Increasing the Authenticity of Group Assignments in an Online Research Course may Lead to Higher Academic Achievement
Bibliographic record
Abstract
A Review of: Finch, J. L., & Jefferson, R. N. (2013). Designing authentic learning tasks for online library instruction. Journal of Academic Librarianship, 39(2), 181-188. http://dx.doi.org/10.1016/j.acalib.2012.10.005 Abstract Objective – To explore what impact assigning authentic tasks to students deliberately grouped by their majors in an online library research course has on student perceptions of teaching quality (teaching presence) and satisfaction. Design – Empirical comparative study. Setting – Medium-size (10,500 full-time students) liberal arts college in the United States of America. Subjects – 33 undergraduate students enrolled in a library research course. Methods – The study focusses on two sections of a one-credit online library research course taught by library faculty. The 17 students in the Spring “express” section were randomly assigned to groups and asked to complete a group annotated bibliography project using MLA style (Class Random). The 16 students registered in the Summer section of the same course were grouped by their majors, and asked to complete a modified version of the annotated bibliography group project in which they were asked to identify and then utilize the citation style most appropriate for their discipline (Class Deliberate). Students in Class Deliberate also received instruction around the role of subject specific citation styles in scholarly communication. Both sections completed a final assignment in which they developed a portal of resources to support their future studies or careers. All 33 students in both sections were invited to complete a modified online version of the Community of Inquiry (COI) survey consisting of 16 questions relating to student perceptions of the course’s teaching and cognitive presences. Questions relating to social presence were not administered. The final grades awarded to all students in both sections were also analyzed. Main Results – A total of 59% of the students in Class Random (10/17) and 67% of the students in Class Deliberate (11/16) completed the online survey. There were no statistically significant differences in the survey responses between the two sections with both groups of students rating the instructor’s teaching presence and the course’s cognitive presence highly. Only 40% of the respondents from Class Random and 46% from Class Deliberate agreed that working with peers facilitated their learning. The mean final grade received by students in Class Deliberate was 95.27 versus 86.15 in Class Random, a statistically significant difference (p
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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 | 0.009 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.026 | 0.011 |
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".