Eating Baby Food or Eating Meat? Student Voices on the “Everyday” Use of PowerPoint in University Teaching
Bibliographic record
Abstract
This research study centers on the use of PowerPoint in university classes. It poses the question: How do students perceive PowerPoint specifically and technology overall impacting their university experiences as a process for learning, as an element of social community building and as a worldview lens for examining and critiquing their world? In a qualitative ethnographic narrative, based on the work of Dorothy Smith, student voices in the everyday are heard in order to provide insider perceptions on the key question. Twenty-four volunteer participants signed consent to engage in focus groups flowing from 3, twenty-one hour face-to-face courses. These courses were comprised of 13 sessions of two 75 minute classes weekly taught by one professor. Following the first introductory class session, remaining classes were divided into two halves. The first half (6 classes) of each course was instructed using PowerPoint and the second half (6 classes) was not. Students were asked to reflect on the impact and benefits of each half section of the course delivery. Additionally, they were asked to comment on how each half of the course affected their meaning making, memory retention of data, process for learning, engagement for community making and worldview lens regarding the use of PowerPoint in university. Findings revealed three themes to consider in the professorial use of PowerPoint as a teaching tool in university, and also raised reflective scrutiny by the learners involved in the benefits and shortcomings of PowerPoint use.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".