Using Cloud-based Collaborative Office Productivity Tools (Google Workspace) to Engage Students in Their Learning and Prepare Them for the Workplace
Bibliographic record
Abstract
Abstract This chapter explores how cloud-based office productivity suite(s) such as Google Workspace have been used to engage students in their learning while also preparing them for the workplace. Using these types of tools can make group-based in-class activities, assignments and projects highly engaging for a diverse student body while also developing skills valued in the workplace. Practical examples are shared regarding how the tools have been used with accounting and business students in courses such as communications and computing, introduction to business, sustainability and leadership. Some examples include how students can use the tools to collaboratively: provide feedback to a post-secondary institution regarding its orientation activities; complete a PESTLE and SWOT analysis of a business; use Google Forms with mobile phones to record observations of the emotional state of individuals and discuss in relation to emotionally intelligent leadership; and create a sustainability report for a post-secondary institution. The examples provided can be adapted as is or modified to engage learners in nearly any discipline at any education level in a face-to-face classroom or via remote delivery.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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; 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".