MétaCan
Menu
Back to cohort
Record W3121073614 · doi:10.18438/eblip29826

Students Value Asynchronous Instruction, Individual Projects and Frequent Communication with the Instructor in an Online Library Science Classroom

2020· article· en· W3121073614 on OpenAlexaffvenue
H. Robson MacDonald

Bibliographic record

VenueEvidence Based Library and Information Practice · 2020
Typearticle
Languageen
FieldComputer Science
TopicWeb and Library Services
Canadian institutionsCarleton University
Fundersnot available
KeywordsClass (philosophy)Asynchronous communicationPsychologyMedical educationLearning ManagementPreferencePerceptionMathematics educationComputer scienceMultimediaMedicineMathematics

Abstract

fetched live from OpenAlex

A Review of: Hajibayova, L. (2017). Students’ viewpoint: What constitutes presence in an online classroom? Cataloging & Classification Quarterly, 55(1), 12–25. https://doi.org/10.1080/01639374.2016.1241972 Abstract Objective – Determine student perceptions of online learning. Design – Survey questionnaire. Setting – An online class in the School of Library and Information Science at a Midwestern US public university. Subjects – 45 graduate students in an abstracting and indexing class. Methods – Class participants filled in an online questionnaire at the end of the semester. The survey covered topics related to collaboration, communication, modes of instruction, and assessment. The researcher calculated frequency counts for questions and did a correlation analysis. Main Results – For collaboration the author found that 62% of students expressed no or limited interest in participation in collaborative projects. Factors for successful completion of group projects included member commitment, instructor involvement, technology tools (discussion boards, wikis, blogs), group size (3–5 people preferred), and the nature and design of the project. Preference for communication frequency via email ranged from daily to never with the highest percentage (28.57%) preferring once a week. Communication frequency through the learning management system (LMS) was similar. The largest percentage of students preferred communication 2–3 times per week for virtual (38.89%) and face-to-face (41.67%) office hours. The correlation between communication via LMS and virtual office hours was r = 0.89, p < 0.05. Of students completing the questionnaire, 47.22% found the instructor’s presence effective. While most students disagreed with using social media in an online course, many friended or followed the instructor or the class social media page. Students preferred asynchronous over synchronous lectures and activities. Preference for frequency was once a week. There was a correlation between synchronous lectures and synchronous activities (r = 0.77, p < 0.05). Student preferences for the frequency of overview and discussion of class materials were roughly equal in distribution (daily, 4–6 times/week, 2–3 times/week, weekly, or never). There was a correlation between synchronous overview and asynchronous overview of class materials (r = 0.93, p < 0.05). In terms of assessment, students found group discussion, individual projects, research papers, quizzes, and tests the most effective class assignments. Several correlation analyses were done between assignment types. Conclusion – This study found students had limited interest in collaborative projects. It was also found that regular communication with the teacher was important. Students preferred asynchronous instruction and activities. They also preferred individual assignments for evaluation.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0050.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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.

Opus teacher head0.022
GPT teacher head0.254
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueEvidence Based Library and Information PracticeSame topicWeb and Library ServicesFrench-language works237,207