Nursing Students’ Perceptions about Effective Pedagogy: Netnographic Analysis
Bibliographic record
Abstract
BACKGROUND: Effective pedagogy that encourages high standards of excellence and commitment to lifelong learning is essential in health professions education to prepare students for real-life challenges such as health disparities and global health issues. Creative learning and innovative teaching strategies empower students with high-quality, practical, real-world knowledge and meaningful skills to reach their potential as future health care providers. OBJECTIVE: The aim of this study was to explore health profession students' perceptions of whether their learning experiences were associated with good or bad pedagogy during asynchronous discussion forums. The further objective of the study was to identify how perceptions of the best and worst pedagogical practices reflected the students' values, beliefs, and understanding about factors that made a pedagogy good during their learning history. METHODS: A netnographic qualitative design was employed in this study. The data were collected on February 3, 2020 by exporting archived data from multiple sessions of a graduate-level nursing course offered between the fall 2016 and spring 2020 semesters at a large private university in the southeast region of the United States. Each student was a data unit. As an immersive data operation, field notes were taken by all research members. Data management and analysis were performed with NVivo 12. RESULTS: A total of 634 posts were generated by 153 students identified in the dataset. Most of these students were female (88.9%). From the 97 categories identified, four themes emerged: (T) teacher presence built through relationship and communication, (E) environment conducive to affective and cognitive learning, (A) assessment and feedback processes that yield a growth mindset, and (M) mobilization of pedagogy through learner- and community-centeredness. CONCLUSIONS: The themes that emerged from our analysis confirm findings from previous studies and provide new insights. Our study highlights the value of technology as a tool for effective pedagogy. A resourceful teacher can use various communication techniques to develop meaningful connections between the learner and teacher. Styles of communication will vary according to the unique expectations and needs of learners with different learning preferences; however, the aim is to fully engage each learner, establish a rapport between and among students, and nurture an environment characterized by freedom of expression in which ideas flow freely. We suggest that future research continue to explore the influence of differing course formats and pedagogical modalities on student learning experiences.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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; a candidate call from one teacher head, 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".