were analyzed using the statistical software SPSS.
 
 Main Results – Most of the students who responded to the questionnaire were between the ages of 16 and 21 (84.3%) with only 2.2% over the age of 40. Approximately 15% of respondents had completed some postsecondary university or vocational education prior to enrolling in their current program.
 
 The students ranked Google, a friend, and a book as the top three places they would go to find information on something they knew little about. Google was also the most popular choice for finding a scholarly article (35% of respondents), followed by the library catalogue (21%). 
 
 A large proportion of students correctly answered questions relating to identifying appropriate search terms. For example, one third of the students selected the correct combination of search concepts for a provided topic, and 77% identified that the choice of search phrase could negatively impact search results. Students also demonstrated prior knowledge of the Boolean operator AND, with 38% correctly identifying its use in the related question. Most students were also able to identify key markers of a website’s credibility.
 
 Questions relating to ethical information use and scholarly literature proved more challenging. Almost half (45%) of the students said that they did not know the characteristics of a peer reviewed journal article. Twenty five percent of respondents indicated that citing an information source was only necessary in the case of direct quotes, with only 28% correctly identifying the need for citing both quotes and paraphrasing. Only 23% were able to select the example of a journal citation from the list presented.
 
 Conclusion – Students enter university with existing strengths in concept identification and basic search formulation, but require the most assistance with locating and identifying scholarly literature and how to cite it appropriately in their work. The findings will inform the development of an online information literacy assessment tool to assist incoming students in identifying areas where they may require additional support as they transition to university.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.778 |
| Open science | 0.001 | 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".