Evidence map›Paper›PMID 33250986›Full record

ArticleEcology and evolution2020

Teaching quantitative ecology online: An evidence-based prescription of best practices.

Miguel A Acevedo

Abstract read
In one paragraph

Article in Ecology and evolution, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Open data facilitate resilience in science during the COVID-19 pandemic.Frontiers in ecology and the environment · 2022
    Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Miguel A AcevedoDepartment of Wildlife Ecology and Conservation University of Florida Gainesville Florida USA.ORCID https://orcid.org/0000-0002-8289-1497

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantitative skills are becoming central to the undergraduate and graduate curriculum in ecology and evolutionary biology. While previous studies acknowledge that students perceive their quantitative training to be inadequate, there is little guidance on best practices. Moreover, with the recent COVID-19 sudden transition to online learning, there is even less guidance on how to effectively teach quantitative ecology online. Here, I synthesize a prescription of pedagogical best practices for teaching quantitative ecology online based on a broad review of the literature on multiple quantitative disciplines. These best practices include the following: (1) design and implement the class to meet learning goals using online strategies specifically; (2) create an open, inclusive, and welcoming online environment that promotes a sense of learning community; (3) acknowledge the diversity of talents and learning strategies; (4) use real-world examples and assessments; (5) account for gaps in knowledge; (6) emphasize the modeling cycle process; (7) focus on developing ideas rather than tools or procedures; (8) if needed, introduce computational tools thoroughly before combining them with mathematical or statistical concepts; (9) evaluate the course constantly; and (10) put your heart and soul into the class. I hope these practices help fellow instructors of quantitative ecology facing similar challenges in providing our students with the knowledge and skills needed to meet the challenges of the future.

Indexed as

active learningecological modelingonline learningpedagogyquantitative ecologystatistics

Identifiers

PMID33250986
PMCPMC7679551

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.